Longitudinal Assessment of Enhancing Foci of Abnormal Signal Intensity in Neurofibromatosis Type 1

BACKGROUND AND PURPOSE:Patients with neurofibromatosis 1 are at increased risk of developing brain tumors, and differentiation from contrast-enhancing foci of abnormal signal intensity can be challenging. We aimed to longitudinally characterize rare, enhancing foci of abnormal signal intensity based on location and demographics.MATERIALS AND METHODS:A total of 109 MR imaging datasets from 19 consecutive patients (7 male; mean age, 8.6 years; range, 2.3–16.8 years) with neurofibromatosis 1 and a total of 23 contrast-enhancing parenchymal lesions initially classified as foci of abnormal signal intensity were included. The mean follow-up period was 6.5 years (range, 1–13.8 years). Enhancing foci of abnormal signal intensity were followed up with respect to presence, location, and volume. Linear regression analysis was performed.RESULTS:Location, mean peak volume, and decrease in enhancing volume over time of the 23 lesions were as follows: 10 splenium of the corpus callosum (295 mm³, 5 decreasing, 3 completely resolving, 2 surgical intervention for change in imaging appearance later confirmed to be gangliocytoma and astrocytoma WHO II), 1 body of the corpus callosum (44 mm³, decreasing), 2 frontal lobe white matter (32 mm³, 1 completely resolving), 3 globus pallidus (50 mm³, all completely resolving), 6 cerebellum (206 mm³, 3 decreasing, 1 completely resolving), and 1 midbrain (34 mm³). On average, splenium lesions began to decrease in size at 12.2 years, posterior fossa lesions at 17.1 years, and other locations at 9.4 years of age.CONCLUSIONS:Albeit very rare, contrast-enhancing lesions in patients with neurofibromatosis 1 may regress over time. Follow-up MR imaging aids in ascertaining regression. The development of atypical features should prompt further evaluation for underlying tumors.

Neurofibromatosis type 1 (NF-1) is an autosomal dominant tumor predisposition syndrome characterized by optic pathway gliomas, neurofibromas, skin manifestations, iris hamartomas, and bone lesions, affecting approximately 1 in 3000 individuals.^1,2 Foci of abnormal signal intensity, previously known as unidentified bright objects or neurofibromatosis bright objects of the brain, are not among the diagnostic criteria but can be found in 43%–95% of pediatric patients with NF-1.^3-7 On MR imaging, FASI appear as T2/FLAIR hyperintense lesions of the brain with a predilection for the basal ganglia, cerebellum, and brain stem. Although FASI are not completely understood, myelin vacuolization is commonly considered as an underlying feature of these lesions.^1,4,5,7-9Patients with NF-1 are at an increased risk of developing low- and high-grade brain tumors, including cerebral and cerebellar astrocytomas, ependymomas, and brain stem gliomas, many of which can mimic FASI on MR imaging.^3,10-14 On the other hand, FASI are known for their dynamic properties and may increase or decrease in size or resolve over time.⁸ Although the reference standard for differentiating brain lesions is transcranial biopsy with its own inherent risks, brain signal abnormalities in patients with NF-1 are primarily followed up by MR imaging to screen for possible tumors.^15-18 Contrast enhancement after administration of a gadolinium-based contrast agent is usually considered atypical for FASI and likely to indicate the presence of a brain tumor. Reports considering contrast enhancement in FASI are sparse, limited to case reports and small numbers in cohort studies.^3,6,19-29 We therefore aimed to characterize lesions considered to represent enhancing FASI based on location, volume of enhancement, and demographics to advance the understanding of these rare lesions.     

Impact of Prematurity on the Tissue Properties of the Neonatal Brain Stem: A Quantitative MR Approach

BACKGROUND AND PURPOSE:Preterm birth interferes with regular brain development. The aim of this study was to investigate the impact of prematurity on the physical tissue properties of the neonatal brain stem using a quantitative MR imaging approach.MATERIALS AND METHODS:A total of 55 neonates (extremely preterm [n = 30]: <28 + 0 weeks gestational age; preterm [n = 10]: 28 + 0–36 + 6 weeks gestational age; term [n = 15]: ≥37 + 0 weeks gestational age) were included in this retrospective study. In most cases, imaging was performed at approximately term-equivalent age using a standard MR protocol. MR data postprocessing software SyMRI was used to perform multidynamic multiecho sequence (acquisition time: 5 minutes, 24 seconds)–based MR postprocessing to determine T1 relaxation time, T2 relaxation time, and proton density. Mixed-model ANCOVA (covariate: gestational age at MR imaging) and the post hoc Bonferroni test were used to compare the groups.RESULTS:There were significant differences between premature and term infants for T1 relaxation time (midbrain: P < .001; pons: P < .001; basis pontis: P = .005; tegmentum pontis: P < .001; medulla oblongata: P < .001), T2 relaxation time (midbrain: P < .001; tegmentum pontis: P < .001), and proton density (tegmentum pontis: P = .004). The post hoc Bonferroni test revealed that T1 relaxation time/T2 relaxation time in the midbrain differed significantly between extremely preterm and preterm (T1 relaxation time: P < .001/T2 relaxation time: P = .02), extremely preterm and term (T1 relaxation time/T2 relaxation time: P < .001), and preterm and term infants (T1 relaxation time: P < .001/T2 relaxation time: P = .006).CONCLUSIONS:Quantitative MR parameters allow preterm and term neonates to be differentiated. T1 and T2 relaxation time metrics of the midbrain allow differentiation between the different stages of prematurity. SyMRI allows for a quantitative assessment of incomplete brain maturation by providing tissue-specific properties while not exceeding a clinically acceptable imaging time.

The myelination process begins in the fetal period and proceeds in a stepwise manner.^1,2 Brain maturation progresses caudally to rostrally following a characteristic pattern.³ Hence, histologically, the maximum myelin deposition is detectable in the spinal cord and the brain stem at the time of birth.^1,3Based on the biochecture of the myelin sheath, neonatal brain development can be evaluated by MR imaging.^4,5 Thus, myelination visualized on conventional T1-weighted and T2-weighted MR contrasts serves as an imaging biomarker for the assessment of brain maturation in neonates.⁶Prematurity is associated with delayed myelination, which is considered a risk factor for impaired neurologic and cognitive development.^7,8 Furthermore, there is a correlation between gestational age (GA) at birth and developmental outcome, with lower GA associated with a higher risk for more severe cognitive impairment.^9,10 Therefore, the assessment of myelination is paramount, primarily in preterm born neonates, to predict potential mental and neurologic impairment. Despite being a highly sensitive tool for the detection of subtle cerebral pathologies in premature infants, the evaluation of myelination by brain MR imaging in this group of patients remains challenging in pediatric neuroimaging.^11-13Quantitative MR techniques enable the characterization of cerebral development and brain maturation based on tissue-specific relaxation parameters and proton density (PD).^14-16 Quantitative T1 and T2 mapping have proved beneficial when assessing neonatal brain myelination qualitatively.^6,17 However, quantitative MR data acquisition is a highly time-consuming process, even with modern methods and therefore is not applicable in the clinical routine.^15,17By acquiring a single multidynamic multiecho (MDME) sequence (acquisition time: 5 minutes, 24 seconds), the MR data postprocessing software SyMRI (Synthetic MR; version 11.1.5) generates a variety of conventional MR contrasts and quantitative MR maps.^18-20 Based on a single sequence, intrinsic physical parameters of the examined tissue, such as T1 relaxation time (T1R), T2 relaxation time (T2R), and PD, can be determined.²⁰ The software allows definition of TR, TE, and TI after data acquisition to generate and to modulate the preferred MR contrasts. Because the image postprocessing is performed in less than 1 minute, SyMRI provides qualitative as well as quantitative MR data in a clinically acceptable time.^21-23In neonates, the process of myelination leads to subtle MR signal changes because of alterations in relaxation parameters and spin density, detectable by quantitative MR techniques. The aim of this study was to investigate the impact of different stages of prematurity on the maturational characteristics of the neonatal brain stem, as measured by SyMRI-based T1, T2, and PD mapping. The study was designed to prove that certain stages of prematurity are linked to specific quantitative MR metrics.     

Neurite Orientation Dispersion and Density Imaging for Assessing Acute Inflammation and Lesion Evolution in MS

BACKGROUND AND PURPOSE:MR imaging is essential for MS diagnosis and management, yet it has limitations in assessing axonal damage and remyelination. Gadolinium-based contrast agents add value by pinpointing acute inflammation and blood-brain barrier leakage, but with drawbacks in safety and cost. Neurite orientation dispersion and density imaging (NODDI) assesses microstructural features of neurites contributing to diffusion imaging signals. This approach may resolve the components of MS pathology, overcoming conventional MR imaging limitations.MATERIALS AND METHODS:Twenty-one subjects with MS underwent serial enhanced MRIs (12.6 ± 9 months apart) including NODDI, whose key metrics are the neurite density and orientation dispersion index. Twenty-one age- and sex-matched healthy controls underwent unenhanced MR imaging with the same protocol. Fifty-eight gadolinium-enhancing and non-gadolinium-enhancing lesions were semiautomatically segmented at baseline and follow-up. Normal-appearing WM masks were generated by subtracting lesions and dirty-appearing WM from the whole WM.RESULTS:The orientation dispersion index was higher in gadolinium-enhancing compared with non-gadolinium-enhancing lesions; logistic regression indicated discrimination, with an area under the curve of 0.73. At follow-up, in the 58 previously enhancing lesions, we identified 2 subgroups based on the neurite density index change across time: Type 1 lesions showed increased neurite density values, whereas type 2 lesions showed decreased values. Type 1 lesions showed greater reduction in size with time compared with type 2 lesions.CONCLUSIONS:NODDI is a promising tool with the potential to detect acute MS inflammation. The observed heterogeneity among lesions may correspond to gradients in severity and clinical recovery after the acute phase.

Conventional MR imaging is essential for MS diagnosis and management, specifically for demonstrating WM lesion dissemination in space (involvement of >1 CNS region) and time (across time accumulation).¹ Conventional MR imaging, however, lacks specificity in characterizing MS WM lesions after the acute phase; all lesions show a similar radiologic appearance on T2WI, irrespective of the degree of inflammation, axonal loss, gliosis, demyelination, and remyelination.^2,3 Furthermore, clinical disability shows limited correlation with volume and the number of detectable WM lesions. The different neuropathologic characteristics of WM lesions as well as the accumulation of tissue damage within normal-appearing WM (NAWM) are some of the other factors possibly playing a role in the development of MS disability.⁴Gadolinium-based imaging improves the utility of conventional MR imaging in MS because gadolinium-enhancing lesions (GELs) represent a radiologic correlate of acute inflammation, corresponding to active lesions associated with blood-brain barrier disruption. However, despite its importance for diagnosis (fulfillment of dissemination in time criteria), the application of gadolinium-based contrast agents has raised a number of safety concerns.⁵ Therefore, alternative MR imaging markers of acute inflammation are needed.Neurite orientation dispersion and density imaging (NODDI) is a clinically feasible diffusion MR imaging technique, incorporating multiple shells with different b-values to model brain tissue into 3 compartments showing different diffusion properties.⁶ According to this orientation-dispersed cylindric model, the isotropic diffusion fraction is highly represented only within CSF, whereas within brain parenchyma, the diffusion signal can be either hindered (Gaussian displacement pattern) or restricted (non-Gaussian displacement pattern). The hindered signal is attributed to the extra-neurite compartment (VEC), defining the extracellular volume fraction whereas the restricted signal is attributed to intraneurite spaces and is thought to correspond to the neurite density index (NDI). A Watson distribution is then used to compute the orientation distribution of the cylinders, quantified from 0 to 1 by the orientation dispersion index (ODI). Highly compacted and parallel WM bundles, such as the corpus callosum, generally show lower ODI values compared with the cortical and subcortical regions, characterized by multidirectional dendritic structures.Even though NODDI applications are novel in MS, this technique appears promising in detecting and modeling the complexity of MS pathology, being potentially more specific than DTI in capturing microstructural substrates.^7-12 NODDI has never been used, however, to assess longitudinal changes within MS lesions and NAWM. For animal studies, only a single work, based on a murine model, longitudinally assessed induced demyelinated lesions, correlating NODDI abnormalities with histopathologic changes.¹³ The authors suggested that after a demyelinating event, the combination of decreasing ODI and increasing NDI with time might reflect improvement in fiber coherency due to remyelination.The aim of this work was to cross-sectionally assess the role of NODDI in indicating gadolinium enhancement in acute lesions and to longitudinally assess NODDI and conventional DTI changes in MS lesions and NAWM in the transition from detectable to undetectable gadolinium enhancement. We hypothesized that NODDI-derived metrics may be promising markers to detect acute inflammation as well as heterogeneity among lesions and their evolution with time.     

Quantitative T1ρ MRI of the Head and Neck Discriminates Carcinoma and Benign Hyperplasia in the Nasopharynx

BACKGROUND AND PURPOSE:T1ρ imaging is a new quantitative MR imaging pulse sequence with the potential to discriminate between malignant and benign tissue. In this study, we evaluated the capability of T1ρ imaging to characterize tissue by applying T1ρ imaging to malignant and benign tissue in the nasopharynx and to normal tissue in the head and neck.MATERIALS AND METHODS:Participants with undifferentiated nasopharyngeal carcinoma and benign hyperplasia of the nasopharynx prospectively underwent T1ρ imaging. T1ρ measurements obtained from the histogram analysis for nasopharyngeal carcinoma in 43 participants were compared with those for benign hyperplasia and for normal tissue (brain, muscle, and parotid glands) in 41 participants using the Mann-Whitney U test. The area under the curve of significant T1ρ measurements was calculated and compared using receiver operating characteristic analysis and the Delong test, respectively. A P < . 05 indicated statistical significance.RESULTS:There were significant differences in T1ρ measurements between nasopharyngeal carcinoma and benign hyperplasia and between nasopharyngeal carcinoma and normal tissue (all, P < . 05). Compared with benign hyperplasia, nasopharyngeal carcinoma showed a lower T1ρ mean (62.14 versus 65.45 × ms), SD (12.60 versus 17.73 × ms), and skewness (0.61 versus 0.76) (all P < .05), but no difference in kurtosis (P = . 18). The T1ρ SD showed the highest area under the curve of 0.95 compared with the T1ρ mean (area under the curve  = 0.72) and T1ρ skewness (area under the curve  = 0.72) for discriminating nasopharyngeal carcinoma and benign hyperplasia (all, P < .05).CONCLUSIONS:Quantitative T1ρ imaging has the potential to discriminate malignant from benign and normal tissue in the head and neck.

The spin-lattice relaxation time in the rotating frame known as T1ρ is sensitive to biologic processes associated with alterations in the macromolecular content of tissue. Quantitative T1ρ imaging has been used to study normal tissue and nonmalignant diseases in cartilage, discs, and ligaments,^1-3 brain,^4-7 liver,^8,9 heart,¹⁰ muscles,¹¹ and parotid glands.^11-13 However, T1ρ imaging also has the potential to characterize benign and malignant processes, but only a few studies have preliminarily evaluated T1ρ for human cancer imaging. These studies showed differences of T1ρ values between high- and low-grade gliomas¹⁴ and between benign and malignant tissue in the brain,^15,16 breast,¹⁷ and prostate.¹⁸We are interested in quantitative MR imaging sequences that can be used to discriminate nasopharyngeal carcinoma (NPC) from benign hyperplasia in the nasopharynx because these entities may overlap on anatomic MR imaging sequences.^19,20 Our hypothesis is that the T1ρ value of malignancy is different from that of benign tissue and can be used to discriminate these 2 entities. In this preliminary study, we also applied T1ρ imaging to a range of normal tissue in the head and neck (brain, pterygoid muscle, and parotid gland) to compare the T1ρ values of normal tissue with those of NPC.     

Inversion Recovery Ultrashort TE MR Imaging of Myelin is Significantly Correlated with Disability in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE:MR imaging has been widely used for the noninvasive evaluation of MS. Although clinical MR imaging sequences are highly effective in showing focal macroscopic tissue abnormalities in the brains of patients with MS, they are not specific to myelin and correlate poorly with disability. We investigated direct imaging of myelin using a 2D adiabatic inversion recovery ultrashort TE sequence to determine its value in assessing disability in MS.MATERIALS AND METHODS:The 2D inversion recovery ultrashort TE sequence was evaluated in 14 healthy volunteers and 31 patients with MS. MPRAGE and T2-FLAIR images were acquired for comparison. Advanced Normalization Tools were used to correlate inversion recovery ultrashort TE, MPRAGE, and T2-FLAIR images with disability assessed by the Expanded Disability Status Scale.RESULTS:Weak correlations were observed between normal-appearing white matter volume (R = –0.03, P = .88), lesion load (R = 0.22, P = .24), and age (R = 0.14, P = .44), and disability. The MPRAGE signal in normal-appearing white matter showed a weak correlation with age (R = –0.10, P = .49) and disability (R = –0.19, P = .31). The T2-FLAIR signal in normal-appearing white matter showed a weak correlation with age (R = 0.01, P = .93) and disability (R = 0.13, P = .49). The inversion recovery ultrashort TE signal was significantly negatively correlated with age (R = –0.38, P = .009) and disability (R = –0.44; P = .01).CONCLUSIONS:Direct imaging of myelin correlates with disability in patients with MS better than indirect imaging of long-T2 water in WM using conventional clinical sequences.

MS is the most common demyelinating disease of the brain.¹ Demyelination affects many aspects of neurologic function, including speech, balance, and cognitive awareness. Across time, this frequently leads to severe and irreversible clinical disability. MR imaging has been widely used for accurate diagnosis of MS, with current techniques focused on imaging the long-T2 water components in WM and GM.^2-4 MS lesions often appear hypointense with T1-weighted gradient recalled-echo sequences² and hyperintense with T2-weighted FSE and T2-weighted FLAIR sequences.³ Active lesions can be highlighted with gadolinium-enhanced imaging.⁴ The magnetization transfer ratio has been used as an indirect marker of myelin disorder in regions of normal-appearing WM (NAWM).⁵ There are also several other advanced imaging techniques for indirect myelin imaging via assessment of myelin water, such as multicomponent T2 or T2* analysis^6,7 and direct visualization of components with short transverse relaxation times.^8,9While conventional MR imaging sequences are highly effective in detecting focal macroscopic brain tissue abnormalities, they are not specific for pathologic substrates of MS lesions such as demyelination and remyelination, and they may not correlate well with patients'' neurologic deficits. Current MR imaging techniques correlate only modestly with disability assessed by the Expanded Disability Status Scale (EDSS).^10-15 The total lesion load showed statistically significant-but-weak correlations with the EDSS score in several large-scale studies (R = 0.1–0.3).^10-12 Composite scores including relaxation times of different tissues and/or volumetric measures generally correlate more strongly with the EDSS score, with a maximum observed correlation of R = 0.34 (P < .001).¹³ Lesions seen with gadolinium-enhanced imaging are only moderately correlated with disability in the first 6 months and are not predictive of changes in the EDSS score in the subsequent 1 or 2 years.¹⁴ A large-scale multicenter study reported very limited correlation between the EDSS score and normalized brain volume (R = –0.18), cross-sectional area (R = –0.26), magnetization transfer ratio of whole-brain tissue (R = –0.16), and GM (R = –0.17).¹⁵The poor performance of conventional MR imaging sequences in assessing disability highlights the need for novel MR imaging techniques that can directly image myelin lipid and enable direct assessment of both myelin damage and repair. However, myelin has an extremely short transverse relaxation time and is not directly detectable with conventional MR images, which typically have TEs of several milliseconds or longer. Ultrashort TE (UTE) sequences can directly detect signal from myelin with ultrashort T2 (ie, excluding water with longer T2s).^16-21 In this study, we describe imaging of WM using a 2D adiabatic inversion recovery prepared UTE (IR-UTE) sequence in healthy volunteers and patients with MS and evaluate its performance in assessing disability in patients with MS compared with 2 conventional clinical sequences.     

Cortical Distribution of Fragile Periventricular Anastomotic Collateral Vessels in Moyamoya Disease: An Exploratory Cross-Sectional Study of Japanese Patients with Moyamoya Disease

BACKGROUND AND PURPOSE:Collateral vessels in Moyamoya disease represent potential sources of bleeding. To test whether these cortical distributions vary among subtypes, we investigated cortical terminations using both standardized MR imaging and MRA.MATERIALS AND METHODS:Patients with Moyamoya disease who underwent MR imaging with MRA in our institution were enrolled in this study. MRA was spatially normalized to the Montreal Neurological Institute space; then, collateral vessels were measured on MRA and classified into 3 types of anastomosis according to the parent artery: lenticulostriate, thalamic, and choroidal. We also obtained the coordinates of collateral vessel outflow to the cortex. Differences in cortical terminations were compared among the 3 types of anastomosis.RESULTS:We investigated 219 patients with Moyamoya disease, and a total of 190 collateral vessels (lenticulostriate anastomosis, n = 72; thalamic anastomosis, n = 21; choroidal anastomosis, n = 97) in 46 patients met the inclusion criteria. We classified the distribution patterns of collateral anastomosis as follows: lenticulostriate collaterals outflowing anteriorly (P < .001; 95% CI, 67.0–87.0) and medially (P < .001; 95% CI, 11.0–24.0) more frequently than choroidal collaterals; lenticulostriate collaterals outflowing anteriorly more frequently than thalamic collaterals (P < .001; 95% CI, 34.0–68.0); and choroidal collaterals outflowing posteriorly more frequently than thalamic collaterals (P < .001; 95% CI, 14.0–34.0). Lenticulostriate anastomoses outflowed to the superior or inferior frontal sulcus and interhemispheric fissure. Thalamic anastomoses outflowed to the insular cortex and cortex around the central sulcus. Choroidal anastomoses outflowed to the cortex posterior to the central sulcus and the insular cortex.CONCLUSIONS:Cortical distribution patterns appear to differ markedly among the 3 types of collaterals.

Collateral vessels in Moyamoya disease develop as the disease progresses.¹ Lenticulostriate arteries (LSAs), perforators from the posterior communicating artery (PcomA), and anterior and posterior choroidal arteries (choAs) are representative collateral vessels that supply the cortex.^2-4 Development of such collateral vessels represents a risk factor for intracerebral hemorrhage,^3,5-7 and these vessels have frequently been considered as the vessels responsible for bleeding in recent reports.^8-10 These collateral vessels connect with medullary arteries near the lateral ventricle and thus supply the cortex via the medullary arteries.^3,4 However, no reports have addressed the cortical distributions of these collateral vessels.Bypass surgery reduces the risk of rebleeding in patients with hemorrhagic onset of Moyamoya disease^7,11-13 and also shrinks collateral vessels in Moyamoya disease.^7,12,14,15 Augmentation of cerebral blood flow via bypass seems to decrease the necessity for development of collateral flow and shrinks existing collaterals.¹⁵ To shrink risky collateral vessels effectively and prevent hemorrhage, well-designed and planned bypass surgeries may be required.¹⁶ Comprehension of the nature and cortical distribution of collateral vessels may thus be clinically useful.MRA performed using a 3T scanner has proved useful for detecting the abnormally extended collateral vessels in Moyamoya disease.² We investigated the cortical distribution of collateral vessels using 3T MR imaging and MRA to clarify whether cortical distributions vary among anastomotic subtypes and to better understand collateral networks.     

Neonatal Developmental Venous Anomalies: Clinicoradiologic Characterization and Follow-Up

BACKGROUND AND PURPOSE:Although developmental venous anomalies have been frequently studied in adults and occasionally in children, data regarding these entities are scarce in neonates. We aimed to characterize clinical and neuroimaging features of neonatal developmental venous anomalies and to evaluate any association between MR imaging abnormalities in their drainage territory and corresponding angioarchitectural features.MATERIALS AND METHODS:We reviewed parenchymal abnormalities and angioarchitectural features of 41 neonates with developmental venous anomalies (20 males; mean corrected age, 39.9 weeks) selected through a radiology report text search from 2135 neonates who underwent brain MR imaging between 2008 and 2019. Fetal and longitudinal MR images were also reviewed. Neurologic outcomes were collected. Statistics were performed using χ², Fisher exact, Mann-Whitney U, or t tests corrected for multiple comparisons.RESULTS:Developmental venous anomalies were detected in 1.9% of neonatal scans. These were complicated by parenchymal/ventricular abnormalities in 15/41 cases (36.6%), improving at last follow-up in 8/10 (80%), with normal neurologic outcome in 9/14 (64.2%). Multiple collectors (P = .008) and larger collector caliber (P < .001) were significantly more frequent in complicated developmental venous anomalies. At a patient level, multiplicity (P = .002) was significantly associated with the presence of ≥1 complicated developmental venous anomaly. Retrospective fetal detection was possible in 3/11 subjects (27.2%).CONCLUSIONS:One-third of neonatal developmental venous anomalies may be complicated by parenchymal abnormalities, especially with multiple and larger collectors. Neuroimaging and neurologic outcomes were favorable in most cases, suggesting a benign, self-limited nature of these vascular anomalies. A congenital origin could be confirmed in one-quarter of cases with available fetal MR imaging.

Developmental venous anomalies (DVAs) are the most frequently diagnosed intracranial vascular malformations, often encountered as incidental neuroimaging findings.^1,2 On MR imaging, DVAs are recognized on postcontrast T1WI as radially oriented veins with a “caput medusae” pattern converging into 1 (or rarely more) dilated venous collector.^3,4 These features may be also detected on precontrast MR images,^3-5 especially if T2*-weighted sequences such as high-resolution SWI are included in the protocol.⁵ In addition, DVAs may be occasionally recognized in utero using fetal MR imaging.⁶DVAs are usually considered benign anatomic variants.⁷ However, they represent areas of venous fragility that can become symptomatic through diverse pathomechanisms.^8,9 Indeed, DVA-associated brain abnormalities are frequently depicted, including-but-not limited-to sporadic cerebral cavernous malformations (CCMs).^8-16 Moreover, a higher prevalence of DVAs has been described in patients with different pathologies and/or genetic conditions.^17-21Although DVAs are widely described and characterized in adults, they remain under-reported in the pediatric population. Indeed, there are noticeably fewer studies focusing exclusively on DVAs in this age group, especially in the neonatal period.^17,18,21-24 In particular, the largest case series of neonatal DVAs described so far included 14 neonates, mostly detected using ultrasound during routine scanning for other reasons,²² with limited information on the prevalence and perinatal characteristics of these vascular abnormalities, including complications and longitudinal evolution. Moreover, additional data on neonatal and fetal DVAs would be of great interest because there is an ongoing debate regarding their congenital or postnatal etiology.²⁵In this study, we aimed to describe the pre- and postnatal appearance of DVAs and associated brain anomalies in a relatively large single-center group of neonates, providing information on their imaging and clinical follow-up. In addition, we tested a possible association between parenchymal and ventricular abnormalities in the drainage territory of neonatal DVAs and their angioarchitectural features.     

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

BACKGROUND AND PURPOSE:Malignant melanoma is an aggressive skin cancer in which brain metastases are common. Our aim was to establish and evaluate a deep learning model for fully automated detection and segmentation of brain metastases in patients with malignant melanoma using clinical routine MR imaging.MATERIALS AND METHODS:Sixty-nine patients with melanoma with a total of 135 brain metastases at initial diagnosis and available multiparametric MR imaging datasets (T1-/T2-weighted, T1-weighted gadolinium contrast-enhanced, FLAIR) were included. A previously established deep learning model architecture (3D convolutional neural network; DeepMedic) simultaneously operating on the aforementioned MR images was trained on a cohort of 55 patients with 103 metastases using 5-fold cross-validation. The efficacy of the deep learning model was evaluated using an independent test set consisting of 14 patients with 32 metastases. Manual segmentations of metastases in a voxelwise manner (T1-weighted gadolinium contrast-enhanced imaging) performed by 2 radiologists in consensus served as the ground truth.RESULTS:After training, the deep learning model detected 28 of 32 brain metastases (mean volume, 1.0 [SD, 2.4] cm³) in the test cohort correctly (sensitivity of 88%), while false-positive findings of 0.71 per scan were observed. Compared with the ground truth, automated segmentations achieved a median Dice similarity coefficient of 0.75.CONCLUSIONS:Deep learning–based automated detection and segmentation of brain metastases in malignant melanoma yields high detection and segmentation accuracy with false-positive findings of <1 per scan.

Malignant melanoma is an aggressive skin cancer associated with high mortality and morbidity rates.^1,2 Brain metastases are common in malignant melanoma,^3,4 subsequently causing potential severe neurologic impairment and worsened outcome. Therefore, it is recommended that melanoma patients with an advanced stage undergo MR imaging of the head for screening purposes to detect metastases.^5-8Owing to an increased workload of radiologists, repetitive evaluation of MR imaging scans can be tiresome, hence bearing an inherent risk of missed diagnosis for subtle lesions, with satisfaction of search effects leading to decreased sensitivity for additional lesions.^9,10 Automatization of detection could serve as an adjunct tool for lesion preselection that can support image evaluation by radiologists and clinicians.^11,12 Furthermore, automated segmentations may be used as a parameter to evaluate therapy response in oncologic follow-up imaging.^13,14 Additionally, exact lesion determination and delineation of size are required for stereotactic radiosurgery.^15,16 In clinical routine, brain lesions have to be segmented manually by the radiosurgeon. This task proves to be time-consuming, in particular if multiple metastases are present. Furthermore, manual segmentation is potentially hampered by interreader variabilities with reduced reproducibility, hence resulting in inaccuracies of lesion delineation.^17,18 In this context, accurate objective and automated segmentations of brain metastases would be highly beneficial.^17-19Recently, deep learning models (DLMs) have shown great potential in detection, segmentation and classification tasks in medical image analysis while having the potential to improve clinical workflow.^20-25 The models apply multiple processing layers that result in deep convolutional neural networks (CNNs). Training data are used to create complex feature hierarchies.^26-28 In general, a DLM includes different layers for convolution, pooling, and classification.²⁸ The required training data are supplied by manual segmentations, which usually serve as the segmentation criterion standard.^18,28,29Previous studies on brain metastases from different tumor entities have demonstrated promising results, reporting a sensitivity for automated deep learning–based detection of lesions of around 80% or higher.^17,30-32 However, the often reported relatively high number of false-positive findings questions their applicability in clinical routine.^17,30The purpose of this study was to develop and evaluate a DLM for automated detection and segmentation of brain metastases in patients with malignant melanoma using heterogeneous MR imaging data from multiple vendors and study centers.     

MRI-Based Assessment of the Pharyngeal Constrictor Muscle as a Predictor of Surgical Margin after Transoral Robotic Surgery in HPV-Positive Tonsillar Cancer

BACKGROUND AND PURPOSE:Transoral robotic surgery is an emerging strategy for treating human papillomavirus–positive cancers, but the role of MR imaging in predicting the surgical outcome has not been established. We aimed to identify preoperative MR imaging characteristics that predispose the outcome of transoral robotic surgery toward an insecure (positive or close) surgical margin in human papillomavirus–positive tonsillar squamous cell carcinoma.MATERIALS AND METHODS:Between December 2012 and May 2019, sixty-nine patients underwent transoral robotic surgery at our institution. Among these, 29 who were diagnosed with human papillomavirus–positive tonsillar squamous cell carcinoma, did not receive neoadjuvant treatment, underwent preoperative 3T MR imaging, and had postoperative pathologic reports and were included in this retrospective study. Two neuroradiologists evaluated the preoperative MR imaging scans to determine the tumor spread through the pharyngeal constrictor muscle using a 5-point scale: 1, normal constrictor; 2, bulging constrictor; 3, thinning constrictor; 4, obscured constrictor; and 5, tumor protrusion into the parapharyngeal fat. The risk of an insecure surgical margin (involved or <1 mm) according to the MR imaging scores was predicted using logistic regression with the Firth correction.RESULTS:The interobserver agreement for the MR imaging scores was excellent (κ = 0.955, P < .001). A score of ≥4 could predict an insecure margin with 87.5% sensitivity and 92.3% specificity (area under the curve = 0.899) and was the only significant factor associated with an insecure margin in the multivariable analysis (OR, 6.59; 95% CI, 3.11–22.28; P < .001).CONCLUSIONS:The pre-transoral robotic surgery MR imaging scoring system for the pharyngeal constrictor muscle is a promising predictor of the surgical margin in human papillomavirus–positive tonsillar squamous cell carcinoma.

Oropharyngeal squamous cell carcinoma (SCC) is a head and neck cancer with increasing prevalence as a consequence of rising human papillomavirus (HPV) infections.^1,2 HPV-positive oropharyngeal SCC is known for its excellent prognosis with substantially improved survival compared with HPV-negative SCC.^3-5 Surgery, radiation, and chemotherapy are the main treatment methods for oropharyngeal SCC and can be used alone or in combination depending on the cancer stage.⁶The treatment protocol for HPV-positive SCC has shifted toward a “deintensification” approach to maintain favorable oncologic outcomes while minimizing treatment-related morbidity.^7-9 Long-term adverse effects from radiation or chemotherapy and high morbidity from traditional surgery through external mandibulotomy can reduce the quality of life, particularly in young patients who have to live with the consequences for far longer.^10–13 Recently, transoral robotic surgery (TORS) has emerged as a first-line treatment, particularly for early-stage HPV-positive oropharyngeal SCC.^14,15 While avoiding functional deficits from the traditional external approaches, TORS can reduce the need for adjuvant therapy after surgery or can use surgery as a single-technique therapy while preserving oncologic outcomes, particularly when the negative margin is achieved by TORS.^2,3,5,16-18Despite these advantages, there is still a risk of obtaining an insecure surgical margin (ie, positive margin involvement by the tumor or a close margin of <1 mm between the tumor and the margin) in TORS, which necessitates adjuvant therapies, even in early T1 and T2 tumors.^3,19 Because oncologic outcomes in such cases are similar to those with chemoradiation alone,³ it is important to preselect patients who are expected to have an insecure surgical margin to avoid unnecessary dual treatment. However, no published study has evaluated the preoperative MR imaging characteristics that can predict the surgical margin after TORS. It has been noted that tumor invasion through the pharyngeal constrictor muscle confirmed in a surgical field will likely have a positive margin related to locoregional recurrence, but data supporting an imaging-based predictor are still lacking.^2,5,20In our study, we aimed to identify preoperative MR imaging characteristics, particularly with regard to pharyngeal constrictor muscle involvement by the tumor in early stage cancers, that predispose the outcome of TORS toward an insecure surgical margin in HPV-positive tonsillar SCC.     

Pilot Study of Hyperpolarized 13C Metabolic Imaging in Pediatric Patients with Diffuse Intrinsic Pontine Glioma and Other CNS Cancers

BACKGROUND AND PURPOSE:Pediatric CNS tumors commonly present challenges for radiographic interpretation on conventional MR imaging. This study sought to investigate the safety and tolerability of hyperpolarized carbon-13 (HP-¹³C) metabolic imaging in pediatric patients with brain tumors.MATERIALS AND METHODS:Pediatric patients 3 to 18 years of age who were previously diagnosed with a brain tumor and could undergo MR imaging without sedation were eligible to enroll in this safety study of HP [1-¹³C]pyruvate. Participants received a one-time injection of HP [1-¹³C]pyruvate and were imaged using dynamic HP-¹³C MR imaging. We assessed 2 dose levels: 0.34 mL/kg and the highest tolerated adult dose of 0.43 mL/kg. Participants were monitored throughout imaging and for 60 minutes postinjection, including pre- and postinjection electrocardiograms and vital sign measurements.RESULTS:Between February 2017 and July 2019, ten participants (9 males; median age, 14 years; range, 10–17 years) were enrolled, of whom 6 completed injection of HP [1-¹³C]pyruvate and dynamic HP-¹³C MR imaging. Four participants failed to undergo HP-¹³C MR imaging due to technical failures related to generating HP [1-¹³C]pyruvate or MR imaging operability. HP [1-¹³C]pyruvate was well-tolerated in all participants who completed the study, with no dose-limiting toxicities or adverse events observed at either 0.34 (n = 3) or 0.43 (n = 3) mL/kg. HP [1-¹³C]pyruvate demonstrated characteristic conversion to [1-¹³C]lactate and [¹³C]bicarbonate in the brain. Due to poor accrual, the study was closed after only 3 participants were enrolled at the highest dose level.CONCLUSIONS:Dynamic HP-¹³C MR imaging was safely performed in 6 pediatric patients with CNS tumors and demonstrated HP [1-¹³C]pyruvate brain metabolism.

Pediatric brain tumors are the most commonly encountered solid tumors in childhood and now contribute to most cancer-related deaths in children.¹ Among these tumors, diffuse intrinsic pontine glioma (DIPG) poses the gravest threat, with the median overall survival in children being only 9 months from diagnosis, despite exhaustive research efforts.² In managing pediatric brain tumors, a key issue facing the neuro-oncology community is the lack of imaging biomarkers that can support definitive and rapid assessment of response or resistance to treatment. While treatment response has traditionally been evaluated through MR imaging, there remain considerable challenges to radiographic interpretations of disease status. These potential shortcomings are exacerbated in the setting of novel therapies, such as immunotherapy, where there are no current standards to determine treatment effect versus disease progression based on imaging alone.Because of the challenges in monitoring pediatric brain tumors using standard MR imaging, hyperpolarized carbon-13 (HP-¹³C) MR imaging presents a promising molecular methodology that can potentially extend current imaging capabilities. HP-¹³C MR imaging has enabled the noninvasive investigation of in vivo brain metabolism using molecular probes whose signal is transiently enhanced via dynamic nuclear polarization.³ In studies of the adult brain,^4-8 intravenously injected HP [1-¹³C]pyruvate was shown to safely transport across the BBB and undergo enzymatic conversion to downstream metabolites [1-¹³C]lactate and [¹³C]bicarbonate, which serve as respective markers of glycolysis⁹ and oxidative phosphorylation.¹⁰ Given the metabolic alterations associated with cancer,^11,12 several of these imaging studies were designed to demonstrate the feasibility of HP-¹³C MR imaging in patients with gliomas^4,5 and also characterize serial imaging.⁸ Kinetic modeling of serial data has most importantly shown evidence of aberrant metabolism in patients with progressive glioblastoma.⁸ Additionally, earlier studies in patients with prostate cancer have indicated potential clinical relevance, based on the elevated ratio of [1-¹³C]lactate to [1-¹³C]pyruvate in biopsy-proved disease.¹³Despite advances in the molecular characterization of pediatric brain tumors, development of imaging biomarkers has remained elusive.² Recent preclinical work evaluating [1-¹³C]pyruvate metabolism in human-derived orthotopic DIPG xenografts revealed that elevated levels of [1-¹³C]lactate could distinguish tumor from healthy brain stem tissue.¹⁴ These data, derived from a disease model recapitulating human histopathology, provided evidence that HP-¹³C imaging may offer relevant metabolic biomarkers of central nervous system tumors.¹⁵ Because DIPG lesions typically demonstrate only T2/FLAIR hyperintensity with little or no contrast enhancement in the weakly perfused environment of the brain stem,¹⁶ these results are promising for a variety of pediatric brain tumors with similarly challenging radiographic presentations. In the setting of recurrent disease, in which standard MR imaging may not have distinct characteristics to confirm active disease versus treatment effect, such biomarkers could provide considerable value. They are also particularly relevant in the context of monitoring the efficacy of targeted treatment, as indicated by recent investigations of treatment response to histone deacetylase inhibitors in preclinical models of glioblastoma.¹⁷The potential to identify tumor metabolism and biomarkers of treatment response combined with the preclinical and clinical support for HP [1-¹³C]pyruvate provided the basis for investigating the use of HP [1-¹³C]pyruvate in PNOC011, a “pilot study of safety and toxicity of acquiring HP-¹³C imaging in children with brain tumors” within the Pacific Pediatric Neuro-Oncology Consortium. The objectives of PNOC011 were to assess the safety and feasibility of HP-¹³C imaging in pediatric patients with brain tumors as a first step toward developing HP methodologies in this population. Herein, we describe our experience in PNOC011 using HP [1-¹³C]pyruvate in a dose-escalation study evaluating pediatric patients with a variety of brain tumors.     

Plaque Composition as a Predictor of Plaque Ulceration in Carotid Artery Atherosclerosis: The Plaque At RISK Study

BACKGROUND AND PURPOSE:Plaque ulceration is a marker of previous plaque rupture. We studied the association between atherosclerotic plaque composition at baseline and plaque ulceration at baseline and follow-up.MATERIALS AND METHODS:We included symptomatic patients with a carotid stenosis of <70% who underwent MDCTA and MR imaging at baseline (n = 180). MDCTA was repeated at 2 years (n = 73). We assessed the presence of ulceration using MDCTA. Baseline MR imaging was used to assess the vessel wall volume and the presence and volume of plaque components (intraplaque hemorrhage, lipid-rich necrotic core, and calcifications) and the fibrous cap status. Associations at baseline were evaluated with binary logistic regression and reported with an OR and its 95% CI. Simple statistical testing was performed in the follow-up analysis.RESULTS:At baseline, the prevalence of plaque ulceration was 27% (49/180). Increased wall volume (OR  = 12.1; 95% CI, 3.5–42.0), higher relative lipid-rich necrotic core (OR = 1.7; 95% CI, 1.3–2.2), higher relative intraplaque hemorrhage volume (OR = 1.7; 95% CI, 1.3–2.2), and a thin-or-ruptured fibrous cap (OR = 3.4; 95% CI, 1.7–6.7) were associated with the presence of ulcerations at baseline. In 8% (6/73) of the patients, a new ulcer developed. Plaques with a new ulceration at follow-up had at baseline a larger wall volume (1.04 cm³ [IQR, 0.97–1.16 cm³] versus 0.86 cm³ [IQR, 0.73–1.00 cm³]; P = .029), a larger relative lipid-rich necrotic core volume (23% [IQR, 13–31%] versus 2% [IQR, 0–14%]; P = .002), and a larger relative intraplaque hemorrhage volume (14% [IQR, 8–24%] versus 0% [IQR, 0–5%]; P < .001).CONCLUSIONS:Large atherosclerotic plaques and plaques with intraplaque hemorrhage and lipid-rich necrotic cores were associated with plaque ulcerations at baseline and follow-up.

Atherosclerosis in the carotid arteries is one of the leading causes of ischemic stroke with arterio-arterial embolism as the main mechanism.^1,2 The degree of lumen stenosis and the symptomatic status of the patient are currently used for risk assessment and treatment decision-making.^3,4 Patients with severe (≥70%) and moderate (50%–69%) carotid artery stenosis benefit from carotid endarterectomy; however, the number needed to treat to prevent recurrent stroke is relatively high.⁵ Moreover, almost half of neurologic events occur in patients with a low degree of stenosis.^6,7 This finding has triggered investigations into other markers that may help to identify patients with a high risk of recurrent stroke. Much attention has been paid to markers of atherosclerosis, like plaque composition and plaque ulceration, with the aim of identifying vulnerable plaques.⁸ These vulnerable plaques have a high risk of rupture, which results in thrombus formation and embolization of plaque material and/or thrombus migrating into the intracranial circulation, thereby causing vascular occlusion and a subsequent ischemic stroke.²Plaque composition is predictive of future cerebrovascular events.^9-12 Atherosclerotic plaque ulceration, visible as plaque-surface disruption, which is a marker of previous plaque rupture, is also correlated with recurrent symptoms and associated with a higher risk of ischemic stroke.^13,14 However, the relation between vulnerable plaque components and plaque rupture is rarely investigated. Both plaque composition and ulceration can be assessed in vivo with different imaging modalities, but MR imaging is the best technique to assess plaque composition due to its superior soft-tissue contrast,¹⁵ whereas MDCTA exceeds MR imaging in the detection of plaque ulcerations due to its excellent spatial resolution with the possibility of multiplanar reconstruction.^16,17Most previous studies investigated the relation between plaque ulcerations and plaque features using a cross-sectional study design. Generally, it was found that intraplaque hemorrhage (IPH), large lipid-rich necrotic core (LRNC), and thinning or ruptured fibrous cap were associated with the presence of ulcerations,^18-21 while the presence of calcifications was inversely related to ulcerations.¹⁹ A prospective study in asymptomatic patients with severe carotid artery stenosis revealed that LRNC volume was a predictor of new surface disruption.^22,23 The aim of the current study was to investigate, in symptomatic patients with mild-to-moderate (30%–69%) carotid artery stenosis, which plaque components at baseline are predictive of plaque rupture at follow-up.     

Clinical,Imaging, and Lab Correlates of Severe COVID-19 Leukoencephalopathy

BACKGROUND AND PURPOSE:Patients infected with the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) can develop a spectrum of neurological disorders, including a leukoencephalopathy of variable severity. Our aim was to characterize imaging, lab, and clinical correlates of severe coronavirus disease 2019 (COVID-19) leukoencephalopathy, which may provide insight into the SARS-CoV-2 pathophysiology.MATERIALS AND METHODS:Twenty-seven consecutive patients positive for SARS-CoV-2 who had brain MR imaging following intensive care unit admission were included. Seven (7/27, 26%) developed an unusual pattern of “leukoencephalopathy with reduced diffusivity” on diffusion-weighted MR imaging. The remaining patients did not exhibit this pattern. Clinical and laboratory indices, as well as neuroimaging findings, were compared between groups.RESULTS:The reduced-diffusivity group had a significantly higher body mass index (36 versus 28 kg/m², P < .01). Patients with reduced diffusivity trended toward more frequent acute renal failure (7/7, 100% versus 9/20, 45%; P = .06) and lower estimated glomerular filtration rate values (49 versus 85 mL/min; P = .06) at the time of MRI. Patients with reduced diffusivity also showed lesser mean values of the lowest hemoglobin levels (8.1 versus 10.2 g/dL, P < .05) and higher serum sodium levels (147 versus 139 mmol/L, P = .04) within 24 hours before MR imaging. The reduced-diffusivity group showed a striking and highly reproducible distribution of confluent, predominantly symmetric, supratentorial, and middle cerebellar peduncular white matter lesions (P < .001).CONCLUSIONS:Our findings highlight notable correlations between severe COVID-19 leukoencephalopathy with reduced diffusivity and obesity, acute renal failure, mild hypernatremia, anemia, and an unusual brain MR imaging white matter lesion distribution pattern. Together, these observations may shed light on possible SARS-CoV-2 pathophysiologic mechanisms associated with leukoencephalopathy, including borderzone ischemic changes, electrolyte transport disturbances, and silent hypoxia in the setting of the known cytokine storm syndrome that accompanies severe COVID-19.

Among the neurologic disorders associated with Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2)^1-3 infection, there have been several reports of diffuse white matter abnormalities, including a “leukoencephalopathy with reduced diffusivity” on diffusion-weighted MR imaging.⁴ This pattern of severe, bilateral white matter involvement appears to develop late in the course of coronavirus disease 2019 (COVID-19) in critically ill patients and may be related to the prolonged hypoxemia that these patients experience, often even while asymptomatic.⁵Indeed, although leukoencephalopathy can result from a diverse group of genetic, toxic/metabolic, inflammatory, and infectious conditions, several well-described leukoencephalopathy syndromes may have direct relevance to COVID-19 pathophysiology. These disorders, which are associated with distinct clinical features, imaging patterns, and laboratory findings, include but are not limited to both delayed posthypoxic leukoencephalopathy (which often develops days or weeks following an initial, typically catastrophic, global hypoxic event, such as carbon monoxide poisoning, drowning, opioid overdose, or other causes of cardiac arrest)^6-9 and sepsis-related leukoencephalopathy (which occurs in critically ill patients and is likely due to deranged blood-brain barrier permeability caused by inflammatory mediators, allowing passage of cytokines and other neurotoxins into the cerebral white matter).^10-13Review of the current literature suggests possible roles for “silent hypoxia” and/or “cytokine storm” in the development of severe COVID-19-related leukoencephalopathy;^5,14,15 the paucity of postmortem studies to date contributes to this uncertainty.¹⁶ Our purpose, therefore, has been to characterize the clinical, imaging, and laboratory correlates of COVID-19 leukoencephalopathy, which may provide insight into the SARS-CoV-2 pathophysiologic mechanisms of severe white matter cellular injury.     

Regional Aneurysm Wall Enhancement is Affected by Local Hemodynamics: A 7T MRI Study

BACKGROUND AND PURPOSE:Aneurysm wall enhancement has been proposed as a biomarker for inflammation and instability. However, the mechanisms of aneurysm wall enhancement remain unclear. We used 7T MR imaging to determine the effect of flow in different regions of the wall.MATERIALS AND METHODS:Twenty-three intracranial aneurysms imaged with 7T MR imaging and 3D angiography were studied with computational fluid dynamics. Local flow conditions were compared between aneurysm wall enhancement and nonenhanced regions. Aneurysm wall enhancement regions were subdivided according to their location on the aneurysm and relative to the inflow and were further compared.RESULTS:On average, wall shear stress was lower in enhanced than in nonenhanced regions (P = .05). Aneurysm wall enhancement regions at the neck had higher wall shear stress gradients (P = .05) with lower oscillations (P = .05) than nonenhanced regions. In contrast, aneurysm wall enhancement regions at the aneurysm body had lower wall shear stress (P = .01) and wall shear stress gradients (P = .008) than nonenhanced regions. Aneurysm wall enhancement regions far from the inflow had lower wall shear stress (P = .006) than nonenhanced regions, while aneurysm wall enhancement regions close to the inflow tended to have higher wall shear stress than the nonenhanced regions, but this association was not significant.CONCLUSIONS:Aneurysm wall enhancement regions tend to have lower wall shear stress than nonenhanced regions of the same aneurysm. Moreover, the association between flow conditions and aneurysm wall enhancement seems to depend on the location of the region on the aneurysm sac. Regions at the neck and close to the inflow tend to be exposed to higher wall shear stress and wall shear stress gradients. Regions at the body, dome, or far from the inflow tend to be exposed to uniformly low wall shear stress and have more aneurysm wall enhancement.

High-resolution vessel wall imaging (HR-VWI) and aneurysm wall enhancement (AWE) are increasingly used to identify intracranial aneurysms with a higher risk of growth^1-3 and rupture.⁴ Aneurysms deemed “stable” on the basis of AWE may be managed conservatively and followed across time,⁵ whereas unstable aneurysms are treated to prevent rupture.However, the clinical significance and exact mechanisms leading to AWE remain unclear.⁶ One early study of patients with SAH with multiple intracranial aneurysms showed enhancement in thick-walled regions of ruptured aneurysms, while unruptured aneurysms did not enhance.⁷ This finding suggested that the presence of AWE on HR-VWI may identify the culprit aneurysm in patients with multiple aneurysms and SAH. Another study observed focal AWE in association with intramural thrombus of ruptured aneurysms and suggested that AWE may be useful in identifying rupture points.⁸ Histopathologic analyses of specimens of intracranial aneurysms treated with microsurgical clipping have shown associations between AWE and wall thickening accompanied by atherosclerotic remodeling,⁹ neovascularization,¹⁰ macrophage infiltration,¹¹ and inflammation.^12,13 Several other studies have demonstrated associations between AWE and known clinical rupture risk factors: size of >7 mm,¹⁴ anterior and posterior communicating artery location,¹⁵ irregular shape,¹⁶ and PHASES score >3 (https://qxmd.com/calculate/calculator_464/phases-score).¹⁷The subjective characterization of AWE has described patterns of enhancement as focal and circumferential. However, it is unknow why AWE does not distribute evenly within the aneurysm sac and whether this heterogeneous AWE is the result of different flow conditions within the aneurysm that ultimately translate into histologic changes.¹⁸ It is believed that flow-induced inflammation may lead to AWE. One study found lower wall shear stress (WSS) and oscillatory shear index in AWE regions compared with nonenhanced regions.¹⁹ Similarly, another study found that aneurysms with AWE were larger and had lower WSS and velocities than aneurysms without enhancement, and the AWE signal intensity was inversely correlated with WSS magnitude.²⁰ A recent study showed that the presence of AWE was associated with low normalized WSS, size, and size ratio.²¹ However, several factors other than inflammation have been proposed as potential causes of increased AWE signals, in particular low-flow patterns that lead to pseudoenhancement signals in vivo.²²Our purpose was to further investigate possible associations between local flow characteristics and focal AWE with the hope of shedding light on the mechanisms responsible for wall enhancement. We used high-resolution 7T MR imaging in determining AWE and studied the local flow patterns in different areas of the aneurysm.     

Tractography of the Cerebellar Peduncles in Second- and Third-Trimester Fetuses

BACKGROUND AND PURPOSE:Little is known about microstructural development of cerebellar white matter in vivo. This study aimed to investigate developmental changes of the cerebellar peduncles in second- and third-trimester healthy fetuses using motion-corrected DTI and tractography.MATERIALS AND METHODS:3T data of 81 healthy fetuses were reviewed. Structural imaging consisted of multiplanar T2-single-shot sequences; DTI consisted of a series of 12-direction diffusion. A robust motion-tracked section-to-volume registration algorithm reconstructed images. ROI-based deterministic tractography was performed using anatomic landmarks described in postnatal tractography. Asymmetry was evaluated qualitatively with a perceived difference of >25% between sides. Linear regression evaluated gestational age as a predictor of tract volume, ADC, and fractional anisotropy.RESULTS:Twenty-four cases were excluded due to low-quality reconstructions. Fifty-eight fetuses with a median gestational age of 30.6 weeks (interquartile range, 7 weeks) were analyzed. The superior cerebellar peduncle was identified in 39 subjects (69%), and it was symmetric in 15 (38%). The middle cerebellar peduncle was identified in all subjects and appeared symmetric; in 13 subjects (22%), two distinct subcomponents were identified. The inferior cerebellar peduncle was not found in any subject. There was a significant increase in volume for the superior cerebellar peduncle and middle cerebellar peduncle (both, P < .05), an increase in fractional anisotropy (both, P < .001), and a decrease in ADC (both, P < .001) with gestational age. The middle cerebellar peduncle had higher volume (P < .001) and fractional anisotropy (P = .002) and lower ADC (P < .001) than the superior cerebellar peduncle after controlling for gestational age.CONCLUSIONS:A robust motion-tracked section-to-volume registration algorithm enabled deterministic tractography of the superior cerebellar peduncle and middle cerebellar peduncle in vivo and allowed characterization of developmental changes.

In the second half of pregnancy, the cerebellum is growing rapidly and is extremely vulnerable.¹ Despite the increasingly recognized association of antenatal and perinatal cerebellar injury with adverse motor and neurologic outcomes later in life,^2-5 little is known about normal cerebellar developmental in the later part of gestation, in particular with regard to changes in microstructure. In fact, most existing fetal MR imaging data addresses primarily changes in cerebellar volume with gestational age (GA) or changes in volume and their association with specific diseases such as congenital heart disease.^6-8In vivo evaluation of cerebellar microstructure using fetal MR imaging has been limited by the technical challenges related to imaging the gravid abdomen, particularly patient motion. However, data from ex vivo MR imaging studies are promising. For instance, Takahashi et al^9,10 performed high-resolution ex vivo DTI of fetal specimens and demonstrated the feasibility of using tractography to outline the cerebellar peduncles prenatally. Even though tractography of the cerebellar peduncles has been sporadically reported in vivo in technical articles or general review articles on fetal DTI,¹¹ the GA-related microstructural changes that occur in the cerebellar peduncles in the second half of pregnancy remain largely unexplored.Recent advances in hardware and software have improved fetal MR imaging substantially. The use of 3T magnets, which have been shown to be safe, results in improvement of the SNR and spatial resolution, which is advantageous to image the small structures of the fetal brain.^12,13 In addition, postprocessing algorithms that enable reconstruction of motion-corrected fetal DTI data are increasingly available and have been used by several groups to characterize the development of the supratentorial white matter tracts in vivo.^14-16 We hypothesize that fetal DTI performed at 3T and processed with a robust section-to-volume motion-correction and registration¹⁴ algorithm will enable tractography of the cerebellar peduncles in fetuses in the second and third trimesters of pregnancy. We aimed to characterize fetal cerebellar tract microstructure and to investigate tract-specific developmental changes.     

Neck Location on the Outer Convexity is a Predictor of Incomplete Occlusion in Treatment with the Pipeline Embolization Device: Clinical and Angiographic Outcomes

BACKGROUND AND PURPOSE:With the increasing use of the Pipeline Embolization Device for the treatment of aneurysms, predictors of clinical and angiographic outcomes are needed. This study aimed to identify predictors of incomplete occlusion at last angiographic follow-up.MATERIALS AND METHODS:In our retrospective, single-center cohort study, 105 ICA aneurysms in 89 subjects were treated with Pipeline Embolization Devices. Patients were followed per standardized protocol. Clinical and angiographic outcomes were analyzed. We introduced a new morphologic classification based on the included angle of the parent artery against the neck location: outer convexity type (included angle,  <160°), inner convexity type (included angle,  >200°), and lateral wall type (160° ≤ included angle  ≤200°). This classification reflects the metal coverage rate and flow dynamics.RESULTS:Imaging data were acquired in 95.3% of aneurysms persistent at 6 months. Complete occlusion was achieved in 70.5%, and incomplete occlusion, in 29.5% at last follow-up. Multivariable regression analysis revealed that 60 years of age or older (OR, 5.70; P = .001), aneurysms with the branching artery from the dome (OR, 10.56; P = .002), fusiform aneurysms (OR, 10.2; P = .009), and outer convexity–type saccular aneurysms (versus inner convexity type: OR, 30.3; P < .001; versus lateral wall type: OR, 9.71; P = .001) were independently associated with a higher rate of incomplete occlusion at the last follow-up. No permanent neurologic deficits or rupture were observed in the follow-up period.CONCLUSIONS:The aneurysm neck located on the outer convexity is a new, incomplete occlusion predictor, joining older age, fusiform aneurysms, and aneurysms with the branching artery from the dome. No permanent neurologic deficits or rupture was observed in the follow-up, even with incomplete occlusion.

Flow-diversion stents with the Pipeline Embolization Device (PED; Medtronic) were first reported in 2008.¹ Since then, multiple trials^2-6 and retrospective studies^3,7,8 have reported the safety and efficacy of the PED in the treatment of intracranial aneurysms. Long-term follow-up data showed a 95.2% occlusion rate at 5 years after treatment^3,8 and no evidence of recanalization of previously occluded aneurysms.³ Angiographic and clinical long-term follow-up data are important because incomplete occlusion leads to retreatment or rerupture in coil embolization.⁹Several factors such as age, sex, smoking, fusiform-type aneurysms, small aspect ratios, and dome-neck ratios have been reported to be predictors of incomplete or complete occlusion.^10-17 However, there is debate about outcomes when using these factors because of limited analysis of the confounding factors. Moreover, the follow-up imaging rate of incomplete occlusion is sometimes insufficient (around 50% at 6 months).¹ Additionally, the same morphologic indices used in coil embolization were used in previous PED studies, even though the 2 methods are different in their treatment mechanism for aneurysms. The metal coverage ratio (MCR)^18-20 is an important metric of PED treatment.Although the MCR correlates with the occlusion rate,¹⁹ it is calculated after treatment and additional work-up is needed to acquire it. Therefore, in this study, we introduced a new classification based on the included angle of the parent artery against the neck location for the aneurysm, which can be measured before the PED treatment and complements the MCR: outer convexity type, inner convexity type, and lateral wall type. In addition, we clarified factors, including our new classification, affecting incomplete occlusion and clinical outcome in PED treatment, on the basis of data with a high follow-up rate.     

Determining the Degree of Dopaminergic Denervation Based on the Loss of Nigral Hyperintensity on SMWI in Parkinsonism

BACKGROUND AND PURPOSE:Nigrostriatal dopaminergic function in patients with Parkinson disease can be assessed using ¹²³I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropan dopamine transporter (¹²³I-FP-CIT) SPECT, and a good correlation has been demonstrated between nigral status on SWI and dopaminergic denervation on ¹²³I-FP-CIT SPECT. Here, we aim to correlate quantified dopamine transporter attenuation on ¹²³I-FP-CIT SPECT with nigrosome-1 status using susceptibility map-weighted imaging (SMWI).MATERIALS AND METHODS:Between May 2017 and January 2018, consecutive patients with idiopathic Parkinson disease (n = 109) and control participants (n = 29) who underwent ¹²³I-FP-CIT SPECT with concurrent 3T SWI were included. SMWI was generated from SWI. Two neuroradiologists evaluated nigral hyperintensity from nigrosome-1 on each side of the substantia nigra. Using consensus reading, we compared the ¹²³I-FP-CIT–specific binding ratio according to nigral hyperintensity status and the ¹²³I-FP-CIT specific binding ratio threshold to confirm the loss of nigral hyperintensity was determined using receiver operating characteristic curve analysis.RESULTS:The concordance rate between SMWI and ¹²³I-FP-CIT SPECT was 65.9%. The ¹²³I-FP-CIT–specific binding ratios in the striatum, caudate nucleus, and putamen were significantly lower when nigral hyperintensity in the ipsilateral substantia nigra was absent than when present (all, P < .001). The ¹²³I-FP-CIT–specific binding ratio threshold values for the determination of nigral hyperintensity loss were 2.56 in the striatum (area under the curve, 0.890), 3.07 in the caudate nucleus (0.830), and 2.36 in the putamen (0.887).CONCLUSIONS:Nigral hyperintensity on SMWI showed high positive predictive value and low negative predictive value with dopaminergic degeneration on ¹²³I-FP-CIT SPECT. In patients with Parkinson disease, the loss of nigral hyperintensity is prominent in patients with lower striatal specific binding ratios.

The second most common neurodegenerative disorder,^1,2 Parkinson disease (PD) is characterized by dopaminergic cell loss within the substantia nigra (SN) of the midbrain that reportedly progresses from structures called nigrosomes,¹ beginning with the largest subdivision of nigrosome-1.^3,4 The presence of nigrosome-1 can be assessed using high-resolution MR imaging, and its absence can serve as a powerful diagnostic tool for PD.^5-13The standardized assessment of nigrostriatal dopaminergic function in patients with PD has been performed using SPECT, including ¹²³I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (¹²³I-FP-CIT) SPECT as its more common variation.^14-16 Although research has demonstrated a good correlation between nigral status determined with SWI and the status of dopaminergic denervation revealed with ¹²³I-FP-CIT SPECT,^5,7 the 2 methods lack absolute agreement. In addition, denervation can reportedly be observed on ¹²³I-FP-CIT SPECT, but nigral hyperintensity is maintained on MR imaging,^5,7 possibly informing a false-negative diagnosis of PD. To the best of our knowledge, no study has evaluated the relationship between the degree of dopaminergic denervation on ¹²³I-FP-CIT SPECT and the status of nigral hyperintensity on SWI.The present study aims to determine the degree of the dopaminergic denervation on ¹²³I-FP-CIT SPECT according to the presence or loss of nigral hyperintensity on 3T MR imaging in patients with PD. We evaluated the striatal specific binding ratios (SBRs) of the ¹²³I-FP-CIT and used susceptibility map-weighted imaging (SMWI) to enhance the visibility of nigrosome-1.^17,18 The purpose of this study was to correlate quantified dopamine transporter attenuation on SPECT with the status of nigral hyperintensity on MR imaging.     

Development and Validation of a Deep Learning–Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images

BACKGROUND AND PURPOSE:Differentiating glioblastoma from solitary brain metastasis preoperatively using conventional MR images is challenging. Deep learning models have shown promise in performing classification tasks. The diagnostic performance of a deep learning–based model in discriminating glioblastoma from solitary brain metastasis using preoperative conventional MR images was evaluated.MATERIALS AND METHODS:Records of 598 patients with histologically confirmed glioblastoma or solitary brain metastasis at our institution between February 2006 and December 2017 were retrospectively reviewed. Preoperative contrast-enhanced T1WI and T2WI were preprocessed and roughly segmented with rectangular regions of interest. A deep neural network was trained and validated using MR images from 498 patients. The MR images of the remaining 100 were used as an internal test set. An additional 143 patients from another tertiary hospital were used as an external test set. The classifications of ResNet-50 and 2 neuroradiologists were compared for their accuracy, precision, recall, F1 score, and area under the curve.RESULTS:The areas under the curve of ResNet-50 were 0.889 and 0.835 in the internal and external test sets, respectively. The area under the curve of neuroradiologists 1 and 2 were 0.889 and 0.768 in the internal test set and 0.857 and 0.708 in the external test set, respectively.CONCLUSIONS:A deep learning–based model may be a supportive tool for preoperative discrimination between glioblastoma and solitary brain metastasis using conventional MR images.

Glioblastoma (GBM) and brain metastases are the most common malignant tumors in adults.¹ These 2 entities have different treatment options, and it is therefore essential to distinguish them promptly to determine the proper treatment strategy. In patients with a history of underlying malignancy and conventional MR imaging findings of multiple enhancing lesions, a diagnosis can be made easily. However, approximately 25%–30% of brain metastases present as single lesions, and in lung cancer—the most common cancer to metastasize to the brain—approximately 50% of patients are thought to have brain metastases as the initial presentation.^2,3 In addition, GBM and solitary brain metastasis have overlapping MR imaging features, including rim enhancement with perilesional T2 hyperintensity, and are thus difficult to differentiate preoperatively.⁴ However, GBM has an infiltrative growth pattern; therefore, tumor cells diffusely infiltrate beyond the enhancing portion, manifesting as a perilesional T2 hyperintense region. Brain metastases have similar MR imaging features; however, this perilesional T2 hyperintensity is primarily due to vasogenic edema caused by the leaky capillary vessels of the enhancing tumor.^5,6 In an effort to detect these microstructural differences, various advanced MR imaging techniques, such as perfusion MR imaging, MR spectroscopy, and diffusion tensor imaging, have been applied to distinguish GBM from solitary brain metastasis, with particular emphasis on the aforementioned perilesional T2 hyperintense region.^7-10 Collectively, these studies have shown promising results indicating that the perilesional T2 hyperintense region, along with the enhancing portion itself, carries valuable information that may preoperatively distinguish these 2 entities. However, advanced imaging techniques require additional scanning time, and their quantitative values can vary depending on the imaging parameters, posing difficult challenges for practical application.Recently, radiomics have been used to analyze various textural and handcrafted features to classify or predict prognosis of disease through medical images that are beyond the perception of human eye.^11,12 However, radiomics needs careful preprocessing steps, including delicate segmentation. Deep learning—a subfield in machine learning—extracts information directly from the data, omitting the step of manual feature extraction in decision making.¹³ In the field of neuro-oncology, specifically glioma imaging, previous studies have shown the potential of deep learning for classifying gliomas based on genetic mutations or clinical outcomes.^14-16In this study, we hypothesized that deep learning may differentiate GBM from solitary brain metastasis without extraction of predefined features. Thus, we aimed to develop a deep learning–based model to differentiate GBM from solitary brain metastasis using preoperative T2-weighted and contrast-enhanced (CE) T1-weighted MR images and further validate its diagnostic performance.     

Glioma-Induced Disruption of Resting-State Functional Connectivity and Amplitude of Low-Frequency Fluctuations in the Salience Network

BACKGROUND AND PURPOSE:Cognitive challenges are prevalent in survivors of glioma, but their neurobiology is incompletely understood. The purpose of this study was to investigate the effect of glioma presence and tumor characteristics on resting-state functional connectivity and amplitude of low-frequency fluctuations of the salience network, a key neural network associated with cognition.MATERIALS AND METHODS:Sixty-nine patients with glioma (mean age, 48.74 [SD, 14.32] years) who underwent resting-state fMRI were compared with 31 healthy controls (mean age, 49.68 [SD, 15.54] years). We identified 4 salience network ROIs: left/right dorsal anterior cingulate cortex and left/right anterior insula. Average salience network resting-state functional connectivity and amplitude of low-frequency fluctuations within the 4 salience network ROIs were computed.RESULTS:Patients with gliomas showed decreased overall salience network resting-state functional connectivity (P = .001) and increased amplitude of low-frequency fluctuations in all salience network ROIs (P < .01) except in the left dorsal anterior cingulate cortex. Compared with controls, patients with left-sided gliomas showed increased amplitude of low-frequency fluctuations in the right dorsal anterior cingulate cortex (P = .002) and right anterior insula (P < .001), and patients with right-sided gliomas showed increased amplitude of low-frequency fluctuations in the left anterior insula (P = .002). Anterior tumors were associated with decreased salience network resting-state functional connectivity (P < .001) and increased amplitude of low-frequency fluctuations in the right anterior insula, left anterior insula, and right dorsal anterior cingulate cortex. Patients with high-grade gliomas had decreased salience network resting-state functional connectivity compared with healthy controls (P < .05). The right anterior insula showed increased amplitude of low-frequency fluctuations in patients with grade II and IV gliomas compared with controls (P < .01).CONCLUSIONS:By demonstrating decreased resting-state functional connectivity and an increased amplitude of low-frequency fluctuations related to the salience network in patients with glioma, this study adds to our understanding of the neurobiology underpinning observable cognitive deficits in these patients. In addition to more conventional functional connectivity, amplitude of low-frequency fluctuations is a promising functional-imaging biomarker of tumor-induced vascular and neural pathology.

Detrimental effects of cancer on cognitive function and, consequently, on the quality of life are emerging as a key focus of cancer survivorship both in research and clinical practice.^1,2 Brain tumors have been shown to affect memory, processing, and attention in patients; however, their underlying neurobiology is incompletely understood.³ Using resting-state functional MR imaging (rsfMRI) to evaluate changes in cognitive resting-state networks may provide a better understanding of the pathology underlying the observable cognitive disruptions in gliomas, the most common primary brain tumor in adults.A “triple network model” of neurocognitive pathology has been proposed, which encompasses the default mode network, involved in mind wandering; the central executive network, involved in decision-making; and the salience network (SN), implicated in modulating activation of the default mode network and central executive network by detecting the presence of salient stimuli.^4-8 While previous rsfMRI research has largely focused on tumor-induced changes in the default mode network,^9,10 our study examined the less-studied SN, a network rooted in the anterior insula and the dorsal anterior cingulate cortex.⁶Prior studies evaluating gliomas and SN resting-state functional connectivity (RSFC) provided conflicting results in small patient samples: Maesawa et al¹⁰ found no significant differences in the SN in 12 patients, while Liu et al¹¹ more recently found decreased SN connectivity in 13 patients. Gliomas impact the integrity of the neurovascular unit to varying degrees, resulting in neurovascular uncoupling that has been reported to confound fMRI interpretations in patients with brain tumors.^12-14 Additionally, research has reported neuronal plasticity manifested by structural reorganization and functional remodeling of neural networks in patients with gliomas with possible alterations in clinically observable cognitive manifestations.^15-17 An rsfMRI metric, the amplitude of low-frequency fluctuations (ALFF), has recently shown promise as a biomarker for brain plasticity and hemodynamic characterization, including neurovascular uncoupling in patients with gliomas.^15-19The purpose of this study was to investigate the effect of glioma presence and tumor characteristics on overall RSFC and regional normalized ALFF within the SN in a large patient population. We hypothesized that there would be decreased average SN RSFC and altered ALFF in patients with gliomas compared with healthy controls. Recent studies have acknowledged that gliomas have variable effects on network integrity based on lesion location and proximity to network ROIs,^20-22 and unilateral gliomas can be associated with plasticity in both the ipsilateral and contralateral hemispheres.^11,17 Research also supports differences in resting-state network reorganization in aggressive high-grade gliomas compared with slower-growing low-grade gliomas.^20,23 Therefore, we also hypothesized that there would be differences in average SN RSFC and regional ALFF in patients based on the anterior-versus-posterior location, hemispheric side, and grade of glioma.     

Utility of Contrast-Enhanced T2 FLAIR for Imaging Brain Metastases Using a Half-dose High-Relaxivity Contrast Agent

BACKGROUND AND PURPOSE:Efficient detection of metastases is important for patient’ treatment. This prospective study was to explore the clinical value of contrast-enhanced T2 FLAIR in imaging brain metastases using half-dose gadobenate dimeglumine.MATERIALS AND METHODS:In vitro signal intensity of various gadolinium concentrations was explored by spin-echo T1-weighted imaging and T2 FLAIR. Then, 46 patients with lung cancer underwent nonenhanced T2 FLAIR before administration of half-dose gadobenate dimeglumine and 3 consecutive contrast-enhanced T2 FLAIR sequences followed by 1 spin-echo T1WI after administration of half-dose gadobenate dimeglumine. After an additional dose of 0.05 mmol/kg, 3D brain volume imaging was performed. All brain metastases were classified as follows: solid-enhancing, ≥ 5 mm (group A); ring-enhancing, ≥ 5 mm (group B); and lesion diameter of <5 mm (group C). The contrast ratio of the lesions on 3 consecutive phases of contrast-enhanced T2 FLAIR was measured, and the percentage increase of contrast-enhanced T2 FLAIR among the 3 groups was compared.RESULTS:In vitro, the maximal signal intensity was achieved in T2 FLAIR at one-eighth to one-half of the contrast concentration needed for maximal signal intensity in T1WI. In vivo, the mean contrast ratio values of metastases on contrast-enhanced T2 FLAIR for the 3 consecutive phases ranged from 63.64% to 83.05%. The percentage increase (PI) values of contrast-enhanced T2 FLAIR were as follows: PI_A < PI_B (P = .001) and PI_A < PI_C (P < .001). The degree of enhancement of brain metastases on contrast-enhanced T2 FLAIR was lower than on 3D brain volume imaging (P < .001) in group A, and higher than on 3D brain volume imaging (P < .001) in group C.CONCLUSIONS:Small or ring-enhancing metastases can be better visualized on delayed contrast-enhanced T2 FLAIR using a half-dose high-relaxivity contrast agent.

Brain metastases occur in approximately 25% of patients with cancer and account for 40% of adult brain tumors.¹ The incidence of brain metastases in patients with lung cancer is highest (19.9%),² resulting in high morbidity and mortality.³ Small metastases, not combined with vasogenic edema or mass effects, are often missed.¹ Improvement of the early detection of small brain metastases will contribute to developing treatment protocols and will affect the outcomes⁴ because small lesions effectively respond to therapies and can be controlled at a substantially higher rate compared with larger lesions.^5,6 For patients with metastases, contrast-enhanced T1WI (CE-T1WI) should be repeatedly performed to assess the progress of brain metastases^7,8 or the efficacy of treatment.^9,10 The conspicuity and detection rate of brain metastases can be improved with a higher dose of gadolinium-based contrast agents (GBCA).¹¹ However, multiple enhanced examinations or use of higher contrast doses may increase the potential adverse effects, such as nephrogenic systemic fibrosis,^12,13 and may lead to higher gadolinium deposition in the brain¹⁴ or other tissues.^15,16Therefore, reducing the gadolinium-based contrast agent dose may decrease the adverse effects produced by gadolinium accumulation, which is crucial to the patient’s health. T2 FLAIR is an inversion recovery pulse sequence that is sensitive to low concentrations of GBCA in the tissue.¹⁷ It is reported that only one-quarter of the routine dose of GBCA is needed for CE-T2 FLAIR to achieve a signal enhancement comparable with that of CE-T1WI; moreover, CE-T2 FLAIR may offer additional morphologic information compared with CE-T1WI alone.^17,18 Due to the suppression of intravascular and CSF signal,¹⁹ CE-T2 FLAIR imaging has been used in the detection of various intra- and extra-axial brain lesions, eg, the delineation of meningeal lesions including meningoencephalitis and leptomeningeal metastases.^20-22Previous studies mostly focused on the use of CE-T2 FLAIR after use of the normal GBCA dose; no studies were performed to assess the utility of low-dose CE-T2 FLAIR in the detection of brain metastases. Additionally, an increased delay of CE-T2 FLAIR scanning can improve the diagnosis of leptomeningeal infectious or tumoral diseases,²³ which means CE-T2 FLAIR has a relationship with scanning time. The purpose of the present study was to investigate the value of delayed low-dose CE-T2 FLAIR compared with routine-dose CE brain volume imaging (BRAVO; GE Healthcare) for contrast enhancement in brain metastases.