多b值DWI在儿童脑肿瘤中的初步研究

目的:探讨多b值DWI在儿童脑肿瘤中的应用价值。方法:对31例脑肿瘤患儿行EPI-DWI扫描,采用0～4000s/mm2之间的12个b值。按照单指数模型计算低b值ADC(ADClow)(b≤200s/mm2)、高b值ADC(ADChigh,200s/mm2相似文献   

肘部尺神经扩散张量成像技术参数优化的研究

目的：优化肘部尺神经扩散张量成像(DTI)参数。方法使用5组不同 b 值和扩散梯度方向数量(NDGDs)DTI 序列采集13名志愿者肘部尺神经图像并建立扩散示踪图(DTT)。比较不同成像参数条件下,尺神经各向异性分数(FA)、表观扩散系数(ADC)、神经纤维束长度和 DTI 图像质量的差异性。结果18个正常尺神经 DTI 结果纳入研究。不同成像条件下,尺神经 FA 值无明显差异。当 NDGDs 一定时,b 值升高,图像质量下降,尺神经 ADC 值减低;而 NDGDs 对 ADC 值和图像质量无显著影响。b=1000 s/mm2,NDGDs=20时,测得尺神经纤维束长度最长,且 DTT 的主观评分最高。结论以 b=1000 s/mm2,NDGDs=20用于肘部尺神经 DTI,可获得良好的图像质量和稳定的观测指标。     

Analytical error propagation in diffusion anisotropy calculations

PURPOSE: To develop an analytical formalism describing how noise and selection of diffusion-weighting scheme propagate through the diffusion tensor imaging (DTI) computational chain into variances of the diffusion tensor elements, and errors in the relative anisotropy (RA) and fractional anisotropy (FA) indices. MATERIALS AND METHODS: Singular-value decomposition (SVD) was used to determine the tensor variances, with diffusion-weighting scheme and measurement noise incorporated into the design matrix. Anisotropy errors were then derived using propagation of error. To illustrate the applications of the model, 12 data sets were acquired from each human subject, over a range of b-values (500-2500 seconds/mm2) and diffusion-weighting gradient directions (N = 6-55). The mean RA and FA values and their respective errors were calculated within a region of interest (ROI) in the splenium. The RA and FA errors as a function of b-value and N were evaluated, and a number of diffusion-weighting schemes were assessed based on a new metric, sum of diffusion tensor variances. RESULTS: When the acquisition time was held constant, the sum of the diffusion tensor variances decreased as N increased. The same trend was also observed for several diffusion-weighting schemes with constant condition number when noise in the diffusion-weighted (DW) images was assumed unity. Errors in both FA and RA increased with b-value and decreased with N. The FA error in the splenium was approximately threefold smaller than RA error, irrespective of b-value or N. CONCLUSION: The condition number may not adequately characterize the noise sensitivity for a given diffusion-weighting scheme. Signal averaging may not be as effective as increasing N, especially when N is small (e.g., N < 13). Due to its smaller error, FA is preferred over RA for quantitative DTI applications.     

大脑白质纤维磁共振弥散张量成像扫描参数研究

目的：探讨不同的磁共振弥散张量成像（diffusion tensor imaging,DTI）扫描参数对大脑白质纤维弥散张量图像的影响,以期获得最佳的扫描参数。方法：21例正常志愿者（男11例,女10例;年龄16-63岁,平均38.7岁）参加了该项研究。随机分为3组：b值组、弥散敏感梯度方向组和层厚/层间距组。各组分别应用不同的DTI扫描参数,第1组b值组：可变参数是b值,分别为300、1 000、3 000 s/mm^2mm,不变参数是：层厚/层间距5 mm/0 mm,弥散敏感梯度方向数21。第2组弥散敏感梯度方向组：可变参数是弥散敏感梯度方向数,分别为6、13、21,不变参数是：层厚/层间距5 mm/0 mm,b值为1 000 s/mm^2。第3组层厚/层间距组,可变参数是层厚/层间距,分别为8 mm/2 mm5、mm/0 mm、3.5 mm/0 mm,不变参数是：b值为1 000 s/mm^2,弥散敏感梯度方向数为21。将所成FA图像和DEC图分为3个不同的等级,进行评价。结果：不同的扫描参数所成大脑白质纤维弥散张量图像的质量是不相同的。在b值组,以低b值所成图像较佳,其中以b值=1 000 s/mm^2为最佳,而高b值所成图像噪声较大。施加的弥散敏感梯度方向数并非越多越好,13个方向与21个方向所成图像没有明显差别,6个方向所成图像质量较差。层厚/层间距对图像的影响最大,层厚越厚,图像的信噪比越大。结论：在临床工作中,比较实用的大脑白质纤维弥散张量成像扫描参数为：b值=1 000 s/mm^2,弥散敏感梯度方向数为13,层厚/层间距为5 mm/0 mm。     

快速 DTI 在急性颈髓损伤的临床应用

目的：研究扩散张量成像(DTI)在急性颈髓损伤(CSCI)的成像特点,评估其临床应用价值。方法本组8例 CSCI 患者(发病72 h 内)均采用3.0T 磁共振仪进行快速颈髓 DTI 扫描,并在工作站进行扩散张量纤维束成像(DTT)。同时,在工作站分别测量并计算颈髓病变区及上下相对正常区的各向异性(FA)值和表观扩散系数(ADC)值,之后进行统计学组间配对 t 检验分析(SPSS 13.0)。结果急性 CSCI 以 C5~C6节段(占4/8)和 C4~C5节段(占3/8)多见,且快速 DTI 均获得了较好的图像质量。急性 CSCI 时病变区 FA 值和 ADC 值均明显低于相对正常区域数值(P <0.01),相应在 FA 图和 ADC 图均表现为低信号,而上下相对正常区 FA 值和 ADC 值间无明显区别;同时,DTT 有利于显示刀刺伤导致的颈髓纤维束断裂,颈髓闭合伤则主要表现为脊髓纤维束紊乱等。结论3.0T 快速 DTI 序列可以在2 min 扫描时间内获得临床较为满意的诊断图像,并通过 FA 值和 ADC 值更敏感地反映急性 CSCI 后髓鞘损伤导致的 FA 改变及细胞毒性水肿和血管源性水肿导致的水分子扩散的变化。     

Redefinition of multiple sclerosis plaque size using diffusion tensor MRI

OBJECTIVE: We used diffusion tensor MRI to redefine the size of multiple sclerosis (MS) plaques on fractional anisotropy (FA) maps. MATERIALS AND METHODS: Thirty-six white matter (WM) plaques were identified in 20 patients with MS. Plaque FA was measured by placing regions of interest (ROIs) on plaques on diffusion tensor images. We compared FA values in identical mirror-image ROIs placed on normal-appearing WM in the contralateral hemisphere. This comparison showed a mean decrease in FA of 41% in plaques, serving as the threshold for outlining abnormal regions in normal-appearing WM surrounding plaques. ROIs were placed around each plaque and FA values were compared with those in the mirror-image ROIs. Combined areas of perilesional normal-appearing WM with 40% or more FA reduction plus plaque were compared with the areas of abnormality on T2-weighted images using a paired Student's t test. A p value of 0.05 or less was considered significant. RESULTS: Mean plaque area was 60 mm(2) (range, 15-103 mm(2)), mean plaque FA was 0.251 (range, 0.133-0.436), and mean FA of contralateral normal-appearing WM was 0.429 (range, 0.204-0.712). Applying a threshold of 40% FA reduction, mean combined area of abnormal WM (including plaque seen on T2-weighted sequences) was 87 mm(2) (range, 30-251 mm(2)) or 145% of the mean plaque area that was seen on T2-weighted images (p < 0.001). CONCLUSION: Using an operator-defined threshold of abnormal FA values based on plaque anisotropy characteristics, we saw a statistically significant increase in plaque size.     

磁共振弥散张量成像对正常大脑白质纤维束构象的初步研究

目的利用磁共振弥散张量成像(DTI)研究正常成人脑内各部位各向异性程度及正常白质纤维束构象特征.方法对25名正常志愿者进行常规MR及DTI序列检查,重建FA图及三维彩色编码张量图.分别在半卵圆中心、基底节区和大脑脚层面测量主要白质束的FA值.结果DTI显示灰质与白质区各向异性存在显著差异,不同部位的白质纤维束各向异性程度亦不相同,且左右两侧基本对称,重建FA图和三维彩色编码张量图可显示白质内大部分主要的白质纤维束.结论DTI可清晰显示脑内白质纤维束的走行及分布,为了解脑功能与白质通路间关系提供了有力研究手段.     

Cross-subject comparison of principal diffusion direction maps.

Diffusion tensor imaging (DTI) data differ fundamentally from most brain imaging data in that values at each voxel are not scalars but 3 x 3 positive definite matrices also called diffusion tensors. Frequently, investigators simplify the data analysis by reducing the tensor to a scalar, such as fractional anisotropy (FA). New statistical methods are needed for analyzing vector and tensor valued imaging data. A statistical model is proposed for the principal eigenvector of the diffusion tensor based on the bipolar Watson distribution. Methods are presented for computing mean direction and dispersion of a sample of directions and for testing whether two samples of directions (e.g., same voxel across two groups of subjects) have the same mean. False discovery rate theory is used to identify voxels for which the two-sample test is significant. These methods are illustrated in a DTI data set collected to study reading ability. It is shown that comparison of directions reveals differences in gross anatomic structure that are invisible to FA.     

In vivo diffusion tensor imaging of the rat spinal cord at 9.4T

PURPOSE: To determine differences in diffusion measurements in white matter (WM) and gray matter (GM) regions of the rat cervical, thoracic, and cauda equina spinal cord using in vivo diffusion tensor imaging (DTI) with a 9.4T MR scanner. MATERIALS AND METHODS: DTI was performed on seven rats in three slices at the cervical, thoracic, and cauda equina regions of the spinal cord using a 9.4T magnet. Axial diffusion weighted images (DWIs) were collected at a b-value of 1000 seconds/mm(2) in six directions. Regions of interest were identified via T2-weighted images for the lateral, dorsal, and ventral funiculi, along with GM regions. RESULTS: Analysis of variance (ANOVA) results indicated significant differences between every WM funiculus compared to GM for longitudinal apparent diffusion coefficient (lADC), transverse apparent diffusion coefficient (tADC), fractional anisotropy (FA), measured longitudinal anisotropy (MA1), and anisotropy index (AI). A significant difference in mean diffusivity (MD) between regions of the spinal cord was not found. Diffusion measurements were significantly different at each spinal level. In general, GM regions were significantly different than WM regions; however, there were few significant differences between individual WM regions. CONCLUSION: In vivo DTI of the rat spinal cord at 9.4T appears sensitive to the architecture of neural structures in the rat spinal cord and may be a useful tool in studying trauma and pathologies in the spinal cord.     

Theory of diffusion tensor imaging and fiber tractography analysis

Magnetic Resonance Imaging (MRI) techniques have been increasingly applied to the study of molecular displacement (diffusion) in biologic tissue. The magnetic resonance measurement of an effective diffusion tensor of water in tissues can provide unique biologically and clinically relevant information that is not available from other imaging modalities. For this purpose Diffusion Tensor Imaging (DTI) is applied. DTI is an MRI variation that may significantly improve our understanding of brain structure and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences sensitive to microscopic random water motion. The resultant images display and allow for quantification of how water diffuses along axes or diffusion encoding directions. This can help measure and quantify a tissue's orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this article we discuss the theory on which DTI depends on, how can be used in mapping fiber tracts. Also the fiber tracking algorithms are presented.     

Diffusion tensor imaging (DTI) of rodent brains in vivo using a 1.5T clinical MR scanner

PURPOSE: To evaluate the feasibility of using a clinical 1.5T MR scanner to perform magnetic resonance (MR) diffusion tensor imaging (DTI) on in vivo rodent brains and to trace major rodent neuronal bundles with anatomical correlation. MATERIALS AND METHODS: Two normal adult Sprague Dawley (SD) rats were anesthetized and imaged in a 1.5T MR scanner with a microscopic coil. DTI was performed at a resolution of 0.94 mm x 0.94 mm x 0.5 mm (reconstructed to 0.47 mm x 0.47 mm x 0.5 mm, with b-factors of 600 seconds/mm2 and 1000 seconds/mm2) and a higher resolution of 0.63 mm x 0.63 mm x 0.5 mm (reconstructed to 0.235 mm x 0.235 mm x 0.5 mm, with a b-factor of 1500 seconds/mm2). The fiber-tracking results were correlated with corresponding anatomical sections stained to visualize neuronal fibers. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of the neuronal fibers were measured and compared with results in published reports. RESULTS: Several major neuronal fiber tracts, including the corticospinal cord, corpus callosum, and anterior commissure, were identified in all DTI data sets. Stained anatomical sections obtained from the rats confirmed the location of these fibers. The ADC values (0.6-0.8 +/- 10(-3) mm2/second) of the fibers were similar to published figures. However, the FA values (0.3-0.35) were lower than those obtained in previous studies of white matter in rodent spinal cord. CONCLUSION: We have demonstrated the feasibility of using a 1.5T clinical MR scanner for neuronal fiber tracking in rodent brains. The technique will be useful in rodent neuroanatomy studies. Further investigation is encouraged to verify the FA values generated by DTI with such techniques.     

创伤性脑白质损伤的扩散张量成像研究

目的:评价扩散张量成像(DTI)在创伤性脑白质损伤(WMI)中的应用价值。方法:16例创伤性脑外伤后经临床诊断有WMI的患者通过Philips 1.5TIntera Achieva MR扫描仪行常规MRI和DTI。后处理获得部分各向异性指数(FA)、表观弥散系数(ADC)和纤维示踪成像三维图。根据T2WI及T2快速场回波图像,分别于WMI区域、同侧同名或对侧同名纤维束正常区域取感兴趣区,测量FA值和ADC值并进行比较。结果:脑外伤患者损伤脑白质中挫伤和出血、仅挫伤和仅出血区域三者之间的FA值(F=0.68,P>0.05)和ADC值(F=0.53,P>0.05)均未见明显不同。除仅出血区域的ADC值与对照区域相比差异无统计学意义(t=1.36,P>0.05),挫伤和出血(t=9.72,P<0.05)、仅挫伤(t=8.28,P<0.05)和仅出血(t=5.44,P<0.05)区域的FA值较正常对照区域明显降低,挫伤和出血(t=4.71,P<0.05)、仅挫伤(t=4.81,P<0.05)的ADC值较正常对照明显增高,纤维示踪成像显示损伤区域脑白质较正常区域稀疏、分离、缺失。结论:DTI技术能够显示患者WMI区域的异常改变,但ADC值对出血的判断有局限性。     

Three dimensional myoarchitecture of the human tongue determined in vivo by diffusion tensor imaging with tractography

PURPOSE: To study the anatomical relationships involving the intrinsic and extrinsic myofiber populations of the human tongue employing diffusion tensor imaging (DTI) with tractography. MATERIALS AND METHODS: Images of the human tongue in vivo were obtained using a twice-refocused spin echo DTI pulse sequence at 1.5 T, isotropic 3 x 3 x 3 mm(3) voxels, b-value 500 seconds/mm(2), and 90 different diffusion sensitizing gradient directions. Multivoxel tracts were generated along the vectors, corresponding to the directions of maximal diffusion in each voxel. The data was visualized using custom fiber tracking software and images compared with known anatomy. RESULTS: DTI tractography depicts the complete three-dimensional (3D) myoarchitecture of the human tongue, specifically demonstrating the geometric relationships between the intrinsic and extrinsic myofiber populations. These results define the manner in which key extrinsic fiber populations merge with the longitudinally-, transversely-, and vertically-aligned intrinsic fibers. CONCLUSION: The current results display for the first time the use of DTI tractography in vivo to visualize the complete structural anatomy of the human tongue and allow us to consider fundamental structure-function relationships.     

Toward a quantitative assessment of diffusion anisotropy

Indices of diffusion anisotropy calculated from diffusion coefficients acquired in two or three perpendicular directions are rotationally variant. In living monkey brain, these indices severely underestimate the degree of diffusion anisotropy. New indices calculated from the entire diffusion tensor are rotationally invariant (RI). They show that anisotropy is highly variable in different white matter regions depending on the degree of coherence of fiber tract directions. In structures with a regular, parallel fiber arrangement, water diffusivity in the direction parallel to the fibers (D_| ≈ 1400–1800 × 10⁻⁶ mm²/s) is almost 10 times higher than the average diffusivity in directions perpendicular to them ((D + D⊥′)/2 ≈ 150–300 × 10⁻⁶ mm²/s), and is almost three times higher than previously reported. In structures where the fiber pattern is less coherent (e.g., where fiber bundles merge), diffusion anisotropy is significantly reduced. However, RI anisotropy indices are still susceptible to noise contamination. Monte Carlo simulations show that these indices are statistically biased, particularly those requiring sorting of the eigenvalues of the diffusion tensor based on their magnitude. A new intervoxel anisotropy index is proposed that locally averages inner products between diffusion tensors in neighboring voxels. This “lattice” RI index has an acceptably low error variance and is less susceptible to bias than any other RI anisotropy index proposed to date.     

MR microscopy of multicomponent diffusion in single neurons.

This study examines multicomponent diffusion in isolated single neurons and discusses the implications of the results for macroscopic water diffusion in tissues. L7 Aplysia neurons were isolated and analyzed using a 600 MHz Bruker wide-bore instrument with a magnetic susceptibility-matched radiofrequency microcoil. Using a biexponential fit, the apparent diffusion coefficients (ADCs) from the cytoplasm (with relative fraction) were 0.48 +/- 0.14 x 10(-3) mm2 x s(-1) (61 +/- 11%) for the fast component, and 0.034 +/- 0.017 x 10(-3) mm2 x s(-1) (32 +/- 11%) for the slow component (N = 10). Diffusion in the nucleus appears to be primarily monoexponential, but with biexponential analysis it yields 1.31 +/- 0.32 x 10(-3) mm2 x s(-1) (89 +/- 6%) for the fast component and 0.057 +/- 0.073 x 10(-3) mm2 x s(-1) (11 +/- 6%) for the slow (N = 5). The slow component in the nucleus may be explained by cytoplasmic volume averaging. These data demonstrate that water diffusion in the cytoplasm of isolated single Aplysia neurons supports a multiexponential model. The ADCs are consistent with previous measurements in the cytoplasm of single neurons and with the slow ADC measurement in perfused brain slices. These distributions may explain the multiple compartments observed in tissues, greatly aiding the development of quantitative models of MRI in whole tissues.     

3.0T MR DTI及DTT对正常青年人腕管内正中神经的定量分析

目的 运用扩散张量成像(DTI)定量分析健康青年人腕管内正中神经(MN)部分功能参数值特点及扩散张量纤维束成像(DTT)重建MN纤维束.方法 采用3.0T MR对25名健康志愿者行腕部常规MR及DTI序列扫描,测量DTI各参数值并重建MN纤维束.结果 ①MN各向异性分数(FA)值=0.686±0.089、MN轴向扩散系数(AD)值=(2.085±0.263)mm2/s、MN径向扩散系数(RD)值=(0.568±0.151)mm2/s、MN平均扩散率(ADC)值=(1.073±0.140)mm2/s.②各层面FA、RD值之间存在显著差异(P<0.05),各层面AD、ADC及各本征值E1、E2、E3之间差异无统计学意义(P>0.05).③腕管内MN从近心端到远心端DTI各部分功能参数均有不同的变化趋势.④MN FA、MN AD、MN RD、MN ADC的95%置信区间上下限分别为(0.675,0.698)、(2.052,2.117)、(0.549,0.587)、(1.056,1.091).⑤利用DTT可以完整地重建显示MN纤维束,远端分支亦能显示.结论 应用DTI及DTT技术可以定量描述MN的FA及直观显示重建的MN纤维束,可为诊断MN病变提供定量的观察指标.     

Classification and quantification of neuronal fiber pathways using diffusion tensor MRI.

Quantitative characterization of neuronal fiber pathways in vivo is of significant neurological and clinical interest. Using the capability of MR diffusion tensor imaging to determine the local orientations of neuronal fibers, novel algorithms were developed to bundle neuronal fiber pathways reconstructed in vivo with diffusion tensor images and to quantify various physical and geometric properties of fiber bundles. The reliability of the algorithms was examined with reproducibility tests. Illustrative results show that consistent physical and geometric measurements of novel properties of neuronal tissue can be obtained, which offer considerable potential for the quantitative study of fiber pathways in vivo.     

Replicability of diffusion tensor imaging measurements of fractional anisotropy and trace in brain

PURPOSE: To evaluate within-scanner and between-scanner reliability of fractional anisotropy (FA) and trace (sum of the diagonal elements of the diffusion tensor) as measured by diffusion tensor imaging (DTI). MATERIALS AND METHODS: Ten young healthy adults were scanned on three separate days, on two different systems made by the same manufacturer. One scan was acquired at one site, and two scans were acquired on two different occasions on another scanner at another site. Three levels of analysis were used to compare the DTI metrics: 1) a voxel-by-voxel analysis of all supratentorial brain (gray matter + white matter + cerebrospinal fluid) and of supratentorial white matter; 2) a slice-by-slice analysis of supratentorial white matter; and 3) a single-region analysis of the corpus callosum. RESULTS: The voxel-by-voxel analysis of all supratentorial brain found that FA and trace measures and correlations were equivalently and significantly higher within than across scanners. For supratentorial white matter, FA was similar within and across scanners, whereas trace demonstrated across-scanner bias. A similar pattern was observed for the slice-by-slice comparison. For the single-region analysis of the corpus callosum, within-scanner FA and trace measures were highly reproducible for FA (CV = 1.9%) and trace (CV = 2.6%), but both DTI measures showed a systematic mean bias across scanners (CV = 4.5% for FA and CV = 7.5% for trace). CONCLUSION: These estimates of measurement variation and scanner bias can be used to predict effect sizes for longitudinal and multisite studies using diffusion tensor imaging.     

High-resolution line scan diffusion tensor MR imaging of white matter fiber tract anatomy

BACKGROUND AND PURPOSE: MR diffusion tensor imaging permits detailed visualization of white matter fiber tracts. This technique, unlike T2-weighted imaging, also provides information about fiber direction. We present findings of normal white matter fiber tract anatomy at high resolution obtained by using line scan diffusion tensor imaging. METHODS: Diffusion tensor images in axial, coronal, and sagittal sections covering the entire brain volume were obtained with line scan diffusion imaging in six healthy volunteers. Images were acquired for b factors 5 and 1000 s/mm(2) at an imaging resolution of 1.7 x 1.7 x 4 mm. For selected regions, images were obtained at a reduced field of view with a spatial resolution of 0.9 x 0.9 x 3 mm. For each pixel, the direction of maximum diffusivity was computed and used to display the course of white matter fibers. RESULTS: Fiber directions derived from diffusion tensor imaging were consistent with known white matter fiber anatomy. The principal fiber tracts were well observed in all cases. The tracts that were visualized included the following: the arcuate fasciculus; superior and inferior longitudinal fasciculus; uncinate fasciculus; cingulum; external and extreme capsule; internal capsule; corona radiata; auditory and optic radiation; anterior commissure; corpus callosum; pyramidal tract; gracile and cuneatus fasciculus; medial longitudinal fasciculus; rubrospinal, tectospinal, central tegmental, and dorsal trigeminothalamic tract; superior, inferior, and middle cerebellar peduncle; pallidonigral and strionigral fibers; and root fibers of the oculomotor and trigeminal nerve. CONCLUSION: We obtained a complete set of detailed white matter fiber anatomy maps of the normal brain by means of line scan diffusion tensor imaging at high resolution. Near large bone structures, line scan produces images with minimal susceptibility artifacts.     

Assessment of multiexponential diffusion features as MRI cancer therapy response metrics

The aim of this study was to empirically test the effect of chemotherapy‐induced tissue changes in a glioma model as measured by several diffusion indices calculated from nonmonoexponential formalisms over a wide range of b‐values. We also compared these results to the conventional two‐point apparent diffusion coefficient calculation using nominal b‐values. Diffusion‐weighted imaging was performed over an extended range of b‐values (120–4000 sec/mm²) on intracerebral rat 9L gliomas before and after a single dose of 1,3‐bis(2‐chloroethyl)‐1‐nitrosourea. Diffusion indices from three formalisms of diffusion‐weighted signal decay [(a) two‐point analytical calculation using either low or high b‐values, (b) a stretched exponential formalism, and (c) a biexponential fit] were tested for responsiveness to therapy‐induced differences between control and treated groups. Diffusion indices sensitive to “fast diffusion” produced the largest response to treatment, which resulted in significant differences between groups. These trends were not observed for “slow diffusion” indices. Although the highest rate of response was observed from the biexponential formalism, this was not found to be significantly different from the conventional monoexponential apparent diffusion coefficient method. In conclusion, parameters from the more complicated nonmonoexponential formalisms did not provide additional sensitivity to treatment response in this glioma model beyond that observed from the two‐point conventional monoexponential apparent diffusion coefficient method. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.