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1.
《Diagnostic and interventional imaging》2020,101(9):555-564
PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%. 相似文献
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Shengxuan Cao Chen Wang Xin Ma Xu Wang Jiazhang Huang Chao Zhang Li Chen Xiang Geng Kan Wang 《Journal of orthopaedic research》2019,37(8):1860-1867
Patients with mechanic ankle instability experience increased tibiotalar and subtalar joint laxity. However, in vivo joint kinematics in functional ankle instability (FAI) patients and lateral ankle sprain (LAS) copers, especially during dynamic activities, are poorly understood. Ten FAI patients, 10 LAS copers, and 10 healthy controls were included in this study. A dual fluoroscopic imaging system was used to analyze the tibiotalar and subtalar joint kinematics during stair descent. Five key poses of stair descent were analyzed. Kinematic data from six degrees of freedom were calculated utilizing a solid modeling software. The range of motion and joint positions in each degree of freedom were compared among the three groups. The tibiotalar joints of FAI patients and LAS copers were significantly more inverted than those of healthy controls during the foot strike (p = 0.016, = 0.264). The subtalar joints of FAI patients were significantly more anteriorly translated (pose 2, p = 0.003, = 0.352; pose 3, p < 0.001, = 0.454; pose 4, p = 0.004, = 0.334), inverted (pose 4, p = 0.027, = 0.234; pose 5,p = 0.034, = 0.221), and externally rotated (pose 4, p = 0.037, = 0.217; pose 5; p = 0.004, = 0.331) than those of healthy controls during the mid‐stance and the heel off. The FAI patients showed excessive tibiotalar inversion and subtalar joint hypermobility during stair descent. Meanwhile, the LAS copers maintained subtalar joint stability, and only showed excessive tibiotalar inversion in foot strike. These data provide insight into the mechanisms behind the development of FAI after initial LAS. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1860–1867, 2019 相似文献
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雄激素不敏感综合征(androgen insensitivity syndrome,AIS)又称为睾丸女性化综合征(testicular feminization syndrome,TFS),是一种X连锁遗传病,是男性假两性畸形中较常见的类型,可分为完全型AIS和不完全型AIS,其原因主要是雄激素受体(androgen receptor,AR)基因的突变导致其对雄激素产生抵抗和不应答。本文回顾南京医科大学附属妇产医院2例CAIS患者的临床资料及诊疗过程,以期能进一步提高对该病的认知及诊治水平。 相似文献
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《Clinical neurophysiology》2020,131(1):213-224
ObjectiveSystematically review the abnormalities in event related potential (ERP) recorded in Rett Syndrome (RTT) patients and animals in search of translational biomarkers of deficits related to the particular neurophysiological processes of known genetic origin (MECP2 mutations).MethodsPubmed, ISI Web of Knowledge and BIORXIV were searched for the relevant articles according to PRISMA standards.ResultsERP components are generally delayed across all sensory modalities both in RTT patients and its animal model, while findings on ERPs amplitude strongly depend on stimulus properties and presentation rate. Studies on RTT animal models uncovered the abnormalities in the excitatory and inhibitory transmission as critical mechanisms underlying the ERPs changes, but showed that even similar ERP alterations in auditory and visual domains have a diverse neural basis. A range of novel approaches has been developed in animal studies bringing along the meaningful neurophysiological interpretation of ERP measures in RTT patients.ConclusionsWhile there is a clear evidence for sensory ERPs abnormalities in RTT, to further advance the field there is a need in a large-scale ERP studies with the functionally-relevant experimental paradigms.SignificanceThe review provides insights into domain-specific neural basis of the ERP abnormalities and promotes clinical application of the ERP measures as the non-invasive functional biomarkers of RTT pathophysiology. 相似文献
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Giorgio Gandaglia Guillaume Ploussard Massimo Valerio Agostino Mattei Cristian Fiori Nicola Fossati Armando Stabile Jean-Baptiste Beauval Bernard Malavaud Mathieu Roumiguié Daniele Robesti Paolo Dell’Oglio Marco Moschini Stefania Zamboni Arnas Rakauskas Francesco De Cobelli Francesco Porpiglia Francesco Montorsi Alberto Briganti 《European urology》2019,75(3):506-514
Background
Available models for predicting lymph node invasion (LNI) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP) might not be applicable to men diagnosed via magnetic resonance imaging (MRI)-targeted biopsies.Objective
To assess the accuracy of available tools to predict LNI and to develop a novel model for men diagnosed via MRI-targeted biopsies.Design, setting, and participants
A total of 497 patients diagnosed via MRI-targeted biopsies and treated with RP and extended pelvic lymph node dissection (ePLND) at five institutions were retrospectively identified.Outcome measurements and statistical analyses
Three available models predicting LNI were evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses. A nomogram predicting LNI was developed and internally validated.Results and limitations
Overall, 62 patients (12.5%) had LNI. The median number of nodes removed was 15. The AUC for the Briganti 2012, Briganti 2017, and MSKCC nomograms was 82%, 82%, and 81%, respectively, and their calibration characteristics were suboptimal. A model including PSA, clinical stage and maximum diameter of the index lesion on multiparametric MRI (mpMRI), grade group on targeted biopsy, and the presence of clinically significant PCa on concomitant systematic biopsy had an AUC of 86% and represented the basis for a coefficient-based nomogram. This tool exhibited a higher AUC and higher net benefit compared to available models developed using standard biopsies. Using a cutoff of 7%, 244 ePLNDs (57%) would be spared and a lower number of LNIs would be missed compared to available nomograms (1.6% vs 4.6% vs 4.5% vs 4.2% for the new nomogram vs Briganti 2012 vs Briganti 2017 vs MSKCC).Conclusions
Available models predicting LNI are characterized by suboptimal accuracy and clinical net benefit for patients diagnosed via MRI-targeted biopsies. A novel nomogram including mpMRI and MRI-targeted biopsy data should be used to identify candidates for ePLND in this setting.Patient summary
We developed the first nomogram to predict lymph node invasion (LNI) in prostate cancer patients diagnosed via magnetic resonance imaging-targeted biopsy undergoing radical prostatectomy. Adoption of this model to identify candidates for extended pelvic lymph node dissection could avoid up to 60% of these procedures at the cost of missing only 1.6% patients with LNI. 相似文献9.
《Journal of Clinical Orthopaedics and Trauma》2019,10(2):380-386
Additive manufacturing is a rapidly emerging technology which is being successfully implemented in the various field of medicine as well as in orthopaedics, where it has applications in reducing cartilage defects and treatments of bones. The technology helps through systematic collection of information about the shape of the "defects" and precise fabrication of complex 3D constructs such as cartilage, heart valve, trachea, myocardial bone tissue and blood vessels. In this paper, a large number of the relevant research papers on the additive manufacturing and its application in medical specifically orthopaedics are identified through Scopus had been studied using Bibliometric analysis and application analysis is undertaken. The bibliometric analysis shows that there is an increasing trend in the research reports on additive manufacturing applications in the field of orthopaedics. Discussions are on using technological advancement like scanning techniques and various challenges of the orthopaedic being met by additive manufacturing technology. For patient-specific orthopaedic applications, these techniques incorporate clinical practice and use for effective planning. 3D printed models printed by this technology are accepted for orthopaedic surgery such as revision of lumbar discectomy, pelvic surgery and large scapular osteochondroma. The applications of additive manufacturing in orthopaedics will experience a rapid translation in future. An orthopaedic surgeon can convert need/idea into a reality by using computer-aided design (CAD) software, analysis software to facilitate the manufacturing. Thus, AM provides a comprehensive opportunity to manufacture orthopaedic implantable medical devices. 相似文献
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