Spatial Shrinkage Estimation of Diffusion Tensors on Diffusion-Weighted Imaging Data

2013 ◽  
Vol 108 (503) ◽  
pp. 864-875 ◽  
Author(s):  
Tao Yu ◽  
Pengfei Li
NeuroImage ◽  
2015 ◽  
Vol 123 ◽  
pp. 89-101 ◽  
Author(s):  
Daan Christiaens ◽  
Marco Reisert ◽  
Thijs Dhollander ◽  
Stefan Sunaert ◽  
Paul Suetens ◽  
...  

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Archit Bhatt ◽  
Vishal Jani

The California, ABCD, and ABCD2 risk scores (ABCD system) were developed to help stratify short-term stroke risk in patients with TIA (transient ischemic attack). Beyond this scope, the ABCD system has been extensively used to study other prognostic information such as DWI (diffusion-weighted imaging) abnormalities, large artery stenosis, atrial fibrillation and its diagnostic accuracy in TIA patients, which are independent predictors of subsequent stroke in TIA patients. Our comprehensive paper suggested that all scores have and equivalent prognostic value in predicting short-term risk of stroke; however, the ABCD2 score is being predominantly used at most centers. The majority of studies have shown that more than half of the strokes in the first 90 days, occur in the first 7 days. The majority of patients studied were predominantly classified to have a higher ABCD/ABCD2 > 3 scores and were particularly at a higher short-term risk of stroke or TIA and other vascular events. However, patients with low risk ABCD2 score < 4 may have high-risk prognostic indicators, such as diffusion weighted imaging (DWI) abnormalities, large artery atherosclerosis (LAA), and atrial fibrillation (AF). The prognostic value of these scores improved if used in conjunction with clinical information, vascular imaging data, and brain imaging data. Before more data become available, the diagnostic value of these scores, its applicability in triaging patients, and its use in evaluating long-term prognosis are rather secondary; thus, indicating that the primary significance of these scores is for short-term prognostic purposes.


Author(s):  
Jian JIANG ◽  
Liangcai BAI ◽  
Xueling ZHANG ◽  
Jianli LIU ◽  
Junlin ZHOU

Background: To evaluate the diagnostic value of diffusion weighted imaging (DWI) and apparent diffusion coefficient measurement (ADC) in glioma. cient measurement (ADC) in glioma. Methods: Thirty two low-grade glioma patients and 31 high-grade glioma patients who were confirmed by pathology in Lanzhou University Second Hospital, Lanzhou, China from February 2016 to January 2019 were selected. The other 30 patients with brain metastases were selected as a control group. DWI imaging data of the three groups were collected, and ADC, relative ADC (rADC) values in tumor parenchyma, peritumor edema area, and contralateral normal white matter area were measured, and the levels of n-acetyl aspartic acid (NAA), choline (Cho), creatine (Cr) of tumor metabolites were analyzed. Results: rADC values in the peri-tumor edema areas of the high-grade glioma group were significantly lower than those in the low-grade group and the metastatic group (P=0.011), and the low-grade group was significantly lower than that in the metastatic group (P < 0.05). NAA/Cho and NAA/Cr in parenchymal and peritumor edema areas of patients in the advanced group were significantly lower than those in the metastatic group (P < 0.05), and Cho /Cr was significantly higher than those in the metastatic group (P < 0.05). Conclusion: the rADC value, NAA/Cho, NAA/Cr and Cho/Cr in parenchymal and peritumor edema areas of the tumor can help to distinguish high-grade glioma, low-grade glioma and brain metastases.


2014 ◽  
Vol 18 (8) ◽  
pp. 1290-1298 ◽  
Author(s):  
Pei Zhang ◽  
Marc Niethammer ◽  
Dinggang Shen ◽  
Pew-Thian Yap

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yi-Hsuan Chuang ◽  
Hsin-You Ou ◽  
Chun-Yen Yu ◽  
Chao-Long Chen ◽  
Ching-Chun Weng ◽  
...  

Abstract Background Tumor recurrence is the major risk factor affecting post-transplant survival. In this retrospective study, we evaluate the prognostic values of magnetic resonance (MR) diffusion-weighted imaging (DWI) in liver transplantation for hepatocellular carcinoma (HCC). Methods From April 2014 to September 2016, 106 HCC patients receiving living donor liver transplantation (LDLT) were enrolled. Nine patients were excluded due to postoperative death within 3 months and incomplete imaging data. The association between tumor recurrence, explant pathologic findings, and DWI parameters was analyzed (tumor-to-liver diffusion weighted imaging ratio, DWIT/L; apparent diffusion coefficients, ADC). The survival probability was calculated using the Kaplan–Meier method. Results Sixteen of 97 patients (16%) developed tumor recurrence during the follow-up period (median of 40.9 months; range 5.2–56.5). In those with no viable tumor (n = 65) on pretransplant imaging, recurrence occurred only in 5 (7.6%) patients. Low minimum ADC values (p = 0.001), unfavorable tumor histopathology (p <  0.001) and the presence of microvascular invasion (p <  0.001) were risk factors for tumor recurrence, while ADCmean (p = 0.111) and DWIT/L (p = 0.093) showed no significant difference between the groups. An ADCmin ≤ 0.88 × 10− 3 mm2/s was an independent factor associated with worse three-year recurrence-free survival (94.4% vs. 23.8%) and overall survival rates (100% vs. 38.6%). Conclusions Quantitative measurement of ADCmin is a promising prognostic indicator for predicting tumor recurrence after liver transplantation.


NeuroImage ◽  
2014 ◽  
Vol 102 ◽  
pp. 704-716 ◽  
Author(s):  
Dianne K. Patterson ◽  
Cyma Van Petten ◽  
Pélagie M. Beeson ◽  
Steven Z. Rapcsak ◽  
Elena Plante

2021 ◽  
Author(s):  
Siemon C de Lange ◽  
Martijn P van den Heuvel

We describe a Connectivity Analysis TOolbox (CATO) for the reconstruction of structural and functional brain connectivity based on diffusion weighted imaging and resting-state functional MRI data. CATO is an integrative and modular software package that enables researchers to run end-to-end reconstructions from MRI data to structural and functional connectome maps, customize their analysis and utilize different software packages during the data preprocessing. The structural and functional connectome maps can be reconstructed with respect to user-defined (sub)cortical atlases providing aligned connectivity matrices for integrative multimodal analyses. We outline the structural and functional processing pipelines in CATO, the implementation in MATLAB and associated stand-alone application, and the calibration of performance with respect to simulated diffusion weighted imaging data and resting-state functional MRI data from the ICT2015 challenge and the Human Connectome Project. CATO is free open-source software and available at www.dutchconnectomelab.nl/CATO.


Sign in / Sign up

Export Citation Format

Share Document