scholarly journals PyDesigner: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Tensor and Diffusional Kurtosis Imaging

2021 ◽  
Author(s):  
Siddhartha Dhiman ◽  
Joshua B Teves ◽  
Kathryn E Thorn ◽  
Emilie T McKinnon ◽  
Hunter G Moss ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Open Source ◽  
Software Package ◽  
Diffusion Tensor ◽  
Ease Of Use ◽  
Resonance Imaging ◽  
Diffusional Kurtosis Imaging ◽  
Weighted Magnetic Resonance Imaging ◽  
Imaging Artifacts

PyDesigner is an open-source and containerized Python software package, adapted from the DESIGNER pipeline, for diffusion weighted magnetic resonance imaging preprocessing and tensor estimation. PyDesigner combines tools from FSL and MRtrix3 to reduce the effects of signal noise and imaging artifacts on multiple diffusion measures that can be derived from the diffusion and kurtosis tensors. This publication describes the main features of PyDesigner and highlights its ease of use across platforms, while examining its accuracy and robustness in deriving commonly used diffusion and kurtosis metrics.

scholarly journals Diagnostic Value of Combined Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging with Diffusion Tensor Imaging in Predicting Parametrial Infiltration in Cervical Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ting-Ting Lin ◽  
Xin-Xiang Li ◽  
Wei-Fu Lv ◽  
Jiang-Ning Dong ◽  
Chao Wei ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Cervical Cancer ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Diagnostic Value ◽  
Intravoxel Incoherent Motion ◽  
Resonance Imaging ◽  
Diffusion Weighted ◽  
Weighted Magnetic Resonance Imaging

Objective. This study sought to determine the diagnostic value of combined intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) in predicting parametrial infiltration (PMI) in patients with cervical cancer. Materials and Methods. We enrolled 65 patients with cervical cancer confirmed by radical hysterectomy (25 PMI-negative and 40 PMI-positive) who underwent IVIM and DTI pretreatment. The parameters of IVIM (ADC, D, D   ∗ , and f) and DTI (average diffusion coefficient (DCavg) and fractional anisotropy (FA)) were recorded by two observers. All parameter differences were tested, and the receiver operating characteristic (ROC) curves were generated to estimate the diagnostic performance of significant metrics and their combinations. Results. Compared to the PMI-negative group, the PMI-positive group had significantly lower D (0.632 ± 0.017 vs. 0.773 ± 0.024, p < 0.001 ) and lower FA (0.073 ± 0.002 vs. 0.085 ± 0.003, p = 0.003 ). The area under the ROC curve (AUC) of D and FA was 0.801 and 0.726, respectively, and the combination of D and FA improved the AUC to 0.931, with a sensitivity and specificity of 80.0% and 97.5%, respectively. Conclusion. D and FA values could be used to help diagnose PMI in patients with cervical cancer. The combination of IVIM and DTI was more valuable than either option alone.

scholarly journals Processing the diffusion-weighted magnetic resonance imaging of the PING dataset

2020 ◽  
Author(s):  
Noor B Al-Sharif ◽  
Etienne St-Onge ◽  
Guillaume Theaud ◽  
Alan C Evans ◽  
Maxime Descoteaux
Keyword(s):  
Magnetic Resonance Imaging ◽  
White Matter ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Fine Tuning ◽  
Resonance Imaging ◽  
Diffusion Weighted ◽  
Weighted Magnetic Resonance Imaging ◽  
The Brain

AbstractDiffusion-weighted magnetic resonance imaging (dMRI) allows for the in-vivo assessment of anatomical white matter in the brain, thus allowing the depiction of structural connectivity. Using structural processing techniques and related methods, a growing body of literature has illustrated that connectomics is a crucial aspect to assessing the brain in health and disease. The Pediatric Imaging Neurocognition and Genetics (PING) dataset was collected and released openly to contribute to the assessment of typical brain development in a pediatric sample. This current work details the processing of diffusion-weighted images from the PING dataset, including rigorous quality assessment and fine-tuning of parameters at every step, to increase the accessibility of these data for connectomic analysis. This processing provides state-of-the-art diffusion measures, both classical diffusion tensor imaging (DTI) and more advanced HARDI-based metrics, enabling the evaluation not only of structural white matter but also of integrated multimodal analyses, i.e. combining structural information from dMRI with functional or gray matter analyses.

scholarly journals Assessment of lacrimal glands in thyroid eye disease with diffusion-weighted magnetic resonance imaging

2019 ◽  
Vol 84 ◽  
pp. 142-146 ◽  
Author(s):  
Ahmed Razek ◽  
El-hadidy Mohamed El-Hadidy ◽  
Mohamed El-Said Moawad ◽  
Nader El-Metwaly ◽  
Amr Abd El-hamid El-Said
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Thyroid Eye Disease ◽  
Eye Disease ◽  
Resonance Imaging ◽  
Lacrimal Glands ◽  
Diffusion Weighted ◽  
Weighted Magnetic Resonance Imaging

Biomineralized iron oxide–polydopamine hybrid nanodots for contrast-enhanced T1-weighted magnetic resonance imaging and photothermal tumor ablation

2021 ◽  
Vol 9 (7) ◽  
pp. 1781-1786
Author(s):  
Ze’ai Wang ◽  
Yanfeng Wang ◽  
Yuan Wang ◽  
Chaogang Wei ◽  
Yibin Deng ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Iron Oxide ◽  
Magnetic Resonance ◽  
Therapeutic Efficacy ◽  
Tumor Ablation ◽  
Resonance Imaging ◽  
Contrast Enhanced ◽  
Weighted Magnetic Resonance Imaging

Biomineralized iron oxide–polydopamine hybrid nanodots are constructed using albumin nanoreactors to facilitate contrast-enhanced T1-weighted magnetic resonance imaging as well as photothermal therapeutic efficacy.

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