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Automatic segmentation of white matter lesions on multi-parametric MRI: convolutional neural network versus vision transformer.
BMC Neurol
January 2025
Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, School of Medicine, College of Medicine, National Sun Yat-Sen University, No. 123 Ta-Pei Road, Niao-Sung Dist, Kaohsiung, 83305, Taiwan.
Background And Purpose: White matter hyperintensities in brain MRI are key indicators of various neurological conditions, and their accurate segmentation is essential for assessing disease progression. This study aims to evaluate the performance of a 3D convolutional neural network and a 3D Transformer-based model for white matter hyperintensities segmentation, focusing on their efficacy with limited datasets and similar computational resources.
Materials And Methods: We implemented a convolution-based model (3D ResNet-50 U-Net with spatial and channel squeeze & excitation) and a Transformer-based model (3D Swin Transformer with a convolutional stem).
Is biparametric MRI a feasible option for detecting clinically significant prostate cancer?: A systematic review and meta-analysis.
Urol Oncol
January 2025
Research Department, Urovallarta Medical Center, Puerto Vallarta, Mexico.
Background: Multiparametric MRI (Mp-MRI) is a key tool to screen for Prostate Cancer (Pca) and Clinically Significant Prostate Cancer (CsPca). It primarily includes T2-Weighted imaging (T2w), diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced imaging (DCE). Despite its improvements in CsPca screening, concerns about the cost-effectiveness of DCE persist due to its associated side effects, increased cost, longer acquisition time, and limitations in patients with poor kidney function.
View Article and Find Full Text PDFQuantitative 3-T Multiparametric MRI Parameters as Predictors of Aggressive Prostate Cancer.
Radiol Imaging Cancer
January 2025
From the Departments of Radiological Sciences (D.H.S.K., I.S., V.M., W.H., K.H.S., D.S.L., S.S.R.), Medicine Statistics Core (T.G.), Pathology (A.S.), and Urology (R.E.R., S.S.R.), David Geffen School of Medicine at UCLA, 885 Tiverton Dr, Los Angeles, CA 90095.
Purpose To determine which quantitative 3-T multiparametric MRI (mpMRI) parameters correlate with and help predict the presence of aggressive large cribriform pattern (LCP) and intraductal carcinoma (IDC) prostate cancer (PCa) at whole-mount histopathology (WMHP). Materials and Methods This retrospective study included 130 patients (mean age ± SD, 62.6 years ± 7.
View Article and Find Full Text PDFDiffusion-weighted MRI-Derived ADC and tumor volume as predictive imaging markers for neoadjuvant chemotherapy response in muscle-invasive bladder cancer.
BMC Med Imaging
January 2025
Urology and Nephrology Research Center, Research Institute for Urology and Nephrology, Shahid Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, No.103, Shahid Jafari St., Pasdaran Ave., Tehran, 1666677951, Iran.
Background: This prospective study tested the hypothesis that the apparent diffusion coefficient (ADC) value and tumor volume (TV) measured in diffusion-weighted magnetic resonance imaging (DW-MRI) before, during, and after the treatment are quantitative imaging markers to assess tumor response in muscle-invasive bladder cancer (MIBC) patients undergoing neoadjuvant chemotherapy (NAC).
Methods: Multi-parametric MRI was prospectively done for MIBC patients at 3 time points. Pre-treatment ADC value, pre-treatment TV, as well as, percent of changes (ΔADC%, and ΔTV%) in these parameters at mid- and post-treatment relative to baseline were calculated and compared between the patients with and without clinical complete response (CR).
Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer.
Insights Imaging
January 2025
Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Bladder cancer is the 10th most common and 13th most deadly cancer worldwide, with urothelial carcinomas being the most common type. Distinguishing between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is essential due to significant differences in management and prognosis. MRI may play an important diagnostic role in this setting.
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