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Preservation of Bilateral Corticospinal Projections from Injured Hemisphere After Perinatal Stroke.
Brain Sci
January 2025
Waisman Center, University of Wisconsin-Madison, Madison, WI 53706, USA.
Background: Perinatal brain injury is a leading cause of developmental disabilities, including cerebral palsy. However, further work is needed to understand early brain development in the presence of brain injury. In this case report, we examine the longitudinal neuromotor development of a term infant following a significant loss of right-hemispheric brain tissue due to a unilateral ischemic stroke.
View Article and Find Full Text PDFDiffusion Tensor Imaging as Neurologic Predictor in Patients Affected by Traumatic Brain Injury: Scoping Review.
Brain Sci
January 2025
CVJ Operative Unit, CVJ Research Center Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy.
: Diffusion tensor imaging (DTI), a variant of Diffusion Weighted Imaging (DWI), enables a neuroanatomical microscopic-like examination of the brain, which can detect brain damage using physical parameters. DTI's application to traumatic brain injury (TBI) has the potential to reveal radiological features that can assist in predicting the clinical outcomes of these patients. What is the ongoing role of DTI in detecting brain alterations and predicting neurological outcomes in patients with moderate to severe traumatic brain injury and/or diffuse axonal injury? : A scoping review of the PubMed, Scopus, EMBASE, and Cochrane databases was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.
View Article and Find Full Text PDFRole of Artificial Intelligence in MRI-Based Rectal Cancer Staging: A Systematic Review.
Cureus
December 2024
Internal Medicine, Belgaum Institute of Medical Science, Belgaum, IND.
Several studies explored the application of artificial intelligence (AI) in magnetic resonance imaging (MRI)-based rectal cancer (RC) staging, but a comprehensive evaluation remains lacking. This systematic review aims to review the performance of AI models in MRI-based RC staging. PubMed and Embase were searched from the inception of the database till October 2024 without any language and year restrictions.
View Article and Find Full Text PDFHigh performance of the diffusion magnetic resonance imaging biomarker diffusion-derived 'vessel density' (DDVD) for separating placentas associated with pre-eclampsia from placentas in normal pregnancy.
Quant Imaging Med Surg
January 2025
Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.
Background: Diffusion-derived 'vessel density' (DDVD) is a surrogate of the area of micro-vessels per unit tissue. DDVD is calculated according to: DDVD (b0b50) = Sb0/ROIarea0 - Sb50/ROIarea50, where Sb0 and Sb50 refer to the tissue signal when is 0 or 50 s/mm. Due to the complexity of pre-eclampsia (PE), even a combination of risk factors and available tests cannot accurately diagnose or predict PE.
View Article and Find Full Text PDFDevelopment and validation of a multi-parametric MRI deep-learning model for preoperative lymphovascular invasion evaluation in rectal cancer.
Quant Imaging Med Surg
January 2025
Department of Magnetic Resonance Imaging Diagnostic, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Background: Lymphovascular invasion (LVI) is an independent prognostic factor for patients with rectal cancer (RC). Recent studies have shown that deep learning (DL)-based magnetic resonance imaging (MRI) has potential in evaluating the treatment response of RC patients, but the role of MRI-based DL in assessing RC LVI remains unclear. This study sought to develop and validate a DL model to evaluate the LVI status of RC patients preoperatively based on MRI, and to test its performance at an external center.
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