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Validation of Clinical Dynamic Contrast-Enhanced Magnetic Resonance Imaging Perfusion Modeling and Neoadjuvant Chemotherapy Response Prediction in Breast Cancer Using FDG and Cu-DOTA-Trastuzumab Positron Emission Tomography Studies.
JCO Clin Cancer Inform
January 2025
SimBioSys Inc, Chicago, IL.
Purpose: Perfusion modeling presents significant opportunities for imaging biomarker development in breast cancer but has historically been held back by the need for data beyond the clinical standard of care (SoC) and uncertainty in the interpretability of results. We aimed to design a perfusion model applicable to breast cancer SoC dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) series with results stable to low temporal resolution imaging, comparable with published results using full-resolution DCE-MRI, and correlative with orthogonal imaging modalities indicative of biophysical markers.
Methods: Subsampled high-temporal-resolution DCE-MRI series were run through our perfusion model and resulting fits were compared for consistency.
The Role of Artificial Intelligence in Predicting Optic Neuritis Subtypes From Ocular Fundus Photographs.
J Neuroophthalmol
December 2024
Division of Ophthalmology (EB-S, AS, AA-A, AS-B, DW, SS, FC), Department of Surgery, University of Calgary, Calgary, Canada; Department of Biomedical Engineering (CN), University of Calgary, Calgary, Canada; Departments of Neurology (LBDL) and Ophthalmology (LBDL), University of Michigan, Ann Arbor, Michigan; and Department of Clinical Neurosciences (SS, FC), University of Calgary, Calgary, Canada.
Background: Optic neuritis (ON) is a complex clinical syndrome that has diverse etiologies and treatments based on its subtypes. Notably, ON associated with multiple sclerosis (MS ON) has a good prognosis for recovery irrespective of treatment, whereas ON associated with other conditions including neuromyelitis optica spectrum disorders or myelin oligodendrocyte glycoprotein antibody-associated disease is often associated with less favorable outcomes. Delay in treatment of these non-MS ON subtypes can lead to irreversible vision loss.
View Article and Find Full Text PDFExtraction and Characterization of Inulin-Like Fructans from Hydroponically Grown Stevia rebaudiana Roots for Food Applications.
Plant Foods Hum Nutr
January 2025
Departamento de Farmácia, Programa de Pós-Graduação em Ciências Farmacêuticas, Laboratório de Biotecnologia de Produtos Naturais e Sintéticos (LABIPROS), Universidade Estadual de Maringá, Av. Colombo 5790, Maringá, Paraná, 87020-900, Brazil.
Stevia rebaudiana is a plant native to South America known for producing steviol glycosides and fructans used in low-calorie and functional foods. This study aimed to cultivate and isolate inulin from hydroponically grown S. rebaudiana roots.
View Article and Find Full Text PDFAltered Intracerebellar Functional Connectivity in Friedreich's Ataxia: A Graph-Theory Functional MRI Study.
Cerebellum
January 2025
Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
Historically, Friedreich's Ataxia (FRDA) has been linked to a relatively preserved cerebellar cortex. Recent advances in neuroimaging have revealed altered cerebello-cerebral functional connectivity (FC), but the extent of intra-cerebellar FC changes and their impact on cognition remains unclear. This study investigates intra-cerebellar FC alterations and their cognitive implications in FRDA.
View Article and Find Full Text PDFDeep Learning to Simulate Contrast-Enhanced MRI for Evaluating Suspected Prostate Cancer.
Radiology
January 2025
From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.).
Background Multiparametric MRI, including contrast-enhanced sequences, is recommended for evaluating suspected prostate cancer, but concerns have been raised regarding potential contrast agent accumulation and toxicity. Purpose To evaluate the feasibility of generating simulated contrast-enhanced MRI from noncontrast MRI sequences using deep learning and to explore their potential value for assessing clinically significant prostate cancer using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.
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