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Purpose: To assess the impact of prostate MRI image quality by means of the Prostate Imaging Quality (PI-QUAL) score, on the identification of extraprostatic extension of disease (EPE), predicted using the EPE Grade Score, Likert Scale Score (LSS) and a clinical nomogram (MSKCCn).
Methods: We retrospectively included 105 patients with multiparametric prostate MRI prior to prostatectomy. Two radiologists evaluated image quality using PI-QUAL (≥4 was considered high quality) in consensus. All cases were also scored using the EPE Grade, the LSS, and the MSKCCn (dichotomized). Inter-rater reproducibility for each score was also assessed. Accuracy was calculated for the entire population and by image quality, considering two thresholds for EPE Grade (≥2 and = 3) and LSS (≥3 and ≥ 4) and using McNemar's test for comparison.
Results: Overall, 66 scans achieved high quality. The accuracy of EPE Grade ranged from 0.695 to 0.743, while LSS achieved values between 0.705 and 0.733. Overall sensitivity for the radiological scores (range = 0.235-0.529) was low irrespective of the PI-QUAL score, while specificity was higher (0.775-0.986). The MSKCCn achieved an AUC of 0.76, outperforming EPE Grade (=3 threshold) in studies with suboptimal image quality (0.821 vs 0.564, p = 0.016). EPE Grade (=3 threshold) accuracy was also better in high image quality studies (0.849 vs 0.564, p = 0.001). Reproducibility was good to excellent overall (95 % Confidence Interval range = 0.782-0.924).
Conclusion: Assessing image quality by means of PI-QUAL is helpful in the evaluation of EPE, as a scan of low quality makes its performance drop compared to clinical staging tools.
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http://dx.doi.org/10.1016/j.ejrad.2023.110973 | DOI Listing |
Stroke
September 2025
Department of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, China (H.Z., K.H., Q.G.).
Background: Poststroke cognitive impairment (PSCI) affects 30% to 50% of stroke survivors, severely impacting functional outcomes and quality of life. This study uses functional near-infrared spectroscopy (fNIRS) to assess task-evoked brain activation and its potential for stratifying the severity in patients with PSCI.
Method: A cross-sectional study was conducted at Nanchong Central Hospital between June 2023 and April 2024.
J Orthop Sports Med
August 2025
Department of Translational Research, College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, California, 91766, USA.
Rotator cuff tendinopathy is a common cause of shoulder pain and dysfunction, presenting in two primary forms: calcific and non-calcific. These subtypes differ significantly in their pathophysiology, clinical manifestations, and natural history, necessitating tailored diagnostic and therapeutic approaches. This review delineates the clinical presentations of calcific rotator cuff tendinopathy (RCCT), characterized by distinct pre-calcific, calcific, and post-calcific stages, and contrasts them with the more insidious, degenerative course of non-calcific rotator cuff tendinopathy.
View Article and Find Full Text PDFRadiol Adv
September 2024
Department of Radiology, Northwestern University and Northwestern Medicine, Chicago, IL, 60611, United States.
Background: In clinical practice, digital subtraction angiography (DSA) often suffers from misregistration artifact resulting from voluntary, respiratory, and cardiac motion during acquisition. Most prior efforts to register the background DSA mask to subsequent postcontrast images rely on key point registration using iterative optimization, which has limited real-time application.
Purpose: Leveraging state-of-the-art, unsupervised deep learning, we aim to develop a fast, deformable registration model to substantially reduce DSA misregistration in craniocervical angiography without compromising spatial resolution or introducing new artifacts.
Comput Struct Biotechnol J
August 2025
Institut de Recherche en Cancérologie de Montpellier (IRCM), Équipe Labellisée Ligue Contre le Cancer, INSERM U1194, Université de Montpellier, Institut régional du Cancer de Montpellier (ICM), Montpellier, France.
Digital twins (DTs) are emerging tools for simulating and optimizing therapeutic protocols in personalized nuclear medicine. In this paper, we present a modular pipeline for constructing patient-specific DTs aimed at assessing and improving dosimetry protocols in PRRT such as therapy. The pipeline integrates three components: (i) an anatomical DT, generated by registering patient CT scans with an anthropomorphic model; (ii) a functional DT, based on a physiologically-based pharmacokinetic (PBPK) model created in SimBiology; and (iii) a virtual clinical trial module using GATE to simulate particle transport, image simulation, and absorbed dose distribution.
View Article and Find Full Text PDFJB JS Open Access
September 2025
Department of Orthopaedic Surgery, St. Luke's University Health Network, Bethlehem, Pennsylvania.
Background: The use of artificial intelligence platforms by medical residents as an educational resource is increasing. Within orthopaedic surgery, older Chat Generative Pre-trained Transformer (ChatGPT) models performed worse than resident physicians on practice examinations and rarely answered questions with images correctly. The newer ChatGPT-4o was designed to improve these deficiencies but has not been evaluated.
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