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Objectives: To investigate the optimal imaging protocols for enhanced chest CT to achieve good image quality and diagnostic performance with a lower radiation dose.
Materials And Methods: This IRB-approved study included both phantoms and patients. Two phantoms were scanned using 4 scanning modes. Images in each group were reconstructed using adaptive statistical iterative reconstruction-V (ASiR-V) at three strength levels of 40%, 60%, and 80%, denoted A1-3-D1-3, respectively with 1-3 representing the three ASiR-V levels. The image quality and radiation dose were evaluated to obtain the best imaging mode. 48 patients underwent contrast-enhanced standard dose CT (SDCT, protocol A) and low-dose CT (LDCT, protocol D) of the chest for follow-up. The image quality, radiation dose, and volume measurements of the left lung, right lung, and trachea using an AI-based software were compared.
Results: In the phantom study, D2 protocol which had the lowest dose, was selected as the optimal imaging protocol for enhanced chest CT. Compared with SDCT, LDCT reduced the radiation dose by 45% compared to SDCT. Images in LDCT with ASiR-V60% had similar noise as the standard SDCT images with the standard ASiR-V40%, but they had higher SNRs and CNRs. In addition, the volumes of the left lung, right lung, and bronchus did not significantly differ between the two groups.
Conclusion: The combination of Auto-kV prescription and ODM with ASiR-V60% in contrast-enhanced chest CT can achieve individualized low dose scanning with satisfactory image quality and diagnostic accuracy.
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http://dx.doi.org/10.1016/j.ejmp.2025.104924 | 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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