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Aim was to evaluate the influence of different quantum iterative reconstruction (QIR) levels on the image quality of femoral photon-counting CT angiographies (PCD-CTA).Ultra-high resolution PCD-CTA were obtained from both extremities of five extracorporeally-perfused cadavers using constant tube voltage and maximum radiation dose (71.2 ± 11.0 mGy). Images were reconstructed with three kernels (Bv48, Bv60, Bv76) and the four available levels of QIR. Signal attenuation in the arterial lumen, muscle, and fat were measured. Contrast-to-noise ratios (CNR) and blurring scores were calculated for objective assessment. Six radiologists evaluated the subjective image quality using a pairwise comparison tool.Higher QIR level resulted in a decisive image noise reduction, especially with sharper convolution kernels (Bv60: Q1 11.5 ± 6.3 HU vs. Q4 8.4 ± 2.6 HU; p < 0.001). Largest improvement of CNR was recorded with ultra-sharp reconstructions (Bv76: Q1 20.2 ± 4.4 vs. Q4 28.0 ± 3.5; p < 0.001). Blurring decreased with higher QIR levels for soft Bv48, remained constant for medium Bv60, and increased for sharp Bv76 reconstructions. Subjective QIR level preference varied kernel depending, preferred combinations were: Bv48/Q4, Bv60/Q2, Bv76/Q3. Interrater agreement was excellent.Sharp kernels benefited most from noise reduction of higher QIR levels in lower extremity PCD-CTA. In sum, QIR level 3 provided the best objective and subjective image quality results.
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http://dx.doi.org/10.1038/s41598-024-79188-3 | 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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