Objective: The objective of this study was to investigate impact of prostate volume variations on prostate-specific antigen density (PSAD) and patient eligibility for active surveillance (AS).
Methods: Prostate volume and PSAD were calculated for 46 patients with prostate cancer in AS who underwent prostate magnetic resonance imaging and transrectal ultrasound (TRUS). Manual method and 2 semiautomated methods for prostate segmentation (3D-SLICER and OsiriX) were used for MR volumetry.
Results: Magnetic resonance volumetric methods showed very good agreement (intraclass correlation coefficient, 0.98). The concordance correlation coefficient was higher among MR volumetry methods (0.971-0.998) than between TRUS and MR volumetry (0.849-0.863). The variation in PSAD estimated by TRUS versus magnetic resonance imaging was higher in large prostates (r = 0.327, P = 0.027). Transrectal ultrasonography volumetry may improperly classify 20% of patients as eligible for AS with PSAD greater than 0.15 threshold.
Conclusions: Although clinically used TRUS reliably estimates PSAD, it may misclassify some patients who are not eligible for AS based on PSAD criteria. Magnetic resonance-based volumetry should be considered for a more reliable PSAD calculation.
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http://dx.doi.org/10.1097/RCT.0b013e318296af5f | DOI Listing |
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
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View Article and Find Full Text PDFBioinformatics
January 2025
Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, W12 0NN, United Kingdom.
Unlabelled: Metabolomics extensively utilizes Nuclear Magnetic Resonance (NMR) spectroscopy due to its excellent reproducibility and high throughput. Both one-dimensional (1D) and two-dimensional (2D) NMR spectra provide crucial information for metabolite annotation and quantification, yet present complex overlapping patterns which may require sophisticated machine learning algorithms to decipher. Unfortunately, the limited availability of labeled spectra can hamper application of machine learning, especially deep learning algorithms which require large amounts of labelled data.
View Article and Find Full Text PDFRadiol Med
January 2025
Medical Science Research Center, Korea University College of Medicine, Seoul, Republic of Korea.
Purpose: To compare the performance of ultrafast MRI with standard MRI in classifying histological factors and subtypes of invasive breast cancer among radiologists with varying experience.
Methods: From October 2021 to November 2022, this prospective study enrolled 225 participants with 233 breast cancers before treatment (NCT06104189 at clinicaltrials.gov).
MAGMA
January 2025
Imaging Physics, Fraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Straße 2, 28359, Bremen, Germany.
Objectives: Caffeine, a known neurostimulant and adenosine antagonist, affects brain physiology by decreasing cerebral blood flow. It interacts with adenosine receptors to induce vasoconstriction, potentially disrupting brain homeostasis. However, the impact of caffeine on blood-brain barrier (BBB) permeability to water remains underexplored.
View Article and Find Full Text PDFClin Rheumatol
January 2025
Department of Rheumatology and Immunology, The First Medical Center, People Liberation Army General Hospital, Beijing, 100853, China.
To study the clinical, imaging, and computed tomography (CT)-guided biopsy pathology of patients with infectious sacroiliitis (ISI). We retrospectively analysed 135 patients diagnosed with ISI between 2008 and 2020, comprehensively evaluating clinical characteristics, laboratory test outcomes, pathological examination results, and magnetic resonance images (MRI). Among the 135 patients with ISI, 90 (66.
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