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Background: Biparametric (bp) magnetic resonance imaging (MRI) could be an alternative MRI for the detection of the clinically significant prostate cancer (csPCa).
Purpose: To compare the accuracies of prostate cancer detection and localization between prebiopsy bpMRI and postbiopsy multiparametric MRI (mpMRI) taken on different days, using radical prostatectomy specimens as the reference standards.
Material And Methods: Data of 41 total consecutive patients who underwent the following examinations and procedures between September 2015 and March 2017 were collected: (1) magnetic resonance- and/or ultrasonography-guided biopsy after bpMRI; (2) postbiopsy mpMRI; and (3) radical prostatectomy with csPCa. Two radiologists scored suspected lesions on bpMRI and mpMRI independently using Prostate Imaging Reporting and Data System version 2. The diagnostic accuracy of detecting csPCa and the Dice similarity coefficient were obtained. Apparent diffusion coefficient (ADC) ratios were also obtained for quantitative comparison between bpMRI and mpMRI.
Results: Diagnostic accuracies on bpMRI and mpMRI were 0.83 and 0.82 for reader 1; 0.80 and 0.82 for reader 2. There are no significantly different values of diagnostic sensitivities or specificities between the readers or between MRI protocols. Intra-observer Dice similarity coefficient was significantly lower in reader 2, compared to that in reader 1 between the two MRI protocols. The range of mean ADC ratio was 0.281-0.635. There was no statistically significant difference in the ADC ratio between bpMRI and mpMRI.
Conclusions: Diagnostic performance of bpMRI without dynamic contrast enhancement MRI is not significantly different from mpMRI with dynamic contrast enhancement MRI in the detection of csPCa.
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http://dx.doi.org/10.1016/j.prnil.2019.12.004 | DOI Listing |
JAMA Psychiatry
September 2025
School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.
Importance: Cannabis is the most commonly used illicit drug, with 10% to 30% of regular users developing cannabis use disorder (CUD), a condition linked to altered hippocampal integrity. Evidence suggests high-intensity interval training (HIIT) enhances hippocampal structure and function, with this form of physical exercise potentially mitigating CUD-related cognitive and mental health impairments.
Objective: To determine the impact of a 12-week HIIT intervention on hippocampal integrity (ie, structure, connectivity, biochemistry) compared with 12 weeks of strength and resistance (SR) training in CUD.
JAMA Dermatol
September 2025
Dermatology Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
JAMA
September 2025
Division of Surgery and Interventional Science, UCL, London, United Kingdom.
Importance: Multiparametric magnetic resonance imaging (MRI), with or without prostate biopsy, has become the standard of care for diagnosing clinically significant prostate cancer. Resource capacity limits widespread adoption. Biparametric MRI, which omits the gadolinium contrast sequence, is a shorter and cheaper alternative offering time-saving capacity gains for health systems globally.
View Article and Find Full Text PDFCereb Cortex
August 2025
Section of Brain Function Information, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan.
This study aimed to identify brain activity modulations associated with different types of visual tracking using advanced functional magnetic resonance imaging techniques developed by the Human Connectome Project (HCP) consortium. Magnetic resonance imaging data were collected from 27 healthy volunteers using a 3-T scanner. During a single run, participants either fixated on a stationary visual target (fixation block) or tracked a smoothly moving or jumping target (smooth or saccadic tracking blocks), alternating across blocks.
View Article and Find Full Text PDFCereb Cortex
August 2025
The Clinical Hospital of Chengdu Brain Sciences Institute, University of Electronic Sciences and Technology of China (UESTC), 2006 Xiyuan Avenue, West Hi Tech Zone, 611731, Chengdu, China.
This commentary reflects three decades of interaction between the Cuban neuroinformatics tradition and the statistical parametric mapping (SPM) framework. From the early development of neurometrics in Cuba to global initiatives like the Global Brain Consortium, our trajectory has paralleled and intersected with that of SPM. We highlight shared commitments to generative modeling, Bayesian inference, and population-level brain mapping, as shaped through collaborations, workshops, and joint theoretical work with Karl Friston and his group.
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