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Purpose: To assess the diagnostic performance of F-flupiridaz positron emission tomography (PET) myocardial perfusion imaging (MPI) for coronary artery disease detection using total perfusion deficit (TPD), an automated metric of combined disease extent and severity.
Methods: Flurpiridaz relative perfusion images and quantitative coronary angiography data from the initial phase III trial were evaluated using receiver operating characteristic analysis at separate endpoints of ≥70% stenosis and ≥50% stenosis, to determine the diagnostic performance of TPD at per-patient (global LV) and per-vessel levels. TPD results at both endpoints were compared with the performance of visual scores and defect extent values available from two previous publications.
Results: Using a normal perfusion database that was created with the data of 25 patients from the flurpiridaz trial population, TPD was calculated in the remaining 729 trial patients. At the threshold of ≥70% stenosis, TPD was observed to have similar (P ≥ .05) per-patient diagnostic performance (74% accuracy) to visual scoring from previous publications (75%, 71%), as well as defect extent (72%). At the per-vessel level, the TPD achieved similar performance to defect extent in the left anterior descending artery (LAD) and left circumflex artery (LCx) (79%, 74% vs 80%, 72% accuracy) with slightly higher accuracy in the right coronary artery (RCA) (77% vs 72%, P = .03), and similar performance to visual scoring in the LAD and RCA (77, 79% vs 76%, 76% accuracy) with marginally lower performance in the LCx (74% vs 79%, P = .03). Similar results were observed at the ≥50% obstructive disease endpoint.
Conclusions: Automated TPD demonstrated similar diagnostic performance for global and regional flurpiridaz PET MPI, respectively, to visual scoring and defect extent quantification.
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http://dx.doi.org/10.1016/j.nuclcard.2025.102266 | DOI Listing |
BJOG
September 2025
Department of Obstetrics and Gynaecology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Objective: To estimate the effect on healthcare resource use after introducing the World Health Organization diagnostic criteria (WHO-2013) for gestational diabetes mellitus (GDM) compared to former criteria in Sweden (SWE-GDM).
Design: A cost-analysis alongside the Changing Diagnostic Criteria for Gestational Diabetes (CDC4G) randomised controlled trial.
Setting: Sweden, with risk-factor based screening for GDM.
Behav Res Methods
September 2025
Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Cybernetics, Prague, Czech Republic.
Automatic markerless estimation of infant posture and motion from ordinary videos carries great potential for movement studies "in the wild", facilitating understanding of motor development and massively increasing the chances of early diagnosis of disorders. There has been a rapid development of human pose estimation methods in computer vision, thanks to advances in deep learning and machine learning. However, these methods are trained on datasets that feature adults in different contexts.
View Article and Find Full Text PDFMAGMA
September 2025
Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3585CX, Utrecht, The Netherlands.
Objective: Within gradient-spoiled transient-state MR sequences like Magnetic Resonance Fingerprinting or Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT), it is examined whether an optimized RF phase modulation can help to improve the precision of the resulting relaxometry maps.
Methods: Using a Cramer-Rao based method called BLAKJac, optimized sequences of RF pulses have been generated for two scenarios (amplitude-only modulation and amplitude + phase modulation) and for several conditions. These sequences have been tested on a phantom, a healthy human brain and a healthy human leg, to reconstruct parametric maps ( and ) as well as their standard deviations.
Neurol Sci
September 2025
Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
The rapid evolution of digital tools in recent years after COVID-19 pandemic has transformed diagnostic and therapeutic practice in neurology. This shift has highlighted the urgent need to integrate digital competencies into the training of future specialists. Key innovations such as telemedicine, artificial intelligence, and wearable health technologies have become central to improving healthcare delivery and accessibility.
View Article and Find Full Text PDFJ Cancer Res Clin Oncol
September 2025
Division of Gastroenterology, Department of Medicine, Asahikawa Medical University, Asahikawa, Japan.
Purpose: Next-generation sequencing (NGS) has revolutionized cancer treatment by enabling comprehensive cancer genomic profiling (CGP) to guide genotype-directed therapies. While several prospective trials have demonstrated varying outcomes with CGP in patients with advanced solid tumors, its clinical utility in colorectal cancer (CRC) remains to be evaluated.
Methods: We conducted a prospective observational study of CGP in our hospital between September 2019 and March 2024.