Objective: The purpose of this study was to evaluate automated CT volumetry in the assessment of living-donor livers for transplant and to compare this technique with software-aided interactive volumetry and manual volumetry.
Materials And Methods: Hepatic CT scans of 18 consecutively registered prospective liver donors were obtained under a liver transplant protocol. Automated liver volumetry was developed on the basis of 3D active-contour segmentation. To establish reference standard liver volumes, a radiologist manually traced the contour of the liver on each CT slice. We compared the results obtained with automated and interactive volumetry with those obtained with the reference standard for this study, manual volumetry.
Results: The average interactive liver volume was 1553 ± 343 cm(3), and the average automated liver volume was 1520 ± 378 cm(3). The average manual volume was 1486 ± 343 cm(3). Both interactive and automated volumetric results had excellent agreement with manual volumetric results (intraclass correlation coefficients, 0.96 and 0.94). The average user time for automated volumetry was 0.57 ± 0.06 min/case, whereas those for interactive and manual volumetry were 27.3 ± 4.6 and 39.4 ± 5.5 min/case, the difference being statistically significant (p < 0.05).
Conclusion: Both interactive and automated volumetry are accurate for measuring liver volume with CT, but automated volumetry is substantially more efficient.
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http://dx.doi.org/10.2214/AJR.10.5958 | DOI Listing |
J Epilepsy Res
December 2024
Department of Neurology, Seoul National University College of Medicine, Seoul, Korea.
Background And Purpose: The magnetic resonance images (MRIs) ability of lesion detection in epilepsy is crucial for a diagnosis and surgical outcome. Using automated artificial intelligence (AI)-based tools for measuring cortical thickness and brain volume originally developed for dementia, we aimed to identify whether it could lateralize epilepsy with normal MRIs.
Methods: Non-lesional 3-Tesla MRIs of 428 patients diagnosed with focal epilepsy, based on semiology and electroencephalography findings, were analyzed.
J Neurol
December 2024
Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Stockholm, Sweden.
Predicting amyloid status is crucial in light of upcoming disease-modifying therapies and the need to identify treatment-eligible patients with Alzheimer's disease. In our study, we aimed to predict CSF-amyloid status and eligibility for anti-amyloid treatment in a memory clinic by (I) comparing the performance of visual/automated rating scales and MRI volumetric analysis and (II) combining MRI volumetric data with neuropsychological tests and APOE4 status. Two hundred ninety patients underwent a comprehensive assessment.
View Article and Find Full Text PDFWorld J Radiol
November 2024
Department of Radiology, Oita University Faculty of Medicine, Yufu 879-5593, Oita, Japan.
Background: Several studies found that early pancreatic atrophy detected by computed tomography (CT) within 6 months was associated with a high incidence of diabetes in patients with type-1 autoimmune pancreatitis (AIP) receiving steroid therapy; however, no long-term follow-up studies have been performed.
Aim: To investigate pancreatic volume (PV) changes using three dimensional (3D)-CT volumetry and their relationship with IgG4 and diabetes in patients with AIP.
Methods: This retrospective study included 33 patients with type-1 AIP receiving steroid therapy.
NPJ Digit Med
November 2024
Heart Disease Prevention Program, Division of Cardiology, University of California Irvine, Irvine, CA, 92697, USA.
Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.
View Article and Find Full Text PDFJ Vet Intern Med
December 2024
Division of General and Interventional Radiology and Neuroradiology, Department of Radiology, Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland.
Background: Lesions causing refractory epilepsy, often associated with temporal lobe epilepsy (TLE), can be undetectable on standard magnetic resonance imaging (MRI) in dogs. Automated brain volumetry, widely used in human medicine, can now be applied in veterinary medicine because of the availability of brain atlases.
Objectives: This study aimed to develop an automatic volumetry method, translate the outcomes into the assessment of temporal lobe volumes in dogs with idiopathic epilepsy, and correlate the results with the electroencephalography (EEG) data of epileptiform discharges (EDs).
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