Purpose: To evaluate the performance of an automated deep learning method in detecting ascites and subsequently quantifying its volume in patients with liver cirrhosis and ovarian cancer.
Materials And Methods: This retrospective study included contrast-enhanced and non-contrast abdominal-pelvic CT scans of patients with cirrhotic ascites and patients with ovarian cancer from two institutions, National Institutes of Health (NIH) and University of Wisconsin (UofW). The model, trained on The Cancer Genome Atlas Ovarian Cancer dataset (mean age, 60 years ± 11 [s.d.]; 143 female), was tested on two internal (NIH-LC and NIH-OV) and one external dataset (UofW-LC). Its performance was measured by the Dice coefficient, standard deviations, and 95% confidence intervals, focusing on ascites volume in the peritoneal cavity.
Results: On NIH-LC (25 patients; mean age, 59 years ± 14 [s.d.]; 14 male) and NIH-OV (166 patients; mean age, 65 years ± 9 [s.d.]; all female), the model achieved Dice scores of 0.855±0.061 (CI: 0.831-0.878) and 0.826±0.153 (CI: 0.764-0.887), with median volume estimation errors of 19.6% (IQR: 13.2-29.0) and 5.3% (IQR: 2.4-9.7) respectively. On UofW-LC (124 patients; mean age, 46 years ± 12 [s.d.]; 73 female), the model had a Dice score of 0.830±0.107 (CI: 0.798-0.863) and median volume estimation error of 9.7% (IQR: 4.5-15.1). The model showed strong agreement with expert assessments, with values of 0.79, 0.98, and 0.97 across the test sets.
Conclusion: The proposed deep learning method performed well in segmenting and quantifying the volume of ascites in concordance with expert radiologist assessments.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11468649 | PMC |
Clin Oral Investig
January 2025
Department of Behavioral and Community Dentistry, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, P.O. Box 450, Gothenburg, SE-40530, Sweden.
Objective: To investigate if changes in body mass index (BMI) result in changes of the mandibular trabecular bone structure.
Materials And Methods: Females (18-35 years at baseline, mean BMI 42,3) were followed from before (n = 117) until two years (n = 66) after obesity treatment (medical or surgical). The mandibular bone trabeculation was classified as sparse, dense, or mixed on intraoral radiographs (Lindh's index).
J Nephrol
January 2025
School of Life and Medical Sciences, University of Hertfordshire, College Lane Campus, Hatfield, UK.
Eur J Trauma Emerg Surg
January 2025
Department of Neurology, Haaglanden Medical Center, PO Box 432, 2501 CK, The Hague, The Netherlands.
Background And Importance: Traumatic intracranial hemorrhage (tICH) after mild traumatic brain injury (mTBI) is not uncommon in the elderly. Often, these patients are admitted to the hospital for observation. The necessity of admission in the absence of clinically important intracranial injuries is however unclear.
View Article and Find Full Text PDFPurpose: Heart failure (HF) is a disease that leads to approximately 300,000 fatalities annually in Europe and 250,000 deaths each year in the United States. Type 2 Diabetes Mellitus (T2DM) is a significant risk factor for HF, and testing for N-terminal (NT)-pro hormone BNP (NT-proBNP) can aid in early detection of HF in T2DM patients. We therefore developed and validated the HFriskT2DM-HScore, an algorithm to predict the risk of HF in T2DM patients, so guiding NT-proBNP investigation in a primary care setting.
View Article and Find Full Text PDFBreast Cancer Res Treat
January 2025
Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!