ArticleAbdominal radiology (New York)2022
Comparison of quantitative 3D magnetic resonance cholangiography measurements obtained using three different image acquisition methods.
Article in Abdominal radiology (New York), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 5 citations in OpenAlex.
- Exploring the Role of MRCP+ for Enhancing Detection of High-Grade Strictures in Primary Sclerosing Cholangitis.Journal of clinical medicine · 2025Article
- Quantitative MRCP metrics as imaging biomarkers to differentiate benign from malignant bile duct obstructions.Frontiers in oncology · 2025Article
- Predicting the image quality of respiratory-gated and breath-hold 3D MRCP from the breathing curve: a prospective study.European radiology · 2023Article
- Novel Mathematical Diagnostic Analysis of Malignant Biliary Stenosis Using Magnetic Resonance Cholangiography in Patients Undergoing Pancreaticoduodenectomy.Cancer diagnosis & prognosisArticle
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Authors and funding
4 authors at 1 institution in 1 country.
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Abstract
purposeTo compare quantitative biliary measurements obtained with three different magnetic resonance cholangiopancreatography (MRCP) acquisition methods.
methodsThis retrospective study was IRB-approved. Patients with combinations of clinically indicated 3D FSE MRCP with sensitivity encoding (SENSE), 3D FSE SENSE MRCP with compressed sensing (CS-FSE; acceleration factor 8), and 3D gradient and spin-echo (GRASE) MRCP, acquired between October 2018 and March 2020, were included. The MRCP + Tuning Threshold algorithm (Perspectum Ltd., Oxford, UK) was used to segment 3D biliary models from MRCP data, with multiple metrics quantified from the models. Single measure, two-way, mixed-effects intra-class correlations, Bland-Altman analyses, and Wilcoxon signed-rank tests were used to compare quantitative measurements.
resultsFrom 160 MRCP datasets (25 3D FSE, 67 3D CS-FSE, 68 3D GRASE) in 69 patients, 48 datasets (7 [28%] 3D FSE, 14 [21%] 3D CS-FSE, 27 [40%] 3D GRASE) failed post-processing due to motion artifacts. The remaining 112 MRCP datasets (18 3D FSE, 53 3D CS-FSE, 41 3D GRASE) from 60 patients were included in the analysis. There was good to excellent agreement between 3D FSE and 3D CS-FSE MRCP for diameter of the left and right hepatic ducts, biliary volume, number and length of ducts, and total length of dilations (ICC: 0.83-0.93). The only metrics that exhibited good agreement between 3D FSE and 3D GRASE MRCP were biliary volume (ICC: 0.75) and total number of dilations (ICC: 0.77).
conclusion3D CS-FSE MRCP produces comparable biliary diameter metrics and global duct quantification to 3D FSE MRCP at a significantly reduced acquisition time.
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