Evidence map›Paper›PMID 42440114›Full record

ArticleAbdominal radiology (New York)2026

Deep learning-based respiratory-triggered magnetic resonance cholangiopancreatography: comparison with conventional respiratory-triggered and breath-hold magnetic resonance cholangiopancreatography.

Rae Rim Ryu, Eun Sun Lee, Hyun Jeong Park, Min Ju Kim, Elisabeth Weiland, Dominik Nickel, Jae Kon Sung

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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Rae Rim RyuDepartment of Radiology, Chung-Ang University Hospital, Seoul, Republic of Korea.
Eun Sun LeeDepartment of Radiology, Chung-Ang University Hospital, Seoul, Republic of Korea.
Hyun Jeong ParkDepartment of Radiology, Chung-Ang University Hospital, Seoul, Republic of Korea.
Min Ju KimDepartment of Radiology, Chung-Ang University Hospital, Seoul, Republic of Korea. mjkim@cauhs.or.kr.ORCID https://orcid.org/0000-0002-5431-6321
Elisabeth WeilandResearch & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany.
Dominik NickelResearch & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany.
Jae Kon SungDepartment of MR Engineering, Siemens Healthineers AG, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate whether deep learning-based respiratory-triggered (DL) 3D magnetic resonance cholangiopancreatography (MRCP) improves acquisition efficiency while providing similar qualitative image assessment results to conventional respiratory-triggered (CON) and breath-hold compressed sensing (BH-CS) MRCP.

methodsThis retrospective study included 116 patients who underwent DL, CON, and BH-CS MRCP. Relative contrast (RC) of the common bile duct (CBD) was quantitatively analyzed. Two reviewers qualitatively assessed ductal visibility (10 segments), background suppression, motion artifacts, overall image quality, and conspicuity of pancreatic cystic lesions. Acquisition efficiency of respiratory-triggered sequences was compared based on the number of effective respiratory cycles.

resultsInterobserver agreement was substantial to almost perfect (κ = 0.73-0.94). RC was significantly higher with DL (0.87 ± 0.07) and BH-CS (0.91 ± 0.08) compared with CON (0.83 ± 0.08; p < 0.01). Visibility of the CBD and common hepatic duct did not differ significantly among sequences, whereas DL and CON showed significantly higher visibility of peripheral intrahepatic and pancreatic duct segments than BH-CS (all p < 0.01). Overall image quality scores were significantly higher for DL and CON than for BH-CS for both readers (mean scores, 3.4-3.5 vs. 2.8). Pancreatic cystic lesions ≥ 1 cm were detected in 14.7% of examinations with no significant difference in detection rates among sequences. For lesion conspicuity, reader 1 found no significant between-sequence differences, whereas reader 2 reported higher conspicuity scores for BH-CS than for DL (adjusted P = 0.01). DL required fewer effective respiratory cycles than CON (19 vs. 60 cycles), corresponding to an approximately 68% reduction in respiratory-triggered acquisition burden.

conclusionDL-based respiratory-triggered 3D MRCP demonstrated improved acquisition efficiency with fewer effective respiratory cycles than CON. No significant differences were detected between DL and CON in qualitative image assessment, while both respiratory-triggered techniques showed higher peripheral duct visibility than BH-CS.

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Deep learningMagnetic resonance cholangiopancreatographyTime factorsWorkflow efficiency

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.