Evidence map›Paper›PMID 42534368›Full record

ArticleWorld journal of radiology2026

Computed tomography derived morphomics in the prediction of long-term outcomes in acute pancreatitis.

Sahil Shet, Orla Cliona O'Shea, Ludolf Gavin Arthur De Kock, Eid Kakish, Ronan James Lee, Naomi Ni Chleirigh, Evan O'Broin, David John Ryan, Michael Martin Maher

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Article in World journal of radiology, 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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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Sahil ShetDepartment of Radiology, School of Medicine, University College Cork, Cork T12 K8AF, Ireland.
Orla Cliona O'SheaSchool of Medicine, University College Cork, Cork T12 K8AF, Ireland.
Ludolf Gavin Arthur De KockDepartment of Radiology, School of Medicine, University College Cork, Cork T12 K8AF, Ireland.
Eid KakishDepartment of Radiology, School of Medicine, University College Cork, Cork T12 K8AF, Ireland.
Ronan James LeeDepartment of Radiology, School of Medicine, University College Cork, Cork T12 K8AF, Ireland.
Naomi Ni ChleirighDepartment of Radiology, Cork University Hospital, Cork T12 DFK4, Ireland.
Evan O'BroinSchool of Medicine, University College Cork, Cork T12 K8AF, Ireland.
David John RyanDepartment of Radiology, School of Medicine, University College Cork, Cork T12 K8AF, Ireland.
Michael Martin MaherDepartment of Radiology, School of Medicine, University College Cork, Cork T12 K8AF, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute pancreatitis is a common abdominal pathology with significant morbidity and mortality in select patients. Currently, prediction of outcome and prognosis in patients with acute pancreatitis is based on a variety of indices, scores, and criteria calculated from biochemical, clinical, and imaging parameters, but all currently available predictors of outcome have limitations. Analytic morphomics, a quantitative technique that assesses body composition from cross-sectional imaging, may offer a novel approach to outcome prediction.

aimTo evaluate whether analytic morphomics-derived parameters can predict recurrence and mortality after an index episode of acute pancreatitis.

methodsFollowing ethical approval, a retrospective single-centre study was conducted at Cork University Hospital. Adult patients presenting with acute pancreatitis between January 2012 and December 2013 were included and followed for 10 years. Patients with pancreatic malignancy, equivocal diagnoses, or age < 18 years were excluded. Cases of acute pancreatitis were classified as acute interstitial oedematous pancreatitis or necrotising pancreatitis. Demographic, biochemical, and clinical data were collected, including the modified Glasgow Imrie severity score. Computed tomography examinations were analysed using CoreSlicer for semi-automated segmentation of skeletal muscle and adipose tissue at the L3 vertebral level. Statistical analysis was performed using Microsoft Excel and Jamovi, including the Mann-Whitney

resultsSeventy-two patients were included with a median modified Glasgow Imrie severity score of 2. Wall muscle (WM) density correlated inversely with disease severity [WM density (Hounsfield units):

conclusionSkeletal muscle quality and SCF are protective factors in acute pancreatitis. Integration of morphomics with existing severity scores may enhance prognostication. Larger studies are needed to validate these findings.

Indexed as

Acute pancreatitisAnalytic morphomicsBody compositionComputed tomographyDisease severityLong-term outcomesMortalitySkeletal muscle densitySubcutaneous fat

Identifiers

PMID42534368
PMCPMC13420184

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