Evidence map›Paper›PMID 38902394›Full record

ArticleInsights into imaging2024

Radiomics models of contrast-enhanced computed tomography for predicting the activity and prognosis of acute pancreatitis.

Ning Jun Yu, Xing Hui Li, Chao Liu, Chao Chen, Wen Han Xu, Chao Chen, Yong Chen, Ting Ting Liu, Tian Wu Chen, Xiao Ming Zhang

Abstract read
In one paragraph

Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Ning Jun Yu *Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Xing Hui Li *Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Chao LiuMedical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Chao ChenDepartment of Radiology, The Second Clinical Medical College of North Sichuan Medical College Nanchong Central Hospital, Nanchong, Sichuan, China.
Wen Han XuMedical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Chao ChenMedical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Yong ChenDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ting Ting LiuMedical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Tian Wu ChenMedical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China.
Xiao Ming ZhangMedical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, No.1 South Maoyuan Road, Nanchong, 637001, Sichuan, China. zhangxm@nsmc.edu.cn.ORCID http://orcid.org/0000-0002-3050-5750

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe modified pancreatitis activity scoring system (mPASS) was proposed to assess the activity of acute pancreatitis (AP) while it doesn't include indicators that directly reflect pathophysiology processes and imaging characteristics.

objectivesTo determine the threshold of admission mPASS and investigate radiomics and laboratory parameters to construct a model to predict the activity of AP.

methodsAP inpatients at institution 1 were randomly divided into training and validation groups based on a 5:5 ratio. AP inpatients at Institution 2 were served as test group. The cutoff value of admission mPASS scores in predicting severe AP was selected to divide patients into high and low level of disease activity group. LASSO was used in screening features. Multivariable logistic regression was used to develop radiomics model. Meaningful laboratory parameters were used to construct combined model.

resultsThere were 234 (48 years ± 10, 155 men) and 101 (48 years ± 11, 69 men) patients in two institutions. The threshold of admission mPASS score was 112.5 in severe AP prediction. The AUC of the radiomics model was 0.79, 0.72, and 0.76 and that of the combined model incorporating rad-score and white blood cell were 0.84, 0.77, and 0.80 in three groups for activity prediction. The AUC of the combined model in predicting disease without remission was 0.74.

conclusionsThe threshold of admission mPASS was 112.5 in predicting severe AP. The model based on CECT radiomics has the ability to predict AP activity. Its ability to predict disease without remission is comparable to mPASS. CRITICAL RELEVANCE STATEMENT: This work is the first attempt to assess the activity of acute pancreatitis using contrast-enhanced CT radiomics and laboratory parameters. The model provides a new method to predict the activity and prognosis of AP, which could contribute to further management. KEY POINTS: Radiomics features and laboratory parameters are associated with the activity of acute pancreatitis. The combined model provides a new method to predict the activity and prognosis of AP. The ability of the combined model is comparable to the modified Pancreatitis Activity Scoring System.

Indexed as

Acute pancreatitisComputed tomographyDisease activityRadiomicsThe modified pancreatitis activity scoring system

Identifiers

PMID38902394
PMCPMC11190132

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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.