Evidence map›Paper›PMID 32655269›Full record

ArticleWorld journal of gastroenterology2020

Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy.

Stuart L Polk, Jung W Choi, Melissa J McGettigan, Trevor Rose, Abraham Ahmed, Jongphil Kim, Kun Jiang, Yoganand Balagurunathan, Jin Qi, Paola T Farah and 3 more

Open access · hybridAbstract read
In one paragraph

Article in World journal of gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 47 citations in OpenAlex.

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  14. Pancreatic Incidentaloma.Journal of clinical medicine · 2022
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  17. Radiomics in surgical oncology: applications and challenges.Computer assisted surgery (Abingdon, England) · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 1 country.

Stuart L PolkUniversity of South Florida College of Medicine, Tampa, FL 33612, United States.
Jung W ChoiDepartment of Diagnostic and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Melissa J McGettiganDepartment of Diagnostic and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Trevor RoseDepartment of Diagnostic and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Abraham AhmedDepartment of Diagnostic and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Jongphil KimDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Kun JiangDepartment of Anatomic Pathology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Yoganand BalagurunathanDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Jin QiDepartment of Cancer Physiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Paola T FarahDepartment of Clinical Science, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Alisha RathiDepartment of Radiology, University of Florida, Gainesville, FL 32610, United States.
Jennifer B PermuthDepartment of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States.
Daniel JeongDepartment of Diagnostic and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, United States. daniel.jeong@moffitt.org.
University of Florida · USFlorida College · USUniversity of South Florida · USMoffitt Cancer Center · US

Funding

Using Radiogenomics to Noninvasively Predict the Malignant Potential of Intraductal Papillary Mucinous Neoplasms of the Pancreas and Uncover Hidden BiologyR37CA229810 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI JEONG, DANIEL, PERMUTH, JENNIFER B · 2019 to 2025
$5.0M
NCI NIH HHS R37 CA229810
6 · The paper itself

Abstract

backgroundIntraductal papillary mucinous neoplasms (IPMNs) are non-invasive pancreatic precursor lesions that can potentially develop into invasive pancreatic ductal adenocarcinoma. Currently, the International Consensus Guidelines (ICG) for IPMNs provides the basis for evaluating suspected IPMNs on computed tomography (CT) imaging. Despite using the ICG, it remains challenging to accurately predict whether IPMNs harbor high grade or invasive disease which would warrant surgical resection. A supplementary quantitative radiological tool, radiomics, may improve diagnostic accuracy of radiological evaluation of IPMNs. We hypothesized that using CT whole lesion radiomics features in conjunction with the ICG could improve the diagnostic accuracy of predicting IPMN histology.

aimTo evaluate whole lesion CT radiomic analysis of IPMNs for predicting malignant histology compared to International Consensus Guidelines.

methodsFifty-one subjects who had pancreatic surgical resection at our institution with histology demonstrating IPMN and available preoperative CT imaging were included in this retrospective cohort. Whole lesion semi-automated segmentation was performed on each preoperative CT using Healthmyne software (Healthmyne, Madison, WI). Thirty-nine relevant radiomic features were extracted from each lesion on each available contrast phase. Univariate analysis of the 39 radiomics features was performed for each contrast phase and values were compared between malignant and benign IPMN groups using logistic regression. Conventional quantitative and qualitative CT measurements were also compared between groups,

resultsTwenty-nine subjects (15 males, age 71 ± 9 years) with high grade or invasive tumor histology comprised the "malignant" cohort, while 22 subjects (11 males, age 70 ± 7 years) with low grade tumor histology were included in the "benign" cohort. Radiomic analysis showed 18/39 precontrast, 19/39 arterial phase, and 21/39 venous phase features differentiated malignant from benign IPMNs (

conclusionMulti-phase CT radiomics evaluation could play a role in improving predictive capability in diagnosing malignancy in IPMNs. Future larger studies may help determine the clinical significance of our findings.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic Intraductal NeoplasmsPancreatic NeoplasmsAgedAged, 80 and overHumansMaleMiddle AgedRetrospective StudiesTomography, X-Ray ComputedIntraductal papillary mucinous neoplasmMultiphase computed tomographyOncologyPancreasPancreatic cancerRadiomics

Identifiers

PMID32655269
PMCPMC7327792
OpenAlexW3038014358

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.