Evidence map›Paper›PMID 39466507›Full record

ArticleJournal of imaging informatics in medicine2025

Developing a Reproducible Radiomics Model for Diagnosis of Active Crohn's Disease on CT Enterography Across Annotation Variations and Acquisition Differences.

Prathyush V Chirra, Pavithran Giriprakash, Alain G Rizk, Jacob A Kurowski, Satish E Viswanath, Namita S Gandhi

Abstract read
In one paragraph

Article in Journal of imaging informatics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
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

6 authors.

Prathyush V ChirraDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Pavithran GiriprakashDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Alain G RizkSection, Abdominal Imaging, Imaging Institute, and Digestive Diseases and Surgery Institute and Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
Jacob A KurowskiDepartment of Pediatric Gastroenterology, Hepatology & Nutrition, Cleveland Clinic, Cleveland, OH, USA.
Satish E ViswanathDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA. satish.viswanath@case.edu.ORCID http://orcid.org/0000-0003-4550-8337
Namita S GandhiSection, Abdominal Imaging, Imaging Institute, and Digestive Diseases and Surgery Institute and Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.

Funding

Cardiovascular risk from comprehensive evaluation of the CT calcium score examR01HL165218 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI Sanjay Rajagopalan, DAVID Lynn WILSON · 2023 to 2026
$3.8M
OPtimizing Technology to Improve Medication Adherence and BP Control (OPTIMA-BP).R01NR019585 · NINR · CASE WESTERN RESERVE UNIVERSITY · PI STILL, CAROLYN HARMON · 2021 to 2025
$3.4M
Novel radiomic signatures for treatment response to neoadjuvant therapy in rectal cancersR01CA280981 · NCI · EMORY UNIVERSITY · PI ANDREI SARAIVA PURYSKO, Emily Steinhagen · 2024 to 2026
$1.7M
RadxTools for assessing tumor treatment response on imagingU01CA248226 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI TIWARI, PALLAVI, VISWANATH, SATISH EASWAR · 2020 to 2022
$1.4M
Radiomics-based Risk Prediction for Therapy Selection in Crohn’s Disease via MRIF31DK130587 · NIDDK · CASE WESTERN RESERVE UNIVERSITY · PI CHIRRA, PRATHYUSH V · 2022 to 2022
$35k
Artificial Intelligence Imaging Predictors for Rectal Cancer ManagementI01BX006439 · VA · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · PI VISWANATH, SATISH EASWAR · 2024 to 2025
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BLRD VA I01 BX006439DOD Peer Reviewed Cancer Research Program W81XWH 19-1-0668DOD Peer Reviewed Cancer Research Program W81XWH-21-1-0345DOD Peer Reviewed Cancer Research Program W81XWH-21-1-0725National Science Foundation Award# 2320952NCI NIH HHS 1R01CA280981-01A1NCI NIH HHS 1U01CA248226-01NCI NIH HHS R01 CA280981NCI NIH HHS U01 CA248226NHLBI NIH HHS 1R01HL165218-01A1NHLBI NIH HHS R01 HL165218NIDDK NIH HHS 1F31DK130587-01A1NIDDK NIH HHS F31 DK130587NINR NIH HHS 1R01NR019585-01A1NINR NIH HHS R01 NR019585U.S. Department of Veterans Affairs 1I01BX006439-01
6 · The paper itself

Abstract

To systematically identify radiomics features on CT enterography (CTE) scans which can accurately diagnose active Crohn's disease across multiple sources of variation. Retrospective study of CTE scans curated between 2013 and 2015, comprising 164 subjects (65 male, 99 female; all patients were over the age of 18) with endoscopic confirmation for the presence or absence of active Crohn's disease. All patients had three distinct sets of scans available (full and reduced dose, where the latter had been reconstructed via two different methods), acquired on a single scanner at a single institution. Radiomics descriptors from annotated terminal ileum regions were individually and systematically evaluated for resilience to different imaging variations (changes in dose/reconstruction, batch effects, and simulated annotation differences) via multiple reproducibility measures. Multiple radiomics models (by accounting for each source of variation) were evaluated in terms of classifier area under the ROC curve (AUC) for identifying patients with active Crohn's disease, across separate discovery and hold-out validation cohorts. Radiomics descriptors selected based on resiliency to multiple sources of imaging variation yielded the highest overall classification performance in the discovery cohort (AUC = 0.79 ± 0.04) which also best generalized in hold-out validation (AUC = 0.81). Performance was maintained across multiple doses and reconstructions while also being significantly better (p < 0.001) than non-resilient descriptors or descriptors only resilient to a single source of variation. Radiomics features can accurately diagnose active Crohn's disease on CTE scans across multiple sources of imaging variation via systematic analysis of reproducibility measures. Clinical utility and translatability of radiomics features for diagnosis and characterization of Crohn's disease on CTE scans will be contingent on their reproducibility across multiple types and sources of imaging variation.

Indexed as

Crohn DiseaseRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedAdultFemaleHumansMaleMiddle AgedRadiomicsReproducibility of ResultsRetrospective StudiesYoung AdultCrohn’s diseaseCTEIterative reconstructionRadiomicsReduced dose

Identifiers

PMID39466507
PMCPMC12092320

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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.