Evidence map›Paper›PMID 42545596›Full record

ArticleInternational journal of computer assisted radiology and surgery2026

Radiomics analysis and classification of esophageal involvement in systemic sclerosis using chest CT images.

Yuito Ueda, Shinnosuke Watanabe, Rea Ikeda, Mikito Suzuki, Masataka Kuwana, Hiroshi Takemura

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Article in International journal of computer assisted radiology and surgery, 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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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yuito UedaDepartment of Mechanical and Aerospace Engineering, Tokyo University of Science, 2641 Yamazaki, Noda-shi, Chiba, 278-8510, Japan. 7525506@ed.tus.ac.jp.ORCID http://orcid.org/0009-0006-8234-4342
Shinnosuke WatanabeSchool of Medicine, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, Tokyo, 113-8602, Japan.
Rea IkedaDepartment of Mechanical and Aerospace Engineering, Tokyo University of Science, 2641 Yamazaki, Noda-shi, Chiba, 278-8510, Japan.
Mikito SuzukiDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, 1-1-5 Sendagi, Bunkyo-ku, Tokyo, 113-8602, Japan.
Masataka KuwanaDepartment of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, 1-1-5 Sendagi, Bunkyo-ku, Tokyo, 113-8602, Japan.
Hiroshi TakemuraDepartment of Mechanical and Aerospace Engineering, Tokyo University of Science, 2641 Yamazaki, Noda-shi, Chiba, 278-8510, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeEsophageal involvement is a common and early manifestation of systemic sclerosis (SSc). This involvement is mainly evaluated by esophageal manometry, but this test is invasive and provides limited morphological information. This study aimed to identify CT-based radiomics features related to esophageal involvement and to evaluate whether the presence or absence of esophageal involvement can be classified with high accuracy.

methodsChest CT images from 64 subjects were analyzed, including 30 patients with SSc and 34 normal subjects. The esophageal region was automatically segmented, and radiomics features were extracted from ellipse-fitted regions of interest on axial slices. Features showing significant differences were selected, and feature combinations were evaluated using exhaustive search. Classification was performed using XGBoost.

resultsFirst-order statistical features at levels corresponding to the third to fifth thoracic vertebrae were significantly associated with the presence of esophageal involvement. Classification using these features showed high accuracy when five to six features were used, indicating that the presence or absence of esophageal involvement can be identified accurately even with a small number of features.

conclusionCT-based radiomics analysis may be a useful noninvasive method for evaluating esophageal involvement. Future studies incorporating pathological correlation and surrounding tissue information may further improve clinical applicability.

Indexed as

CT imagingRadiomicsSystemic sclerosis (SSc)XGBoost

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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.