Evidence map›Paper›PMID 41612222›Full record

ArticleBMC medical imaging2026

Development of imaging protocol and radiomics-based nomogram for assessing lesion reversibility in connective tissue disease-associated interstitial lung disease.

Ying Zhang, Feng Zhang, Huawei Wu, Yu Wang, Xiao Yu, Shusen Lin, Ye Yu, Jiaxu Wei, Yan Zhou

Abstract read
In one paragraph

Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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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

9 authors.

Ying ZhangRadiology Department, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, No.160 Pujian Road, Shanghai, China.
Feng ZhangRadiology Department, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, No.160 Pujian Road, Shanghai, China.
Huawei WuRadiology Department, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, No.160 Pujian Road, Shanghai, China.
Yu WangClinical and Technical Support, Philips Healthcare, No.718 Lingshi Road, Shanghai, China.
Xiao YuClinical and Technical Support, Philips Healthcare, No.718 Lingshi Road, Shanghai, China.
Shusen LinSiemens Healthineers China, No.399 West Haiyang Road, Shanghai, China.
Ye YuRadiology Department, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, No.160 Pujian Road, Shanghai, China.
Jiaxu WeiRadiology Department, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, No.160 Pujian Road, Shanghai, China.
Yan ZhouRadiology Department, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, No.160 Pujian Road, Shanghai, China. renjizy@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAssessing the reversibility of connective tissue disease associated interstitial lung disease (CTD-ILD) is critical for treatment decision-making, yet standardized imaging criteria and baseline predictive tools remain limited. We aimed to establish a CT-based protocol to determine lesion reversibility and develop a combined radiomics–morphology nomogram to predict baseline reversibility.

methodsWe retrospectively analyzed consecutive CTD-ILD patients (January 2016–June 2022, diagnosed via ACR/EULAR criteria) from three branches of Renji Hospital. CTD-ILD diagnoses were established by a multidisciplinary team of respiratory physicians and thoracic radiologists based on clinical manifestations and chest CT imaging. Patients from the South Branch were randomly split into training and internal validation cohorts (7:3), while patients from the East and West Branches formed an independent external validation cohort. Lesion reversibility was adjudicated using longitudinal CT series across six lung zones: the scan with the greatest lesion extent was defined as baseline (CT0); completely reversible (CR) lesions were defined as complete absorption of baseline lesions on any follow-up CT, whereas non-CR required persistence of baseline lesions on both 3–6-month (CTF1) and 12-month (CTF2) follow-up CTs. Zonal-level radiomics signatures and visual CT features were used to develop radiomics, visual, and combined nomogram models.

resultsThe final cohort included 153 patients (median age, 53 years; interquartile range, 44–62 years), with 40 males (26.1%) and 113 females (73.9%) with 575 affected lung zones. Cohorts comprised 66/28/59 patients (training/internal validation/external validation). The radiomics model showed moderate discrimination (areas under the curve [AUCs] 0.72/0.77/0.73), while the visual model performed similarly or better (AUCs 0.82/0.87/0.78). The combined nomogram achieved the best overall performance (AUCs 0.86/0.90/0.82), with significant improvement over the visual model in the training and external validation cohorts.

conclusionWe established a longitudinal imaging protocol to standardize reversibility assessment and validated a combined nomogram that integrates quantitative and visual data. This tool accurately predicts lesion reversibility at baseline, potentially facilitating personalized treatment strategies for CTD-ILD patients.

Indexed as

Connective Tissue DiseasesLung Diseases, InterstitialNomogramsTomography, X-Ray ComputedAdultFemaleHumansMaleMiddle AgedRadiomicsRetrospective StudiesConnective tissue diseaseInterstitialLung diseasesRadiomicsTomographyX-ray computed

Identifiers

PMID41612222
PMCPMC12924472

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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.