Evidence map›Paper›PMID 42861182›Full record

ArticleQuantitative imaging in medicine and surgery2026

Evaluation of Delphi high-resolution computed tomography phenotype classification for treatment-naïve patients with pulmonary sarcoidosis.

Ce Wang, Sijia Guo, Shi Shu, Feiyan Chang, Hongliang Sun, Yanhong Ren, Huaping Dai, Tongxi Liu, Sheng Xie

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Article in Quantitative imaging in medicine 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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9 authors.

Ce WangDepartment of Radiology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.
Sijia GuoDepartment of Radiology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.
Shi ShuCenter of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Feiyan ChangDepartment of Radiology, China-Japan Friendship Hospital, Beijing, China.
Hongliang SunDepartment of Radiology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.
Yanhong RenCenter of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Huaping DaiCenter of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Tongxi LiuDepartment of Radiology, China-Japan Friendship Hospital, Beijing, China.
Sheng XieDepartment of Radiology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The recently developed Delphi consensus provides a simplified high-resolution computed tomography (HRCT) phenotype classification system for pulmonary sarcoidosis. This study aimed to investigate the clinical value of HRCT phenotype classification from the Delphi consensus study on pulmonary sarcoidosis in treatment‑naïve patients and to identify potential refinements for classifying early‑stage sarcoidosis. Methods: This retrospective single-center study included 278 treatment‑naïve patients with pulmonary sarcoidosis. HRCT signs were scored, and clinical data were recorded for all patients. Patients were followed up to observe the treatment effect, recurrence, and onset of pulmonary fibrosis. Associations between HRCT findings, pulmonary function tests (PFTs), early corticosteroid response, recurrence, and fibrosis progression were analyzed. The imaging data were then classified into seven Delphi-defined HRCT phenotypes to evaluate their clinical and prognostic relevance. Results: HRCT signs, including nodules, consolidation, and ground-glass opacity (GGO), were significantly associated with decreased PFT parameters. The presence of central consolidation and nodules was predictive of a favorable early treatment response, while the presence of coarse granular GGOs was associated with a significantly higher risk of recurrence. In terms of Delphi HRCT phenotype, there were 196 patients with the nonfibrotic phenotype (70.5%) and 28 patients with likely-to-be fibrotic phenotypes (10.1%) in our cohort. However, there were unclassifiable cases, including those with isolated lymphadenopathy (12.2%), GGO (5.4%), and pleural effusion‑dominant (1.8%) patterns. Likely-to-be fibrotic phenotypes were associated with the greatest impairment of pulmonary function and the highest risk of fibrosis. The consolidation-dominant type was also associated with an increased risk of fibrosis. According to Cox proportional hazards regression, the isolated lymphadenopathy type was associated with a lower risk of recurrence. Conclusions: The Delphi HRCT phenotype classification is clinically useful but may not be sufficient to fully characterize early-stage pulmonary sarcoidosis. The isolated lymphadenopathy and GGO-dominant types should be considered in the future framework due to their distinct functional and prognostic relevance.

Indexed as

high-resolution computed tomography (HRCT)imaging phenotypespulmonary fibrosisSarcoidosis

Identifiers

PMID42861182
PMCPMC13654091

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