ArticleDiscover oncology2023
Is it possible to differentiate pulmonary sarcoidosis in tumor patients and pulmonary lymphangitic carcinomatosis caused by extrapulmonary tumors on 18F-FDG PET/CT images?
Article in Discover oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- Dual-tracerRadiology case reports · 2026Article
- Pulmonary lymphangitic carcinomatosis as an unusual presentation of renal cell carcinoma: a case report and a brief literature review.International journal of surgery case reports · 2026Article
- The Role of [18F]FDG PET Imaging for the Assessment of Pulmonary Lymphangitic Carcinomatosis: A Comprehensive Narrative Literature Review.Diagnostics (Basel, Switzerland) · 2025Review
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposePulmonary sarcoidosis (PS) and pulmonary lymphangitic carcinomatosis (PLC) can be complications in tumor patients, and both involve the pulmonary interstitium and have similar imaging findings. Our objective was to distinguish PS and PLC on 18F-FDG PET/CT images. MATERIAL AND
methodsThe authors reviewed 18F-FDG PET/CT data of PS and PLC, diagnosed based on histopathology and imaging, in patients with tumors from July 2015 to January 2023. Three independent readers performed a blinded comparative analysis of 18F-FDG PET/CT signs in all patients. A multivariate logistic regression model was used to establish a differential diagnosis model.
resultsA total of 114 patients were included in the study: 56 patients with PS (mean age, 56 ± 11 [SD] years; 10 men) and 58 patients with PLC caused by extrapulmonary tumors (mean age, 51 ± 11 [SD] years; 21 men). For PS, breast cancer and cervical cancer were the most common primary tumors. For PLC, breast cancer and gastric cancer were the most common extrapulmonary tumors. The model constructed using multivariate logistic regression consisted of five factors: area of lymph node involvement, bronchovascular bundle diffuse thickening, interlobular septal thickening, pleural effusion, and subpleural hypermetabolic activity. The area under the model characteristic curve was 0.973 (95% CI 0.925-0.994), with a sensitivity, specificity, and positive and negative likelihood ratios of 87.50%, 98.28%, 50.75 and 0.13 respectively.
conclusionThere are detailed differences in 18F-FDG PET/CT manifestations of PS in tumor patients and PLC caused by extrapulmonary tumors, and the constructed diagnostic model has high clinical application value in differentiating the two.
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