ArticleJapanese journal of radiology2023
PET morphology helps distinguish solitary and solid pulmonary tuberculosis from non-small cell lung cancer.
Article in Japanese journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Post-Tuberculosis Sequelae and Active Tuberculosis in Lung Cancer: Imaging Patterns and Clinical Associations-A Retrospective Single-Center Cohort Study.Journal of clinical medicine · 2026Article
- Recent advances in theranostics and oncology PET: emerging radionuclides and targets.Annals of nuclear medicine · 2025Review
- Generative AI and large language models in nuclear medicine: current status and future prospects.Annals of nuclear medicine · 2024Review
- From FDG and beyond: the evolving potential of nuclear medicine.Annals of nuclear medicine · 2023Review
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Authors and funding
7 authors.
Funding
Abstract
objectiveSolitary and solid pulmonary tuberculosis (PTB) and non-small cell lung cancer (NSCLC) can present overlapping imaging features, causing diagnostic dilemmas. Hence, this study aimed to identify positron emission tomography (PET) morphological features derived from fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (
methodsClinical records and
resultsPTB presented with more heterogeneous glucometabolism than NSCLC in PET imaging (50% vs 17%, P < 0.05), especially in lesions with a maximum diameter < 30 mm (39% vs. 5%, P < 0.05). NSCLC usually showed centric hypometabolism, whereas PTB more frequently presented with an eccentric metabolic pattern, mainly including piebald, half-side, lesser curvature, and greater curvature shapes. Multivariate logistic regression identified that glucometabolic heterogeneity, eccentric hypometabolism, smaller lesion size, calcification, satellite lesions, and higher CT value of the hypometabolic area were independently diagnostic factors for PTB.
conclusionsMorphological features derived from
Indexed as
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Registered trials
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