» Articles » PMID: 38605064

Enhancing NSCLC Recurrence Prediction with PET/CT Habitat Imaging, CtDNA, and Integrative Radiogenomics-blood Insights

Abstract

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

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References
1.
Chicklore S, Goh V, Siddique M, Roy A, Marsden P, Cook G . Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis. Eur J Nucl Med Mol Imaging. 2012; 40(1):133-40. DOI: 10.1007/s00259-012-2247-0. View

2.
Reuben A, Gittelman R, Gao J, Zhang J, Yusko E, Wu C . TCR Repertoire Intratumor Heterogeneity in Localized Lung Adenocarcinomas: An Association with Predicted Neoantigen Heterogeneity and Postsurgical Recurrence. Cancer Discov. 2017; 7(10):1088-1097. PMC: 5628137. DOI: 10.1158/2159-8290.CD-17-0256. View

3.
Wu J, Li C, Gensheimer M, Padda S, Kato F, Shirato H . Radiological tumor classification across imaging modality and histology. Nat Mach Intell. 2021; 3:787-798. PMC: 8612063. DOI: 10.1038/s42256-021-00377-0. View

4.
Wu J, Gensheimer M, Zhang N, Guo M, Liang R, Zhang C . Tumor Subregion Evolution-Based Imaging Features to Assess Early Response and Predict Prognosis in Oropharyngeal Cancer. J Nucl Med. 2019; 61(3):327-336. PMC: 7067523. DOI: 10.2967/jnumed.119.230037. View

5.
Cascone T, McKenzie J, Mbofung R, Punt S, Wang Z, Xu C . Increased Tumor Glycolysis Characterizes Immune Resistance to Adoptive T Cell Therapy. Cell Metab. 2018; 27(5):977-987.e4. PMC: 5932208. DOI: 10.1016/j.cmet.2018.02.024. View