Potentials of pretreatment [18F]FDG PET/CT for non-invasive prediction of the tumor unfavorable pathological indices and microenvironment in NSCLC

Abstract Purpose To investigate pretreatment [ 18 F]FDG PET/CT in predicting tumor pathological features and microenvironment. Methodology Fifty-one patients with histo-pathologically proven non-small cell lung cancer (NSCLC) underwent pretreatment [ 18 F]FDG PET/CT, and their clinicopathological data were collected. PET-derived biomarkers (SUVmax, mean, MTV, and TLG), consolidation-to-tumor ratio (CTR), and histopathological data (tumor grade, differentiation, tumor histological subtype, tumor-infiltrating lymphocytes (TILs), degree of desmoplasia, degree of necrosis, tumor budding, and nuclear grade), as well as a proposed risk stratification pathological scoring system, were all assessed. Results A CTR cut-off point of 0.34 was able to discriminate between low- and high-grade tumors with a sensitivity and specificity of 75.9% and 68.2%, respectively ( p = 0.012). Low CTR was significantly associated with the tumor pathological subtype “adenocarcinoma,” low nuclear grade, negative tumor necrosis, and low pathological scores, respectively ( p < 0.05). No significant associations were observed for CTR with tumor budding score, desmoplasia score, or TILs% (p-values > 0.05). High SUVmax (> 12.64) and high SUVmean (> 4.28) values were significantly associated with SCC tumors ( p = 0.023 and 0.04, respectively). SUVmean was significantly associated with cytological differentiation ( p = 0.023). A statistical trend was noted for SUVmax concerning nuclear grade and desmoplasia scores ( p = 0.068 and 0.061, respectively). No statistically significant associations were revealed for MTV and TLG concerning different pathological features (p-values > 0.05). Primary lung tumors positive for desmoplasia revealed higher metabolic activity regarding SUVmax, with a statistical trend observed ( p = 0.072). No statistically significant associations were observed concerning other metabolic parameters (p-values > 0.05). Conclusion PET/CT-derived biomarkers appear promising for predicting tumor unfavorable pathological features and microenvironment in NSCLC.

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Journal
Clinical and Translational Imaging
Published
2024-10-24
DOI
https://doi.org/10.1007/s40336-024-00663-y
Primary Topic
Medical Imaging Techniques and Applications
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article
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article

Potentials of pretreatment [18F]FDG PET/CT for non-invasive prediction of the tumor unfavorable pathological indices and microenvironment in NSCLC

Mai Amr Elahmadawy, Ismail Elantably, Mohamed Emam Sobeih, Noha Fadl et al.
Clinical and Translational Imaging
Medical Imaging Techniques and Applications
article

Potentials of pretreatment [18F]FDG PET/CT for non-invasive prediction of the tumor unfavorable pathological indices and microenvironment in NSCLC

Mai Amr Elahmadawy, Ismail Elantably, Mohamed Emam Sobeih, Noha Fadl, Rasha Mahmoud Allam, Hazem Abdelazim, Hosna Moustafa
article en

Abstract

Abstract Purpose To investigate pretreatment [ 18 F]FDG PET/CT in predicting tumor pathological features and microenvironment. Methodology Fifty-one patients with histo-pathologically proven non-small cell lung cancer (NSCLC) underwent pretreatment [ 18 F]FDG PET/CT, and their clinicopathological data were collected. PET-derived biomarkers (SUVmax, mean, MTV, and TLG), consolidation-to-tumor ratio (CTR), and histopathological data (tumor grade, differentiation, tumor histological subtype, tumor-infiltrating lymphocytes (TILs), degree of desmoplasia, degree of necrosis, tumor budding, and nuclear grade), as well as a proposed risk stratification pathological scoring system, were all assessed. Results A CTR cut-off point of 0.34 was able to discriminate between low- and high-grade tumors with a sensitivity and specificity of 75.9% and 68.2%, respectively ( p = 0.012). Low CTR was significantly associated with the tumor pathological subtype “adenocarcinoma,” low nuclear grade, negative tumor necrosis, and low pathological scores, respectively ( p < 0.05). No significant associations were observed for CTR with tumor budding score, desmoplasia score, or TILs% (p-values > 0.05). High SUVmax (> 12.64) and high SUVmean (> 4.28) values were significantly associated with SCC tumors ( p = 0.023 and 0.04, respectively). SUVmean was significantly associated with cytological differentiation ( p = 0.023). A statistical trend was noted for SUVmax concerning nuclear grade and desmoplasia scores ( p = 0.068 and 0.061, respectively). No statistically significant associations were revealed for MTV and TLG concerning different pathological features (p-values > 0.05). Primary lung tumors positive for desmoplasia revealed higher metabolic activity regarding SUVmax, with a statistical trend observed ( p = 0.072). No statistically significant associations were observed concerning other metabolic parameters (p-values > 0.05). Conclusion PET/CT-derived biomarkers appear promising for predicting tumor unfavorable pathological features and microenvironment in NSCLC.

Clinical and Translational ImagingVol. 12(6)
Cairo University (EG)
Reduced inequalities
Openalex Percentile: Top 69%
Medical Imaging Techniques and Applications
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