PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients
Abstract
:1. Introduction
2. Methodological Aspects of Tumor Volume Delineation
3. The Prognostic Role of Volume-Based PET Parameters in Primary NSCLC
4. The Prognostic Role of Volume-Based PET Parameters in All Metabolically Active Lesions of NSCLC
5. Volume-Based PET Parameters in the Era of Immunotherapy
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Clinical Study | N° of Patients | TNM Stage | Endpoints | Volumetric Parameters | Threshold or Delineation Method | Determination of Cut-Off Value | Cut-Off Values | |
---|---|---|---|---|---|---|---|---|
MTV | TLG | |||||||
Davison et al. (2013) [47] | 39 | I/IV | 12 mo. Survival OS | MTV/TLG | gradient-based | median value ROC curve | 9.7 mL 79 mL | 74 g 349 g |
Hyun et al. (2013) [40] | 529 | IA/IIB | OS/DFS | MTV/TLG | mediastinal background SUVavg plus its 2 SD | ROC curve | 16 cm3 | 70 g |
Anwar et al. (2018) [48] | 49 | IA/IB | DFS | MTV/TLG | SUV (2.5) | ROC curve | 6.6 mL | 36.6 g |
Dosani et al. (2019) [49] | 134 | inoperable IA/IB | LC OS | MTV/TLG | gradient-based | median value | 2.4 mL | 10.9 g |
Yanarates et al. (2020) [50] | 258 | IIIB/IV | OS/PFS | MTV/TLG | 50%SUVmax | ROC curve | 5.7 mL | 49.4 g |
Kim et al. (2014) [51] | 63 | IA/IIB | OLM | MTV/TLG | SUV (2.5) | ROC curve | 18.9 cm3 | 88.4 g |
Park et al. (2015) [52] | 139 | I | OLM | MTV/TLG | SUV (2.0) | ROC curve | 3.055 mL | 9.829 g |
Roengvoraphoj et al. (2018) [53] | 65 | inoperable IIIA/IIIB | OS | MTV | 50%SUVmax | pre-CRT post-CRT Δmid-CRT | 63 cm3 25 cm3 ≥15% | - - - |
Roengvoraphoj et al. (2018) [54] | 60 | inoperable IIIA/IIIB | OS | MTV | 50%SUVmax | Δpost-CRT | ≥80% | - |
Clinical Study | N° of Patients | TNM Stage | Endpoints | Volumetric Parameters | Threshold or Delineation Method | Determination of Cut-Off Value | Cut-Off Values | |
---|---|---|---|---|---|---|---|---|
MTV | TLG | |||||||
Bazan et al. (2017) [57] | 230 | inoperable IIB/IIIB | OS LC | MTV | 60% adaptive threshold of the SUVpeak within each lesion | median value | 32 mL | - |
Finkle et al. (2017) [58] | 330 | IIB/IIIB | OS | MTV | gradient-based | Log-rank test | 29.2 mL | - |
Ventura et al. (2020) [59] | 193 | operable I/IV | OS | MTV/TLG | 42%SUVmax | ROC curve | 8.15 mL | 21.85 g |
Liao et al. (2012) [24] | 169 | inoperable lI/IV | OS | MTV/TLG | gradient-based | tertiles | 33.5 mL 134.9 mL 473.0 mL | 107.3 g 504.0 g 1898.1 g |
Pellegrino et al. (2019) [60] | 65 | I/IV | OS/PFS | MTV/TLG | SUV (2.5) | ROC curve | 9.5 mL | 54.7 g |
Chen et al. (2012) [61] | 105 | I/IV | OS/PFS | TLG | 50%SUVmax | ROC curve | - | 655 g |
Vanhove et al. (2018) [62] | 105 | I/IV | OS/PFS | MTV/TLG | 50%SUVmax | median value | 14.6 mL | 93.4 g |
Lapa et al. (2017) [63] | 278 | I/IV | OS | MTV | SUV (2.5) | R software | 49.5 mL | - |
Pu et al. (2018) [64] | 935 | I/IV | OS | MTV | gradient-based | quartiles | 10 mL 53.4 mL 155 mL | - - - |
Chin et al. (2018) [65] | 55 | oligometastatic I/IV | OS | MTV/TLG | gradient-based | quartiles (highest vs. remaining) | 17.8 mL | 86.8 g |
Kong et al. (2019) [29] | 102 | inoperable I/III | OS | MTV/TLG | Auto-segmentation at tumor/aorta ratio of 1.5 followed by manual editing according to CT anatomy | median value after mid-RT with conventional RT or PET-adapted RT | 41 mL 46 mL | - - |
Chen et al. (2019) [66] | 25 | IIIA/IIIB | OS/PFS | MTV/TLG | 50%SUVmax | Δmedian value after mid-RT | 42% | 65% |
Xiao et al. (2017) [67] | 17 | II/III | RT adjustment based on ΔMTV | MTV | fixed source/background ratio combined with CT anatomy based manual editing | mean value pre-RT mean value during-RT | 136.2 mL 64.7 mL | - - |
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Pellegrino, S.; Fonti, R.; Pulcrano, A.; Del Vecchio, S. PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients. Diagnostics 2021, 11, 210. https://doi.org/10.3390/diagnostics11020210
Pellegrino S, Fonti R, Pulcrano A, Del Vecchio S. PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients. Diagnostics. 2021; 11(2):210. https://doi.org/10.3390/diagnostics11020210
Chicago/Turabian StylePellegrino, Sara, Rosa Fonti, Alessandro Pulcrano, and Silvana Del Vecchio. 2021. "PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients" Diagnostics 11, no. 2: 210. https://doi.org/10.3390/diagnostics11020210
APA StylePellegrino, S., Fonti, R., Pulcrano, A., & Del Vecchio, S. (2021). PET-Based Volumetric Biomarkers for Risk Stratification of Non-Small Cell Lung Cancer Patients. Diagnostics, 11(2), 210. https://doi.org/10.3390/diagnostics11020210