Predicting the Efficacy of SBRT for Lung Cancer with 18F-FDG PET/CT Radiogenomics
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients and Inclusion Criteria
2.2. Imaging Protocol for 18F-FDG PET/CT
2.3. Stereotactic Body Radiation Therapy (SBRT)
2.4. Segmentation, and Feature Extraction and Selection
2.4.1. Segmentation
2.4.2. Feature Extraction
2.4.3. Feature Selection and Model Construction
2.5. Model Evaluation and Validation
2.6. Statistical Analysis
3. Results
3.1. Clinical Characteristics
3.2. Extraction and Selection of Radiomic Features
3.3. Model Performance
3.4. Bootstrap Validation
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Numbers of Cases (n) | Constituent Ratio (%) |
---|---|---|
Age, years (≤70 y/>70 y) | 63/60 | 51.22/48.78 |
Sex (male/female) | 103/20 | 83.74/16.26 |
KPS (100/90/80/70) | 2/40/78/3 | 1.63/32.52/63.41/2.44 |
ECOG performance status (0/1/2) | 47/74/2 | 38.21/60.16/1.63 |
Cigarette smoking (ever been smoker/never smoker) | 40/83 | 32.52/67.48 |
Tumor location (central/peripheral) | 62/61 | 50.41/49.59 |
Pathological type (adenocarcinoma/squamous cell carcinoma/unknown) | 37/52/34 | 30.08/42.28/27.64 |
Source of tumor (primary/metastatic) | 94/29 | 76.42/23.58 |
EGFR mutation (positive/negative) | 25/98 | 20.33/79.67 |
T classification (T1–T4) | 51/32/22/18 | 41.46/26.02/17.89/14.63 |
Overall stage (I–II/III–IV) | 43/80 | 34.96/65.04 |
Maximal SUV (≤9.6/>9.6) | 63/60 | 51.22/48.78 |
BED (≤100/>100) | 74/49 | 60.16/39.84 |
Characteristics | Long PFS (n = 52) | Short PFS (n = 71) | p |
---|---|---|---|
Age (≤70 y/>70 y) | 24/28 | 39/32 | 0.34 |
Sex (female/male) | 9/43 | 11/60 | 0.81 |
KPS (100/90/80/70) | 1/20/29/2 | 1/20/49/1 | 0.43 |
ECOG performance status (0/1/2) | 22/28/2 | 25/46/0 | 0.15 |
Cigarette smoking (ever/never) | 36/16 | 47/24 | 0.85 |
Tumor location (central/peripheral) | 29/23 | 55/16 | 0.36 |
Pathology (adenocarcinoma/squamous cell carcinoma/unknown) | 18/21/13 | 19/31/21 | 0.68 |
Source of tumor (primary/metastatic) | 39/13 | 55/16 | 0.83 |
T classification (1–4) | 18/14/10/10 | 33/18/12/8 | 0.49 |
Overall stage (I–II/III–IV) | 23/29 | 20/51 | 0.07 |
Maximal SUV (≤9.6/>9.6) | 28/24 | 35/36 | 0.62 |
BED (≤100/>100) | 36/16 | 38/33 | 0.08 |
Models | AUC | ACC | SEN | SPE | PPV | NPV | Delong’s P |
---|---|---|---|---|---|---|---|
Radiogenomic model | 0.86 | 0.78 | 0.71 | 0.83 | 0.76 | 0.80 | |
Radiomic model | 0.84 | 0.77 | 0.71 | 0.82 | 0.74 | 0.79 | >0.05 |
Clinical EGFR model | 0.67 | 0.65 | 0.52 | 0.75 | 0.60 | 0.68 | <0.05 |
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Chen, K.; Hou, L.; Chen, M.; Li, S.; Shi, Y.; Raynor, W.Y.; Yang, H. Predicting the Efficacy of SBRT for Lung Cancer with 18F-FDG PET/CT Radiogenomics. Life 2023, 13, 884. https://doi.org/10.3390/life13040884
Chen K, Hou L, Chen M, Li S, Shi Y, Raynor WY, Yang H. Predicting the Efficacy of SBRT for Lung Cancer with 18F-FDG PET/CT Radiogenomics. Life. 2023; 13(4):884. https://doi.org/10.3390/life13040884
Chicago/Turabian StyleChen, Kuifei, Liqiao Hou, Meng Chen, Shuling Li, Yangyang Shi, William Y. Raynor, and Haihua Yang. 2023. "Predicting the Efficacy of SBRT for Lung Cancer with 18F-FDG PET/CT Radiogenomics" Life 13, no. 4: 884. https://doi.org/10.3390/life13040884