Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients
2.2. PET/CT Imaging Technique
2.3. Radiomic Features Extraction
2.4. Clinical End Points and Follow-Up
2.5. Statistical Analysis
3. Results
3.1. Patient Characteristics
3.2. Radiomic Parameters and DFS Association
3.3. Radiomic Parameters and OS Association
3.4. Type of Treatment and DFS/OS Association
3.5. Multivariate Analysis: Radiomic Features (GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis), Type of Treatment, and DFS/OS
4. Discussion
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
OC | Ovarian Cancer |
HSOC | High-Grade Serous Carcinoma |
MR | Magnetic Resonance |
PET/CT | Positron Emission Tomography/Computed Tomography |
VOI | Volume of interest |
18F-FDG | 18F-Fluorodeoxyglucose |
FIGO | International Federation of Gynecology and Obstetrics |
PSF | point spread function |
SUV | standardized uptake value |
SUVmax | maximum uptake value |
PERCIST criteria | Positron Emission Tomography Response Criteria in Solid Tumors. |
SULmax | normalized for lean body weight maximum uptake value |
DFS | Disease-free Survival |
OS | Overall Survival |
HR | Hazard Ratio |
TLG | total lesion glycolysis |
GLZLM or GLSZM | Grey Level Zone Length Matrix or Grey Level Size Zone Matrix |
ZSNU | Zone Size Non Uniformity |
GLRLM | Gray level Run Length Matrix |
RLNU | Run Length Non Uniformity |
NGLDM | Neighbouring grey level dependence |
GLZLM_ZLNU | Grey level zone length matrix Zone length nonuniformity |
GLDZM | Grey Level Distance Zone Matrix |
MTV | Metabolic tumor volume |
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Matrix | Index |
---|---|
First order features | |
Morphological | Approximate Volume |
MORPHOLOGICAL_Compacity | |
MORPHOLOGICAL_Compactness2 | |
MORPHOLOGICAL_Centre OF Mass Shift | |
Intensity-based | Total Lesion Glycolysis |
Variance | |
Kurtosis | |
Minimum Grey Level | |
Histogram Uniformity | |
Higher order features | |
Gray-Level Cooccurrence Matrix (GLCM) | GLCM_Joint Maximum |
GLCM_Inverse Difference Moment | |
GLCM_Inverse Variance | |
GLCM_Correlation | |
GLCM_Cluster Tendency | |
GLCM_Cluster Shade | |
Neighborhood grey tone difference (NGTDM) | Coarseness |
Contrast | |
Busyness | |
Gray level Run-Length Matrix (GLRLM) | Long Runs Emphasis |
Run Length Non Uniformity | |
Grey-Level Zone Length Matrix (GLZLM) or Grey-Level Size Zone Matrix (GLSZM) | Large Zone High Grey Level Emphasis |
Zone Size Non Uniformity | |
Normalised Zone Size Non Uniformity |
Characteristic | Patients |
---|---|
Total patients | 36 |
Mean age, years (range) | 60 (42–84) |
FIGO stage | |
III | 12 (33.3%) |
IV | 24 (66.7%) |
Histology | |
High-grade serous carcinoma | 36 |
Type of treatment | |
Neoadjuvant chemotherapy + interval debulking surgery | 20 (55.6%) |
Primary cytoreductive surgery + adjuvant chemotherapy | 8 (22.2%) |
Chemotherapy only | 8 (22.2%) |
Chemotherapy | |
Carboplatin + paclitaxel with Bevacizumab + Bevacizumab as maintenance | 6 (16.6%) |
Carboplatin + paclitaxel + Bevacizumab as maintenance | 13 (36.1%) |
Carboplatin + paclitaxel without Bevacizumab | 3 (8.3%) |
Carboplatin + paclitaxel with Bevacizumab without maintenance | 14 (38.9%) |
PARPi | 1 (2.7%) |
Mean Follow-up months | 31.19 |
Mean DFS, months | 19.6 ± 11 |
Mean OS, months | 37.1 ± 20.3 |
n = 36 | MTV | TLG | _Kurtosis | GLSZM_ZSNU | GLRLM_RLNU |
---|---|---|---|---|---|
Mean | 1025.7 | 3828.1 | 4.3 | 1275.7 | 11,100.4 |
Median | 756.8 | 2885.5 | 1.3 | 1059.2 | 8017.6 |
Max | 4016.2 | 13,023.0 | 58.7 | 5265.0 | 42,719.5 |
Min | 19.2 | 154.0 | −0.8 | 60.0 | 194.9 |
SD | 973.8 | 3383.4 | 10.1 | 1225.7 | 10,107.9 |
Feature | ROC Cut Off | Se | Sp | Mean DFS/OS (Months) | p | HR (CI 95%) | p | |
---|---|---|---|---|---|---|---|---|
Group Superior to Cut-Off | Group Inferior to Cut-Off | |||||||
DSF analysis | ||||||||
GLRLM_RLNU | 7388.3 | 0.73 | 0.60 | 19.7 | 31.7 | 0.035 * | 0.402 | 0.041 * |
GLSZM_ZSNU | 1103.9 | 0.50 | 0.60 | 21.6 | 26.9 | 0.206 | - | - |
OS analysis | ||||||||
_Kurtosis | 1.8 | 0.66 | 0.71 | 44.3 | 68 | 0.053 | - | - |
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Travaglio Morales, D.; Huerga Cabrerizo, C.; Losantos García, I.; Coronado Poggio, M.; Cordero García, J.M.; Llobet, E.L.; Monachello Araujo, D.; Rizkallal Monzón, S.; Domínguez Gadea, L. Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer. Diagnostics 2023, 13, 3394. https://doi.org/10.3390/diagnostics13223394
Travaglio Morales D, Huerga Cabrerizo C, Losantos García I, Coronado Poggio M, Cordero García JM, Llobet EL, Monachello Araujo D, Rizkallal Monzón S, Domínguez Gadea L. Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer. Diagnostics. 2023; 13(22):3394. https://doi.org/10.3390/diagnostics13223394
Chicago/Turabian StyleTravaglio Morales, Daniela, Carlos Huerga Cabrerizo, Itsaso Losantos García, Mónica Coronado Poggio, José Manuel Cordero García, Elena López Llobet, Domenico Monachello Araujo, Sebastián Rizkallal Monzón, and Luis Domínguez Gadea. 2023. "Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer" Diagnostics 13, no. 22: 3394. https://doi.org/10.3390/diagnostics13223394