Prognostic value of textural features obtained from F-fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) in patients with locally advanced cervical cancer undergoing concurrent chemoradiotherapy

Is PET Radiomics Useful to Predict Pathologic Tumor Response and Prognosis in Locally Advanced Cervical Cancer?

This study investigated whether radiomic features extracted from pretreatment [18F]FDG PET could improve the prediction of both histopathologic tumor response and survival in patients with locally advanced cervical cancer (LACC) treated with neoadjuvant chemoradiotherapy followed by surgery compared with conventional PET parameters and histopathologic features. Methods: The medical records of all consecutive patients with LACC referred between July 2010 and July 2016 were reviewed. [18F]FDG PET/CT was performed before neoadjuvant chemoradiotherapy. Radiomic features were extracted from the primary tumor volumes delineated semiautomatically on the PET images and reduced by factor analysis. A receiver-operating-characteristic analysis was performed, and conventional and radiomic features were dichotomized with Liu's method according to pathologic response (pR) and cancer-specific death. According to the study protocol, only areas under the curve of more than 0.70 were selected for further analysis, including logistic regression analysis for response prediction and Cox regression analysis for survival prediction. Results: A total of 195 patients fulfilled the inclusion criteria. At pathologic evaluation after surgery, 131 patients (67.2%) had no or microscopic (≤3 mm) residual tumor (pR0 or pR1, respectively); 64 patients (32.8%) had macroscopic residual tumor (>3 mm, pR2). With a median follow-up of 76.0 mo (95% CI, 70.7-78.7 mo), 31.3% of patients had recurrence or progression and 20.0% died of the disease. Among conventional PET parameters, SUVmean significantly differed between pathologic responders and nonresponders. Among radiomic features, 1 shape and 3 textural features significantly differed between pathologic responders and nonresponders. Three radiomic features significantly differed between presence and absence of recurrence or progression and between presence and absence of cancer-specific death. Areas under the curve were less than 0.70 for all parameters; thus, univariate and multivariate regression analyses were not performed. Conclusion: In a large series of patients with LACC treated with neoadjuvant chemoradiotherapy followed by surgery, PET radiomic features could not predict histopathologic tumor response and survival. It is crucial to further explore the biologic mechanism underlying imaging-derived parameters and plan a large, prospective, multicenter study with standardized protocols for all phases of the process of radiomic analysis to validate radiomics before its use in clinical routine.

Development and validation of a 18F-FDG PET/CT radiomics nomogram for predicting progression free survival in locally advanced cervical cancer: a retrospective multicenter study

BACKGROUND

The existing staging system cannot meet the needs of accurate survival prediction. Accurate survival prediction for locally advanced cervical cancer (LACC) patients who have undergone concurrent radiochemotherapy (CCRT) can improve their treatment management. Thus, this present study aimed to develop and validate radiomics models based on pretreatment 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) images to accurately predict the prognosis in patients.

METHODS

The data from 190 consecutive patients with LACC who underwent pretreatment 18F-FDG PET-CT and CCRT at two cancer hospitals were retrospectively analyzed; 176 patients from the same hospital were randomly divided into training (n = 117) and internal validation (n = 50) cohorts. Clinical features were selected from the training cohort using univariate and multivariate Cox proportional hazards models; radiomic features were extracted from PET and CT images and filtered using least absolute shrinkage and selection operator and Cox proportional hazard regression. Three prediction models and a nomogram were then constructed using the previously selected clinical, CT and PET radiomics features. The external validation cohort that was used to validate the models included 23 patients with LACC from another cancer hospital. The predictive performance of the constructed models was evaluated using receiver operator characteristic curves, Kaplan Meier curves, and a nomogram.

RESULTS

In total, one clinical, one PET radiomics, and three CT radiomics features were significantly associated with progression-free survival in the training cohort. Across all three cohorts, the combined model displayed better efficacy and clinical utility than any of these parameters alone in predicting 3-year progression-free survival (area under curve: 0.661, 0.718, and 0.775; C-index: 0.698, 0.724, and 0.705, respectively) and 5-year progression-free survival (area under curve: 0.661, 0.711, and 0.767; C-index, 0.698, 0.722, and 0.676, respectively). On subsequent construction of a nomogram, the calibration curve demonstrated good agreement between actually observed and nomogram-predicted values.

CONCLUSIONS

In this study, a clinico-radiomics prediction model was developed and successfully validated using an independent external validation cohort. The nomogram incorporating radiomics and clinical features could be a useful clinical tool for the early and accurate assessment of long-term prognosis in patients with LACC patients who undergo concurrent chemoradiotherapy.

The prognostic value of FIGO staging defined by combining MRI and [18F]FDG PET/CT in patients with locally advanced cervical cancer

The last version of the FIGO classification recommended imaging tools to complete the clinical assessment of patients with cervical cancer. However, the preferable imaging approach is still unclear. We aimed to explore the prognostic power of Magnetic Resonance Imaging (MRI), contrast-enhanced Computed Tomography (ceCT), and [18F]-Fluorodeoxyglucose Positron Emission Tomography ([18F]FDG-PET)/CT in patients staged for locally advanced cervical cancer (LACC, FIGO stages IB3-IVA). Thirty-six LACC patients (mean age 55.47 ± 14.01, range 31-82) were retrospectively enrolled. All of them underwent MRI, ceCT and [18F]FDG-PET/CT before receiving concurrent chemoradiotherapy. A median dose of 45 Gy (range 42-50.4; 25-28 fractions, 5 fractions per week, 1 per day) was delivered through the external-beam radiation therapy (EBRT) on the pelvic area, while a median dose of 57.5 Gy (range 16-61.1; 25-28 fractions, 5 fractions per week, 1 per day) was administered on metastatic nodes. The median doses for brachytherapy treatment were 28 Gy (range 28-30; 4-5 fractions, 1 every other day). Six cycles of cisplatin or carboplatin were administered weekly. The study endpoints were recurrence-free survival (RFS) and overall survival (OS). Metastatic pelvic lymph nodes at MRI independently predicted RFS (HR 13.271, 95% CI 1.730-101.805; P = 0.027), while metastatic paraaortic lymph nodes at [18F]FDG-PET/CT independently predicted both RFS (HR 11.734, 95% CI 3.200-43.026; P = .005) and OS (HR 13.799, 95% CI 3.378-56.361; P < 0.001). MRI and [18F]FDG-PET/CT findings were incorporated with clinical evidences into the FIGO classification. With respect to the combination of clinical, MRI and ceCT data, the use of next-generation imaging (NGI) determined a stage migration in 10/36 (27.7%) of patients. Different NGI-based FIGO classes showed remarkably different median RFS (stage IIB: not reached; stage IIIC1: 44 months; stage IIIC2: 3 months; P < 0.001) and OS (stage IIB: not reached; stage IIIC1: not reached; stage IIIC2: 14 months; P < 0.001). A FIGO classification based on the combination of MRI and [18F]FDG-PET/CT might predict RFS and OS of LACC patients treated with concurrent chemoradiotherapy.