Prognostic values of ADCmean and SUVmax of the primary tumour in cervical cancer patients treated with definitive chemoradiotherapy.

We analysed the correlation of 18F-fluorodeoxyglucose uptake into primary tumours using the maximum standardised uptake value (SUVmax) and the mean apparent diffusion coefficient (ADCmean) values in magnetic resonance imaging (MRI) with the clinical and pathological factors in patients with cervical cancer who were treated with concurrent chemoradiotherapy. The patients were stratified according to the primary tumour pre-treatment ADCmean and SUVmax cut-off values. There were significant correlations between the SUVmax of the primary tumour and tumour size, and the treatment response. The correlation between the ADCmean and FIGO stage, tumour size, and the lymph node metastasis was significant. The SUVmax was significantly and inversely correlated with the ADCmean for cervical cancer (r = -0.44, p <.001). In the multivariate analysis, the primary tumour ADCmean, treatment response and the lymph node metastasis emerged as significant independent predictors of both OS and DFS, and of the primary tumour SUVmax for DFS. Tumour size has a borderline significance for OS. High SUVmax and low ADCmean of the primary tumour are important predictive factors for identifying high-risk patients with cervical cancer who are treated with definitive chemoradiotherapy. These results point to a future role for the diffusion-weighted MRI and for 18F-fluorodeoxyglucose positron emission tomography, not only in the staging of cervical cancer but as an aid in the selection of an adjuvant treatment regimen after chemoradiotherapy for individual patients. Impact statement What is already known on this subject? A negative correlation between primary tumour SUVmax derived from positron emission tomography (PET/CT) and ADCmin derived from diffusion weighted magnetic resonance imaging (DW-MRI) in various cancer types and cervical cancer has been demonstrated. However, the prognostic value of primary tumour SUVmax and ADCmean in cervical cancer patients treated with definitive chemoradiotherapy is not well studied yet. What the results of this study add? The patients with high-risk features (larger tumours, extensive stage, lymph node metastasis) had higher primary tumour SUVmax and lower ADCmean values. Primary tumour ADCmean and lymph node metastasis emerged as significant independent predictors of both overall and disease-free survival. This study demonstrated that the functional biomarkers delivered from PET-CT and DW-MRI are important in predicting the treatment outcomes in the squamous cell carcinoma of cervix treated with definitive chemoradiotherapy, where clinical and radiological findings are very important, since these patients are not staged surgically. What are the implications of these findings for clinical practice and/or further research? Based on these findings, there may be a future role of DW-MRI and FDG/PET-CT not only in the staging of cervical cancer but as an aid in the selection of an adjuvant treatment regimen after chemoradiotherapy (ChRT) for individual patients.

Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.

PURPOSE: This study investigated imaging biomarkers derived from PSMA-PET acquired pre- and post-metastasis-directed therapy (MDT) to predict 2-year metastasis-free survival (MFS), which provides valuable early response assessment to improve patient outcomes. MATERIALS/METHODS: An international cohort of 117 oligometastatic castration-sensitive prostate cancer (omCSPC) patients, comprising 34 from John Hopkins Hospital (JHH) and 83 from Baskent University (BU), were treated with stereotactic ablative radiation therapy (SABR) MDT with both pre- and post-MDT PSMA-PET/CT scans acquired. PET radiomic features were analyzed from a CT-PET fusion defined gross tumor volume ((GTV) or zone 1), and a 5 mm expansion ring area outside the GTV (zone 2). A total of 1748 PET radiomic features were extracted from these zones. The six most significant features selected using the Chi2 method, along with five clinical parameters (age, Gleason score, number of total lesions, untreated lesions, and pre-MDT prostate-specific antigen (PSA)) were extracted as inputs to the models. Various machine learning models, including Random Forest, Decision Tree, Support Vector Machine, and Naïve Bayesian, were employed for 2-year MFS prediction and tested using leave-one-out and cross-institution validation. RESULTS: Six radiomic features, including Total Energy, Entropy, and Standard Deviation from pre-PSMA-PET zone 1, Total Energy and Contrast from post-PSMA-PET zone 1, and Entropy from pre-PSMA-PET zone 2, along with five clinical parameters were selected for predicting 2-year MFS. In a leave-one-out test with all the patients, random forest achieved an accuracy of 80 % and an AUC of 0.82 in predicting 2-year MFS. In cross-institution validation, the model correctly predicted 2-year MFS events with an accuracy of 75 % and an AUC of 0.77 for patients from JHH, and an accuracy of 78 % and an AUC of 0.80 for BU patients, respectively. CONCLUSION: Our study demonstrated the promise of using pre- and post-MDT PSMA-PET-based imaging biomarkers for MFS prediction for omCSPC patients.

The role of stereotactic body radiotherapy in switching systemic therapy for patients with extracranial oligometastatic renal cell carcinoma

BackgroundTargeting oligometastatic lesions with metastasis-directed therapy (MDT) using stereotactic-body radiotherapy (SBRT) may improve treatment outcomes and postpone the need for second-line systemic therapy (NEST). We looked at the results of oligometastatic renal cell carcinoma (RCC) patients who had five or fewer lesions and were treated with SBRT.MethodsWe examined the treatment outcomes of 70 extracranial metastatic RCC (mRCC) patients treated at two oncology centers between 2011 and 2020. The clinical parameters of patients with and without NEST changes were compared. The prognostic factors for overall survival (OS), progression-free survival (PFS), and NEST-free survival were evaluated.ResultsMedian age was 67 years (range 31–83 years). Lung and bone metastasis were found in 78.4% and 12.6% of patients, respectively. With a median follow-up of 21.1 months, median OS was 49.1 months and the median PFS was 18.3 months. Histology was a prognostic factor for OS, BED, and treatment switch for PFS in univariate analysis. In multivariate analysis, the significant predictor of poor OS was clear cell histology, and a lower BED for PFS. Following SBRT for oligometastatic lesions, 19 patients (27.2%) had a median NEST change of 15.2 months after MDT completion. There were no significant differences in median OS or PFS between patients who had NEST changes and those who did not. No patient experienced grade ≥ 3 acute and late toxicities.ConclusionsThe SBRT to oligometastatic sites is an effective and safe treatment option for ≤ 5 metastases in RCC patients by providing favorable survival and delaying NEST change. (AU)