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Purpose The aim of this study is to determine if radiomics features extracted from staging magnetic resonance (MR) images could predict 2-year long-term clinical outcome in patients with locally advanced cervical cancer (LACC) after neoadjuvant chemoradiotherapy (NACRT). Materials and methods We retrospectively enrolled patients with LACC diagnosis who underwent NACRT followed by radical surgery in two different institutions. Radiomics features were extracted from pre-treatment 1.5 T T2w MR images. The predictive performance of each feature was quantified in terms of Wilcoxon–Mann–Whitney test. Among the significant features, Pearson correlation coefficient (PCC) was calculated to quantify the correlation among the different predictors. A logistic regression model was calculated considering the two most significant features at the univariate analysis showing the lowest PCC value. The predictive performance of the model created was quantified out using the area under the receiver operating characteristic curve (AUC). Results A total of 175 patients were retrospectively enrolled (142 for the training cohort and 33 for the validation one). 1896 radiomic feature were extracted, 91 of which showed significance (p < 0.05) at the univariate analysis. The radiomic model showing the highest predictive value combined the features calculated starting from the gray level co-occurrence-based features. This model achieved an AUC of 0.73 in the training set and 0.91 in the validation set. Conclusions The proposed radiomic model showed promising performances in predicting 2-year overall survival before NACRT. Nevertheless, the observed results should be tested in larger studies with consistent external validation cohorts, to confirm their potential clinical use.

PurposeTo compare the survival and toxicity outcomes in patients with endometrial cancer treated with either high-dose-rate (HDR) or low-dose-rate (LDR) vaginal brachytherapy (VBT) following external beam radiotherapy (EBRT).Material and methodsFrom January 2000 to December 2014, patients with endometrial cancer after radical hysterectomy with/without pelvic and/or para-aortic lymphadenectomy were treated with adjuvant EBRT (45 Gy, 1.8 Gy/day to the whole pelvis) and subsequent VBT boost (HDR dose of 7 Gy in one fraction or LDR VBT dose of 25 Gy). The dose was prescribed at 0.5 cm from the surface of the applicator and the proximal half to two-thirds of the vagina was irradiated. The outcomes of patients were evaluated in terms of local control (LC), overall survival (OS), and rates of adverse events.ResultsWe analyzed data of 200 patients treated with EBRT followed by HDR VBT boost in 78 patients and LDR VBT boost in 122 patients. With a median follow-up of 25 months (range, 6-163), 5-year OS was 98% and 97% in the LDR and HDR groups, respectively (p = 0.37). The 5-year LC was similar (93% in both groups) (p = 0.81). In multivariate analyses, none of the factors assessed (age, stage, grade) impacted OS (p = 0.37) or LC (p = 0.81). Patients treated with LDR VBT after EBRT had higher rates of acute gastrointestinal toxicity. No differences were found in acute genitourinary or hematological toxicities. Late toxicity such as vaginal stenosis was registered during regular follow-up visits and was similar in the two groups (p = 0.67).ConclusionsIn our analysis, there were no differences in terms of OS and late toxicity outcomes for patients receiving LDR or HDR VBT. HDR VBT is a safe technique in comparison to LDR VBT.

The aim of this study was to create a radiomics model for Locally Advanced Cervical Cancer (LACC) patients to predict pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NACRT) analysing T2-weighted 1.5 T magnetic resonance imaging (MRI) acquired before treatment start. Patients with LACC and an International Federation of Gynecology and Obstetrics stage from IB2 to IVA at diagnosis were retrospectively enrolled for this study. All patients underwent NACRT, followed by radical surgery; pCR―assessed on surgical specimen―was defined as absence of any residual tumour. Finally, 1889 features were extracted from MR images; features showing statistical significance in predicting pCR at the univariate analysis were selected following an iterative method, which was ad-hoc developed for this study. Based on this method, 15 different classifiers were trained considering the most significant features selected. Model selection was carried out using the area under the receiver operating characteristic curve (AUC) as target metrics. One hundred eighty-three patients from two institutions were analysed. The model, showing the highest performance with an AUC of 0.80, was the random forest method initialised with default parameters. Radiomics appeared to be a reliable tool in pCR prediction for LACC patients undergoing NACRT, supporting the identification of patient risk groups, which paves treatment pathways tailored according to the predicted outcome.

Background: Recent studies have highlighted the potentialities of a radiobiological parameter, the early regression index (ERITCP), in the treatment response prediction for rectal cancer patients treated with chemoradiotherapy followed by surgery. The aim of this study is to evaluate the performance of this parameter in predicting pathological complete response (pCR) in the context of low field MR guided radiotherapy (MRgRT) for cervical cancer (CC). Methods: A total of 16 patients affected by CC were enrolled. All patients underwent a MRgRT treatment, with prescription of 50.6 Gy in 22 fractions. A daily MR acquisition was performed at simulation and on each treatment fraction. Gross tumor volume (GTV) was delineated on the MR images acquired at the following biological effective dose (BED) levels: 14, 28, 42, 54 and 62 Gy. The ERITCP was calculated at the different BED levels and its predictive performance was quantified in terms of receiver operating characteristic (ROC) curve. Results: pCR was observed in 11/16 cases. The highest discriminative power of ERITCP was reported when a BED value of 28 Gy is reached, obtaining an area under curve (AUC) of 0.84. Conclusion: This study confirmed ERITCP as a promising response biomarker also for CC, although further studies with larger cohort of patients are recommended.