The five-year survival rate of epithelial ovarian cancer (EOC) is approximately 35–40% despite maximal treatment efforts, highlighting a need for stratification biomarkers for personalized treatment. Here we extract 657 quantitative mathematical descriptors from the preoperative CT images of 364 EOC patients at their initial presentation. Using machine learning, we derive a non-invasive summary-statistic of the primary ovarian tumor based on 4 descriptors, which we name “Radiomic Prognostic Vector” (RPV). RPV reliably identifies the 5% of patients with median overall survival less than 2 years, significantly improves established prognostic methods, and is validated in two independent, multi-center cohorts. Furthermore, genetic, transcriptomic and proteomic analysis from two independent datasets elucidate that stromal phenotype and DNA damage response pathways are activated in RPV-stratified tumors. RPV and its associated analysis platform could be exploited to guide personalized therapy of EOC and is potentially transferrable to other cancer types.

Purpose: Build predictive radiomic models for early relapse and BRCA mutation based on a multicentric database of high-grade serous ovarian cancer (HGSOC) and validate them in a test set coming from different institutions. Methods: Preoperative CTs of patients with HGSOC treated at four referral centers were retrospectively acquired and manually segmented. Hand-crafted features and deep radiomics features were extracted respectively by dedicated software (MODDICOM) and a dedicated convolutional neural network (CNN). Features were selected with and without prior harmonization (ComBat harmonization), and models were built using different machine learning algorithms, including clinical variables. Results: We included 218 patients. Radiomic models showed low performance in predicting both BRCA mutation (AUC in test set between 0.46 and 0.59) and 1-year relapse (AUC in test set between 0.46 and 0.56); deep learning models demonstrated similar results (AUC in the test of 0.48 for BRCA and 0.50 for relapse). The inclusion of clinical variables improved the performance of the radiomic models to predict BRCA mutation (AUC in the test set of 0.74). Conclusions: In our multicentric dataset, representative of a real-life clinical scenario, we could not find a good radiomic predicting model for PFS and BRCA mutational status, with both traditional radiomics and deep learning, but the combination of clinical and radiomic models improved model performance for the prediction of BRCA mutation. These findings highlight the need for standardization through the whole radiomic pipelines and robust multicentric external validations of results.

Objective The benefit of surgery and maintenance treatment with PARP inhibitors (PARPi) has been clearly demonstrated in ovarian cancer. Also, the efficacy and safety of stereotactic body radiotherapy has been shown in patients with metastatic, persistent, and recurrent disease. The aim of this study is to evaluate the management of oligometastatic progression during PARPi maintenance treatment. Methods This is an observational, retrospective, single-arm study conducted from June 2017 to December 2020 in patients with recurrent ovarian cancer with oligometastatic progression under PARPi maintenance treatment and receiving surgery or stereotactic body radiotherapy for such recurrence. PARPi treatment was continued until further progression of the disease. The primary objective of the study was the median prolongation of the treatment-free interval-p (without platinum) after local treatment. Results A total of 186 patients with ovarian cancer were treated with PARPi at recurrence. Of these, 30 (16%) developed oligometastatic progression. The median age was 49.5 years (range 35–73). Olaparib, niraparib and rucaparib were administered to 33%, 60%, and 7% of patients, respectively. The median prolongation of the treatment-free interval-p of patients treated with surgery or stereotactic body radiotherapy was 6 and 10 months, respectively (p=0.53). The median treatment-free interval-p of patients treated with surgery or stereotactic body radiotherapy at the time of oligometastatic progression was 32 and 29 months, respectively (p=0.44). At the time of this publication, 50% of patients are still on treatment with PARPi following progression. Conclusions Patients with recurrent ovarian cancer who have oligometastic progression during PARPi maintenance may continue to benefit from PARPi if combined with local treatment.

Objective: To provide up-to-date European Society of Urogenital Radiology (ESUR) guidelines for staging and follow-up of patients with ovarian cancer (OC). Methods: Twenty-one experts, members of the female pelvis imaging ESUR subcommittee from 19 institutions, replied to 2 rounds of questionnaires regarding imaging techniques and structured reporting used for pre-treatment evaluation of OC patients. The results of the survey were presented to the other authors during the group’s annual meeting. The lexicon was aligned with the Society of American Radiology (SAR)-ESUR lexicon; a first draft was circulated, and then comments and suggestions from the other authors were incorporated. Results: Evaluation of disease extent at diagnosis should be performed by chest, abdominal, and pelvic CT. The radiological report should map the disease with specific mention of sites that may preclude optimal cytoreductive surgery. For suspected recurrence, CT and [¹⁸F]FDG PET-CT are both valid options. MRI can be considered in experienced centres, as an alternative to CT, considering the high costs and the need for higher expertise in reporting. Conclusions: CT is the imaging modality of choice for preoperative evaluation and follow-up in OC patients. A structured radiological report, including specific mention of sites that may preclude optimal debulking, is of value for patient management. Key Points: Question Guidelines were last published for ovarian cancer (OC) imaging in 2010; here, guidance on imaging techniques and reporting, incorporating advances in the field, are provided. Findings Structured reports should map out sites of disease, highlighting sites that limit cytoreduction. For suspected recurrence, CT and 18FDG PET-CT are options, and MRI can be considered. Clinical relevance Imaging evaluation of OC patients at initial diagnosis (mainly based on CT), using a structured report that considers surgical needs is valuable in treatment selection and planning.