ESR Essentials: characterisation and staging of adnexal masses with MRI and CT-practice recommendations by ESUR.

Ovarian masses encompass various conditions, from benign to highly malignant, and imaging plays a vital role in their diagnosis and management. Ultrasound, particularly transvaginal ultrasound, is the foremost diagnostic method for adnexal masses. Magnetic Resonance Imaging (MRI) is advised for more precise characterisation if ultrasound results are inconclusive. The ovarian-adnexal reporting and data system (O-RADS) MRI lexicon and scoring system provides a standardised method for describing, assessing, and categorising the risk of each ovarian mass. Determining a histological differential diagnosis of the mass may influence treatment decision-making and treatment planning. When ultrasound or MRI suggests the possibility of cancer, computed tomography (CT) is the preferred imaging technique for staging. It is essential to outline the extent of the malignancy, guide treatment decisions, and evaluate the feasibility of cytoreductive surgery. This article provides a comprehensive overview of the key imaging processes in evaluating and managing ovarian masses, from initial diagnosis to initial treatment. It also includes pertinent recommendations for properly performing and interpreting various imaging modalities. KEY POINTS: MRI is the modality of choice for indeterminate ovarian masses at ultrasound, and the O-RADS MRI lexicon and score enable unequivocal communication with clinicians. CT is the recommended modality for suspected ovarian masses to tailor treatment and surgery. Multidisciplinary meetings integrate information and help decide the most appropriate treatment for each patient.

Patient satisfaction with ultrasound, whole-body CT and whole-body diffusion-weighted MRI for pre-operative ovarian cancer staging: a multicenter prospective cross-sectional survey.

BACKGROUND: In addition to the diagnostic accuracy of imaging methods, patient-reported satisfaction with imaging methods is important. OBJECTIVE: To report a secondary outcome of the prospective international multicenter Imaging Study in Advanced ovArian Cancer (ISAAC Study), detailing patients' experience with abdomino-pelvic ultrasound, whole-body contrast-enhanced computed tomography (CT), and whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) for pre-operative ovarian cancer work-up. METHODS: In total, 144 patients with suspected ovarian cancer at four institutions in two countries (Italy, Czech Republic) underwent ultrasound, CT, and WB-DWI/MRI for pre-operative work-up between January 2020 and November 2022. After having undergone all three examinations, the patients filled in a questionnaire evaluating their overall experience and experience in five domains: preparation before the examination, duration of examination, noise during the procedure, radiation load of CT, and surrounding space. Pain perception, examination-related patient-perceived unexpected, unpleasant, or dangerous events ('adverse events'), and preferred method were also noted. RESULTS: Ultrasound was the preferred method by 49% (70/144) of responders, followed by CT (38%, 55/144), and WB-DWI/MRI (13%, 19/144) (p<0.001). The poorest experience in all domains was reported for WB-DWI/MRI, which was also associated with the largest number of patients who reported adverse events (eg, dyspnea). Patients reported higher levels of pain during the ultrasound examination than during CT and WB-DWI/MRI (p<0.001): 78% (112/144) reported no pain or mild pain, 19% (27/144) moderate pain, and 3% (5/144) reported severe pain (pain score >7 of 10) during the ultrasound examination. We did not identify any factors related to patients' preferred method. CONCLUSION: Ultrasound was the imaging method preferred by most patients despite being associated with more pain during the examination in comparison with CT and WB-DWI/MRI. TRIAL REGISTRATION NUMBER: NCT03808792.

Perceptions of radiologists on structured reporting for cancer imaging-a survey by the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To assess radiologists' current use of, and opinions on, structured reporting (SR) in oncologic imaging, and to provide recommendations for a structured report template. MATERIALS AND METHODS: An online survey with 28 questions was sent to European Society of Oncologic Imaging (ESOI) members. The questionnaire had four main parts: (1) participant information, e.g., country, workplace, experience, and current SR use; (2) SR design, e.g., numbers of sections and fields, and template use; (3) clinical impact of SR, e.g., on report quality and length, workload, and communication with clinicians; and (4) preferences for an oncology-focused structured CT report. Data analysis comprised descriptive statistics, chi-square tests, and Spearman correlation coefficients. RESULTS: A total of 200 radiologists from 51 countries completed the survey: 57.0% currently utilized SR (57%), with a lower proportion within than outside of Europe (51.0 vs. 72.7%; p = 0.006). Among SR users, the majority observed markedly increased report quality (62.3%) and easier comparison to previous exams (53.5%), a slightly lower error rate (50.9%), and fewer calls/emails by clinicians (78.9%) due to SR. The perceived impact of SR on communication with clinicians (i.e., frequency of calls/emails) differed with radiologists' experience (p < 0.001), and experience also showed low but significant correlations with communication with clinicians (r = - 0.27, p = 0.003), report quality (r = 0.19, p = 0.043), and error rate (r = - 0.22, p = 0.016). Template use also affected the perceived impact of SR on report quality (p = 0.036). CONCLUSION: Radiologists regard SR in oncologic imaging favorably, with perceived positive effects on report quality, error rate, comparison of serial exams, and communication with clinicians. CLINICAL RELEVANCE STATEMENT: Radiologists believe that structured reporting in oncologic imaging improves report quality, decreases the error rate, and enables better communication with clinicians. Implementation of structured reporting in Europe is currently below the international level and needs society endorsement. KEY POINTS: • The majority of oncologic imaging specialists (57% overall; 51% in Europe) use structured reporting in clinical practice. • The vast majority of oncologic imaging specialists use templates (92.1%), which are typically cancer-specific (76.2%). • Structured reporting is perceived to markedly improve report quality, communication with clinicians, and comparison to prior scans.

Leiomyoma or sarcoma? MRI performance in the differential diagnosis of sonographically suspicious uterine masses.

PURPOSE: To assess the diagnostic performance of MRI in distinguishing between leiomyomas and malignant/potentially malignant mesenchymal neoplasms in patients with rapidly enlarging/sonographically suspicious uterine masses. METHODS: IRB-approved retrospective study including 88 patients (51 ± 11 years) who underwent MRI for rapidly enlarging/sonographically suspicious uterine mass at our Institution between January 2016 and December 2021, followed by surgery or >12 months follow-up. Qualitative image analysis was independently performed by 2 radiologists and included lesion's margins (sharp/irregular), architecture (homogeneous/inhomogeneous), presence of endometrial infiltration (yes/no), necrotic areas (yes/no), hemorrhagic areas (yes/no), predominant signal intensity on T1-WI, T2-WI, CE T1-WI, DWI, and ADC map. The same radiologists performed quantitative image analysis in consensus, which included lesion's maximum diameter, lesion/myometrium signal intensity ratio on T2-WI and CE T1-weighted images, lesion/endometrium signal intensity ratio on DWI and ADC map and necrosis percentage. Lesions were classified as benign or malignant. Imaging findings were compared with pathology and/or follow-up. RESULTS: After surgery (52/88 patients) or follow-up (36/88 patients, 33 ± 20 months), 83/88 (94.3%) lesions were classified as benign and 5/88 (5.7%) as malignant/potentially malignant. Presence of necrotic areas, high necrosis percentage, hyperintensity on DWI and high lesion/endometrium DWI signal intensity ratio were significantly associated with malignant/potentially malignant lesions (p = 0.027, 0.002, 0.008 and 0.015, respectively). The two readers identified malignant/potentially malignant lesions with 95.5% accuracy, 80.0% sensitivity, 96.4% specificity, 57.1 % PPV, 93.3% NPV. CONCLUSION: MRI has high accuracy in identifying malignant/potentially malignant myometrial masses. In everyday practice, however, MRI positive predictive value is relatively low given the low pre-test malignancy probability.

Predictive factors of surgical complications after pelvic exenteration for gynecological malignancies: a large single-institution experience.

OBJECTIVE: To evaluate pre-operative predictors of early (<30 days) severe complications (grade Dindo 3+) in patients with gynecological malignancy submitted to pelvic exenteration (PE). METHODS: We retrospectively analyzed 129 patients submitted to surgery at Fondazione Policlinico Gemelli between 2010 and 2019. We included patients affected by primary or recurrent/persistent cervical, endometrial, or vulvar/vaginal cancers. Post-operative complications were graded according to the Dindo classification. Logistic regression was used to analyze potential predictors of complications. RESULTS: We performed 63 anterior PE, 10 posterior PE, and 56 total PE. The incidence of early severe post-operative complications was 27.9% (n=36), and the early mortality rate was 2.3% (n=3). More frequent complications were related to the urinary diversion and intestinal surgery. In univariable analysis, hemoglobin ≤10 g/dL (odds ratio [OR]=4.2; 95% confidence interval [CI]=1.65-10.7; p=0.003), low albumin levels (OR=3.9; 95% CI=1.27-12.11; p=0.025), diabetes (OR=4.15; 95% CI=1.22-14.1; p=0.022), 2+ comorbidities at presentation (OR=5.18; 95% CI=1.49-17.93; p=0.012) were predictors of early severe complications. In multivariable analysis, only low hemoglobin and comorbidities at presentation were independent predictors of complications. CONCLUSION: Pelvic exenteration is an aggressive surgery characterized by a high rate of post-operative complications. Pre-operative assessment of comorbidities and patient health status are crucial to better select the right candidate for this type of surgery.

Prediction of the Risk of Malignancy of Adnexal Masses during Pregnancy Comparing Subjective Assessment and Non-Contrast MRI Score (NCMS) in Radiologists with Different Expertise.

Ovarian cancer represents 7% of all cancers in pregnant women. Characterising an ovarian mass during pregnancy is essential to avoid unnecessary treatment and, if treatment is required, to plan it accordingly. Although ultrasonography (US) is the first-line modality to characterise adnexal masses, MRI is indicated when adnexal masses are indeterminate at the US examination. An MRI risk stratification system has been proposed to assign a malignancy probability based on the adnexal lesion's MRI, but features of the scoring system require the administration of intravenous gadolinium-based contrast agents, a method that might have a limited use in pregnant women. The non-contrast MRI score (NCMS) has been used and evaluated in non-pregnant women to characterise adnexal masses indeterminate at the US examination. Therefore, we evaluated the diagnostic accuracy of the NCMS in pregnant women, analysing 20 cases referred to our specialised institution. We also evaluated the diagnostic agreement between two radiologists with different expertise. The two readers classified ovarian masses as benign or malignant using both subjective assessment (SA), based on the interpretive evaluation of imaging findings derived from personal experience, and the NCMS, which includes five categories where 4 and 5 indicate a high probability of a malignant mass. The expert radiologist correctly classified 90% of the diagnoses, using both SA and the NCMS, relying on a sensitivity of 85.7% and a specificity of 92.3%, with a false positive rate of 7.7% and a false negative rate of 14.3%. The non-expert radiologist correctly identified patients at a lower rate, especially using the SA. The analysis of the inter-observer agreement showed a K = 0.47 (95% CI: 0.48-0.94) for the SA (agreement in 71.4% of cases) and a K = 0.8 (95% CI: 0.77-1.00) for the NCMS (agreement in 90% of cases). Although in pregnant patients, non-contrast MRI is used, our results support the use of a quantitative score, i.e., the NCMS, as an accurate tool. This procedure may help less experienced radiologists to reduce the rate of false negatives or positives, especially in centres not specialised in gynaecological imaging, making the MRI interpretation easier and more accurate for radiologists who are not experts in the field, either.

Ovarian cancer beyond imaging: integration of AI and multiomics biomarkers.

High-grade serous ovarian cancer is the most lethal gynaecological malignancy. Detailed molecular studies have revealed marked intra-patient heterogeneity at the tumour microenvironment level, likely contributing to poor prognosis. Despite large quantities of clinical, molecular and imaging data on ovarian cancer being accumulated worldwide and the rise of high-throughput computing, data frequently remain siloed and are thus inaccessible for integrated analyses. Only a minority of studies on ovarian cancer have set out to harness artificial intelligence (AI) for the integration of multiomics data and for developing powerful algorithms that capture the characteristics of ovarian cancer at multiple scales and levels. Clinical data, serum markers, and imaging data were most frequently used, followed by genomics and transcriptomics. The current literature proves that integrative multiomics approaches outperform models based on single data types and indicates that imaging can be used for the longitudinal tracking of tumour heterogeneity in space and potentially over time. This review presents an overview of studies that integrated two or more data types to develop AI-based classifiers or prediction models.Relevance statement Integrative multiomics models for ovarian cancer outperform models using single data types for classification, prognostication, and predictive tasks.Key points• This review presents studies using multiomics and artificial intelligence in ovarian cancer.• Current literature proves that integrative multiomics outperform models using single data types.• Around 60% of studies used a combination of imaging with clinical data.• The combination of genomics and transcriptomics with imaging data was infrequently used.

The Utility of Contrast-Enhanced Magnetic Resonance Imaging in Uterine Cervical Cancer: A Systematic Review.

Correct staging of cervical cancer is essential to establish the best therapeutic procedure and prognosis for the patient. MRI is the best imaging modality for local staging and follow-up. According to the latest ESUR guidelines, T2WI and DWI-MR sequences are fundamental in these settings, and CE-MRI remains optional. This systematic review, according to the PRISMA 2020 checklist, aims to give an overview of the literature regarding the use of contrast in MRI in cervical cancer and provide more specific indications of when it may be helpful. Systematic searches on PubMed and Web Of Science (WOS) were performed, and 97 papers were included; 1 paper was added considering the references of included articles. From our literature review, it emerged that many papers about the use of contrast in cervical cancer are dated, especially about staging and detection of tumor recurrence. We did not find strong evidence suggesting that CE-MRI is helpful in any clinical setting for cervical cancer staging and detection of tumor recurrence. There is growing evidence that perfusion parameters and perfusion-derived radiomics models might have a role as prognostic and predictive biomarkers, but the lack of standardization and validation limits their use in a research setting.

Radiomics and Radiogenomics of Ovarian Cancer: Implications for Treatment Monitoring and Clinical Management.

Ovarian cancer, one of the deadliest gynecologic malignancies, is characterized by high intra- and inter-site genomic and phenotypic heterogeneity. The traditional information provided by the conventional interpretation of diagnostic imaging studies cannot adequately represent this heterogeneity. Radiomics analyses can capture the complex patterns related to the microstructure of the tissues and provide quantitative information about them. This review outlines how radiomics and its integration with other quantitative biological information, like genomics and proteomics, can impact the clinical management of ovarian cancer.

Myosteatosis as an independent predictor of short-term mortality in successfully reperfused acute ischemic stroke.

BACKGROUND AND PURPOSE: Poor clinical outcomes are still common in successfully reperfused acute ischemic stroke patients. The aim of our study was to assess the impact of sarcopenia and myosteatosis on neurological outcomes and mortality in successfully reperfused acute ischemic stroke patients. MATERIALS AND METHODS: We included in our retrospective observational study 166 consecutive patients who underwent technically successful mechanical thrombectomy for anterior circulation acute ischemic stroke between Jan 2016 and Dec 2019. ASPECTS and collateral score were assessed on pre-operative CT/CTA. Masseter muscles area and attenuation were measured on CTA images. Clinical and radiological variables were tested in multivariate logistic models to predict the probability of death and, among survivors, of incurring poor outcome. RESULTS: At admission, mean NIHSS was 19 (SD = 6.5), mean body mass index 25.5 (SD = 4.4) kg/m2, and mean ASPECTS 8.0 (SD = 1.9). Of all, 48.2% patients showed good collaterals, 38.5% intermediate collaterals, and 13.3% poor collaterals. Overall, 90 days mRS was ≤2 in 48.2% of the patients, 3-5 in 30.7%, and 6 in 21.1%. At multivariate logistic regression, age (OR = 1.08, p = 0.036), ASPECTS (OR = 0.59, p = 0.013), and masseter muscles attenuation (OR = 0.93, p = 0.010) were independent predictors of mortality, whereas sex (OR = 7.15, p = 0.043), age (OR = 1.05, p = 0.042), body mass index (OR = 1.35, p = 0.013), NIHSS (OR = 1.12, p = 0.012), and ASPECTS (OR = 0.64, p = 0.024) were independent predictors of poor neurological outcome (mRS 3-5). CONCLUSION: Beyond other well-known variables, low masseter attenuation, indicating myosteatosis, represents an independent negative prognostic factor for 90 days mortality in patients successfully reperfused after anterior circulation stroke.

Trabectedin plus pegylated liposomal doxorubicin in patients with disease progression after PARP inhibitor maintenance: a real-life case-control study.

OBJECTIVE: Poly (ADP-ribose) polymerase (PARP) inhibitor resistance is problematic in epithelial ovarian cancer management and sequencing strategies may be performed to overcome this issue. In this context, our study evaluated the role of non-platinum doublet pegylated liposomal doxorubicin/trabectedin in ovarian cancer platinum-sensitive patients who experienced disease progression under PARP inhibitor maintenance. METHODS: This case-control study includes patients with recurrent epithelial ovarian cancer treated between March 2016 and April 2021 who progressed under PARP inhibitor maintenance. Data of patients treated with pegylated liposomal doxorubicin/trabectedin (experimental group) were matched 1:1 with a series of patients who received platinum-based treatment (control group). The study outcomes were overall clinical benefit (including complete, partial, and stable response), progression-free survival, and overall survival. The safety of both treatments was also evaluated. RESULTS: A total of 26 patients in both groups were analyzed. Clinical benefit was achieved in 15 (57%) patients in the study group and 17 (65%) patients in the control group (p=0.38). Patients receiving pegylated liposomal doxorubicin/trabectedin had 5 months of progression-free survival, compared with 5 months in patients treated with platinum-based treatment (p=0.62). Patients in the experimental group achieved a median overall survival of 16 months compared with 19 months in the control group (p=0.26) There was no difference concerning severe toxicities (G3-G4) between groups, except for hepatic toxicity, which was experienced in 30% of the patients receiving pegylated liposomal doxorubicin/trabectedin and none in the control group (p<0.009). CONCLUSIONS: Pegylated liposomal doxorubicin/trabectedin might be an alternative option to platinum-based treatment in patients experiencing disease progression during PARP inhibitor maintenance with an acceptable toxicity profile. This might be a therapeutic option in this setting, sparing platinum compounds for subsequent relapse.

Fetal MRI prior to intrauterine surgery of open neural tube defects: What does the radiologist need to know.

The management of myelomeningocele study trial showed significant prognostic improvement in fetal repair before 26 weeks of gestation. Hence, surgery in utero represents the best treatment option for open-neural tube defects (NTDs). Fetal surgery of open-NTDs has specific inclusion and exclusion criteria, which can be adequately studied with fetal MRI. The main concern: the spine (spinal defects other than Myelomeningocele and Myeloschisis, the level of the lesion higher than T1 or lower than S1 and the degree of kyphosis ≥ 30°), the skull/brain (no cerebellum herniation and Chiari II malformation and the presence of any intracranial abnormality unrelated to open NTDs), the uterus (cervix length less than 2 cm, multiple gestations and placental and uterine abnormalities) and any other fetal abnormality not attributed to spinal defect. In this review, we describe the fundamental role of fetal MRI in supporting therapeutic decisions in pre-surgery intrauterine planning through the accurate and comprehensive description of findings, providing a proposal of a structured report. In addition, we describe how post-surgical MRI is important in investigating the effectiveness of surgery and detecting repairing complications.

Preoperative Tumor Texture Analysis on MRI for High-Risk Disease Prediction in Endometrial Cancer: A Hypothesis-Generating Study.

OBJECTIVE: To develop and validate magnetic resonance (MR) imaging-based radiomics models for high-risk endometrial cancer (EC) prediction preoperatively, to be able to estimate deep myometrial invasion (DMI) and lymphovascular space invasion (LVSI), and to discriminate between low-risk and other categories of risk as proposed by ESGO/ESTRO/ESP (European Society of Gynaecological Oncology-European Society for Radiotherapy & Oncology and European Society of Pathology) guidelines. METHODS: This retrospective study included 96 women with EC who underwent 1.5-T MR imaging before surgical staging between April 2009 and May 2019 in two referral centers divided into training (T = 73) and validation cohorts (V = 23). Radiomics features were extracted using the MODDICOM library with manual delineation of whole-tumor volume on MR images (axial T2-weighted). Diagnostic performances of radiomic models were evaluated by area under the receiver operating characteristic (ROC) curve in training (AUCT) and validation (AUCV) cohorts by using a subset of the most relevant texture features tested individually in univariate analysis using Wilcoxon-Mann-Whitney. RESULTS: A total of 228 radiomics features were extracted and ultimately limited to 38 for DMI, 29 for LVSI, and 15 for risk-classes prediction for logistic radiomic modeling. Whole-tumor radiomic models yielded an AUCT/AUCV of 0.85/0.68 in DMI estimation, 0.92/0.81 in LVSI prediction, and 0.84/0.76 for differentiating low-risk vs other risk classes (intermediate/high-intermediate/high). CONCLUSION: MRI-based radiomics has great potential in developing advanced prognostication in EC.

Magnetic resonance imaging in cervical cancer interventional radiotherapy (brachytherapy): a pictorial essay focused on radiologist management.

The standard treatment for locally advanced cervical cancer (LACC) is platinum-based chemotherapy in association with external beam radiotherapy (EBRT) and brachytherapy (BT), often also called 'interventional radiotherapy' (IRT). Magnetic resonance imaging (MRI) is the most accurate imaging modality for both staging and response evaluation; therefore MRI-guided IRT has become the method of choice for planning a radiation boost after EBRT. The aim of this paper was to describe the MRI radiological workflow currently ongoing at our Institution. In addition, we provided a detailed pictorial essay of our experience, especially for radiologists, to implement MRI-based IRT spread in clinical practice.

The role of apparent diffusion coefficient (ADC) in the evaluation of lymph node status in patients with locally advanced cervical cancer: our experience and a review.

Purpose: To evaluate the role of apparent diffusion coefficient (ADC) value measurement in the diagnosis of meta-static lymph nodes (LNs) in patients with locally advanced cervical cancer (LACC) and to present a systematic review of the literature. Material and methods: Magnetic resonance imaging (MRI) exams of patients with LACC were retrospectively eva-luated. Mean ADC, relative ADC (rADC), and correct ADC (cADC) values of enlarged LNs were measured and compared between positron emission tomography (PET)-positive and PET-negative LNs. Comparisons were made using the Mann-Whitney U-test and Student's t-test. ROC curves were generated for each parameter to identify the optimal cut-off value for differentiation of the LNs. A systematic search in the literature was performed, exploring several databases, including PubMed, Scopus, the Cochrane library, and Embase. Results: A total of 105 LNs in 34 patients were analysed. The median ADC value of PET-positive LNs (0.907 × 10-3 mm2/s [0.780-1.080]) was lower than that in PET-negative LNs (1.275 × 10-3 mm2/s [1.063-1.525]) (p < 0.05). rADC and cADC values were lower in PET-positive LNs (rADC: 0.120 × 10-3 mm2/s [-0.060-0.270]; cADC: 1.130 [0.980-1.420]) than in PET-negative LNs (rADC: 0.435 × 10-3 mm2/s [0.225-0.673]; cADC: 1.615 [1.210-1.993]) LNs (p < 0.05). ADC showed the highest area under the curve (AUC 0.808). Conclusions: Mean ADC, rADC, and cADC were significantly lower in the PET-positive group than in the PET-negative group. The ADC cut-off value of 1.149 × 10-3 mm2/s showed the highest sensitivity. These results confirm the usefulness of ADC in differentiating metastatic from non-metastatic LNs in LACC.

Features of cystadenofibroma on magnetic resonance imaging: an update using the O-RADS lexicon and considering diffusion-weighted and perfusion imaging.

PURPOSE: Cystadenofibroma (CAF) is a rare tumour of the ovary that can be confused with a borderline or malignant lesion due to its morphological characteristics. The study aims to analyse the MRI (magnetic resonance imaging) features of histologically proven ovarian cystadenofibromas according to lexicon-based and O-RADS (Ovarian-Adnexal Reporting and Data System) descriptors, with particular attention to time-intensity curves (TIC) and Diffusion-Weighted sequences (DWI); we also wanted to test the performance of O-RADS MRI risk stratification system in this particular subgroup of patients. METHODS: We have included all patients who performed MR between October 2019 and December 2021 after an inconclusive trans-vaginal ultrasound. All patients underwent surgery with histological results of CAF. According to the O-RADS lexicon, we reported the morphological characteristics of each lesion and their appearance in the perfusion-weighted imaging (PWI) and DWI sequences. We assessed the risk of malignancy for each lesion through O-RADS MRI score. RESULTS: Twenty-one histologically proven CAF were analysed, of which 20 benign and one borderline with degeneration into adenocarcinoma. We described the typical morphological characteristics of CAF according to lexicon-based and O-RADS descriptors. Analysis of time-intensity curves (TIC) in PWI sequences showed a slow and progressive enhancement of solid tissue (type I curve), configuring an O-RADS score of 2 or 3, except for the only malignant lesion that showed a type II curve and restriction in DWI (O-RADS 4). CONCLUSIONS: Our study is the largest comprising PWI and DWI sequences, highlighting their pivotal role. O-RADS score correctly classified the masses as benign or malignant.

Management of oligometastatic ovarian cancer recurrence during PARP inhibitor maintenance.

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.

CT-Based Radiomics and Deep Learning for BRCA Mutation and Progression-Free Survival Prediction in Ovarian Cancer Using a Multicentric Dataset.

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.

MRI in uterine cancers with uncertain origin: Endometrial or cervical? Radiological point of view with review of the literature.

Therapeutic options and clinical management of cervical and endometrial cancers differs significantly. When clinical and histological analysis of a uterine mass are unable to differentiate between an endocervical or endometrial origin, magnetic resonance imaging (MRI) plays a pivotal role in discriminating the anatomical origin, supporting the clinician in the treatment planning. Cervical adenocarcinomas are more likely to be centered in the cervical region and involving both cervical canal and stromal ring, with possible parametrial invasion. Endometrial adenocarcinomas usually present an elongated morphology and are centered in the endometrial cavity predominantly involving endometrium and myometrium. On contrast-enhanced sequences, cervical cancers are more frequently hypervascular compared to endometrial cancers. In cases of uncertain findings, diffusion-weighted imaging (DWI) can provide additional helpful information with significantly higher apparent coefficient diffusion (ADC) values in cervical adenocarcinomas compared to endometrial adenocarcinomas. However, even when MRI cannot precisely reveal the origin of the tumor, it provides valuable information on several prognostic factors that can help treatment planning.

Correlation between FA and ADC, number and length of the periprostatic neurovascular fibers.

PURPOSE: Our aim was to explore the relation between FA and ADC, number and length of the periprostatic neurovascular fibers (PNF) by means of 1.5 T Diffusion Tensor Imaging (DTI) imaging through a multivariate linear regression analysis model. METHODS: For this retrospective study, 56 patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including DTI, were enrolled between October 2014 and December 2018. Multivariate regression analysis was performed to evaluate the statistically significant correlation between FA values (dependent variable) and ADC, the number and the length of PNF (independent variables), if p-value <0.05. A value of 0.5 indicated poor agreement; 0.5-0.75, moderate agreement; 0.75-0.9, good agreement; 0.61-0.80, good agreement; and 0.9-1.00, excellent agreement. RESULTS: The overall fit of the multivariate regression model was excellent, with R2 value of 0.9445 (R2 adjusted 0.9412; p < 0.0001). Multivariate linear regression analysis showed a statistically significant correlation (p < 0.05) for all the three independent variables. The r partial value was -0.9612 for ADC values (p < 0.0001), suggesting a strong negative correlation, 0.4317 for the number of fiber tracts (p < 0.001), suggesting a moderate positive correlation, and -0.306 for the length of the fiber tracts (p < 0.05), suggesting a weak negative correlation. CONCLUSIONS: Our multivariate linear regression model has demonstrated a statistically significant correlation between FA values of PNF with other DTI parameters, in particular with ADC.