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Primary aldosteronism (PA) due to a unilateral aldosterone-producing adenoma is a common cause of hypertension. This can be cured, or greatly improved, by adrenal surgery. However, the invasive nature of the standard pre-surgical investigation contributes to fewer than 1% of patients with PA being offered the chance of a cure. The primary objective of our prospective study of 143 patients with PA ( NCT02945904 ) was to compare the accuracy of a non-invasive test, [ 11 C]metomidate positron emission tomography computed tomography (MTO) scanning, with adrenal vein sampling (AVS) in predicting the biochemical remission of PA and the resolution of hypertension after surgery. A total of 128 patients reached 6- to 9-month follow-up, with 78 (61%) treated surgically and 50 (39%) managed medically. Of the 78 patients receiving surgery, 77 achieved one or more PA surgical outcome criterion for success. The accuracies of MTO at predicting biochemical and clinical success following adrenalectomy were, respectively, 72.7 and 65.4%. For AVS, the accuracies were 63.6 and 61.5%. MTO was not significantly superior, but the differences of 9.1% (95% confidence interval = −6.5 to 24.1%) and 3.8% (95% confidence interval = −11.9 to 9.4) lay within the pre-specified −17% margin for non-inferiority ( P  = 0.00055 and P  = 0.0077, respectively). Of 24 serious adverse events, none was considered related to either investigation and 22 were fully resolved. MTO enables non-invasive diagnosis of unilateral PA. Comparison of non-invasive [ 11 C]metomidate PET-CT with adrenal vein sampling for predicting biochemical remission of primary aldosteronism showed non-superiority, suggesting that the non-invasive method is suitable for the diagnosis of unilateral primary aldosteronism.

High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. We use an ensemble machine learning model trained to predict the change in total disease volume using data obtained at diagnosis ( n  = 72). The model is validated in an internal hold-out cohort ( n  = 20) and an independent external patient cohort ( n  = 42). In the external cohort the integrated radiomics model reduces the prediction error by 8% with respect to the clinical model, achieving an AUC of 0.78 for RECIST 1.1 classification compared to 0.47 for the clinical model. Our results emphasize the value of including radiomics data in integrative models of treatment response and provide methods for developing new biomarker-based clinical trials of NACT in HGSOC. Response to treatment in high grade serous ovarian carcinoma (HGSOC) is highly variable. Here, the authors leverage a radiogenomic model to predict neoadjuvant chemotherapy response in HGSOC, including clinical data, medical imaging, and blood-based biomarkers such as CA-125 and ctDNA features.

Abstract Context In primary aldosteronism, cosecretion of cortisol may alter cortisol-derived adrenal venous sampling indices. Objective To identify whether cortisol cosecretion in primary aldosteronism alters adrenal venous sampling parameters and interpretation. Design Retrospective case–control study Setting A tertiary referral center Patients 144 adult patients with primary aldosteronism who had undergone both adrenocorticotropic hormone-stimulated adrenal venous sampling and dexamethasone suppression testing between 2004 and 2018. Main Outcome Measures Adrenal venous sampling indices including adrenal vein aldosterone/cortisol ratios and the selectivity, lateralization, and contralateral suppression indices. Results 21 (14.6%) patients had evidence of cortisol cosecretion (defined as a failure to suppress cortisol to ≤50 nmol/L post dexamethasone). Patients with evidence of cortisol cosecretion had a higher inferior vena cava cortisol concentration (P = .01) than those without. No difference was observed between the groups in terms of selectivity index, lateralization index, lateralization of aldosterone excess, or adrenal vein cannulation rate. Conclusions Cortisol cosecretion alters some parameters in adrenocorticotrophic hormone-stimulated adrenal venous sampling but does not result in alterations in patient management.

Background The germ cell supranetwork multidisciplinary team (SMDT) for the Anglian Network covers a population of 7.5 million. Methods We reviewed 10 years of SMDT discussion and categorised them into five domains ((1) overall outcome, (2) chemotherapy regimens—untreated disease and salvage therapy, (3) radiology, (4) pathology and (5) complex cases) to assess the impact of the SMDT. Results A total of 2892 new cases were reviewed. In the first 5 years, patients with good prognosis disease had poorer survival in low-volume vs high-volume centres (87.8 vs 95.3, p  = 0.02), but the difference was no longer significant in the last 5 years (93.3 vs 95.1, p  = 0.30). Radiology review of 3206 scans led to rejection of the diagnosis of progression in 26 cases and a further 10 cases were down-staged. There were 790 pathology reviews by two specialised uropathologists, which lead to changes in 75 cases. 18 F-fluorodeoxyglucose ( 18 FDG) PET-CT was undertaken during this time period but did not help to predict who would have viable cancer. A total of 26 patients with significant mental health issues who were unable to give informed consent were discussed. Conclusion SMDT working has led to an improvement in outcomes and refining of treatment in patients with germ cell tumours.

Objectives To determine whether threshold criteria using semi-quantitative multiphase-dynamic contrast-enhanced magnetic resonance imaging (DCE- MRI) can improve prediction of malignancy in complex adnexal masses. Methods MRI features of 70 complex adnexal masses with enhancing components in 63 patients were reviewed and correlated with histopathology ( n  = 67) or radiological follow-up ( n  = 3). Masses were categorised as benign ( n  = 34) or borderline/invasive malignant ( n  = 36). Borderline lesions ( n  = 6) were also analysed separately. Using the semi-quantitative breast analysis software, regions of interest were drawn around the most avidly enhancing component of each lesion. Maximum absolute enhancement of signal intensities (SI max ), maximum relative enhancement (SI rel ) and wash-in rate (WIR) were recorded. Optimal threshold criteria were established to predict borderline/invasive malignancy. Results There was a significant difference in mean SI max ( P  < 0.05), SI rel ( P  < 0.01) and WIR ( P  < 0.001) between benign and borderline/invasive malignant groups. A cut-off WIR ≥9.5 l/s had a specificity of 88% and positive predictive value of 86% for predicting malignancy, significantly better than conventional MRI (62%, P  < 0.01). WIR <8.2 l/s had a negative predictive value of 94%. Conclusion Threshold criteria using semi-quantitative multiphase DCE-MRI improves specificity in the prediction of malignancy in complex adnexal masses with enhancing components and is complementary to standard qualitative assessment. Key Points • Semi-quantitative DCE-MRI threshold criteria are effective for predicting ovarian malignancy • The surgical approach may be altered depending on DCE-MRI threshold criteria analysis • Borderline tumours demonstrate significant overlap with benign lesions using DCE-MRI threshold criteria

CT of the abdomen and pelvis is the first line imaging modality for staging, selecting treatment options and assessing disease response in ovarian cancer. The staging CT provides disease distribution, disease burden and is the imaging surrogate for surgico-pathological FIGO staging. Optimal cyto-reductive surgery offers patients’ the best chance for disease control or cure, but sub-optimal resection confers no advantage over chemotherapy and adversely increases the risk of post surgical complications. Although there is extensive literature comparing performance of CT against laparoscopy and surgery, for the staging abdominal and pelvic CT, there are currently no accepted guidelines for interpretation or routinely used minimum data set templates for reporting these complex CT scans often with extensive radiological findings. This review provides a systematic approach for identifying the important radiological findings and highlighting important sites of disease within the abdomen and pelvis, which may alter or preclude surgery at presentation or after adjuvant chemotherapy. The distribution of sites and volume of disease can be used to categorize patients as suitable, probably suitable or not suitable for optimal cyto-reductive surgery. This categorization can potentially assist oncological surgeons and oncologists as a semi objective assessment tool useful for selecting patient treatment, streamlining multi disciplinary discussion and improving the reproducibility and correlation of CT with surgical findings. The review also highlights sites of disease and complications of ovarian cancer which should be included as part of the radiological report as these may require additional surgical input from non gynaecological surgeons or influence treatment selection.

Computed tomography (CT) or magnetic resonance imaging (MRI) of the head and neck is frequently performed to evaluate most primary head and neck cancers. Most are mucosal and the mucosal extent can be evaluated best by visual inspection by the clinician. However, these tumours have the tendency to spread submucosally, and this extension into the deeper tissue planes may be impossible to detect by clinical examination. Some regions such as the base of the skull, pterygopalatine and infratemporal fossa, orbits, and brain are beyond clinical evaluation, although critical management decisions have to be made based on the involvement of these structures; imaging findings are of the utmost importance in such cases. Perineural and/or perivascular spread, leading to tumour progression, local or distant recurrences can be detected by imaging. Bone involvement, or cartilage invasion or destruction, can be visualized using CT or MRI. Metastatic adenopathies can be identified, sometimes still in a subclinical stage or in sites inaccessible by clinical examination, such as in the retropharyngeal or paratracheal lymph nodes. All of these findings can profoundly influence the staging and management of the patient with head and neck cancer. Finally, imaging may be used to monitor tumour response and to detect recurrent or persistent disease before it becomes clinically evident, possibly with a better chance for successful salvage. Besides imaging findings, the results of initial pathological specimens and smoking history are vital for patient management, and these patients should be formally staged in a multidisciplinary setting.

There has been a significant increase in the availability of testing for pheochromocytoma and paraganglioma (PPGL) germline susceptibility genes. As more patients with genetic mutations are identified, cascade genetic testing of family members is also increasing. This results in identifying genetic predispositions at a much earlier age. With our current understanding of familial PPGL syndromes, lifelong surveillance is required. This review focuses on carriers of succinate dehydrogenase (SDH) mutations. For genetic testing to be proven worthwhile, the results must be used for patient benefit. For SDHx mutations, this should equate to a surveillance program that is safe and removes as much uncertainty around diagnosis as possible. Early identification of these tumors is the goal of any surveillance program, as surgical resection is the mainstay of treatment with curative intent to prevent the morbidity and mortality consequences associated with catecholamine excess, in addition to the risk of malignancy. Modality and frequency of surveillance imaging and how to engage individuals in the process of surveillance remain controversial questions. The data reviewed here and the cumulative advice supports the avoidance of using radiation-exposing imaging in this group of individuals that require lifelong screening.We review the current literature on surveillance protocols for asymptomatic individuals that harbor SDHx mutations. The authors give their views on future directions of surveillance protocols.

Purpose To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods. Methods A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established “no-new-Net” framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training ( n  = 276), evaluation ( n  = 104) and testing ( n  = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test. Results Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin ( p values being 4 × 10 –7 , 3 × 10 –4 , 4 × 10 –2 , respectively), and for the omental lesions on the evaluation set ( p  = 1 × 10 –3 ). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions ( p  = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions. Conclusion Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions. Relevance statement Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines. Key points • The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines. Graphical Abstract

This pictorial review aims to discuss and illustrate the up-to-date use of preprocedural magnetic resonance imaging (MRI) in selecting patients and planning uterine artery embolization (UAE). The merits of magnetic resonance angiography (MRA) in demonstrating the pelvic vasculature to guide UAE are highlighted. MRI features of fibroids and their main differential diagnoses are presented. Fibroid characteristics, such as location, size, and enhancement, which may impact patient selection and outcome, are presented based on recent literature. Pelvic arterial anatomy relevant to UAE, including vascular variants are illustrated, with conventional angiography and MRA imaging correlation. MRA preprocedural determination of the optimal projection angles for uterine artery catheterization is straightforward and constitutes an important strategy to minimize ionizing radiation exposure during UAE. A reporting template for MRI/MRA preassessement of UAE for fibroid treatment is provided.