The liver is the commonest site of metastatic disease for patients with colorectal cancer, with at least 25% developing colorectal liver metastases (CRLM) during the course of their illness. The management of CRLM has evolved into a complex field requiring input from experienced members of a multi-disciplinary team involving radiology (cross sectional, nuclear medicine and interventional), Oncology, Liver surgery, Colorectal surgery, and Histopathology. Patient management is based on assessment of sophisticated clinical, radiological and biomarker information. Despite incomplete evidence in this very heterogeneous patient group, maximising resection of CRLM using all available techniques remains a key objective and provides the best chance of long-term survival and cure. To this end, liver resection is maximised by the use of downsizing chemotherapy, optimisation of liver remnant by portal vein embolization, associating liver partition and portal vein ligation for staged hepatectomy, and combining resection with ablation, in the context of improvements in the functional assessment of the future remnant liver. Liver resection may safely be carried out laparoscopically or open, and synchronously with, or before, colorectal surgery in selected patients. For unresectable patients, treatment options including systemic chemotherapy, targeted biological agents, intra-arterial infusion or bead delivered chemotherapy, tumour ablation, stereotactic radiotherapy, and selective internal radiotherapy contribute to improve survival and may convert initially unresectable patients to operability. Currently evolving areas include biomarker characterisation of tumours, the development of novel systemic agents targeting specific oncogenic pathways, and the potential re-emergence of radical surgical options such as liver transplantation.

Objectives• To determine the optimal method for assessing stone volume, and thus stone burden, by comparing the accuracy of scalene, oblate, and prolate ellipsoid volume equations with three-dimensional (3D)-reconstructed stone volume.• Kidney stone volume may be helpful in predicting treatment outcome for renal stones. While the precise measurement of stone volume by 3D reconstruction can be accomplished using modern computer tomography (CT) scanning software, this technique is not available in all hospitals or with routine acute colic scanning protocols. Therefore, maximum diameters as measured by either X-ray or CT are used in the calculation of stone volume based on a scalene ellipsoid formula, as recommended by the European Association of Urology. Methods• In all, 100 stones with both X-ray and CT (1-2-mm slices) were reviewed. Complete and partial staghorn stones were excluded.• Stone volume was calculated using software designed to measure tissue density of a certain range within a specified region of interest.• Correlation coefficients among all measured outcomes were compared. Stone volumes were analysed to determine the average 'shape' of the stones. Results• The maximum stone diameter on X-ray was 3-25 mm and on CT was 3-36 mm, with a reasonable correlation (r = 0.77).• Smaller stones (<9 mm) trended towards prolate ellipsoids ('rugby-ball' shaped), stones of 9-15 mm towards oblate ellipsoids (disc shaped), and stones >15 mm towards scalene ellipsoids.• There was no difference in stone shape by location within the kidney. Conclusions• As the average shape of renal stones changes with diameter, no single equation for estimating stone volume can be recommended.• As the maximum diameter increases, calculated stone volume becomes less accurate, suggesting that larger stones have more asymmetric shapes.• We recommend that research looking at stone clearance rates should use 3D-reconstructed stone volumes when available, followed by prolate, oblate, or scalene ellipsoid formulas depending on the maximum stone diameter.

Objectives To assess the predictive value and correlation to pathological progression of the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scoring system in the follow-up of prostate cancer (PCa) patients on active surveillance (AS). Methods A total of 295 men enrolled on an AS programme between 2011 and 2018 were included. Baseline multiparametric magnetic resonance imaging (mpMRI) was performed at AS entry to guide biopsy. The follow-up mpMRI studies were prospectively reported by two sub-specialist uroradiologists with 10 years and 13 years of experience. PRECISE scores were dichotomized at the cut-off value of 4, and the sensitivity, specificity, positive predictive value and negative predictive value were calculated. Diagnostic performance was further quantified by using area under the receiver operating curve (AUC) which was based on the results of targeted MRI-US fusion biopsy. Univariate analysis using Cox regression was performed to assess which baseline clinical and mpMRI parameters were related to disease progression on AS. Results Progression rate of the cohort was 13.9% (41/295) over a median follow-up of 52 months. With a cut-off value of category ≥ 4, the PRECISE scoring system showed sensitivity, specificity, PPV and NPV for predicting progression on AS of 0.76, 0.89, 0.52 and 0.96, respectively. The AUC was 0.82 (95% CI = 0.74–0.90). Prostate-specific antigen density (PSA-D), Likert lesion score and index lesion size were the only significant baseline predictors of progression (each p < 0.05). Conclusion The PRECISE scoring system showed good overall performance, and the high NPV may help limit the number of follow-up biopsies required in patients on AS. Key Points • PRECISE scores 1–3 have high NPV which could reduce the need for re-biopsy during active surveillance. • PRECISE scores 4–5 have moderate PPV and should trigger either close monitoring or re-biopsy. • Three baseline predictors (PSA density, lesion size and Likert score) have a significant impact on the progression-free survival (PFS) time.