Background: Medical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors. Method: Aggregated data were collected for 50 measures across 29 UK medical schools. Data include institutional history (e.g. rate of production of hospital and GP specialists in the past), curricular influences (e.g.

Background: What subjects UK medical schools teach, what ways they teach subjects, and how much they teach those subjects is unclear. Whether teaching differences matter is a separate, important question. This study provides a detailed picture of timetabled undergraduate teaching activity at 25 UK medical schools, particularly in relation to problem-based learning (PBL). Method: The Analysis of Teaching of Medical Schools (AToMS) survey used detailed timetables provided by 25 schools with standard 5-year courses. Timetabled teaching events were coded in terms of course year, duration, teaching format, and teaching content. Ten schools used PBL. Teaching times from timetables were validated against two other studies that had assessed GP teaching and lecture, seminar, and tutorial times. Results: A total of 47,258 timetabled teaching events in the academic year 2014/2015 were analysed, including SSCs (student-selected components) and elective studies. A typical UK medical student receives 3960 timetabled hours of teaching during their 5-year course. There was a clear difference between the initial 2 years which mostly contained basic medical science content and the later 3 years which mostly consisted of clinical teaching, although some clinical teaching occurs in the first 2 years. Medical schools differed in duration, format, and content of teaching. Two main factors underlay most of the variation between schools, Traditional vs PBL teaching and Structured vs Unstructured teaching. A curriculum map comparing medical schools was constructed using those factors. PBL schools differed on a number of measures, having more PBL teaching time, fewer lectures, more GP teaching, less surgery, less formal teaching of basic science, and more sessions with unspecified content. Discussion: UK medical schools differ in both format and content of teaching. PBL and non-PBL schools clearly differ, albeit with substantial variation within groups, and overlap in the middle. The important question of whether differences in teaching matter in terms of outcomes is analysed in a companion study (MedDifs) which examines how teaching differences relate to university infrastructure, entry requirements, student perceptions, and outcomes in Foundation Programme and postgraduate training.

Background False positive multiparametric magnetic resonance imaging (mpMRI) phenotypes prompt unnecessary biopsies. The Prostate MRI Imaging Study (PROMIS) provides a unique opportunity to explore such phenotypes in biopsy-naïve men with raised prostate-specific antigen (PSA) and suspected cancer. Objective To compare mpMRI lesions in men with/without significant cancer on transperineal mapping biopsy (TPM). Design, setting, and participants PROMIS participants ( n = 235) underwent mpMRI followed by a combined biopsy procedure at University College London Hospital, including 5-mm TPM as the reference standard. Patients were divided into four mutually exclusive groups according to TPM findings: (1) no cancer, (2) insignificant cancer, (3) definition 2 significant cancer (Gleason ≥3 + 4 of any length and/or maximum cancer core length ≥4 mm of any grade), and (4) definition 1 significant cancer (Gleason ≥4 + 3 of any length and/or maximum cancer core length ≥6 mm of any grade). Outcome measurements and statistical analysis Index and/or additional lesions present in 178 participants were compared between TPM groups in terms of number, conspicuity, volume, location, and radiological characteristics. Results and limitations Most lesions were located in the peripheral zone. More men with significant cancer had two or more lesions than those without significant disease (67% vs 37%; p <  0.001). In the former group, index lesions were larger (mean volume 0.68 vs 0.50 ml; p <  0.001, Wilcoxon test), more conspicuous (Likert 4–5: 79% vs 22%; p <  0.001), and diffusion restricted (mean apparent diffusion coefficient [ADC]: 0.73 vs 0.86; p <  0.001, Wilcoxon test). In men with Likert 3 index lesions, log 2 PSA density and index lesion ADC were significant predictors of definition 1/2 disease in a logistic regression model (mean cross-validated area under the receiver-operator characteristic curve: 0.77 [95% confidence interval: 0.67–0.87]). Conclusions Significant cancer-associated MRI lesions in biopsy-naïve men have clinical-radiological differences, with lesions seen in prostates without significant disease. MRI-calculated PSA density and ADC could predict significant cancer in those with indeterminate MRI phenotypes. Patient summary Magnetic resonance imaging (MRI) lesions that mimic prostate cancer but are, in fact, benign prompt unnecessary biopsies in thousands of men with raised prostate-specific antigen. In this study we found that, on closer look, such false positive lesions have different features from cancerous ones. This means that doctors could potentially develop better tools to identify cancer on MRI and spare some patients from unnecessary biopsies.

Background: Three-dimensional (3D) multiecho balanced steady-state free precession (ME-bSSFP) has previously been demonstrated in preclinical hyperpolarized (HP) 13 C-MRI in vivo experiments, and it may be suitable for clinical metabolic imaging of prostate cancer (PCa). Purpose: To validate a signal simulation framework for the use of sequence parameter optimization. To demonstrate the feasibility of ME-bSSFP for HP 13 C-MRI in patients. To evaluate the metabolism in PCa measured by ME-bSSFP. Study Type: Retrospective single-center cohort study.

Computer-aided diagnosis (CAD) of prostate cancer on multiparametric magnetic resonance imaging (mpMRI), using artificial intelligence (AI), may reduce missed cancers and unnecessary biopsies, increase inter-observer agreement between radiologists, and alleviate pressures caused by rising case incidence and a shortage of specialist radiologists to read prostate mpMRI. However, well-designed evaluation studies are required to prove efficacy above current clinical practice. A systematic search of the MEDLINE, EMBASE, and arXiv electronic databases was conducted for studies that compared CAD for prostate cancer detection or classification on MRI against radiologist interpretation and a histopathological reference standard, in treatment-naïve men with a clinical suspicion of prostate cancer. Twenty-seven studies were included in the final analysis. Due to substantial heterogeneities in the included studies, a narrative synthesis is presented. Several studies reported superior diagnostic accuracy for CAD over radiologist interpretation on small, internal patient datasets, though this was not observed in the few studies that performed evaluation using external patient data. Our review found insufficient evidence to suggest the clinical deployment of artificial intelligence algorithms at present. Further work is needed to develop and enforce methodological standards, promote access to large diverse datasets, and conduct prospective evaluations before clinical adoption can be considered.