T he scientific, academic, medical and data science communities have come together in the face of the COVID-19 pandemic crisis to rapidly assess novel paradigms in artificial intelligence (AI) that are rapid and secure, and potentially incentivize data sharing and model training and testing without the usual privacy and data ownership hurdles of conventional collaborations 1,2 . Healthcare providers, researchers and industry have pivoted their focus to address unmet and critical clinical needs created by the crisis, with remarkable results [3][4][5][6][7][8][9] . Clinical trial recruitment has been expedited and facilitated by national regulatory bodies and an international cooperative spirit 10-12 . The data analytics and AI disciplines have always fostered open

This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.

ObjectiveTo evaluate diffusion kurtosis imaging (DKI) and magnetisation transfer imaging (MTI) compared to standard MRI for prostate cancer assessment in a re-biopsy population.MethodsThirty-patients were imaged at 3 T including DKI (Kapp and Dapp) with b-values 150/450/800/1150/1500 s/mm2 and MTI performed with and without MT saturation. Patients underwent transperineal biopsy based on prospectively defined MRI targets. Receiver-operating characteristic (ROC) analyses assessed the parameters and Wilcoxon-signed ranked test assessed relationships between metrics.ResultsTwenty patients had ≥ 1 core positive for cancer in a total of 26 MRI targets (Gleason 3+3 in 8, 3+4 in 12, ≥ 4+3 in 6): 13 peripheral (PZ) and 13 transition zone (TZ). The apparent diffusion coefficient (ADC) and Dapp were significantly lower and the Kapp and MT ratio (MTR) significantly higher in tumour versus benign tissue (all p ≤ 0.005); ROC values 0.767-1.000. Normal TZ had: lower ADC and Dapp and higher Kapp and MTR compared to normal PZ. MTR showed a moderate correlation to Kapp (r = 0.570) and Dapp (r = -0.537) in normal tissue but a poor correlation in tumours. No parameter separated low-grade (Gleason 3+3) from high-grade (≥ 3+4) disease for either PZ (p = 0.414-0.825) or TZ (p = 0.148-0.825).ConclusionADC, Dapp, Kapp and MTR all distinguished benign tissue from tumour, but none reliably differentiated low- from high-grade disease.Key Points• MTR was significantly higher in PZ and TZ tumours versus normal tissue • K app was significantly lower and D app higher for PZ and TZ tumours • There was no incremental value for DKI/MTI over mono-exponential ADC parameters • No parameter could consistently differentiate low-grade (Gleason 3+3) from high-grade (≥ 3+4) disease • Divergent MTR/DKI values in TZ tumours suggests they offer different functional information Electronic supplementary materialThe online version of this article (10.1007/s00330-017-5169-1) contains supplementary material, which is available to authorized users.

Purpose This prospective study evaluated the use of vascular, extracellular and restricted diffusion for cytometry in tumours (VERDICT) MRI to investigate the tissue microstructure in glioma. VERDICT-derived parameters were correlated with both histological features and tumour subtype and were also used to explore the peritumoural region. Methods Fourteen consecutive treatment-naïve patients (43.5 years ± 15.1 years, six males, eight females) with suspected glioma underwent diffusion-weighted imaging including VERDICT modelling. Tumour cell radius and intracellular and combined extracellular/vascular volumes were estimated using a framework based on linearisation and convex optimisation. An experienced neuroradiologist outlined the peritumoural oedema, enhancing tumour and necrosis on T2-weighted imaging and contrast-enhanced T1-weighted imaging. The same regions of interest were applied to the co-registered VERDICT maps to calculate the microstructure parameters. Pathology sections were analysed with semi-automated software to measure cellularity and cell size. Results VERDICT parameters were successfully calculated in all patients. The imaging-derived results showed a larger intracellular volume fraction in high-grade glioma compared to low-grade glioma (0.13 ± 0.07 vs. 0.08 ± 0.02, respectively; p = 0.05) and a trend towards a smaller extracellular/vascular volume fraction (0.88 ± 0.07 vs. 0.92 ± 0.04, respectively; p = 0.10). The conventional apparent diffusion coefficient was higher in low-grade gliomas compared to high-grade gliomas, but this difference was not statistically significant (1.22 ± 0.13 × 10 −3 mm 2 /s vs. 0.98 ± 0.38 × 10 −3 mm 2 /s, respectively; p = 0.18). Conclusion This feasibility study demonstrated that VERDICT MRI can be used to explore the tissue microstructure of glioma using an abbreviated protocol. The VERDICT parameters of tissue structure correlated with those derived on histology. The method shows promise as a potential test for diagnostic stratification and treatment response monitoring in the future. Key Points • VERDICT MRI is an advanced diffusion technique which has been correlated with histopathological findings obtained at surgery from patients with glioma in this study. • The intracellular volume fraction measured with VERDICT was larger in high-grade tumours compared to that in low-grade tumours. • The results were complementary to measurements from conventional diffusion-weighted imaging, and the technique could be performed in a clinically feasible timescale. Electronic supplementary material The online version of this article (10.1007/s00330-019-6011-8) contains supplementary material, w...

To investigate the repeatability of diffusion-weighted imaging parameter including ADC-derived histogram values in prostate cancer. Methods: 10 patients with prostate cancer were prospectively recruited to a retest cohort. 3 T diffusion-weighted MRI of the prostate was acquired consecutively with patient getting off the scanner between studies. Prostatectomy-histopathology defined tumour regions-of-interest were outlined on ADC maps and diffusionweighted metrics including histograms were calculated. The coefficient of reproducibility (CoR) and Bland-Altman plots were used to assess repeatability. Results: 10 th centile, 90 th centile, and median ADC showed good repeatability with mean difference ranging from-0.005 to-0.025 × 10 3 mm 2 s-1 , and CoR ranging from 0.271-0.294 × 10 3 mm 2 s-1 of scan 1 mean). Two measures of heterogeneity and simplified texture, IQR and mean local range, had only moderate repeatability. IQR had a mean difference of-0.032 × 10 3 mm 2 s-1 between scans with CoR 0.181 × 10 3 mm 2 s-1 (56% of scan 1 mean). Mean local range had a mean difference-0.008 × 10 3 mm 2 s-1 between scans (37% of scan 1 mean). Bland-Altman plots showed good repeatability for test and re-test analysis for median, percentile and mean range values. All ADC values had good reliability regardless of whether the tumour border was included in quantitative analysis. ADC histogram skew had poor repeatability, CoR 0.78 × 10 3 mm 2 s-1 (373% of scan 1 mean). Conclusion: 10 th and 90 th centile ADC demonstrated sufficient repeatability for clinical use. However, more advanced measures of heterogeneity such as histogram skew, IQR, or mean local range may be limited by their repeatability.

PROPELLER-DWI demonstrates better image quality and decreases both artefact and distortion compared to conventional echo planar sequences in patients with hip metalwork.

BackgroundRight ventricular (RV) dysfunction and heart failure with preserved ejection fraction may contribute to exercise intolerance in obesity. To further define RV exercise responses, we investigated RV–arterial coupling in obesity with and without development of exercise pulmonary venous hypertension (ePVH).MethodsRV–arterial coupling defined as RV end-systolic elastance/pulmonary artery elastance (Ees/Ea) was calculated from invasive cardiopulmonary exercise test data in 6 controls, 8 obese patients without ePVH (Obese−ePVH) and 8 obese patients with ePVH (Obese+ePVH) within a larger series. ePVH was defined as a resting pulmonary arterial wedge pressure < 15 mmHg but ≥ 20 mmHg on exercise. Exercise haemodynamics were further evaluated in 18 controls, 20 Obese−ePVH and 17 Obese+ePVH patients.ResultsBoth Obese−ePVH and Obese+ePVH groups developed exercise RV–arterial uncoupling (peak Ees/Ea = 1.45 ± 0.26 vs 0.67 ± 0.18 vs 0.56 ± 0.11, p < 0.001, controls vs Obese−ePVH vs Obese+ePVH respectively) with higher peak afterload (peak Ea = 0.31 ± 0.07 vs 0.75 ± 0.32 vs 0.88 ± 0.62 mL/mmHg, p = 0.043) and similar peak contractility (peak Ees = 0.50 ± 0.16 vs 0.45 ± 0.22 vs 0.48 ± 0.17 mL/mmHg, p = 0.89). RV contractile reserve was highest in controls (ΔEes = 224 ± 80 vs 154 ± 39 vs 141 ± 34% of baseline respectively, p < 0.001). Peak Ees/Ea correlated with peak pulmonary vascular compliance (PVC, r = 0.53, p = 0.02) but not peak pulmonary vascular resistance (PVR, r = − 0.20, p = 0.46). In the larger cohort, Obese+ePVH patients on exercise demonstrated higher right atrial pressure, lower cardiac output and steeper pressure-flow responses. BMI correlated with peak PVC (r = − 0.35, p = 0.04) but not with peak PVR (r = 0.24, p = 0.25).ConclusionsExercise RV–arterial uncoupling and reduced RV contractile reserve further characterise obesity-related exercise intolerance. RV dysfunction in obesity may develop independent of exercise LV filling pressures.

‘Federated Learning’ (FL) is a method to train Artificial Intelligence (AI) models with data from multiple sources while maintaining anonymity of the data thus removing many barriers to data sharing. During the SARS-COV-2 pandemic, 20 institutes collaborated on a healthcare FL study to predict future oxygen requirements of infected patients using inputs of vital signs, laboratory data, and chest x-rays, constituting the “EXAM” (EMR CXR AI Model) model. EXAM achieved an average Area Under the Curve (AUC) of over 0.92, an average improvement of 16%, and a 38% increase in generalisability over local models. The FL paradigm was successfully applied to facilitate a rapid data science collaboration without data exchange, resulting in a model that generalised across heterogeneous, unharmonized datasets. This provided the broader healthcare community with a validated model to respond to COVID-19 challenges, as well as set the stage for broader use of FL in healthcare.