Implications of all the available evidence It is possible to utilise deep learning to develop biomarkers for automatic prediction of patient outcome directly from conventional histopathology images. In colorectal cancer, the marker was found to be a clinically useful prognostic marker in analysis of a large series of patients who received consistent, modern cancer treatment.

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ObjectivesThe accuracy and precision of two new methods of model-based radiostereometric analysis (RSA) were hypothesised to be superior to a plain radiograph method in the assessment of polyethylene (PE) wear.MethodsA phantom device was constructed to simulate three-dimensional (3D) PE wear. Images were obtained consecutively for each simulated wear position for each modality. Three commercially available packages were evaluated: model-based RSA using laser-scanned cup models (MB-RSA), model-based RSA using computer-generated elementary geometrical shape models (EGS-RSA), and PolyWare. Precision (95% repeatability limits) and accuracy (Root Mean Square Errors) for two-dimensional (2D) and 3D wear measurements were assessed.ResultsThe precision for 2D wear measures was 0.078 mm, 0.102 mm, and 0.076 mm for EGS-RSA, MB-RSA, and PolyWare, respectively. For the 3D wear measures the precision was 0.185 mm, 0.189 mm, and 0.244 mm for EGS-RSA, MB-RSA, and PolyWare respectively. Repeatability was similar for all methods within the same dimension, when compared between 2D and 3D (all p > 0.28). For the 2D RSA methods, accuracy was below 0.055 mm and at least 0.335 mm for PolyWare. For 3D measurements, accuracy was 0.1 mm, 0.2 mm, and 0.3 mm for EGS-RSA, MB-RSA and PolyWare respectively. PolyWare was less accurate compared with RSA methods (p = 0.036). No difference was observed between the RSA methods (p = 0.10).ConclusionsFor all methods, precision and accuracy were better in 2D, with RSA methods being superior in accuracy. Although less accurate and precise, 3D RSA defines the clinically relevant wear pattern (multidirectional). PolyWare is a good and low-cost alternative to RSA, despite being less accurate and requiring a larger sample size.