Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, and clinical decision support, with the goal of ... Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, and clinical decision support, with the goal of ... Created with BioRender.com

Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology. Key Points • Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing “precision” of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.

Optical computed tomography (optical-CT) of 3D radiation dosimeters is a promising avenue for delivering an economic and reliable quality control of radiotherapy treatments such as intensity modulated radiotherapy, brachytherapy and stereotactic radiosurgery. The main problems in transferring 3D dosimeters to clinical setting have been in (1) the complexity of manufacture and behaviour of 3D dosimeters and (2) time-consuming readout and analysis of 3D dosimeters. This paper addresses the readout problem by showing that fast (20 min tomography scan), precise (projection absorbance signal-to-noise ratio is greater than 100:1 across the absorbance range 0.2 to 1.5) and accurate (good linearity in the calibration curve) measurements are possible using a novel method of optically scanning a laser beam across the 3D dosimeter.

Optical computed tomography has now become a well-established method for making empirical measurements of 3D dose distributions in radiotherapy treatment verification. The requirement for effective refractive index matching as part of the scanning process has long been an inconvenience for users, limiting the speed of sample throughput. We propose a new method for reconstructing data that takes explicit account of the refracted path of the light rays and demonstrate theoretically the conditions under which there are sufficient data to create a good reconstruction. Examples of the performance of the algorithm are given. For smoothly varying data, reconstructed images of very high quality are obtained, with RMS deviation of under 1% from the original, provided that the irradiated region lies entirely within a critical radius. For the dosimeter material PRESAGE, this critical value is approximately 0.65 of the sample radius. Regions outside this are not reconstructed successfully, but we argue that there are many cases where this disadvantage is outweighed by the benefits of the technique.