GANIL Status report

International audienc

Radiomics to better characterize small renal masses

Purpose: Radiomics is a specific field of medical research that uses programmable recognition tools to extract objective information from standard images to combine with clinical data, with the aim of improving diagnostic, prognostic, and predictive accuracy beyond standard visual interpretation. We performed a narrative review of radiomic applications that may support improved characterization of small renal masses (SRM). The main focus of the review was to identify and discuss methods which may accurately differentiate benign from malignant renal masses, specifically between renal cell carcinoma (RCC) subtypes and from angiomyolipoma without visible fat (fat-poor AML) and oncocytoma. Furthermore, prediction of grade, sarcomatoid features, and gene mutations would be of importance in terms of potential clinical utility in prognostic stratification and selecting personalised patient management strategies. / Methods: A detailed search of original articles was performed using the PubMed–MEDLINE database until 20 September 2020 to identify the English literature relevant to radiomics applications in renal tumour assessment. In total, 42 articles were included in the analysis in 3 main categories related to SRM: prediction of benign versus malignant SRM, subtypes, and nuclear grade, and other features of aggressiveness. / Conclusion: Overall, studies reported the superiority of radiomics over expert radiological assessment, but were mainly of retrospective design and therefore of low-quality evidence. However, it is clear that radiomics is an attractive modality that has the potential to improve the non-invasive diagnostic accuracy of SRM imaging and prediction of its natural behaviour. Further prospective validation studies of radiomics are needed to augment management algorithms of SRM

Near-optimal combination of disparity across a log-polar scaled visual field

The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment

A novel tool for quantitative measurement of distortion in keratoconus.

BACKGROUND: Keratoconus is associated with thinning and anterior protrusion of the cornea resulting in the symptoms of blurry and distorted vision. The commonly used clinical vision tests such as visual acuity and contrast sensitivity may not reflect the symptoms experienced in keratoconus and there are no quantitative tools to measure visual distortion. In this study, we used a quantitative test based on vernier alignment and field matching techniques to quantify visual distortion in keratoconus and assess its relation to corneal structural changes. METHODS: A total of 50 participants (25 keratoconus and 25 visually normal) completed the experiment where they aligned supra-threshold white target circles in opposite field in reference to guidelines and circles to complete a square structure monocularly. The task was repeated five times and the global distortion index (GDI) and global uncertainty index (GUI) were calculated as the mean and standard deviation respectively of local perceived misalignment of target circles over five trials. RESULTS: Both GDI and GUI were higher in participants with keratoconus compared to controls (p < 0.01). Both parameters correlated with the best corrected visual acuity, maximum corneal curvature (Kmax), topographical keratoconus classification (TKC) and central corneal thickness (CCT). CONCLUSION: Our findings show that the quantitative measure of distortion could be a useful tool for behavioural assessment of progressive keratoconus