QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results.

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder translating DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties could enable clinical review of the most uncertain regions, thereby building trust and paving the way toward clinical translation. Several uncertainty estimation methods have recently been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentage of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, highlighting the need for uncertainty quantification in medical image analyses. Finally, in favor of transparency and reproducibility, our evaluation code is made publicly available at https://github.com/RagMeh11/QU-BraTS.

"Personal Knowledge" in Medicine and the Epistemic Shortcomings of Scientism.

In this paper, we outline a framework for understanding the different kinds of knowledge required for medical practice and use this framework to show how scientism undermines aspects of this knowledge. The framework is based on Michael Polanyi's claim that knowledge is primarily the product of the contemplations and convictions of persons and yet at the same time carries a sense of universality because it grasps at reality. Building on Polanyi's ideas, we propose that knowledge can be described along two intersecting "dimensions": the tacit-explicit and the particular-general. These dimensions supersede the familiar "objective-subjective" dichotomy, as they more accurately describe the relationship between medical science and medical practice. Scientism, we argue, excludes tacit and particular knowledge and thereby distorts "clinical reality" and impairs medical practice and medical ethics.

Observational study of the visibility of branded tobacco packaging and smoking at outdoor bars/cafes in Wellington, New Zealand.

AIM: To collect data on tobacco brand visibility on packaging on outdoor tables at bars/cafes in a downtown area, prior to a proposed plain packaging law. METHOD: The study was conducted in the Central Business District of Wellington City in March 2014. Observational data were systematically collected on tobacco packaging visibility and smoking by patrons at 55 bars/cafes with outdoor tables. RESULTS: A total of 19,189 patrons, 1707 tobacco packs and 1357 active smokers were observed. One tobacco pack was visible per 11.0 patrons and the active smoking prevalence was 7.1% (95%CI: 4.9-9.2%), similar to Australian results (8.3%). Eighty percent of packs were positioned face-up (showing the brand), 8% face-down (showing the large pictorial warning), and 12% in other positions. Pack visibility per patron was significantly greater in areas without child patrons (RR=3.1, p<0.0001). Both smoking and pack visibility tended to increase from noon into the evenings on weekends. Inter-observer reliability for key measures in this study was high (Bland-Altman plots). CONCLUSION: Tobacco branding on packaging was frequently visible because of the way smokers position their packs. These results highlight the residual problem posed by this form of marketing. The results also provide baseline data for the future evaluation of plain packaging if a proposed law is implemented in New Zealand. Other results warrant further research, particularly the reasons for lower pack visibility and smoking when children were present.