Automatic Tumor Grading on Colorectal Cancer Whole-Slide Images: Semi-Quantitative Gland Formation Percentage and New Indicator Exploration

Tumor grading is an essential factor for cancer staging and survival prognostication. The widely used the WHO grading system defines the histological grade of CRC adenocarcinoma based on the density of glandular formation on whole-slide images (WSIs). We developed a fully automated approach for stratifying colorectal cancer (CRC) patients' risk of mortality directly from histology WSI relating to gland formation. A tissue classifier was trained to categorize regions on WSI as glands, stroma, immune cells, background, and other tissues. A gland formation classifier was trained on expert annotations to categorize regions as different degrees of tumor gland formation versus normal tissues. The glandular formation density can thus be estimated using the aforementioned tissue categorization and gland formation information. This estimation was called a semi-quantitative gland formation ratio (SGFR), which was used as a prognostic factor in survival analysis. We evaluated gland formation percentage and validated it by comparing it against the WHO cutoff point. Survival data and gland formation maps were then used to train a spatial pyramid pooling survival network (SPPSN) as a deep survival model. We compared the survival prediction performance of estimated gland formation percentage and the SPPSN deep survival grade and found that the deep survival grade had improved discrimination. A univariable Cox model for survival yielded moderate discrimination with SGFR (c-index 0.62) and deep survival grade (c-index 0.64) in an independent institutional test set. Deep survival grade also showed better discrimination performance in multivariable Cox regression. The deep survival grade significantly increased the c-index of the baseline Cox model in both validation set and external test set, but the inclusion of SGFR can only improve the Cox model less in external test and is unable to improve the Cox model in the validation set

E-learning improves knowledge and practical skills in haemophilia patients on home treatment:A randomized controlled trial

Home treatment of haemophilia is currently the standard of care for patients with severe haemophilia. Home treatment increases the responsibility of the patients for their own treatment and care. Therefore, it is of utmost importance to attain a high level of knowledge and practical skills. The aim of our study was to investigate whether or not an educational e-learning program improves knowledge and skills of adult patients with haemophilia on home treatment. Participants treated at the Haemophilia Treatment Center of the Erasmus University Medical Centre completed a questionnaire to test their knowledge of haemophilia, treatment of bleedings and of complications of treatment and were observed during the intravenous injection of clotting factor concentrate, using a standardized scoring list. Afterwards they were randomized to follow an e-learning program or no intervention (control group). After 1month they completed the same questionnaire again and practical skills were scored once more. At baseline, haemophilia patients (n=30) scored 24 of 48 questions in the questionnaire correctly. Seventy-five per cent of the items on the practical skills scoring list were performed correctly. One month later, the e-learning group (n=16; 36; 18-45) showed a higher level of theoretical knowledge compared to the control group (n=14; 26; 19-32; P&lt;0.001). Also practical skills were significantly better in the group that followed the e-learning program compared to the control group (respectively P=0.002). Self-efficacy of 90% vs. 80% the patients with haemophilia was high in all patients. Our study shows that in haemophilia patients with haemophilia, who are on home treatment, knowledge of haemophilia treatment and complications as well as practical skills can be improved by an educational e-learning program.</p