Vague-Segment Technique: Automatic Computation of Tumor Stroma Ratio for Breast Cancer on Whole Slides.

The calculation of Tumor Stroma Ratio (TSR) is a challenging medical issue that could improve predictions of neoadjuvant chemotherapy benefits and patient prognoses. Although several studies on breast cancer and deep learning methods have achieved promising results, the drawbacks that pixel-level semantic segmentation processes could not extract core tumor regions containing both tumor pixels and stroma pixels make it difficult to accurately calculate TSR. In this paper, we propose a Vague-Segment Technique (VST) consisting of a designed SwinV2UNet module and a modified Suzuki algorithm. Specifically, the SwinV2UNet identifies tumor pixels and generate pixel-level classification results, based on which the modified Suzuki algorithm extracts the contour of core tumor regions in terms of cosine angle. Through this way, VST obtains vaguely segmentation results of core tumor regions containing both tumor pixels and stroma pixels, where the TSR could be calculated by the formula of Intersection over Union (IOU). For the training and evaluation, we utilize the well-known The Cancer Genome Atlas (TCGA) database to create an annotated dataset, while 150 images with TSR annotations from real cases are also collected. The experimental results illustrate that the proposed VST could generate better tumor identification results compared with state-of-the-art methods, where the extracted core tumor regions lead to more consistencies of calculated TSR with senior experts compared to junior pathologists. The experimental results demonstrate the superiority of our proposed pipeline, which has promise for future clinical application.

Risk factors of thyroid nodule in diabetic patients and the correlation with Traditional Chinese Medicine constitution / 国际中医中药杂志

Objective:To explore the risk factors of thyroid nodules in diabetic patients and its correlation with Traditional Chinese Medicine (TCM) constitution.Methods:A Total of 213 cases of diabetic patients in Guang’anmen Hospital and Tangshan Hospital from January 2019 to August 2020 were choosen to do the questionnaire, with containly symptom and constitution. The patients were divided into diabetes with thyroid nodules group and diabetes without thyroid nodules group according to whether thyroid nodules were combined. We compared the clinical data characteristics of 2 groups, and used multi-factor logistic regression model to analyze the risk factors of diabetic patients with thyroid nodules and their correlation with TCM constitutions. Results:Diabetes patients aged from 50-80 years old [ OR=2.949, 95% CI (1.266-6.714)], females [ OR=3.736, 95% CI (1.823-1.541)], diabetes duration≥15 years [ OR=1.558, 95% CI (1.623-1.585)], elevated HbA1c [ OR=5.862, 95% CI (1.418-23.629)], elevated VLDL [ OR=2.851, 95% CI (1.597-6.824)], frequent insomnia [ OR=1.970, 95% CI (1.315-3.395)], Qi stagnation [ OR=4.357, 95% CI (2.634-8.377)], blood stasis [ OR=4.420, 95% CI (1.874-15.258)] are more likely to suffer from thyroid nodules ( P<0.05). Conclusion:Diabetic patients aged from 50-80 years old, females, diabetes duration≥15 years, elevated HbA1c, family history of thyroid nodules, frequent insomnia, and mood swings are more likely to develop thyroid nodules; qi stagnation and blood stasis are dangerous constitutions for diabetic patients with thyroid nodules.