Robust Automated Tumour Segmentation on Histological and Immunohistochemical Tissue Images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification

Документы архива Учреждения образования «Белорусский государственный медицинский университет» за 1976 – 2013 гг.: организация работ по комплектованию, обеспечению сохранности и использованию : реферат к дипломной работе / Ольга Викторовна Лобач; БГУ, Исторический факультет, Кафедра источниковедения; науч. рук. Яцкевич Д.Л.

Determining the underlying cause of persistent eosinophilia is important for effective clinical management but remains a diagnostic challenge in many cases. We identified STAT5B N642H, an established oncogenic mutation, in 27/1715 (1.6%) cases referred for investigation of eosinophilia. Of the 27 mutated cases, a working diagnosis of hypereosinophilic syndrome (HES; n = 7) or a myeloid neoplasm with eosinophilia (n = 20) had been made prior to the detection of STAT5B N642H. Myeloid panel analysis identified a median of 2 additional mutated genes (range 0–4) with 4 cases having STAT5B N642H as a sole abnormality. STAT5B N642H was absent in cultured T cells of 4/4 positive cases. Individuals with SF3B1 mutations (9/27; 33%) or STAT5B N642H as a sole abnormality had a markedly better overall survival compared to cases with other additional mutations (median 65 months vs. 14 months; hazard ratio = 8.1; P < 0.001). The overall survival of STAT5B-mutated HES cases was only 30 months, suggesting that these cases should be reclassified as chronic eosinophilic leukemia, not otherwise specified (CEL-NOS). The finding of STAT5B N642H as a recurrent mutation in myeloid neoplasia with eosinophilia provides a new diagnostic and prognostic marker as well as a potential target for therapy