Bimodality of intratumor Ki67 expression is an independent prognostic factor of overall survival in patients with invasive breast carcinoma

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman’s D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity

Rare types of breast carcinoma

Breast cancer (BC) is a heterogeneous disease that encompasses several distinct entities with remarkably different characteristics. Histological type is one of important BC characteristics. Histological type is associated with differences in epidemiology, diagnostic issues, clinical course, prognosis. When we talk about BC, ductal and lobular carcinoma is usually what we have in mind. However, the other types that comprise less than 10% of BC are also very important. The rarity of many of these neoplasms does not allow large or randomized studies to define the optimal treatment. Many of the descriptions are from case reports and small series. The aim of this retrospective study was to analyze the data on rare breast cancers, to describe their main characteristics, and to calculate survival rates. We believe that the experience of our institution will contribute to the available data about these rare breast cancers and help in better understanding of this subgroup

Ki67/SATB1 ratio is an independent prognostic factor of overall survival in patients with early hormone receptor-positive invasive ductal breast carcinoma

Biological diversity of breast cancer presents challenges for personalized therapy and necessitates multiparametric approaches to understand and manage the disease. Multiple protein biomarkers tested by immunohistochemistry (IHC), followed by digital image analysis and multivariate statistics of the data, have been shown to be effective in exploring latent profiles of tumor tissue immunophenotype. In this study, based on tissue microarrays of 107 patients with hormone receptor (HR) positive invasive ductal breast carcinoma, we investigated the prognostic value of the integrated immunophenotype to predict overall survival (OS) of the patients. A set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16) was used. The main factor of the variance was characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α; it was associated with histological grade but did not predict OS. The second factor was driven by SATB1 expression along with moderate positive HIF-1α and weak negative Ki67 loadings. Importantly, this factor did not correlate with any clinicopathologic parameters, but was an independent predictor of better OS. Ki67 and SATB1 did not reach statistical significance as single predictors; however, high Ki67/SATB1 ratio was an independent predictor of worse OS. In addition, our data indicate potential double prognostic meaning of HIF-1α expression in breast cancer and necessitate focused studies, taking into account the immunophenotype interactions and tissue heterogeneity aspects

Explainable Artificial Intelligence-Based Decision Support System for Assessing the Nutrition-Related Geriatric Syndromes

The use of artificial intelligence in geriatrics is very promising and relevant, as the diagnosis of a geriatric patient is a complex, experience-based, and time-consuming process that involves a variety of questionnaires and subjective and inaccurate patient responses. This paper proposes the explainable artificial intelligence-based (XAI) clinical decision support system (CDSS) to assess nutrition-related factors (symptoms) and to determine the likelihood of geriatric patient health risks associated with four syndromes: malnutrition, oropharyngeal dysphagia, dehydration, and eating disorders in dementia. The proposed system’s prototype was tested under real conditions at the geriatric department of Lithuanian University of Health Sciences Kaunas Hospital. The subjects of this study were 83 geriatric patients with various health conditions. The assessments of the nutritional status and syndromes of the patients provided by the CDSS were compared with the diagnoses of the physicians obtained using standard assessment methods. The results show that proposed CDSS can efficiently diagnose nutrition-related geriatric syndromes with high accuracy: 87.95% for malnutrition, 87.95% for oropharyngeal dysphagia, 90.36% for eating disorders in dementia, and 86.75% for dehydration. The research confirms that the proposed XAI-based CDSS is an effective tool, able to assess nutrition-related health risk factors and their dependencies and, in some cases, makes even a more accurate decision than a less experienced physician

Clinical and Ultrasound Characteristics of the Microcystic Elongated and Fragmented (MELF) Pattern in Endometrial Cancer According to the International Endometrial Tumor Analysis (IETA) criteria

OBJECTIVES: To describe sonographic features of the microcystic elongated and fragmented (MELF) pattern of myometrial invasion (MI) using the International Endometrial Tumor Analysis (IETA) criteria; to assess the effect of the MELF pattern on preoperative ultrasound evaluation of MI; and to determine the relationship of the MELF pattern to more advanced stage ( 65 IB) and lymph node metastases (LNM) in women with endometrioid endometrial cancer (EEC). METHODS/MATERIALS: We included 850 women with EEC from the prospective IETA 4 study. Ultrasound experts performed all ultrasound examinations, accordingto the IETA protocol. Reference pathologists assessed the presence orabsence of the MELF pattern. Sonographic features and accuracy of ultrasound assessment of MI were compared in cases with the presence and the absence of the MELF pattern. The MELF pattern was correlated to more advanced stage ( 65IB) and LNM. RESULTS: The MELF pattern was present in 197 (23.2%) women. On preoperative ultrasound imaging the endometrium was thicker (p = 0.031), more richly vascularized (p = 0.003) with the multiple multifocal vessel pattern (p < 0.001) and the assessment of adenomyosis was more often uncertain (p < 0.001). The presence or the absence of the MELF pattern did not affect the accuracy of the assessment of MI. The MELF pattern was associated with MI 65 50% (p < 0.001), cervical stromal invasion (CSI) (p = 0.037), more advanced stage ( 65 IB) (p < 0.001) and LNM (p = 0.011). CONCLUSIONS: Tumors with the MELF pattern were slightly larger, more richly vascularized with multiple multifocal vessels and assessment of adenomyosis was more uncertain on ultrasound imaging. The MELF pattern did not increase the risk of underestimating MI in preoperative ultrasound staging. Tumors with the MELF pattern were more than twice as likely to have more advanced stage ( 65 IB) and LNM