Adaptive Localization of Focus Point Regions via Random Patch Probabilistic Density from Whole-Slide, Ki-67-Stained Brain Tumor Tissue

Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved

Adaptive Localization of Focus Point Regions via Random Patch Probabilistic Density from Whole-Slide, Ki-67-Stained Brain Tumor Tissue

Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved

Estrogen receptor-negative breast ductal carcinoma: clinicopathological features and MIB-1 (Ki-67) proliferative index association.

Breast cancer estrogen receptor (ER) status is one of the strong additional factors in predicting response of patients towards hormonal treatment. The main aim of this study was to assess the morphological characteristics and proliferative activity using MIB-1(Ki-67) of estrogen receptor negative invasive breast ductal carcinoma (NOS type) as well as to correlate these features with clinicopathological data. We also aim to study the expression of c-erbB2 in ER negative breast tumors. High proliferative rate (MIB-1 above 20%) was observed in 63 (63.6%) of 99 ER negative tumors and that these tumors were associated with high expression of c-erbB2 (57.6%). We observed that MIB-1 is a reliable independent prognostic indicator for ER negative infiltrating ductal carcinoma in this study

Additional file 3: Figure S1. of MicroRNA-200c and microRNA-31 regulate proliferation, colony formation, migration and invasion in serous ovarian cancer

The representative image of ISH showing the miR-200c blue chromogenic signal in the cytoplasmic region of a high-grade SEOC cancer epithelia and weak staining in the neighbouring stroma cells. Positive miR-200c staining was also noted in the nucleoli of SEOC cells. Image was captured at 200× magnifications. Figure S2. Expression of miR-31 in tissue and cell lines of serous ovarian cancer. (A) Expression of miR-31 in serous ovarian cancer compared to the normal ovarian tissue samples. (B) Expression of miR-31 in two serous ovarian cancer cell lines, CAOV3 and SKOV3 compared to the HOSE, the human normal ovarian surface epithelial cells. Data are presented as means ± standard deviation generated from triplicates. (***p < 0.05). Figure S3. Detection of miRNA transfection efficiency in (A) CAOV3 and (B) SKOV3 cells. Twenty four hours after transfection with 150 nM 5’ fluorescein-labeled scrambled miRNA, the transfection efficiency was determined by flow cytometry. The P1 region represents the percentage of cells that were successfully transfected with 5’ fluorescein-labeled scrambled miRNA by Lipofectamine 2000. Mock transfection represents cells treated with Lipofectamine 2000 only. The results were analyzed with FACS Diva Version 6.1.3 software, which indicated that the miRNA transfection efficiency in CAOV3 and SKOV3 cells were approximately 60 % and 80 %, respectively. Table S3. Summary of the pathway enrichment analysis and putative target genes for miR-200c. Table S4. Summary of the pathway enrichment analysis and putative target genes for miR-31. (DOCX 2955 kb

Additional file 2: Table S2. of MicroRNA-200c and microRNA-31 regulate proliferation, colony formation, migration and invasion in serous ovarian cancer

Complete list of the 85 miRNAs evaluated across all samples. (XLSX 50 kb

C-erbB2 overexpression shows strong positivity (3+) on the cell membrane by immunohistochemistry (×200 magnification).

<p>C-erbB2 overexpression shows strong positivity (3+) on the cell membrane by immunohistochemistry (×200 magnification).</p

Significant correlation between tumor staging and tumor size, tumor grade, lymph node metastases in ER-negative tumor.

<p>Correlation is significant at the 0.05 level (2-sided).</p

Significant correlation between axillary lymph node metastases and tumor margin in ER-negative tumor.

<p>Correlation is significant at the 0.05 level (2-sided).</p

Clinical outcome of ER-negative tumor cases (within 0 to 5 years follow up) in relation with morphological and clinicopathological data.

<p>Clinical outcome of ER-negative tumor cases (within 0 to 5 years follow up) in relation with morphological and clinicopathological data.</p

Immunohistochemical stain for ER in invasive breast carcinoma showing strong nuclear positivity (×200 magnification).

<p>Immunohistochemical stain for ER in invasive breast carcinoma showing strong nuclear positivity (×200 magnification).</p