Automated recognition and counting of the immunoreactive neuroendocrine cells in chronic gastritis (the preliminary study).

The paper presents the designed software CAMI (Computerized Analysis of Microscopic Images) for a digital reconstruction of the diversiform glands seen in chronic inflammatory gastric mucosa, and for automated recognition and quantization of the immunoreactive neuroendocrine (NE) cells appearing within mucosal glands. Digital reconstruction of the individual gastric gland is difficult due to variable shapes of the glandular cross-sections. Fifteen gastric biopsy specimens representing chronic gastritis were stained routinely with H+E and immunohistochemically with 3 NE markers: Chromogranin A, Somatostatin and Serotonin. Two expert pathologists counted manually the NE cells with the light microscope in 4 types of glandular cross-sections: round, short- oblique, long- oblique and longitudinal. The automated counting of the NE cells was performed on the digital images presenting the same microscopic areas which were selected for the manual reading. The first step of image analysis was concerned to the cell extraction and recognition of the cytoplasmic immunoreactivity. The unstained nuclei of the NE cells were spotted by the sequential thresholding algorithm combined with the artificial neural network of Support\Vector Machine (SVM) type. The second step of image analysis comprised reconstruction of the glands. The presumed shape of each gastric gland was defined by the cellular lining of viewed glandular cross-section. The designed algorithm for gland reconstruction was based on the cell masks. The third step of analysis dealt the cell counting. Every recognized gland with the face cells was used for the NE cell evaluation. The results of the automated quantization compared with manual counting results for the number of NE cells showed high concordance in 3 types of glandular cross-sections: round, short- and long- oblique. A difference noticed in the results of the longitudinal glands should be verified in the extended study. The designed software CAMI is more adequate for the gland recognition with an discontinuous gland face seen in the immunohistochemical digital images, which appear to be a difficult problem for the accurate automated analysis of the cellular component of glands

The Analysis of Receptor-binding Cancer Antigen Expressed on SiSo Cells (RCAS1) immunoreactivity within the microenvironment of the ovarian cancer lesion relative to the applied therapeutic strategy

RCAS1 is involved in generating the suppressive profile of the tumor microenvironment that helps cancer cells evade immune surveillance. The status of the cells surrounding the cancer nest may affect both the progression of the cancer and the development of metastases. In cases of ovarian cancer, a large number of patients do not respond to the applied therapy. The patient’s response to the applied therapy is directly linked to the status of the tumor microenvironment and the intensity of its suppressive profile. We analyzed the immunoreactivity of RCAS1 on the cells present in the ovarian cancer microenvironment in patients with the disease; these cells included macrophages and carcinoma-associated fibroblasts. Later we analyzed the immunoreactivity levels within these cells, taking into consideration the clinical stage of the cancer and the therapeutic strategy applied, such as the number of chemotherapy regiments, primary cytoreductive surgery, or the presence of advanced ascites. In the patients who did not respond to the therapy we observed significantly higher immunoreactivity levels of RCAS1 within the cancer nest than in those patients who did respond; moreover, in the non-responsive patients we found RCAS1 within both macrophages and carcinoma-associated fibroblasts. RCAS1 staining may provide information about the intensity of the immuno-suppressive microenvironment profile found in cases of ovarian cancer and its intensity may directly relate to the clinical outcome of the disease

Automated recognition and counting of the immunoreactive neuroendocrine cells in chronic gastritis (the preliminary study).

The paper presents the designed software CAMI (Computerized Analysis of Microscopic Images) for a digital reconstruction of the diversiform glands seen in chronic inflammatory gastric mucosa, and for automated recognition and quantization of the immunoreactive neuroendocrine (NE) cells appearing within mucosal glands. Digital reconstruction of the individual gastric gland is difficult due to variable shapes of the glandular cross-sections. Fifteen gastric biopsy specimens representing chronic gastritis were stained routinely with H+E and immunohistochemically with 3 NE markers: Chromogranin A, Somatostatin and Serotonin. Two expert pathologists counted manually the NE cells with the light microscope in 4 types of glandular cross-sections: round, short- oblique, long- oblique and longitudinal. The automated counting of the NE cells was performed on the digital images presenting the same microscopic areas which were selected for the manual reading. The first step of image analysis was concerned to the cell extraction and recognition of the cytoplasmic immunoreactivity. The unstained nuclei of the NE cells were spotted by the sequential thresholding algorithm combined with the artificial neural network of SupportVector Machine (SVM) type. The second step of image analysis comprised reconstruction of the glands. The presumed shape of each gastric gland was defined by the cellular lining of viewed glandular cross-section. The designed algorithm for gland reconstruction was based on the cell masks. The third step of analysis dealt the cell counting. Every recognized gland with the face cells was used for the NE cell evaluation. The results of the automated quantization compared with manual counting results for the number of NE cells showed high concordance in 3 types of glandular cross-sections: round, short- and long- oblique. A difference noticed in the results of the longitudinal glands should be verified in the extended study. The designed software CAMI is more adequate for the gland recognition with an discontinuous gland face seen in the immunohistochemical digital images, which appear to be a difficult problem for the accurate automated analysis of the cellular component of glands

Ekspresja naskórkowego czynnika wzrostu typu 2 (HER-2) w raku żołądka - korelacja cech klinicznych i histologicznych u pacjentów Centrum Onkologii w Bydgoszczy

Gastric cancer is one of the most common tumours in Poland and it is often diagnosed at the advanced stage. Progression of the disease is the most important prognostic factor. It is assessed according to the TNM classifi cation; however the prognosis in patients at the same clinical stage is often different. Therefore, in these cases there is a need to evaluate additional factors in order to determine the biological course of the disease. HER-2 (epidermal growth factor receptor type 2) expression is one of the prognostic predictors recently evaluated in the clinical studies. The fi rst reports on HER-2 protein overexpression in gastric cancers were published in the late twentieth century, but its importance as a prognostic factor is still inconclusive and further research is needed. The aim of our study was to evaluate a relationship between the expression of HER-2 and microscopic features (histological type according to Lauren and WHO classifi cation, grading, Ki-67 expression) in gastric cancers in 194 patients treated at the Oncology Centre in Bydgoszcz. HER-2-positive gastric cancers were more common in women than in men (11 (14.5%) versus 7 (5.9%) patients). The highest incidence of cancers with HER-2 overexpression was found in the group of tubular cancers (28.6%) and papillary cancers (14.3%). Among mucinous cancers and mucocellulare carcinoma, HER-2 receptor overexpression was found in 2.6% and 5.9%, respectively. However, there was the highest percentage of HER-2 receptor overexpression (20.3%) in tumours classifi ed by Lauren as intestinal. There was higher statistically signifi cant (p = 0.0021) level of Ki-67 expression in the group of HER-2-positive cancers.Rak żołądka jest jednym z najczęstszych nowotworów złośliwych w Polsce. Nowotwór ten rozpoznawany jest często w stadium zaawansowanym. Najważniejszym czynnikiem rokowniczym jest zaawansowanie, oceniane według klasyfi kacji TNM, jednak rokowanie u chorych o tym samym stopniu zaawansowania klinicznego często jest różne. Z tego powodu dla określenia przebiegu biologicznego choroby w tych przypadkach potrzebna jest ocena dodatkowych czynników. Jednym z ostatnio ocenianych w badaniach klinicznych czynników prognostycznych i jednocześnie predykcyjnych jest ekspresja naskórkowego czynnika wzrostu typu 2, HER-2 (ang. Human Epidermal Growth Factor Receptor 2). Pierwsze doniesienia dotyczące nadekspresji białka HER-2 w rakach żołądka opublikowano pod koniec XX wieku, jednak jego znaczenie jako czynnika rokowniczego jest wciąż niejednoznaczne i konieczne są dalsze badania. Celem naszych badań była ocena zależności pomiędzy ekspresją HER-2 i cechami obrazu mikroskopowego guza (typ histologiczny według Laurena, według klasyfi kacji WHO, gradingu, ekspresją Ki-67) w rakach żołądka u 194 pacjentów Centrum Onkologii w Bydgoszczy. HER-2-dodatnie raki żołądka znacznie częściej występowały u kobiet niż u mężczyzn (11 (14,5 %) versus 7 (5,9 %) pacjentów). Najwyższą częstość raków z nadekspresją HER-2 stwierdzono w grupie raków cewkowych (28,6%) oraz papilarnych (14,3%). W grupie raków śluzowych i śluzowokomórkowych nadeskpresję receptora HER-2 stwierdzono odpowiednio w 2,6% i 5,9%. Natomiast w rakach sklasyfi kowanych jako jelitowe według Laurena zanotowano najwyższy odsetek guzów wykazujących nadekspresję receptora HER- 2 (20,3%). W grupie raków HER-2-dodatnich zaobserwowano wyższy, istotny statystycznie (p=0.0021) poziom ekspresji Ki-67

Status ekspresji receptorów estrogenowych (ER), progesteronowych (PR) i ludzkiego epidermalnego czynnika wzrostu HER-2 w rakach piersi: badania populacji pacjentek Centrum Onkologii w Bydgoszczy

In Poland, the number of newly diagnosed cases of breast cancers increases continuously and currently amounts to ca. 16000 cases per annum, with a reduced tendency in a number of deaths caused by the breast cancer observed for last 20 years. According to statistical data for 2010, the breast cancer represented 22.4% of all neoplasms in women and was fi rst in terms of occurrence.Liczba nowych zachorowań na raka piersi w Polsce stale rośnie i aktualnie wynosi około 16000 na rok, przy czym na przestrzeni minionych 20 lat obserwuje się tendencję do obniżenia liczby zgonów spowodowanych rakiem piersi. Według danych statystycznych za rok 2010, rak piersi stanowił 22,4% wszystkich nowotworów u kobiet i znajdował się na pierwszym miejscu w kolejności występowania