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Ex-vivo freshly surgical removed pancreatic ductal adenocarcinoma (PDAC) specimens were assessed using pCLE and then processed for paraffin embeding and histopathological diagnostic in an endeavour to find putative image analysis algorithms that might recognise adenocarcinoma. Methods: Twelve patients diagnosed with PDAC on endoscopic ultrasound and FNA confirmation underwent surgery. Removed samples were sprayed with acriflavine as contrast agent, underwent pCLE with an experimental probe and compared with previous recordings of normal pancreatic tissue. Subsequently, all samples were subjected to cross-sectional histopathology, including surgical resection margins for controls. pCLE records, as well as corespondant cytokeratin-targeted immunohistochemistry images were processed using the same morphological classifiers in the Image ProPlus AMS image analysis software. Specific morphometric classifiers were automatically generated on all images: Area, Hole Area (HA), Perimeter, Roundness, Integrated Optical Density (IOD), Fractal Dimension (FD), Ferret max (Fmax), Ferret mean (Fmean), Heterogeneity and Clumpiness. Results: After histopathological confirmation of adenocarcinoma areas, we have found that the same morphological classifiers could clearly differentiate between tumor and non-tumor areas on both pathology and correspondand pCLE (area, roundness, IOD, ferret and heterogeneity (p < 0.001), perimeter and hole area (p < 0.05). Conclusions: This pilot study proves that classical morphometrical classifiers can clearly differentiate adenocarcimoma on pCLE data, and the implementation in a live image-analysis algorithm might help in improving the specificity of pCLE in vivo diagnostic. [ABSTRACT FROM AUTHOR]

Patients with primary colorectal cancer can present with obstructions, tumor bleeding, or perforations, which represent acute complications. This paper aimed to analyze and compare the clinical and pathological profiles of two patient groups: one with colorectal cancer and a related complication and another without any specific complication. We performed a five-year retrospective study on colorectal cancer patients admitted to a surgery unit and comparatively explored the main clinical and pathological features of the tumors belonging to the two groups. A total of 250 patients with colorectal cancer were included in the analysis. Of these, 117 (46.8%) had presented a type of complication. The comparative analysis that examined several clinical and pathological parameters showed a statistically significant difference for unfavorable prognosis factors in the group with complications. This was evident for features such as vascular and perineural invasion, lymph node involvement, pathological primary tumor stage, and TNM stage. Colorectal cancers with a related complication belonged to a group of tumors with a more aggressive histopathologic profile and more advanced stages. Furthermore, the comparable incidence of cases in the two groups of patients warrants further efforts to be made in terms of early detection and prognosis prediction of colorectal cancer. [ABSTRACT FROM AUTHOR]

Gastric cancer continues to be a significant malignancy worldwide, accounting for approximately one million new cases in 2020. Scientists are focusing on the cancerous cells' plasma membrane (PM) as a potential therapeutic target in cancer because it functions as the cell's interface with its environment through a variety of mechanisms. The capacity of membrane shape and its structures to influence biological processes frequently occurs through the regulation of enzymes or preferential protein binding to membranes via membrane shape changes. We aimed here to assess the morphological irregularities of the cellular membranes in gastric adenocarcinoma tumors, and to find any putative differences from normal gastric mucosae epithelial cells. We analyzed the pattern of E-cadherin at the level of the cell membrane using the fractal dimension (FD) analysis on fluorescence immunohistochemistry samples labeled with E-cadherin in gastric well/moderate and solid gastric adenocarcinoma from patients without any associated chemotherapeutic treatment or radiotherapy. Images were binarized based on a fixed threshold of the E-cadherin fluorescence channel, and then the FD of the binarized image outlines has been calculated in order to assess the ruggedness of the cellular membranes. Overall assessment of the FD revealed that the subtle membrane variations were evident enough to deem a statistically significant difference and the complexity of the membrane roughness was clearly higher for adenocarcinoma cases. We intended to evaluate if separating adenocarcinoma cases as low grade (G1 and G2) and high grade (G3 and solid), FD analysis could still differentiate membrane patterns and check if the available clinical parameters like age, gender, tumor location, lymph ganglia involved might correlate with FD values for adenocarcinoma patients. Altogether, the morphological analysis of a simple marker for the cell membrane can identify and distinguish tumor cells. Although there was a limited correlation between this analysis and the main clinical and pathological indicators of the disease, it will be very useful in the future for automatic computer-assisted diagnosis on slides, as well as for evaluating cellular adhesion and inter-cellular trafficking in cancer cells. [ABSTRACT FROM AUTHOR]

Pathological diagnosis of prostate adenocarcinoma often requires complementary methods. On prostate biopsy tissue from 39 patients including benign nodular hyperplasia (BNH), atypical adenomatous hyperplasia (AAH), and adenocarcinomas, we have performed combined histochemical-immunohistochemical stainings for argyrophilic nucleolar organizer regions (AgNORs) and glandular basal cells. After ascertaining the pathology, we have analyzed the number, roundness, area, and fractal dimension of individual AgNORs or of their skeleton-filtered maps. We have optimized here for the first time a combination of AgNOR morphological denominators that would reflect best the differences between these pathologies. The analysis of AgNORs' roundness, averaged from large composite images, revealed clear-cut lower values in adenocarcinomas compared to benign and atypical lesions but with no differences between different Gleason scores. Fractal dimension (FD) of AgNOR silhouettes not only revealed significant lower values for global cancer images compared to AAH and BNH images, but was also able to differentiate between Gleason pattern 2 and Gleason patterns 3-5 adenocarcinomas. Plotting the frequency distribution of the FDs for different pathologies showed clear differences between all Gleason patterns and BNH. Together with existing morphological classifiers, AgNOR analysis might contribute to a faster and more reliable machine-assisted screening of prostatic adenocarcinoma, as an essential aid for pathologists. [ABSTRACT FROM AUTHOR]