Nuclear shape descriptors by automated morphometry may distinguish aggressive variants of squamous cell carcinoma from relatively benign skin proliferative lesions: a pilot study

Histomorphometric analysis of liver biopsies of treated patients with Gaucher disease type 1

Gaucher disease (GD) is an autosomal recessive lysosomal disorder caused by a disturbance in the metabolism of glucocerebroside in the macrophages. Most of its manifestations – hepatosplenomegaly, anemia, thrombocytopenia, and bone pain – are amenable to a macrophage-target therapy such as enzyme replacement. However, there is increasing evidence that abnormalities of the liver persist despite the specific GD treatment. In this work, we adapted histomorphometry techniques to the study of hepatocytes in GD using liver tissue of treated patients, developing the first morphometrical method for canalicular quantification in immunohistochemistry-stained liver biopsies, and exploring histomorphometric characteristics of GD. This is the first histomorphometric technique developed for canalicular analysis on histological liver biopsy samples.

Ex Vivo MR Histology and Cytometric Feature Mapping Connect Three-dimensional in Vivo MR Images to Two-dimensional Histopathologic Images of Murine Sarcomas

Purpose To establish a platform for quantitative tissue-based interpretation of cytoarchitecture features from tumor MRI measurements. Materials and Methods In a pilot preclinical study, multicontrast in vivo MRI of murine soft-tissue sarcomas in 10 mice, followed by ex vivo MRI of fixed tissues (termed MR histology), was performed. Paraffin-embedded limb cross-sections were stained with hematoxylin-eosin, digitized, and registered with MRI. Registration was assessed by using binarized tumor maps and Dice similarity coefficients (DSCs). Quantitative cytometric feature maps from histologic slides were derived by using nuclear segmentation and compared with registered MRI, including apparent diffusion coefficients and transverse relaxation times as affected by magnetic field heterogeneity (T2* maps). Cytometric features were compared with each MR image individually by using simple linear regression analysis to identify the features of interest, and the goodness of fit was assessed on the basis of R² values. Results Registration of MR images to histopathologic slide images resulted in mean DSCs of 0.912 for ex vivo MR histology and 0.881 for in vivo MRI. Triplicate repeats showed high registration repeatability (mean DSC, >0.9). Whole-slide nuclear segmentations were automated to detect nuclei on histopathologic slides (DSC = 0.8), and feature maps were generated for correlative analysis with MR images. Notable trends were observed between cell density and in vivo apparent diffusion coefficients (best line fit: R² = 0.96, P < .001). Multiple cytoarchitectural features exhibited linear relationships with in vivo T2* maps, including nuclear circularity (best line fit: R² = 0.99, P < .001) and variance in nuclear circularity (best line fit: R² = 0.98, P < .001). Conclusion An infrastructure for registering and quantitatively comparing in vivo tumor MRI with traditional histologic analysis was successfully implemented in a preclinical pilot study of soft-tissue sarcomas. Keywords: MRI, Pathology, Animal Studies, Tissue Characterization Supplemental material is available for this article. © RSNA, 2021.

Nuclear morphometric analysis in tissue as an objective tool with potential use to improve melanoma staging

Alterations in nuclear size and shape are commonly observed in cancers, and its objective evaluation may provide valuable clinical information about the outcome of the disease. Here, we applied the nuclear morphometric analysis in tissues in hematoxylin and eosin-digitized slides of nevi and melanoma, to objectively contribute to the prognostic evaluation of these tumors. To this, we analyzed the nuclear morphometry of 34 melanomas classified according to the TNM stage. Eight cases of melanocytic nevi were used as non-neoplastic tissues to set the non-neoplastic parameters of nuclear morphology. Our samples were set as G1 (control, nevi), G2 (T1T2N0M0), G3 (T3T4N0M0), G4 (T1T2N1M1), and G5 (T3T4N1M1). Image-Pro Plus 6.0 software was used to acquire measurements related to nuclear size (variable: Area) and shape (variables: Aspect, AreaBox, Roundness, and RadiusRatio, which were used to generate the Nuclear Irregularity Index). From these primary variables, a set of secondary variables were generated. All the seven primary and secondary variables related to the nuclear area were different among groups (Pillai's trace P<0.001), whereas Nuclear Irregularity Index, which is the variable related to nuclear shape, did not differ among groups. The secondary variable 'Average Area of Large Nuclei' was able to differ all pairwise comparisons, including thin nonmetastatic from thin metastatic tumors. In conclusion, the objective quantification of nuclear area in hematoxylin and eosin slides may provide objective information about the risk stratification of these tumors and has the potential to be used as an additional method in clinical decision making.