Computerized nuclear morphometry for the prediction of inguinal lymph nodes metastases in squamous cell carcinoma of the vulva

Simplified low-cost methodology to establish, histologically process and analyze three-dimensional cancer cell spheroid arrays

Differently of two-dimensional cell culture, three-dimensional (3D) multicellular spheroid model allows cells to establish cell-cell/cell-matrix interactions over the entire cell surface, more closely mimicking tumor microenvironments and cellular subpopulations with specific standards of morphology, differentiation and gene expression. Thenceforth several methodologies involving or the 3D cell aggregates generation or its histological processing and analysis have emerged, but in general they are laborious, expensive and complex to set up as a routine technique. Thus, we developed a complete methodology, detailing a simple, accessible and low-cost step by step, including 1) the 3D cell aggregate generation using hanging drop technique; 2) providing a simple way to assess morphological parameters of generated spheroids; followed by 3) a multiple and organized histological processing, keeping several individual spheroids inside an agarose apparatus, maintaining a known order and position of each ones, similar to tissue microarray principle; 4) until the last step, where it is allowed a simultaneous histological composition analysis of several spheroid slices, organized side by side, in a same block section, through conventional stainings or 5) immunostaining against different molecular markers. Therefore, the present methodology aims to popularize 3D cell culture, allowing to make this a regular technique in basic cell biology research, once all steps are performed without using onerous reagents, materials or equipment. In addition to bring the agarose apparatus as a simple low cost novelty, allowing high-throughput analysis of several spheroids simultaneously in an organized manner.

Immunohistochemical and electron microscopic morphometric image analysis of hepatocellular carcinoma in association of HCV infection

Early detection of hepatocellular carcinoma (HCC) is crucial for successful therapy. The present work examined the value of ultrastructural morphometric image analysis of hepatocyte nuclei in patients with chronic hepatitis C virus (HCV) versus HCC cases with chronic HCV and the corresponding surgical tumor-free safe margins (TFMs), to highlight any early predictive signs of neoplastic cellular transformation. This work also performed an immunohistochemical assessment of cytokeratin 19 (CK19) and Ki-67-positive cells to visualize any associated proliferative activity in the examined groups. The results showed significant decrease in the hepatocyte nuclear surface areas in the HCC and TFMs versus those in the HCV cases. The hepatocyte nucleolar surface area was significantly increased in the HCC cases versus that in the HCV cases. This increase was associated with a significant increase in Ki-67-positive cells in the HCC cases compared to those in the other groups. Conversely, the mean number of CK 19-positive cells was significantly reduced in the HCC cases compared to the cell numbers in TFMs and HCV cases with severe hepatic fibrosis. Liver progenitor cells (LPCs) were discerned in the reactive ductules and canaliculo-ductular junctions that characterized TFMs. LPCs were sporadically distributed in the liver lobules and reactive bile ductules in the HCC samples. In conclusion, CK 19 represents an important marker for distinguishing between dysplastic and malignant liver nodules. Electron microscopic morphometric image analysis may be considered as adjunct factor for assessing hepatocyte malignant transformation. Wider scale studies are needed to authenticate these results.

Early histological findings may predict the clinical phenotype in Crohn's colitis

BACKGROUND AND AIMS

Predicting the clinical course of Crohn's disease (CD) is relevant for treatment selection. Currently, such diagnostic tools are lacking. In a previous pilot study, morphometric tissue image analysis showed promise in predicting the clinical phenotype and need for surgery. In this study, we aimed to validate our previous results on a larger cohort.

METHODS

Colonic biopsies from CD patients with colonic or ileocolonic disease and at least five years of post-biopsy clinical follow-up were analyzed. The results were used to predict post-biopsy clinical phenotypes and outcomes. Data analysis was performed using multivariate regression models, discriminant score (DS) computations and Neural Network (NNET).

RESULTS

Multivariate analysis of morphometric variables differentiated between B1 and B2 phenotypes (sensitivity 81%, specificity 74%, accuracy on cross-validation 75%; area under the curve (AUC) of 0.74 (CI 0.6-0.84; NNET model sensitivity 87%, specificity 67% on the testing population)). Differentiation between B1 and B3 phenotypes was also possible (sensitivity 69%, specificity 76%, accuracy 70.5% on cross-validation; AUC 0.78 (CI 0.68-0.89); NNET model sensitivity 78%, specificity 77% on the testing population)). Differentiating between B2 and B3 phenotypes was not possible using morphometric variables. Multivariate analysis predicted surgery (sensitivity 67%, specificity 72.5%, accuracy 69%; AUC 0.72 (CI 0.61-0.82); NNET model sensitivity 80%, specificity 91% on the testing population)).

CONCLUSIONS

This study validates previous results and suggests that morphometric image analysis of early biopsies from Crohn's colitis patients may contribute to the prediction of future outcomes such as clinical phenotype and surgery. Prospective validation on larger cohorts is still needed.

Characterization of squamous cell carcinomas of the head and neck using methods of spatial statistics

In the present study, 53 cases of squamous cell carcinomas of the head and neck were characterized by a quantitative histological texture analysis based on principles of spatial statistics. A planar tessellation of the epithelial tumour component was generated by a skeletonization algorithm. The size distribution of the virtual cells of this planar tessellation, and the size distribution of the profiles of the tumour cell nuclei were estimated in terms of area and boundary length. The intensity, the reduced second moment function (K-function) and the pair correlation function of the point process of the centroids of the profiles of the tumour cell nuclei were also estimated. For both purposes, it is necessary to correct for edge effects, which we consider in this paper in some detail. Specifically, the point patterns of the tumour cell nuclei were considered as realizations of a point process, where the points exist only in the epithelial tumour component (the permitted phase) and not in the stroma (the forbidden phase). The methods allow to characterize each individual tumour by a series of summary statistics. The total set of cases was then partitioned into two groups: 19 cases without lymph node metastases (pN0), and 34 nodal positive cases (pN1 or pN2). Statistical analysis showed no significant differences between the intensities, the mean K-functions and the mean pair correlation functions of the tumour cell nucleus profiles of the two groups. However, there were some significant differences between the sizes of the virtual cells and of the nucleus profiles of the nodal negative cases as compared to the nodal positive cases. In a logistic regression analysis, one of the quantitative nuclear size variables (mean nuclear area) was found to be a significant predictor of lymph node metastasis, in addition to tumour stage. The study shows the potential of methods of spatial statistics for objective quantitative grading of squamous cell carcinomas of the head and neck, and provides an example for modelling histological point patterns as realizations of planar point processes occupying a reference phase which is only a partial component of the total tissue.

Preoperative prediction of papillary thyroid carcinoma prognosis with the assistance of computerized morphometry of cytology samples obtained by fine-needle aspiration: preliminary report

BACKGROUND

The purpose of this study was to analyze the relationship between cytologic features, clinical features, and recurrence of papillary thyroid cancer (PTC). We hoped to predict prognosis preoperatively.

METHODS

We retrospectively studied cytologic features by using computerized morphometry and clinical data of 118 patients with usual-type PTC without initial metastasis, including 34 patients with cancer recurrence in 10 years after surgery and 84 patients who did not have recurrence for more than 10 years after surgery. Another 24 patients were recruited for validation.

RESULTS

Multivariate logistic analysis indicated that nucleus-to-cell ratio, variation of nuclear area, tumor size, and patient age were significantly related to recurrence. Cox regression analysis showed that hazard ratios were 3.34, 1.53, 1.77, and 2.6, respectively.

CONCLUSION

Cytologic features of PTC analyzed with computerized morphometry significantly correlated with recurrence. It helped to predict prognosis preoperatively and may be helpful for planning further treatment.

Benign versus malignant parakeratosis: a nuclear morphometry study

Parakeratosis is relatively common in both benign and malignant skin diseases. It is a useful feature for classifying certain types of dermatitis; however, its value in distinguishing benign from malignant neoplastic squamous lesions has not been investigated. Parakeratotic nuclei are pyknotic and often elongated, regardless of the underlying disease. However, we have noticed a quite consistent difference in nuclear morphology between benign and malignant parakeratosis, which has not been formally described in the literature. To test the hypothesis that morphological differences may aid in the discrimination between certain benign and malignant dermatopathological lesions, we used computer-aided nuclear morphometry to analyze parakeratosis from 28 cases of squamous cell carcinoma, 19 cases of verruca vulgaris, and 23 cases of psoriasiform dermatitis. Significant differences in nuclear area and area variability were observed between benign and malignant cases. These two parameters together could separate most squamous cell carcinomas from benign cases. Through this study, we hope to raise the awareness that even parakeratosis, the most superficial morphological datum available for histopathological evaluation, may harbor distinct changes of nuclear atypia in squamous cell carcinoma. In some overly superficial shave biopsies, parakeratosis may be the only material available for evaluation. For such cases, if squamous cell carcinoma is in the differential diagnosis, then the parakeratotic nuclei should be examined carefully to determine the likelihood of malignancy. Computer-aided nuclear morphometry may have potential diagnostic value for such cases.