Nuclear morphometry in indeterminate thyroid nodules

Morphometric study in thyroid tumors

Various morphonuclear studies using digital image analysis have been taken into account in order to establish the malignancy of thyroid lesions based on their size and on the chromatographic characteristics of tumor cell nuclei. Nuclear morphometry involves the measurement of nuclear parameters to obtain diagnostically important information in an objective and reproducible manner. The aim of the present study was to evaluate the detailed morphometric analysis of histopathological preparations with lesions of the thyroid gland and to investigate its role in differentiating between benign and malignant thyroid lesions. The present study included 10 benign and 26 malignant thyroid cases with different selected thyroid lesions. Using a microscope connected to a computerized video system, nuclear morphometric parameters including the nuclear area, perimeter, average intensity, red average, width and roundness, were measured and analyzed. The main parameters used in the statistical calculation were significant in distinguishing between benign and malignant thyroid lesions. The association of morphometry in cytological smears for suspected malignant follicular lesions led to increased accuracy in establishing a suspicious malignant diagnosis for follicular lesions. Nuclear morphometry provides an unbiased point of view that increases diagnosis accuracy. Computerized morphometry can positively influence diagnostic accuracy, allowing for a better correlation with clinical and imaging data.

The Role of Cytomorphometric Image Analysis in the Diagnosis of Thyroid Nodules

Introduction Fine needle aspiration cytology (FNAC) plays a vital role in the diagnosis of thyroid nodules. However, it is challenging due to the heterogeneity of thyroid nodules, overlapping cytomorphological features, and interobserver variability. Cytomorphometric analysis turns subjective observations into quantitative values. In this study, we performed cytomorphometric image analysis on cytological smears of thyroid nodules, classified according to The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). Materials and methods A retrospective analysis of Papanicolaou (PAP) and Hematoxylin & Eosin (H&E) stained fine needle aspirate smears from 50 patients with thyroid nodules with available follow-up histopathology was performed for a period of two years (March 2021 - March 2023), after obtaining approval from the institutional human ethical committee (IHEC-LOP/2020/IM0355). The nodules were categorized according to TBSRTC and were then subjected to cytomorphometric image analysis. Each nucleus was analyzed for 14 parameters, including aspect ratio, intensity, diameter, perimeter, roundness, area, fractal dimension, feret diameter, circularity, radii, fournier description, and chromatin texture parameters such as heterogeneity and clumpiness. The data obtained was analyzed through relevant statistical methods using SPSS version 23 (IBM Inc., Armonk, New York) and was compared by using the analysis of variance (ANOVA) test and post hoc test. Results Our results revealed that cytomorphometric image analysis not only distinguishes benign and malignant thyroid nodules but also can aid in categorizing thyroid nodules with predominant follicular patterns, such as follicular variant of papillary carcinoma, follicular adenoma and follicular carcinoma (p<0.001). Conclusions Morphometric analysis of cytological smears combined with cytomorphology has the potential to be an important tool in the diagnosis of thyroid nodules. It can improve diagnostic accuracy for better treatment and improved prognosis.

Nuclear morphometry and chromatin texture changes in hepatocellular carcinoma samples may predict outcomes of liver transplanted patients

Background

Nuclear changes are typical in the carcinogenesis of hepatocellular carcinoma (HCC). Morphometry and chromatin texture analysis are quantitative methods for their quantification. In this study, we analyzed nuclear morphometry and chromatin texture parameters in samples of hepatocellular carcinoma from liver transplant patients and their associations with clinicopathologic variables.

Methods

Samples of HCC and adjacent tissue from 34 individuals were collected in tissue microarray blocks. Stained slides were microphotographed using an optical microscope and nuclear parameters analyzed in ImageJ (FracLac plug-in). ROC curve analysis was used to find accurate cut-offs for differentiation of neoplastic and non-neoplastic cells. The inter-rater agreement was also evaluated.

Results

Nuclear morphometric and textural differences were observed between the samples of HCC and adjacent tissue of liver transplant patients. Lower mean gray value (p = 0.034) and Feret diameter (p = 0.024) were associated with higher Model for End-Stage Liver Disease (MELD) scores. Nuclei with larger area (p = 0.014) and larger Feret diameter (p = 0.035) were associated with lower survival. Lower aspect ratio was associated with HCC recurrence after the transplant (p = 0.048). The cut-off of 1.13 μm (p =  < 0.001) for aspect ratio and cut-off of 21.15 μm (p = 0.038) for perimeter were established for the differentiation of neoplastic and non-neoplastic cells. The morphometric analysis was reproducible to area, circularity, Feret diameter, mean gray value and aspect ratio between observers (p =  < 0.001).

Conclusions

Nuclear morphometric differences between the HCC and the adjacent tissue samples were associated with prognostic variables (MELD scores, recurrence and survival) and may predict liver transplant patients’ outcomes.