Computer-Assisted Cell Morphometry and Ploidy Analysis in the Assessment of Thyroid Follicular Neoplasms

Abstract

Conventional cytology cannot discriminate between benign and malignant follicular neoplasms. Our study evaluated the diagnostic role of computer-assisted image analysis in the presurgical assessment of thyroid follicular neoplasms. Fifty-eight patients (14 males, 44 females, age range, 45-75 years) who underwent surgery for cytologic diagnosis of thyroid follicular neoplasm were studied. All patients were first evaluated on clinical grounds and assigned a high/low suspicion of malignancy on the basis of gender, age, and nodule size. Cell image analysis was subsequently performed using a Cytometrica BYK Gulden microscope image processor on Feulgen-stained thyroid cytologic smears. A different population of 50 benign and 50 malignant, histologically evaluated nodules was studied in order to establish image analysis criteria suggestive of thyroid malignancy. Ploidy histogram, proliferation index (PI), nuclear area coefficient of variation (NACV), and anisocariosis ratio (AR) were studied. Thyroid cancer was diagnosed in 16 of 58 follicular neoplasms. Only 7 of these lesions were clinically suspicious (43.7%), whereas 14 of 16 (87.5%) malignant tumors were identified by image analysis. Positive and negative predictive values of image analysis versus clinical evaluation were 46.6% versus 30.4% and 92.8% versus 74.3%, respectively. The distribution of ploidy pattern was different in benign versus malignant follicular neoplasms (chi2 8.25, p = 0.016), malignant lesions showing an increased frequency of heteroclonal aneuploid DNA content (37.5% vs. 7.1%). Increased PI (mean +/- standard deviation (SD) = 11.3 +/- 5.7 vs. 7.1 +/- 6.1; p < 0.01) and NACV (mean +/- SD = 25.28 +/- 1.89 vs. 20.14 0.91; p < 0.01) levels were also observed in malignant follicular neoplasms. In conclusion, computer-assisted image analysis may profitably support clinical evaluation in the assessment of thyroid follicular neoplasms.

Preoperative Evaluation of Thyroid Epithelial Lesions by DNA Ploidy and Galectin-3 Expression in FNAC

“…The present study results were in concordance with Frasoldati et al [41] and Konarska et al [46] who provided significantly higher mean PI in carcinomas than in benign lesions, and stated that PI values were independent of DNA ploidy level. Galectin-3 is a component of soluble beta-galactoside binding lectins, which is up-regulated in thyroid carcinoma, while its expression in normal and benign thyroid tissue is absent or weak.…”

“…Similar results were recorded by Frasoldati et al [41] and Bakr et al [42] and they concluded that aneuploidy was significantly more frequent in malignant cases. However, they also observed that aneuploidy was not exclusive of malignancy; aneuploid follicular adenomas exist and they may represent cases undergoing malignant transformation.…”

“…Many studies suggested that DNA ploidy studies may be a helpful scientific tool in identification of neoplastic epithelial follicular cells, as DNA euploidy excludes the presence of neither malignancy nor neoplasia [6,7]. Furthermore, many studies have also demonstrated that nuclear DNA content and ploidy assessment may be a prognostic factor for patients of thyroid carcinomas [8].…”

Laser induced fluorescence model of human goiter

“…This methodology provides a potentially important tool for replacing the conventional injuring biopsy by noninvasive optical one and performing wide area surveillance using fluorescence imaging techniques [8] or LIF spectra measurements in tissue scanning mode, which we introduce in the present paper. This method has incontestable advantages over advanced conventional diagnostic technologies such as computer-assisted cell morphometry [9].…”

“…4 (adenoma and goiter). In this case adenomatous tissue occupies a much smaller volume (with linear size ≈ 250 µm), which is practically impossible to find even with such an advanced conventional method as fine needle aspiration with computer-assisted cell morphometry [9]. Therefore the possibilities of LIF diagnosis of biological tissue become unique.…”