Can the analysis of chromatin texture and nuclear fractal dimensions serve as effective means to distinguish non-invasive follicular thyroid neoplasm with papillary-like nuclear features from other malignancies with follicular pattern in the thyroid?: a study

ABSTRACT

Objective

Thyroid carcinoma ranks as the 9th most prevalent global cancer, accounting for 586,202 cases and 43,636 deaths in 2020. Computerized image analysis, utilizing artificial intelligence algorithms, emerges as a potential tool for tumor evaluation.

Aim

This study aims to assess and compare chromatin textural characteristics and nuclear dimensions in follicular neoplasms through gray-level co-occurrence matrix (GLCM), fractal, and morphometric analysis.

Method

A retrospective cross-sectional study involving 115 thyroid malignancies, specifically 49 papillary thyroid carcinomas with follicular morphology, was conducted from July 2021 to July 2023. Ethical approval was obtained, and histopathological examination, along with image analysis, was performed using ImageJ software.

Results

A statistically significant difference was observed in contrast (2.426 (1.774–3.412) vs 2.664 (1.963–3.610), p = .002), correlation (1.202 (1.071–1.298) vs 0.892 (0.833–0.946), p = .01), and ASM (0.071 (0.090–0.131) vs 0.044 (0.019–0.102), p = .036) between NIFTP and IFVPTC. However, morphometric parameters did not yield statistically significant differences among histological variants

Conclusion

Computerized image analysis, though promising in subtype discrimination, requires further refinement and integration with traditional diagnostic parameters. The study suggests potential applications in scenarios where conventional histopathological assessment faces limitations due to limited tissue availability. Despite limitations such as a small sample size and a retrospective design, the findings contribute to understanding thyroid carcinoma characteristics and underscore the need for comprehensive evaluations integrating various diagnostic modalities.

KEYWORDS:

• Cancer
• endocrine system
• image processing
• thyroid

Disclosure statement

No potential conflict of interest was reported by the author(s).

Consent to participate statement

The study, being a retrospective study will collect all patient related data from the hospital medical records only. The study involves no more than minimal risk to the study subjects. Therefore, the institutional ethics committee, has granted an exemption from requiring written informed consent for the study.

Statement of ethics

This study protocol was reviewed and approved by Institutional ethics committee, (IEC(H) Reg. No. EC/NEW/INST/2020/1221.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.