Indeterminate thyroid cytology: Detecting malignancy using analysis of nuclear images

Background: Thyroid nodules diagnosed as 'atypia of undetermined significance/ follicular lesion of undetermined significance' (AUS/FLUS) or 'follicular neoplasm/ suspected follicular neoplasm' (FN/SFN), according to Bethesda’s classification, represena challenge in clinical practice. Computerized analysis of nuclear images (CANI) could be a useful tool for these cases. Our aim was to evaluate the ability of CANI to correctly classify AUS/FLUS and FN/SFN thyroid nodules for malignancy. Methods: We studied 101 nodules cytologically classified as AUS/FLUS (n = 68) or FN/SFN (n = 33) from 97 thyroidectomy patients. Slides with cytological material were submitted for manual selection and analysis of the follicular cell nuclei for morphometric and texture parameters using ImageJ software. The histologically benign and malignant lesions were compared for such parameters which were then evaluated for the capacity to predict malignancy using the classification and regression trees gini model. The intraclass coefficient of correlation was used to evaluate method reproducibility. Results: In AUS/FLUS nodule analysis, the benign and malignant nodules differed for entropy (P < 0.05), while the FN/SFN nodules differed for fractal analysis, coefficient of variation (CV) of roughness, and CV-entropy (P < 0.05). Considering the AUS/FLUS and FN/SFN nodules separately, it correctly classified 90.0 and 100.0% malignant nodules, with a correct global classification of 94.1 and 97%, respectively. We observed that reproducibility was substantially or nearly complete (0.61–0.93) in 10 of the 12 nuclear parameters evaluated. Conclusion: CANI demonstrated a high capacity for correctly classifying AUS/FLUS and FN/SFN thyroid nodules for malignancy. This could be a useful method to help increase diagnostic accuracy in the indeterminate thyroid cytology.This study received financial support from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP; processes number 2016/14987-0 and number 2016/14988-6). Further funding through 'Fundação para a Ciência e Tecnologi' – FCT and FEDER 'Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020'; by Operacional Programme for Competitiveness and Internationalization 'POCI' (Grant no. POCI-01-0145-FEDER-007274); by the 'Advancing cancer research: from basic knowledge to application' (grant no. NORTE-01-0145-FEDER-000029); and by the 'Projetos Estruturados de I & D & I', funded by Norte 2020 – Programa Operacional Regional do Norte

Follicular lesions with papillary nuclear characteristics: Differences in chromatin detected by computerized image analysis

Objective: Follicular lesions of the thyroid with papillary carcinoma nuclear characteristics are classified as infiltrative follicular variant of papillary thyroid carcinoma-FVPTC (IFVPTC), encapsulated/ well demarcated FVPTC with tumour capsular invasion (IEFVPTC), and the newly described category “non-invasive follicular thyroid neoplasm with papillary-like nuclear features” (NIFTP) formerly known as non-invasive encapsulated FVPTC.This study evaluated whether computerized image analysis can detect nuclear differences between these three tumour subtypes. Materials and methods: Slides with histological material from 15 cases of NIFTP and 33 cases of FVPTC subtypes (22 IEFVPTC, and 11 IFVPTC) were analyzed using the Image J image processing program.Tumour cells were compared for both nuclear morphometry and chromatin textural characteristics. Results: Nuclei from NIFTP and IFVPTC tumours differed in terms of chromatin textural features (grey intensity): mean (92.37 ± 21.01 vs 72.99 ± 14.73, p = 0.02), median (84.93 ± 21.17 vs 65.18 ± 17.08, p = 0.02), standard deviation (47.77 ± 9.55 vs 39.39 ± 7.18; p = 0.02), and coefficient of variation of standard deviation (19.96 ± 4.01 vs 24.75 ± 3.31; p = 0.003). No differences were found in relation to IEFVPTC. Conclusion: Computerized image analysis revealed differences in nuclear texture between NIFTP and IFVPTC, but not for IEFVPTC.The present study was supported by a fellowships supporting from Sao Paulo State University (PROPE- -Unesp; process no. 33347) and Fundação de Amparo à Pesquisa do Estado de São Paulo (Fapesp; process nº 2014/10028-2). Further funding was obtained from FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE 2020 – Operational Program for Competitiveness and Internationalization (POCI), Portugal 2020, and by Portuguese funds through FCT (Fundação para a Ciência e a Tecnologia)/Ministério da Ciência, Tecnologia e Inovação in the framework of the project “Advancing cancer research: from basic knowledgment to application”; NORTE-01-0145-FEDER-000029; “Projetos Estruturados de I&D&I, funded by Norte 2020-Programa Operacional Regional do Norte