Histogram analysis of greyscale sonograms to differentiate between the subtypes of follicular variant of papillary thyroid cancer

M. R. Kwon, J. H. Shin, S. Y. Hahn, Y. L. Oh, J. Y. Kwak, E. Lee, Y. Lim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Aim: To evaluate the diagnostic value of histogram analysis using ultrasound (US) to differentiate between the subtypes of follicular variant of papillary thyroid carcinoma (FVPTC). Materials and methods: The present study included 151 patients with surgically confirmed FVPTC diagnosed between January 2014 and May 2016. Their preoperative US features were reviewed retrospectively. Histogram parameters (mean, maximum, minimum, range, root mean square, skewness, kurtosis, energy, entropy, and correlation) were obtained for each nodule. Results: The 152 nodules in 151 patients comprised 48 non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs; 31.6%), 60 invasive encapsulated FVPTCs (EFVPTCs; 39.5%), and 44 infiltrative FVPTCs (28.9%). The US features differed significantly between the subtypes of FVPTC. Discrimination was achieved between NIFTPs and infiltrative FVPTC, and between invasive EFVPTC and infiltrative FVPTC using histogram parameters; however, the parameters were not significantly different between NIFTP and invasive EFVPTC. Conclusion: It is feasible to use greyscale histogram analysis to differentiate between NIFTP and infiltrative FVPTC, but not between NIFTP and invasive EFVPTC. Histograms can be used as a supplementary tool to differentiate the subtypes of FVPTC.

Original languageEnglish
Pages (from-to)591.e1-591.e7
JournalClinical Radiology
Volume73
Issue number6
DOIs
Publication statusPublished - 2018 Jun

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Papillary Thyroid cancer
Thyroid Neoplasms

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

Cite this

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title = "Histogram analysis of greyscale sonograms to differentiate between the subtypes of follicular variant of papillary thyroid cancer",
abstract = "Aim: To evaluate the diagnostic value of histogram analysis using ultrasound (US) to differentiate between the subtypes of follicular variant of papillary thyroid carcinoma (FVPTC). Materials and methods: The present study included 151 patients with surgically confirmed FVPTC diagnosed between January 2014 and May 2016. Their preoperative US features were reviewed retrospectively. Histogram parameters (mean, maximum, minimum, range, root mean square, skewness, kurtosis, energy, entropy, and correlation) were obtained for each nodule. Results: The 152 nodules in 151 patients comprised 48 non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs; 31.6{\%}), 60 invasive encapsulated FVPTCs (EFVPTCs; 39.5{\%}), and 44 infiltrative FVPTCs (28.9{\%}). The US features differed significantly between the subtypes of FVPTC. Discrimination was achieved between NIFTPs and infiltrative FVPTC, and between invasive EFVPTC and infiltrative FVPTC using histogram parameters; however, the parameters were not significantly different between NIFTP and invasive EFVPTC. Conclusion: It is feasible to use greyscale histogram analysis to differentiate between NIFTP and infiltrative FVPTC, but not between NIFTP and invasive EFVPTC. Histograms can be used as a supplementary tool to differentiate the subtypes of FVPTC.",
author = "Kwon, {M. R.} and Shin, {J. H.} and Hahn, {S. Y.} and Oh, {Y. L.} and Kwak, {J. Y.} and E. Lee and Y. Lim",
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Histogram analysis of greyscale sonograms to differentiate between the subtypes of follicular variant of papillary thyroid cancer. / Kwon, M. R.; Shin, J. H.; Hahn, S. Y.; Oh, Y. L.; Kwak, J. Y.; Lee, E.; Lim, Y.

In: Clinical Radiology, Vol. 73, No. 6, 06.2018, p. 591.e1-591.e7.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Histogram analysis of greyscale sonograms to differentiate between the subtypes of follicular variant of papillary thyroid cancer

AU - Kwon, M. R.

AU - Shin, J. H.

AU - Hahn, S. Y.

AU - Oh, Y. L.

AU - Kwak, J. Y.

AU - Lee, E.

AU - Lim, Y.

PY - 2018/6

Y1 - 2018/6

N2 - Aim: To evaluate the diagnostic value of histogram analysis using ultrasound (US) to differentiate between the subtypes of follicular variant of papillary thyroid carcinoma (FVPTC). Materials and methods: The present study included 151 patients with surgically confirmed FVPTC diagnosed between January 2014 and May 2016. Their preoperative US features were reviewed retrospectively. Histogram parameters (mean, maximum, minimum, range, root mean square, skewness, kurtosis, energy, entropy, and correlation) were obtained for each nodule. Results: The 152 nodules in 151 patients comprised 48 non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs; 31.6%), 60 invasive encapsulated FVPTCs (EFVPTCs; 39.5%), and 44 infiltrative FVPTCs (28.9%). The US features differed significantly between the subtypes of FVPTC. Discrimination was achieved between NIFTPs and infiltrative FVPTC, and between invasive EFVPTC and infiltrative FVPTC using histogram parameters; however, the parameters were not significantly different between NIFTP and invasive EFVPTC. Conclusion: It is feasible to use greyscale histogram analysis to differentiate between NIFTP and infiltrative FVPTC, but not between NIFTP and invasive EFVPTC. Histograms can be used as a supplementary tool to differentiate the subtypes of FVPTC.

AB - Aim: To evaluate the diagnostic value of histogram analysis using ultrasound (US) to differentiate between the subtypes of follicular variant of papillary thyroid carcinoma (FVPTC). Materials and methods: The present study included 151 patients with surgically confirmed FVPTC diagnosed between January 2014 and May 2016. Their preoperative US features were reviewed retrospectively. Histogram parameters (mean, maximum, minimum, range, root mean square, skewness, kurtosis, energy, entropy, and correlation) were obtained for each nodule. Results: The 152 nodules in 151 patients comprised 48 non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs; 31.6%), 60 invasive encapsulated FVPTCs (EFVPTCs; 39.5%), and 44 infiltrative FVPTCs (28.9%). The US features differed significantly between the subtypes of FVPTC. Discrimination was achieved between NIFTPs and infiltrative FVPTC, and between invasive EFVPTC and infiltrative FVPTC using histogram parameters; however, the parameters were not significantly different between NIFTP and invasive EFVPTC. Conclusion: It is feasible to use greyscale histogram analysis to differentiate between NIFTP and infiltrative FVPTC, but not between NIFTP and invasive EFVPTC. Histograms can be used as a supplementary tool to differentiate the subtypes of FVPTC.

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