Gemstone Spectral CT Virtual Noncontrast Images and Iodine Maps for the Characterization of Thyroid Lesions and Distinguishing Thyroid Papillary Carcinoma from Nodular Goiter.
Journal
International journal of endocrinology
ISSN: 1687-8337
Titre abrégé: Int J Endocrinol
Pays: Egypt
ID NLM: 101516376
Informations de publication
Date de publication:
2023
2023
Historique:
received:
21
06
2022
revised:
07
12
2022
accepted:
30
01
2023
entrez:
9
3
2023
pubmed:
10
3
2023
medline:
10
3
2023
Statut:
epublish
Résumé
Gemstone spectral contrast-enhanced CT with virtual noncontrast (VNC) images and iodine maps can potentially reduce the number of required CT scans for thyroid lesions. However, data regarding the clinical utility of VNC images and iodine maps in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter are still limited. To determine whether VNC images and iodine density could reliably aid in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter compared with true noncontrast (TNC) images. This retrospective study included patients with thyroid papillary carcinoma or nodular goiter who underwent TNC and contrast-enhanced gemstone spectral CT scans. The consistency of qualitative parameters, including intralesional calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis, between TNC and VNC images, was analyzed using the kappa statistic. TNC attenuation, VNC attenuation, absolute attenuation between TNC and VNC, and iodine density were compared between thyroid papillary carcinoma and nodular goiter by using Student's VNC and TNC imaging showed comparable performance in delineating calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis (all VNC imaging, a promising substitute for TNC imaging, has comparable diagnostic efficacy for reliably characterizing thyroid lesions. Iodine density could be valuable for distinguishing thyroid papillary carcinoma from nodular goiter.
Sections du résumé
Background
UNASSIGNED
Gemstone spectral contrast-enhanced CT with virtual noncontrast (VNC) images and iodine maps can potentially reduce the number of required CT scans for thyroid lesions. However, data regarding the clinical utility of VNC images and iodine maps in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter are still limited.
Purpose
UNASSIGNED
To determine whether VNC images and iodine density could reliably aid in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter compared with true noncontrast (TNC) images.
Methods
UNASSIGNED
This retrospective study included patients with thyroid papillary carcinoma or nodular goiter who underwent TNC and contrast-enhanced gemstone spectral CT scans. The consistency of qualitative parameters, including intralesional calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis, between TNC and VNC images, was analyzed using the kappa statistic. TNC attenuation, VNC attenuation, absolute attenuation between TNC and VNC, and iodine density were compared between thyroid papillary carcinoma and nodular goiter by using Student's
Results
UNASSIGNED
VNC and TNC imaging showed comparable performance in delineating calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis (all
Conclusions
UNASSIGNED
VNC imaging, a promising substitute for TNC imaging, has comparable diagnostic efficacy for reliably characterizing thyroid lesions. Iodine density could be valuable for distinguishing thyroid papillary carcinoma from nodular goiter.
Identifiants
pubmed: 36891376
doi: 10.1155/2023/8220034
pmc: PMC9988381
doi:
Types de publication
Journal Article
Langues
eng
Pagination
8220034Informations de copyright
Copyright © 2023 Chun Yao et al.
Déclaration de conflit d'intérêts
One author of the study (YT L) is a consultant for GE Healthcare; however, she was only responsible for the statistical analysis of features derived from patients' images. All features were anonymous, without the knowledge of patient information such as name, image data, and CT protocol acquisition. Our hospital managed the data, and the authors were responsible for the integrity of the data. The other authors are not employees or consultants in the industrial fields and have not controlled any data or information that may present a conflicts of interest.
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