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A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study.
Li, Zongbao; Zhong, Yifan; Lv, Yan; Zheng, Jianzhong; Hu, Yu; Yang, Yanyan; Li, Yunxi; Sun, Meng; Liu, Siqian; Guo, Yan; Zhang, Mengchao; Zhou, Le.
Afiliación
  • Li Z; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Zhong Y; Department of Radiology, Affiliated Fifth People's Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 611130, China.
  • Lv Y; Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Zheng J; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Hu Y; Department of Radiology, The People's Hospital of Bao'an, Shenzhen University, Shenzhen, 518101, China.
  • Yang Y; Department of Radiology, The People's Hospital of Bao'an, Shenzhen University, Shenzhen, 518101, China.
  • Li Y; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Sun M; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Liu S; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Guo Y; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China.
  • Zhang M; Life Sciences, GE Healthcare, Shenyang, 110000, China.
  • Zhou L; Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, 130000, China. zhangmengchao@jlu.edu.cn.
Cancer Imaging ; 24(1): 62, 2024 May 15.
Article en En | MEDLINE | ID: mdl-38750551
ABSTRACT

OBJECTIVES:

To develop and validate radiomics model based on computed tomography (CT) for preoperative prediction of CN0 status in patients with papillary thyroid carcinoma (PTC).

METHODS:

A total of 548 pathologically confirmed LNs (243 non-metastatic and 305 metastatic) two distinct hospitals were retrospectively assessed. A total of 396 radiomics features were extracted from arterial-phase CT images, where the strongest features containing the most predictive potential were further selected using the least absolute shrinkage and selection operator (LASSO) regression method. Delong test was used to compare the AUC values of training set, test sets and cN0 group.

RESULTS:

The Rad-score showed good discriminating performance with Area Under the ROC Curve (AUC) of 0.917(95% CI, 0.884 to 0.950), 0.892 (95% CI, 0.833 to 0.950) and 0.921 (95% CI, 868 to 0.973) in the training, internal validation cohort and external validation cohort, respectively. The test group of CN0 with a AUC of 0.892 (95% CI, 0.805 to 0.979). The accuracy was 85.4% (sensitivity = 81.3%; specificity = 88.9%) in the training cohort, 82.9% (sensitivity = 79.0%; specificity = 88.7%) in the internal validation cohort, 85.4% (sensitivity = 89.7%; specificity = 83.8%) in the external validation cohort, 86.7% (sensitivity = 83.8%; specificity = 91.3%) in the CN0 test group.The calibration curve demonstrated a significant Rad-score (P-value in H-L test > 0.05). The decision curve analysis indicated that the rad-score was clinically useful.

CONCLUSIONS:

Radiomics has shown great diagnostic potential to preoperatively predict the status of cN0 in PTC.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias de la Tiroides / Tomografía Computarizada por Rayos X / Cáncer Papilar Tiroideo Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Cancer Imaging / Cancer imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM / NEOPLASIAS Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias de la Tiroides / Tomografía Computarizada por Rayos X / Cáncer Papilar Tiroideo Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Cancer Imaging / Cancer imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM / NEOPLASIAS Año: 2024 Tipo del documento: Article País de afiliación: China