A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study.
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.Palabras clave
Texto completo:
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Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Tiroides
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Tomografía Computarizada por Rayos X
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Cáncer Papilar Tiroideo
Límite:
Adult
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Aged
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Female
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Humans
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Male
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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