A Thyroid Ultrasound Image-based Artificial Intelligence Model for Diagnosis of Central Compartment Lymph Node Metastasis in Papillary Thyroid Carcinoma / 中国医学科学院学报
Acta Academiae Medicinae Sinicae
; (6): 911-916, 2021.
Article
in Zh
| WPRIM
| ID: wpr-921559
Responsible library:
WPRO
ABSTRACT
Objective To establish an artificial intelligence model based on B-mode thyroid ultrasound images to predict central compartment lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC). Methods We retrieved the clinical manifestations and ultrasound images of the tumors in 309 patients with surgical histologically confirmed PTC and treated in the First Medical Center of PLA General Hospital from January to December in 2018.The datasets were split into the training set and the test set.We established a deep learning-based computer-aided model for the diagnosis of CLNM in patients with PTC and then evaluated the diagnosis performance of this model with the test set. Result The accuracy,sensitivity,specificity,and area under receiver operating characteristic curve of our model for predicting CLNM were 80%,76%,83%,and 0.794,respectively. Conclusion Deep learning-based radiomics can be applied in predicting CLNM in patients with PTC and provide a basis for therapeutic regimen selection in clinical practice.
Key words
Full text:
1
Index:
WPRIM
Main subject:
Thyroid Neoplasms
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Artificial Intelligence
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Retrospective Studies
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Risk Factors
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Thyroid Cancer, Papillary
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Lymph Nodes
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Lymphatic Metastasis
Type of study:
Diagnostic_studies
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Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limits:
Humans
Language:
Zh
Journal:
Acta Academiae Medicinae Sinicae
Year:
2021
Type:
Article