Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: HT exhibit varying degrees of glandular fibrosis, leading to some areas having a "nodular-like" appearance
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Artificial intelligence (AI) has been increasingly applied in the medical field, but its accuracy in diagnosing HT-associated thyroid nodules (TNs) still requires further refinement. This article reviews the progress of multimodal ultrasound technology combined with AI in assessing and diagnosing the benign and malignant nature of TNs in patients with HT.
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Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such as nodular goiter and thyroid cancer (especially papillary thyroid carcinoma, PTC), and their risk of
APA
DuanYang S, Qu W, et al. (2026). Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.. European journal of medical research. https://doi.org/10.1186/s40001-026-04092-7
MLA
DuanYang S, et al.. "Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.." European journal of medical research, 2026.
PMID
41721450 ↗
Abstract 한글 요약
Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such as nodular goiter and thyroid cancer (especially papillary thyroid carcinoma, PTC), and their risk of PTC is significantly higher than that of non-HT individuals. Patients with HT exhibit varying degrees of glandular fibrosis, leading to some areas having a "nodular-like" appearance. Some of these nodules may display features suggestive of malignancy, which can be difficult to distinguish using conventional ultrasound. Multimodal ultrasound combined with fine-needle aspiration biopsy (FNAB) has emerged as the most effective method currently for identifying the benign or malignant nature of nodules in the context of HT, owing to its advantages of cost-effectiveness, convenience, and reproducibility. Artificial intelligence (AI) has been increasingly applied in the medical field, but its accuracy in diagnosing HT-associated thyroid nodules (TNs) still requires further refinement. This article reviews the progress of multimodal ultrasound technology combined with AI in assessing and diagnosing the benign and malignant nature of TNs in patients with HT.
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🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반
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