본문으로 건너뛰기
← 뒤로

Enhancement on CT for preoperative diagnosis of metastatic lymph nodes in thyroid cancer: a comparison across experience levels.

1/5 보강
European radiology 📖 저널 OA 34.3% 2022: 1/4 OA 2023: 0/7 OA 2024: 2/11 OA 2025: 18/71 OA 2026: 70/165 OA 2022~2026 2025 Vol.35(1) p. 20-28
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
399 patients with DTC.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Quantitative CT parameters indicating strong LN enhancement demonstrated excellent interobserver agreement and good diagnostic performance. Quantitative assessment of contrast enhancement offers a more objective model for the identification of metastatic LNs.

Roh YH, Chung SR, Yang SJ, Baek JH, Choi YJ, Sung TY

📝 환자 설명용 한 줄

[OBJECTIVES] To investigate the diagnostic performance and interobserver agreement of quantitative CT parameters indicating strong lymph node (LN) enhancement in differentiated thyroid cancer (DTC), c

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • 95% CI 0.8-0.9

이 논문을 인용하기

↓ .bib ↓ .ris
APA Roh YH, Chung SR, et al. (2025). Enhancement on CT for preoperative diagnosis of metastatic lymph nodes in thyroid cancer: a comparison across experience levels.. European radiology, 35(1), 20-28. https://doi.org/10.1007/s00330-024-10919-w
MLA Roh YH, et al.. "Enhancement on CT for preoperative diagnosis of metastatic lymph nodes in thyroid cancer: a comparison across experience levels.." European radiology, vol. 35, no. 1, 2025, pp. 20-28.
PMID 38980412 ↗

Abstract

[OBJECTIVES] To investigate the diagnostic performance and interobserver agreement of quantitative CT parameters indicating strong lymph node (LN) enhancement in differentiated thyroid cancer (DTC), comparing them with qualitative analysis by radiologists of varying experience.

[MATERIALS AND METHODS] This study included 463 LNs from 399 patients with DTC. Three radiologists independently analyzed strong LN enhancement on CT. Qualitative analysis of strong enhancement was defined as LN cortex showing greater enhancement than adjacent muscles on the arterial phase. Quantitative analysis included the mean attenuation value (MAV) of LN on arterial phase (LN) and venous phase (LN), LN normalized to the common carotid artery (NAV), internal jugular vein (NAV), and sternocleidomastoid muscle (NAV), attenuation difference [AD; (LN - MAV)], and relative washout ratio [((LN - LN)/LN) × 100]. The interobserver agreement and diagnostic performance of the quantitative and qualitative analyses were evaluated.

[RESULTS] Interobserver agreement was excellent for all quantitative CT parameters (ICC, 0.83-0.94) and substantial for qualitative assessment (κ = 0.61). All CT parameters except for LN showed good diagnostic performance for metastatic LNs (AUC, 0.81-0.85). NAV (0.85, 95% CI: 0.8-0.9) and AD (0.85, 95% CI: 0.81-0.89) had the highest AUCs. All quantitative parameters except for NAV had significantly higher AUCs than qualitative assessments by inexperienced radiologists, with no significant difference from assessments by an experienced radiologist.

[CONCLUSION] Quantitative assessment of LN enhancement on arterial phase CT showed higher interobserver agreement and AUC values than qualitative analysis by inexperienced radiologists, supporting the need for a standardized quantitative CT parameter-based model for determining strong LN enhancement.

[CLINICAL RELEVANCE STATEMENT] When assessing strong LN enhancement in DTC, quantitative CT parameters indicating strong enhancement can improve interobserver agreement, regardless of experience level. Therefore, the development of a standardized diagnostic model based on quantitative CT parameters might be necessary.

[KEY POINTS] Accurate preoperative assessment of LN metastasis in thyroid cancer is crucial. Quantitative CT parameters indicating strong LN enhancement demonstrated excellent interobserver agreement and good diagnostic performance. Quantitative assessment of contrast enhancement offers a more objective model for the identification of metastatic LNs.

🏷️ 키워드 / MeSH 📖 같은 키워드 OA만

같은 제1저자의 인용 많은 논문 (3)

🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반