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Utility of time-dependent diffusion MRI based microstructural parameters in predicting lymph node metastasis in breast cancer.

1/5 보강
European journal of radiology 📖 저널 OA 9.4% 2022: 0/1 OA 2023: 0/2 OA 2024: 0/4 OA 2025: 1/40 OA 2026: 10/67 OA 2022~2026 2026 Vol.194() p. 112515
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
추출되지 않음
I · Intervention 중재 / 시술
preoperative magnetic resonance imaging (MRI), incorporating both conventional MRI and td-dMRI
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Quantitative MRI parameters were compared using Student's t-test or the Mann-Whitney U test.

Chen S, Bai J, Guo X, Xiao Z, Chen M, Thorsten F

📝 환자 설명용 한 줄

[PURPOSE] This study aimed to evaluate the potential of time-dependent diffusion magnetic resonance imaging (td-dMRI) quantitative parameters in differentiating lymph node metastasis status in breast

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • 표본수 (n) 56
  • p-value P < 0.001
  • Sensitivity 85.7 %
  • Specificity 79.2 %

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↓ .bib ↓ .ris
APA Chen S, Bai J, et al. (2026). Utility of time-dependent diffusion MRI based microstructural parameters in predicting lymph node metastasis in breast cancer.. European journal of radiology, 194, 112515. https://doi.org/10.1016/j.ejrad.2025.112515
MLA Chen S, et al.. "Utility of time-dependent diffusion MRI based microstructural parameters in predicting lymph node metastasis in breast cancer.." European journal of radiology, vol. 194, 2026, pp. 112515.
PMID 41242317 ↗

Abstract

[PURPOSE] This study aimed to evaluate the potential of time-dependent diffusion magnetic resonance imaging (td-dMRI) quantitative parameters in differentiating lymph node metastasis status in breast cancer patients.

[METHODS] This retrospective study included 109 breast cancer patients who underwent preoperative magnetic resonance imaging (MRI), incorporating both conventional MRI and td-dMRI. Four microstructural parameters, including cell diameter, extracellular water diffusion coefficient, intracellular volume fraction, and cellular density, were estimated with the imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) method, along with three apparent diffusion coefficient (ADC) values at different frequencies. Patients were classified into lymph node metastatic (n = 56) and non-metastatic (n = 53) groups based on pathological findings. Quantitative MRI parameters were compared using Student's t-test or the Mann-Whitney U test. Binary logistic regression was used to identify independent predictors of lymph node metastasis, and receiver operating characteristic (ROC) curve analysis was performed to evaluate the model's performance. Independent predictive factors were identified, and a nomogram model was developed. The calibration of the model was subsequently evaluated by plotting a calibration curve. A P-value < 0.05 was considered statistically significant.

[RESULTS] Td-dMRI parameters revealed significant differences, with the metastatic group showing a higher intracellular volume fraction (0.301 ± 0.088 vs. 0.228 ± 0.066; P < 0.001) and cell diameter (13.999 ± 1.962 μm vs. 12.069 ± 2.331 μm; P < 0.001). Additionally, the metastatic group exhibited significantly lower ADC, ADC, and ADC values (1.174 ± 0.133 × 10 mm/s, 1.057 ± 0.141 × 10 mm/s, and 0.790 ± 0.128 × 10 mm/s, respectively) compared to the non-metastatic group (1.425 ± 0.167 × 10 mm/s, 1.248 ± 0.192 × 10 mm/s, and 1.031 ± 0.207 × 10 mm/s; P < 0.001). ROC analysis yielded an area under the curve (AUC) of 0.892 for ADC. Binary logistic regression identified cell diameter and ADC as independent predictors of metastasis, achieving a combined AUC of 0.910, with a sensitivity of 85.7 % and specificity of 79.2 %. A nomogram was developed based on the identified independent risk factors, and the calibration curve indicated good agreement between the predicted and observed probabilities. Inter-observer intraclass correlation coefficient (ICC) values were all above 0.85, indicating excellent reliability.

[CONCLUSIONS] Td-dMRI microstructural mapping is a promising tool for distinguishing lymph node metastasis status in breast cancer. Independent parameters such as cell diameter and ADC provide reliable metrics to support clinical decision-making and personalized treatment strategies.

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