Diagnostic performance of T2-weighted imaging and intravoxel incoherent motion diffusion-weighted MRI for predicting metastatic axillary lymph nodes in T1 and T2 stage breast cancer.
| Autor: | Liu, Yuanyuan, Luo, Hongbing, Wang, Chunhua, Chen, Xiaoyu, Wang, Min, Zhou, Peng, Ren, Jing |
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| Předmět: |
LYMPH nodes
BREAST cancer DIFFUSION magnetic resonance imaging LOGISTIC regression analysis MANN Whitney U Test DIGITAL image processing MAGNETIC resonance imaging METASTASIS TUMOR classification DIAGNOSTIC imaging T-test (Statistics) SIGNAL processing DESCRIPTIVE statistics SENSITIVITY & specificity (Statistics) DATA analysis software BREAST tumors AXILLARY lymph node dissection |
| Zdroj: | Acta Radiologica; Apr2022, Vol. 63 Issue 4, p447-457, 11p |
| Abstrakt: | Background: Non-invasive modalities for assessing axillary lymph node (ALN) are needed in clinical practice. Purpose: To investigate the suspicious ALN on unenhanced T2-weighted (T2W) imaging and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) for predicting ALN metastases (ALNM) in patients with T1–T2 stage breast cancer and clinically negative ALN. Material and Methods: Two radiologists identified the most suspicious ALN or the largest ALN in negative axilla by T2W imaging features, including short axis (Size-S), long axis (Size-L)/S ratio, fatty hilum, margin, and signal intensity on T2W imaging. The IVIM parameters of these selected ALNs were also obtained. The Mann–Whitney U test or t-test was used to compare the metastatic and non-metastatic ALN groups. Finally, logistic regression analysis with T2W imaging and IVIM features for predicting ALNM was conducted. Results: This study included 49 patients with metastatic ALNs and 50 patients with non-metastatic ALNs. Using the above conventional features on T2W imaging, the sensitivity and specificity in predicting ALNM were not high. Compared with non-metastatic ALNs, metastatic ALNs had lower pseudo-diffusion coefficient (D*) (P = 0.043). Logistic regression analysis showed that the most useful features for predicting ALNM were signal intensity and D*. The sensitivity and specificity predicting ALNM that satisfied abnormal signal intensity and lower D* were 73.5% and 84%, respectively. Conclusions: The abnormal signal intensity on T2W imaging and one IVIM feature (D*) were significantly associated with ALNM, with sensitivity of 73.5% and specificity of 84%. [ABSTRACT FROM AUTHOR] |
| Databáze: | Complementary Index |
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