医学
淋巴血管侵犯
动态对比度
磁共振成像
乳腺癌
乳房磁振造影
磁共振弥散成像
放射科
对比度(视觉)
肿瘤科
转移
癌症
乳腺摄影术
内科学
计算机科学
人工智能
作者
Almıla Coşkun Bilge,Ezel Yaltırık Bilgin,Zarife Melda Bulut,Işıl Esen Bostancı,Erkan Bilgin
标识
DOI:10.1177/08465371231212893
摘要
Purpose: Our single-centre retrospective study aimed to investigate the relationship between preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings and apparent diffusion coefficient (ADC) values and lymphovascular invasion (LVI) status of the lesions in patients with clinically-radiologically lymph node-negative invasive breast cancer. Methods: A total of 250 breast lesions diagnosed in preoperative magnetic resonance imaging were identified. All patients were divided into 2 subgroups: LVI-negative and LVI-positive according to the pathological findings of surgical specimens. The 2 groups’ DCE-MRI findings, ADC values, and histopathological results of lesions were compared. Results: LVI was detected in 100 of 250 lesions. Younger age than 45 years and larger lesion size than 20 mm were found to be associated with the presence of LVI ( P < .001). High histological and nuclear grade ( P = .001), HER2-enriched molecular subtype ( P = .001), and Ki-67 positivity ( P = .016) were significantly associated with LVI. The LVI positivity rate was significantly higher in the lesions with medium-rapid initial phase kinetic curve and washout delayed phase kinetic curve ( P = .001). The presence of LVI was significantly associated with the presence of peritumoural edema, sentinel lymph node metastasis, adjacent vessel sign, and increased whole breast vascularity ( P < .001). When diffusion-weighted imaging findings were evaluated, it was determined that tumoural ADC values lower than 1068 × 10 −6 mm 2 /second ( P = .002) and peritumoural-tumoural ADC ratios higher than 1.5 ( P = .001) statistically increased the probability of LVI. Conclusion: The patient’s age, various histopathological and DCE-MRI findings, tumoural ADC value, and peritumoural-tumoural ADC ratio may be useful in the preoperative prediction of LVI status in breast cancer lesions.
科研通智能强力驱动
Strongly Powered by AbleSci AI