Johansen Roar, Jensen Line R, Rydland Jana, Goa Pål E, Kvistad Kjell A, Bathen Tone F, Axelson David E, Lundgren Steinar, Gribbestad Ingrid S
Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
J Magn Reson Imaging. 2009 Jun;29(6):1300-7. doi: 10.1002/jmri.21778.
To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5-year survival in patients with locally advanced breast cancer.
DCE-MRI was performed in patients scheduled for NAC (n = 24) before and after the first treatment cycle. Clinical response was evaluated after completed NAC. Relative signal intensity (RSI) and area under the curve (AUC) were calculated from the DCE-curves and compared to clinical treatment response. Kohonen and probabilistic neural network (KNN and PNN) analysis were used to predict 5-year survival.
RSI and AUC were reduced after only one cycle of NAC in patients with clinical treatment response (P = 0.02 and P = 0.08). The mean and 10th percentile RSI values before NAC were significantly lower in patients surviving more than 5 years compared to nonsurvivors (P = 0.05 and 0.02). This relationship was confirmed using KNN, which demonstrated that patients who remained alive clustered in separate regions from those that died. Calibration of contrast enhancement curves by PNN for patient survival at 5 years yielded sensitivity and specificity for training and testing ranging from 80%-92%.
DCE-MRI in locally advanced breast cancer has the potential to predict 5-year survival in a small patient cohort. In addition, changes in tumor vascularization after one cycle of NAC can be assessed.
评估动态对比增强磁共振成像(DCE-MRI)作为早期预测局部晚期乳腺癌患者新辅助化疗(NAC)疗效及5年生存率的工具。
对计划接受NAC的患者(n = 24)在第一个治疗周期前后进行DCE-MRI检查。在完成NAC后评估临床疗效。从DCE曲线计算相对信号强度(RSI)和曲线下面积(AUC),并与临床治疗反应进行比较。采用Kohonen和概率神经网络(KNN和PNN)分析预测5年生存率。
临床治疗有反应的患者在仅一个周期的NAC后,RSI和AUC降低(P = 0.02和P = 0.08)。5年以上生存患者NAC前的平均RSI值和第10百分位数RSI值显著低于未生存患者(P = 0.05和0.02)。使用KNN证实了这种关系,结果表明存活患者与死亡患者聚集在不同区域。PNN对患者5年生存率的对比增强曲线校准得出训练和测试的敏感性和特异性范围为80%-92%。
局部晚期乳腺癌的DCE-MRI有可能在一小群患者中预测5年生存率。此外,可评估NAC一个周期后肿瘤血管生成的变化。