Pickles Martin D, Lowry Martin, Manton David J, Gibbs Peter, Turnbull Lindsay W
Post-graduate Medical School, Division of Cancer, Centre for Magnetic Resonance Investigations, University of Hull, UK.
Breast Cancer Res Treat. 2005 May;91(1):1-10. doi: 10.1007/s10549-004-5819-2.
Neoadjuvant chemotherapy has become the standard treatment for patients with locally advanced breast cancer; however a technique that can accurately differentiate responders from non-responders at an early time point during treatment has still to be identified. The purpose of this work was to evaluate the ability of pharmacokinetically modelled dynamic contrast-enhanced MRI data to predict and monitor response of patients diagnosed with locally advanced breast cancer to neoadjuvant chemotherapy, at an early time point during treatment. Sixty-eight patients with histology proven breast cancer underwent MRI examination prior to treatment, early during treatment and following the final cycle of chemotherapy. A two compartment pharmacokinetic model provided the kinetic parameters transfer constant (Ktrans), rate constant (Kep) and extracellular extravascular space (Ve) for a region of interest encompassing the whole lesion (ROIwhole) and a 3x3 pixel 'hot-spot' showing the greatest mean maximum percentage enhancement from within that region (ROIhs). Following treatment 48 patients were classified as responders and 20 as non-responders based on total tumour volume reduction. Tumour volume changes between the pre-treatment and early treatment time points demonstrated differences between responders and non-responders with percentage change revealing the most significant result (p<0.001). Analysis based on ROIhs provided more statistically significant differences between responders and non-responders then ROIwhole analysis. ROIhs analysis demonstrated differences between responders and non-responders both prior to and early during treatment. A highly significant reduction in both Ktrans and Kep (p<0.001) was noted for responders between the pre-treatment and early treatment time points, while Ve significantly increased during the same time period for non-responders (p<0.001). Quantification of dynamic contrast enhancement parameters provides a potential means for differentiating responders from non-responders early during their treatment, thereby allowing a prompt change in treatment if necessary.
新辅助化疗已成为局部晚期乳腺癌患者的标准治疗方法；然而，一种能够在治疗早期准确区分反应者与无反应者的技术仍有待确定。这项工作的目的是评估药代动力学建模的动态对比增强MRI数据在治疗早期预测和监测诊断为局部晚期乳腺癌的患者对新辅助化疗反应的能力。68例经组织学证实为乳腺癌的患者在治疗前、治疗早期和化疗最后一个周期后接受了MRI检查。一个双室药代动力学模型为包含整个病变的感兴趣区域（ROIwhole）和显示该区域内最大平均最大百分比增强的3x3像素“热点”（ROIhs）提供了动力学参数转移常数（Ktrans）、速率常数（Kep）和细胞外血管外间隙（Ve）。治疗后，根据肿瘤总体积减少情况，48例患者被分类为反应者，20例为无反应者。治疗前和治疗早期时间点之间的肿瘤体积变化显示反应者和无反应者之间存在差异，百分比变化显示出最显著的结果（p<0.001）。基于ROIhs的分析比基于ROIwhole的分析在反应者和无反应者之间提供了更具统计学意义的差异。ROIhs分析显示反应者和无反应者在治疗前和治疗早期均存在差异。在治疗前和治疗早期时间点之间，反应者的Ktrans和Kep均显著降低（p<0.001），而无反应者在同一时期Ve显著增加（p<0.001）。动态对比增强参数的量化为在治疗早期区分反应者与无反应者提供了一种潜在方法，从而在必要时允许及时改变治疗方案。
