Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy.
Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy.
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作者：
免疫疗法针对患者的免疫系统来对抗癌症。这项回顾性研究的目的是评估肿瘤对术前免疫治疗的反应，并在早期治疗时间点使用MRI预测病理学完全反应。基于我们对多中心I-SPY 2临床试验队列的分析，我们发现弥散加权MRI在评估免疫治疗方面上级动态对比增强MRI，后者是标准和最常用的MRI模式，而在仅提供标准化疗的对照队列中未观察到显著差异。本研究验证了以下假设：弥散加权MRI（DWI）中测量的表观弥散系数（ADC）的变化是一种独立的成像标记物，ADC在评估接受新辅助免疫治疗的局部晚期乳腺癌患者的治疗反应方面优于功能性肿瘤体积（FTV）。共有249例患者被随机分配到标准新辅助化疗与pembrolizumab（pembro）或无pembrolizumab（对照）。分析治疗开始前和治疗开始后3周进行的DCE-MRI和DWI。使用逻辑回归模型评估肿瘤ADC指标（平均值，ADC直方图的第5至第95位）和FTV的百分比变化，以预测病理完全缓解（pCR）。pembro队列中平均ADC百分比变化的ROC曲线下面积（AUC）估计值（0.73，95%置信区间[CI]：0.52 - 0.93）高于对照队列（0.63，95% CI：0.43 - 0.83）。在对照队列中，第95百分位数ADC的百分比变化达到最高AUC，0.69（95% CI：0.52 - 0.85）。在pembro队列中，第25百分位数ADC的百分比变化达到最高AUC，0.75（95% CI：0.55 - 0.95）。pembro和对照队列的FTV百分比变化的AUC估计值分别为0.61（95% CI：0.39 - 0.83）和0.66（95% CI：0.47 - 0.85）。在新辅助免疫治疗的早期治疗时间点，肿瘤ADC可能比FTV更好地预测pCR。
Immunotherapy targets patients’ immune systems to fight cancer. The aim of this retrospective study is to assess tumor response to pre-operative immunotherapy and predict pathologic complete response using MRI at an early treatment time- point. Based on our analysis with a cohort from the multi-center I-SPY 2 clinical trial, we found diffusion-weighted MRI is superior to dynamic contrast-enhanced MRI, where the latter is a standard and most-commonly used MRI modality, in assessing immunotherapy, while no significant difference was observed in the control cohort where only standard chemotherapy was provided. This study tested the hypothesis that a change in the apparent diffusion coefficient (ADC) measured in diffusion-weighted MRI (DWI) is an independent imaging marker, and ADC performs better than functional tumor volume (FTV) for assessing treatment response in patients with locally advanced breast cancer receiving neoadjuvant immunotherapy. A total of 249 patients were randomized to standard neoadjuvant chemotherapy with pembrolizumab (pembro) or without pembrolizumab (control). DCE-MRI and DWI, performed prior to and 3 weeks after the start of treatment, were analyzed. Percent changes of tumor ADC metrics (mean, 5th to 95th percentiles of ADC histogram) and FTV were evaluated for the prediction of pathologic complete response (pCR) using a logistic regression model. The area under the ROC curve (AUC) estimated for the percent change in mean ADC was higher in the pembro cohort (0.73, 95% confidence interval [CI]: 0.52 to 0.93) than in the control cohort (0.63, 95% CI: 0.43 to 0.83). In the control cohort, the percent change of the 95th percentile ADC achieved the highest AUC, 0.69 (95% CI: 0.52 to 0.85). In the pembro cohort, the percent change of the 25th percentile ADC achieved the highest AUC, 0.75 (95% CI: 0.55 to 0.95). AUCs estimated for percent change of FTV were 0.61 (95% CI: 0.39 to 0.83) and 0.66 (95% CI: 0.47 to 0.85) for the pembro and control cohorts, respectively. Tumor ADC may perform better than FTV to predict pCR at an early treatment time-point during neoadjuvant immunotherapy.
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影响因子：
19.7
作者：
Park, Sang Hee;Moon, Woo Kyung;Noh, Dong-Young
通讯作者：
Noh, Dong-Young
影响因子：
3.4
作者：
Li, Xi-ru;Cheng, Liu-quan;Liu, Lei
通讯作者：
Liu, Lei
DOI：
10.1186/s13054-017-1678-1
发表时间：
2017-04-14
期刊：
Critical care (London, England)
影响因子：
--
作者：
Kroschinsky F;Stölzel F;von Bonin S;Beutel G;Kochanek M;Kiehl M;Schellongowski P;Intensive Care in Hematological and Oncological Patients (iCHOP) Collaborative Group
通讯作者：
Intensive Care in Hematological and Oncological Patients (iCHOP) Collaborative Group
影响因子：
19.7
作者：
Partridge, Savannah C.;Zhang, Zheng;Hylton, Nola M.
通讯作者：
Hylton, Nola M.
影响因子：
5.9
作者：
Minarikova L;Bogner W;Pinker K;Valkovič L;Zaric O;Bago-Horvath Z;Bartsch R;Helbich TH;Trattnig S;Gruber S
通讯作者：
Gruber S