Pretreatment diffusion-weighted and dynamic contrast-enhanced MRI for prediction of local treatment response in squamous cell carcinomas of the head and neck.
Pretreatment diffusion-weighted and dynamic contrast-enhanced MRI for prediction of local treatment response in squamous cell carcinomas of the head and neck.
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DOI：
10.2214/ajr.12.9432
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发表时间：
2013-01
期刊：
影响因子：
--
通讯作者：
Poptani H
中科院分区：
文献类型：
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作者：
Chawla S;Kim S;Dougherty L;Wang S;Loevner LA;Quon H;Poptani H
本研究的目的是通过联合使用原发肿瘤和转移淋巴结的弥散加权成像（DWI）和高空间分辨率、高时间分辨率动态增强MRI（DCE-MRI）参数，预测头颈部鳞状细胞癌（HNSCC）患者对放化疗的反应。32例患者接受了治疗前DWI和DCE-MRI，使用改良的放射状成像序列。数据的后处理包括运动校正算法，以减少运动伪影。计算原发性肿瘤和淋巴结肿块的中位表观扩散系数（ADC）、体积转移常数（Ktranss）、细胞外血管外体积分数（ve）和血浆体积分数（vp）。使用0.10或更小的阈值中位数卡方值来估计DCE-MRI图的质量。使用多变量逻辑回归和受试者工作特征曲线分析来确定区分应答者和无应答者的最佳模型。84%的原发性肿瘤和100%的结节性肿块的χ2值可接受。排除了5例DCE-MRI数据不满意的患者，并从分析中删除了3例死于无关原因的患者的DCEMRI数据。其余患者（n = 24）的中位随访时间为23.72个月。当将原发肿瘤和淋巴结肿块的ADC和DCE-MRI参数（Ktranss、ve、vp）纳入多变量logistic回归分析时，观察到区分应答者（n = 16）和无应答者（n = 8）的显著更高的判别准确性（曲线下面积[AUC] = 0.85），灵敏度为81.3%，特异性为75%。联合使用DWI和DCE-MRI参数从原发肿瘤和结节肿块可能有助于预测放化疗治疗HNSCC患者的反应。
The objective of our study was to predict response to chemoradiation therapy in patients with head and neck squamous cell carcinoma (HNSCC) by combined use of diffusion-weighted imaging (DWI) and high-spatial-resolution, high-temporal-resolution dynamic contrast-enhanced MRI (DCE-MRI) parameters from primary tumors and metastatic nodes. Thirty-two patients underwent pretreatment DWI and DCE-MRI using a modified radial imaging sequence. Postprocessing of data included motion-correction algorithms to reduce motion artifacts. The median apparent diffusion coefficient (ADC), volume transfer constant (Ktrans), extracellular extravascular volume fraction (ve), and plasma volume fraction (vp) were computed from primary tumors and nodal masses. The quality of the DCE-MRI maps was estimated using a threshold median chi-square value of 0.10 or less. Multivariate logistic regression and receiver operating characteristic curve analyses were used to determine the best model to discriminate responders from nonresponders. Acceptable χ2 values were observed from 84% of primary tumors and 100% of nodal masses. Five patients with unsatisfactory DCE-MRI data were excluded and DCEMRI data for three patients who died of unrelated causes were censored from analysis. The median follow-up for the remaining patients (n = 24) was 23.72 months. When ADC and DCE-MRI parameters (Ktrans, ve, vp) from both primary tumors and nodal masses were incorporated into multivariate logistic regression analyses, a considerably higher discriminative accuracy (area under the curve [AUC] = 0.85) with a sensitivity of 81.3% and specificity of 75% was observed in differentiating responders (n = 16) from nonresponders (n = 8). The combined use of DWI and DCE-MRI parameters from both primary tumors and nodal masses may aid in prediction of response to chemoradiation therapy in patients with HNSCC.