文章：

使用单次激发和多次激发回波平面扩散成像技术校正头颈部癌症表观扩散系数测量中的梯度非线性偏差

Correction of Gradient Nonlinearity Bias in Apparent Diffusion Coefficient Measurement for Head and Neck Cancers Using Single- and Multi-Shot Echo Planar Diffusion Imaging

原文发布日期：28 May 2025

DOI: 10.3390/cancers17111796

类型: Article

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英文摘要：

Background/Objectives:This work prospectively evaluates the vendor-provided Low Variance (LOVA) apparent diffusion coefficient (ADC) gradient nonlinearity correction (GNC) technique for primary tumors, neck nodal metastases, and normal masseter muscles in patients with head and neck cancers (HNCs).Methods: Multiple b-value diffusion-weighted (DW)-MR images were acquired on a 3.0 T scanner using a single-shot echo planar imaging (SS-EPI) and multi-shot (MS)-EPI for diffusion phantom materials (20% and 40% polyvinylpyrrolidone (PVP) in water). Pretreatment DW-MRI acquisitions were performed for sixty HNC patients (n = 60) who underwent chemoradiation therapy. ADC values with and without GNC were calculated offline using a monoexponential diffusion model over all b-values, relative percentage (r%) changes (Δ) in ADC values with and without GNC were calculated, and the ADC histograms were analyzed.Results: Mean ADC values calculated using SS-EPI DW data with and without GNC differed by ≤1% for both PVP20% and PVP40% at the isocenter, whereas off-center differences were ≤19.6% for both concentrations. A similar trend was observed for these materials with MS-EPI. In patients, the mean rΔADC (%) values measured with SS-EPI differed by 4.77%, 3.98%, and 5.68% for primary tumors, metastatic nodes, and masseter muscle. MS-EPI exhibited a similar result with 5.56%, 3.95%, and 4.85%, respectively.Conclusions: This study showed that the GNC method improves the robustness of the ADC measurement, enhancing its value as a quantitative imaging biomarker used in HNC clinical trials.

摘要翻译： 

背景/目的：本研究前瞻性评估了供应商提供的低方差（LOVA）表观扩散系数（ADC）梯度非线性校正（GNC）技术，针对头颈癌（HNC）患者原发肿瘤、颈部淋巴结转移灶及正常咬肌的应用效果。方法：使用单次激发平面回波成像（SS-EPI）与多次激发（MS）-EPI序列，在3.0 T扫描仪上对扩散模体材料（20%与40%聚乙烯吡咯烷酮（PVP）水溶液）采集多b值扩散加权（DW）-MR图像。对60例接受放化疗的HNC患者（n=60）进行治疗前DW-MRI扫描。采用单指数扩散模型基于全b值离线计算经GNC校正与未校正的ADC值，计算校正前后ADC值的相对百分比（r%）变化（Δ），并对ADC直方图进行分析。结果：在等中心点处，使用SS-EPI DW数据计算的PVP20%与PVP40%模体经GNC校正与未校正的平均ADC值差异均≤1%；而在偏离中心位置，两种浓度溶液的差异均≤19.6%。MS-EPI序列对上述材料呈现相似趋势。在患者数据中，SS-EPI序列测得原发肿瘤、转移淋巴结及咬肌的平均rΔADC（%）值差异分别为4.77%、3.98%与5.68%；MS-EPI序列相应结果为5.56%、3.95%与4.85%。结论：本研究表明GNC方法可提升ADC测量的稳健性，增强其作为定量影像生物标志物在HNC临床试验中的应用价值。

原文链接：

Correction of Gradient Nonlinearity Bias in Apparent Diffusion Coefficient Measurement for Head and Neck Cancers Using Single- and Multi-Shot Echo Planar Diffusion Imaging