Multi-modality imaging parameters that predict rapid tumor regression in head and neck radiotherapy

Eric Aliotta , Ramesh Paudyal , Bill Diplas , James Han , Yu-Chi Hu , Jung Hun Oh , Vaios Hatzoglou , Naomi Jensen , Peng Zhang , Michalis Aristophanous , Nadeem Riaz , Joseph O. Deasy , Nancy Y. Lee , Amita Shukla-Dave
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Abstract

Background and purpose

Volume regression during radiotherapy can indicate patient-specific treatment response. We aimed to identify pre-treatment multimodality imaging (MMI) metrics from positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT) that predict rapid tumor regression during radiotherapy in human papilloma virus (HPV) associated oropharyngeal carcinoma.

Materials and methods

Pre-treatment FDG PET-CT, diffusion-weighted MRI (DW-MRI), and intra-treatment (at 1, 2, and 3 weeks) MRI were acquired in 72 patients undergoing chemoradiation therapy for HPV+ oropharyngeal carcinoma. Nodal gross tumor volumes were delineated on longitudinal images to measure intra-treatment volume changes. Pre-treatment PET standardized uptake value (SUV), CT Hounsfield Unit (HU), and non-gaussian intravoxel incoherent motion DW-MRI metrics were computed and correlated with volume changes. Intercorrelations between MMI metrics were also assessed using network analysis. Validation was carried out on a separate cohort (N = 64) for FDG PET-CT.

Results

Significant correlations with volume loss were observed for baseline FDG SUVmean (Spearman ρ = 0.46, p < 0.001), CT HUmean (ρ = 0.38, p = 0.001), and DW-MRI diffusion coefficient, Dmean (ρ = -0.39, p < 0.001). Network analysis revealed 41 intercorrelations between MMI and volume loss metrics, but SUVmean remained a statistically significant predictor of volume loss in multivariate linear regression (p = 0.01). Significant correlations were also observed for SUVmean in the validation cohort in both primary (ρ = 0.30, p = 0.02) and nodal (ρ = 0.31, p = 0.02) tumors.

Conclusions

Multiple pre-treatment imaging metrics were correlated with rapid nodal gross tumor volume loss during radiotherapy. FDG-PET SUV in particular exhibited significant correlations with volume regression across the two cohorts and in multivariate analysis.

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预测头颈部放疗中肿瘤快速消退的多模态成像参数
背景和目的放疗期间的体积消退可表明患者的特异性治疗反应。我们旨在从正电子发射断层扫描(PET)、磁共振成像(MRI)和计算机断层扫描(CT)中确定治疗前多模态成像(MMI)指标,以预测人乳头状瘤病毒(HPV)相关口咽癌放疗期间肿瘤的快速消退。材料与方法 对 72 名接受化疗的 HPV+ 口咽癌患者进行了治疗前 FDG PET-CT、弥散加权磁共振成像(DW-MRI)和治疗中(1、2 和 3 周)磁共振成像检查。在纵向图像上划定结节性大体肿瘤体积,以测量治疗期间的体积变化。计算治疗前 PET 标准化摄取值 (SUV)、CT 霍斯菲尔德单位 (HU) 和非高斯体外不相干运动 DW-MRI 指标,并将其与体积变化相关联。还利用网络分析法评估了 MMI 指标之间的相互关系。结果基线 FDG SUVmean(Spearman ρ = 0.46,p < 0.001)、CT HUmean(ρ = 0.38,p = 0.001)和 DW-MRI 弥散系数 Dmean(ρ = -0.39,p < 0.001)与体积丢失有显著相关性。网络分析显示,MMI 和容积损失指标之间存在 41 种相互关系,但在多元线性回归中,SUVmean 仍是容积损失的一个具有统计学意义的预测指标(p = 0.01)。在原发性肿瘤(ρ = 0.30,p = 0.02)和结节性肿瘤(ρ = 0.31,p = 0.02)的验证队列中也观察到 SUVmean 的显著相关性。FDG-PET的SUV值尤其与两个队列的肿瘤体积缩小有显著相关性,在多变量分析中也是如此。
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来源期刊
Physics and Imaging in Radiation Oncology
Physics and Imaging in Radiation Oncology Physics and Astronomy-Radiation
CiteScore
5.30
自引率
18.90%
发文量
93
审稿时长
6 weeks
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