Heiselman Jon S, Ecker Brett L, Langdon-Embry Liana, O'Reilly Eileen M, Miga Michael I, Jarnagin William R, Do Richard K G, Horvat Natally, Wei Alice C, Chakraborty Jayasree
Memorial Sloan Kettering Cancer Center, Department of Surgery, Hepatopancreatobiliary Unit, New York, New York, United States.
Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States.
J Med Imaging (Bellingham). 2023 May;10(3):036002. doi: 10.1117/1.JMI.10.3.036002. Epub 2023 Jun 2.
Pancreatic ductal adenocarcinoma (PDAC) frequently presents as hypo- or iso-dense masses with poor contrast delineation from surrounding parenchyma, which decreases reproducibility of manual dimensional measurements obtained during conventional radiographic assessment of treatment response. Longitudinal registration between pre- and post-treatment images may produce imaging biomarkers that more reliably quantify treatment response across serial imaging.
Thirty patients who prospectively underwent a neoadjuvant chemotherapy regimen as part of a clinical trial were retrospectively analyzed in this study. Two image registration methods were applied to quantitatively assess longitudinal changes in tumor volume and tumor burden across the neoadjuvant treatment interval. Longitudinal registration errors of the pancreas were characterized, and registration-based treatment response measures were correlated to overall survival (OS) and recurrence-free survival (RFS) outcomes over 5-year follow-up. Corresponding biomarker assessments via manual tumor segmentation, the standardized response evaluation criteria in solid tumors (RECIST), and pathological examination of post-resection tissue samples were analyzed as clinical comparators.
Average target registration errors were for a biomechanical image registration algorithm and for a diffeomorphic intensity-based algorithm, corresponding to 1-2 times voxel resolution. Cox proportional hazards analysis showed that registration-derived changes in tumor burden were significant predictors of OS and RFS, while none of the alternative comparators, including manual tumor segmentation, RECIST, or pathological variables were associated with consequential hazard ratios. Additional ROC analysis at 1-, 2-, 3-, and 5-year follow-up revealed that registration-derived changes in tumor burden between pre- and post-treatment imaging were better long-term predictors for OS and RFS than the clinical comparators.
Volumetric changes measured by longitudinal deformable image registration may yield imaging biomarkers to discriminate neoadjuvant treatment response in ill-defined tumors characteristic of PDAC. Registration-based biomarkers may help to overcome visual limits of radiographic evaluation to improve clinical outcome prediction and inform treatment selection.
胰腺导管腺癌（PDAC）常表现为低密度或等密度肿块，与周围实质的对比度差，这降低了在传统放射学治疗反应评估中获得的手动尺寸测量的可重复性。治疗前和治疗后图像之间的纵向配准可能会产生成像生物标志物，从而更可靠地量化连续成像中的治疗反应。
本研究回顾性分析了30例作为临床试验一部分前瞻性接受新辅助化疗方案的患者。应用两种图像配准方法定量评估新辅助治疗期间肿瘤体积和肿瘤负荷的纵向变化。对胰腺的纵向配准误差进行了表征，并将基于配准的治疗反应测量与5年随访期间的总生存期（OS）和无复发生存期（RFS）结果相关联。通过手动肿瘤分割、实体瘤标准化反应评估标准（RECIST）以及切除后组织样本的病理检查进行的相应生物标志物评估作为临床对照进行分析。
生物力学图像配准算法的平均目标配准误差为 ，基于微分同胚强度算法的平均目标配准误差为 ，对应于1 - 2倍体素分辨率。Cox比例风险分析表明，配准得出的肿瘤负荷变化是OS和RFS的显著预测因子，而包括手动肿瘤分割、RECIST或病理变量在内的其他对照均与相应的风险比无关。在1年、2年、3年和5年随访时进行的额外ROC分析显示，治疗前和治疗后成像之间配准得出的肿瘤负荷变化比临床对照更能作为OS和RFS的长期预测因子。
通过纵向可变形图像配准测量的体积变化可能产生成像生物标志物，以区分PDAC特征性边界不清肿瘤的新辅助治疗反应。基于配准的生物标志物可能有助于克服放射学评估的视觉限制，以改善临床结果预测并为治疗选择提供依据。
