Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, California.
Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
Int J Radiat Oncol Biol Phys. 2022 Sep 1;114(1):163-172. doi: 10.1016/j.ijrobp.2022.04.044. Epub 2022 May 26.
The benefit of radiation therapy for pancreatic ductal adenocarcinoma (PDAC) remains unclear. We hypothesized that a new mechanistic mathematical model of chemotherapy and radiation response could predict clinical outcomes a priori, using a previously described baseline measurement of perfusion from computed tomography scans, normalized area under the enhancement curve (nAUC).
We simplified an existing mass transport model that predicted cancer cell death by replacing previously unknown variables with averaged direct measurements from randomly selected pathologic sections of untreated PDAC. This allowed using nAUC as the sole model input to approximate tumor perfusion. We then compared the predicted cancer cell death to the actual cell death measured from corresponding resected tumors treated with neoadjuvant chemoradiation in a calibration cohort (n = 80) and prospective cohort (n = 25). After calibration, we applied the model to 2 separate cohorts for pathologic and clinical associations: targeted therapy cohort (n = 101), cetuximab/bevacizumab + radiosensitizing chemotherapy, and standard chemoradiation cohort (n = 81), radiosensitizing chemotherapy to 50.4 Gy in 28 fractions.
We established the relationship between pretreatment computed v nAUC to pathologically verified blood volume fraction of the tumor (r = 0.65; P = .009) and fractional tumor cell death (r = 0.97-0.99; P < .0001) in the calibration and prospective cohorts. On multivariate analyses, accounting for traditional covariates, nAUC independently associated with overall survival in all cohorts (mean hazard ratios, 0.14-0.31). Receiver operator characteristic analyses revealed discrimination of good and bad prognostic groups in the cohorts with area under the curve values of 0.64 to 0.71.
This work presents a new mathematical modeling approach to predict clinical response from chemotherapy and radiation for PDAC. Our findings indicate that oxygen/drug diffusion strongly influences clinical responses and that nAUC is a potential tool to select patients with PDAC for radiation therapy.
放射治疗对胰腺导管腺癌(PDAC)的益处仍不清楚。我们假设,一种新的化疗和放射反应的机制数学模型可以使用之前描述的来自 CT 扫描的灌注基线测量值(归一化增强曲线下面积,nAUC),预先预测临床结果。
我们简化了一个现有的质量传输模型,该模型通过用未经处理的 PDAC 的随机选择的病理切片的平均直接测量值替换之前未知的变量,来预测癌细胞死亡。这允许使用 nAUC 作为唯一的模型输入来近似肿瘤灌注。然后,我们将预测的癌细胞死亡与接受新辅助放化疗的相应切除肿瘤中实际测量的细胞死亡进行比较,该模型在校准队列(n=80)和前瞻性队列(n=25)中进行了验证。校准后,我们将该模型应用于 2 个独立的队列,用于病理和临床关联:靶向治疗队列(n=101),西妥昔单抗/贝伐单抗+放射增敏化疗;标准放化疗队列(n=81),50.4 Gy 28 分次放射增敏化疗。
我们建立了预处理计算机 v nAUC 与肿瘤病理验证的血容量分数(r=0.65;P=0.009)和肿瘤细胞死亡分数(r=0.97-0.99;P<0.0001)之间的关系,在校准和前瞻性队列中得到验证。在多变量分析中,考虑到传统的协变量,nAUC 与所有队列的总生存独立相关(平均危险比,0.14-0.31)。受试者工作特征分析显示,在曲线下面积值为 0.64 至 0.71 的队列中,区分了预后良好和预后不良的组。
本研究提出了一种新的数学建模方法,用于预测 PDAC 的化疗和放疗的临床反应。我们的研究结果表明,氧气/药物扩散强烈影响临床反应,nAUC 是选择 PDAC 患者进行放疗的潜在工具。