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首页> 外文期刊>International Journal of Radiation Oncology, Biology, Physics >Locoregional control of non-small cell lung cancer in relation to automated early assessment of tumor regression on cone beam computed tomography
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Locoregional control of non-small cell lung cancer in relation to automated early assessment of tumor regression on cone beam computed tomography

机译:非小细胞肺癌的局部控制与锥体束计算机断层扫描自动早期评估肿瘤消退相关

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Purpose Large interindividual variations in volume regression of non-small cell lung cancer (NSCLC) are observable on standard cone beam computed tomography (CBCT) during fractionated radiation therapy. Here, a method for automated assessment of tumor volume regression is presented and its potential use in response adapted personalized radiation therapy is evaluated empirically. Methods and Materials Automated deformable registration with calculation of the Jacobian determinant was applied to serial CBCT scans in a series of 99 patients with NSCLC. Tumor volume at the end of treatment was estimated on the basis of the first one third and two thirds of the scans. The concordance between estimated and actual relative volume at the end of radiation therapy was quantified by Pearson's correlation coefficient. On the basis of the estimated relative volume, the patients were stratified into 2 groups having volume regressions below or above the population median value. Kaplan-Meier plots of locoregional disease-free rate and overall survival in the 2 groups were used to evaluate the predictive value of tumor regression during treatment. Cox proportional hazards model was used to adjust for other clinical characteristics. Results Automatic measurement of the tumor regression from standard CBCT images was feasible. Pearson's correlation coefficient between manual and automatic measurement was 0.86 in a sample of 9 patients. Most patients experienced tumor volume regression, and this could be quantified early into the treatment course. Interestingly, patients with pronounced volume regression had worse locoregional tumor control and overall survival. This was significant on patient with non-adenocarcinoma histology. Conclusions Evaluation of routinely acquired CBCT images during radiation therapy provides biological information on the specific tumor. This could potentially form the basis for personalized response adaptive therapy.
机译:目的在分级放射治疗期间,在标准锥束计算机断层扫描(CBCT)上可以观察到非小细胞肺癌(NSCLC)体积消退的个体差异较大。在这里,提出了一种自动评估肿瘤体积消退的方法,并根据经验评估了其在适应性适应性放射治疗中的潜在用途。方法和材料在99例非小细胞肺癌患者中,采用可雅可比行列式计算的自动可变形配准用于系列CBCT扫描。根据扫描的前三分之一和三分之二来估计治疗结束时的肿瘤体积。放射治疗结束时的估计相对体积与实际相对体积之间的一致性通过皮尔森相关系数进行量化。根据估计的相对体积,将患者分为两组,两组之间的体积回归低于或高于人群中位数。两组的局部无疾病发生率和总生存率的Kaplan-Meier图用于评估治疗期间肿瘤消退的预测价值。使用Cox比例风险模型调整其他临床特征。结果从标准CBCT图像自动测量肿瘤消退是可行的。在9位患者的样本中,手动和自动测量之间的Pearson相关系数为0.86。大多数患者经历了肿瘤体积消退,这可以在治疗过程的早期量化。有趣的是,明显消退的患者局部肿瘤控制和总体生存率较差。这对非腺癌组织学患者意义重大。结论评估放射治疗期间常规采集的CBCT图像可提供有关特定肿瘤的生物学信息。这可能会形成个性化反应适应性治疗的基础。

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