The aim of this work was to develop models for tumor control probability (TCP) in radioembolization with 90Y PET/CT-derived radiobiologic dose metrics. Methods: Patients with primary liver cancer or liver metastases who underwent radioembolization with glass microspheres were imaged with 90Y PET/CT for voxel-level dosimetry to determine lesion absorbed dose (AD) metrics, biological effective dose (BED) metrics, equivalent uniform dose, and equivalent uniform BED for 28 treatments (89 lesions). The lesion dose-shrinkage correlation was assessed on the basis of RECIST and, when available, modified RECIST (mRECIST) at first follow-up. For a subset with mRECIST, logit regression TCP models were fit via maximum likelihood to relate lesion-level binary response to the dose metrics. As an exploratory analysis, the nontumoral liver dose-toxicity relationship was also evaluated. Results: Lesion dose-shrinkage analysis showed that there were no significant differences between model parameters for primary and metastatic subgroups and that correlation coefficients were superior with mRECIST. Therefore, subsequent TCP analysis was performed for the combined group using mRECIST only. The overall lesion-level mRECIST response rate was 57%. The AD and BED metrics yielding 50% TCP were 292 and 441 Gy, respectively. All dose metrics considered for TCP modeling, including mean AD, were significantly associated with the probability of response, with high areas under the curve (0.87-0.90, P < 0.0001) and high sensitivity (>0.75) and specificity (>0.83) calculated using a threshold corresponding to 50% TCP. Because nonuniform AD deposition by microspheres cannot be determined by PET at a microscopic scale, radiosensitivity values extracted here by fitting models to clinical response data were substantially lower than reported for in vitro cell cultures or for external-beam radiotherapy clinical studies. There was no correlation between nontumoral liver AD and toxicity measures. Conclusion: Despite the heterogeneous patient cohort, logistic regression TCP models showed a strong association between various dose metrics and the probability of response. The performance of mean AD was comparable to that of radiobiologic dose metrics that involve more complex calculations. These results demonstrate the importance of considering TCP in treatment planning for radioembolization.

中文翻译：

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通过基于PET / CT的剂量指标的Logit模型预测90Y放射栓塞中的肿瘤控制。

这项工作的目的是使用90Y PET / CT衍生的放射生物学剂量指标开发放射栓塞中的肿瘤控制概率（TCP）模型。方法：对接受原位肝癌或肝转移的玻璃微球放射性栓塞患者进行90Y PET / CT体素水平剂量成像，以确定病变吸收剂量（AD）指标，生物学有效剂量（BED）指标，等效均等剂量，和等效的统一BED进行28次治疗（89个病灶）。在RECIST的基础上评估病变的剂量-收缩相关性，并在可能的情况下在首次随访时评估改良的RECIST（mRECIST）。对于具有mRECIST的子集，通过最大可能性拟合logit回归TCP模型，以将病灶级别的二进制响应与剂量指标相关联。作为探索性分析，还评估了非肿瘤肝的剂量-毒性关系。结果：病变剂量收缩分析显示，主要和转移亚组的模型参数之间无显着差异，并且mRECIST的相关系数更高。因此，仅使用mRECIST对合并的组执行后续的TCP分析。总体病灶水平的mRECIST缓解率为57％。产生50％TCP的AD和BED度量分别为292 Gy和441 Gy。TCP建模考虑的所有剂量指标（包括平均AD）均与应答概率显着相关，曲线下面积高（0.87-0.90，P <0.0001），并具有高灵敏度（> 0.75）和特异性（> 0.83）使用对应于50％TCP的阈值。由于PET无法在微观规模上确定微球体AD沉积的不均匀性，因此此处通过对临床反应数据进行拟合模型提取的放射敏感性值大大低于体外细胞培养或体外放射治疗临床研究的报道。非肿瘤肝AD与毒性指标之间无相关性。结论：尽管患者队列异质，但逻辑回归TCP模型显示了各种剂量指标与反应可能性之间的强相关性。平均AD的表现可与涉及更复杂计算的放射生物学剂量指标相媲美。这些结果表明在放射栓塞治疗计划中考虑TCP的重要性。通过对临床反应数据进行拟合模型在此处提取的放射敏感性值大大低于体外细胞培养或体外放射疗法临床研究的报道。非肿瘤肝AD与毒性指标之间无相关性。结论：尽管患者队列异质，但逻辑回归TCP模型显示了各种剂量指标与反应可能性之间的强相关性。平均AD的表现可与涉及更复杂计算的放射生物学剂量指标相媲美。这些结果表明在放射栓塞治疗计划中考虑TCP的重要性。通过对临床反应数据进行拟合模型在此处提取的放射敏感性值大大低于体外细胞培养或体外放射疗法临床研究的报道。非肿瘤肝AD与毒性指标之间无相关性。结论：尽管患者队列异质，但逻辑回归TCP模型显示了各种剂量指标与反应可能性之间的强相关性。平均AD的表现可与涉及更复杂计算的放射生物学剂量指标相媲美。这些结果表明在放射栓塞治疗计划中考虑TCP的重要性。非肿瘤肝AD与毒性指标之间无相关性。结论：尽管患者队列异质，但逻辑回归TCP模型显示了各种剂量指标与反应可能性之间的强相关性。平均AD的表现可与涉及更复杂计算的放射生物学剂量指标相媲美。这些结果表明在放射栓塞治疗计划中考虑TCP的重要性。非肿瘤肝AD与毒性指标之间无相关性。结论：尽管患者队列异质，但逻辑回归TCP模型显示了各种剂量指标与反应可能性之间的强相关性。平均AD的表现可与涉及更复杂计算的放射生物学剂量指标相媲美。这些结果表明在放射栓塞治疗计划中考虑TCP的重要性。