Dose-Response in Radionuclide Therapy

靶向放射性核素治疗作为一种潜在的癌症治疗方式正在被积极研究。这个 吸收剂量与肿瘤反应或正常器官毒性的关系在优化中很重要 放射性核素疗法。目前对这种关系的理解几乎完全源于外部 而不是放射性核素治疗的经验。使用来自临床放射性核素治疗的数据 我们建议评估放射性核素剂量学在试验设计和肿瘤中的潜在作用。 反应或毒性预测。这项建议将解决以下问题：1.什么是 估计吸收剂量与肿瘤和正常器官反应的关系？2.患者 特定的、基于3-D成像的剂量学比基于更简单的标准体模的剂量学更具优势 方法？3.解释吸收剂量率和辐射剂量率差异的放射生物学模型 一致性改善应答预测？4.既往治疗如何影响血液毒性和 剂量-反应关系？使用3D-ID，由PI开发的针对患者的3D剂量测量程序包 在NIH之前的支持下，提出了以下目标来解决这些问题：1.在公司内部 在3D-ID中利用和解释剂量率和空间均匀性信息的放射生物学建模 评估响应概率。2.1甲状腺疾病患者接受治疗后的剂量-反应关系 1比131。2.2.获得非霍奇金淋巴瘤患者接受非霍奇金淋巴瘤治疗的剂量-反应关系 清髓性Tositumomab(Bexxar；131L-抗CD20)和Ibritumomab Tiuxetan(Zvalin；90Y-抗CD20)。 3.比较通过考虑剂量率、不均匀性和患者- 具体解剖(即，使用3D-ID)与使用更简单的标准体模获得的解剖 方法学(Olinda)；在非霍奇金淋巴瘤研究中，评估FL.T3配体在改善剂量反应中的作用 与血液毒性的关系。剂量学被认为是反应的最佳预测因子。 在放射性核素治疗之后。放射性核素治疗数据的标准化、严格剂量分析 来评估这一假设，确定所需的复杂程度，并了解 其他因素也会影响吸收剂量与反应的关系。

Targeted radionuclide therapy is being actively investigated as a potential cancer therapy modality. The relationship between absorbed dose and tumor response or normal organ toxicity is important in optimizing radionuclide therapy. Current understanding of this relationship is almost completely derived from external beam rather than radionuclide therapy experience. Using data derived from clinical radionuclide therapy studies we propose to evaluate the potential role of radionuclide dosimetry in trial design and tumor response or toxicity prediction. The following questions will be addressed by this proposal: 1. What is the relationship between estimated absorbed dose and tumor and normal organ response? 2. Does patient specific, 3-D imaging-based dosimetry provide an advantage over a simpler, standard phantom-based approach? 3. Does radiobiologic modeling that accounts for differences in absorbed dose rate and uniformity improve response prediction? 4. How does prior therapy influence hematologic toxicity and the dose-response relationship? Using 3D-ID, a patient-specific 3-D dosimetry package developed by the PI with previous NIH support, the following aims are proposed to address these questions 1.Incorporate radiobiologic modeling in 3D-ID to utilize and interpret dose-rate and spatial uniformity information in evaluating response probability. 2.1.Obtain dose-response relationships in thyroid disease patients treated with 1-131. 2.2. Obtain dose-response relationships for non-hodgkins lymphoma patients treated with non- myeloablative Tositumomab (Bexxar; 131l-anti-CD20) and Ibritumomab Tiuxetan (Zevalin; 90Y-anti-CD20). 3. Compare dose-responserelationships obtained by accounting for dose-rate, non-uniformity and patient- specific anatomy (i.e., using 3D-ID) with those obtained using a simpler, standard-phantom based methodology (OLINDA); in the NHL studies, evaluate the role of FL.T3 ligand in improving thedose-response relationship for hematologic toxicity. Dosimetry has been assumed to be the best predictor of response following radionuclide treatment. Standardized, rigorous dosimetric analyses of radionuclide therapy data are needed to evaluate this assumption, identify the level of complexity required and to understand how other factors can impact the absorbed dose vs response relationship.