One-click Automated 3D Treatment Planning for Radiopharmaceutical Therapy

用于放射性药物治疗的一键式自动化 3D 治疗计划

• 批准号: 10081884
• 负责人: Joseph Grudzinski
• 金额: $ 88.4万
• 依托单位: VOXIMETRY, INC.
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10081884
• 关键词: 3-Dimensional; Academic Medical Centers; Affect; Agreement; Algorithms; Automation; Award; Benchmarking; Biodistribution; Cancer Patient; Capital Expenditures; Clinical; Clinical Trials; Computer software; Data; Databases; Deposition; Discipline of Nuclear Medicine; Disseminated Malignant Neoplasm; Dose; Economic Development; Ecosystem; External Beam Radiation Therapy; FOLH1 gene; Funding; Grant; Healthcare; Healthcare Systems; Hour; Image; Intellectual Property; Interview; Investments; Lead; Letters; Licensing; Lymphoma; Medical; Metastatic Prostate Cancer; Metastatic to; Methods; Modeling; Neoplasm Metastasis; Neuroendocrine Tumors; Normal tissue morphology; Overdose; Patient-Focused Outcomes; Patients; Phase; Physicians; Physiology; Radiation; Radioactivity; Radioisotopes; Radiopharmaceuticals; Resources; Secure; Small Business Innovation Research Grant; Testing; Time; Treatment outcome; Tumor Tissue; Universities; Wisconsin; Work; X-Ray Computed Tomography; base; cancer therapy; chemotherapy; commercialization; cost; cost effective; dosimetry; experience; image registration; individual patient; individualized medicine; neoplastic cell; personalized medicine; pharmacokinetic model; side effect; simulation; single photon emission computed tomography; tool; treatment planning; tumor

PROJECT SUMMARY/ABSTRACT Radiopharmaceutical therapy (RPT), an alternative to chemotherapy, has worked well in patients with lymphoma, late-stage, metastatic prostate cancer, and neuroendocrine tumors. It is effective at delivering pinpoint radioactivity specifically to metastatic tumor cells distributed throughout the body. Patients who are treated with RPT agents typically receive the same amount of radioactivity even though the unique physiology of each patient impacts biodistribution of the radioactive drug over time and can affect treatment outcome. Alternatively, by imaging the radiation emitted by the RPT agent within the body, it is possible to calculate how much radiation energy is deposited in tumors and normal tissues within an individual patient (“dosimetry”). This information affords personalized medicine because the amount of radioactivity can be adjusted to avoid underdosing (not enough tumor radiation to kill the tumor) or overdosing (too much radiation to normal tissue that leads to side effects) the patient. From experience with external beam radiation therapy (EBRT), we know that patient-specific prescriptions based on absorbed dose ("treatment planning") lead to better patient outcomes. Like EBRT, patient-specific treatment planning for RPT requires sophisticated dosimetry tools that Voximetry Inc (“Vox”) has developed. As part of a previous Phase I SBIR grant, Vox has developed a Monte Carlo dosimetry algorithm which leverages the enormous computing power of graphics processing units (GPUs) to perform voxel-based dosimetry. Our approach will make treatment planning faster and more accurate, so that it can be used clinically to compute patient-specific dosimetry within minutes as opposed to tens of hours required on central processing units (CPUs). Vox will ultimately benefit cancer patients by making available a personalized treatment that targets metastatic cancer that in many cases is more efficacious and has fewer side effects than chemotherapy. In this proposal, we aim to integrate our fully benchmarked and IP- protected dosimetry algorithm into an automated, cost-effective RPT treatment planning solution, Torch, by adding additional features such as image registration, contour propagation, and voxel-based pharmacokinetic (PK) modeling. Torch will not only be the most accurate product on the market, it will be 1/3 of the cost of competitors’ offerings. The specific aims that will be accomplished in the proposal are to (1) develop GPU- accelerated deformable image registration and contour propagation within the Torch workflow, (2) develop GPU-accelerated pharmacokinetic modeling for voxel-level time activity curve integration, and (3) validate Torch through beta testing using computational phantoms and patient data. The successful completion of these aims will support a commercially viable product that is ready for clinical use. This product will be proven safe and effective in a retrospective clinical trial which will be followed by a 510(k) application to the FDA.

项目概要/摘要 放射药物治疗（RPT）是化疗的替代方案，对患有以下疾病的患者效果良好 它对淋巴瘤、晚期、转移性前列腺癌和神经内分泌肿瘤有效。 精确定位分布在全身的转移性肿瘤细胞的放射性。 尽管独特的生理学原理，用 RPT 剂治疗的患者通常会受到相同量的放射性 随着时间的推移，每位患者的身体状况都会影响放射性药物的生物分布，并可能影响治疗结果。 或者，通过对 RPT 剂在体内发出的辐射进行成像，可以计算出如何 许多辐射能量沉积在个体患者体内的肿瘤和正常组织中（“剂量测定”）。 信息提供了个性化医疗，因为可以调整放射性量以避免 剂量不足（肿瘤辐射不足以杀死肿瘤）或剂量过量（对正常组织的辐射过多 根据外照射放射治疗 (EBRT) 的经验，我们知道。 基于吸收剂量的针对特定患者的处方（“治疗计划”）可以为患者带来更好的效果 与 EBRT 一样，针对 RPT 的患者特定治疗计划需要复杂的剂量测定工具。 作为先前第一阶段 SBIR 资助的一部分，Vox 开发了 Monte。 卡洛剂量测定算法利用图形处理单元的强大计算能力 （GPU）执行基于体素的剂量测定我们的方法将使治疗计划更快、更准确。 准确，因此可以在临床上使用它在几分钟内计算出患者特定的剂量测定，而不是 Vox 需要中央处理器 (CPU) 花费数十个小时，最终将使癌症患者受益。 提供针对转移性癌症的个性化治疗，在许多情况下更有效且更有效 与化疗相比，副作用更少。在这项提案中，我们的目标是整合我们的完全基准测试和 IP- 将受保护的剂量测定算法集成到自动化、经济高效的 RPT 治疗计划解决方案 Torch 中 添加附加功能，例如图像配准、轮廓传播和基于体素的药代动力学 (PK) 建模，Torch 不仅是市场上最精确的产品，而且成本将是市场上的 1/3。 该提案将实现的具体目标是 (1) 开发 GPU- 在 Torch 工作流程中加速可变形图像配准和轮廓传播，(2) 开发 用于体素级时间活性曲线积分的 GPU 加速药代动力学建模，以及 (3) 验证 Torch 通过使用计算模型和患者数据的 beta 测试成功完成。 这些目标将支持商业上可行的产品，该产品将被证明可以用于临床。 在一项回顾性临床试验中安全有效，随后将向 FDA 提交 510(k) 申请。