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.

项目摘要/摘要 放射药物治疗（RPT）是化学疗法的一种替代方法，在患者中效果很好 淋巴瘤，晚期，前列腺癌和神经内分泌肿瘤。它有效地交付 精确指向分布在整个体内的转移性肿瘤细胞。患者 即使独特的生理 每个患者的影响会随着时间的推移影响放射性药物的生物分布，并可能影响治疗结果。 另外，通过对体内RPT发射的辐射进行成像，可以计算如何计算 许多辐射能沉积在单个患者的肿瘤和正常组织中（“剂量法”）。这 信息提供个性化药物，因为可以调整放射性的量以避免 服药不足（肿瘤辐射不足以杀死肿瘤）或过量剂量（对正常组织的辐射过多 导致副作用）患者。从外部梁辐射疗法（EBRT）的经验，我们知道 基于吸收剂量（“治疗计划”）的患者特定处方会导致更好的患者 结果。像EBRT一样，针对RPT的患者特定治疗计划需要复杂的剂量计工具 Voximetry Inc（“ Vox”）已开发。作为上一阶段I SBIR赠款的一部分，Vox开发了蒙特 卡洛剂量学算法利用图形处理单元的巨大计算能力 （GPU）执行基于体素的剂量法。我们的方法将使治疗计划更快，更多 准确，因此可以在临床上使用它来计算患者特定的剂量测定法，而不是 中央处理单元（CPU）需要数十小时。 Vox最终将通过使癌症患者受益 可用于针对转移性癌症的个性化治疗方法，在许多情况下， 副作用比化学疗法少。在此提案中，我们旨在整合我们的完全基准和IP- 通过保护剂量算法的剂量算法将其纳入自动化的，具有成本效益的RPT治疗计划解决方案，TORCH，由 添加其他功能，例如图像注册，轮廓传播和基于体素的药代动力学 （PK）建模。火炬不仅将是市场上最准确的产品，还将是成本的1/3 竞争对手的产品。提案中将实现的具体目的是（1）发展GPU- 在火炬工作流程中加速可变形的图像注册和轮廓传播，（2）发展 用于体素级时活动曲线的GPU加速药代动力学建模，（3）验证 使用计算幻象和患者数据进行beta测试通过TORCH。成功完成 这些目标将支持准备临床使用的商业可行产品。该产品将被证明 在回顾性临床试验中安全有效，随后将向FDA申请510（k）。