SBIR-STTR Award

The clinical outcome of radiation therapy depends on delivering the highest possible absorbed dose to the tumor(s) while limiting the dose to normal tissues. Unfortunately, unlike external beam radiotherapy (EBRT), current RT prescription methods do not consider absorbed dose to individual patients but instead use empirically derived or standard methods. Thus, up to 50% of these patients receive sub-optimal prescriptions leading to sub-optimal clinical outcomes including under-dosing of the tumor or severe toxicity in healthy tissues. Clearly this violates the basic tenants of radiation oncology because the radiation doses received by these patients are neither justified nor optimized. Our solution, RAPID (Radionuclide Assessment Platform for Internal Dosimetry), will be the first commercialized desktop Monte Carlo radionuclide dosimetry system. It will utilize a heterogeneous CPU/GPU (Graphical Processing Units) architecture that will minimize the computational complexity stemming from problems encountered in RT dosimetry. RAPID will provide accurate radiation dosimetry results within a clinically acceptable timeframe of less than 5 minutes. The long-term objective of this project is to develop the first FDA approved patient-specific treatment planning software for RT that is completely accessible. Health care systems, drug companies, and clinical researchers are expected to access this technology to provide the best possible care for cancer patients.

Public Health Relevance Statement:
PROJECT NARRATIVE Millions of patients are treated with radionuclide therapy each year. Unfortunately, current radionuclide prescription methods do not consider absorbed dose to individual patients but instead use empirically derived or standard methods leading to suboptimal treatment outcomes in some patients. Our solution, RAPID (Radionuclide Assessment Platform for Internal Dosimetry), will be the first commercialized Monte Carlo radionuclide dosimetry software that will permit patient-specific treatment planning.

Project Terms:
Accounting; Address; Architecture; base; cancer care; Cancer Patient; Clinical; Clinical Trials; cluster computing; Computer software; cost; Data; Data Set; design; Discipline of Nuclear Medicine; Dose; Dose-Limiting; dosimetry; Economics; FDA approved; Feedback; flexibility; graphical user interface; Healthcare Systems; High Performance Computing; image processing; improved; individual patient; Legal patent; Maintenance; Medical; Methods; Monte Carlo Method; Normal tissue morphology; Outcome; Patient-Focused Outcomes; Patients; Performance; PET/CT scan; Pharmaceutical Preparations; Phase; Physicians; Physics; Positioning Attribute; Procedures; prospective; prototype; Radiation; Radiation Oncology; Radiation therapy; Radioactive; Radioisotopes; Radiometry; Radionuclide therapy; Research; Research Activity; Research Personnel; simulation; software development; software systems; Source; stem; Stream; System; Technical Expertise; Technology; Testing; Therapeutic; Tissues; tool; Toxic effect; Translating; Treatment outcome; treatment planning; tumor; United States National Institutes of Health

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.

Public Health Relevance Statement:
PROJECT NARRATIVE Millions of patients are treated with radiopharmaceutical therapy each year. Unfortunately, current prescription methods do not consider absorbed dose to individual patients but instead use empirically derived or standard methods leading to suboptimal treatment outcomes in some patients. Our solution, Torch, will be the first commercialized Monte Carlo radionuclide dosimetry software that will permit patient-specific treatment planning.

Project Terms:
3-Dimensional; Academic Medical Centers; Affect; Agreement; Algorithms; Automation; Award; base; Benchmarking; Biodistribution; Cancer Patient; cancer therapy; Capital Expenditures; chemotherapy; Clinical; Clinical Trials; commercialization; Computer software; cost; cost effective; Data; Databases; Deposition; Discipline of Nuclear Medicine; Disseminated Malignant Neoplasm; Dose; dosimetry; Economic Development; Ecosystem; experience; External Beam Radiation Therapy; FOLH1 gene; Funding; Grant; Healthcare; Healthcare Systems; Hour; Image; image registration; individual patient; individualized medicine; Intellectual Property; Interview; Investments; Lead; Letters; Licensing; Lymphoma; Medical; Metastatic Prostate Cancer; Metastatic to; Methods; Modeling; Neoplasm Metastasis; neoplastic cell; Neuroendocrine Tumors; Normal tissue morphology; Overdose; Patient-Focused Outcomes; Patients; personalized medicine; pharmacokinetic model; Phase; Physicians; Physiology; Radiation; Radioactivity; Radioisotopes; Radiopharmaceuticals; Resources; Secure; side effect; simulation; single photon emission computed tomography; Small Business Innovation Research Grant; Testing; Time; tool; Treatment outcome; treatment planning; tumor; Tumor Tissue; Universities; Wisconsin; Work; X-Ray Computed Tomography