权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Bringing Capacity for Theranostic Dosimetry Planning to the Nuclear Medicine Clinic

为核医学诊所带来治疗诊断剂量测定规划的能力

基本信息

批准号：
10620806
负责人：
YUNI K DEWARAJA
金额：
$ 59.43万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10620806
关键词：
Clinic Clinical Clinical Protocols Code Collaborations Computer software Development Discipline of Nuclear Medicine Dose Ensure Environment FOLH1 gene Foundations Future Image Image Analysis Imaging Device Kidney Label Learning Lesion Malignant Neoplasms Malignant neoplasm of prostate Medical Imaging Methods Modeling Neuroendocrine Tumors Organ Outcome Patient-Focused Outcomes Patients Peptide Receptor Procedures Protocols documentation Public Health Radiation therapy Radioisotopes Radiolabeled Radionuclide therapy Recording of previous events Reproducibility Risk Software Validation Standardization Survival Rate System Test Result Testing Therapeutic Effect Therapy Clinical Trials Time Toxic effect Translating Weight X-Ray Computed Tomography absorption clinical practice clinical translation cytotoxic radiation data handling design dosimetry experience imaging Segmentation imaging biomarker improved individualized medicine industry partner innovation novel personalized approach predictive modeling prospective radioligand radiomics reconstruction response single photon emission computed tomography standard of care targeted agent theranostics tool treatment planning tumor

项目摘要

Abstract Internally administered targeted radionuclide therapy (TRT) with radio-labeled molecules that deliver cytotoxic radiation to tumor has been successfully used to treat multiple cancers. Despite promising results, there is much room to improve the durable response and survival rates achieved with TRT. TRT is ideally suited for the theranostic approach to treatment because emission imaging performed before initiating a treatment cycle can be used to predict the absorbed doses (ADs) that will be delivered. Thus, the activity needed for a therapeutic effect on tumor while keeping critical organ toxicities at an acceptable level can be planned on an individualized basis. While precise treatment planning is routinely used in external beam radiotherapy, in TRT however, treatment with fixed or weight-based activities without consideration of delivered ADs continues to be the standard of care. The main barrier to dosimetry guided personalization of TRT is the lack of dosimetry tools that are valid yet practical for the clinic environment. To improve this situation the objective is to develop, validate and bring to the clinic a platform for patient-specific dosimetry-driven treatment planning that is practical for clinical use and adaptable to various TRTs. The proposed system will integrate a toolbox for SPECT/CT imaging based voxel-level dosimetry with end-to-end testing (Aim 1), validated protocols for reducing the imaging burden associated with patient specific dosimetry (Aim 2), robust dose – outcome models that include clinical factors and imaging biomarkers as covariates (Aim 2), and an interactive user interface that the clinician can use to plan the therapy considering dosimetric and clinical factors and the resulting efficacy/toxicity trade-off (Aim 3). The system integrates new components that will be developed exploiting recent advances such as learning-based methods for low-count SPECT reconstruction and efficient image segmentation atop our existing foundation that includes a previously developed fast Monte Carlo dosimetry code. The collaboration with an industry partner with a track record in translating innovative tools for medical image analysis will help ensure clinical translation of the system. To demonstrate the capacity of the tools developed, patient studies will focus on 177Lu DOTATATE treatment of neuroendocrine tumors. This recently approved therapy is administered in four cycles with fixed activity although there is a unique opportunity to perform SPECT imaging-based lesion/organ dosimetry after each cycle to plan the next cycle. The system can be adapted to therapies with other radionuclides and targeting agents that can benefit from SPECT/CT imaging based planning such as radioligand therapy with 177Lu PSMA for prostate cancer and emerging therapies with alpha emitters. The proposed system integrates adaptations of tools developed in the past by both teams and new tools to bring a new capacity to the end user to effectively plan TRT with all data handling conveniently performed within one platform. This will have a significant positive impact because a personalized dosimetry guided approach to TRT is likely to substantially improve efficacy while maintaining low toxicity, compared with the current arbitrary ‘one dose fits all’ approach.

摘要体内给药靶向放射性核素治疗(TRT)，使用放射性标记分子传递细胞毒肿瘤放射治疗已成功应用于多种癌症的治疗。尽管结果很有希望，但仍有很多改善TRT的持久反应和存活率的空间。TRT非常适合于治疗的无声学方法，因为在开始治疗周期之前进行发射成像可以用于预测将被释放的吸收剂量(ADS)。因此，治疗所需的活动在将关键器官毒性保持在可接受的水平的同时对肿瘤的影响可以个性化地计划基础。虽然精确的治疗计划通常用于外照射，但在TRT中，在不考虑投放广告的情况下，采用固定或基于体重的活动来处理仍然是护理的标准。剂量学引导TRT个人化的主要障碍是缺乏剂量学工具对于临床环境来说是有效的，但也是实用的。为了改善这种情况，目标是开发、验证并为临床提供了一个平台，用于患者特定剂量学驱动的治疗计划，适用于临床应用，可适应各种TRT。拟议的系统将集成SPECT/CT成像工具箱基于端到端测试的体素级别剂量测量(目标1)，用于减少成像负担的有效协议与患者特定剂量学(AIM 2)相关，包含临床因素的稳健剂量-结果模型和作为协变量的成像生物标记物(目标2)，以及临床医生可以用来计划的交互式用户界面该疗法考虑了剂量学和临床因素以及由此产生的疗效/毒性权衡(目标3)。这个系统集成了将利用最新进展(如基于学习的技术)开发的新组件用于低计数SPECT重建和高效图像分割的方法建立在我们现有的基础上包括先前开发的快速蒙特卡罗剂量学代码。与行业合作伙伴的合作在翻译创新的医学图像分析工具方面的记录将有助于确保临床翻译系统。为了证明开发的工具的能力，患者研究将集中在177Lu DOTATE 神经内分泌肿瘤的治疗。这种最近批准的治疗方法分四个周期进行，固定的活动，尽管有一个独特的机会来进行基于SPECT成像的病变/器官剂量测量每个周期都要计划下一个周期。该系统可用于其他放射性核素和靶向治疗。可以从基于SPECT/CT成像的计划中受益的代理，例如使用177Lu PSMA进行放射配基治疗用于前列腺癌和阿尔法排放物的新兴疗法。拟议的系统集成了以下方面的改编过去由两个团队开发的工具和新工具为最终用户带来了有效的新能力计划TRT，在一个平台内方便地执行所有数据处理。这将产生重大的积极影响影响，因为个性化剂量学指导的TRT方法可能会显著提高疗效，同时保持低毒性，与目前任意的“一刀切”的方法相比。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Differences in tumor-to-normal organ SUV ratios measured with 68 Ga-DOTATATE PET compared with 177 Lu-DOTATATE SPECT in patients with neuroendocrine tumors.

DOI：
10.1097/mnm.0000000000001592
发表时间：
2022-08-01
期刊：
NUCLEAR MEDICINE COMMUNICATIONS
影响因子：
1.5
作者：
Wong, Ka Kit;Frey, Kirk A.;Niedbala, Jeremy;Kaza, Ravi K.;Worden, Francis P.;Fitzpatrick, Kellen J.;Dewaraja, Yuni K.
通讯作者：
Dewaraja, Yuni K.

Experimental validation of Monte Carlo dosimetry for therapeutic beta emitters with radiochromic film in a 3D-printed phantom.

DOI：
10.1002/mp.15926
发表时间：
2023-01
期刊：
MEDICAL PHYSICS
影响因子：
3.8
作者：
Van, Benjamin;Dewaraja, Yuni K.;Niedbala, Jeremy T.;Rosebush, Gerrid;Kazmierski, Matthew;Hubers, David;Mikell, Justin K.;Wilderman, Scott J.
通讯作者：
Wilderman, Scott J.

Technical note: Impact of dose voxel kernel (DVK) values on dosimetry estimates in 177 Lu and 90 Y radiopharmaceutical therapy (RPT) applications.

技术说明：剂量体素核 (DVK) 值对 177 Lu 和 90 Y 放射性药物治疗 (RPT) 应用中剂量测定估计的影响。

DOI：
10.1002/mp.16729
发表时间：
2024
期刊：
Medical physics
影响因子：
3.8
作者：
Danieli,Rachele;Pistone,Daniele;Tranel,Jonathan;Botta,Francesca;Uribe-Munoz,Carlos;Raspanti,Davide;Salvat,Francesc;Wilderman,ScottJ;Bardiès,Manuel;Amato,Ernesto;Dewaraja,YuniK;Cremonesi,Marta
通讯作者：
Cremonesi,Marta

Advanced imaging and theranostics in thyroid cancer.

甲状腺癌的先进成像和治疗诊断学。