Assessment of a Radiomics-Based Computer-Aided Diagnosis Tool for Cancer Risk Stratification of Pulmonary Nodules

基于放射组学的计算机辅助诊断工具对肺结节癌症风险分层的评估

基本信息

批准号：
10644765
负责人：
Roger Yeon-Kyu Kim
金额：
$ 24.96万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-01 至 2028-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10644765
关键词：
Address Adult Advisory Committees Agreement Award Benign Biometry Biopsy Cancer Center Classification Clinic Clinical Clinical Management Clinical Oncology Clinical Research Clinical Trials Clinical Trials Design Clinical effectiveness Complex Computer-Assisted Diagnosis Cost Effectiveness Analysis Data Development Plans Diagnosis Diagnostic Early Diagnosis Effectiveness Epidemiology Evaluation Eye Face Financial Support Goals Human Image Individual Institution Intervention K-Series Research Career Programs Knowledge Lung Lung nodule Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Malignant neoplasm of thorax Mentors Mentorship Methods Modeling Outcome Patient-Focused Outcomes Patients Pennsylvania Performance Physicians Positioning Attribute Postdoctoral Fellow Probability Procedures Process Publishing Pulmonary Challenge Pulmonology Quality-Adjusted Life Years Research Research Personnel Research Training Retrospective cohort Retrospective cohort study Risk Risk Estimate Scientist Testing Thoracic Oncology Time Training Universities Use Effectiveness Vision X-Ray Computed Tomography base cancer care cancer diagnosis cancer risk career career development clinical practice clinical risk clinically significant cohort collaborative environment comparative effectiveness trial cost cost effective cost effectiveness cost-effectiveness evaluation diagnostic accuracy effectiveness evaluation experience improved indexing innovation lung cancer screening multidisciplinary new technology novel participant enrollment primary outcome radiomics randomized, clinical trials research clinical testing risk prediction model risk stratification serial imaging skill acquisition supportive environment tool treatment as usual uptake

Address Adult Advisory Committees Agreement Award Benign Biometry Biopsy Cancer Center Classification Clinic Clinical Clinical Management Clinical Oncology Clinical Research Clinical Trials Clinical Trials Design Clinical effectiveness Complex Computer-Assisted Diagnosis Cost Effectiveness Analysis Data Development Plans Diagnosis Diagnostic Early Diagnosis Effectiveness Epidemiology Evaluation Eye Face Financial Support Goals Human Image Individual Institution Intervention K-Series Research Career Programs Knowledge Lung Lung nodule Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Malignant neoplasm of thorax Mentors Mentorship Methods Modeling Outcome Patient-Focused Outcomes Patients Pennsylvania Performance Physicians Positioning Attribute Postdoctoral Fellow Probability Procedures Process Publishing Pulmonary Challenge Pulmonology Quality-Adjusted Life Years Research Research Personnel Research Training Retrospective cohort Retrospective cohort study Risk Risk Estimate Scientist Testing Thoracic Oncology Time Training Universities Use Effectiveness Vision X-Ray Computed Tomography base cancer care cancer diagnosis cancer risk career career development clinical practice clinical risk clinically significant cohort collaborative environment comparative effectiveness trial cost cost effective cost effectiveness cost-effectiveness evaluation diagnostic accuracy effectiveness evaluation experience improved indexing innovation lung cancer screening multidisciplinary new technology novel participant enrollment primary outcome radiomics randomized, clinical trials research clinical testing risk prediction model risk stratification serial imaging skill acquisition supportive environment tool treatment as usual uptake

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项目摘要

PROJECT SUMMARY/ABSTRACT This proposal describes a comprehensive 5-year mentored career development plan with the goal of training the candidate to become a leading independent physician-scientist focused on improving the diagnostic evaluation and management of pulmonary nodules (PNs) to optimize early detection of thoracic cancer and minimize unnecessary harms to patients. The candidate is currently a Post-Doctoral Research Fellow and Attending Pulmonologist at the University of Pennsylvania (Penn). The proposal builds upon Dr. Kim’s previous research training in epidemiology and biostatistics and clinical experience in thoracic oncology. PNs are commonly detected by computed tomography (CT). Lung biopsy, a highly invasive procedure, is required for a definitive diagnosis but carries significant risks and costs. Thus, clinicians face the diagnostic challenge of PN malignancy risk estimation when deciding which patients should undergo a biopsy, and which should be surveilled with repeat imaging. The overall goal of this project is to address the current inadequacy of estimating malignancy risk within the diagnostic process of PN evaluation by assessing the clinical utility and effectiveness of a radiomics-based computer-aided diagnosis (CAD) tool. This novel technology synthesizes quantitative features from raw CT imaging data invisible to the human eye and has been previously demonstrated by the candidate’s team to improve clinicians’ PN diagnostic accuracy. This project’s goal will be accomplished via three complementary specific aims. In Aim 1, a retrospective cohort study will be performed to determine the clinical utility of a CAD-based risk stratification strategy using net reclassification indices, decision curve analysis, and relative utility curves. In Aim 2, a pilot, single-center pragmatic randomized clinical trial will be conducted to compare the clinical effectiveness of a CAD-based risk stratification strategy to usual care for appropriate management of PNs, defined as biopsy or empiric treatment for malignant PNs and surveillance for benign PNs. Finally, in Aim 3, the cost-effectiveness of a CAD-based risk stratification strategy will be evaluated using decision analytic models for a simulated cohort of individuals with newly detected PNs. Dr. Kim has outlined a rigorous training plan of coursework, skills acquisition (with a focus on clinical utility analysis, clinical trial design, decision analytic modeling, and cost-effectiveness analysis), and professional career development. To realize this vision, he has assembled a distinguished, multidisciplinary mentorship and advisory team, led by his primary mentor, Dr. Anil Vachani, the Director of Clinical Research in the Section of Interventional Pulmonology and Thoracic Oncology at Penn, and co-mentor, Dr. Katharine Rendle, Deputy Director for Research at the Penn Center for Cancer Care Innovation. Penn provides an outstanding intellectual, collaborative, and supportive environment for this proposal, positioning Dr. Kim to successfully complete the aims and training plan so that he will be a competitive applicant for an R01 award to perform a multicenter comparative effectiveness trial assessing PN malignancy risk stratification strategies.

项目摘要/摘要该提案描述了一项全面的5年职业发展计划，目的是培训成为领先的独立身体科学家的候选人，专注于改善诊断评估和管理肺结核（PNS），以优化胸癌的早期检测和最大程度地减少对患者的不必要危害。候选人目前是博士后研究员，宾夕法尼亚大学（宾夕法尼亚州）的肺科医生参加。该提案建立在金博士以前的流行病学和生物统计学以及胸部肿瘤学的临床经验的研究培训。 PNS是通常通过计算机断层扫描（CT）检测到。肺活检是一种高度侵入性的手术，需要确定的诊断，但具有重大的风险和成本。那，临床医生面临PN的诊断挑战决定哪些患者应进行活检时，恶性风险估计，哪些应为通过重复成像进行监视。该项目的总体目标是解决当前的不足通过评估临床效用和基于放射线学的计算机辅助诊断（CAD）工具的有效性。这项新技术合成原始CT成像数据的定量特征是人眼看不见的，以前是由候选人团队展示，以提高临床医生的PN诊断准确性。这个项目的目标将是通过三个完整的特定目标完成。在AIM 1中，将进行回顾性队列研究要使用净重新分类指数确定基于CAD的风险分层策略的临床实用性，决策曲线分析和相对效用曲线。在AIM 2中，飞行员单中心务实的随机临床将进行试验，以将基于CAD的风险分层策略与通常的临床有效性进行比较护理适当管理PNS，定义为恶性PN的活检或经验治疗良性PNS的监视。最后，在AIM 3中，基于CAD的风险分层策略的成本效益将使用新检测到的PN的个体的模拟队列进行决策分析模型进行评估。金博士概述了一项严格的课程培训计划，即技能获取（重点是临床实用程序分析，临床试验设计，决策分析建模和成本效益分析）和专业职业发展。为了实现这一愿景，他召集了一个区别，多学科的精神训练和由他的主要导师Anil Vachani博士领导的咨询团队，该部分的临床研究主任宾夕法尼亚州的介入肺病学和胸腔肿瘤学，以及副手Katharine Rendle博士宾夕法尼亚州癌症护理创新中心研究主任。宾夕法尼亚州提供了出色的该建议的智力，协作和支持环境，将金博士定位为成功完成目标和培训计划，以便他将成为R01奖的竞争申请人，以执行多中心比较有效性试验评估PN恶性风险分层策略。