Dissemination of a Software Platform for Efficient CT Radiation Dose Optimization and Diagnostic Performance Assessment

传播高效 CT 辐射剂量优化和诊断性能评估的软件平台

• 批准号: 10631960
• 负责人: Lifeng Yu
• 金额: $ 31.08万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-20 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10631960
• 关键词: Address; Adoption; Classification; Clinical; Collaborations; Communities; Complex; Computer software; Data; Databases; Detection; Development; Diagnostic; Dose; Educational workshop; Electronic Mail; Encapsulated; Evaluation; Exposure to; Funding; Goals; Human; Image; Imaging Phantoms; Knowledge; Laboratories; Learning; Lesion; Libraries; Manufacturer; Measurement; Measures; Methods; Modeling; Newsletter; Noise; Patient Care; Patients; Performance; Play; Privatization; Protocols documentation; Publications; Radiation; Radiation Dose Unit; Radiation exposure; Reproducibility of Results; Research; Research Personnel; Scanning; Signal Transduction; Software Tools; System; Techniques; Technology; Testing; Translations; United States National Institutes of Health; Validation; Variant; Visual; Work; X-Ray Computed Tomography; clinical practice; clinical research site; computerized data processing; deep learning; diagnostic tool; improved; innovation; interest; novel; novel diagnostics; open source; reconstruction; response; symposium; tool; validation studies; web platform; web site

PROJECT SUMMARY/ABSTRACT With the introduction of many novel techniques to minimize radiation dose in CT, there is still a large variation in terms of radiation dose levels prescribed in CT exams and therefore a large variation of diagnostic performance. Some patients may receive higher dose than necessary. Some may be under-dosed and mis- diagnosed as a result of insufficient image quality. In order to determine the appropriate amount of radiation dose reduction in each exam, accurate quantification of diagnostic performance is needed so that the dose reduction can be achieved without sacrificing important diagnostic information. However, currently there is a lack of efficient and quantitative tools for objective assessment of diagnostic performance, particularly for many of the novel dose reduction methods involving non-linear processing of the data such as iterative reconstruction and deep-learning-based noise reduction methods. The specific goal of this application is to disseminate a highly automated solution, CT Protocol optimization (CTPro) software, to a wide CT community. This quantitative tool provides an efficient implementation of diagnostic performance assessment and CT radiation dose optimization. This tool is based on channelized Hotelling observer (CHO), which itself was developed decades ago to mimic human observer visual responses in signal detection tasks. However, the use of CHO in clinical CT is quite limited because of a lack of rigorous validation and efficient and robust implementation in practice. We were the first to demonstrate its correlation with human observer performance in low-contrast detection, classification and localization tasks in clinical CT. The main objective of the current proposal is to optimize this tool for simplicity and robustness, and disseminate it to CT researchers and clinical users, which will be accomplished through 3 specific aims: Aim 1: Optimize CTPro for simplicity, robustness, and generalizability. Aim 2: Develop an open-source web-based platform for software dissemination. Aim 3: Build use cases and disseminate CTPro. The proposed work is significant because the software tool will allow any CT users and researchers to perform CT radiation dose optimization and diagnostic performance evaluation in an efficient, quantitative, and objective manner. This work is innovative in that the automated tool will use quantitative measures of diagnostic performance to systematically guide the complex task of CT dose optimization, moving beyond traditional metrics that are inappropriate for many novel dose reduction techniques. The software tool, once widely employed, will facilitate a paradigm shift in how dose optimization and the evaluation of dose reduction techniques are performed, and will allow a more rapid and consistent adoption of dose reduction technology into clinical practice, which will benefit millions of CT patients.

项目摘要/摘要 随着许多新技术的引入以最大限度地减少CT的辐射剂量，仍有很大的变化 根据CT检查中规定的辐射剂量水平，因此诊断结果的差异很大 性能。一些患者可能会接受超过必要的剂量。一些可能是剂量不足和误用- 诊断为图像质量不足。为了确定合适的辐射量 减少剂量在每次检查中，需要准确量化诊断性能，以便剂量 可以在不牺牲重要诊断信息的情况下实现减少。但是，目前有一个 缺乏客观评估诊断业绩的有效和量化工具，特别是对许多 涉及诸如迭代等数据的非线性处理的新的剂量减少方法 基于重构和深度学习的降噪方法。 这个应用程序的具体目标是传播一个高度自动化的解决方案，CT协议优化 (CTPro)软件，提供给广泛的CT社区。此量化工具提供了一种高效的 诊断性能评估和CT辐射剂量优化。此工具基于通道化 霍特林观察者(CHO)，它本身是在几十年前开发的，以模拟人类观察者的视觉反应 在信号检测任务中。然而，由于缺乏严谨的标准，CHO在临床CT中的应用相当有限 在实践中进行验证和高效而稳健的实施。我们最先证明了它们之间的关联 具有人类观察者在临床CT低对比度检测、分类和定位任务中的表现。 当前提案的主要目标是优化这一工具，以实现简单性和稳健性，以及 将其传播给CT研究人员和临床用户，这将通过3个具体目标来实现： 目标1：优化CTPro以实现简单性、健壮性和通用性。 目标2：开发一个基于网络的开源软件传播平台。 目标3：构建用例并传播CTPro。 拟议的工作意义重大，因为该软件工具将允许任何CT用户和研究人员执行 CT辐射剂量优化和诊断性能评估在有效、定量和 客观的态度。这项工作是创新的，因为自动化工具将使用 诊断性能，系统地指导复杂的CT剂量优化任务，超越 传统的测量方法不适用于许多新的剂量减少技术。软件工具，曾经 广泛应用，将促进剂量优化和剂量减少评估的范式转变 技术的实施，并将允许更快和更一致地采用剂量减少技术 进入临床实践，这将使数百万CT患者受益。

项目成果

Rapid measurement of the low contrast detectability of CT scanners.

• DOI: 10.1002/mp.14657
• 发表时间: 2021-03
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: Omigbodun A;Vaishnav JY;Hsieh SS
• 通讯作者: Hsieh SS

Improvements in dose efficiency with high resolution scan modes in photon counting CT.

光子计数 CT 中高分辨率扫描模式提高了剂量效率。

• DOI: 10.1117/12.2654334
• 发表时间: 2023
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Shunhavanich,Picha;Rajendran,Kishore;Fan,Mingdong;McCollough,CynthiaH;Leng,Shuai;Yu,Lifeng;Hsieh,ScottS
• 通讯作者: Hsieh,ScottS

Efficient Evaluation of Low-contrast Detectability of Deep-CNN-based CT Reconstruction Using Channelized Hotelling Observer on the ACR Accreditation Phantom.

在 ACR 认证模型上使用通道化 Hotelling 观察器对基于深度 CNN 的 CT 重建的低对比度可检测性进行有效评估。

• DOI: 10.1117/12.2612414
• 发表时间: 2022
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Fan,Mingdong;Zhou,Zhongxing;Vrieze,Thomas;Wang,Jia;McCollough,Cynthia;Yu,Lifeng
• 通讯作者: Yu,Lifeng

Automated Web-based Software for CT Quality Control Testing of Low-contrast Detectability using Model Observers.

基于网络的自动化软件，用于使用模型观察器对低对比度可检测性进行 CT 质量控制测试。

• DOI: 10.1117/12.3008777
• 发表时间: 2024
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Zhou,Zhongxing;Wellinghoff,Jarod;Fan,Mingdong;Hsieh,Scott;Holmes3rd,David;McCollough,CynthiaH;Yu,Lifeng
• 通讯作者: Yu,Lifeng

3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.

具有 12000 个亚毫米病变的 3D 打印模型，可提高 CT 可检测性评估的效率。

• DOI: 10.1002/mp.17064
• 发表时间: 2024
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: Shunhavanich,Picha;Mei,Kai;Shapira,Nadav;Stayman,JosephWebster;McCollough,CynthiaH;Gang,Grace;Leng,Shuai;Geagan,Michael;Yu,Lifeng;Noël,PeterB;Hsieh,ScottS
• 通讯作者: Hsieh,ScottS