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.

Public Health Relevance

There has been a lack of quantitative tools for efficient and objective assessment of diagnostic performance in CT, which is the reason why inappropriate radiation dose is frequently used in CT exams, resulting in unnecessarily high radiation exposure to patients or lose of important diagnostic information. The purpose of this project is to disseminate a highly automated solution to a wide CT community for efficient CT radiation dose optimization. If successful, appropriate amount of radiation can be prescribed for millions of CT patients at any facility, while maintaining the level of diagnostic information required for high quality patient care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
1U24EB028936-01
Application #
9881453
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Shabestari, Behrouz
Project Start
2019-09-20
Project End
2024-05-31
Budget Start
2019-09-20
Budget End
2020-05-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905