CONFERENCE PROCEEDINGS
Advanced Search
Home > Journals > J. Med. Imag. > Volume 10 > Issue 6 > Article
27 December 2023 Coronary stenosis quantification in cardiac computed tomography angiography: multi-factorial optimization of image quality and radiation dose
Mojtaba Zarei, Ehsan Abadi, William Paul Segars, Ehsan Samei
Author Affiliations +
Journal of Medical Imaging, Vol. 10, Issue 6, 063502 (December 2023). https://doi.org/10.1117/1.JMI.10.6.063502
Abstract

Background

The accuracy and variability of quantification in computed tomography angiography (CTA) are affected by the interplay of imaging parameters and patient attributes. The assessment of these combined effects has been an open engineering challenge.

Purpose

In this study, we developed a framework that optimizes imaging parameters for accurate and consistent coronary stenosis quantification in cardiac CTA while accounting for patient-specific variables.

Methods

The framework utilizes a task-specific image quality index, the estimability index (e′), approximated by a surrogate estimability polynomial function (EPF) capable of finding the optimal protocol that (1) maximizes image quality with an upper bound for desired radiation dose or (2) minimizes the dose level with a lower bound of acceptable image quality. The optimization process was formulated with the decision variables being subject to a set of constraints. The methodology was verified using CTA data from a prior clinical trial (prospective multi-center imaging study for evaluation of chest pain) by assessing the concordance of its prediction with the trial results. Further, the framework was used to derive an optimum protocol for each case based on the patient attributes, gauging how much improvement would have been possible if the derived optimized protocol would have been deployed.

Results

The framework produced results consistent with imaging physics principles with approximated EPFs of 97% accuracy. The feature importance evaluation demonstrated a close match with earlier studies. The verification study found e′ scores closely predicting the cardiologist scores to within 95% in terms of the area under the receiver operating characteristic curve and predicting potential for either an average of fourfold increase in e′ within a targeted dose or a reduction in radiation dose by an average of 57% without reducing the image quality.

Conclusions

The protocol optimization framework provides means to assess and optimize CTA in terms of either image quality or radiation dose objectives with its results predicting prior clinical trial findings.
© 2023 Society of Photo-Optical Instrumentation Engineers (SPIE)
Citation Download Citation
Mojtaba Zarei, Ehsan Abadi, William Paul Segars, and Ehsan Samei "Coronary stenosis quantification in cardiac computed tomography angiography: multi-factorial optimization of image quality and radiation dose," Journal of Medical Imaging 10(6), 063502 (27 December 2023). https://doi.org/10.1117/1.JMI.10.6.063502
Received: 10 April 2023; Accepted: 14 November 2023; Published: 27 December 2023
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $24.00
Non-members: $28.00 ADD TO CART
JOURNAL ARTICLE
 18 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image quality
Computed tomography
Mathematical optimization
Decision trees
Angiography
Clinical trials
Data modeling
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top