Application of speCtraL computed tomogrAphy to impRove specIficity of cardiac compuTed tomographY (CLARITY study): rationale and design

Abstract

IntroductionAnatomic stenosis evaluation on coronary CT angiography (CCTA) lacks specificity in indicating the functional significance of a stenosis. Recent developments in CT techniques (including dual-layer spectral detector CT [SDCT] and static stress CT perfusion [CTP]) and image analyses (including fractional flow reserve [FFR] derived from CCTA images [FFRCT] and deep learning analysis [DL]) are potential strategies to increase the specificity of CCTA by combining both anatomical and functional information in one investigation. The aim of the current study is to assess the diagnostic performance of (combinations of) SDCT, CTP, FFRCTand DL for the identification of functionally significant coronary artery stenosis.Methods and analysisSeventy-five patients aged 18 years and older with stable angina and known coronary artery disease and scheduled to undergo clinically indicated invasive FFR will be enrolled. All subjects will undergo the following SDCT scans: coronary calcium scoring, static stress CTP, rest CCTA and if indicated (history of myocardial infarction) a delayed enhancement acquisition. Invasive FFR of ≤0.80, measured within 30 days after the SDCT scans, will be used as reference to indicate a functionally significant stenosis. The primary study endpoint is the diagnostic performance of SDCT (including CTP) for the identification of functionally significant coronary artery stenosis. Secondary study endpoint is the diagnostic performance of SDCT, CTP, FFRCTand DL separately and combined for the identification of functionally significant coronary artery stenosis.Ethics and disseminationEthical approval was obtained. All subjects will provide written informed consent. Study findings will be disseminated through peer-reviewed conference presentations and journal publications.Trial registration numberNCT03139006; Pre-results.

Deep learning from dual‐energy information for whole‐heart segmentation in dual‐energy and single‐energy non‐contrast‐enhanced cardiac CT

“…The dual-energy set contained CT images of 18 patients that were scanned using a dual-layer detector CT scanner (IQon, Philips Healthcare, Best, The Netherlands) in an ongoing prospective study aimed at assessing the diagnostic performance of dual-layer detector CT for the identification of functionally significant coronary artery stenosis. 26 Each patient received a non-contrast-enhanced acquisition which was reconstructed into an NCCT image. This was followed by an acquisition with contrast enhancement.…”

Dual-energy CT and coronary imaging

“…Future studies are still needed to determine the comparative effectiveness of stress CTP across multiple centers and platforms versus established and emerging methods for detecting myocardial ischemia, such as SPECT and CT-FFR. For instance, an ongoing study have been designed to compare the diagnostic performance of dlDECT, stress CT perfusion, CT-FFR, and deep learning to increase specificity using anatomical and functional imaging (74).…”

CNN-Based Segmentation of the Cardiac Chambers and Great Vessels in Non-Contrast-Enhanced Cardiac CT

“…We used a primary data set (van Hamersvelt et al, 2019) consisting of CT images of 18 patients scanned on a Philips IQon dual-layer-detector CT scanner (Philips Healthcare, Best, The Netherlands). Hence, a CT acquisition with contrast enhancement could be reconstructed into a CCTA and a VNC image and these two images were perfectly aligned.…”