Characterization of cardiac quiescence from retrospective cardiac computed tomography using a correlation‐based phase‐to‐phase deviation measure

Abstract

Purpose: Accurate knowledge of cardiac quiescence is crucial to the performance of many cardiac imaging modalities, including computed tomography coronary angiography (CTCA). To accurately quantify quiescence, a method for detecting the quiescent periods of the heart from retrospective cardiac computed tomography (CT) using a correlation-based, phase-to-phase deviation measure was developed. Methods: Retrospective cardiac CT data were obtained from 20 patients (11 male, 9 female, 33-74 yr) and the left main, left anterior descending, left circumflex, right coronary artery (RCA), and interventricular septum (IVS) were segmented for each phase using a semiautomated technique. Cardiac motion of individual coronary vessels as well as the IVS was calculated using phase-to-phase deviation. As an easily identifiable feature, the IVS was analyzed to assess how well it predicts vessel quiescence. Finally, the diagnostic quality of the reconstructed volumes from the quiescent phases determined using the deviation measure from the vessels in aggregate and the IVS was compared to that from quiescent phases calculated by the CT scanner. Three board-certified radiologists, fellowship-trained in cardiothoracic imaging, graded the diagnostic quality of the reconstructions using a Likert response format: 1 = excellent, 2 = good, 3 = adequate, 4 = nondiagnostic. Results: Systolic and diastolic quiescent periods were identified for each subject from the vessel motion calculated using the phase-to-phase deviation measure. The motion of the IVS was found to be similar to the aggregate vessel (AGG) motion. The diagnostic quality of the coronary vessels for the quiescent phases calculated from the aggregate vessel (P AGG ) and IVS (P IVS ) deviation signal using the proposed methods was comparable to the quiescent phases calculated by the CT scanner (P CT ). The one exception was the RCA, which improved for P AGG for 18 of the 20 subjects when compared to P CT (P CT = 2.48; P AGG = 2.07, p = 0.001). Conclusions: A method for quantifying the motion of specific coronary vessels using a correlationbased, phase-to-phase deviation measure was developed and tested on 20 patients receiving cardiac CT exams. The IVS was found to be a suitable predictor of vessel quiescence. The diagnostic quality of the quiescent phases detected by the proposed methods was comparable to those calculated by the CT scanner. The ability to quantify coronary vessel quiescence from the motion of the IVS can be used to develop new CTCA gating techniques and quantify the resulting potential improvement in CTCA image quality. C 2015 American Association of Physicists in Medicine.

Echocardiography as an indication of continuous-time cardiac quiescence

“…Location of the IVS for (a) echocardiography and (b) CT. For CT, the blue volume corresponds to the IVS, segmented using the techniques presented by Wick et al (2015b).…”

Evaluation of motion artifact metrics for coronary CT angiography

“…Because of the complexity of motion artifacts, it is difficult to quantify these motion artifact effects individually. Therefore, previous studies have proposed motion artifact metrics that evaluate the overall vessel image quality …”

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

“…The algorithm demonstrated an average phase agreement of 5% between the proposed algorithm and the clinical algorithm, with comparable or better subjective image quality ratings for the selected phase. 11 One limitation of this algorithm is that the coronary artery segmentation was not fully automated. As with previous algorithms, low-motion phases were selected using phase-to-phase processing, typically using 4D data reconstructed at 1% phase intervals.…”

“…As with previous algorithms, low-motion phases were selected using phase-to-phase processing, typically using 4D data reconstructed at 1% phase intervals. 8,11 The objective of this study was to develop and evaluate an automated algorithm to select the best cardiac phase for CCTA reconstruction. The proposed algorithm differs from the previous approaches because the optimal phase is identified based on vessel image quality directly, compared to the previous approaches that included motion estimation and interphase processing.…”

“…8 In a recently proposed algorithm, a deviation metric is calculated as the correlation coefficient between the segmented coronary artery volumes of neighboring phases. 11 The low-motion phase is selected based on the estimated velocity, which is approximated from the deviation metric assuming linear motion and limited vessel deformation in the reconstructed image. The algorithm demonstrated an average phase agreement of 5% between the proposed algorithm and the clinical algorithm, with comparable or better subjective image quality ratings for the selected phase.…”