Automatic selection of the optimal cardiac phase for gated three-dimensional coronary x-ray angiography

Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

PURPOSE

The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease.

METHODS

After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment quality. The performance of our automated method was evaluated by comparing the automatically identified best-quality segments identified by the computer to those selected by the observers.

RESULTS

For the 20 test cases, 254 groups of corresponding vessel segments were identified after multiple phase registration and recursive matching. The AI-BQ segments agreed with the radiologist's top 2 ranked segments in 78.3% of the 254 groups (Cohen's kappa 0.60), and with the 4 nonradiologist observers in 76.8%, 84.3%, 83.9%, and 85.8% of the 254 groups. In addition, 89.4% of the AI-BQ segments agreed with at least two observers' top 2 rankings, and 96.5% agreed with at least one observer's top 2 rankings. In comparison, agreement between the four observers' top ranked segment and the radiologist's top 2 ranked segments were 79.9%, 80.7%, 82.3%, and 76.8%, respectively, with kappa values ranging from 0.56 to 0.68.

CONCLUSIONS

The performance of our automated method for selecting the best-quality coronary segments from a multiple-phase cCTA acquisition was comparable to the selection made by human observers. This study demonstrates the potential usefulness of the automated method in clinical practice, enabling interpreting physicians to fully utilize the best available information in cCTA for diagnosis of coronary disease, without requiring manual search through the multiple phases and minimizing the variability in image phase selection for evaluation of coronary artery segments across the diversity of human readers with variations in expertise.

Best-Quality Vessel Identification Using Vessel Quality Measure in Multiple-Phase Coronary CT Angiography

The detection of stenotic plaques strongly depends on the quality of the coronary arterial tree imaged with coronary CT angiography (cCTA). However, it is time consuming for the radiologist to select the best-quality vessels from the multiple-phase cCTA for interpretation in clinical practice. We are developing an automated method for selection of the best-quality vessels from coronary arterial trees in multiple-phase cCTA to facilitate radiologist's reading or computerized analysis. Our automated method consists of vessel segmentation, vessel registration, corresponding vessel branch matching, vessel quality measure (VQM) estimation, and automatic selection of best branches based on VQM. For every branch, the VQM was calculated as the average radial gradient. An observer preference study was conducted to visually compare the quality of the selected vessels. 167 corresponding branch pairs were evaluated by two radiologists. The agreement between the first radiologist and the automated selection was 76% with kappa of 0.49. The agreement between the second radiologist and the automated selection was also 76% with kappa of 0.45. The agreement between the two radiologists was 81% with kappa of 0.57. The observer preference study demonstrated the feasibility of the proposed automated method for the selection of the best-quality vessels from multiple cCTA phases.

Reconstruction of coronary arteries from X-ray angiography: A review

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research.

ECG gated tomographic reconstruction for 3-D rotational coronary angiography

A method is proposed for 3-D reconstruction of coronary from a limited number of projections in rotational angiography. A Bayesian maximum a posteriori (MAP) estimation is applied with a Poisson distributed projection to reconstruct the 3D coronary tree at a given instant of the cardiac cycle. Several regularizers are investigated L0-norm, L1 and L2 -norm in order to take into account the sparsity of the data. Evaluations are reported on simulated data obtained from a 3D dynamic sequence acquired on a 64-slice GE LightSpeed CT scan. A performance study is conducted to evaluate the quality of the reconstruction of the structures.

Clinical feasibility of a fully automated 3D reconstruction of rotational coronary X-ray angiograms

BACKGROUND

Although fixed view x-ray angiography remains the primary technique for anatomic imaging of coronary artery disease, the known shortcomings of 2D projection imaging may limit accurate 3D vessel and lesion definition and characterization. A recently developed method to create 3D images of the coronary arteries uses x-ray projection images acquired during a 180 degrees C-arm rotation and continuous contrast injection followed by ECG-gated iterative reconstruction. This method shows promise for providing high-quality 3D reconstructions of the coronary arteries with no user interaction but requires clinical evaluation.

METHODS AND RESULTS

The reconstruction strategy was evaluated by comparing the reconstructed 3D volumetric images with the 2D angiographic projection images from the same 23 patients to ascertain overall image quality, lesion visibility, and a comparison of 3D quantitative coronary analysis with 2D quantitative coronary analysis. The majority of the resulting 3D volume images were rated as having high image quality (66%) and provided the physician with additional clinical information such as complete visualization of bifurcations and unobtainable views of the coronary tree. True-positive lesion detection rates were high (90 to 100%), whereas false-positive detection rates were low (0 to 8.1%). Finally, 3D quantitative coronary analysis showed significant similarity with 2D quantitative coronary analysis in terms of lumen diameters and provided vessel segment length free from the errors of foreshortening.

CONCLUSIONS

Fully automated reconstruction of rotational coronary x-ray angiograms is feasible, produces 3D volumetric images that overcome some of the limitations of standard 2D angiography, and is ready for further implementation and study in the clinical environment.

A model-based reconstruction method for 3-D rotational coronary angiography

This paper presents a model-based reconstruction method of the coronary tree from a few number of projections in rotational angiography imaging. The reconstruction relies on projections acquired at a same cardiac phase and an energy function minimization that aims to lead the deformation of the 3D model to fit projection data whereas preserving coherence both in time and space. Some preliminary results are provided on simulated rotational angiograms.

Three-dimensional coronary visualization, Part 2: 3D reconstruction

Fully automatic generation of a volumetric representation of the coronary artery tree can be achieved by rotational coronary angiography acquisition and three-dimensional tomographic reconstruction. The generated volume datasets can assist the physician during percutaneous coronary interventions by visualizing three-dimensional coronary morphology and offering utility tools to derive various quantitative measurements. These utility tools allow lesion assessment, optimal working-view selection for specific vessel segments, and improved guidance via overlay functionality or follow C-arc. This article gives an overview of reconstruction methods, clinical tools, and present clinical data.

Rotational coronary angiography

The numerous well-documented limitations of standard fixed-acquisition coronary angiography led to the development of rotational angiography. This acquisition method uses automated gantry movements while numerous angiographic projections are obtained, and thus overcomes many of the limitations of standard angiography. This article highlights the techniques, advantages, and disadvantages of each type of rotational angiography currently commercially available. Also included is a discussion of the evolution of rotational angiography, from its initial conception and pilot studies to its latest step forward on the developmental road towards enhanced coronary imaging.

Computer assistance for solving imaging problems

Medical imaging has moved into an era of digital files and processing of images to yield three-dimensional models and reconstructions. This development has opened up opportunities to apply computer techniques in traditional imaging tasks. Two of the most common imaging tasks are those to correct the two-dimensional projection problems of foreshortening of lesions and of vessel overlap. This article explores the use of computers to assist in these tasks, to create databases for guiding decision making, to provide graphics to assist the physician, and to simulate cardiovascular procedures.

Automatic generation of time resolved motion vector fields of coronary arteries and 4D surface extraction using rotational x-ray angiography

Rotational coronary angiography provides a multitude of x-ray projections of the contrast agent enhanced coronary arteries along a given trajectory with parallel ECG recording. These data can be used to derive motion information of the coronary arteries including vessel displacement and pulsation. In this paper, a fully automated algorithm to generate 4D motion vector fields for coronary arteries from multi-phase 3D centerline data is presented. The algorithm computes similarity measures of centerline segments at different cardiac phases and defines corresponding centerline segments as those with highest similarity. In order to achieve an excellent matching accuracy, an increasing number of bifurcations is included as reference points in an iterative manner. Based on the motion data, time-dependent vessel surface extraction is performed on the projections without the need of prior reconstruction. The algorithm accuracy is evaluated quantitatively on phantom data. The magnitude of longitudinal errors (parallel to the centerline) reaches approx. 0.50 mm and is thus more than twice as large as the transversal 3D extraction errors of the underlying multi-phase 3D centerline data. It is shown that the algorithm can extract asymmetric stenoses accurately. The feasibility on clinical data is demonstrated on five different cases. The ability of the algorithm to extract time-dependent surface data, e.g. for quantification of pulsating stenosis is demonstrated.

Initial clinical experience of selective coronary angiography using one prolonged injection and a 180° rotational trajectory

OBJECTIVE

Evaluate the safety of prolonged coronary injections during a rotational acquisition covering 180 degrees.

BACKGROUND

Rotational angiography has been adapted to coronary angiography and shown to reduce radiation and contrast exposure. Three-dimensional (3D) reconstructions and other advanced applications require imaging over a 180 degrees -arc with a single but longer injection of larger contrast volumes.

METHODS

Thirty patients referred for angiography were enrolled. Blood pressure (BP), heart rate (HR), symptoms, and ectopy were recorded before-and-after injections.

RESULTS

Pre and post-injection HRs for the LCA/RCA were not statistically different (LCA-pre-injection 63+/-13 bpm vs. LCA-post-injection 62+/-11 bpm, P=0.54 and RCA-pre-injection 65+/-12 bpm vs. RCA-post-injection 65+/-10, P=0.88). Central aortic pressure values were not statistically different for the RCA injections (RCA-systolic-pre-injection 118+/-14 mm Hg vs. RCA-systolic-post-injection 112+/-25 mm Hg, P=0.15, and RCA diastolic-pre-injection 69+/-9 mm Hg vs. RCA-diastolic-post-injection 60+/-10 mm Hg, P=0.88) but were statistically significant for the LCA injections (LCA systolic-pre-injection 122+/-19 mm Hg vs. LCA-systolic-post-injection 116+/-17 mm Hg, P=0.0004, and LCA-diastolic-pre-injection 69+/-10 mm Hg vs. LCA-diastolic-post-injection 65+/-9 mm Hg, P=0.0007). There were no symptoms or electrical events documented during or immediately post-injection.

CONCLUSION

This study demonstrates the feasibility and safety of longer coronary injections. There were no significant HR changes, clinically insignificant pressure changes, and no adverse reactions. Additional studies will be needed to assure its safety in a larger and clinically more varied patient population.