Image Quality, Overall Evaluability, and Effective Radiation Dose of Coronary Computed Tomography Angiography With Prospective Electrocardiographic Triggering Plus Intracycle Motion Correction Algorithm in Patients With a Heart Rate Over 65 Beats Per Minute

Optimizing coronary CT angiography quality with motion-compensated reconstruction for second-generation dual-layer spectral detector CT

OBJECTIVES

To investigate the effect of motion-compensated reconstruction (MCR) algorithm on improving the image quality of coronary computed tomography angiography (CCTA) using second-generation dual-layer spectral detector computed tomography (DLCT), and to evaluate the influence of heart rate (HR) on the motion-correction efficacy of this algorithm.

MATERIALS AND METHODS

We retrospectively enrolled 127 patients who underwent CCTA for suspected coronary artery disease using second-generation DLCT. We divided the patients into two subgroups according to their average HR during scanning: the "HR < 75 bpm" group and the "HR ≥ 75 bpm" group. All images were reconstructed by the standard (STD) algorithm and MCR algorithm. Subjective image quality (4-point Likert scale), interpretability, and objective image quality between the STD and MCR in the whole population and within each subgroup were compared.

RESULTS

MCR showed significantly higher Likert scores and interpretability than STD on the per-segment (3.58 ± 0.69 vs. 2.82 ± 0.93, 98.4% vs. 91.9%), per-vessel (3.12 ± 0.81 vs. 2.12 ± 0.74, 96.3% vs. 78.7%) and per-patient (2.57 ± 0.76 vs. 1.62 ± 0.55, 90.6% vs. 59.1%) levels (all p < 0.001). In the analysis of HR subgroups on a per-vessel basis of interpretability, significant differences were observed only in the right coronary artery in the low HR group, whereas significant differences were noted in three major coronary arteries in the high HR group. For objective image quality assessment, MCR significantly improved the SNR (13.22 ± 4.06 vs. 12.72 ± 4.06) and the contrast-to-noise ratio (15.84 ± 4.82 vs. 15.39 ± 4.38) compared to STD (both p < 0.001).

CONCLUSION

MCR significantly improves the subjective image quality, interpretability, and objective image quality of CCTA, especially in patients with higher HRs.

CLINICAL RELEVANCE STATEMENT

The motion-compensated reconstruction algorithm of the second-generation dual-layer spectral detector computed tomography is helpful in improving the image quality of coronary computed tomography angiography in clinical practice, especially in patients with higher heart rates.

KEY POINTS

Motion artifacts from cardiac movement affect the quality and interpretability of coronary computed tomography angiography (CCTA). This motion-compensated reconstruction (MCR) algorithm significantly improves the image quality of CCTA in clinical practice. Image quality improvement by using MCR was more significant in the high heart rate group.

Bodyweight-adjusted Contrast Media With Shortened Injection Duration for Step-and-Shoot Coronary Computed Tomography Angiography to Acquire Improved Image Quality

PURPOSE

Shortened injection durations are not recommended in step-and-shoot coronary computed tomography angiography (CCTA). We aimed to evaluate the image quality of CCTA performed using bodyweight-adjusted iodinated contrast media (ICM) with different injection durations to generate an optimized ICM administration protocol to acquire convincible image quality in step-and-shoot CCTA.

MATERIALS AND METHODS

A total of 200 consecutive patients with suspected coronary artery disease (CAD) were enrolled in group A (N=50, 350 mgI/mL, bodyweight×0.8 mL/kg with a 13-s injection duration), group B (N=50, 350 mgI/mL, bodyweight×0.9 mL/kg with a 13-s injection duration), group C (N=50, 350 mgI/mL, bodyweight×0.8 mL/kg with a 12-s injection duration), and group D (N=50, 320 mgI/mL, bodyweight×0.8 mL/kg with a 13-s injection duration). Patient characteristics, ICM administration protocols, quantitative computed tomography (CT) value measurements, and qualitative image scores were analyzed and compared among the groups.

RESULTS

Groups A and D achieved the lowest ICM volume, saline volume, injection flow rate, and total iodine and iodine injection rates among the groups. All the CT values of the coronary arteries in all groups were >300 HU. All the observers' average scores exceeded three points. In group A, the CT values showed significant positive correlation with the iodine injection rate ( r =0.226, P <0.001), whereas the signal-to-noise ratio ( r =-0.004, P =0.927) and contrast-to-noise ratio ( r =-0.006, P =0.893) values were not.

CONCLUSIONS

Bodyweight×0.8 mL/kg with a 13-second injection duration is a comprehensive option for step-and-shoot CCTA with improved image quality, and a 350 mgI/mL iodine concentration is preferred.

Impact of coronary CT image quality on the accuracy of the FFRCT Planner

OBJECTIVE

To assess the accuracy of a virtual stenting tool based on coronary CT angiography (CCTA) and fractional flow reserve (FFR) derived from CCTA (FFRCT Planner) across different levels of image quality.

MATERIALS AND METHODS

Prospective, multicenter, single-arm study of patients with chronic coronary syndromes and lesions with FFR ≤ 0.80. All patients underwent CCTA performed with recent-generation scanners. CCTA image quality was adjudicated using the four-point Likert scale at a per-vessel level by an independent committee blinded to the FFRCT Planner. Patient- and technical-related factors that could affect the FFRCT Planner accuracy were evaluated. The FFRCT Planner was applied mirroring percutaneous coronary intervention (PCI) to determine the agreement with invasively measured post-PCI FFR.

RESULTS

Overall, 120 patients (123 vessels) were included. Invasive post-PCI FFR was 0.88 ± 0.06 and Planner FFRCT was 0.86 ± 0.06 (mean difference 0.02 FFR units, the lower limit of agreement (LLA) - 0.12, upper limit of agreement (ULA) 0.15). CCTA image quality was assessed as excellent (Likert score 4) in 48.3%, good (Likert score 3) in 45%, and sufficient (Likert score 2) in 6.7% of patients. The FFRCT Planner was accurate across different levels of image quality with a mean difference between FFRCT Planner and invasive post-PCI FFR of 0.02 ± 0.07 in Likert score 4, 0.02 ± 0.07 in Likert score 3 and 0.03 ± 0.08 in Likert score 2, p = 0.695. Nitrate dose ≥ 0.8mg was the only independent factor associated with the accuracy of the FFRCT Planner (95%CI - 0.06 to - 0.001, p = 0.040).

CONCLUSION

The FFRCT Planner was accurate in predicting post-PCI FFR independent of CCTA image quality.

CLINICAL RELEVANCE STATEMENT

Being accurate in predicting post-PCI FFR across a wide spectrum of CT image quality, the FFRCT Planner could potentially enhance and guide the invasive treatment. Adequate vasodilation during CT acquisition is relevant to improve the accuracy of the FFRCT Planner.

KEY POINTS

• The fractional flow reserve derived from coronary CT angiography (FFRCT) Planner is a novel tool able to accurately predict fractional flow reserve after percutaneous coronary intervention. • The accuracy of the FFRCT Planner was confirmed across a wide spectrum of CT image quality. Nitrates dose at CT acquisition was the only independent predictor of its accuracy. • The FFRCT Planner could potentially enhance and guide the invasive treatment.

CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline

BACKGROUND AND OBJECTIVE

The standard non-invasive imaging technique used to assess the severity and extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography Angiography (CCTA). However, manual grading of each patient's CCTA according to the CAD-Reporting and Data System (CAD-RADS) scoring is time-consuming and operator-dependent, especially in borderline cases. This work proposes a fully automated, and visually explainable, deep learning pipeline to be used as a decision support system for the CAD screening procedure. The pipeline performs two classification tasks: firstly, identifying patients who require further clinical investigations and secondly, classifying patients into subgroups based on the degree of stenosis, according to commonly used CAD-RADS thresholds.

METHODS

The pipeline pre-processes multiplanar projections of the coronary arteries, extracted from the original CCTAs, and classifies them using a fine-tuned Multi-Axis Vision Transformer architecture. With the aim of emulating the current clinical practice, the model is trained to assign a per-patient score by stacking the bi-dimensional longitudinal cross-sections of the three main coronary arteries along channel dimension. Furthermore, it generates visually interpretable maps to assess the reliability of the predictions.

RESULTS

When run on a database of 1873 three-channel images of 253 patients collected at the Monzino Cardiology Center in Milan, the pipeline obtained an AUC of 0.87 and 0.93 for the two classification tasks, respectively.

CONCLUSION

According to our knowledge, this is the first model trained to assign CAD-RADS scores learning solely from patient scores and not requiring finer imaging annotation steps that are not part of the clinical routine.

Design of a 3D printed coronary artery model for CT optimization

INTRODUCTION

To design a custom phantom of the coronary arteries to optimize CT coronary angiography (CCTA) protocols.

METHODS

Characteristics of the left and right coronary arteries (mean Hounsfield Unit (HU) values and diameters) were collected from consecutive CCTA examinations (n = 43). Four different materials (two mixtures of glycerine, gelatine and water, pig hearts, Ecoflex™ silicone) were scanned inside a Lungman phantom using the CCTA protocol to find the closest model to in vivo data. A 3D printed model of the coronary artery tree was created using CCTA data by exporting a CT volume rendering into Autodesk Meshmixer™ software. The model was placed in an acid bath for 5 h, then covered in Ecoflex™, which was removed after drying. Both the Ecoflex™ and pig heart were later filled with a mixture of contrast (Visipaque 320 mg I/ml), NaCl and gelatin and scanned with different levels of tube current and iterative reconstruction (ASiR-V). Objective (HU, noise and size (vessel diameter) and subjective analysis were performed on all scans.

RESULTS

The gelatine mixtures had HU values of 130 and 129, Ecoflex™ 65 and the pig heart 56. At the different mA/ASiR-V levels the contrast filled Ecoflex™ had a mean HU 318 ± 4, noise 47±7HU and diameter of 4.4 mm. The pig heart had a mean HU of 209 ± 5, noise 38±4HU and a diameter of 4.4 mm. With increasing iterative reconstruction level the visualisation of the pig heart arteries decreased so no measurements could be performed.

CONCLUSION

The use of a 3D printed model of the arteries and casting with the Ecoflex™ silicone is the most suitable solution for a custom-designed phantom.

IMPLICATIONS FOR PRACTICE

Custom designed phantoms using 3D printing technology enable cost effective optimisation of CT protocols.

Tube Voltage, DNA Double-Strand Breaks, and Image Quality in Coronary CT Angiography

OBJECTIVE

To evaluate the effects of tube voltage on image quality in coronary CT angiography (CCTA), the estimated radiation dose, and DNA double-strand breaks (DSBs) in peripheral blood lymphocytes to optimize the use of CCTA in the era of low radiation doses.

MATERIALS AND METHODS

This study included 240 patients who were divided into 2 groups according to the DNA DSB analysis methods, i.e., immunofluorescence microscopy and flow cytometry. Each group was subdivided into 4 subgroups: those receiving CCTA only with different tube voltages of 120, 100, 80, or 70 kVp. Objective and subjective image quality was evaluated by analysis of variance. Radiation dosages were also recorded and compared.

RESULTS

There was no significant difference in demographic characteristics between the 2 groups and 4 subgroups in each group (all p > 0.05). As tube voltage decreased, both image quality and radiation dose decreased gradually and significantly. After CCTA, γ-H2AX foci and mean fluorescence intensity in the 120-, 100-, 80-, and 70-kVp groups increased by 0.14, 0.09, 0.07, and 0.06 foci per cell and 21.26, 9.13, 8.10, and 7.13 (all p < 0.05), respectively. The increase in the DNA DSB level in the 120-kVp group was higher than those in the other 3 groups (all p < 0.05), while there was no significant difference in the DSBs levels among these latter groups (all p > 0.05).

CONCLUSION

The 100-kVp tube voltage may be optimal for CCTA when weighing DNA DSBs against the estimated radiation dose and image quality, with further reductions in tube voltage being unnecessary for CCTA.

Improved visualization of the coronary arteries using motion correction during vasodilator stress CT myocardial perfusion imaging

BACKGROUND

Vasodilator stress computed tomography perfusion (sCTP) imaging is complementary to coronary CT angiography (CCTA), used to determine the hemodynamic significance of coronary artery disease. However, it requires a separate image acquisition due to motion artifacts caused by higher heart rates during stress, resulting in increased iodine contrast dose and radiation. We sought to determine whether a novel motion correction algorithm applied to stress images would improve the visualization of the coronary arteries to potentially allow CCTA + sCTP evaluation in a single scan.

METHODS

28 patients referred for clinically indicated CCTA (iCT, Philips) underwent sCTP imaging (retrospective-gating with dose modulation; 100 kVp and 250 mA; 5.2 ± 4.3 mSv) after regadenoson (0.4 mg, Astellas). Stress images were reconstructed using standard filtered back-projection (FBP) and also processed to generate interaction-free coronary motion-compensated back-projection reconstructions (MCR). Each coronary artery from standard FBP and MCR images was viewed side-by-side by a reader blinded to the reconstruction technique, who graded severity of motion artifact by segment (scale 0-5, with 3 as the threshold for diagnostic quality) and to measure signal-to-noise and contrast-to-noise ratios (SNR, CNR).

RESULTS

Visualization scores were higher with MCR for all coronary segments, including 14/86 (16%) segments deemed as non-diagnostic on FBP images. SNR (7 ± 2) and CNR (15 ± 8) were unchanged by motion-correction (7 ± 3, p = 0.88 and 15 ± 5, p = 0.94, respectively).

CONCLUSIONS

MCR improves the visualization of coronary anatomy on sCTP images without degrading image characteristics. This algorithm is an important step towards the combined assessment of coronary anatomy and myocardial perfusion in a single scan, which will reduce study time, radiation exposure and contrast dose.