The usefulness of low radiation dose subtraction coronary computed tomography angiography for patients with calcification using 320-row area detector CT

Subtraction coronary CT angiography in patients with high heart rate

All the previous subtraction coronary CT angiography (CCTA) had strict heart rate (HR) inclusion criteria. In this study, a new subtraction method was applied to patients with various HR. The post-contrast scan time was respectively 3.5 s after ascending aorta peak enhancement while HR >80 bpm, 4 s while 65≤ HR ≤80 bpm and 4.5 s while HR <65 bpm. Forty-six patients who underwent the new subtraction protocol were enrolled and patients were stratified into the high HR group (≥70 bpm) and low HR group (<70 bpm). Eighteen patients with 15 severe calcification segments and 25 stent segments further received invasive coronary angiography (ICA). In all included patients, the coronary artery enhancement was compared between the high and low HR groups. In patients with ICA performed, the image quality improvement and diagnostic effectiveness for detection of significant coronary segments stenosis (>50%) were compared between the conventional CCTA and subtraction CCTA and between the high HR group and low HR group, respectively. All enrolled patients got sufficient coronary artery enhancement. In patients with ICA performed, receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) for the diagnosis of significant stenosis was 0.93 in subtraction CCTA and 0.73 in conventional CCTA (p < 0.05). Furthermore, there were no significant differences in image quality improvement, specificity, positive predictive value and accuracy between the high HR group and low HR group. The new subtraction CCTA method broadened the clinical availability for patients with high HR.

Use of a deep-learning-based lumen extraction method to detect significant stenosis on coronary computed tomography angiography in patients with severe coronary calcification

Background

Coronary computed tomography angiography examinations are increasingly becoming established as a minimally invasive method for diagnosing coronary diseases. However, although various imaging and processing methods have been developed, coronary artery calcification remains a major limitation in the evaluation of the vascular lumen. Subtraction coronary computed tomography angiography (Sub-CCTA) is a method known to be able to reduce the influence of coronary artery calcification and is therefore feasible for improving the diagnosis of significant stenosis in patients with severe calcification. However, Sub-CCTA still involves some problems, such as the increased radiation dose due to plain (mask) imaging, extended breath-holding time, and misregistration due to differences in the imaging phase. Therefore, we considered using artificial intelligence instead of Sub-CCTA to visualize the coronary lumen with high calcification. Given this background, the present study aimed to evaluate the diagnostic performance of a deep learning-based lumen extraction method (DL-LEM) to detect significant stenosis on CCTA in 99 consecutive patients (891 segments) with severe coronary calcification from November 2015 to March 2018. We also estimated the impact of DL-LEM on the medical economics in Japan.

Results

The DL-LEM slightly improved the per-segment diagnostic accuracy from 74.5 to 76.4%, and the area under the curve (AUC) slightly improved from 0.752 to 0.767 (p = 0.030). When analyzing the 228 segments that could not be evaluated because of severe calcification on the original CCTA images, the DL-LEM improved the accuracy from 35.5 to 42.5%, and the AUC improved from 0.500 to 0.587 (p = 0.00018). As a result, DL-LEM analysis could have avoided invasive coronary angiography in 4/99 cases (per patient). From the calculated results, it was estimated that the number of exams that can be avoided in Japan in one year is approximately 747 for invasive coronary angiography, 219 for fractional flow reserve, and 248 for nuclear exam. The total amount of medical fee that could be reduced was 225,629,368 JPY.

Conclusions

These findings suggest that the DL-LEM may improve the diagnostic performance in detecting significant stenosis in patients with severe coronary calcification. In addition, the results suggest that not a small medical economic effect can be expected.

The usefulness of subtraction coronary computed tomography angiography for in-stent restenosis assessment of patients with CoCr stent using 320-row area detector CT

The aim of this study was to assess in-stent restenosis (ISR) of coronary artery for patients with CoCr stent using subtraction coronary computed tomography angiography (CCTA) with one-breath-hold scan on 320-row area detector CT, invasive coronary angiography (ICA) as clinical standard.Patients who were referred for CCTA from January 2020 to May 2021 were retrospectively analyzed. Pre-contrast and CCTA was performed with dedicated one-breath-hold subtraction scan protocol and post processing to get subtracted-CCTA image without stent. Subjective image qualities and diagnosable rate were analyzed for CCTA and subtracted-CCTA respectively. The ISR degree of each stent was evaluated both on CCTA and subtracted-CCTA images. The receiver-operating characteristic curve with sensitivity, specificity, accuracy of CCTA, and subtracted-CCTA in the diagnosis of ISR were calculated with ICA as reference.Forty patients with 85 CoCr coronary stents of 3 to 3.5 mm diameter with ICA confirmation within 1 month were finally included. Subtracted-CCTA showed more diagnosable segments of stent (91.76% [78/85]) than those of CCTA (50.59% [43/85]) (P < .001). The subjective image quality score of CCTA was 2.23 ± 1.32 while 3.41 ± 0.90 on subtracted-CCTA (P < .001). Both subtracted-CCTA and CCTA showed high consistency with ICA (Kappa = 0.795 and 0.918 respectively). The area under the curve was 0.607 for CCTA and 0.757 for subtracted-CCTA (P < .001) for stent based diagnose, respectively. The sensitivity, specificity, accuracy of CCTA, and subtracted-CCTA were 90.0%, 97.0%, 95.3%, and 87.5%, 100.0%, 97.43%, respectively.Subtracted-CCTA showed improved diagnose performance for ISR, which potentially reduce further follow-up ICA procedures for patients with CoCr stents.

Diagnostic Improvements of Deep Learning-Based Image Reconstruction for Assessing Calcification-Related Obstructive Coronary Artery Disease

Objectives: The objective of this study was to explore the diagnostic value of deep learning-based image reconstruction (DLR) and hybrid iterative reconstruction (HIR) for calcification-related obstructive coronary artery disease (CAD) evaluation by using coronary CT angiography (CCTA) images and subtraction CCTA images.

Methods: Forty-two consecutive patients with known or suspected coronary artery disease who underwent coronary CTA on a 320-row CT scanner and subsequent invasive coronary angiography (ICA), which was used as the reference standard, were enrolled. The DLR and HIR images were reconstructed as CTA_DLR and CTA_HIR, and, based on which, the corresponding subtraction CCTA images were established as CTA_sDLR and CTA_sHIR, respectively. Qualitative images quality comparison was performed by using a Likert 4 stage score, and quantitative images quality parameters, including image noise, signal-to-noise ratio, and contrast-to-noise ratio were calculated. Diagnostic performance on the lesion level was assessed and compared among the four CCTA approaches (CTA_DLR, CTA_HIR, CTA_sDLR, and CTA_sHIR).

Results: There were 166 lesions of 86 vessels in 42 patients (32 men and 10 women; 62.9 ± 9.3 years) finally enrolled for analysis. The qualitative and quantitative image qualities of CTA_sDLR and CTA_DLR were superior to those of CTA_sHIR and CTA_HIR, respectively. The diagnostic accuracies of CTA_sDLR, CTA_DLR, CTA_sHIR, and CTA_HIR to identify calcification-related obstructive diameter stenosis were 83.73%, 69.28%, 75.30%, and 65.66%, respectively. The false-positive rates of CTA_sDLR, CTA_DLR, CTA_sHIR, and CTA_HIR for luminal diameter stenosis ≥50% were 15%, 31%, 24%, and 34%, respectively. The sensitivity and the specificity to identify ≥50% luminal diameter stenosis was 90.91% and 83.23% for CTA_sDLR.

Conclusion: Our study showed that deep learning–based image reconstruction could improve the image quality of CCTA images and diagnostic performance for calcification-related obstructive CAD, especially when combined with subtraction technique.

Incremental Diagnostic Value of CT Fractional Flow Reserve Using Subtraction Method in Patients with Severe Calcification: A Pilot Study

Although on-site workstation-based CT fractional flow reserve (CT-FFR) is an emerging method for assessing vessel-specific ischemia in coronary artery disease, severe calcification is a significant factor affecting CT-FFR’s diagnostic performance. The subtraction method significantly improves the diagnostic value with respect to anatomic stenosis for patients with severe calcification in coronary CT angiography (CCTA). We evaluated the diagnostic capability of CT-FFR using the subtraction method (subtraction CT-FFR) in patients with severe calcification. This study included 32 patients with 45 lesions with severe calcification (Agatston score >400) who underwent both CCTA and subtraction CCTA using 320-row area detector CT and also received invasive FFR within 90 days. The diagnostic capabilities of CT-FFR and subtraction CT-FFR were compared. The sensitivities, specificities, positive predictive values (PPVs), and negative predictive values (NPVs) of CT-FFR vs. subtraction CT-FFR for detecting hemodynamically significant stenosis, defined as FFR ≤ 0.8, were 84.6% vs. 92.3%, 59.4% vs. 75.0%, 45.8% vs. 60.0%, and 90.5% vs. 96.0%, respectively. The area under the curve for subtraction CT-FFR was significantly higher than for CT-FFR (0.84 vs. 0.70) (p = 0.04). The inter-observer and intra-observer variabilities of subtraction CT-FFR were 0.76 and 0.75, respectively. In patients with severe calcification, subtraction CT-FFR had an incremental diagnostic value over CT-FFR, increasing the specificity and PPV while maintaining the sensitivity and NPV with high reproducibility.

Combined assessment of subtended myocardial volume and myocardial blood flow for diagnosis of obstructive coronary artery disease using cardiac computed tomography: A feasibility study

BACKGROUND

This study aimed to evaluate the combined diagnostic performance of coronary artery stenosis-subtended myocardial volume (V_sub) and myocardial blood flow (MBFsub) on computed tomography (CT) for detecting obstructive coronary artery disease (CAD) assessed by invasive coronary angiography (ICA) and fractional flow reserve (FFR).

METHODS

Thirty-nine patients who underwent coronary CT angiography (CTA) and stress dynamic myocardial CT perfusion (CTP) prior to ICA were enrolled. Obstructive CAD was defined as severe (≥70%) or moderate (30-69%) stenosis with FFR ≤0.8 on ICA. The V_sub was semi-automatically calculated from coronary CTA data using Voronoi diagram-based myocardial segmentation. The standard CT-MBF based on the 17-segment model was calculated using dynamic stress CTP data and deconvolution analysis. The CT-MBFsub was automatically analyzed by integrating the CT-MBF and Voronoi diagram-based myocardial segmentation analyses. The diagnostic performance of combined CT-MBFsub and V_sub assessment was determined using receiver operating characteristic analysis and compared with standard CT-MBF and CT-MBFsub.

RESULTS

Of 117 vessels in 39 patients, 72 vessels were suspected of significant stenosis on CTA and 33 vessels had obstructive CAD on ICA and FFR. The sensitivity and specificity for identifying obstructive CAD were 67% and 82% for standard CT-MBF, 70% and 77% for CT-MBFsub, and 85% and 82% for combined CT-MBFsub and V_sub assessment. The area under the receiver operating characteristic curve of the combined CT-MBFsub and V_sub assessment was significantly higher than those of standard CT-MBF and CT-MBFsub (0.89 vs. 0.75, 0.77; p<0.05).

CONCLUSIONS

The V_sub may aid in increasing the diagnostic performance of CT-MBFsub for detecting obstructive CAD.

Should CT replace IVUS for evaluation of CAD in large-scale clinical trials: Effects of medical therapy on atherosclerotic plaque

Clinical trials assessing the effect of medical therapies on atherosclerotic plaques have hitherto employed invasive imaging techniques such as intravascular ultrasound (IVUS). This has limited the study population to high-risk patients in whom invasive coronary angiography is indicated; moreover, IVUS typically is performed utilizing a target lesion-based analysis. Recently, comprehensive quantitative analysis of all atherosclerotic plaques in the complete coronary artery network has become possible through the use of coronary computed tomography angiography (CCTA). Excellent inter-observer and inter-scan reproducibility of CCTA has been reported. Several studies have already tested the applicability of CCTA-measured plaque volume changes as an imaging surrogate endpoint in clinical trials and have found positive results. Further, substantial evidence supports the use of CCTA as a novel imaging surrogate that can accurately assess the changes in plaque characteristics according to medical treatment. In this review, we summarize current evidences that support the use of CCTA as a novel imaging surrogate that can replace IVUS in evaluating the results of treatment. We also attempt to determine whether the technological advances in CCTA will extend its application beyond use as a diagnostic method in clinical practice to use in large-scale clinical trials.