Project description:BackgroundTo analyze the imaging features of coronary artery-to-pulmonary artery fistula (CPAF) on coronary computed tomography angiography (CCTA).MethodsThis was a retrospective study of 3,975 patients who underwent 320 row detector CCTA examinations in our hospital from May 2015 to July 2020. A total of 22 patients who diagnosed with CPAF were reviewed for CCTA imaging characteristics, including the origin, number, blood volume, opening size, and course of fistula vessels, and the drainage site, size, and imaging features of the fistula. All cases were analyzed for the presence of coronary atherosclerotic plaque and that of deficient left ventricular myocardial perfusion.ResultsA total of 22 CPAF cases detected by CCTA were collected (men, 11; women, 11; median age, 59.6±10.1 years). There were 7, 10, and 5 cases detected with 1, 2, and 3 fistula vessels, respectively, among which 4 originated from the left coronary artery, 4 from the right coronary artery, and 14 had bilateral origins. There were 10 cases in which the fistula vessels presented as a worm-like tortuous dilation with (n=5) or without (n=5) aneurysm, while 12 cases showed malformed vascular networks with (n=8) or without (n=4) aneurysm, respectively. The calculated incidence of aneurysm formation was 59.09%, and fistula vessels with an aneurysm had larger blood volume than those without. All fistula showed a single drainage site, with an average diameter of 2.81±1.48 mm where the diameter of fistula with aneurysm was larger than that without. The fistula vessels drained into the left anterolateral and anterior walls of main pulmonary artery and the proximal left inferior PA, respectively. Typical jet sign, smoke sign, and isodensity sign were presented in 22, 14 and 1 case, respectively. For the coexistent abnormalities analyzed in 22 cases, 17 participants with CPAF demonstrated hypoperfusion of the fistula vessels, and 11 demonstrated calcified plaque accompanied with luminal stenosis to different degrees.ConclusionsThe 320-row detector CCTA can comprehensively characterize the morphological features of CPAF, which is an optimal choice for physicians to make an accurate assessment before formulating patient management strategies.
Project description:BackgroundAlthough four-dimensional cone-beam computed tomography (4D-CBCT) is valuable to provide onboard image guidance for radiotherapy of moving targets, it requires a long acquisition time to achieve sufficient image quality for target localization. To improve the utility, it is highly desirable to reduce the 4D-CBCT scanning time while maintaining high-quality images. Current motion-compensated methods are limited by slow speed and compensation errors due to the severe intraphase undersampling.PurposeIn this work, we aim to propose an alternative feature-compensated method to realize the fast 4D-CBCT with high-quality images.MethodsWe proposed a feature-compensated deformable convolutional network (FeaCo-DCN) to perform interphase compensation in the latent feature space, which has not been explored by previous studies. In FeaCo-DCN, encoding networks extract features from each phase, and then, features of other phases are deformed to those of the target phase via deformable convolutional networks. Finally, a decoding network combines and decodes features from all phases to yield high-quality images of the target phase. The proposed FeaCo-DCN was evaluated using lung cancer patient data.Results(1) FeaCo-DCN generated high-quality images with accurate and clear structures for a fast 4D-CBCT scan; (2) 4D-CBCT images reconstructed by FeaCo-DCN achieved 3D tumor localization accuracy within 2.5 mm; (3) image reconstruction is nearly real time; and (4) FeaCo-DCN achieved superior performance by all metrics compared to the top-ranked techniques in the AAPM SPARE Challenge.ConclusionThe proposed FeaCo-DCN is effective and efficient in reconstructing 4D-CBCT while reducing about 90% of the scanning time, which can be highly valuable for moving target localization in image-guided radiotherapy.
Project description:Amongst patients with suspected obstructive coronary artery disease (CAD), less than a third of patients have obstructive disease on invasive coronary angiography (ICA) and fewer still have flow-limiting obstructive disease as determined by invasive fractional flow reserve (FFR). FFR is a powerful tool in guiding revascularization of flow-limiting lesions which in turn improves clinical outcome in those with haemodynamically significant obstructive disease. However FFR is infrequently performed due to the cost, time and patient discomfort the procedure entails. Further advances in non-invasive imaging has allowed FFR to be derived non-invasively by applying computational fluid dynamic (CFD) modeling to the coronary computed tomography angiography (CCTA) dataset without the need to induce hyperemia or modify the standard CCTA acquisition protocol. FFR derived from CCTA has been shown to have excellent correlation with invasive FFR and remains diagnostically robust in presence of reduced signal-to-noise ratio (SNR), coronary calcification and motion artifact. More recently, new data have emerged evaluating the clinical impact of fractional flow reserve computed tomography (FFRCT) on the assessment and management of patients with stable chest pain. One such study is the Prospective LongitudinAl trial of FFRCT: Outcome and Resource IMpacts (PLATFORM) study which showed an improved patient selection for ICA using CCTA-FFRCT approach by increasing the likelihood of identifying obstructive CAD at ICA amongst those intended for invasive testing. CCTA-FFRCT may therefore serve as efficacious gatekeeper to ICA that enriches the ICA population. The utility of FFRCT has also helped deepened our understanding of CAD. Through CFD modeling, it is now recognized that there are mechanistic forces of wall shear stress (WSS) and axial plaque force acting on coronary plaques. This has created further interest in exploring the possible interplay between these mechanistic forces on the development of coronary plaque and vulnerability of these plaques to rupture.
Project description:BackgroundTo study dose reduction using iterative reconstruction (IR) for pediatric great vessel stent computed tomography (CT).MethodsFive different great vessel stents were separately placed in a gel-containing plastic holder within an anthropomorphic chest phantom. The stent lumen was filled with diluted contrast gel. CT acquisitions were performed at routine dose, 52% and 81% reduced dose and reconstructed with filtered back projection (FBP) and IR. Objective image quality in terms of noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as subjective image quality were evaluated.ResultsNoise, SNR and CNR were improved with IR at routine and 52% reduced dose, compared to FBP at routine dose. The lowest dose level resulted in decreased objective image quality with both FBP and IR. Subjective image quality was excellent at all dose levels.ConclusionIR resulted in improved objective image quality at routine dose and 52% reduced dose, while objective image quality deteriorated at 81% reduced dose. Subjective image quality was not affected by dose reduction.
Project description:Background With the emergence of coronary computed tomography (CT) angiography, anomalous aortic origin of a coronary artery (ANOCOR) is more frequently diagnosed. Fractional flow reserve derived from CT (FFRCT) is a noninvasive functional test providing anatomical and functional evaluation of the overall coronary tree. These unique features of anatomical and functional evaluation derived from CT could help for the management of patients with ANOCOR. We aimed to retrospectively evaluate the physiological and clinical impact of FFRCT analysis in the ANOCOR registry population. Methods and Results The ANOCOR registry included patients with ANOCOR detected during invasive coronary angiography or coronary CT angiography between January 2010 and January 2013, with a planned 5-year follow-up. We retrospectively performed FFRCT analysis in patients with coronary CT angiography of adequate quality. Follow-up was performed with a clinical composite end point (cardiac death, myocardial infarction, and unplanned revascularization). We obtained successful FFRCT analyses and 5-year clinical follow-up in 54 patients (average age, 60±13 years). Thirty-eight (70%) patients had conservative treatment, and 16 (30%) patients had coronary revascularization after coronary CT angiography. The presence of an ANOCOR course was associated with a moderate reduction of FFRCT value from 1.0 at the ostium to 0.90±0.10 downstream the ectopic course and 0.82±0.11 distally. No significant difference in FFRCT values was identified between at-risk and not at-risk ANOCOR. After a 5-year follow-up, only one unplanned percutaneous revascularization was reported. Conclusions The presence of ANOCOR was associated with a moderate hemodynamic decrease of FFRCT values and associated with a low risk of cardiovascular events after a 5-year follow-up in this middle-aged population.
Project description:ObjectivesCoronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC.MethodsFully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1-10, 11-100, 101-400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers).ResultsOf 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman's r = 0.90, 95% confidence interval [CI] 0.89-0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98-0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland-Altman analysis demonstrated little difference (1.69, 95% limits of agreement: -41.22, 44.60) and there was almost excellent agreement (Cohen's κ = 0.90, 95% CI 0.88-0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan.ConclusionsThis artificial intelligence-based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation.Key points• Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)-based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis.
Project description:BackgroundLead exposure is a risk factor for increased blood pressure and cardiovascular disease, even when blood lead levels (BLLs) are within the normal range.ObjectiveThis study aimed to investigate the association between BLL and coronary artery stenosis (CAS) in asymptomatic adults using 128-slice dual-source coronary computed tomography (CT) angiography.MethodsWe analyzed medical records data from 2,193 adults (1,461 men and 732 women) who elected to complete a screening health examination, coronary CT angiography, and BLL measurement during 2011-2018 and had no history of CAS symptoms, cardiovascular disease, or occupational exposure to lead. Logistic regression models were used to estimate associations between moderate-to-severe CAS (≥25% stenosis) and a 1-μg/dL increase in blood lead, with and without adjustment for age, sex, hypertension, diabetes mellitus, dyslipidemia, body mass index, regular exercise, smoking status, and alcohol drinking.ResultsBLLs ranged from 0.12 to 10.14μg/dL, with an arithmetic mean of 2.71±1.26μg/dL. The arithmetic mean was higher for men than for women (2.98±1.26μg/dL vs. 2.18±1.08μg/dL, p<0.001) and higher in the moderate-to-severe CAS group than in the no-CAS or <25% stenosis group (3.02±1.44μg/dL vs. 2.67±1.23μg/dL, p<0.001). Moderate-to-severe CAS was significantly associated with BLL before and after adjustment, with an adjusted odds ratio for a 1-μg/dL increase in BLL of 1.14 (95% CI: 1.02, 1.26), p=0.017.ConclusionsBLL was positively associated with the prevalence of moderate-to-severe CAS in Korean adults who completed an elective screening examination for early cardiovascular disease, 94% of whom had a BLL of <5μg/dL. More efforts and a strict health policy are needed to further reduce BLLs in the general population. https://doi.org/10.1289/EHP7351.
Project description:The influence of newer-generation CT on the clinical indications and appropriateness of cardiac CT has not been adequately surveyed. We aimed to evaluate the distribution of appropriateness ratings and test the outcomes of cardiac CT using second-generation 320-row CT. The 2010 appropriate use criteria (AUC) were applied at the point of service to a consecutive series of patients (N = 309) who were referred for cardiac CT. The CT indication was determined based on interviews and medical records. The proportions of patients within the categories of appropriate (A), uncertain (U), inappropriate (I), and not covered were described. The prevalence of significant coronary artery disease (CAD) was also compared among the categories. The proportions were 49.2%, 25.9%, and 20.7% for appropriate, uncertain, and inappropriate indication, respectively. The indication that was not covered was only 4.2%. Significant CAD was more frequently observed for uncertain- than appropriate indication (42.5% vs 27.6%; P = 0.03), although the number of significant stenosed segments was not different (P = 0.13). The recent advancement of cardiac CT increased the proportion of uncertain scans, which were associated with a high prevalence of significant CAD.
Project description:ObjectivesCoronary CT angiography (CCTA) is becoming increasingly important in the workup of coronary artery disease. Imaging of stents and in-stent stenoses remains a challenge. This work investigates the assessability of in-stent stenoses in photon counting CT (PCCT) using ultra-high-resolution (UHR) imaging and optimized reconstruction kernels.MethodsIn an established phantom, 6 stents with inserted hypodense stenoses were scanned in both standard resolution (SRM) and UHR in a clinical PCCT scanner (NAEOTOM Alpha, Siemens Healthineers, Germany). Reconstructions were made both with the clinically established and optimized kernels. The visible stent lumen and the extent of stenosis were quantitatively measured and compared with the angiographic reference standard. Also, region-of-interest (ROI)-based measurements and a qualitative assessment of image quality were performed.ResultsThe visible stent lumen and the extent of stenosis were measured more precisely in UHR compared to SRM (0.11 ± 0.19 vs 0.41 ± 0.22 mm, P < .001). The optimized kernel further improved the accuracy of the measurements and image quality in UHR (0.35 ± 0.23 vs 0.47 ± 0.19 mm, P < .001). Compared to angiography, stenoses were overestimated in PCCT, on average with an absolute difference of 18.20% ± 4.11%.ConclusionsPhoton counting CCTA allows improved imaging of in-stent stenoses in a phantom using UHR imaging and optimized kernels. These results support the use of UHR and optimized kernels in clinical practice and further studies.Advances in knowledgeUHR imaging and optimized reconstruction kernels should be used in CCTA in the presence of cardiac stents.
Project description:Objective: We aimed to evaluate the visual measurements of coronary artery calcium (CAC) on nonelectrocardiogram (ECG)-gated chest computed tomography (CT) using a simple scoring method that involves counting the number of CT slices containing CAC. Materials and Methods: We analyzed 163 participants who underwent both coronary and chest CT examinations at six centers within 3 months. Agatston scores were calculated on standard ECG-gated scans and classified as none (0), mild (1-99), moderate (100-400), or severe (>400). Next, chest CT images were reconstructed to standard 5.0 mm axial slices. Then, CAC on chest CT scans was measured using two methods: the Weston score (sum of the assigned score of each vessel, range: 0-12) and number of slices showing CAC (Ca-slice#). Results: When the Weston score and Ca-slice# were divided into four levels according to the optimal divisional levels corresponding to the Agatston score classes, good agreements with the 4-grade Agatston score were observed (kappa value=0.610 and 0.794, respectively). The sensitivity and specificity of Ca-slice# ≥9 to identify severe Agatston scores of >400 were 86% and 96%, respectively. Conclusion: The Ca-slice#, a simple scoring method using chest CT scans, was in good agreement with the ECG-gated Agatston score.