Agreement of Fractional Flow Reserve Estimated by Computed Tomography With Invasively Measured Fractional Flow Reserve: A Systematic Review and Meta-Analysis

BACKGROUND

Fractional flow reserve (FFR) is the ratio of blood pressure measured distal to a stenosis and pressure proximal to a stenosis. FFR can be estimated noninvasively using computed tomography (CT) although the usefulness of this technique remains controversial. This meta-analysis evaluated the agreement of FFR estimated by CT (FFR-CT) with invasively measured FFR. The study also evaluated the diagnostic accuracy of FFR-CT, defined as the ability of FFR-CT to classify lesions as hemodynamically significant (invasive FFR ≤0.8) or insignificant (invasive FFR >0.8).

METHODS AND RESULTS

Forty-three studies reporting on 7291 blood vessels from 5236 patients were included. A moderate positive linear relationship between FFR-CT and invasively measured FFR was observed (Spearman correlation coefficient: 0.67). Agreement between the 2 measures increased as invasively measured FFR values approached 1. The overall diagnostic accuracy, sensitivity and specificity of FFR-CT were 82.2%, 80.9%, and 83.1%, respectively. Diagnostic accuracy of 90% could be demonstrated for FFR-CT values >0.90 and <0.49. The diagnostic accuracy of off-site tools was 79.4% and the diagnostic accuracy of on-site tools was 84.1%.

CONCLUSIONS

The agreement between FFR-CT and invasive FFR is moderate although agreement is highest in vessels with FFR-CT >0.9. Diagnostic accuracy varies widely with FFR-CT value but is above 90% for FFR-CT values >0.90 and <0.49. Furthermore, on-site and off-site tools have similar performance. Ultimately, FFR-CT may be a useful adjunct to CT coronary angiography as a gatekeeper for invasive coronary angiogram.

Cardiac Computed Tomography in Congenital Heart Disease

Computed tomography (CT) has emerged as a leading imaging modality in the evaluation of congenital heart disease (CHD). With ever-faster acquisition speed, decreasing radiation exposure, impeccable anatomic detail, optional functional data, and numerous post-processing tools, CT offers broad utility in CHD diagnosis, preoperative planning, and postoperative assessment. In this article, the far-reaching role of CT in CHD is reviewed, focusing on technical imaging considerations and key clinical applications.

Evaluation of stable angina by coronary computed tomographic angiography versus standard of care: A systematic review and meta-analysis

INTRODUCTION

There is limited data comparing Coronary Computed Tomography Angiography (CCTA) versus the usual Standard of care (SOC) in patients with suspected stable coronary artery disease (CAD). We aimed to perform a systematic review and meta-analysis to compare CCTA versus SOC in patients with stable CAD.

METHODS

We searched multiple databases for randomized controlled trials (RCTs) comparing CCTA with SOC, which included various functional testing approaches for evaluating stable CAD. We used a random-effects model to calculate risk ratios (RRs) with 95 % confidence intervals (CIs). Outcomes included all-cause mortality, myocardial infarction (MI), hospitalization for unstable angina (UA), invasive angiography, revascularization, percutaneous coronary intervention (PCI), and coronary artery bypass grafting (CABG).

RESULTS

We identified 6 RCTs with 19,881 patients with stable CAD, of which 9995 underwent CCTA, and 9886 underwent SOC. There were no significant differences between CCTA and SOC in terms of all-cause mortality (RR: 0.91; 95 % CI: 0.70-1.19; p = 0.50), MI (RR: 0.78; 95 % CI: 0.58-1.05; p = 0.11), hospitalizations for UA (RR: 1.20; 95 % CI: 0.95-1.51;p = 0.12), invasive angiography (RR: 0.71; 95 % CI: 0.32-1.61; p = 0.42), revascularization (RR:1.25; 95 % CI: 0.83-1.89; p = 0.29), PCI (RR: 1.20; 95 % CI: 0.78-1.85; p = 0.40), and CABG rates (RR: 0.89; 95 % CI: 0.530-1.49; p = 0.65).

CONCLUSION

In patients with stable CAD, CCTA is associated with similar outcomes compared to the usual Standard of care. Given its potential to quickly rule out severe obstructive disease, its ability to provide non-invasive physiology and identify non-obstructive CAD with plaque information makes it an attractive addition to the available armamentarium to evaluate chest pain.

Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment

Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.

CT Coronary Angiography: Technical Approach and Atherosclerotic Plaque Characterization

Coronary computed tomography angiography (CCTA) currently represents a robust imaging technique for the detection, quantification and characterization of coronary atherosclerosis. However, CCTA remains a challenging task requiring both high spatial and temporal resolution to provide motion-free images of the coronary arteries. Several CCTA features, such as low attenuation, positive remodeling, spotty calcification, napkin-ring and high pericoronary fat attenuation index have been proved as associated to high-risk plaques. This review aims to explore the role of CCTA in the characterization of high-risk atherosclerotic plaque and the recent advancements in CCTA technologies with a focus on radiomics plaque analysis.

A simplified coronary model for diagnosis of ischemia-causing coronary stenosis

BACKGROUND AND OBJECTIVE

The functional assessment of the severity of coronary stenosis from coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFR) has recently attracted interest. However, existing algorithms run at high computational cost. Therefore, this study proposes a fast calculation method of FFR for the diagnosis of ischemia-causing coronary stenosis.

METHODS

We combined CCTA and machine learning to develop a simplified single-vessel coronary model for rapid calculation of FFR. First, a zero-dimensional model of single-vessel coronary was established based on CCTA, and microcirculation resistance was determined through the relationship between coronary pressure and flow. In addition, a coronary stenosis model based on machine learning was introduced to determine stenosis resistance. Computational FFR (cFFR) was then obtained by combining the zero-dimensional model and the stenosis model with inlet boundary conditions for resting (cFFRr) and hyperemic (cFFRh) aortic pressure, respectively. We retrospectively analyzed 75 patients who underwent clinically invasive FFR (iFFR), and verified the model accuracy by comparison of cFFR with iFFR.

RESULTS

The average computing time of cFFR was less than 2 s. The correlations between cFFRr and cFFRh with iFFR were r = 0.89 (p < 0.001) and r = 0.90 (p < 0.001), respectively. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio for cFFRr and cFFRh were 90.7%, 95.0%, 89.1%, 76.0%, 98.0%, 8.7, 0.1 and 92.0%, 95.0%, 90.9%, 79.2%, 98.0%, 10.5, 0.1, respectively.

CONCLUSIONS

The proposed model enables rapid prediction of cFFR and exhibits high diagnostic performance in selected patient cohorts. The model thus provides an accurate and time-efficient computational tool to detect ischemia-causing stenosis and assist with clinical decision-making.

Fractional flow reserve measured via left internal mammary artery after coronary artery bypass grafting: Two case reports

BACKGROUND

The fractional flow reserve (FFR) has made the treatment of coronary heart disease more precise. However, there are few reports on the measurement of FFR via the left internal mammary artery (LIMA). Herein, we described the determination of further treatments by measuring FFR via the LIMA in 2 cases after coronary artery bypass grafting (CABG).

CASE SUMMARY

Case 1 was a 66-year-old male who was admitted due to “chest tightness after CABG.” The patient underwent CABG 7 years prior due to coronary heart disease. Coronary artery angiography showed complete occlusion of the left anterior descending artery (LAD), and subtotal occlusion of the third segment of the right coronary artery. On arterial angiography, there was 85% stenosis at the distal end of the anastomosis of the LIMA-LAD graft. FFR via LIMA was determined at 0.75. Thus, balloon dilation was performed in Case 1. FFR after balloon dilation was 0.94. Case 2 was a 60-year-old male who was admitted due to “chest tightness after CABG.” The patient underwent CABG 6 years prior due to coronary heart disease. There was 60% segmental stenosis in the middle segment of LAD and 75% anastomotic stenosis. FFR measured via LIMA was 0.83 (negative); thus the intervention was not performed. Case 2 was given drug treatments. At the 3-mo follow-up, there was no recurrence of chest tightness or shortness of breath in both cases. They are currently under continual follow-up.

CONCLUSION

We provided evidence that FFR measurement via grafted blood vessels, especially LIMA, after CABG is a good method to determine the intervention course.

Identification and validation of diagnostic biomarkers of coronary artery disease progression in type 1 diabetes via integrated computational and bioinformatics strategies

OBJECTIVE

Our study aimed to identify early peripheral blood diagnostic biomarkers and elucidate the immune mechanisms of coronary artery disease (CAD) progression in patients with type 1 diabetes mellitus (T1DM).

METHODS

Three transcriptome datasets were retrieved from the Gene Expression Omnibus (GEO) database. Gene modules associated with T1DM were selected with weighted gene co-expression network analysis. Differentially expressed genes (DEGs) between CAD and acute myocardial infarction (AMI) peripheral blood tissues were identified using limma. Candidate biomarkers were selected with functional enrichment analysis, node gene selection from a constructed protein-protein interaction (PPI) network, and 3 machine learning algorithms. Candidate expression was compared, and the receiver operating characteristic curve (ROC) and nomogram were constructed. Immune cell infiltration was assessed with the CIBERSORT algorithm.

RESULTS

A total of 1283 genes comprising 2 modules were detected as the most associated with T1DM. In addition, 451 DEGs related to CAD progression were identified. Among them, 182 were common to both diseases and mainly enriched in immune and inflammatory response regulation. The PPI network yielded 30 top node genes, and 6 were selected using the 3 machine learning algorithms. Upon validation, 4 genes (TLR2, CLEC4D, IL1R2, and NLRC4) were recognized as diagnostic biomarkers with the area under the curve (AUC) > 0.7. All 4 genes were positively correlated with neutrophils in patients with AMI.

CONCLUSION

We identified 4 peripheral blood biomarkers and provided a nomogram for early diagnosing CAD progression to AMI in patients with T1DM. The biomarkers were positively associated with neutrophils, indicating potential therapeutic targets.

Evaluation of the Advantages of Myocardial Blood Flow Index in the Diagnosis of Chronic Obstructive Coronary Artery Disease Versus Coronary Computed Tomography Angiography: A Feasibility Study

Background: There is a hidden relationship between the degree of coronary artery stenosis and downstream myocardial remodeling. The mutual influence in myocardial ischemia and myocardial remodeling provides an index for quantifying the myocardial blood flow based on the principles of physics. Objectives: This study aimed to evaluate the advantages of myocardial blood flow index (MBFI) in the diagnosis of chronic obstructive coronary artery disease (CAD). Patients and Methods: The data of 68 patients (39 males; mean age: 57.0 ± 10.20 years) with suspected CAD were analyzed retrospectively, including the imaging findings of coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) within one week. The MBFI was also calculated for the patients. After determining the optimal cut-off value based on ICA (stenosis ≥ 70%) as the gold standard test, the diagnostic performance of MBFI and CCTA was compared. The diagnostic accuracy was examined by the receiver operating characteristic (ROC) curve. For statistical analysis, chi-square test was performed to analyze influence data, and a P-value less than 0.05 was considered statistically significant. Results: In 68 cases evaluated in this study, the average scan dose of CCTA was 3.02 ± 1.15 mSv. There were 28 cases with stenosis ≥ 70%. The optimal cutoff value of MBFI and CCTA was 0.111 and 70%, respectively. Also, the area under the curve (AUC) for MBFI and CCTA was 0.857 and 0.621 (Z = 2.091, P = 0.0365), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value were 92.31%, 92.86%, 88.89%, and 95.12% for MBFI and 61.54%, 78.57%, 64.00%, and 76.74% for CCTA, respectively. The diagnostic accuracy was also estimated at 92.65% for MBFI and 72.06% for CCTA (χ2 = 9.844, P = 0.0017). Conclusion: In this study, MBFI performed better than CCTA in identifying lesions with stenosis ≥ 70%. A lower MBFI indicated the need for an upcoming active intervention, while a higher MBFI suggested avoiding unnecessary invasive testing.

Multi-modality cardiac imaging in the management of diabetic heart disease

Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease.

Evaluation of the Relationship between Left Coronary Artery Bifurcation Angle and Coronary Artery Disease: A Systematic Review

Recent studies have suggested a relationship between wide left coronary artery bifurcation (left anterior descending [LAD]-left circumflex [LCx]) angle and coronary artery disease (CAD). Current literature is multifaceted. Different studies have analysed this relationship using computational fluid dynamics, by considering CAD risk factors, and from simple causal-comparative and correlational perspectives. Hence, the purpose of this systematic review was to critically evaluate the current literature and determine whether there is sufficient evidence available to prove the relationship between LAD-LCx angle and CAD. Five electronic databases (ProQuest, Scopus, PubMed, CINAHL Plus with Full Text, and Emcare) were used to locate relevant texts, which were then screened according to predefined eligibility criteria. Thirteen eligible articles were selected for review. Current evidence suggests individuals with a wide LAD-LCx angle experience altered haemodynamics at the bifurcation site compared to those with narrower angles, which likely facilitates a predisposition to developing CAD. However, further research is required to determine causality regarding relationships between LAD-LCx angle and CAD risk factors. Insufficient valid evidence exists to support associations between LAD-LCx angle and degree of coronary stenosis, and future haemodynamic analyses should explore more accurate coronary artery modelling, as well as CAD progression in already stenosed bifurcations.

Change in Computed Tomography-Derived Fractional Flow Reserve Across the Lesion Improve the Diagnostic Performance of Functional Coronary Stenosis

Aims: This study sought to evaluate the diagnostic performance of change in computed tomography-derived fractional flow reserve (CT-FFR) across the lesion (ΔCT-FFR) for identifying ischemia lesions with FFR as the reference standard.

Methods: Patients who underwent coronary CT angiography (CCTA) and FFR measurement within 1 week from December 2018 to December 2019 were retrospectively enrolled. CT-FFR within 2 cm distal to the lesion, ΔCT-FFR and plaque characteristics were analyzed. The diagnostic accuracy of CCTA (coronary stenosis ≥ 50%), CT-FFR ≤ 0.80, and ΔCT-FFR ≥ 0.15 (based on the largest Youden index) were assessed with FFR as the reference standard. The relationship between plaque characteristics and ΔCT-FFR was analyzed.

Results: The specificity of ΔCT-FFR and CT-FFR were 70.8 and 67.4%, respectively, which were both higher than CCTA (39.3%) (both P &lt; 0.001), while there were no statistical significance in sensitivity among the three (84.5, 77.4, 88.1%, respectively; P = 0.08). The area under the curves (AUCs) of ΔCT-FFR and CT-FFR were 0.803 and 0.743, respectively, which were both higher than that of CCTA (0.637) (both P &lt; 0.05), and the AUC of ΔCT-FFR was higher than that of CT-FFR (P &lt; 0.001). Multivariable analysis showed that low-attenuation plaque (LAP) volume (odds ratio [OR], 1.006) and plaque length (OR, 1.021) were independently correlated with ΔCT-FFR (both P &lt; 0.05).

Conclusions: CT-FFR and ΔCT-FFR and here especially the ΔCT-FFR could improve the diagnostic performance of ischemia compared with CCTA alone. LAP volume and plaque length were the independent risk factors of ΔCT-FFR.

COVID-19 Imaging: What We Know Now and What Remains Unknown

Infection with SARS-CoV-2 ranges from an asymptomatic condition to a severe and sometimes fatal disease, with mortality most frequently being the result of acute lung injury. The role of imaging has evolved during the pandemic, with CT initially being an alternative and possibly superior testing method compared with reverse transcriptase-polymerase chain reaction (RT-PCR) testing and evolving to having a more limited role based on specific indications. Several classification and reporting schemes were developed for chest imaging early during the pandemic for patients suspected of having COVID-19 to aid in triage when the availability of RT-PCR testing was limited and its level of performance was unclear. Interobserver agreement for categories with findings typical of COVID-19 and those suggesting an alternative diagnosis is high across multiple studies. Furthermore, some studies looking at the extent of lung involvement on chest radiographs and CT images showed correlations with critical illness and a need for mechanical ventilation. In addition to pulmonary manifestations, cardiovascular complications such as thromboembolism and myocarditis have been ascribed to COVID-19, sometimes contributing to neurologic and abdominal manifestations. Finally, artificial intelligence has shown promise for use in determining both the diagnosis and prognosis of COVID-19 pneumonia with respect to both radiography and CT.

Coronary Assessment and Revascularization Before Transcutaneous Aortic Valve Implantation: An Update on Current Knowledge

Transcutaneous aortic valve implantation (TAVI) has led to a paradigm shift in the treatment of severe aortic stenosis (AS) in the elderly and is expanding to still younger and lower-risk patients with severe AS as an alternative to surgical aortic valve replacement (SAVR). While the role of coronary artery bypass grafting with SAVR is well-documented, the analog of percutaneous coronary intervention with TAVI is less so. The aim of this review is to provide an overview of the important challenges in treating severe AS and co-existing coronary artery disease in patients planned for TAVI.

Evaluation of patients with respiratory infections during the first pandemic wave in Germany: characteristics of COVID-19 versus non-COVID-19 patients

BACKGROUND

Characteristics of COVID-19 patients have mainly been reported within confirmed COVID-19 cohorts. By analyzing patients with respiratory infections in the emergency department during the first pandemic wave, we aim to assess differences in the characteristics of COVID-19 vs. Non-COVID-19 patients. This is particularly important regarding the second COVID-19 wave and the approaching influenza season.

METHODS

We prospectively included 219 patients with suspected COVID-19 who received radiological imaging and RT-PCR for SARS-CoV-2. Demographic, clinical and laboratory parameters as well as RT-PCR results were used for subgroup analysis. Imaging data were reassessed using the following scoring system: 0 - not typical, 1 - possible, 2 - highly suspicious for COVID-19.

RESULTS

COVID-19 was diagnosed in 72 (32,9%) patients. In three of them (4,2%) the initial RT-PCR was negative while initial CT scan revealed pneumonic findings. 111 (50,7%) patients, 61 of them (55,0%) COVID-19 positive, had evidence of pneumonia. Patients with COVID-19 pneumonia showed higher body temperature (37,7 ± 0,1 vs. 37,1 ± 0,1 °C; p = 0.0001) and LDH values (386,3 ± 27,1 vs. 310,4 ± 17,5 U/l; p = 0.012) as well as lower leukocytes (7,6 ± 0,5 vs. 10,1 ± 0,6G/l; p = 0.0003) than patients with other pneumonia. Among abnormal CT findings in COVID-19 patients, 57 (93,4%) were evaluated as highly suspicious or possible for COVID-19. In patients with negative RT-PCR and pneumonia, another third was evaluated as highly suspicious or possible for COVID-19 (14 out of 50; 28,0%). The sensitivity in the detection of patients requiring isolation was higher with initial chest CT than with initial RT-PCR (90,4% vs. 79,5%).

CONCLUSIONS

COVID-19 patients show typical clinical, laboratory and imaging parameters which enable a sensitive detection of patients who demand isolation measures due to COVID-19.

Renal ultrasound findings secondary to COVID-19 related collapsing focal segmental glomerulosclerosis - A case report

SARS-CoV-2 (COVID-19) is well known to have extrapulmonary manifestations, including acute renal failure. While radiologic findings of COVID-19 pulmonary-involvement have been described, renal findings associated with COVID-19 have not. We present a case of a 38-year-old Afro-Caribbean female diagnosed with COVID-19 whose renal ultrasound showed increased parenchymal echogenicity, decreased global color Doppler signal with elevated resistive indices, but no large vessel thrombi. Non-targeted renal biopsy demonstrated collapsing focal segmental glomerulosclerosis (FSGS), likely secondary to COVID-19 infection, which may be a specific manifestation of this disease that has been predominantly reported in Black patients. We report several findings on renal ultrasound with duplex Doppler not previously associated with COVID, specifically with FSGS, which in conjunction can be useful to both the radiologist and the clinician, potentially pointing them in the direction of this diagnosis and early treatment.

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Renal ultrasound provides benefit in cases of COVID-19 with acute kidney injury.

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Collapsing focal segmental glomerulosclerosis can occur secondary to COVID-19.

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This entity occurs nearly exclusively in Black patients.

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Ultrasound may show echogenic kidneys, elevated resistive index, altered perfusion.

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When these sonographic features are seen, clinicians should consider biopsy.

Quantitative Chest CT analysis in discriminating COVID-19 from non-COVID-19 patients

INTRODUCTION

COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients.

MATERIALS AND METHODS

From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p < 0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis.

RESULTS

Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66 ± 16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63 ± 15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55 ± 0.26L vs 0.43 ± 0.23L, p = 0.0005) and fibrotic alterations (0.05 ± 0.03 L vs 0.04 ± 0.03 L, p < 0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p < 0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p < 0.001), respectively.

CONCLUSIONS

Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.