Stress myocardial CT perfusion: an update and future perspective

Prevalence of low-attenuation plaques and statin therapy in plaque rupture type of acute coronary syndrome

BACKGROUND

We sought to investigate the differences in coronary plaque morphology on coronary computed tomography angiography (CCTA) and medical therapy between acute coronary syndrome (ACS) and stable ischemic heart disease (SIHD). We also explored the relationship between plaque morphology on CCTA at the initial phase and lesion morphology in the acute phase of ACS.

METHODS

In 5967 patients who underwent invasive coronary angiography, 58 ACS and 91 SIHD patients who had prior CCTA imaging of the culprit lesion and denied ischemic heart disease at CCTA scanning were enrolled.

RESULTS

Although the prevalence of positive remodeling was not different (P = 0.27), low-attenuation plaques (LAP) on prior CCTA were significantly higher in ACS than in SIHD (52% vs. 24%, P < 0.01). The frequency of coronary stenosis grading did not differ between the two groups (P = 0.14). In ACS patients, the frequencies of plaque rupture and lipid-rich plaque assessed by optical coherence tomography (OCT) were significantly higher in LAP than in non-LAP (73% vs. 23%, P < 0.01; 82% and 23%, P < 0.01). Multivariate regression analysis revealed that statin use and LAP on prior CCTA were predictors of future ACS events (P < 0.01, and P < 0.05, respectively).

CONCLUSIONS

LAP on CCTA, not positive arterial remodeling, and lack of statin therapy were associated with ACS development. In addition, LAP more frequently led to the development of the plaque rupture type of ACS compared with non-LAP. Lipid-lowering therapy with statins might be useful to prevent plaque rupture in patients with LAP regardless of coronary stenosis.

A Novel Quantitative Parameter for Static Myocardial Computed Tomography: Myocardial Perfusion Ratio to the Aorta

We evaluated the feasibility of myocardial perfusion ratio to the aorta (MPR) in static computed tomography perfusion (CTP) for detecting myocardial perfusion abnormalities assessed by single-photon emission computed tomography (SPECT). Twenty-five patients with suspected coronary artery disease who underwent dynamic CTP and SPECT were retrospectively evaluated. CTP images scanned at a sub-optimal phase for detecting myocardial perfusion abnormalities were selected from dynamic CTP images and used as static CTP images in the present study. The diagnostic accuracy of MPR derived from static CTP was compared to those of visual assessment and conventional quantitative parameters such as myocardial CT attenuation (HU) and transmural perfusion ratio (TPR). The area under the curve of MPR (0.84; 95% confidence interval [CI], 0.76−0.90) was significantly higher than those of myocardial CT attenuation (0.73; 95% CI, 0.65−0.79) and TPR (0.76; 95% CI, 0.67−0.83) (p < 0.05). Sensitivity and specificity were 67% (95% CI, 54−77%) and 90% (95% CI, 86−92%) for visual assessment, 51% (95% CI, 39−63%) and 86% (95% CI, 82−89%) for myocardial CT attenuation, 63% (95% CI, 51−74%) and 84% (95% CI, 80−88%) for TPR, and 78% (95% CI, 66−86%) and 84% (95% CI, 80−88%) for MPR, respectively. MPR showed higher diagnostic accuracy for detecting myocardial perfusion abnormality compared with myocardial CT attenuation and TPR.

Beyond Coronary CT Angiography: CT Fractional Flow Reserve and Perfusion

심장 전산화단층촬영은 비약적인 기술발전과 다양한 연구 결과를 바탕으로 심혈관위험 계층화와 치료 결정을 위한 관상동맥 질환의 진단과 예후 평가성능이 입증되었다. 전산화단층촬영 관상동맥조영술은 폐쇄성 관상동맥 질환에 대한 음성 예측도가 높아서 침습적 혈관조영술의 빈도를 줄일 수 있는 관상동맥 질환 관련 검사의 관문으로 부상했지만, 진단특이도가 상대적으로 낮다. 하지만 심장 전산화단층촬영을 이용한 분획혈류예비력과 심근관류를 분석하여 관상동맥 질환의 혈역학적 유의성을 확인하는 기능적 평가를 통해 그 한계를 극복할 수 있다. 최근에는 이를 보다 객관적이고 재현 가능하도록 인공지능을 접목하는 연구들이 활발히 진행되고 있다. 본 종설에서는 심장 전산화단층촬영의 기능적 영상화 기법들에 대해 알아보고자 한다.

Myocardial perfusion imaging using computed tomography: Current status, clinical value and prognostic implications

Combined anatomical and functional evaluation of coronary artery disease (CAD) using computed tomography (CT) has recently emerged as an accurate, robust, and non-invasive tool for the evaluation of ischemic heart disease. Cardiac CT has become a one-stop-shop imaging modality that allows the simultaneous depiction, characterization, and quantification of coronary atherosclerosis and the assessment of myocardial ischemia. Advancements in scanner technology (improvements in spatial and temporal resolution, dual-energy imaging, wide detector panels) and the implementation of iterative reconstruction algorithms enables the detection of myocardial ischemia in both qualitative and quantitative fashion using low-dose scanning protocols. The addition of CT perfusion (CTP) to standard coronary CT angiography is a reliable tool to improve diagnostic accuracy. CTP using static first-pass imaging enables qualitative assessment of the myocardial tissue, whereas dynamic perfusion imaging can also provide quantitative information on myocardial blood flow. Myocardial tissue assessment by CTP holds the potential to refine risk in stable chest pain or microvascular dysfunction. CTP can aid the detection of residual ischemia after coronary intervention. Comprehensive evaluation of CAD using CTP might therefore improve the selection of patients for aggressive secondary prevention therapy or coronary revascularization with high diagnostic certainty. In addition, prognostic information provided by perfusion CT imaging could improve patient outcomes by quantifying the ischemic burden of the left ventricle. The current review focuses on the clinical value of myocardial perfusion imaging by CT, current status of CTP imaging and the use of myocardial CTP in various patient populations for the diagnosis of ischemic heart disease.

Coronary Computer Tomography Angiography in 2021-Acquisition Protocols, Tips and Tricks and Heading beyond the Possible

Recent technological advances, together with an increasing body of evidence from randomized trials, have placed coronary computer tomography angiography (CCTA) in the center of the diagnostic workup of patients with coronary artery disease. The method was proven reliable in the diagnosis of relevant coronary artery stenosis. Furthermore, it can identify different stages of the atherosclerotic process, including early atherosclerotic changes of the coronary vessel wall, a quality not met by other non-invasive tests. In addition, newer computational software can measure the hemodynamic relevance (fractional flow reserve) of a certain stenosis. In addition, if required, information related to cardiac and valvular function can be provided with specific protocols. Importantly, recent trials have highlighted the prognostic relevance of CCTA in patients with coronary artery disease, which helped establishing CCTA as the first-line method for the diagnostic work-up of such patients in current guidelines. All this can be gathered in one relatively fast examination with minimal discomfort for the patient and, with newer machines, with very low radiation exposure. Herein, we provide an overview of the current technical aspects, indications, pitfalls, and new horizons with CCTA, providing examples from our own clinical practice.

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies

The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging plays an important role in diagnosis and management of cardiomyopathies and provides useful prognostic information. Most molecular factors exert their functions by interacting with other cellular components, thus many diseases reflect perturbations of intracellular networks. Indeed, complex diseases and traits such as cardiomyopathies are caused by perturbations of biological networks. The network medicine approach, by integrating systems biology, aims to identify pathological interacting genes and proteins, revolutionizing the way to know cardiomyopathies and shifting the understanding of their pathogenic phenomena from a reductionist to a holistic approach. In addition, artificial intelligence tools, applied to morphological and functional imaging, could allow imaging scans to be automatically analyzed to extract new parameters and features for cardiomyopathy evaluation. The aim of this review is to discuss the tools of network medicine in cardiomyopathies that could reveal new candidate genes and artificial intelligence imaging-based features with the aim to translate into clinical practice as diagnostic, prognostic, and predictive biomarkers and shed new light on the clinical setting of cardiomyopathies. The integration and elaboration of clinical habits, molecular big data, and imaging into machine learning models could provide better disease phenotyping, outcome prediction, and novel drug targets, thus opening a new scenario for the implementation of precision medicine for cardiomyopathies.

An 8-layer residual U-Net with deep supervision for segmentation of the left ventricle in cardiac CT angiography

BACKGROUND AND OBJECTIVES

Accurate segmentation of left ventricle (LV) is a fundamental step in evaluation of cardiac function. Cardiac CT angiography (CCTA) has become an important clinical diagnostic method for cardio-vascular disease (CVD) due to its non-invasive, short exam time, and low cost. To obtain the segmentation of the LV in CCTA scans, we present a deep learning method based on an 8-layer residual U-Net with deep supervision.

METHODS

Based on the original 4-layer U-Net, our method deepened the network to eight layers, which increased the fitting capacity of the network, thus greatly improved its LV recognition capability. Residual blocks were incorporated to optimize the network from the increased depth. Auxiliary paths as deep supervision were introduced to supervise the intermediate information to improve the segmentation quality. In this study, we collected CCTA scans of 100 patients. Eighty patients with 1600 discrete slices were used to train the LV segmentation and the remaining 20 patients with 400 discrete slices were used for testing our method. An interactive graph cut algorithm was utilized reliably to annotate the LV reference standard that was further confirmed by cardiologists. Online data augmentation was performed in the training process to improve the generalization and robustness of our method.

RESULTS

Compared with the segmentation results from the original U-Net and FC-DenseNet56 with Dice similarity coefficient (DSC) of 0.878±0.230 and 0.897±0.189, respectively, our method demonstrated higher segmentation accuracy and robustness for varying LV shape, size, and contrast, achieving DSC of 0.927±0.139. Without online data augmentation, our method resulted in inferior performance with DSC of 0.911±0.170. In addition, compared with the provided results from other existing studies in the LV segmentation of cardiac CT images, our method achieved a competitive performance for the LV segmentation.

CONCLUSIONS

The proposed 8-layer residual U-Net with deep supervision accurately and efficiently segments the LV in CCTA scans. This method has potential advantages to be a reliable segmentation method and useful for the evaluation of cardiac function in the future study.

[Computed tomography or cardiovascular magnetic resonance imaging for diagnosis of chronic coronary syndrome?]

BACKGROUND

Noninvasive imaging modalities are of central importance in the diagnosis of chronic coronary syndrome (CCS) in the current guidelines of the European Society of Cardiology (ESC), while the role of primary invasive coronary angiography in this context is increasingly being questioned. This review provides a summary of the most important diagnostic strategies from the radiology perspective.

METHODOLOGICAL ISSUE

The diagnostic algorithm is guided by the pretest probability (PTP) for the presence of CCS, which can be estimated based on age, sex, and symptoms. It is important to note that PTP in the current guidelines has decreased significantly compared to older recommendations and this change has an impact on the selection of the most appropriate imaging technique.

STANDARD RADIOLOGICAL METHODS

In patients with low PTP (>5% and <15%) and without prediagnosed coronary artery disease (CAD), CCS can be safely ruled out with inconspicuous computed tomography angiogram (CTA) of the coronary vessels. In patients with increased PTP (>15%) or prediagnosed CAD, noninvasive functional imaging should be primarily used to detect ischemia.

PERFORMANCE AND METHODICAL INNOVATIONS

The excellent sensitivity (89%), specificity (87%) and high prognostic relevance make stress perfusion cardiovascular magnetic resonance (CMR) imaging the functional method of first choice. Technical innovations and the use of artificial intelligence-based methods for image analysis could contribute to further improve its accuracy in the future.

PRACTICAL RECOMMENDATIONS

Radiologists should be aware of the recommendations of the current guidelines and work towards the establishment of coronary CTA and stress perfusion CMR in clinical routine.

[Possibilities of Stress Computed Tomography Myocardial Perfusion Imaging in the Diagnosis of Ischemic Heart Disease]

Computed tomography angiography (CT-angiography, CTA) allows noninvasive visualization of coronary arteries (CA). This method is highly sensitive in detecting coronary atherosclerosis. However, standard CTA does not allow evaluation of the hemodynamic significance of found CA stenoses, which requires additional functional tests for detection of myocardial ischemia. This review focuses on possibilities of clinical use, limitations, technical aspects, and prospects of a combination of CT-angiography and CT myocardial perfusion imaging in diagnostics of ischemic heart disease.

Validation of a novel cardiac motion correction algorithm for x-ray computed tomography: From phantom experiments to initial clinical experience

A novel cardiac motion correction algorithm has been introduced recently. Unlike other segmentation-based approaches it is fully automatic and capable of correcting motion artifacts of myocardial wall and other moving structures as well as coronary arteries of the heart. In addition, it requires raw data of only less than a single rotation for motion estimation and correction, which is a significant advantage from the perspective of x-ray exposure and workflow. The aim of this study is to explore the capability of the proposed method through phantoms and in-vivo experiments. Motion correction of coronary arteries and other heart structures including myocardial wall is the main focus of the evaluation. First, we provide a brief introduction to the concept of the motion correction algorithm. Next we address the procedure of our studies using an XCAT phantom and commercially available physical phantoms. Results of XCAT phantom demonstrate that our solution significantly improves the structural similarity of coronary arteries compared to FBP (proposed: 0.94, FBP: 0.77, p<0.001). Besides, it provides significantly lower root mean square error (proposed: 20.27, FBP: 25.33, p = 0.01) of the whole heart image. Mocomo phantom study shows that the proposed method improves the visualization of coronary arteries estimated based on motion score (1: worst, 5: best) from two experienced radiologists (proposed: 3.5, FBP: 2.1, p<0.001). The results of these phantom studies reveal that the proposed has a great potential in handling motion artifacts of other heart structures as well as coronary arteries. Finally, we provide the results of in-vivo animal and human studies. The 3D and 4D heart images show a consistently superior performance in the visualization of coronary arteries along with myocardial wall and other cardiothoracic structures. Based on these findings of our studies, we are of the opinion that our solution has a considerable potential to improve temporal resolution of cardiac CT imaging. This would open the door to innovations in structural or functional diagnosis of the heart.

Automatic segmentation and quantification of epicardial adipose tissue from coronary computed tomography angiography

Epicardial adipose tissue (EAT) is a visceral fat deposit, that's known for its association with factors, such as obesity, diabetes mellitus, age, and hypertension. Segmentation of the EAT in a fast and reproducible way is important for the interpretation of its role as an independent risk marker intricate. However, EAT has a variable distribution, and various diseases may affect the volume of the EAT, which can increase the complexity of the already time-consuming manual segmentation work. We propose a 3D deep attention U-Net method to automatically segment the EAT from coronary computed tomography angiography (CCTA). Five-fold cross-validation and hold-out experiments were used to evaluate the proposed method through a retrospective investigation of 200 patients. The automatically segmented EAT volume was compared with physician-approved clinical contours. Quantitative metrics used were the Dice similarity coefficient (DSC), sensitivity, specificity, Jaccard index (JAC), Hausdorff distance (HD), mean surface distance (MSD), residual mean square distance (RMSD), and the center of mass distance (CMD). For cross-validation, the median DSC, sensitivity, and specificity were 92.7%, 91.1%, and 95.1%, respectively, with JAC, HD, CMD, MSD, and RMSD are 82.9% ± 8.8%, 3.77 ± 1.86 mm, 1.98 ± 1.50 mm, 0.37 ± 0.24 mm, and 0.65 ± 0.37 mm, respectively. For the hold-out test, the accuracy of the proposed method remained high. We developed a novel deep learning-based approach for the automated segmentation of the EAT on CCTA images. We demonstrated the high accuracy of the proposed learning-based segmentation method through comparison with ground truth contour of 200 clinical patient cases using 8 quantitative metrics, Pearson correlation, and Bland-Altman analysis. Our automatic EAT segmentation results show the potential of the proposed method to be used in computer-aided diagnosis of coronary artery diseases (CADs) in clinical settings.

Computed tomographic evaluation of myocardial ischemia

Myocardial ischemia is caused by a mismatch between myocardial oxygen consumption and oxygen delivery in coronary artery disease (CAD). Stratification and decision-making based on ischemia improves the prognosis in patients with CAD. Non-invasive tests used to evaluate myocardial ischemia include stress electrocardiography, echocardiography, single-photon emission computed tomography, and magnetic resonance imaging. Invasive fractional flow reserve is considered the reference standard for assessment of the hemodynamic significance of CAD. Computed tomography (CT) angiography has emerged as a first-line imaging modality for evaluation of CAD, particularly in the population at low to intermediate risk, because of its high negative predictive value; however, CT angiography does not provide information on the hemodynamic significance of stenosis, which lowers its specificity. Emerging techniques, e.g., CT perfusion and CT-fractional flow reserve, help to address this limitation of CT, by determining the hemodynamic significance of coronary artery stenosis. CT perfusion involves acquisition during the first pass of contrast medium through the myocardium following pharmacological stress. CT-fractional flow reserve uses computational fluid dynamics to model coronary flow, pressure, and resistance. In this article, we review these two functional CT techniques in the evaluation of myocardial ischemia, including their principles, technology, advantages, limitations, pitfalls, and the current evidence.

Diagnostic accuracy of stress myocardial computed tomography perfusion imaging to detect myocardial ischemia: a comparison with coronary flow velocity reserve derived from transthoracic Doppler echocardiography

BACKGROUND

Our aim was to evaluate the ability of adenosine triphosphate (ATP)-stress myocardial computed tomography perfusion (CTP) imaging to detect myocardial ischemia in the left anterior descending artery (LAD) territory, and to compare this method with coronary flow velocity reserve (CFVR) measured by transthoracic Doppler echocardiography (TTDE).

METHODS

ATP-stress CTP and CFVR were performed in 50 patients with stable angina pectoris. Myocardial ischemia assessed from CTP imaging was defined as qualitative visual perfusion defects and reduced myocardial blood flow (MBF) based on quantitative assessment. A cut-off value of CFVR of 2.0 was used.

RESULTS

The mean CFVR was 1.9 ± 0.6 in ischemic regions by CTP, whereas it was 2.9 ± 0.8 in non-ischemic regions (p < 0.001). CTP imaging could accurately predict CFVR <2.0 with 84.0% diagnostic accuracy (94.7% sensitivity, 77.4% specificity, 72.0% positive predictive value, and 96.0% negative predictive value). When receiver operating characteristic curve analysis of the MBF data was performed to detect CFVR <2.0, the area under the curve was 0.89, and the optimal MBF cut-off value was 1.43 mL/g/min.

CONCLUSIONS

This study suggests that qualitative and quantitative assessment of ATP-stress CTP exhibits a good correlation with CFVR for evaluation of myocardial ischemia.

Diagnostic Accuracy of Perfusional Computed Tomography in Moderate Coronary Stenosis: Comparison With Fractional Flow Reserve

Coronary computed tomography with myocardial perfusion imaging (CCTA-MPI) provides data on coronary anatomy and perfusion and may be useful in the assessment of ischemic coronary artery disease (CAD). Management of angiographically intermediate coronary lesions is challenging, and coronary fractional flow reserve (FFR) evaluation is recommended to assess whether these lesions are functionally significant. Our aim was to evaluate the diagnostic accuracy of CCTA-MPI in patients with stable CAD and at least 1 angiographically intermediate coronary lesion submitted to FFR. In this single-center prospective study, patients with stable CAD and at least 1 moderate coronary stenosis (50%-70% by visual estimation) were referred for CCTA-MPI (64-row multidetector) assessment before coronary FFR evaluation. Patients with severe coronary obstructions (≥70%) were excluded. The significance level adopted for all tests was 5%. Twenty-eight patients (mean age 60 ± SD years, 54% women) with 33 intermediate coronary obstructions were enrolled. Ten patients (30%) had functionally significant coronary obstructions characterized by FFR ≤0.8. The sensitivity, specificity, and accuracy of CCTA-MPI for the detection of functionally significant coronary obstructions were 30%, 100%, and 78.8%, respectively. CCTA-MPI positive predictive value was 100%, whereas negative predictive value was 76.7%. Correlation coefficient between tests was 0.48 (P = 0.005). On a novel approach to evaluate intermediate coronary lesions, accuracy of CCTA-MPI was 78.8%. The positive predictive value of an abnormal CCTA-MPI on this population was 100%, suggesting that CCTA-MPI may have a role in the assessment of patients with anatomically identified intermediate coronary lesions.

Clinical Outcomes of Dynamic Computed Tomography Myocardial Perfusion Imaging Combined With Coronary Computed Tomography Angiography Versus Coronary Computed Tomography Angiography–Guided Strategy

Background:

Dynamic computed tomography (CT) myocardial perfusion imaging (MPI) provides quantitative myocardial blood flow for the precise assessment of myocardial ischemia. However, compared with coronary CT angiography (CCTA), whether this functional imaging modality can reduce invasive coronary angiography without revascularization remains unknown. We aimed to determine the clinical outcomes of a dynamic CT-MPI+CCTA-guided versus CCTA-guided strategy in patients with suspected coronary artery disease.

Methods:

Consecutive patients with intermediate pretest probability of coronary artery disease were prospectively enrolled and randomized to dynamic CT-MPI+CCTA-guided or CCTA-guided workup. The primary end point was the rate of invasive coronary angiography without revascularization within 3 months. The secondary end point was a composite of major adverse cardiac event at the 3-month, 6-month, and 1-year follow-up.

Results:

A total of 240 patients (mean age, 69.01±11.2 years; 173 men) were included. The total radiation dose and contrast media usage within 90 days were higher in the CT-MPI+CCTA group than in the CCTA group (10.3 versus 7.1 mSv, P =0.031; 134.5±40.6 versus 108.1±48.2 mL, P <0.0001). Compared with the CCTA-guided group, the CT-MPI+CCTA-guided group had significantly lower rates of invasive coronary angiography within 90 days (48.3% [58/120] versus 30.8% [37/120], P =0.006) and invasive coronary angiography without revascularization (50.0% [29/58] versus 10.8% [4/37], P <0.0001). There were no significant differences regarding the frequency of major adverse cardiac event between the 2 groups at the 3-month, 6-month, and 1-year follow-up.

Conclusions:

In patients with intermediate pretest probability of coronary artery disease, CT-MPI+CCTA-guided patient management may be preferred over the CCTA-guided strategy as an approach to reduce unnecessary invasive procedures.

Combination of Lesion Stenosis and Myocardial Supply Area Assessed by Coronary Computed Tomography Angiography for Prediction of Myocardial Ischemia

Recent clinical studies revealed that anatomical information assessed by coronary computed tomography angiography (CTA) may be used effectively to diagnose coronary artery disease (CAD). However, a physiological assessment, demonstrating myocardial ischemia, is required to justify a therapeutic strategy for CAD. This study aimed to investigate whether using CTA to assess myocardial supply area can improve the prediction of myocardial ischemia.We analyzed 201 vessels with moderate (luminal narrowing ≥ 50%, < 70%) and severe (luminal narrowing ≥ 70%, < 99%) stenosis on CTA from 174 patients, who were suspected of having stable angina and underwent measurement of fractional flow reserve (FFR). The myocardial area supplied by the coronary artery, distal to the stenosis, was evaluated with CTA, as reported previously (modified Alberta Provincial Project for Outcome Assessment in Coronary Heart score) and was classified into 3 groups (large, medium, and small).Both percentage area stenosis and myocardial supply area were significantly correlated with FFR (r = -0.46, P < 0.01, and r = -0.45, P < 0.01). Among patients who had coronary plaques, with moderate stenosis and a small myocardial supply area, only 3 of 42 lesions (7%) were identified as ischemic; deviation from the ischemic threshold (FFR = 0.80) was P < 0.01. The combined assessment of lesion stenosis and myocardial supply area, using CTA, improved the prediction of myocardial ischemia significantly compared to lesion stenosis alone (77% versus 59%, P < 0.01).Adding the assessment of myocardial supply area to standard CTA might help predict myocardial ischemia in patients with stable angina pectoris.

EIT monitors valid and robust regional ventilation distribution in pathologic ventilation states in porcine study using differential DualEnergy-CT (ΔDECT)

It is crucial to precisely monitor ventilation and correctly diagnose ventilation-related pathological states for averting lung collapse and lung failure in Intensive Care Unit (ICU) patients. Although Electrical Impedance Tomography (EIT) may deliver this information continuously and non-invasively at bedside, to date there are no studies that systematically compare EIT and Dual Energy CT (DECT) during inspiration and expiration (ΔDECT) regarding varying physiological and ICU-typical pathological conditions such as atelectasis. This study aims to prove the accuracy of EIT through quantitative identification and monitoring of pathological ventilation conditions on a four-quadrant basis using ΔDECT. In a cohort of 13 pigs, this study investigated systematic changes in tidal volume (TV) and positive end-expiratory pressure (PEEP) under physiological ventilation conditions. Pathological ventilation conditions were established experimentally by single-lung ventilation and pulmonary saline lavage. Spirometric data were compared to voxel-based entire lung ΔDECT, and EIT intensities were compared to ΔDECT of a 12-cm slab of the lung around the EIT belt, the so called ΔDECT_Belt. To validate ΔDECT data with spirometry, a Pearson’s correlation coefficient of 0.92 was found for 234 ventilation conditions. Comparing EIT intensity with ΔDECT_(Belt), the correlation r = 0.84 was found. Normalized cross-correlation function (NCCF) between scaled global impedance (EIT) waveforms and global volume ventilator curves was r = 0.99 ± 0.003. The EIT technique correctly identified the ventilated lung in all cases of single-lung ventilation. In the four-quadrant based evaluation, which assesses the difference between end-expiratory lung volume (ΔEELV) and the corresponding parameter in EIT, i.e. the end-expiratory lung impedance (ΔEELI), the Pearson’s correlation coefficient of 0.94 was found. The respective Pearson’s correlation coefficients implies good to excellent concurrence between global and regional EIT ventilation data validated by ventilator spirometry and DECT imaging. By providing real-time images of the lung, EIT is a promising, EIT is a promising, clinically robust tool for bedside assessment of regional ventilation distribution and changes of end-expiratory lung volume.

Hemodynamic impact of coronary stenosis using computed tomography: comparison between noninvasive fractional flow reserve and 3D fusion of coronary angiography with stress myocardial perfusion

Vasodilator-stress CT perfusion imaging in addition to CT coronary angiography (CTCA) may provide a single-test alternative to nuclear stress testing, commonly used to assess hemodynamic significance of stenosis. Another alternative is fractional flow reserve (FFR) calculated from cardiac CT images. We studied the concordance between these two approaches and their relationship to outcomes. We prospectively studied 150 patients with chest pain, who underwent CTCA and regadenoson CT. CTCA images were interpreted for presence and severity of stenosis. Fused 3D displays of subendocardial X-ray attenuation with coronary arteries were created to detect stress perfusion defects (SPD) in each coronary territory. In patients with stenosis > 25%, CT-FFR was quantified. Significant stenosis was determined by: (1) combination of stenosis > 50% with an SPD, (2) CT-FFR ≤ 0.80. Patients were followed-up for 36 ± 25 months for death, myocardial infarction or revascularization. After excluding patients with normal arteries and technical/quality issues, in final analysis of 76 patients, CTCA depicted stenosis > 70% in 13/224 arteries, 50-70% in 24, and < 50% in 187. CT-FFR ≤ 0.80 was found in 41/224 arteries, and combination of SPD with > 50% stenosis in 31/224 arteries. Inter-technique agreement was 89%. Despite high incidence of abnormal CT-FFR (30/76 patients), only 7 patients experienced adverse outcomes; 6/7 also had SPDs. Only 1/9 patients with CT-FFR ≤ 0.80 but normal perfusion had an event. Fusion of CTCA and stress perfusion can help determine the hemodynamic impact of stenosis in one test, in good agreement with CT-FFR. Adding stress CT perfusion analysis may help risk-stratify patients with abnormal CT-FFR.

Advances in cardiac CT contrast injection and acquisition protocols

Cardiac computed tomography (CT) imaging has become an important part of modern cardiovascular care. Coronary CT angiography (CTA) is the first choice imaging modality for non-invasive visualization of coronary artery stenosis. In addition, cardiac CT does not only provide anatomical evaluation, but also functional and valvular assessment, and myocardial perfusion evaluation. In this article we outline the factors which influence contrast enhancement, give an overview of current contrast injection and acquisition protocols, with focus on current emerging topics such as pre-transcatheter aortic valve replacement (TAVR) planning, cardiac CT for congenital heart disease (CHD) patients, and myocardial CT perfusion (CTP). Further, we point out areas where we see potential for future improvements in cardiac CT imaging based on a closer interaction between CT scanner settings and contrast injection protocols to tailor injections to patient- and exam-specific factors.

Computed tomography of cardiomyopathies

Cardiac computed tomography (CT) is increasingly used in the evaluation of cardiomyopathies, particularly in patients who are not able to undergo other non-invasive imaging tests such as magnetic resonance imaging (MRI) due to the presence of MRI-incompatible pacemakers/defibrillators or other contraindications or due to extensive artifacts from indwelling metallic devices. Advances in scanner technology enable acquisition of CT images with high spatial resolution, good temporal resolution, wide field of view and multi-planar reconstruction capabilities. CT is useful in cardiomyopathies in several ways, particularly in the evaluation of coronary arteries, characterization of cardiomyopathy phenotype, quantification of cardiac volumes and function, treatment-planning, and post-treatment evaluation. In this article, we review the imaging techniques and specific applications of CT in the evaluation of cardiomyopathies.

Myocardial blood flow quantification for evaluation of coronary artery disease by computed tomography

During the last decade coronary computed tomography angiography (CTA) has become the preeminent non-invasive imaging modality to detect coronary artery disease (CAD) with high accuracy. However, CTA has a limited value in assessing the hemodynamic significance of a given stenosis due to a modest specificity and positive predictive value. In recent years, different CT techniques for detecting myocardial ischemia have emerged, such as CT-derived fractional flow reserve (FFR-CT), transluminal attenuation gradient (TAG), and myocardial CT perfusion (CTP) imaging. Myocardial CTP imaging can be performed with a single static scan during first pass of the contrast agent, with monoenergetic or dual-energy acquisition, or as a dynamic, time-resolved scan during stress by using coronary vasodilator agents (adenosine, dipyridamole, or regadenoson). A number of CTP techniques are available, which can assess myocardial perfusion in both a qualitative, semi-quantitative or quantitative manner. Once used primarily as research tools, these modalities are increasingly being used in routine clinical practice. All these techniques offer the substantial advantage of combining anatomical and functional evaluation of flow-limiting coronary stenosis in the same examination that would be beneficial for clinical decision-making. This review focuses on the state-of the-art and future trends of these evolving imaging modalities in the field of cardiology for the physiologic assessments of CAD.

Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations

In clinical cardiology, both anatomy and physiology are needed to diagnose cardiac pathologies. CT imaging and computer simulations provide valuable and complementary data for this purpose. However, it remains challenging to gain useful information from the large amount of high-dimensional diverse data. The current tools are not adequately integrated to visualize anatomic and physiologic data from a complete yet focused perspective. We introduce a new computer-aided diagnosis framework, which allows for comprehensive modeling and visualization of cardiac anatomy and physiology from CT imaging data and computer simulations, with a primary focus on ischemic heart disease. The following visual information is presented: (1) Anatomy from CT imaging: geometric modeling and visualization of cardiac anatomy, including four heart chambers, left and right ventricular outflow tracts, and coronary arteries; (2) Function from CT imaging: motion modeling, strain calculation, and visualization of four heart chambers; (3) Physiology from CT imaging: quantification and visualization of myocardial perfusion and contextual integration with coronary artery anatomy; (4) Physiology from computer simulation: computation and visualization of hemodynamics (e.g., coronary blood velocity, pressure, shear stress, and fluid forces on the vessel wall). Substantially, feedback from cardiologists have confirmed the practical utility of integrating these features for the purpose of computer-aided diagnosis of ischemic heart disease.

Comparison of Coronary Computed Tomography Angiography-Derived vs Invasive Fractional Flow Reserve Assessment: Meta-Analysis with Subgroup Evaluation of Intermediate Stenosis

RATIONALE AND OBJECTIVES

Invasive coronary angiography (ICA) with fractional flow reserve (FFR) assessment is the reference standard for the detection of hemodynamically relevant coronary lesions. We have investigated whether coronary computed tomography angiography (cCTA)-derived FFR (fractional flow reserve from coronary computed tomographic angiography [CT-FFR]) measurement improves diagnostic accuracy over cCTA.

METHODS AND RESULTS

A literature search was performed for studies comparing invasive FFR, cCTA, and CT-FFR. The analysis included three prospective multicenter trials and two retrospective single-center studies; a total of 765 patients and 1306 vessels were included in the meta-analysis. Compared to invasive FFR on a per-lesion basis, CT-FFR reached a pooled sensitivity, specificity, positive predictive value, and negative predictive value of 83.7% (95% confidence interval [CI]: 78.1-89.3), 74.7% (95% CI: 52.2-97.1), 64.8% (95% CI: 52.1-77.5), and 90.1% (95% CI: 80.8-99.3) compared to 84.6% (95% CI: 78.1-91.1), 49.7% (95% CI: 31.1-68.4), 39.0% (95% CI: 28.0-50.1), and 87.3% (95% CI: 72.5-100.0) for cCTA alone. In 634 vessels with intermediate stenosis (30%-70%), sensitivity, specificity, positive predictive value, and negative predictive value were 81.4% (95% CI: 70.4-92.9), 71.7% (95% CI: 54.5-89.0), 59.4% (95% CI: 35.5-83.4), and 89.9% (95% CI: 85.0-94.7) compared to 90.2% (95% CI: 80.6-99.9), 35.4% (95% CI: 23.5-47.3), 50.7% (95% CI: 30.6-70.8), and 82.5% (95% CI: 64.5-100.0) for cCTA alone. The summary area under the receiver operating characteristic curve of CT-FFR was superior to cCTA alone on a per-vessel (0.90 [95% CI: 0.82-0.98] vs 0.74 [95% CI: 0.63-0.86]; P = .0047) and for intermediate stenoses (0.76 [95% CI: 0.65-0.88] vs 0.57 [95% CI: 0.49-0.66]; P = .0027).

CONCLUSION

CT-FFR significantly improves specificity without noticeably altering the sensitivity of cCTA with invasive FFR as a reference standard for the detection of hemodynamically relevant stenosis.

Patient-specific 17-segment myocardial modeling on a bull's eye map

The purpose of this study was to develop and validate cardiac computed tomog-raphy (CT) quantitative analysis software with a patient-specific, 17-segment myocardial model that uses electrocardiogram (ECG)-gated cardiac CT images to differentiate between normal controls and severe aortic stenosis (AS) patients. ECG-gated cardiac CT images from 35 normal controls and 144 AS patients were semiautomatically segmented to create a patient-specific, 17-segment myocardial model. Two experts then manually determined the anterior and posterior interven-tricular grooves to be boundaries between the 1st and 2nd segments and between the 3rd and 4th segments, respectively, to correct the model. Each segment was automatically identified as follows. The outer angle of two boundaries was divided to differentiate the 1st, 4th, 5th, and 6th segments in the basal plane, whereas the inner angle divided the 2nd and 3rd segments. The segments of the midplane were similarly divided. Segmental area distributions were quantitatively evaluated on the bull's-eye map on the basis of the morphological boundaries by measuring the area of each segment. Segmental areas of severe AS patients and normal controls were significantly different (t-test, all p-values < 0.011) in the proposed model because the septal regions of the severe AS patients were smaller than those of normal controls and the difference was enough to divide the two groups. The capabilities of the 2D segmental areas (p < 0.011) may be equivalent to those of 3D segmental analysis (all p-values < 0.001) for differentiating the two groups (t-test, all p-values < 0.001). The proposed method is superior to the conventional 17-segment in relation to reflection of patient-specific morphological variation and allows to obtain a more precise mapping between segments and the AHA recommended nomenclature. It can be used to differentiate severer AS patients and normal controls and also helps to understand the left ventricular morphology at a glance.

Noninvasive Imaging to Evaluate Women With Stable Ischemic Heart Disease

Declines in cardiovascular deaths have been dramatic for men but occur significantly less in women. Among patients with symptomatic ischemic heart disease (IHD), women experience relatively worse outcomes compared with their male counterparts. Evidence to date has failed to adequately explore unique female imaging targets and their correlative signs and symptoms of IHD as major determinants of IHD risk. We highlight sex-specific anatomic and functional differences in contemporary imaging and introduce imaging approaches that leverage refined targets that may improve IHD risk prediction and identify potential therapeutic strategies for symptomatic women.

Static and dynamic assessment of myocardial perfusion by computed tomography

Recent developments in computed tomography (CT) technology have fulfilled the prerequisites for the clinical application of myocardial CT perfusion (CTP) imaging. The evaluation of myocardial perfusion by CT can be achieved by static or dynamic scan acquisitions. Although both approaches have proved clinically feasible, substantial barriers need to be overcome before its routine clinical application. The current review provides an outline of the current status of CTP imaging and also focuses on disparities between static and dynamic CTPs for the evaluation of myocardial blood flow.

Stress Computed Tomography Myocardial Perfusion Imaging: A New Topic in Cardiology

Since its introduction about 15 years ago, coronary computed tomography angiography has become today the most accurate clinical instrument for noninvasive assessment of coronary atherosclerosis. Important technical developments have led to a continuous stream of new clinical applications together with a significant reduction in radiation dose exposure. Latest generation computed tomography scanners (≥ 64 slices) allow the possibility of performing static or dynamic perfusion imaging during stress by using coronary vasodilator agents (adenosine, dipyridamole, or regadenoson), combining both functional and anatomical information in the same examination. In this article, the emerging role and state-of-the-art of myocardial computed tomography perfusion imaging are reviewed and are illustrated by clinical cases from our experience with a second-generation dual-source 128-slice scanner (Somatom Definition Flash, Siemens; Erlangen, Germany). Technical aspects, data analysis, diagnostic accuracy, radiation dose and future prospects are reviewed.

Quantitative myocardial perfusion with stress dual-energy CT: iodine concentration differences between normal and ischemic or necrotic myocardium. Initial experience

OBJECTIVES

To determine whether the quantification of iodine with stress dual-energy computed tomography (DECT-S) allows for the discrimination between a normal and an ischemic or necrotic myocardium using magnetic resonance (MR) as a reference.

METHODS

This retrospective study was approved by the institutional review board, with waiver of informed consent. Thirty-six cardiac MR and DECT-S images from patients with suspected coronary artery disease were evaluated. Perfusion defects were visually determined, and myocardial iodine concentration was calculated by two observers using DECT colour-coded iodine maps. Iodine concentration differences were calculated using parametric tests. Receiver operating characteristic (ROC) curve analysis was conducted to estimate the optimal iodine concentration threshold for discriminating pathologic myocardium.

RESULTS

In total, 576 cardiac segments were evaluated. There were differences in mean iodine concentration (p < 0.001) between normal (2.56 ± 0.66 mg/mL), ischemic (1.98 ± 0.36 mg/dL) and infarcted segments (1.35 ± 0.57 mg/mL). A myocardium iodine concentration of 2.1 mg/mL represented the optimal threshold to discriminate between normal and pathologic myocardium (sensitivity 75 %, specificity 73.6 %, area under the curve 0.806). Excellent agreement was found in measured myocardium iodine concentration (intraclass correlation coefficient 0.814).

CONCLUSION

Cardiac DECT-S with iodine quantification may be useful to differentiate healthy and ischemic or necrotic myocardium.

KEY POINTS

• DECT-S allows for determination of myocardial iodine concentration as a quantitative perfusion parameter. • A high interobserver correlation exists in measuring myocardial iodine concentration with DECT-S. • Myocardial iodine concentration may be useful in the assessment of patients with CAD.

Dipyridamole stress myocardial perfusion by computed tomography in patients with left bundle branch block

Background

Functional tests have limited accuracy for identifying myocardial ischemia in patients with left bundle branch block (LBBB).

Objective

To assess the diagnostic accuracy of dipyridamole-stress myocardial computed tomography perfusion (CTP) by 320-detector CT in patients with LBBB using invasive quantitative coronary angiography (QCA) (stenosis ≥ 70%) as reference; to investigate the advantage of adding CTP to coronary computed tomography angiography (CTA) and compare the results with those of single photon emission computed tomography (SPECT) myocardial perfusion scintigraphy.

Methods

Thirty patients with LBBB who had undergone SPECT for the investigation of coronary artery disease were referred for stress tomography. Independent examiners performed per-patient and per-coronary territory assessments. All patients gave written informed consent to participate in the study that was approved by the institution’s ethics committee.

Results

The patients’ mean age was 62 ± 10 years. The mean dose of radiation for the tomography protocol was 9.3 ± 4.6 mSv. With regard to CTP, the per-patient values for sensitivity, specificity, positive and negative predictive values, and accuracy were 86%, 81%, 80%, 87%, and 83%, respectively (p = 0.001). The per-territory values were 63%, 86%, 65%, 84%, and 79%, respectively (p < 0.001). In both analyses, the addition of CTP to CTA achieved higher diagnostic accuracy for detecting myocardial ischemia than SPECT (p < 0.001).

Conclusion

The use of the stress tomography protocol is feasible and has good diagnostic accuracy for assessing myocardial ischemia in patients with LBBB.

Acute left circumflex coronary artery occlusion detected on nongated CT

We describe a patient with chest pain and a nondiagnostic electrocardiogram in whom computed tomographic (CT) aortography demonstrated myocardial hypoperfusion in the distribution of the circumflex artery as well as an abrupt cutoff of contrast in the left circumflex artery. Subsequent cardiac catheterization confirmed occlusion of the circumflex artery and led to revascularization. The diagnosis of acute myocardial infarction on CT can dramatically alter the clinical management of a patient, especially in cases in which other tests are equivocal.

Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest

Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for determination of the physiologic significance of the visualized stenoses. In this paper, we propose a new system to determine the physiologic manifestation of coronary stenoses by assessment of myocardial perfusion from typically acquired CTA images at rest. As a first step, we develop an automated segmentation method to delineate the left ventricle. Both endocardium and epicardium are compactly modeled with subdivision surfaces and coupled by explicit thickness representation. After initialization with five anatomical landmarks, the model is adapted to a target image by deformation increments including control vertex displacements and thickness variations guided by trained AdaBoost classifiers, and regularized by a prior of deformation increments from principal component analysis (PCA). The evaluation using a 5-fold cross-validation demonstrates the overall segmentation error to be 1.00 ± 0.39 mm for endocardium and 1.06 ± 0.43 mm for epicardium, with a boundary contour alignment error of 2.79 ± 0.52. Based on our LV model, two types of myocardial perfusion analyzes have been performed. One is a perfusion network analysis, which explores the correlation (as network edges) pattern of perfusion between all pairs of myocardial segments (as network nodes) defined in AHA 17-segment model. We find perfusion network display different patterns in the normal and disease groups, as divided by whether significant coronary stenosis is present in quantitative coronary angiography (QCA). The other analysis is a clinical validation assessment of the ability of the developed algorithm to predict whether a patient has significant coronary stenosis when referenced to an invasive QCA ground truth standard. By training three machine learning techniques using three features of normalized perfusion intensity, transmural perfusion ratio, and myocardial wall thickness, we demonstrate AdaBoost to be slightly better than Naive Bayes and Random Forest by the area under receiver operating characteristics (ROC) curve. For the AdaBoost algorithm, an optimal cut-point reveals an accuracy of 0.70, with sensitivity and specificity of 0.79 and 0.64, respectively. Our study shows perfusion analysis from CTA images acquired at rest is useful for providing physiologic information in diagnosis of obstructive coronary artery stenoses.