Myocardial Coverage and Radiation Dose in Dynamic Myocardial Perfusion Imaging Using Third-Generation Dual-Source CT

Myocardial late enhancement using dual-source CT: intraindividual comparison of single-energy shuttle and dual-energy acquisition

OBJECTIVES

Myocardial computed tomography late enhancement (CT-LE) is a valuable modality used for the assessment of myocardial infarction and fibrosis and is effective in detecting latent cardiac amyloidosis. However, the optimal acquisition mode for CT-LE remains unknown. Here, we compared single-energy shuttle mode and DE mode for improving the quality of CT-LE imaging using dual-source CT.

METHODS

Fifteen patients with suspected or known ischemic heart disease underwent CT-LE imaging 5 min after coronary CT in both shuttle and dual-energy (DE) modes. In DE mode, virtual monoenergetic images at various keVs were reconstructed, and extracellular volume (ECV) was quantified using iodine-specific images. For shuttle mode, ECV was assessed by subtracting the volume from pre-contrast images from CT-LE after non-rigid registration.

RESULTS

In DE mode, signal-noise-to-ratio was the highest at 70 keV, but it was still lower than that in shuttle mode (p < 0.001). Contrast-noise-to-ratio was the highest on DE mode at 40 keV and was comparable with that in shuttle mode (p = 0.51). Interobserver agreement for infarct detection was higher in shuttle mode (kappa = 0.981) compared to DE mode (kappa = 0.808). Global ECV was comparable between shuttle and DE modes (p = 0.96). However, the coefficient of variation of segmental ECV was significantly lower in shuttle mode (p < 0.001).

CONCLUSION

Shuttle mode CT-LE demonstrates superior image quality, better agreement in infarct detection, and ECV consistency in comparison to DE mode, suggesting its potential as the preferred approach for CT-LE imaging using dual-source CT despite limited z-axis coverage of 10.5 cm.

CLINICAL RELEVANCE STATEMENT

CT late enhancement imaging in shuttle mode provides superior image quality and consistent extracellular volume measurements compared to dual-energy mode, highlighting its potential as the preferred acquisition method for CT late enhancement imaging in dual-source CT.

KEY POINTS

Shuttle mode and dual-energy acquisition are compared for optimal myocardial CT-late enhancement (CT-LE) imaging. Shuttle mode can provide better image quality and more consistent extracellular volume measurements. Despite limited coverage, shuttle mode may be preferred for myocardial CT-LE imaging.

Super-resolution deep learning reconstruction for improved quality of myocardial CT late enhancement

PURPOSE

Myocardial computed tomography (CT) late enhancement (LE) allows assessment of myocardial scarring. Super-resolution deep learning image reconstruction (SR-DLR) trained on data acquired from ultra-high-resolution CT may improve image quality for CT-LE. Therefore, this study investigated image noise and image quality with SR-DLR compared with conventional DLR (C-DLR) and hybrid iterative reconstruction (hybrid IR).

METHODS AND METHODS

We retrospectively analyzed 30 patients who underwent CT-LE using 320-row CT. The CT protocol comprised stress dynamic CT perfusion, coronary CT angiography, and CT-LE. CT-LE images were reconstructed using three different algorithms: SR-DLR, C-DLR, and hybrid IR. Image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and qualitative image quality scores are in terms of noise reduction, sharpness, visibility of scar and myocardial boarder, and overall image quality. Inter-observer differences in myocardial scar sizing in CT-LE by the three algorithms were also compared.

RESULTS

SR-DLR significantly decreased image noise by 35% compared to C-DLR (median 6.2 HU, interquartile range [IQR] 5.6-7.2 HU vs 9.6 HU, IQR 8.4-10.7 HU; p < 0.001) and by 37% compared to hybrid IR (9.8 HU, IQR 8.5-12.0 HU; p < 0.001). SNR and CNR of CT-LE reconstructed using SR-DLR were significantly higher than with C-DLR (both p < 0.001) and hybrid IR (both p < 0.05). All qualitative image quality scores were higher with SR-DLR than those with C-DLR and hybrid IR (all p < 0.001). The inter-observer differences in scar sizing were reduced with SR-DLR and C-DLR compared with hybrid IR (both p = 0.02).

CONCLUSION

SR-DLR reduces image noise and improves image quality of myocardial CT-LE compared with C-DLR and hybrid IR techniques and improves inter-observer reproducibility of scar sizing compared to hybrid IR. The SR-DLR approach has the potential to improve the assessment of myocardial scar by CT late enhancement.

State of the art of CT myocardial perfusion

Coronary computed tomography angiography (CCTA) is a powerful tool to rule out coronary artery disease (CAD). In the last decade, myocardial perfusion CT (CTP) technique has been developed for the evaluation of myocardial ischemia, thereby increasing positive predictive value for diagnosis of obstructive CAD. A diagnostic strategy combining CCTA and perfusion acquisitions provides both anatomical coronary evaluation and functional evaluation of the stenosis, increasing the specificity and the positive predictive value of cardiac CT. This could improve risk stratification and guide revascularization procedures, reducing unnecessary diagnostic procedures in invasive coronary angiography. Two different acquisitions protocol have been developed for CTP. Static CTP allows a qualitative or semiquantitative evaluation of myocardial perfusion using a single scan during the first pass of iodinated contrast material in the myocardium. Dynamic CTP is capable of a quantitative evaluation of perfusion through multiple acquisitions, providing direct measure of the myocardial blood flow. For both, CTP acquisition hyperemia is reached using stressor agents such as adenosine or regadenoson. CTP in addition to CCTA acquisition shows good diagnostic accuracy compared to invasive fractional flow reserve (FFR). Furthermore, the evaluation of late iodine enhancement (LIE) could be performed allowing the detection of myocardial infarction.

Dynamic CT-perfusion parameters as indicators of microcirculation: investigation in patients without obstructive coronary artery disease

AIM

To investigate the relationship between each CTP parameter and that between CTP parameters and patient characteristics in patients without obstructive coronary artery disease (CAD).

MATERIALS AND METHODS

Seventy-seven (28 female; 65.0±10.3 years) patients with suspected CAD who underwent coronary CT angiography (CCTA) and dynamic CTP with vasodilator stress were included. Patients with obstructive coronary stenosis (≥50%) on CCTA were excluded. Myocardial blood flow (MBF) and myocardial blood volume (MBV) were calculated using the slope and peak of the time-attenuation curves of the myocardium and blood. Perfused capillary blood volume (PCBV), extravascular extracellular volume (EEV), and flow extraction product (FE) were calculated using the extended Tofts model.

RESULTS

MBF, MBV, and PCBV were strongly correlated with each other (all r > 0.80 and all p < 0.001), whereas FE and EEV were strongly correlated with each other (r = 0.88 and p < 0.001). In univariate linear regression analysis, male sex and smoking status were significantly associated with MBF, MBV, and PCBV, while age was significantly associated with FE and EEV (all p < 0.05). In stepwise multivariate analysis, smoking status was independently associated with MBF, MBV. and PCBV, while age was the only factor associated with FE and EEV (all p < 0.05).

CONCLUSION

FE and EEV may reflect different mechanisms of microvascular dysfunction than MBF, MBV, and PCBV.

Automatic Osteoporosis Screening System Using Radiomics and Deep Learning from Low-Dose Chest CT Images

OBJECTIVE

Develop two fully automatic osteoporosis screening systems using deep learning (DL) and radiomics (Rad) techniques based on low-dose chest CT (LDCT) images and evaluate their diagnostic effectiveness.

METHODS

In total, 434 patients who underwent LDCT and bone mineral density (BMD) examination were retrospectively enrolled and divided into the development set (n = 333) and temporal validation set (n = 101). An automatic thoracic vertebra cancellous bone (TVCB) segmentation model was developed. The Dice similarity coefficient (DSC) was used to evaluate the segmentation performance. Furthermore, the three-class Rad and DL models were developed to distinguish osteoporosis, osteopenia, and normal bone mass. The diagnostic performance of these models was evaluated using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA).

RESULTS

The automatic segmentation model achieved excellent segmentation performance, with a mean DSC of 0.96 ± 0.02 in the temporal validation set. The Rad model was used to identify osteoporosis, osteopenia, and normal BMD in the temporal validation set, with respective area under the receiver operating characteristic curve (AUC) values of 0.943, 0.801, and 0.932. The DL model achieved higher AUC values of 0.983, 0.906, and 0.969 for the same categories in the same validation set. The Delong test affirmed that both models performed similarly in BMD assessment. However, the accuracy of the DL model is 81.2%, which is better than the 73.3% accuracy of the Rad model in the temporal validation set. Additionally, DCA indicated that the DL model provided a greater net benefit compared to the Rad model across the majority of the reasonable threshold probabilities Conclusions: The automated segmentation framework we developed can accurately segment cancellous bone on low-dose chest CT images. These predictive models, which are based on deep learning and radiomics, provided comparable diagnostic performance in automatic BMD assessment. Nevertheless, it is important to highlight that the DL model demonstrates higher accuracy and precision than the Rad model.

Automated identification of myocardial perfusion defects in dynamic cardiac computed tomography using deep learning

PURPOSE

The purpose of this study was to develop and evaluate deep convolutional neural network (CNN) models for quantifying myocardial blood flow (MBF) as well as for identifying myocardial perfusion defects in dynamic cardiac computed tomography (CT) images.

METHODS

Adenosine stress cardiac CT perfusion data acquired from 156 patients having or being suspected with coronary artery disease were considered for model development and validation. U-net-based deep CNN models were developed to segment the aorta and myocardium and to localize anatomical landmarks. Color-coded MBF maps were obtained in short-axis slices from the apex to the base level and were used to train a deep CNN classifier. Three binary classification models were built for the detection of perfusion defect in the left anterior descending artery (LAD), the right coronary artery (RCA), and the left circumflex artery (LCX) territories.

RESULTS

Mean Dice scores were 0.94 (±0.07) and 0.86 (±0.06) for the aorta and myocardial deep learning-based segmentations, respectively. With the localization U-net, mean distance errors were 3.5 (±3.5) mm and 3.8 (±2.4) mm for the basal and apical center points, respectively. The classification models identified perfusion defects with the accuracy of mean area under the receiver operating curve (AUROC) values of 0.959 (±0.023) for LAD, 0.949 (±0.016) for RCA, and 0.957 (±0.021) for LCX.

CONCLUSION

The presented method has the potential to fully automate the quantification of MBF and subsequently identify the main coronary artery territories with myocardial perfusion defects in dynamic cardiac CT perfusion.

Basis and current state of computed tomography perfusion imaging: a review

Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.

Dose Reduction of Dynamic Computed Tomography Myocardial Perfusion Imaging by Tube Voltage Change: Investigation in a Swine Model

Background

It is unclear whether tube voltage influences the measurement of perfusion parameters. The present study sought to evaluate the influence of tube voltage change on myocardial blood flow (MBF) measurements in dynamic computed tomography myocardial perfusion imaging (CTP).

Methods and Results

Seven swine [mean weight 55.8 kg ± 1.6 (standard deviation)] underwent rest and stress dynamic CTP with tube voltages of 100 and 70 kV. The image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), radiation dose and MBF value were compared. The 70 kV images had higher CT attenuation and higher image noise (27.9 ± 2.4 vs. 21.5 ± 1.9, P < 0.001) than the 100 kV images, resulting in a higher SNR (20.5 ± 1.6 vs. 15.6 ± 1.8, P < 0.001) and CNR (17.6 ± 1.5 vs. 12.4 ± 1.7, P < 0.001). Compared to the use of conventional 100 kV, 70 kV yielded an approximately 64.6% radiation dose reduction while generating comparable MBF values, both at rest (88.3 ± 14.9 ml/100 g/min vs. 85.6 ± 17.4 ml/100 g/min, P = 0.21) and stress (101.4 ± 21.5 ml/100 g/min vs. 99.6 ± 21.4 ml/100 g/min, P = 0.58) states.

Conclusion

Dynamic CTP using 70 kV instead of 100 kV does not substantially influence the MBF value but significantly reduces the radiation dose. Additional research is required to investigate the clinical significance of this change.

Dynamic Myocardial Perfusion CT for the Detection of Hemodynamically Significant Coronary Artery Disease

OBJECTIVES

In this international, multicenter study, using third-generation dual-source computed tomography (CT), we investigated the diagnostic performance of dynamic stress CT myocardial perfusion imaging (CT-MPI) in addition to coronary CT angiography (CTA) compared to invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR).

BACKGROUND

CT-MPI combined with coronary CTA integrates coronary artery anatomy with inducible myocardial ischemia, showing promising results for the diagnosis of hemodynamically significant coronary artery disease in single-center studies.

METHODS

At 9 centers in Europe, Japan, and the United States, 132 patients scheduled for ICA were enrolled; 114 patients successfully completed coronary CTA, adenosine-stress dynamic CT-MPI, and ICA. Invasive FFR was performed in vessels with 25% to 90% stenosis. Data were analyzed by independent core laboratories. For the primary analysis, for each coronary artery the presence of hemodynamically significant obstruction was interpreted by coronary CTA with CT-MPI compared to coronary CTA alone, using an FFR of ≤0.80 and angiographic severity as reference. Territorial absolute myocardial blood flow (MBF) and relative MBF were compared using C-statistics.

RESULTS

ICA and FFR identified hemodynamically significant stenoses in 74 of 289 coronary vessels (26%). Coronary CTA with ≥50% stenosis demonstrated a per-vessel sensitivity, specificity, and accuracy for the detection of hemodynamically significant stenosis of 96% (95% CI: 91%-100%), 72% (95% CI: 66%-78%), and 78% (95% CI: 73%-83%), respectively. Coronary CTA with CT-MPI showed a lower sensitivity (84%; 95% CI: 75%-92%) but higher specificity (89%; 95% CI: 85%-93%) and accuracy (88%; 95% CI: 84%-92%). The areas under the receiver-operating characteristic curve of absolute MBF and relative MBF were 0.79 (95% CI: 0.71-0.86) and 0.82 (95% CI: 0.74-0.88), respectively. The median dose-length product of CT-MPI and coronary CTA were 313 mGy·cm and 138 mGy·cm, respectively.

CONCLUSIONS

Dynamic CT-MPI offers incremental diagnostic value over coronary CTA alone for the identification of hemodynamically significant coronary artery disease. Generalized results from this multicenter study encourage broader consideration of dynamic CT-MPI in clinical practice. (Dynamic Stress Perfusion CT for Detection of Inducible Myocardial Ischemia [SPECIFIC]; NCT02810795).

Hyperemic myocardial blood flow in patients with atrial fibrillation before and after catheter ablation: A dynamic stress CT perfusion study

BACKGROUND

Atrial fibrillation (AF) patients without coronary artery stenosis often show clinical evidence of ischemia. However myocardial perfusion in AF patients has been poorly studied. The purposes of this study were to investigate altered hyperemic myocardial blood flow (MBF) in patients with AF compared with risk-matched controls in sinus rhythm (SR), and to evaluate hyperemic MBF before and after catheter ablation using dynamic CT perfusion.

METHODS

Hyperemic MBF was quantified in 87 patients with AF (44 paroxysmal, 43 persistent) scheduled for catheter ablation using dynamic CT perfusion, and compared with hyperemic MBF in 87 risk-matched controls in SR. Follow-up CT after ablation was performed in 49 AF patients.

RESULTS

Prior to ablation, hyperemic MBF of patients in AF during the CT (1.29 ± 0.34 ml/mg/min) was significantly lower than in patients in SR (1.49 ± 0.26 ml/g/min, p = 0.002) or matched controls (1.65 ± 0.32 ml/g/min, p < 0.001); no significant difference was seen between patients in SR during the CT and matched controls (vs. 1.50 ± 0.31 ml/g/min, p = 0.815). In patients in AF during the pre-ablation CT (n = 24), hyperemic MBF significantly increased after ablation from 1.30 ± 0.35 to 1.53 ± 0.17 ml/g/min (p = 0.004); whereas in patients in SR during the pre-ablation CT (n = 25), hyperemic MBF did not change significantly after ablation (from 1.46 ± 0.26 to 1.49 ± 0.27 ml/g/min, p = 0.499).

CONCLUSION

In the current study using stress perfusion CT, hyperemic MBF in patients with AF during pre-ablation CT was significantly lower than that in risk-matched controls, and improved significantly after restoration of SR by catheter ablation, indicating that MBF abnormalities in AF patients are caused primarily by AF itself.

Clinical Validation of the Accuracy of Absolute Myocardial Blood Flow Quantification with Dual-Source CT Using 15O-Water PET

PURPOSE

To determine the fitting equation that can correct for the underestimation of myocardial blood flow (MBF) measurement by using dynamic CT perfusion (CTP) with dual-source CT (MBFCT), using MBF with oxygen 15-labeled water (15O-water) PET (MBFPET) as a reference, and to determine the accuracy of corrected MBFCT (MBFCT-corrected) compared with MBFPET in a separate set of participants.

MATERIALS AND METHODS

In this prospective study (reference no. 2466), 34 participants (mean age, 70 years ± 8 [standard deviation]; 27 men) known or suspected to have coronary artery disease underwent dynamic stress CTP and stress 15O-water PET between January 2014 and December 2018. The participants were randomly assigned to either a pilot group (n = 17), to determine the fitting equation on the basis of the generalized Renkin-Crone model that can explain the relation between MBFCT and MBFPET, or to a validation group (n = 17), to validate MBFCT-corrected compared with MBFPET. The agreement between MBFCT-corrected and MBFPET was evaluated by intraclass correlation and Bland-Altman analysis.

RESULTS

In the pilot group, MBFCT was lower than MBFPET (1.24 mL/min/g ± 0.28 vs 2.51 mL/min/g ± 0.89, P < .001) at the segment level. The relationship between MBFCT and MBFCT-corrected was represented as MBFCT = MBFCT-corrected × {1-exp[-(0.11 × MBFCT-corrected + 1.54)/MBFCT-corrected]}. In the validation group, MBFCT-corrected was 2.66 mL/min/g ± 1.93, and MBFPET was 2.68 mL/min/g ± 1.87 at the vessel level. MBFCT-corrected showed an excellent agreement with MBFPET (intraclass correlation coefficient = 0.93 [95% CI: 0.87, 0.96]). The measurement bias of MBFCT-corrected and MBFPET was -0.02 mL/min/g ± 0.74.

CONCLUSION

Underestimation of MBF by CT was successfully corrected with a correction method that was based on contrast kinetics in the myocardium.Keywords: CT, CT-Perfusion, PET, Cardiac, Heart Supplemental material is available for this article. © RSNA, 2021.