Synthetic Extracellular Volume Fraction Derived Using Virtual Unenhanced Attenuation of Blood on Dual-Energy Contrast-Enhanced Cardiac CT in Nonischemic Cardiomyopathy

Synthetic hematocrit from virtual non-contrast images for myocardial extracellular volume evaluation with photon-counting detector CT

OBJECTIVES

To assess the accuracy of a synthetic hematocrit derived from virtual non-contrast (VNC) and virtual non-iodine images (VNI) for myocardial extracellular volume (ECV) computation with photon-counting detector computed tomography (PCD-CT).

MATERIALS AND METHODS

Consecutive patients undergoing PCD-CT including a coronary CT angiography (CCTA) and a late enhancement (LE) scan and having a blood hematocrit were retrospectively included. In the first 75 patients (derivation cohort), CCTA and LE scans were reconstructed as VNI at 60, 70, and 80 keV and as VNC with quantum iterative reconstruction (QIR) strengths 2, 3, and 4. Blood pool attenuation (BPmean) was correlated to blood hematocrit. In the next 50 patients (validation cohort), synthetic hematocrit was calculated using BPmean. Myocardial ECV was computed using the synthetic hematocrit and compared with the ECV using the blood hematocrit as a reference.

RESULTS

In the derivation cohort (49 men, mean age 79 ± 8 years), a correlation between BPmean and blood hematocrit ranged from poor for VNI of CCTA at 80 keV, QIR2 (R2 = 0.12) to moderate for VNI of LE at 60 keV, QIR4; 70 keV, QIR3 and 4; and VNC of LE, QIR3 and 4 (all, R2 = 0.58). In the validation cohort (29 men, age 75 ± 14 years), synthetic hematocrit was calculated from VNC of the LE scan, QIR3. Median ECV was 26.9% (interquartile range (IQR), 25.5%, 28.8%) using the blood hematocrit and 26.8% (IQR, 25.4%, 29.7%) using synthetic hematocrit (VNC, QIR3; mean difference, -0.2%; limits of agreement, -2.4%, 2.0%; p = 0.33).

CONCLUSION

Synthetic hematocrit calculated from VNC images enables an accurate computation of myocardial ECV with PCD-CT.

CLINICAL RELEVANCE STATEMENT

Virtual non-contrast images from cardiac late enhancement scans with photon-counting detector CT allow the calculation of a synthetic hematocrit, which enables accurate computation of myocardial extracellular volume.

KEY POINTS

Blood hematocrit is mandatory for conventional myocardial extracellular volume computation. Synthetic hematocrit can be calculated from virtual non-iodine and non-contrast photon-counting detector CT images. Synthetic hematocrit from virtual non-contrast images enables computation of the myocardial extracellular volume.

Feasibility of the Threshold-Based Quantification of Myocardial Fibrosis on Cardiac CT as a Prognostic Marker in Nonischemic Dilated Cardiomyopathy

OBJECTIVE

This study investigated the feasibility and prognostic relevance of threshold-based quantification of myocardial delayed enhancement (MDE) on CT in patients with nonischemic dilated cardiomyopathy (NIDCM).

MATERIALS AND METHODS

Forty-three patients with NIDCM (59.3 ± 17.1 years; 21 male) were included in the study and underwent cardiac CT and MRI. MDE was quantified manually and with a threshold-based quantification method using cutoffs of 2, 3, and 4 standard deviations (SDs) on three sets of CT images (100 kVp, 120 kVp, and 70 keV). Interobserver agreement in MDE quantification was assessed using the intraclass correlation coefficient (ICC). Agreement between CT and MRI was evaluated using the Bland-Altman method and the concordance correlation coefficient (CCC). Patients were followed up for the subsequent occurrence of the primary composite outcome, including cardiac death, heart transplantation, heart failure hospitalization, or appropriate use of an implantable cardioverter-defibrillator. The Kaplan-Meier method was used to estimate event-free survival according to MDE levels.

RESULTS

Late gadolinium enhancement (LGE) was observed in 29 patients (67%, 29/43), and the mean LGE found with the 5-SD threshold was 4.1% ± 3.6%. The 4-SD threshold on 70-keV CT showed excellent interobserver agreement (ICC = 0.810) and the highest concordance with MRI (CCC = 0.803). This method also yielded the smallest bias with the narrowest range of 95% limits of agreement compared to MRI (bias, -0.119%; 95% limits of agreement, -4.216% to 3.978%). During a median follow-up of 1625 days (interquartile range, 712-1430 days), 10 patients (23%, 10/43) experienced the primary composite outcome. Event-free survival significantly differed between risk subgroups divided by the optimal MDE cutoff of 4.3% (log-rank P = 0.005).

CONCLUSION

The 4-SD threshold on 70-keV monochromatic CT yielded results comparable to those of MRI for quantifying MDE as a marker of myocardial fibrosis, which showed prognostic value in patients with NIDCM.

Spectral Photon-Counting Computed Tomography: Technical Principles and Applications in the Assessment of Cardiovascular Diseases

Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements' composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable.

Novel Techniques in Imaging Congenital Heart Disease: JACC Scientific Statement

Recent years have witnessed exponential growth in cardiac imaging technologies, allowing better visualization of complex cardiac anatomy and improved assessment of physiology. These advances have become increasingly important as more complex surgical and catheter-based procedures are evolving to address the needs of a growing congenital heart disease population. This state-of-the-art review presents advances in echocardiography, cardiac magnetic resonance, cardiac computed tomography, invasive angiography, 3-dimensional modeling, and digital twin technology. The paper also highlights the integration of artificial intelligence with imaging technology. While some techniques are in their infancy and need further refinement, others have found their way into clinical workflow at well-resourced centers. Studies to evaluate the clinical value and cost-effectiveness of these techniques are needed. For techniques that enhance the value of care for congenital heart disease patients, resources will need to be allocated for education and training to promote widespread implementation.

Prediction of pancreatic fibrosis by dual-energy CT-derived extracellular volume fraction: Comparison with MRI

OBJECTIVES

To investigate the correlation between dual-energy CT (DECT) and MRI measurements of the extracellular volume fraction (ECV) and to assess the accuracy of both methods in predicting pancreatic fibrosis (PF).

METHODS

We retrospectively analyzed 43 patients who underwent pancreatectomy and preoperative pancreatic DECT and MRI between November 2018 and May 2022. The ECV was calculated using the T1 relaxation time (for MR-ECV) or absolute enhancement (for DECT-ECV) at equilibrium phase (180 s after contrast injection in our study). Pearson coefficient and Bland-Altman analysis were used to compare the correlation between the two ECVs, Spearman correlations were used to investigate the association between imaging parameters and PF, Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the ECVs for advanced fibrosis (F2-F3), and multivariate logistic regression analysis was used to examine the relationship between PF and imaging parameters.

RESULTS

There was a strong correlation between DECT- and MR-derived ECVs (r = 0.948; p < 0.001). The two ECVs were positively correlated with PF (DECT: r = 0.647, p < 0.001; MR: r = 0.614, p < 0.001), and the mean values were 0.34 ± 0.08 (range: 0.22-0.62) and 0.35 ± 0.09 (range: 0.24-0.66), respectively. The area under the operating characteristic curve (AUC) for subjects with advanced fibrosis diagnosed by ECV was 0.86 for DECT-ECV and 0.87 for MR-ECV. Multivariate logistic regression analysis showed that the DECT-ECV was an independent predictor of PF.

CONCLUSIONS

The ECV could be an effective predictor of histological fibrosis, and DECT is equivalent to MRI for characterizing pancreatic ECV changes.

CT for the evaluation of myocardial extracellular volume with MRI as reference: a systematic review and meta-analysis

OBJECTIVE

Myocardial extracellular volume (ECV) fraction is an important imaging biomarker in clinical decision-making. CT-ECV is a potential alternative to MRI for ECV quantification. We conducted a meta-analysis to comprehensively assess the reliability of CT for ECV quantification with MRI as a reference.

METHODS

We systematically searched PubMed, EMBASE, and the Cochrane Library for relevant articles published since the establishment of the database in July 2022. The articles comparing CT-ECV with MRI as a reference were included. Meta-analytic methods were applied to determine the pooled weighted bias, limits of agreement (LOA), and correlation coefficient (r) between CT-ECV and MRI-ECV.

RESULTS

Seventeen studies with a total of 459 patients and 2231 myocardial segments were included. The pooled mean difference (MD), LOA, and r for ECV quantification at the per-patient level was (0.07%; 95% LOA: - 0.42 to 0.55%) and 0.89 (95% CI: 0.86-0.91), respectively, while on the per-segment level was (0.44%; 95% LOA: 0.16-0.72%) and 0.84 (95% CI: 0.82-0.85), respectively. The pooled r from studies with the ECViodine method for ECV quantification was significantly higher compared to those with the ECVsub method (0.94 (95% CI: 0.91-0.96) vs. 0.84 (95% CI: 0.80-0.88), respectively, p = 0.03). The pooled r from septal segments was significantly higher than those from non-septal segments (0.88 (95% CI: 0.86-0.90) vs. 0.76 (95% CI: 0.71-0.90), respectively, p = 0.009).

CONCLUSION

CT showed a good agreement and excellent correlation with MRI for ECV quantification and is a potentially attractive alternative to MRI.

CLINICAL RELEVANCE STATEMENT

The myocardial extracellular volume fraction can be acquired using a CT scan, which is not only a viable alternative to myocardial extracellular volume fraction derived from MRI but is also less time-consuming and costly for patients.

KEY POINTS

• Noninvasive CT-ECV is a viable alternative to MRI-ECV for ECV quantification. • CT-ECV using the ECViodine method showed more accurate myocardial ECV quantification than ECVsub. • Septal myocardial segments showed lower measurement variability than non-septal segments for the ECV quantification.

Cardiac Computed Tomography for Quantification of Myocardial Extracellular Volume Fraction: A Systematic Review and Meta-Analysis

BACKGROUND

Extracellular volume (ECV) is a quantitative measure of extracellular compartment expansion, and an increase in ECV is a marker of myocardial fibrosis. Although cardiac magnetic resonance (CMR) is considered the standard imaging tool for ECV quantification, cardiac computed tomography (CT) has also been used for ECV assessment.

OBJECTIVES

The aim of this meta-analysis was to evaluate the correlation and agreement in the quantification of myocardial ECV by CT and CMR.

METHODS

PubMed and Web of Science were searched for relevant publications reporting on the use of CT for ECV quantification compared with CMR as the reference standard. The authors employed a meta-analysis using the restricted maximum-likelihood estimator with a random-effects method to estimate summary correlation and mean difference. A subgroup analysis was performed to compare the correlation and mean differences between single-energy CT (SECT) and dual-energy CT (DECT) techniques for the ECV quantification.

RESULTS

Of 435 papers, 13 studies comprising 383 patients were identified. The mean age range was 57.3 to 82 years, and 65% of patients were male. Overall, there was an excellent correlation between CT-derived ECV and CMR-derived ECV (mean: 0.90 [95% CI: 0.86-0.95]). The pooled mean difference between CT and CMR was 0.96% (95% CI: 0.14%-1.78%). Seven studies reported correlation values using SECT, and 4 studies reported those using DECT. The pooled correlation from studies utilizing DECT for ECV quantification was significantly higher compared with those with SECT (mean: 0.94 [95% CI: 0.91-0.98] vs 0.87 [95% CI: 0.80-0.94], respectively; P = 0.01). There was no significant difference in pooled mean differences between SECT vs DECT (P = 0.85).

CONCLUSIONS

CT-derived ECV showed an excellent correlation and mean difference of <1% with CMR-derived ECV. However, the overall quality of the included studies was low, and larger, prospective studies are needed to examine the accuracy and diagnostic and prognostic utility of CT-derived ECV.

Cardiac CT in CRT as a Singular Imaging Modality for Diagnosis and Patient-Tailored Management

Between 30-40% of patients with cardiac resynchronization therapy (CRT) do not show an improvement in left ventricular (LV) function. It is generally known that patient selection, LV lead implantation location, and device timing optimization are the three main factors that determine CRT response. Research has shown that image-guided CRT placement, which takes into account both anatomical and functional cardiac properties, positively affects the CRT response rate. In current clinical practice, a multimodality imaging approach comprised of echocardiography, cardiac magnetic resonance imaging, or nuclear medicine imaging is used to capture these features. However, with cardiac computed tomography (CT), one has an all-in-one acquisition method for both patient selection and the division of a patient-tailored, image-guided CRT placement strategy. This review discusses the applicability of CT in CRT patient identification, selection, and guided placement, offering insights into potential advancements in optimizing CRT outcomes.

Myocardial extracellular volume quantification with computed tomography-current status and future outlook

Non-invasive quantification of the extracellular volume (ECV) is a method for the evaluation of focal and diffuse myocardial fibrosis, potentially obviating the need for invasive endomyocardial biopsy. While ECV quantification with cardiac magnetic resonance imaging (ECVMRI) is already an established method, ECV quantification with CT (ECVCT) is an attractive alternative to ECVMRI, similarly using the properties of extracellular contrast media for ECV calculation. In contrast to ECVMRI, ECVCT provides a more widely available, cheaper and faster tool for ECV quantification and allows for ECV calculation also in patients with contraindications for MRI. Many studies have already shown a high correlation between ECVCT and ECVMRI and accumulating evidence suggests a prognostic value of ECVCT quantification in various cardiovascular diseases. Adding a late enhancement scan (for dual energy acquisitions) or a non-enhanced and late enhancement scan (for single-energy acquisitions) to a conventional coronary CT angiography scan improves risk stratification, requiring only minor adaptations of the contrast media and data acquisition protocols and adding only little radiation dose to the entire scan.Critical relevance statementThis article summarizes the technical principles of myocardial extracellular volume (ECV) quantification with CT, reviews the literature comparing ECVCT with ECVMRI and histopathology, and reviews the prognostic value of myocardial ECV quantification for various cardiovascular disease.Key points• Non-invasive quantification of myocardial fibrosis can be performed with CT.• Myocardial ECV quantification with CT is an alternative in patients non-eligible for MRI.• Myocardial ECV quantification with CT strongly correlates with ECV quantification using MRI.• Myocardial ECV quantification provides incremental prognostic information for various pathologies affecting the heart (e.g., cardiac amyloidosis).

Cardiovascular Applications of Photon-Counting CT Technology: A Revolutionary New Diagnostic Step

Photon-counting computed tomography (PCCT) is an emerging technology that can potentially transform clinical CT imaging. After a brief description of the PCCT technology, this review summarizes its main advantages over conventional CT: improved spatial resolution, improved signal and contrast behavior, reduced electronic noise and artifacts, decreased radiation dose, and multi-energy capability with improved material discrimination. Moreover, by providing an overview of the existing literature, this review highlights how the PCCT benefits have been harnessed to enhance and broaden the diagnostic capabilities of CT for cardiovascular applications, including the detection of coronary artery calcifications, evaluation of coronary plaque extent and composition, evaluation of coronary stents, and assessment of myocardial tissue characteristics and perfusion.

Detection of Low Blood Hemoglobin Levels on Pulmonary CT Angiography: A Feasibility Study Combining Dual-Energy CT and Machine Learning

OBJECTIVES

To evaluate if dual-energy CT (DECT) pulmonary angiography (CTPA) can detect anemia with the aid of machine learning.

METHODS

Inclusion of 100 patients (mean age ± SD, 51.3 ± 14.8 years; male-to-female ratio, 42/58) who underwent DECT CTPA and hemoglobin (Hb) analysis within 24 h, including 50 cases with Hb below and 50 controls with Hb ≥ 12 g/dL. Blood pool attenuation was assessed on virtual noncontrast (VNC) images at eight locations. A classification model using extreme gradient-boosted trees was developed on a training set (n = 76) for differentiating cases from controls. The best model was evaluated in a separate test set (n = 24).

RESULTS

Blood pool attenuation was significantly lower in cases than controls (p-values < 0.01), except in the right atrium (p = 0.06). The machine learning model had sensitivity, specificity, and accuracy of 83%, 92%, and 88%, respectively. Measurements at the descending aorta had the highest relative importance among all features; a threshold of 43 HU yielded sensitivity, specificity, and accuracy of 68%, 76%, and 72%, respectively.

CONCLUSION

VNC imaging and machine learning shows good diagnostic performance for detecting anemia on DECT CTPA.