Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets

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.

Photon-counting detector computed tomography in cardiac imaging

Photon-counting detector computed tomography (PCD-CT) has emerged as a revolutionary technology in CT imaging. PCD-CT offers significant advancements over conventional energy-integrating detector CT, including increased spatial resolution, artefact reduction and inherent spectral imaging capabilities. In cardiac imaging, PCD-CT can offer a more accurate assessment of coronary artery disease, plaque characterisation and the in-stent lumen. Additionally, it might improve the visualisation of myocardial fibrosis through qualitative late enhancement imaging and quantitative extracellular volume measurements. The use of PCD-CT in cardiac imaging holds significant potential, positioning itself as a valuable modality that could serve as a one-stop-shop by integrating both angiography and tissue characterisation into a single examination. Despite its potential, large-scale clinical trials, standardisation of protocols and cost-effectiveness considerations are required for its broader integration into clinical practice. This narrative review provides an overview of the current literature on PCD-CT regarding the possibilities and limitations of cardiac imaging.

Diagnostic performance of photon-counting detector CT for differentiation between adrenal adenomas and metastases

OBJECTIVES

Aim of this study was to assess the value of virtual non-contrast (VNC) reconstructions in differentiating between adrenal adenomas and metastases on a photon-counting detector CT (PCD-CT).

MATERIAL AND METHODS

Patients with adrenal masses and contrast-enhanced CT scans in portal venous phase were included. Image reconstructions were performed, including conventional VNC (VNCConv) and PureCalcium VNC (VNCPC), as well as virtual monochromatic images (VMI, 40-90 keV) and iodine maps. We analyzed images using semi-automatic segmentation of adrenal lesions and extracted quantitative data. Logistic regression models, non-parametric tests, Bland-Altman plots, and a random forest classifier were used for statistical analyses.

RESULTS

The final study cohort consisted of 90 patients (36 female, mean age 67.8 years [range 39-87]) with adrenal lesions (45 adenomas, 45 metastases). Compared to metastases, adrenal adenomas showed significantly lower CT-values in VNCConv and VNCPC (p = 0.007). Mean difference between VNC and true non-contrast (TNC) was 17.67 for VNCConv and 14.85 for VNCPC. Random forest classifier and logistic regression models both identified VNCConv and VNCPC as the best discriminators. When using 26 HU as the threshold in VNCConv reconstructions, adenomas could be discriminated from metastases with a sensitivity of 86.7% and a specificity of 75.6%.

CONCLUSION

VNC algorithms overestimate CT values compared to TNC in the assessment of adrenal lesions. However, they allow a reliable discrimination between adrenal adenomas and metastases and could be used in clinical routine in near future with an increased threshold (e.g., 26 HU). Further (multi-center) studies with larger patient cohorts and standardized protocols are required.

CLINICAL RELEVANCE STATEMENT

VNC reconstructions overestimate CT values compared to TNC. Using a different threshold (e.g., 26 HU compared to the established 10 HU), VNC has a high diagnostic accuracy for the discrimination between adrenal adenomas and metastases.

KEY POINTS

• Virtual non-contrast reconstructions may be promising tools to differentiate adrenal lesions and might save further diagnostic tests. • The conventional and a new calcium-preserving virtual non-contrast algorithm tend to systematically overestimate CT-values compared to true non-contrast images. • Therefore, increasing the established threshold for true non-contrast images (e.g., 10HU) may help to differentiate between adrenal adenomas and metastases on contrast-enhanced CT.

Cardiac computed tomography with late contrast enhancement: A review

Cardiac computed tomography (CCT) has assumed an increasingly significant role in the evaluation of coronary artery disease (CAD) during the past few decades, whereas cardiovascular magnetic resonance (CMR) remains the gold standard for myocardial tissue characterization. The discovery of late myocardial enhancement following intravenous contrast administration dates back to the 1970s with ex-vivo CT animal investigations; nevertheless, the clinical application of this phenomenon for cardiac tissue characterization became prevalent for CMR imaging far earlier than for CCT imaging. Recently the technical advances in CT scanners have made it possible to take advantage of late contrast enhancement (LCE) for tissue characterization in CCT exams. Moreover, the introduction of extracellular volume calculation (ECV) on cardiac CT images combined with the possibility of evaluating cardiac function in the same exam is making CCT imaging a multiparametric technique more and more similar to CMR. The aim of our review is to provide a comprehensive overview on the role of CCT with LCE in the evaluation of a wide range of cardiac conditions.

CT radiomic features reproducibility of virtual non-contrast series derived from photon-counting CCTA datasets using a novel calcium-preserving reconstruction algorithm compared with standard non-contrast series: focusing on epicardial adipose tissue

PURPOSE

We aimed to evaluate the reproducibility of computed tomography (CT) radiomic features (RFs) about Epicardial Adipose Tissue (EAT). The features derived from coronary photon-counting computed tomography (PCCT) angiography datasets using the PureCalcium (VNCPC) and conventional virtual non-contrast (VNCConv) algorithm were compared with true non-contrast (TNC) series.

METHODS

RFs of EAT from 52 patients who underwent PCCT were quantified using VNCPC, VNCConv, and TNC series. The agreement of EAT volume (EATV) and EAT density (EATD) was evaluated using Pearson's correlation coefficient and Bland-Altman analysis. A total of 1530 RFs were included. They are divided into 17 feature categories, each containing 90 RFs. The intraclass correlation coefficients (ICCs) and concordance correlation coefficients (CCCs) were calculated to assess the reproducibility of RFs. The cutoff value considered indicative of reproducible features was > 0.75.

RESULTS

the VNCPC and VNCConv tended to underestimate EATVs and overestimate EATDs. Both EATV and EATD of VNCPC series showed higher correlation and agreement with TNC than VNCConv series. All types of RFs from VNCPC series showed greater reproducibility than VNCConv series. Across all image filters, the Square filter exhibited the highest level of reproducibility (ICC = 67/90, 74.4%; CCC = 67/90, 74.4%). GLDM_GrayLevelNonUniformity feature had the highest reproducibility in the original image (ICC = 0.957, CCC = 0.958), exhibiting a high degree of reproducibility across all image filters.

CONCLUSION

The accuracy evaluation of EATV and EATD and the reproducibility of RFs from VNCPC series make it an excellent substitute for TNC series exceeding VNCConv series.

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.

Heart rate sensitivity of virtual non-contrast calcium scores derived from photon counting detector CT data: a phantom study

PURPOSE

To assess the reliability of virtual non-contrast (VNC) derived coronary artery calcium quantities in relation to heart rate and the VNC algorithm used compared to reference true non-contrast (TNC), considering several clinically established acquisition modes.

MATERIAL AND METHODS

An ad hoc built coronary phantom containing four calcified lesions and an iodinated lumen was scanned using three cardiac acquisition modes three times within an anthropomorphic cardiac motion phantom simulating different heart rates (0, 60, 80, 100 bpm) and reconstructed with a conventional (VNCconv) and a calcium-sensitive (VNCpc) VNC algorithm. TNC reference was scanned at 0 bpm with non-iodinated lumen. Calcium scores were assessed in terms of number of lesions detected, Agatston and volume scores and global noise was measured. Paired t-test and Wilcoxon test were performed to test measurements for significant difference.

RESULTS

For both VNC algorithms used, calcium levels or noise were not significantly affected by heart rate. Measurements on VNCpc reconstructions best reproduced TNC results, but with increased variability (Agatston scores at 0 bpm for TNC, VNCconv, and VNCpc were 47.1 ± 1.1, 6.7 ± 2.8 (p < 0.001), and 45.3 ± 7.6 (p > 0.05), respectively). VNC reconstructions showed lower noise levels compared to TNC, especially for VNCpc (noiseheart on TNC, VNCconv and VNCpc at 0 bpm was 5.0 ± 0.4, 4.5 ± 0.2, 4.2 ± 0.2).

CONCLUSION

No significant heart rate dependence of VNC-based calcium scores was observed in an intra-reconstruction comparison. VNCpc reproduces TNC scores better than VNCconv without significant differences and decreased noise, however, with an increasing average deviation with rising heart rates. VNC-based CACS should be used with caution as the measures show higher variability compared to reference TNC and therefore hold the potential of incorrect risk categorization.

Cardiac imaging with photon counting CT

CT of the heart, in particular ECG-controlled coronary CT angiography (cCTA), has become clinical routine due to rapid technical progress with ever new generations of CT equipment. Recently, CT scanners with photon-counting detectors (PCD) have been introduced which have the potential to address some of the remaining challenges for cardiac CT, such as limited spatial resolution and lack of high-quality spectral data. In this review article, we briefly discuss the technical principles of photon-counting detector CT, and we give an overview on how the improved spatial resolution of photon-counting detector CT and the routine availability of spectral data can benefit cardiac applications. We focus on coronary artery calcium scoring, cCTA, and on the evaluation of the myocardium.

Epicardial adipose tissue, metabolic disorders, and cardiovascular diseases: recent advances classified by research methodologies

Epicardial adipose tissue (EAT) is located between the myocardium and visceral pericardium. The unique anatomy and physiology of the EAT determines its great potential in locally influencing adjacent tissues such as the myocardium and coronary arteries. Classified by research methodologies, this study reviews the latest research progress on the role of EAT in cardiovascular diseases (CVDs), particularly in patients with metabolic disorders. Studies based on imaging techniques demonstrated that increased EAT amount in patients with metabolic disorders is associated with higher risk of CVDs and increased mortality. Then, in-depth profiling studies indicate that remodeled EAT may serve as a local mediator of the deleterious effects of cardiometabolic conditions and plays a crucial role in CVDs. Further, in vitro coculture studies provided preliminary evidence that the paracrine effect of remodeled EAT on adjacent cardiomyocytes can promote the occurrence and progression of CVDs. Considering the important role of EAT in CVDs, targeting EAT might be a potential strategy to reduce cardiovascular risks. Several interventions have been proved effective in reducing EAT amount. Our review provides valuable insights of the relationship between EAT, metabolic disorders, and CVDs, as well as an overview of the methodological constructs of EAT-related studies.

Multiphase photon counting detector CT data sets - Which combination of contrast phase and virtual non-contrast algorithm is best suited to replace true non-contrast series in the assessment of active bleeding?

PURPOSE

Aim of this study was to determine which virtual non-contrast (VNC) reconstruction algorithm, applied to which contrast phase of computed tomography angiography, best matches true non-contrast (TNC) images in the assessment of active bleeding.

METHOD

Patients who underwent a triphasic scan (pre-contrast, arterial, portal venous contrast) on a photon-counting detector CT (PCD-CT) (120 kV, image quality level 68) with suspected active (tumor, postoperative, spontaneous or other) bleeding were retrospectively included in this study. Conventional (VNCConv) and a calcium-preserving VNC algorithm (VNCPC) were derived from both arterial (art) and portal venous (pv) contrast scans, and analyzed quantitatively and qualitatively by two independent and blinded raters.

RESULTS

40 patients (22 female, mean age 76 years) were included. Measurements of CT values showed significant albeit small differences between TNC and VNC for most analyzed tissue regions without clear superiority of a VNC algorithm or contrast phase (e.g. ΔHU fat TNC to VNCPCpv 3.1 HU). However, qualitative analysis showed a preference to VNCPCpv in terms of image quality (on a 5-point Likert scale VNCConvart = 3.5 ± 0.8, VNCPCart = 3.7 ± 0.7, VNCConvpv = 3.7 ± 0.7, VNCPCpv = 3.8 ± 0.7) and residual calcium contrast (VNCConvart = 3.0 ± 0.8, VNCPCart = 3.5 ± 0.7, VNCConvpv = 3.6 ± 0.7, VNCPCpv = 3.9 ± 0.6).

CONCLUSIONS

When multiple post-contrast phases are available, VNCPC series based on portal venous phase are the most suitable replacement for an additional pre-contrast scan, with the prospect of a significant reduction in patient radiation dose.

Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers

Obesity is a modifiable cardiovascular risk factor, but adipose tissue (AT) depots in humans are anatomically, histologically, and functionally heterogeneous. For example, visceral AT is a pro-atherogenic secretory AT depot, while subcutaneous AT represents a more classical energy storage depot. Perivascular adipose tissue (PVAT) regulates vascular biology via paracrine cross-talk signals. In this position paper, the state-of-the-art knowledge of various AT depots is reviewed providing a consensus definition of PVAT around the coronary arteries, as the AT surrounding the artery up to a distance from its outer wall equal to the luminal diameter of the artery. Special focus is given to the interactions between PVAT and the vascular wall that render PVAT a potential therapeutic target in cardiovascular diseases. This Clinical Consensus Statement also discusses the role of PVAT as a clinically relevant source of diagnostic and prognostic biomarkers of vascular function, which may guide precision medicine in atherosclerosis, hypertension, heart failure, and other cardiovascular diseases. In this article, its role as a 'biosensor' of vascular inflammation is highlighted with description of recent imaging technologies that visualize PVAT in clinical practice, allowing non-invasive quantification of coronary inflammation and the related residual cardiovascular inflammatory risk, guiding deployment of therapeutic interventions. Finally, the current and future clinical applicability of artificial intelligence and machine learning technologies is reviewed that integrate PVAT information into prognostic models to provide clinically meaningful information in primary and secondary prevention.

Photon Counting CT: Technical Principles, Clinical Applications, and Future Prospects

Photon-counting computed tomography (PCCT) is a new technique that utilizes photon-counting detectors to convert individual X-ray photons directly into an electrical signal, which can achieve higher spatial resolution, improved iodine signal, radiation dose reduction, artifact reduction, and multienergy imaging. This review introduces the technical principles of PCCT, and summarizes its first-in-human experience and current applications in clinical settings, and discusses the future prospects of PCCT.

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.