Research paper
Automatic quantification of the myocardial extracellular volume by cardiac computed tomography: Synthetic ECV by CCT

https://doi.org/10.1016/j.jcct.2017.02.006Get rights and content

Abstract

Background

The quantification of extracellular volume fraction (ECV) by Cardiac Computed Tomography (CCT) can identify changes in the myocardial interstitium due to fibrosis or infiltration. Current methodologies require laboratory blood hematocrit (Hct) measurement – which complicates the technique. The attenuation of blood (HUblood) is known to change with anemia. We hypothesized that the relationship between Hct and HUblood could be calibrated to rapidly generate a synthetic ECV without formally measuring Hct.

Methods

The association between Hct and HUblood was derived from forty non-contrast thoracic CT scans using regression analysis. Synthetic Hct was then used to calculate synthetic ECV, and in turn compared with ECV using blood Hct in a validation cohort with mild interstitial expansion due to fibrosis (aortic stenosis, n = 28, ECVCT = 28 ± 4%) and severe interstitial expansion due to amyloidosis (n = 27; ECVCT = 54 ± 11%, p < 0.001). For histological validation, synthetic ECV was correlated with collagen volume fraction (CVF) in a separate cohort with aortic stenosis (n = 18). All CT scans were performed at 120 kV and 160 mAs.

Results

HUblood was a good predictor of Hct (R2 = 0.47; p < 0.01), with the regression model (Hct = [0.51 * HUblood] + 17.4) describing the association. Synthetic ECV correlated well with conventional ECV (R2 = 0.96; p < 0.01) with minimal bias and 2SD difference of 5.7%. Synthetic ECV correlated as well as conventional ECV with histological CVF (both R2 = 0.50, p < 0.01). Finally, we implemented an automatic ECV plug-in for offline analysis.

Conclusion

Synthetic ECV by CCT provides instantaneous quantification of the myocardial extracellular space without the need for blood sampling.

Introduction

Extracellular volume fraction (ECV) quantification by cardiac computed tomography (CCT)1, 2, 3, 4, 5 and cardiovascular magnetic resonance (CMR)6, 7 is a promising new imaging biomarker for interstitial expansion due to myocardial fibrosis and cardiac amyloid deposition. Emerging data suggests ECV predicts outcome as well as left ventricular ejection fraction8, 9 and there is increasing interest in targeting the interstitium during the development of heart failure therapy.10 Current methodologies for ECV quantification require blood hematocrit (Hct) measurement, which adds a layer of complexity and is potentially a barrier to easy clinical implementation. Alternatively, for CMR, we recently proposed a synthetic ECV technique, removing the need for Hct measurement by utilizing the relationship between relaxivity of blood and lab measured Hct.11 It is unknown if a similar approach can be used for CCT, although a relationship between anemia and unenhanced blood attenuation has been observed;12, 13, 14, 15, 16, 17 for example the “aortic ring sign” and “dense intra-ventricular septum“ on unenhanced thoracic CTs suggest underlying anemia.17, 18, 19 We hypothesized that the relationship between Hct and unenhanced blood attenuation (HUblood) could be used to estimate a synthetic Hct, permitting immediate synthetic ECV calculation without blood sampling. We used existing patient cohorts1, 4 to investigate how synthetic ECV (a) compares to conventional ECV, and (b) correlates with the histological reference standard collagen volume fraction. We also implemented an automated synthetic ECV measurement plug-in within the open-source DICOM viewer OsiriX.20

Section snippets

Material and methods

This study is a retrospective analysis of prospectively acquired data, received local ethical approval and conformed to the principles of the Helsinki Declaration. The study received no industry support. All participants provided informed and written consent. Exclusion criteria were uncontrolled arrhythmia or impaired renal function (estimated glomerular filtration rate <45 mL/min). Prior to the scan, following insertion of an intravenous cannula, a 2-mL blood sample was collected and sent for

Step 1. Derivation cohort

40 thoracic CT scans with contemporaneous Hct samples within 20 days (mean 8 ± 7 days) of the scan were included (n = 40, 53% male, age 60 ± 20 years) with a broad range of Hct (mean 38.2 ± 6.0%; range 24.7–50.7%) and HUblood (mean 40 ± 8; range 20–55). The linear regression equation was: (sHct = [0.51 * HUblood] + 17.4) with R2 = 0.47 p < 0.001 (Fig. 1).

Step 2. Creation of the synthetic ECV equation

Blood hematocrit was substituted by the derived synthetic Hct to derive a synthetic ECV: Synthetic ECV = (1 – ([0.51 * HUblood] + 17.4)) × (ΔHU

Discussion

Identifying interstitial heart disease is important for diagnosis and prognosis,10 and myocardial extracellular volume fraction (ECV) can be measured non-invasively by CCT.1, 2, 3, 4 However, its measurement is complicated by the necessity for venous blood sampling, image analysis and then offline ECV calculation. This process is cumbersome and a major obstacle for implementing this technique into routine clinical practice. In this manuscript, we simplify the technique by calculating ECV

Conclusion

Synthetic hematocrit derived from the relationship between blood hematocrit and blood attenuation allows quantification of the myocardial extracellular volume fraction by cardiac computed tomography without the need for blood sampling. ECV shows great potential, allowing myocardial tissue characterization with negligible effect on workflow and radiation dose. However wider adoption requires simplification and automation of the established technique – synthetic ECV offers this.

Conflict of interest

No conflict of interest declared.

Funding

TAT and SB are supported by Doctoral Research Fellowships from the National Institute for Health Research, UK (NIHR-DRF-2013-06-102/NIHR-DRF-2011-04-008). MF and SKW are supported by Clinical Research Training Fellowships from the British Heart Foundation (grants FS/12/56/29723 and FS/10/72/28568). JCM is directly and indirectly supported by the University College London Hospitals NIHR Biomedical Research Centre and Biomedical Research Unit at Barts Hospital, respectively. FP: this work form

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