Author + information
- Published online November 6, 2017.
- Graham J. Fent, MBChB,
- Pankaj Garg, MD,
- James R.J. Foley, MBChB,
- Peter P. Swoboda, PhD,
- Laura E. Dobson, MD,
- Bara Erhayiem, BMBS,
- Thomas A. Treibel, MBBS,
- James C. Moon, MD,
- John P. Greenwood, PhD and
- Sven Plein, PhD∗ ()
- ↵∗Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, LIGHT Laboratories, University of Leeds, LS2 9JT Leeds, United Kingdom
Myocardial extracellular volume fraction (ECV) assessed by cardiac magnetic resonance (CMR) estimates the proportion of myocardial extracellular space relative to its cellular component. Conventionally, ECV calculation requires knowledge of the patient’s hematocrit (Hct). Treibel et al. (1) recently demonstrated that a synthetic ECV can be calculated by estimating Hct from the longitudinal relaxation rate (R1 = 1/T1) of blood. This eliminates the time and cost of obtaining a venous Hct sample. So far, synthetic ECV has only been described for data acquired with a single vendor (Siemens, Berlin, Germany) and field strength (1.5-T). We hypothesized that synthetic ECV can also be derived from other platforms and acquisition methods, potentially broadening applicability of this method.
We analyzed data of 421 patients undergoing T1 mapping for research purposes and clinical indications, 203 of whom underwent CMR scans at 1.5-T (Ingenia, Philips, Best, the Netherlands) and 218 at 3.0-T (Achieva-dStream, Philips). Patients on both scanners were randomly split into equally sized derivation and validation subgroups. Derivation groups served to enable derivation of linear regression equations for the relationship of Hct and R1 of blood. This equation was used to calculate synthetic ECV and assess its correlation with conventionally calculated ECV in the validation groups. The 1.5-T cohort comprised 47 patients with valvular heart disease and 44 with ST-segment elevation myocardial infarction and 112 patients undergoing CMR for acute clinical reasons. The 3.0-T cohort comprised 26 healthy control subjects and 159 patients with rheumatoid arthritis and 33 patients with hypertrophic cardiomyopathy.
MOdified Look-Locker Inversion Recovery (MOLLI) acquisition schemes were used to acquire T1 maps produced using vendor software before and 15 min after administration of either 0.2 mmol/kg gadopentate dimeglumine (Magnevist, Bayer Schering, Berlin, Germany) or 0.15 mmol/kg gadobutrol (Gadovist, Bayer Schering). For all 1.5-T patients, a pre-contrast 5s(3s)3s and post-contrast 4s(1s)3s(1s)2s scheme was used. For all 3.0-T patients the same 3(3s)3(3s)5 scheme was used pre- and post-contrast. T1 values were derived by drawing a region of interest within the interventricular septum and blood pool at mid-ventricular level using post-processing software (CVI 42, Circle Cardiovascular Imaging, Calgary, Canada). Scar was included within the interventricular septum region of interest when present. Analysis was blinded. ECV was calculated as has previously been reported (1). Statistical analyses were performed using SPSS version 22 (IBM Corporation, Armonk, New York). All results are presented as mean ± SD.
There was a broad range of Hct in both 1.5-T and 3.0-T derivation groups (0.41 ± 0.05; range 0.27 to 0.53 at 1.5-T; and 0.42 ± 0.04; range 0.31 to 0.54 at 3.0-T). There was also a broad range of blood pre-contrast T1 in 1.5-T and 3.0-T derivation groups (1,608 ± 105 ms; range 1,402 to 1,912 ms at 1.5-T; and 1,780 ± 99 ms; range 1,457 to 1,993 ms at 3.0-T). The conventionally calculated ECV in the validation groups was 32 ± 9% (range 19% to 77%) for 1.5-T and 29 ± 5% (range 20% to 53%) for 3.0-T.
The regression lines between Hct and R1 blood were linear at both field strengths (1.5-T: R2 = 0.50, p < 0.001; 3.0-T: R2 = 0.46, p < 0.001), with the following regression equations (Figure 1):where Hct is hematocrit (between 0 and 1) and R1blood is 1/T1blood in milliseconds.
Using these equations to calculate synthetic ECV in both validation cohorts, conventional and synthetic ECV were highly correlated (Figure 1) (R2 = 0.95, p < 0.001 at 1.5-T; and R2 = 0.92, p < 0.01 at 3.0-T).
On Bland-Altman analysis, synthetic ECV demonstrated minimal bias at both 1.5-T (bias = −0.81%, 95% confidence interval: −4.97% to 3.35%) and 3.0-T (bias = −0.30%, 95% confidence interval: −3.92% to 3.33%).
We have demonstrated that synthetic ECV, derived by estimating Hct from pre-contrast blood T1 values acquired with a MOLLI method on 1.5- and 3.0-T Philips systems, strongly correlates with conventionally calculated ECV. The correlation values demonstrated between Hct and R1 blood in the derivation cohort and between conventional and synthetic ECV in the validation cohort are similar to those reported in the Treibel et al. (1) on a Siemens platform using both MOLLI and Shortened MOdified Look-Locker Inversion recovery (ShMOLLI) pulse sequences. This underscores the accuracy of synthetic ECV and its applicability across platforms and field strength. It offers the potential for use on a routine clinical CMR list, eliminating the need for a venous Hct sample, enabling rapid clinical decision-making.
Please note: Dr. Fent is funded by a National Institute of Healthcare Research grant (1/117/27). Prof. Plein is funded by a British Heart Foundation fellowship (FS 10/62/2840). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- 2017 American College of Cardiology Foundation