Synthetic hematocrit derived from the longitudinal relaxation of blood can lead to clinically significant errors in measurement of extracellular volume fraction in pediatric and young adult patients

Cardiac magnetic resonance findings in cardiac amyloidosis

PURPOSE OF REVIEW

The purpose of this review is to highlight the increasing importance of cardiac magnetic resonance (CMR) imaging in diagnosing and managing cardiac amyloidosis, especially given the recent advancements in treatment options.

RECENT FINDINGS

This review emphasizes the crucial role of late gadolinium enhancement (LGE) with phase-sensitive inversion recovery (PSIR) techniques in both diagnosing and predicting patient outcomes in cardiac amyloidosis. The review also explores promising new techniques for diagnosing early-stage disease, such as native T1 mapping and ECV quantification. Additionally, it delves into experimental techniques like diffusion tensor imaging, MR elastography, and spectroscopy.

SUMMARY

This review underscores CMR as a powerful tool for diagnosing cardiac amyloidosis, assessing risk factors, and monitoring treatment response. While LGE imaging remains the current best practice for diagnosis, emerging techniques such as T1 mapping and ECV quantification offer promise for improved detection, particularly in early stages of the disease. This has significant implications for patient management as newer therapeutic options become available for cardiac amyloidosis.

Estimating synthetic hematocrit and extracellular volume from native blood pool T1 times at 3 Tesla CMR: Derivation of a conversion equation, accuracy and comparison with published formulas

PURPOSE

Calculation of extracellular volume fraction (ECV), a marker of myocardial fibrosis in cardiac magnetic resonance imaging (CMR), requires hematocrit (Hct). We aimed to correlate Hct levels with native blood T1 times, to derive a formula for estimating synthetic Hct (Hctsyn) and synthetic ECV (ECVsyn), to assess accuracy of ECVsyn and to compare our model with published formulas.

METHOD

In this retrospective study, a cohort of 250 CMR scans with T1 mapping (3T, MOLLI 5(3)3, endsystolic aquisition), was divided into a derivation and validation cohort. Native T1 times of the left ventricular blood pool (T1native,midLV) were correlated with Hct levels from blood sampling within 24 h (Hct24h) and a formula for calculation of Hctsyn was derived by linear regression.

RESULTS

In the derivation cohort (n = 167), Hct24h showed a good association with T1native,midLV (r = -0.711, p < 0.001). The resulting regression equation was Hctsyn = 1/T1native,midLV * 1355.52-0.310. In the validation cohort (n = 83), Hctsyn and Hct24h showed good correlation (r = 0.726, p < 0.001), while ECVsyn, and ECV24h demonstrated excellent correlation (r = 0.940, p < 0.001). ECVsyn had a minimal bias of 0.28 % and the misclassification rate (8.8 %) was comparable to the variability introduced by repeated Hct measurements (misclassification in 7.5 %). Applying published formulas in our cohort resulted in incorrect classification in up to 60 %.

CONCLUSION

We provide a formula for estimating Hctsyn from native blood T1 on a 3T scanner. The measurement error of ECVsyn is low and comparable to the error due to retest variability of conventional Hct. Scanner- and sequence-specific formulas should be used.

The Role of Multimodality Imaging in Cardiomyopathy

PURPOSE OF REVIEW

There has been increasing use of multimodality imaging in the evaluation of cardiomyopathies.

RECENT FINDINGS

Echocardiography, cardiac magnetic resonance (CMR), cardiac nuclear imaging, and cardiac computed tomography (CCT) play an important role in the diagnosis, risk stratification, and management of patients with cardiomyopathies. Echocardiography is essential in the initial assessment of suspected cardiomyopathy, but a multimodality approach can improve diagnostics and management. CMR allows for accurate measurement of volumes and function, and can easily detect unique pathologic structures. In addition, contrast imaging and parametric mapping enable the characterization of tissue features such as scar, edema, infiltration, and deposition. In non-ischemic cardiomyopathies, metabolic and molecular nuclear imaging is used to diagnose rare but life-threatening conditions such amyloidosis and sarcoidosis. There is an expanding use of CCT for planning electrophysiology procedures such as cardioversion, ablations, and device placement. Furthermore, CCT can evaluate for complications associated with advanced heart failure therapies such as cardiac transplant and mechanical support devices. Innovations in multimodality cardiac imaging should lead to increased volumes and better outcomes.

A comparative study of synthetic and venous hematocrit for calculating cardiovascular magnetic resonance-derived extracellular volume

The extracellular volume (ECV) fraction derived from cardiac magnetic resonance (CMR) can reflect various pathologies. The application of ECVs was limited by the strict requirement that hematocrit (Hct0) should be obtained within 24 hours of CMR scan. The aim of this study was to obtain accurate and convenient ECV calculated from the venous Hct and synthetic Hct in CMR. A total of 839 subjects were retrospectively enrolled. The subjects were divided into derivation cohort for local sex-specific models and validation cohort for assessing the accuracy of different ECVs. In the validation cohort, venous Hcts from 7 days before the scan (Hct1 - 7), outside 7 days (Hct> 7), the closest day (Hctclosest), and Hctsyn were compared with Hct0. The agreement and correlation of the conventional ECV (ECV0) with the corresponding ECVs were analyzed. The factors affecting the accuracy of ECVsyn were assessed. ECV1-7 and ECVclosest had the best correlation and smallest bias with ECV0 (R = 0.959 and 0.951, bias = 0.02% and - 0.03%). When using an absolute 2% error as the standard, the performance of ECV1-7 was the best, with an accuracy of 81.0%, followed by ECVclosest (78.8%), ECV> 7 (77.2%) and ECVsyn (70.7%). Abnormally low and high Hcts and decreased left ventricular ejection fractions were associated with miscalculation of ECVsyn, especially patients with dilated cardiomyopathy. We recommend extending the time interval between a Hct and a CMR scan to 7 days for ECV calculation. The synthetic ECV should be used cautiously, especially for patients with extremely low or high Hcts, decreased cardiac function, and dilated cardiomyopathy.

Establishment and validation of an extracellular volume model without blood sampling in ST-segment elevation myocardial infarction patients

Aims

Recent studies have shown that extracellular volume (ECV) can also be obtained without blood sampling by the linear relationship between haematocrit (HCT) and blood pool R1 (1/T1). However, whether this relationship holds for patients with myocardial infarction is still unclear. This study established and validated an ECV model without blood sampling in ST-segment elevation myocardial infarction (STEMI) patients.

Methods and results

A total of 398 STEMI patients who underwent cardiac magnetic resonance (CMR) examination with T1 mapping and venous HCT within 24 h were retrospectively analysed. All patients were randomly divided into a derivation group and a validation group. The mean CMR scan time was 3 days after primary percutaneous coronary intervention. In the derivation group, a synthetic HCT formula was obtained by the linear regression between HCT and blood pool R1 (R 2 = 0.45, P < 0.001). The formula was used in the validation group; the results showed high concordance and correlation between synthetic ECV and conventional ECV in integral (bias = -0.12; R 2 = 0.92, P < 0.001), myocardial infarction site (bias = -0.23; R 2 = 0.93, P < 0.001), and non-myocardial infarction sites (bias = -0.09; R 2 = 0.94, P < 0.001).

Conclusion

In STEMI patients, synthetic ECV without blood sampling had good consistency and correlation with conventional ECV. This study might provide a convenient and accurate method to obtain the ECV from CMR to identify myocardial fibrosis.

Quantification of myocardial extracellular volume without blood sampling

Aims

Cardiac magnetic resonance (CMR) T1 relaxation time mapping is an established technique primarily used to identify diffuse interstitial fibrosis and oedema. The myocardial extracellular volume (ECV) can be calculated from pre- and post-contrast T1 relaxation times and is a reproducible parametric index of the proportion of volume occupied by non-cardiomyocyte components in myocardial tissue. The conventional calculation of the ECV requires blood sampling to measure the haematocrit (HCT). Given the high variability of the HCT, the blood collection is recommended within 24 h of the CMR scan, limiting its applicability and posing a barrier to the clinical routine use of ECV measurements. In recent years, several research groups have proposed a method to determine the ECV by CMR without blood sampling. This is based on the inverse relationship between the T1 relaxation rate (R1) of blood and the HCT. Consequently, a 'synthetic' HCT could be estimated from the native blood R1, avoiding blood sampling.

Methods and results

We performed a review and meta-analysis of published studies on synthetic ECV, as well as a secondary analysis of previously published data to examine the effect of the chosen regression modell on bias. While, overall, a good correlation and little bias between synthetic and conventional ECV were found in these studies, questions regarding its accuracy remain.

Conclusion

Synthetic HCT and ECV can provide a 'non-invasive' quantitative measurement of the myocardium's extracellular space when timely HCT measurements are not available and large alterations in ECV are expected, such as in cardiac amyloidosis. Due to the dependency of T1 relaxation times on the local setup, calculation of local formulas using linear regression is recommended, which can be easily performed using available data.

Synthetic Extracellular Volume in Cardiac Magnetic Resonance Without Blood Sampling: a Reliable Tool to Replace Conventional Extracellular Volume

Background:

The calculation of extracellular volume (ECV) in cardiac magnetic resonance requires hematocrit, limiting its applicability in clinical practice. Based on the linear relationship between hematocrit and blood T1 relaxivity, a synthetic ECV could be estimated without a blood sample. We aim to develop and test regression models for synthetic ECV without blood sampling in 1.5-T and 3.0-T scanners.

Methods:

A total of 1101 subjects who underwent cardiac magnetic resonance scanning with native and postcontrast T1 mapping and venous hematocrit within 24 hours were retrospectively enrolled. Subjects were randomly split into derivation (n=550) and validation (n=551) subgroups for each scanner. Different regression models were derived controlling for sex, field strength, and left ventricle/right ventricle blood pool and validated in the validation group. We performed additional validation analyses in subgroups of patients with histological validation (n=17), amyloidosis (n=29), anemia (n=185), and reduced ejection fraction (n=322).

Results:

In the derivation group, 8 specific models and 2 common estimate models were derived. In the validation group, using specific models, synthetic ECV had high agreement with conventional ECV (R², 0.87; P<0.0001 and R², 0.88, P<0.0001; −0.16% and −0.10%, left ventricle and right ventricle model, respectively). Common models also performed well (R², 0.88; P<0.0001 and R², 0.89, P<0.0001; −0.21% and −0.18%, left ventricle and right ventricle model, respectively). Histological validation demonstrated equal performance of synthetic and measured ECV. Synthetic ECV as calculated by the common model showed a bias in the anemia cohort significantly reduced by the specific model (−2.45 to −1.28, right ventricle common and specific model, respectively).

Conclusions:

Synthetic ECV provided a promising way to calculate ECV without blood sampling. Specific models could provide the most accurate value, while common models could be more suitable in routine clinical practice because of their simplicity while maintaining adequate accuracy.

Feasibility of Hepatic T1-Mapping and Extracellular Volume Quantification on Routine Cardiac Magnetic Resonance Imaging in Patients with Infiltrative and Systemic Disorders

RATIONALE AND OBJECTIVES

Cardiac magnetic resonance imaging (CMR) is commonly obtained to evaluate for myocardial infiltrative disorders and fibrosis. Pre- and post-Gadolinium contrast T1-mapping sequences are employed to estimate interstitial expansion using extracellular volume fraction (ECV). Given the proximity of the liver to the heart, T1 and ECV quantification of the liver is feasible on CMR. The purpose of this study was to evaluate for hepatic measures of fibrosis and interstitial expansion in patients with amyloidosis or systemic disease on CMR.

MATERIALS AND METHODS

Myocardial and hepatic native T1 values were measured retrospectively using a cardiac short axis modified Look-Locker inversion recovery sequence. Myocardial and hepatic ECV were calculated using pre- and post-contrast T1 and blood pool values according to the following formula: ECV = (Δ(1/T1) myocardium or liver and/or Δ(1/T1) blood)x(1 - hematocrit). Patients were divided into three cohorts by final diagnosis: amyloidosis, systemic disease (e.g. sarcoid, scleroderma), and controls (EF > 50, no ischemia).

RESULTS

Of the 135 patients who underwent CMR, 22 had cardiac amyloidosis (age 59.9 ± 12.6 yrs, 41% female), 20 had systemic disease (age 50.9 ± 13.4 yrs, 35% female), and 93 were controls (age 49.5 ± 17.3 yrs, 50% female). Myocardial T1 and ECV values were highest for patients with amyloid, second highest for systemic disease, and least for controls (T1: 1169 ± 92 vs 1101 ± 53 vs 1027 ± 73 ms, p < 0.0001; ECV: 0.47 ± 0.11 vs 0.31 ± 0.05 vs 0.27 ± 0.04, p < 0.0001). Hepatic T1 and ECV were similarly higher in patients with amyloid and systemic disease compared to controls (T1: 646 ± 101 vs 660 ± 93 vs 595 ± 58 ms, p < 0.0001; ECV: 0.38 ± 0.08 vs 0.37 ± 0.05 vs 0.31 ± 0.03, p < 0.0001). There was a positive correlation between hepatic T1 and ECV (R² = 0.282, p < 0.0001). No patients had abnormal liver function tests or clinical liver disease.

CONCLUSION

Hepatic ECV quantification on CMR in patients with amyloidosis and systemic disorders is feasible. Further longitudinal investigation regarding detection of early or subclinical liver disease is warranted.

Synthetic extracellular volume fraction without hematocrit sampling for hepatic applications

Purpose

Calculation of extracellular volume fraction (ECV) currently receives increasing interest as a potential biomarker for non-invasive assessment of liver fibrosis. ECV calculation requires hematocrit (Hct) sampling, which might be difficult to obtain in a high-throughput radiology department. The aim of this study was to generate synthetic ECV for hepatic applications without the need for Hct sampling.

Methods

In this prospective study participants underwent liver MRI. T1 mapping was performed before and after contrast administration. Blood Hct was obtained prior to MRI. We hypothesized that the relationship between Hct and longitudinal relaxation rate of blood (R1 = 1/T1_blood) could be calibrated and used to generate the equation for synthetic Htc and ECV calculation. Conventional and synthetic ECV were calculated. Pearson correlation, linear regression and Bland–Altman method were used for statistical analysis.

Results

180 consecutive patients were divided into derivation (n = 90) and validation (n = 90) cohorts. In the derivation cohort, native R1_blood and Hct showed a linear relationship (Hct_MOLLI = 98.04 × (1/T1_blood) − 33.17, R² = 0.75, P < 0.001), which was used to calculate synthetic ECV in the validation and whole study cohorts. Synthetic and conventional ECV showed significant correlations in the derivation, validation and in the whole study cohorts (r = 0.99, 0.97 and 0.99, respectively, P < 0.001, respectively) with minimal bias according to the Bland–Altman analysis.

Conclusion

Synthetic ECV seems to offer an alternative method for non-invasive quantification of the hepatic ECV. It may potentially overcome an important barrier to clinical implementation of ECV and thus, enable broader use of hepatic ECV in routine clinical practice.

Myocardial extracellular volume by T1 mapping: a new marker of arrhythmia in mitral valve prolapse

OBJECTIVES

We aimed to evaluate the relationship between mitral annular disjunction (MAD) severity and myocardial interstitial fibrosis at the left ventricular (LV) base in patients with mitral valve prolapse (MVP), and to assess the association between severity of interstitial fibrosis and the occurrence of ventricular arrhythmic events.

BACKGROUND

In MVP, MAD has been associated with myocardial replacement fibrosis and arrhythmia, but the importance of interstitial fibrosis remains unknown.

METHODS

In this retrospective study, 30 patients with MVP and MAD (MVP-MAD) underwent cardiovascular magnetic resonance (CMR) with assessment of MAD length, late gadolinium enhancement (LGE), and basal segments myocardial extracellular volume (ECVsyn). The control group included 14 patients with mitral regurgitation (MR) but no MAD (MR-NoMAD) and 10 patients with normal CMR (NoMR-NoMAD). Fifteen MVP-MAD patients underwent 24 h-Holter monitoring.

RESULTS

LGE was observed in 47% of MVP-MAD patients and was absent in all controls. ECVsyn was higher in MVP-MAD (30 ± 3% vs 24 ± 3% MR-NoMAD, p < 0.001 and vs 24 ± 2% NoMR-NoMAD, p < 0.001), even in MVP-MAD patients without LGE (29 ± 3% vs 24 ± 3%, p < 0.001 and vs 24 ± 2%, p < 0.001, respectively). MAD length correlated with ECVsyn (rho = 0.61, p < 0.001), but not with LGE extent. Four patients had history of out-of-hospital cardiac arrest; LGE and ECVsyn were equally performant to identify those high-risk patients, area under the receiver operating characteristic (ROC) curve 0.81 vs 0.83, p = 0.84). Among patients with Holter, 87% had complex ventricular arrhythmia. ECVsyn was above the cut-off value in all while only 53% had LGE.

CONCLUSION

Increase in ECVsyn, a marker of interstitial fibrosis, occurs in MVP-MAD even in the absence of LGE, and was correlated with MAD length and increased risk of out-of-hospital cardiac arrest. ECV should be includedin the CMR examination of MVP patients in an effort to better assess fibrous remodelling as it may provide additional value beyond the assessment of LGE in the arrhythmic risk stratification.

Extracellular volume quantification using synthetic haematocrit assessed from native and post-contrast longitudinal relaxation T1 times of a blood pool

Background

In terms of cardiovascular magnetic resonance are haematocrit values required for calculation of extracellular volume fraction (ECV). Previously published studies have hypothesized that haematocrit could be calculated from T1 blood pool relaxation time, however only native T1 relaxation time values have been used and the resulting formulae had been both in reciprocal and linear proportion. The aim of the study was to generate a synthetic haematocrit formula from only native relaxation time values first, calculate whether linear or reciprocal model is more precise in haematocrit estimation and then determine whether adding post-contrast values further improve its precision.

Methods

One hundred thirty-nine subjects underwent CMR examination. Haematocrit was measured using standard laboratory methods. Afterwards T1 relaxation times before and after the application of a contrast agent were measured and a statistical relationship between these values was calculated.

Results

Different linear and reciprocal models were created to estimate the value of synthetic haematocrit and ECV. The highest coefficient of determination was observed in the combined reciprocal model “− 0.047 + (779/ blood native) − (11.36/ blood post-contrast)”.

Conclusions

This study provides more evidence that assessing synthetic haematocrit and synthetic ECV is feasible and statistically most accurate model to use is reciprocal. Adding post-contrast values to the calculation was proved to improve the precision of the formula statistically significantly.

Performance of Synthetic Extracellular Volume Fraction in Different Cardiac Phenotypes From a Prospective Cohort of Patients Referred for Cardiac Magnetic Resonance

BACKGROUND

A synthetic myocardial extracellular volume fraction (sECV) can be obtained without blood hematocrit (Hct) by using the linear relationship between Hct and the longitudinal relaxation time of blood. Concerns have been raised about the widespread clinical application of this approach.

PURPOSE

To assess the relationship between measured ECV (m-ECV) and sECV, using both a published model and a locally derived one.

STUDY TYPE

Single-center, prospective.

FIELD STRENGTH/SEQUENCE

A 1.5 T/modified Look Locker (MOLLI) sequence.

SUBJECTS

Fifty-two healthy subjects and 113 patients (76 with and 37 without a hypertrophic cardiac phenotype).

ASSESSMENT

Three ECV values were obtained for each patient: 1) measured ECV (m-ECV), using Hct from a venous blood sample; 2) Fent-synthetic ECV (F-sECV), using the equation proposed by Fent et al; and 3) Local-synthetic ECV (L-sECV), using the equation obtained from a local derivation cohort comprising 83 subjects.

STATISTICAL TESTS

Shapiro-Wilk test, analysis of variance, Kruskal Wallis test, Pearson correlation, Bland-Altman analysis, univariate and multivariable regression analysis.

RESULTS

In the validation cohort (N = 82), Bland-Altmann analysis revealed an excellent agreement between m-ECV and L-sECV with a statistically insignificant bias (-0.1%, limits of agreement: -2.8% and 2.6%; P = 0.528), while in the overall population (N = 165), the mean bias between m-ECV and F-sECV was small but significant (1.2%, limits of agreement: -1.5% and 3.9%, P < 0.05). F-sECV bias was significantly higher for measured Hct (m-Hct) values <0.372 (2.3% vs. 1.0%, P < 0.05). Among the phenotype subgroups, amyloidotic patients showed a higher bias compared to others, both with F-sECV and L-sECV (2.3% vs. 1.1%, P < 0.05 and 1.1% vs. 0.2%, P < 0.05, respectively).

DATA CONCLUSION

Although synthetic ECV performs well in an external cohort, the use of a local formula further improves the accuracy of ECV estimate over a broad spectrum of cardiac phenotypes. Local sECV performs better for a wider range of Hct values, compared to the published model. Amyloidosis is the only group associated with a lower accuracy.

LEVEL OF EVIDENCE

5 TECHNICAL EFFICACY: Stage 2.

Myocardial extracellular volume fraction quantification in an animal model of the doxorubicin-induced myocardial fibrosis: a synthetic hematocrit method using 3T cardiac magnetic resonance

Background

Visualization of diffuse myocardial fibrosis is challenging and mainly relies on histology. Cardiac magnetic resonance (CMR), which uses extracellular contrast agents, is a rapidly developing technique for measuring the extracellular volume (ECV). The objective of this study was to evaluate the feasibility of the synthetic myocardial ECV fraction based on 3.0 T CMR compared with the conventional ECV fraction.

Methods

This study was approved by the local animal care and ethics committee. Fifteen beagle models with diffuse myocardial fibrosis, including 12 experimental and three control subjects, were generated by injecting doxorubicin 30 mg/m² intravenously every three weeks for 24 weeks. Short-axis (SAX) and 4-chamber long-axis (LAX) T1 maps were acquired for both groups. The association between hematocrit (Hct) and native T1_blood was derived from 9 non-contrast CMR T1 maps of 3 control beagles using regression analysis. Synthetic ECV was then calculated using the synthetic Hct and compared with conventional ECV at baseline and the 16^th and 24^th week after doxorubicin administration. The collagen volume fraction (CVF) value was measured on digital biopsy samples. Bland-Altman plots were used to analyze the agreement between conventional and synthetic ECV. Correlation analyses were performed to explore the association among conventional ECV, synthetic ECV, CVF, and left ventricular ejection fraction (LVEF).

Results

The regression model synthetic Hct = 816.46*R1_blood - 0.01 (R²=0.617; P=0.012) was used to predict the Hct from native T1_blood values. The conventional and synthetic ECV fractions of experimental animals at the 16^th and 24^th week after modeling were significantly higher than those measured at the baseline (31.4%±2.2% and 36.3%±2.1% vs. 22.9%±1.7%; 29.9%±2.4% and 36.1%±2.6% vs. 22.0%±2.4%; all with P<0.05). Bland-Altman plots showed a bias (1.0%) between conventional and synthetic ECV with 95% limits of agreement of -2.5% to 4.4% in the per-subject analysis (n=21) and a bias (1.0%) between conventional and synthetic ECV with 95% limits of agreement of -2.4% to 4.3% in the per-segment analysis (n=294). Conventional and synthetic ECV were well correlated with CVF (r=0.937 and 0.925, all with P<0.001, n=10).

Conclusions

Our study showed promising results for using synthetic ECV compared with the conventional ECV for providing accurate quantification of myocardial ECV without the need for blood sampling.

Is a timely assessment of the hematocrit necessary for cardiovascular magnetic resonance-derived extracellular volume measurements?

BACKGROUND

Cardiovascular magnetic resonance (CMR)-derived extracellular volume (ECV) requires a hematocrit (Hct) to correct contrast volume distributions in blood. However, the timely assessment of Hct can be challenging and has limited the routine clinical application of ECV. The goal of the present study was to evaluate whether ECV measurements lead to significant error if a venous Hct was unavailable on the day of CMR.

METHODS

109 patients with CMR T1 mapping and two venous Hcts (Hct0: a Hct from the day of CMR, and Hct1: a Hct from a different day) were retrospectively identified. A synthetic Hct (Hctsyn) derived from native blood T1 was also assessed. The study used two different ECV methods, (1) a conventional method in which ECV was estimated from native and postcontrast T1 maps using a region-based method, and (2) an inline method in which ECV was directly measured from inline ECV mapping. ECVs measured with Hct0, Hct1, and Hctsyn were compared for each method, and the reference ECV (ECV0) was defined using the Hct0. The error between synthetic (ECVsyn) and ECV0was analyzed for the two ECV methods.

RESULTS

ECV measured using Hct1 and Hctsyn were significantly correlated with ECV0 for each method. No significant differences were observed between ECV0 and ECV measured with Hct1 (ECV1; 28.4 ± 6.6% vs. 28.3 ± 6.1%, p = 0.789) and between ECV0 and ECV calculated with Hctsyn (ECVsyn; 28.4 ± 6.6% vs. 28.2 ± 6.2%, p = 0.45) using the conventional method. Similarly, ECV0 was not significantly different from ECV1 (28.5 ± 6.7% vs. 28.5 ± 6.2, p = 0.801) and ECVsyn (28.5 ± 6.7% vs. 28.4 ± 6.0, p = 0.974) using inline method. ECVsyn values revealed relatively large discrepancies in patients with lower Hcts compared with those with higher Hcts.

CONCLUSIONS

Venous Hcts measured on a different day from that of the CMR examination can still be used to measure ECV. ECVsyn can provide an alternative method to quantify ECV without needing a blood sample, but significant ECV errors occur in patients with severe anemia.

Journal of Cardiovascular Magnetic Resonance: 2017/2018 in review

There were 89 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 76 original research papers, 4 reviews, 5 technical notes, 1 guideline, and 3 corrections. The volume was down slightly from 2017 with a corresponding 15% decrease in manuscript submissions from 405 to 346 and thus reflects a slight increase in the acceptance rate from 25 to 26%. The decrease in submissions for the year followed the initiation of the increased author processing charge (APC) for Society for Cardiovascular Magnetic Resonance (SCMR) members for manuscripts submitted after June 30, 2018. The quality of the submissions continues to be high. The 2018 JCMR Impact Factor (which is published in June 2019) was slightly lower at 5.1 (vs. 5.46 for 2017; as published in June 2018. The 2018 impact factor means that on average, each JCMR published in 2016 and 2017 was cited 5.1 times in 2018. Our 5 year impact factor was 5.82.In accordance with Open-Access publishing guidelines of BMC, the JCMR articles are published on-line in a continuus fashion in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful for the JCMR audience to annually summarize the publications into broad areas of interest or themes, so that readers can view areas of interest in a single article in relation to each other and contemporaneous JCMR publications. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, as in the past two years, I have used this publication to also convey information regarding the editorial process and as a "State of our JCMR."This is the 12th year of JCMR as an open-access publication with BMC (formerly known as Biomed Central). The timing of the JCMR transition to the open access platform was "ahead of the curve" and a tribute to the vision of Dr. Matthias Friedrich, the SCMR Publications Committee Chair and Dr. Dudley Pennell, the JCMR editor-in-chief at the time. The open-access system has dramatically increased the reading and citation of JCMR publications and I hope that you, our authors, will continue to send your very best, high quality manuscripts to JCMR for consideration. It takes a village to run a journal and I thank our very dedicated Associate Editors, Guest Editors, Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner. These efforts have allowed the JCMR to continue as the premier journal of our field. This entire process would also not be possible without the dedication and efforts of our managing editor, Diana Gethers. Finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 4th year as your editor-in-chief. It has been a tremendous experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!

Tissue characterisation and myocardial mechanics using cardiac MRI in children with hypertrophic cardiomyopathy

INTRODUCTION

Distinguishing between hypertrophic cardiomyopathy and other causes ofleft ventricular hypertrophy can be difficult in children. We hypothesised that cardiac MRI T1 mapping could improve diagnosis of paediatric hypertrophic cardiomyopathy and that measures of myocardial function would correlate with T1 times and extracellular volume fraction.

METHODS

Thirty patients with hypertrophic cardiomyopathy completed MRI with tissue tagging, T1-mapping, and late gadolinium enhancement. Left ventricular circumferential strain was calculated from tagged images. T1, partition coefficient, and synthetic extracellular volume were measured at base, mid, apex, and thickest area of myocardial hypertrophy. MRI measures compared to cohort of 19 healthy children and young adults. Mann-Whitney U, Spearman's rho, and multivariable logistic regression were used for statistical analysis.

RESULTS

Hypertrophic cardiomyopathy patients had increased left ventricular ejection fraction and indexed mass. Hypertrophic cardiomyopathy patients had decreased global strain and increased native T1 (-14.3% interquartile range [-16.0, -12.1] versus -17.3% [-19.0, -15.7], p < 0.001 and 1015 ms [991, 1026] versus 990 ms [972, 1001], p = 0.019). Partition coefficient and synthetic extracellular volume were not increased in hypertrophic cardiomyopathy. Global native T1 correlated inversely with ejection fraction (ρ = -0.63, p = 0.002) and directly with global strain (ρ = 0.51, p = 0.019). A logistic regression model using ejection fraction and native T1 distinguished between hypertrophic cardiomyopathy and control with an area under the receiver operating characteristic curve of 0.91.

CONCLUSION

In this cohort of paediatric hypertrophic cardiomyopathy, strain was decreased and native T1 was increased compared with controls. Native T1 correlated with both ejection fraction and strain, and a model using native T1 and ejection fraction differentiated patients with and without hypertrophic cardiomyopathy.

Myocardial Partition Coefficient of Gadolinium: A Pilot Study in Patients With Acute Myocarditis, Chronic Myocardial Infarction, and in Healthy Volunteers

BACKGROUND

The tissue-blood partition coefficient (PC) of gadolinium, derived from T1 measurements, reflects myocardial connective tissue fraction and tissue injury, increasing in proportion with edema or fibrosis. We determined the myocardial PC of gadolinium in patients with acute myocarditis, chronic myocardial infarction (MI), and healthy volunteers. We hypothesized that the characteristics of the injured myocardium in patients with MI and myocarditis may differ and that the PC will be higher in chronically injured myocardium (MI) compared with acutely injured myocardium (myocarditis).

METHODS

We performed late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging and T1 mapping before and after administration of gadolinium (0.1 mmol/kg Gd-BOPTA) at 3 Tesla in 10 healthy volunteers (47.1 ± 12.4 years), 18 patients with chronic MI (62.5 ± 8.1 years), and 16 patients with acute myocarditis (42.5 ± 13.9 years).

RESULTS

In patients with chronic MI and focal scar by LGE, the whole left ventricular myocardial PC (0.45 ± 0.05) was higher compared with patients with MI without focal scar (0.39 ± 0.03, P = 0.02) but not significantly different from whole myocardial PC in volunteers (0.40 ± 0.05) or patients with myocarditis (0.41 ± 0.05). The PC in myocarditis scars was lower than in chronic MI scars (0.60 ± 0.12 vs 0.77 ± 0.16, P = 0.016). The relationships of PC and scar burden, expressed as % LGE, were similar and significant for the 2 groups (P = 0.042).

CONCLUSION

The tissue-blood partition coefficient of Gd-BOPTA is elevated in areas of acute and chronic myocardial injury and may serve as a marker for disease activity and density of scars, which was found to be higher in chronic MI than in acute myocarditis.

Journal of Cardiovascular Magnetic Resonance 2017

There were 106 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 92 original research papers, 3 reviews, 9 technical notes, and 1 Position paper, 1 erratum and 1 correction. The volume was similar to 2016 despite an increase in manuscript submissions to 405 and thus reflects a slight decrease in the acceptance rate to 26.7%. The quality of the submissions continues to be high. The 2017 JCMR Impact Factor (which is published in June 2018) was minimally lower at 5.46 (vs. 5.71 for 2016; as published in June 2017), which is the second highest impact factor ever recorded for JCMR. The 2017 impact factor means that an average, each JCMR paper that were published in 2015 and 2016 was cited 5.46 times in 2017.In accordance with Open-Access publishing of Biomed Central, the JCMR articles are published on-line in continuus fashion and in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful to annually summarize the publications into broad areas of interest or theme, so that readers can view areas of interest in a single article in relation to each other and other contemporary JCMR articles. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, I have elected to use this format to convey information regarding the editorial process to the readership.I hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your very best, high quality manuscripts to JCMR for consideration. I thank our very dedicated Associate Editors, Guest Editors, and Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner and that the JCMR continues to be recognized as the forefront journal of our field. And finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 3rd year as your editor-in-chief. It has been a tremendous learning experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!

Cardiac magnetic resonance T1 mapping. Part 1: Aspects of acquisition and evaluation

While an enormous number of studies have documented pathological alterations of the myocardial native longitudinal relaxation time (T1) and the fraction of the extracellular myocardial volume (ECV), it has also become clear that continuously evolving T1 mapping sequence, acquisition and evaluation techniques have a substantial impact on quantitative results, making the translation of reported findings into routine clinical use particularly challenging. To provide a basis for the discussion of pathological myocardial T1 and ECV alterations, the present review aims to summarize the methodological aspects of myocardial T1 mapping along with technical and physiological factors influencing results and normal ranges of myocardial native T1 and ECV reported across studies.

Extracellular volume fraction measurements derived from the longitudinal relaxation of blood-based synthetic hematocrit may lead to clinical errors in 3 T cardiovascular magnetic resonance

BACKGROUND

The extracellular volume (ECV), derived from cardiovascular magnetic resonance (CMR) T1 mapping, is a biomarker of the extracellular space in the myocardium. The hematocrit (HCT), measured from venipuncture, is required for ECV measurement. We test the clinic values of synthetic ECV, which is derived from the longitudinal relaxation of blood-based (T1blood) synthetic hematocrit in 3 T CMR.

METHODS

A total of 226 subjects with CMR T1 mapping and HCT measurement taken on the same day as the CMR were retrospectively enrolled and randomly split into derivation (n = 121) and validation (n = 105) groups, comprising healthy subjects (n = 45), type 2 diabetes mellitus (T2DM) patients (n = 60), hypertrophic cardiomyopathy (HCM) patients (n = 93), and 28 other patients. Correlation of T1blood with the measured HCT (HCTm) was established in the derivation group and used in both the derivation and the validation groups. The relationships between the ECV values derived from both the synthetic HCT (HCTsyn) and HCTm were explored. In addition, the differences in the ECV values among the HC, T2DMs, and HCMs were compared.

RESULTS

Regression between the HCTm and 1/T1blood was linear (R2 = 0.19, p < 0.001), and the regression equation was: HCTsyn = [561.6*(1/T1blood)] + 0.098 in the derivation group. The measured ECV (ECVm) was strongly correlated with the synthetic ECV (ECVsyn) (R2 = 0.87, p < 0.001) and mildly correlated with the difference between the ECVsyn and ECVm (R2 = 0.10, p < 0.001) in the derivation group. Also in this group, the ECVm was larger in T2DMs than that in healthy cohort (29.1 ± 3.1% vs. 26.4 ± 2.4%, p = 0.002), whereas, the ECVsyn did not differ between T2DMs and healthy cohort (28.3 ± 2.9% vs. 26.9 ± 2.2%, p = 0.064). Compared with the healthy cohort, the HCMs were associated with higher ECVsyn and ECVm of the mid-ventricle in both the derivation and the validation groups. Using our center's normal cut-off of 31.8%, the use of ECVsyn would lead to a 6-25% incorrect categorization of patients in the derivation and validation groups.

CONCLUSIONS

ECVsyn derived from HCTsyn may lead to clinical errors in 3 T CMR, especially for patients who have only a subtle elevation in ECV.

Importance of standardizing timing of hematocrit measurement when using cardiovascular magnetic resonance to calculate myocardial extracellular volume (ECV) based on pre- and post-contrast T1 mapping

BACKGROUND

Cardiovascular magnetic resonance (CMR) can be used to calculate myocardial extracellular volume fraction (ECV) by relating the longitudinal relaxation rate in blood and myocardium before and after contrast-injection to hematocrit (Hct) in blood. Hematocrit is known to vary with body posture, which could affect the calculations of ECV. The aim of this study was to test the hypothesis that there is a significant increase in calculated ECV values if the Hct is sampled after the CMR examination in supine position compared to when the patient arrives at the MR department.

METHODS

Forty-three consecutive patients including various pathologies as well as normal findings were included in the study. Venous blood samples were drawn upon arrival to the MR department and directly after the examination with the patient remaining in supine position. A Modified Look-Locker Inversion recovery (MOLLI) protocol was used to acquire mid-ventricular short-axis images before and after contrast injection from which motion-corrected T1 maps were derived and ECV was calculated.

RESULTS

Hematocrit decreased from 44.0 ± 3.7% before to 40.6 ± 4.0% after the CMR examination (p < 0.001). This resulted in a change in calculated ECV from 24.7 ± 3.8% before to 26.2 ± 4.2% after the CMR examination (p < 0.001). All patients decreased in Hct after the CMR examination compared to before except for two patients whose Hct remained the same.

CONCLUSION

Variability in CMR-derived myocardial ECV can be reduced by standardizing the timing of Hct measurement relative to the CMR examination. Thus, a standardized acquisition of blood sample for Hct after the CMR examination, when the patient is still in supine position, would increase the precision of ECV measurements.

Noninvasive hematocrit assessment for cardiovascular magnetic resonance extracellular volume quantification using a point-of-care device and synthetic derivation

BACKGROUND

Calculation of cardiovascular magnetic resonance (CMR) extracellular volume (ECV) requires input of hematocrit, which may not be readily available. The purpose of this study was to evaluate the diagnostic accuracy of ECV calculated using various noninvasive measures of hematocrit compared to ECV calculated with input of laboratory hematocrit as the reference standard.

METHODS

One hundred twenty three subjects (47.7 ± 14.1 years; 42% male) were prospectively recruited for CMR T1 mapping between August 2016 and April 2017. Laboratory hematocrit was assessed by venipuncture. Noninvasive hematocrit was assessed with a point-of-care (POC) device (Pronto-7® Pulse CO-Oximeter®, Masimo Personal Health, Irvine, California, USA) and by synthetic derivation based on the relationship with blood pool T1 values. Left ventricular ECV was calculated with input of laboratory hematocrit (Lab-ECV), POC hematocrit (POC-ECV), and synthetic hematocrit (synthetic-ECV), respectively. Statistical analysis included Wilcoxon signed-rank test, Bland-Altman analysis, receiver-operating curve analysis and intra-class correlation (ICC).

RESULTS

There was no significant difference between Lab-ECV and POC-ECV (27.1 ± 4.7% vs. 27.3 ± 4.8%, p = 0.106), with minimal bias and modest precision (bias - 0.18%, 95%CI [- 2.85, 2.49]). There was no significant difference between Lab-ECV and synthetic-ECV (26.7 ± 4.4% vs. 26.5 ± 4.3%, p = 0.084) in subjects imaged at 1.5 T, although bias was slightly higher and limits of agreement were wider (bias 0.23%, 95%CI [- 2.82, 3.27]). For discrimination of abnormal Lab-ECV ≥30%, POC-ECV had good diagnostic performance (sensitivity 85%, specificity 96%, accuracy 94%, and AUC 0.902) and synthetic-ECV had moderate diagnostic performance (sensitivity 71%, specificity 98%, accuracy 93%, and AUC 0.849). POC-ECV had excellent test-retest (ICC 0.994, 95%CI[0.987, 0.997]) and inter-observer agreement (ICC 0.974, 95%CI[0.929, 0.991]).

CONCLUSIONS

Myocardial ECV can be accurately and reproducibly calculated with input of hematocrit measured using a noninvasive POC device, potentially overcoming an important barrier to implementation of ECV. Further evaluation of synthetic ECV is required prior to clinical implementation.

Blood T1* correction increases accuracy of extracellular volume measurements using 3T cardiovascular magnetic resonance: Comparison of T1 and T1* maps

The goals were to compare the differences between ECV_L (extracellular volume derived from myocardial T1 and blood T1), ECV_c (combination of myocardial T1 and blood T1*), and ECVnL (derived from myocardium T1* and blood T1*), and to explore the diagnostic accuracy of these factors for discriminating between controls and patients. The Modified Look-Locker Inversion Recovery sequence was performed in 42 subjects to generate both T1 and T1* maps. Native and post-contrast T1 values for myocardium and blood pool were obtained, and ECVL, ECVc, and ECVnL were then calculated. The global ECVc values were smaller than the ECVL values (0.006, 2.11%, p < 0.001) and larger than the ECVnL values (0.06, 21.6%, p < 0.001) in all participants. The ECVc led to a 4–6% increase in the AUC value and a 24–32% reduction in the sample size to differentiate between the controls and other patients when compared with the ECVL. Blood T1* correction can improve the precision of blood T1 values and can consequently increase the accuracy of the extracellular volume fraction measurement. The ECVc can be used to improve diagnostic accuracy and reduce the sample size required for a clinical study.

Myocardial T1 mapping and extracellular volume quantification: an overview of technical and biological confounders

Novel tissue biomarkers based on the spin–lattice relaxation time T1, a fundamental property in the theory of magnetic resonance physics, have emerged as a new approach for myocardial tissue characterization with many validated clinical applications. This article is intended as an overview of the physical and physiological mechanisms underlying the interpretation and the accuracy of any practical measurement of T1, or derived biomarkers such as extravascular volume fraction, and also includes a discussion of potential pitfalls. Numerous caveats und knowledge gaps related to the precise interpretation of T1-based biomarkers remain, which are being addressed incrementally through ongoing research. Equally important, further careful standardization will pave the way for a wider clinical translation of these novel T1-based biomarkers of tissue remodeling, which have been well validated for their sensitivity to pathophysiological changes, though for the most part in single-center studies.