Quality assurance of quantitative cardiac T1-mapping in multicenter clinical trials - A T1 phantom program from the hypertrophic cardiomyopathy registry (HCMR) study

Intravenous iron therapy results in rapid and sustained rise in myocardial iron content through a novel pathway

BACKGROUND AND AIMS

Intravenous iron therapies contain iron-carbohydrate complexes, designed to ensure iron becomes bioavailable via the intermediary of spleen and liver reticuloendothelial macrophages. How other tissues obtain and handle this iron remains unknown. This study addresses this question in the context of the heart.

METHODS

A prospective observational study was conducted in 12 patients receiving ferric carboxymaltose (FCM) for iron deficiency. Myocardial, spleen, and liver magnetic resonance relaxation times and plasma iron markers were collected longitudinally. To examine the handling of iron taken up by the myocardium, intracellular labile iron pool (LIP) was imaged in FCM-treated mice and cells.

RESULTS

In patients, myocardial relaxation time T1 dropped maximally 3 h post-FCM, remaining low 42 days later, while splenic T1 dropped maximally at 14 days, recovering by 42 days. In plasma, non-transferrin-bound iron (NTBI) peaked at 3 h, while ferritin peaked at 14 days. Changes in liver T1 diverged among patients. In mice, myocardial LIP rose 1 h and remained elevated 42 days after FCM. In cardiomyocytes, FCM exposure raised LIP rapidly. This was prevented by inhibitors of NTBI transporters T-type and L-type calcium channels and divalent metal transporter 1.

CONCLUSIONS

Intravenous iron therapy with FCM delivers iron to the myocardium rapidly through NTBI transporters, independently of reticuloendothelial macrophages. This iron remains labile for weeks, reflecting the myocardium's limited iron storage capacity. These findings challenge current notions of how the heart obtains iron from these therapies and highlight the potential for long-term dosing to cause cumulative iron build-up in the heart.

Cardiovascular Magnetic Resonance Before Invasive Coronary Angiography in Suspected Non-ST-Segment Elevation Myocardial Infarction

BACKGROUND

In suspected non-ST-segment elevation myocardial infarction (NSTEMI), this presumed diagnosis may not hold true in all cases, particularly in patients with nonobstructive coronary arteries (NOCA). Additionally, in multivessel coronary artery disease, the presumed infarct-related artery may be incorrect.

OBJECTIVES

This study sought to assess the diagnostic utility of cardiac magnetic resonance (CMR) before invasive coronary angiogram (ICA) in suspected NSTEMI.

METHODS

A total of 100 consecutive stable patients with suspected acute NSTEMI (70% male, age 62 ± 11 years) prospectively underwent CMR pre-ICA to assess cardiac function (cine), edema (T2-weighted imaging, T1 mapping), and necrosis/scar (late gadolinium enhancement). CMR images were interpreted blinded to ICA findings. The clinical care and ICA teams were blinded to CMR findings until post-ICA.

RESULTS

Early CMR (median 33 hours postadmission and 4 hours pre-ICA) confirmed only 52% (52 of 100) of patients had subendocardial infarction, 15% transmural infarction, 18% nonischemic pathologies (myocarditis, Takotsubo and other forms of cardiomyopathies), and 11% normal CMR; 4% were nondiagnostic. Subanalyses according to ICA findings showed that, in patients with obstructive coronary artery disease (73 of 100), CMR confirmed only 84% (61 of 73) had MI, 10% (7 of 73) nonischemic pathologies, and 5% (4 of 73) normal. In patients with NOCA (27 of 100), CMR found MI in only 22% (6 of 27 true MI with NOCA), and reclassified the presumed diagnosis of NSTEMI in 67% (18 of 27: 11 nonischemic pathologies, 7 normal). In patients with CMR-MI and obstructive coronary artery disease (61 of 100), CMR identified a different infarct-related artery in 11% (7 of 61).

CONCLUSIONS

In patients presenting with suspected NSTEMI, a CMR-first strategy identified MI in 67%, nonischemic pathologies in 18%, and normal findings in 11%. Accordingly, CMR has the potential to affect at least 50% of all patients by reclassifying their diagnosis or altering their potential management.

Misclassification of females and males in cardiovascular magnetic resonance parametric mapping: the importance of sex-specific normal ranges for diagnosis of health vs. disease

AIMS

Cardiovascular magnetic resonance parametric mapping enables non-invasive quantitative myocardial tissue characterization. Human myocardium has normal ranges of T1 and T2 values, deviation from which may indicate disease or change in physiology. Normal myocardial T1 and T2 values are affected by biological sex. Consequently, normal ranges created with insufficient numbers of each sex may result in sampling biases, misclassification of healthy values vs. disease, and even misdiagnoses. In this study, we investigated the impact of using male normal ranges for classifying female cases as normal or abnormal (and vice versa).

METHODS AND RESULTS

One hundred and forty-two healthy volunteers (male and female) were scanned on two Siemens 3T MR systems, providing averaged global myocardial T1 and T2 values on a per-subject basis. The Monte Carlo method was used to generate simulated normal ranges from these values to estimate the statistical accuracy of classifying healthy female or male cases correctly as 'normal' when using sex-specific vs. mixed-sex normal ranges. The normal male and female T1- and T2-mapping values were significantly different by sex, after adjusting for age and heart rate.

CONCLUSION

Using 15 healthy volunteers who are not sex specific to establish a normal range resulted in a typical misclassification of up to 36% of healthy females and 37% of healthy males as having abnormal T1 values and up to 16% of healthy females and 12% of healthy males as having abnormal T2 values. This paper highlights the potential adverse impact on diagnostic accuracy that can occur when local normal ranges contain insufficient numbers of both sexes. Sex-specific reference ranges should thus be routinely adopted in clinical practice.

Image-Based Biological Heart Age Estimation Reveals Differential Aging Patterns Across Cardiac Chambers

BACKGROUND

Biological heart age estimation can provide insights into cardiac aging. However, existing studies do not consider differential aging across cardiac regions.

PURPOSE

To estimate biological age of the left ventricle (LV), right ventricle (RV), myocardium, left atrium, and right atrium using magnetic resonance imaging radiomics phenotypes and to investigate determinants of aging by cardiac region.

STUDY TYPE

Cross-sectional.

POPULATION

A total of 18,117 healthy UK Biobank participants including 8338 men (mean age = 64.2 ± 7.5) and 9779 women (mean age = 63.0 ± 7.4).

FIELD STRENGTH/SEQUENCE

A 1.5 T/balanced steady-state free precession.

ASSESSMENT

An automated algorithm was used to segment the five cardiac regions, from which radiomic features were extracted. Bayesian ridge regression was used to estimate biological age of each cardiac region with radiomics features as predictors and chronological age as the output. The "age gap" was the difference between biological and chronological age. Linear regression was used to calculate associations of age gap from each cardiac region with socioeconomic, lifestyle, body composition, blood pressure and arterial stiffness, blood biomarkers, mental well-being, multiorgan health, and sex hormone exposures (n = 49).

STATISTICAL TEST

Multiple testing correction with false discovery method (threshold = 5%).

RESULTS

The largest model error was with RV and the smallest with LV age (mean absolute error in men: 5.26 vs. 4.96 years). There were 172 statistically significant age gap associations. Greater visceral adiposity was the strongest correlate of larger age gaps, for example, myocardial age gap in women (Beta = 0.85, P = 1.69 × 10-26 ). Poor mental health associated with large age gaps, for example, "disinterested" episodes and myocardial age gap in men (Beta = 0.25, P = 0.001), as did a history of dental problems (eg LV in men Beta = 0.19, P = 0.02). Higher bone mineral density was the strongest associate of smaller age gaps, for example, myocardial age gap in men (Beta = -1.52, P = 7.44 × 10-6 ).

DATA CONCLUSION

This work demonstrates image-based heart age estimation as a novel method for understanding cardiac aging.

EVIDENCE LEVEL

1.

TECHNICAL EFFICACY

Stage 1.

Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images

Background

Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for non-invasive myocardial tissue characterisation. However, accurate segmentation of the left ventricular (LV) myocardium remains a challenge due to limited training data and lack of quality control. This study addresses these issues by leveraging generative adversarial networks (GAN)-generated virtual native enhancement (VNE) images to expand the training set and incorporating an automated quality control-driven (QCD) framework to improve segmentation reliability.

Methods

A dataset comprising 4,716 LGE images (from 1,363 patients with hypertrophic cardiomyopathy and myocardial infarction) was used for development. To generate additional clinically validated data, LGE data were augmented with a GAN-based generator to produce VNE images. LV was contoured on these images manually by clinical observers. To create diverse candidate segmentations, the QCD framework involved multiple U-Nets, which were combined using statistical rank filters. The framework predicted the Dice Similarity Coefficient (DSC) for each candidate segmentation, with the highest predicted DSC indicating the most accurate and reliable result. The performance of the QCD ensemble framework was evaluated on both LGE and VNE test datasets (309 LGE/VNE images from 103 patients), assessing segmentation accuracy (DSC) and quality prediction (mean absolute error (MAE) and binary classification accuracy).

Results

The QCD framework effectively and rapidly segmented the LV myocardium (<1 s per image) on both LGE and VNE images, demonstrating robust performance on both test datasets with similar mean DSC (LGE: 0.845 ± 0.075 ; VNE: 0.845 ± 0.071 ; p = n s ). Incorporating GAN-generated VNE data into the training process consistently led to enhanced performance for both individual models and the overall framework. The quality control mechanism yielded a high performance (MAE = 0.043 , accuracy = 0.951 ) emphasising the accuracy of the quality control-driven strategy in predicting segmentation quality in clinical settings. Overall, no statistical difference (p = n s ) was found when comparing the LGE and VNE test sets across all experiments.

Conclusions

The QCD ensemble framework, leveraging GAN-generated VNE data and an automated quality control mechanism, significantly improved the accuracy and reliability of LGE segmentation, paving the way for enhanced and accountable diagnostic imaging in routine clinical use.

Incident Clinical and Mortality Associations of Myocardial Native T1 in the UK Biobank

BACKGROUND

Cardiac magnetic resonance native T1-mapping provides noninvasive, quantitative, and contrast-free myocardial characterization. However, its predictive value in population cohorts has not been studied.

OBJECTIVES

The associations of native T1 with incident events were evaluated in 42,308 UK Biobank participants over 3.17 ± 1.53 years of prospective follow-up.

METHODS

Native T1-mapping was performed in 1 midventricular short-axis slice using the Shortened Modified Look-Locker Inversion recovery technique (WIP780B) in 1.5-T scanners (Siemens Healthcare). Global myocardial T1 was calculated using an automated tool. Associations of T1 with: 1) prevalent risk factors (eg, diabetes, hypertension, and high cholesterol); 2) prevalent and incident diseases (eg, any cardiovascular disease [CVD], any brain disease, valvular heart disease, heart failure, nonischemic cardiomyopathies, cardiac arrhythmias, atrial fibrillation [AF], myocardial infarction, ischemic heart disease [IHD], and stroke); and 3) mortality (eg, all-cause, CVD, and IHD) were examined. Results are reported as odds ratios (ORs) or HRs per SD increment of T1 value with 95% CIs and corrected P values, from logistic and Cox proportional hazards regression models.

RESULTS

Higher myocardial T1 was associated with greater odds of a range of prevalent conditions (eg, any CVD, brain disease, heart failure, nonischemic cardiomyopathies, AF, stroke, and diabetes). The strongest relationships were with heart failure (OR: 1.41 [95% CI: 1.26-1.57]; P = 1.60 × 10-9) and nonischemic cardiomyopathies (OR: 1.40 [95% CI: 1.16-1.66]; P = 2.42 × 10-4). Native T1 was positively associated with incident AF (HR: 1.25 [95% CI: 1.10-1.43]; P = 9.19 × 10-4), incident heart failure (HR: 1.47 [95% CI: 1.31-1.65]; P = 4.79 × 10-11), all-cause mortality (HR: 1.24 [95% CI: 1.12-1.36]; P = 1.51 × 10-5), CVD mortality (HR: 1.40 [95% CI: 1.14-1.73]; P = 0.0014), and IHD mortality (HR: 1.36 [95% CI: 1.03-1.80]; P = 0.0310).

CONCLUSIONS

This large population study demonstrates the utility of myocardial native T1-mapping for disease discrimination and outcome prediction.

Cardiovascular magnetic resonance for evaluation of cardiac involvement in COVID-19: recommendations by the Society for Cardiovascular Magnetic Resonance

Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has affected nearly 600 million people to date across the world. While COVID-19 is primarily a respiratory illness, cardiac injury is also known to occur. Cardiovascular magnetic resonance (CMR) imaging is uniquely capable of characterizing myocardial tissue properties in-vivo, enabling insights into the pattern and degree of cardiac injury. The reported prevalence of myocardial involvement identified by CMR in the context of COVID-19 infection among previously hospitalized patients ranges from 26 to 60%. Variations in the reported prevalence of myocardial involvement may result from differing patient populations (e.g. differences in severity of illness) and the varying intervals between acute infection and CMR evaluation. Standardized methodologies in image acquisition, analysis, interpretation, and reporting of CMR abnormalities across would likely improve concordance between studies. This consensus document by the Society for Cardiovascular Magnetic Resonance (SCMR) provides recommendations on CMR imaging and reporting metrics towards the goal of improved standardization and uniform data acquisition and analytic approaches when performing CMR in patients with COVID-19 infection.

Fast, interleaved, Look-Locker-based T1 mapping with a variable averaging approach: Towards temperature mapping at low magnetic field

Proton resonance frequency shift (PRFS) is currently the gold standard method for magnetic resonance thermometry. However, the linearity between the temperature-dependent phase accumulation and the static magnetic field B₀ confines its use to rather high-field scanners. Applications such as thermal therapies could naturally benefit from lower field MRI settings through leveraging increased accessibility, a lower physical and economical footprint, and further consideration of the technical challenges associated with the integration of heating systems into conventional clinical scanners. T 1 -based thermometry has been proposed as an alternative to the gold standard; however, because of longer acquisition times, it has found clinical use solely with adipose tissue where PRFS fails. At low field, the enhanced T 1 dispersion, combined with reduced relaxation times, make T 1 mapping an appealing candidate. Here, an interleaved Look-Locker-based T 1 mapping sequence was proposed for temperature quantification at 0.1 T. A variable averaging scheme was introduced, to maximize the signal-to-noise ratio throughout T 1 recovery. In calibrated samples, an average T 1 accuracy of 85% ± 4% was achieved in 10 min, compared with the 77% ± 7% obtained using a standard averaging scheme. Temperature maps between 29.0 and 41.7°C were eventually reconstructed, with a precision of 3.0 ± 1.1°C and an accuracy of 1.5 ± 1.0°C. Accounting for longer thermal treatments and less strict temperature constraints, applications such as MR-guided mild hyperthermia treatments at low field could be envisioned.

Acute Response in the Noninfarcted Myocardium Predicts Long-Term Major Adverse Cardiac Events After STEMI

BACKGROUND

Acute ST-segment elevation myocardial infarction (STEMI) has effects on the myocardium beyond the immediate infarcted territory. However, pathophysiologic changes in the noninfarcted myocardium and their prognostic implications remain unclear.

OBJECTIVES

The purpose of this study was to evaluate the long-term prognostic value of acute changes in both infarcted and noninfarcted myocardium post-STEMI.

METHODS

Patients with acute STEMI undergoing primary percutaneous coronary intervention underwent evaluation with blood biomarkers and cardiac magnetic resonance (CMR) at 2 days and 6 months, with long-term follow-up for major adverse cardiac events (MACE). A comprehensive CMR protocol included cine, T2-weighted, T2∗, T1-mapping, and late gadolinium enhancement (LGE) imaging. Areas without LGE were defined as noninfarcted myocardium. MACE was a composite of cardiac death, sustained ventricular arrhythmia, and new-onset heart failure.

RESULTS

Twenty-two of 219 patients (10%) experienced an MACE at a median of 4 years (IQR: 2.5-6.0 years); 152 patients returned for the 6-month visit. High T1 (>1250 ms) in the noninfarcted myocardium was associated with lower left ventricular ejection fraction (LVEF) (51% ± 8% vs 55% ± 9%; P = 0.002) and higher NT-pro-BNP levels (290 pg/L [IQR: 103-523 pg/L] vs 170 pg/L [IQR: 61-312 pg/L]; P = 0.008) at 6 months and a 2.5-fold (IQR: 1.03-6.20) increased risk of MACE (2.53 [IQR: 1.03-6.22]), compared with patients with normal T1 in the noninfarcted myocardium (P = 0.042). A lower T1 (<1,300 ms) in the infarcted myocardium was associated with increased MACE (3.11 [IQR: 1.19-8.13]; P = 0.020). Both noninfarct and infarct T1 were independent predictors of MACE (both P = 0.001) and significantly improved risk prediction beyond LVEF, infarct size, and microvascular obstruction (C-statistic: 0.67 ± 0.07 vs 0.76 ± 0.06, net-reclassification index: 40% [IQR: 12%-64%]; P = 0.007).

CONCLUSIONS

The acute responses post-STEMI in both infarcted and noninfarcted myocardium are independent incremental predictors of long-term MACE. These insights may provide new opportunities for treatment and risk stratification in STEMI.

Imaging Methods: Magnetic Resonance Imaging

Myocardial inflammation occurs following activation of the cardiac immune system, producing characteristic changes in the myocardial tissue. Cardiovascular magnetic resonance is the non-invasive imaging gold standard for myocardial tissue characterization, and is able to detect image signal changes that may occur resulting from inflammation, including edema, hyperemia, capillary leak, necrosis, and fibrosis. Conventional cardiovascular magnetic resonance for the detection of myocardial inflammation and its sequela include T2-weighted imaging, parametric T1- and T2-mapping, and gadolinium-based contrast-enhanced imaging. Emerging techniques seek to image several parameters simultaneously for myocardial tissue characterization, and to depict subtle immune-mediated changes, such as immune cell activity in the myocardium and cardiac cell metabolism. This review article outlines the underlying principles of current and emerging cardiovascular magnetic resonance methods for imaging myocardial inflammation.

Artificial Intelligence for Contrast-Free MRI: Scar Assessment in Myocardial Infarction Using Deep Learning-Based Virtual Native Enhancement

BACKGROUND

Myocardial scars are assessed noninvasively using cardiovascular magnetic resonance late gadolinium enhancement (LGE) as an imaging gold standard. A contrast-free approach would provide many advantages, including a faster and cheaper scan without contrast-associated problems.

METHODS

Virtual native enhancement (VNE) is a novel technology that can produce virtual LGE-like images without the need for contrast. VNE combines cine imaging and native T1 maps to produce LGE-like images using artificial intelligence. VNE was developed for patients with previous myocardial infarction from 4271 data sets (912 patients); each data set comprises slice position-matched cine, T1 maps, and LGE images. After quality control, 3002 data sets (775 patients) were used for development and 291 data sets (68 patients) for testing. The VNE generator was trained using generative adversarial networks, using 2 adversarial discriminators to improve the image quality. The left ventricle was contoured semiautomatically. Myocardial scar volume was quantified using the full width at half maximum method. Scar transmurality was measured using the centerline chord method and visualized on bull's-eye plots. Lesion quantification by VNE and LGE was compared using linear regression, Pearson correlation (R), and intraclass correlation coefficients. Proof-of-principle histopathologic comparison of VNE in a porcine model of myocardial infarction also was performed.

RESULTS

VNE provided significantly better image quality than LGE on blinded analysis by 5 independent operators on 291 data sets (all P<0.001). VNE correlated strongly with LGE in quantifying scar size (R, 0.89; intraclass correlation coefficient, 0.94) and transmurality (R, 0.84; intraclass correlation coefficient, 0.90) in 66 patients (277 test data sets). Two cardiovascular magnetic resonance experts reviewed all test image slices and reported an overall accuracy of 84% for VNE in detecting scars when compared with LGE, with specificity of 100% and sensitivity of 77%. VNE also showed excellent visuospatial agreement with histopathology in 2 cases of a porcine model of myocardial infarction.

CONCLUSIONS

VNE demonstrated high agreement with LGE cardiovascular magnetic resonance for myocardial scar assessment in patients with previous myocardial infarction in visuospatial distribution and lesion quantification with superior image quality. VNE is a potentially transformative artificial intelligence-based technology with promise in reducing scan times and costs, increasing clinical throughput, and improving the accessibility of cardiovascular magnetic resonance in the near future.

Determination of oxygen relaxivity in oxygen nanobubbles at 3 and 7 Tesla

OBJECTIVE

Oxygen-loaded nanobubbles have shown potential for reducing tumour hypoxia and improving treatment outcomes, however, it remains difficult to noninvasively measure the changes in partial pressure of oxygen (PO₂) in vivo. The linear relationship between PO₂ and longitudinal relaxation rate (R₁) has been used to noninvasively infer PO₂ in vitreous and cerebrospinal fluid, and therefore, this experiment aimed to investigate whether R₁ is a suitable measurement to study oxygen delivery from such oxygen carriers.

METHODS

T₁ mapping was used to measure R₁ in phantoms containing nanobubbles with varied PO₂ to measure the relaxivity of oxygen (r_1Ox) in the phantoms at 7 and 3 T. These measurements were used to estimate the limit of detection (LOD) in two experimental settings: preclinical 7 T and clinical 3 T MRI.

RESULTS

The r_1Ox in the nanobubble solution was 0.00057 and 0.000235 s^-1/mmHg, corresponding to a LOD of 111 and 103 mmHg with 95% confidence at 7 and 3 T, respectively.

CONCLUSION

This suggests that T₁ mapping could provide a noninvasive method of measuring a > 100 mmHg oxygen delivery from therapeutic nanobubbles.

Clinical translation of quantitative magnetic resonance imaging biomarkers - An overview and gap analysis of current practice

PURPOSE

This overview of the current landscape of quantitative magnetic resonance imaging biomarkers (qMR IBs) aims to support the standardisation of academic IBs to assist their translation to clinical practice.

METHODS

We used three complementary approaches to investigate qMR IB use and quality management practices within the UK: 1) a literature search of qMR and quality management terms during 2011-2015 and 2016-2020; 2) a database search for clinical research studies using qMR IBs during 2016-2020; and 3) a survey to ascertain the current availability and quality management practices for clinical MRI scanners and associated equipment at research institutions across the UK.

RESULTS

The analysis showed increased use of all qMR methods between the periods 2011-2015 and 2016-2020 and diffusion-tensor MRI and volumetry to be popular methods. However, the "translation ratio" of journal articles to clinical research studies was higher for qMR methods that have evidence of clinical translation via a commercial route, such as fat fraction and T2 mapping. The number of journal articles citing quality management terms doubled between the periods 2011-2015 and 2016-2020; although, its proportion relative to all journal articles only increased by 3.0%. The survey suggested that quality assurance (QA) and quality control (QC) of data acquisition procedures are under-reported in the literature and that QA/QC of acquired data/data analysis are under-developed and lack consistency between institutions.

CONCLUSIONS

We summarise current attempts to standardise and translate qMR IBs, and conclude by outlining the ideal quality management practices and providing a gap analysis between current practice and a metrological standard.

Phantom-based correction for standardization of myocardial native T1 and extracellular volume fraction in healthy subjects at 3-Tesla cardiac magnetic resonance imaging

OBJECTIVES

To investigate the effect of the phantom-based correction method for standardizing myocardial native T1 and extracellular volume fraction (ECV) in healthy subjects.

METHODS

Seventy-one healthy asymptomatic adult (≥ 20 years) volunteers of five different age groups (34 men and 37 women, 45.5 ± 15.5 years) were prospectively enrolled in three academic hospitals. Cardiac MRI including Modified Look - Locker Inversion recovery T1 mapping sequence was performed using a 3-Tesla system with a different type of scanner for each hospital. Native T1 and ECV were measured in the short-axis T1 map and analyzed for mean values of the 16 entire segments. The myocardial T1 value of each subject was corrected based on the site-specific equation derived from the T1 Mapping and ECV Standardization phantom. The global native T1 and ECV were compared between institutions before and after phantom-based correction, and the variation in native T1 and ECV among institutions was assessed using a coefficient of variation (CoV).

RESULTS

The global native T1 value significantly differed between the institutions (1198.7 ± 32.1 ms, institution A; 1217.7 ± 39.9 ms, institution B; 1232.7 ± 31.1 ms, institution C; p = 0.002), but the mean ECV did not (26.6-27.5%, p = 0.355). After phantom-based correction, the global native T1 and ECV were 1289.7 ± 32.4 ms and 25.0 ± 2.7%, respectively, and CoV for native T1 between the three institutions decreased from 3.0 to 2.5%. The corrected native T1 value did not significantly differ between institutions (1284.5 ± 31.5 ms, institution A; 1296.5 ± 39.1 ms, institution B; 1291.3 ± 29.3 ms, institution C; p = 0.440), and neither did the ECV (24.4-25.9%, p = 0.078).

CONCLUSIONS

The phantom-based correction method can provide standardized reference T1 values in healthy subjects.

KEY POINTS

• After phantom-based correction, the global native T1 of 16 entire myocardial segments on 3-T cardiac MRI is 1289.4 ± 32.4 ms, and the extracellular volume fraction was 25.0 ± 2.7% for healthy subjects. • After phantom - based correction was applied, the differences in the global native T1 among institutions became insignificant, and the CoV also decreased from 3.0 to 2.5%.

MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks

Background: Quantitative cardiovascular magnetic resonance (CMR) T1 mapping has shown promise for advanced tissue characterisation in routine clinical practise. However, T1 mapping is prone to motion artefacts, which affects its robustness and clinical interpretation. Current methods for motion correction on T1 mapping are model-driven with no guarantee on generalisability, limiting its widespread use. In contrast, emerging data-driven deep learning approaches have shown good performance in general image registration tasks. We propose MOCOnet, a convolutional neural network solution, for generalisable motion artefact correction in T1 maps.

Methods: The network architecture employs U-Net for producing distance vector fields and utilises warping layers to apply deformation to the feature maps in a coarse-to-fine manner. Using the UK Biobank imaging dataset scanned at 1.5T, MOCOnet was trained on 1,536 mid-ventricular T1 maps (acquired using the ShMOLLI method) with motion artefacts, generated by a customised deformation procedure, and tested on a different set of 200 samples with a diverse range of motion. MOCOnet was compared to a well-validated baseline multi-modal image registration method. Motion reduction was visually assessed by 3 human experts, with motion scores ranging from 0% (strictly no motion) to 100% (very severe motion).

Results: MOCOnet achieved fast image registration (<1 second per T1 map) and successfully suppressed a wide range of motion artefacts. MOCOnet significantly reduced motion scores from 37.1±21.5 to 13.3±10.5 (p < 0.001), whereas the baseline method reduced it to 15.8±15.6 (p < 0.001). MOCOnet was significantly better than the baseline method in suppressing motion artefacts and more consistently (p = 0.007).

Conclusion: MOCOnet demonstrated significantly better motion correction performance compared to a traditional image registration approach. Salvaging data affected by motion with robustness and in a time-efficient manner may enable better image quality and reliable images for immediate clinical interpretation.

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy

BACKGROUND

Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to develop a contrast agent-free technology to replace LGE for faster and cheaper CMR scans.

METHODS

A CMR virtual native enhancement (VNE) imaging technology was developed using artificial intelligence. The deep learning model for generating VNE uses multiple streams of convolutional neural networks to exploit and enhance the existing signals in native T1 maps (pixel-wise maps of tissue T1 relaxation times) and cine imaging of cardiac structure and function, presenting them as LGE-equivalent images. The VNE generator was trained using generative adversarial networks. This technology was first developed on CMR datasets from the multicenter Hypertrophic Cardiomyopathy Registry, using hypertrophic cardiomyopathy as an exemplar. The datasets were randomized into 2 independent groups for deep learning training and testing. The test data of VNE and LGE were scored and contoured by experienced human operators to assess image quality, visuospatial agreement, and myocardial lesion burden quantification. Image quality was compared using a nonparametric Wilcoxon test. Intra- and interobserver agreement was analyzed using intraclass correlation coefficients (ICC). Lesion quantification by VNE and LGE were compared using linear regression and ICC.

RESULTS

A total of 1348 hypertrophic cardiomyopathy patients provided 4093 triplets of matched T1 maps, cines, and LGE datasets. After randomization and data quality control, 2695 datasets were used for VNE method development and 345 were used for independent testing. VNE had significantly better image quality than LGE, as assessed by 4 operators (n=345 datasets; P<0.001 [Wilcoxon test]). VNE revealed lesions characteristic of hypertrophic cardiomyopathy in high visuospatial agreement with LGE. In 121 patients (n=326 datasets), VNE correlated with LGE in detecting and quantifying both hyperintensity myocardial lesions (r=0.77-0.79; ICC=0.77-0.87; P<0.001) and intermediate-intensity lesions (r=0.70-0.76; ICC=0.82-0.85; P<0.001). The native CMR images (cine plus T1 map) required for VNE can be acquired within 15 minutes and producing a VNE image takes less than 1 second.

CONCLUSIONS

VNE is a new CMR technology that resembles conventional LGE but without the need for contrast administration. VNE achieved high agreement with LGE in the distribution and quantification of lesions, with significantly better image quality.

Multi-site, multi-platform comparison of MRI T1 measurement using the system phantom

Recent innovations in quantitative magnetic resonance imaging (MRI) measurement methods have led to improvements in accuracy, repeatability, and acquisition speed, and have prompted renewed interest to reevaluate the medical value of quantitative T₁. The purpose of this study was to determine the bias and reproducibility of T₁ measurements in a variety of MRI systems with an eye toward assessing the feasibility of applying diagnostic threshold T₁ measurement across multiple clinical sites. We used the International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) system phantom to assess variations of T₁ measurements, using a slow, reference standard inversion recovery sequence and a rapid, commonly-available variable flip angle sequence, across MRI systems at 1.5 tesla (T) (two vendors, with number of MRI systems n = 9) and 3 T (three vendors, n = 18). We compared the T₁ measurements from inversion recovery and variable flip angle scans to ISMRM/NIST phantom reference values using Analysis of Variance (ANOVA) to test for statistical differences between T₁ measurements grouped according to MRI scanner manufacturers and/or static field strengths. The inversion recovery method had minor over- and under-estimations compared to the NMR-measured T₁ values at both 1.5 T and 3 T. Variable flip angle measurements had substantially greater deviations from the NMR-measured T₁ values than the inversion recovery measurements. At 3 T, the measured variable flip angle T₁ for one vendor is significantly different than the other two vendors for most of the samples throughout the clinically relevant range of T₁. There was no consistent pattern of discrepancy between vendors. We suggest establishing rigorous quality control procedures for validating quantitative MRI methods to promote confidence and stability in associated measurement techniques and to enable translation of diagnostic threshold from the research center to the entire clinical community.

Demographic, multi-morbidity and genetic impact on myocardial involvement and its recovery from COVID-19: protocol design of COVID-HEART-a UK, multicentre, observational study

BACKGROUND

Although coronavirus disease 2019 (COVID-19) is primarily a respiratory illness, myocardial injury is increasingly reported and associated with adverse outcomes. However, the pathophysiology, extent of myocardial injury and clinical significance remains unclear.

METHODS

COVID-HEART is a UK, multicentre, prospective, observational, longitudinal cohort study of patients with confirmed COVID-19 and elevated troponin (sex-specific > 99th centile). Baseline assessment will be whilst recovering in-hospital or recently discharged, and include cardiovascular magnetic resonance (CMR) imaging, quality of life (QoL) assessments, electrocardiogram (ECG), serum biomarkers and genetics. Assessment at 6-months includes repeat CMR, QoL assessments and 6-min walk test (6MWT). The CMR protocol includes cine imaging, T1/T2 mapping, aortic distensibility, late gadolinium enhancement (LGE), and adenosine stress myocardial perfusion imaging in selected patients. The main objectives of the study are to: (1) characterise the extent and nature of myocardial involvement in COVID-19 patients with an elevated troponin, (2) assess how cardiac involvement and clinical outcome associate with recognised risk factors for mortality (age, sex, ethnicity and comorbidities) and genetic factors, (3) evaluate if differences in myocardial recovery at 6 months are dependent on demographics, genetics and comorbidities, (4) understand the impact of recovery status at 6 months on patient-reported QoL and functional capacity.

DISCUSSION

COVID-HEART will provide detailed characterisation of cardiac involvement, and its repair and recovery in relation to comorbidity, genetics, patient-reported QoL measures and functional capacity.

CLINICAL TRIAL REGISTRATION

ISRCTN 58667920. Registered 04 August 2020.

Comparison between cardiac magnetic resonance stress T1 mapping and [15O]H2O positron emission tomography in patients with suspected obstructive coronary artery disease

AIMS

To compare cardiac magnetic resonance (CMR) measurement of T1 reactivity (ΔT1) with [15O]H2O positron emission tomography (PET) measurements of quantitative myocardial perfusion.

METHODS AND RESULTS

Forty-three patients with suspected obstructed coronary artery disease underwent [15O]H2O PET and CMR at 1.5-T, including rest and adenosine stress T1 mapping (ShMOLLI) and late gadolinium enhancement to rule out presence of scar tissue. ΔT1 was determined for the three main vascular territories and compared with [15O]H2O PET-derived regional stress myocardial blood flow (MBF) and myocardial flow reserve (MFR). ΔT1 showed a significant but poor correlation with stress MBF (R2 = 0.04, P = 0.03) and MFR (R2 = 0.07, P = 0.004). Vascular territories with impaired stress MBF (i.e. ≤2.30 mL/min/g) demonstrated attenuated ΔT1 compared with vascular territories with preserved stress MBF (2.9 ± 2.2% vs. 4.1 ± 2.2%, P = 0.008). In contrast, ΔT1 did not differ between vascular territories with impaired (i.e. <2.50) and preserved MFR (3.2 ± 2.6% vs. 4.0 ± 2.1%, P = 0.25). Receiver operating curve analysis of ΔT1 resulted in an area under the curve of 0.66 [95% confidence interval (CI): 0.57-0.75, P = 0.009] for diagnosing impaired stress MBF and 0.62 (95% CI: 0.53-0.71, P = 0.07) for diagnosing impaired MFR.

CONCLUSIONS

CMR stress T1 mapping has poor agreement with [15O]H2O PET measurements of absolute myocardial perfusion. Stress T1 and ΔT1 are lower in vascular territories with reduced stress MBF but have poor accuracy for detecting impaired myocardial perfusion.

Cardiovascular magnetic resonance stress and rest T1-mapping using regadenoson for detection of ischemic heart disease compared to healthy controls

Background

Adenosine stress T1-mapping on cardiovascular magnetic resonance (CMR) can differentiate between normal, ischemic, infarcted, and remote myocardial tissue classes without the need for contrast agents. Regadenoson, a selective coronary vasodilator, is often used in stress perfusion imaging when adenosine is contra-indicated, and has advantages in ease of administration, safety profile, and clinical workflow. We aimed to characterize the regadenoson stress T1-mapping response in healthy individuals, and to investigate its ability to differentiate between myocardial tissue classes in patients with coronary artery disease (CAD).

Methods

Eleven healthy controls and 25 patients with CAD underwent regadenoson stress perfusion CMR, as well as rest and stress ShMOLLI T1-mapping. Native T1 values and stress T1 reactivity were derived for normal myocardium in healthy controls and for different myocardial tissue classes in patients with CAD.

Results

Healthy controls had normal myocardial native T1 values at rest (931 ± 22 ms) with significant global regadenoson stress T1 reactivity (δT1 = 8.2 ± 0.8% relative to baseline; p < 0.0001). Infarcted myocardium had significantly higher resting T1 (1215 ± 115 ms) than ischemic, remote, and normal myocardium (all p < 0.0001) with an abolished stress T1 response (δT1 = −0.8% [IQR: −1.9–0.5]). Ischemic myocardium had elevated resting T1 compared to normal (964 ± 57 ms; p < 0.01) with an abolished stress T1 response (δT1 = 0.5 ± 1.6%). Remote myocardium in patients had comparable resting T1 to normal (949 ms [IQR: 915–973]; p = 0.06) with blunted stress reactivity (δT1 = 4.3% [IQR: 3.1–6.3]; p < 0.0001).

Conclusions

Healthy controls demonstrate significant stress T1 reactivity during regadenoson stress. Regadenoson stress and rest T1-mapping is a viable alternative to adenosine and exercise for the assessment of CAD and can distinguish between normal, ischemic, infarcted, and remote myocardium.

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Regadenoson has advantages over adenosine in terms of administration, safety profile, and clinical workflow.

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There are distinct tissue characteristics for normal, ischemic, infarcted, and remote myocardium.

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Healthy controls demonstrate significant stress T1 reactivity during vasodilator stress.

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Regadenoson stress T1-mapping can distinguish between different myocardial tissue classes.

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Regadenoson stress T1-mapping is a viable alternative to adenosine and exercise for the assessment of coronary artery disease.