Accuracy, precision, and reproducibility of four T1 mapping sequences: a head-to-head comparison of MOLLI, ShMOLLI, SASHA, and SAPPHIRE

Repeatability of Open-MOLLI: An open-source inversion recovery myocardial T1 mapping sequence for fast prototyping

PURPOSE

To develop an open-source prototype of myocardial T1 mapping (Open-MOLLI) to improve accessibility to cardiac T1 mapping and evaluate its repeatability. With Open-MOLLI, we aim to enable faster implementation and testing of sequence modifications and to facilitate inter-scanner and cross-vendor reproducibility studies.

METHODS

Open-MOLLI is an inversion-recovery sequence using a balanced SSFP (bSSFP) readout, with inversion and triggering schemes based on the 5(3)3 MOLLI sequence, developed in Pulseq. Open-MOLLI and MOLLI sequences were acquired in the ISMRM/NIST phantom and 21 healthy volunteers. In 18 of those subjects, Open-MOLLI and MOLLI were repeated in the same session (test-retest).

RESULTS

Phantom T1 values were comparable between methods, specifically for the vial with reference T1 value most similar to healthy myocardium T1 (T1vial3 = 1027 ms): T1MOLLI = 1011 ± 24 ms versus T1Open-MOLLI = 1009 ± 20 ms. In vivo T1 estimates were similar between Open-MOLLI and MOLLI (T1MOLLI = 1004 ± 33 ms vs. T1Open-MOLLI = 998 ± 52 ms), with a mean difference of -17 ms (p = 0.20), despite noisier Open-MOLLI weighted images and maps. Repeatability measures were slightly higher for Open-MOLLI (RCMOLLI = 3.0% vs. RCOpen-MOLLI = 4.4%).

CONCLUSION

The open-source sequence Open-MOLLI can be used for T1 mapping in vivo with similar mean T1 values to the MOLLI method. Open-MOLLI increases the accessibility to cardiac T1 mapping, providing also a base sequence to which further improvements can easily be added and tested.

The diagnostic performance of T1 mapping in the assessment of breast lesions: A preliminary study

PURPOSE

To assess T1 mapping performance in distinguishing between benign and malignant breast lesions and to explore its correlation with histopathologic features in breast cancer.

METHODS

This study prospectively enrolled 103 participants with a total of 108 lesions, including 25 benign and 83 malignant lesions. T1 mapping, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) were performed. Two radiologists independently outlined the ROIs and analyzed T1 and apparent diffusion coefficient (ADC) values for each lesion, assessing interobserver reliability with the intraclass correlation coefficient (ICC). T1 and ADC values were compared between benign and malignant lesions, across different histopathological characteristics (histological grades, estrogen, progesterone and HER2 receptors expression, Ki67, N status). Receiver operating characteristic (ROC) analysis and Pearson correlation coefficient (ρ) were performed.

RESULTS

T1 values showed statistically significant differences between benign and malignant groups (P < 0.001), with higher values in the malignant (1817.08 ms ± 126.64) compared to the benign group (1429.31 ms ± 167.66). In addition, T1 values significantly increased in the ER (-) group (P = 0.001). No significant differences were found in T1 values among HER2, Ki67, N status, and histological grades groups. Furthermore, T1 values exhibited a significant correlation (ρ) with ER (P < 0.01) and PR (P = 0.03). The AUC for T1 value in distinguishing benign from malignant lesions was 0.69 (95 % CI: 0.55 - 0.82, P = 0.005), and for evaluating ER status, it was 0.75 (95 % CI: 0.62 - 0.87, P = 0.002).

CONCLUSIONS

T1 mapping holds the potential as an imaging biomarker to assist in the discrimination of benign and malignant breast lesions and assessing the ER expression status in breast cancer.

Free-breathing, fat-corrected T1 mapping of the liver with stack-of-stars MRI, and joint estimation of T1, PDFF, R 2 * , and B 1 +

PURPOSE

Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat andB 1 + $$ {B}_1^{+} $$ inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition.

THEORY AND METHODS

Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T.

RESULTS

The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps.

CONCLUSION

The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, andB 1 + $$ {B}_1^{+} $$ in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.

Free-breathing 3D whole-heart joint T1/T2 mapping and water/fat imaging at 0.55 T

PURPOSE

To develop and validate a highly efficient motion compensated free-breathing isotropic resolution 3D whole-heart joint T1/T2 mapping sequence with anatomical water/fat imaging at 0.55 T.

METHODS

The proposed sequence takes advantage of shorter T1 at 0.55 T to acquire three interleaved water/fat volumes with inversion-recovery preparation, no preparation, and T2 preparation, respectively. Image navigators were used to facilitate nonrigid motion-compensated image reconstruction. T1 and T2 maps were jointly calculated by a dictionary matching method. Validations were performed with simulation, phantom, and in vivo experiments on 10 healthy volunteers and 1 patient. The performance of the proposed sequence was compared with conventional 2D mapping sequences including modified Look-Locker inversion recovery and T2-prepared balanced steady-SSFP sequence.

RESULTS

The proposed sequence has a good T1 and T2 encoding sensitivity in simulation, and excellent agreement with spin-echo reference T1 and T2 values was observed in a standardized T1/T2 phantom (R2 = 0.99). In vivo experiments provided good-quality co-registered 3D whole-heart T1 and T2 maps with 2-mm isotropic resolution in a short scan time of about 7 min. For healthy volunteers, left-ventricle T1 mean and SD measured by the proposed sequence were both comparable with those of modified Look-Locker inversion recovery (640 ± 35 vs. 630 ± 25 ms [p = 0.44] and 49.9 ± 9.3 vs. 54.4 ± 20.5 ms [p = 0.42]), whereas left-ventricle T2 mean and SD measured by the proposed sequence were both slightly lower than those of T2-prepared balanced SSFP (53.8 ± 5.5 vs. 58.6 ± 3.3 ms [p < 0.01] and 5.2 ± 0.9 vs. 6.1 ± 0.8 ms [p = 0.03]). Myocardial T1 and T2 in the patient measured by the proposed sequence were in good agreement with conventional 2D sequences and late gadolinium enhancement.

CONCLUSION

The proposed sequence simultaneously acquires 3D whole-heart T1 and T2 mapping with anatomical water/fat imaging at 0.55 T in a fast and efficient 7-min scan. Further investigation in patients with cardiovascular disease is now warranted.

Native myocardial T1 mapping using inversion recovery T1-weighted turbo field echo sequence

This study proposes the use of the inversion recovery T1-weighted turbo field echo (IR-T1TFE) sequence for myocardial T1 mapping and compares the results obtained with those of the modified Look-Locker inversion recovery (MOLLI) method for accuracy, precision, and reproducibility. A phantom containing seven vials with different T1 values was imaged, thereby comparing the T1 measurements between the inversion recovery spin-echo (IR-SE) technique, MOLLI, and the IR-T1TFE. The accuracy, precision, and reproducibility of the T1-mapping sequences were analyzed in a phantom study. Fifteen healthy subjects were recruited for the in vivo comparison of native myocardial T1 mapping using MOLLI and IR-T1TFE sequences. After myocardium segmentation, the T1 value of the entire myocardium was calculated. In the phantom study, excellent accuracy was achieved using IR-T1TFE for all T1 ranges. MOLLI displayed lower accuracy than IR-T1TFE (p =0.016), substantially underestimating T1 at large T1 values (> 1000 ms). In the in vivo study, the first mean myocardial T1 values ± SD using MOLLI and IR-T1TFE were 1306 ± 70 ms and 1484 ± 28 ms, respectively, and the second were 1297 ± 68 ms and 1474 ± 43 ms, respectively. The native myocardial T1 obtained with MOLLI was lower than that of IR-T1TFE (p < 0.001). The reproducibility of native myocardial T1 mapping within the same sequence was not statistically significant (p = 0.11). This study demonstrates the utility and validity of myocardial T1 mapping using IR-T1TFE, which is a common sequence. This method was found to have high accuracy and reproducibility.

Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging

Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent heterogeneity of these diseases poses challenges, necessitating advanced analytical methods like radiomics and artificial intelligence. Radiomics extracts quantitative features from medical images, capturing intricate patterns and subtle variations that may elude visual inspection. Artificial intelligence techniques, including deep learning, can analyze these features to generate knowledge, define novel imaging biomarkers, and support diagnostic decision-making and outcome prediction. Radiomics and artificial intelligence thus hold promise for significantly enhancing diagnostic and prognostic capabilities in cardiac imaging, paving the way for more personalized and effective patient care. This review explores the synergies between radiomics and artificial intelligence in cardiac imaging, following the radiomics workflow and introducing concepts from both domains. Potential clinical applications, challenges, and limitations are discussed, along with solutions to overcome them.

Imaging of Cardiac Fibrosis: An Update, From the AJR Special Series on Imaging of Fibrosis

Myocardial fibrosis (MF) is defined as excessive production and deposition of extra-cellular matrix proteins that result in pathologic myocardial remodeling. Three types of MF have been identified: replacement fibrosis from tissue necrosis, reactive fibrosis from myocardial stress, and infiltrative interstitial fibrosis from progressive deposition of nondegradable material such as amyloid. Although echocardiography, nuclear medicine, and CT play important roles in the assessment of MF, MRI is pivotal in the evaluation of MF, with the late gadolinium enhancement (LGE) technique used as a primary end point. The LGE technique focuses on the pattern and distribution of gadolinium accumulation in the myocardium and assists in the diagnosis and establishment of the cause of both ischemic and nonischemic cardiomyopathy. LGE MRI also aids prognostication and risk stratification. In addition, LGE MRI is used to guide the management of patients considered for ablation for arrhythmias. Parametric mapping techniques, including T1 mapping and extracellular volume measurement, allow detection and quantification of diffuse fibrosis, which may not be detected by LGE MRI. These techniques also allow monitoring of disease progression and therapy response. This review provides an update on the imaging of MF, including prognostication and risk stratification tools, electrophysiologic considerations, and disease monitoring.

Post-hoc standardisation of parametric T1 maps in cardiovascular magnetic resonance imaging: a proof-of-concept

BACKGROUND

In cardiovascular magnetic resonance imaging parametric T1 mapping lacks universally valid reference values. This limits its extensive use in the clinical routine. The aim of this work was the introduction of our self-developed Magnetic Resonance Imaging Software for Standardization (MARISSA) as a post-hoc standardisation approach.

METHODS

Our standardisation approach minimises the bias of confounding parameters (CPs) on the base of regression models. 214 healthy subjects with 814 parametric T1 maps were used for training those models on the CPs: age, gender, scanner and sequence. The training dataset included both sex, eleven different scanners and eight different sequences. The regression model type and four other adjustable standardisation parameters were optimised among 240 tested settings to achieve the lowest coefficient of variation, as measure for the inter-subject variability, in the mean T1 value across the healthy test datasets (HTE, N = 40, 156 T1 maps). The HTE were then compared to 135 patients with left ventricular hypertrophy including hypertrophic cardiomyopathy (HCM, N = 112, 121 T1 maps) and amyloidosis (AMY, N = 24, 24 T1 maps) after applying the best performing standardisation pipeline (BPSP) to evaluate the diagnostic accuracy.

FINDINGS

The BPSP reduced the COV of the HTE from 12.47% to 5.81%. Sensitivity and specificity reached 95.83% / 91.67% between HTE and AMY, 71.90% / 72.44% between HTE and HCM, and 87.50% / 98.35% between HCM and AMY.

INTERPRETATION

Regarding the BPSP, MARISSA enabled the comparability of T1 maps independently of CPs while keeping the discrimination of healthy and patient groups as found in literature.

FUNDING

This study was supported by the BMBF / DZHK.

MRI-derived extracellular volume as a biomarker of cancer therapy cardiotoxicity: systematic review and meta-analysis

OBJECTIVES

MRI-derived extracellular volume (ECV) allows characterization of myocardial changes before the onset of overt pathology, which may be caused by cancer therapy cardiotoxicity. Our purpose was to review studies exploring the role of MRI-derived ECV as an early cardiotoxicity biomarker to guide timely intervention.

MATERIALS AND METHODS

In April 2022, we performed a systematic search on EMBASE and PubMed for articles on MRI-derived ECV as a biomarker of cancer therapy cardiotoxicity. Two blinded researchers screened the retrieved articles, including those reporting ECV values at least 3 months from cardiotoxic treatment. Data extraction was performed for each article, including clinical and technical data, and ECV values. Pooled ECV was calculated using the random effects model and compared among different treatment regimens and among those who did or did not experience overt cardiac dysfunction. Meta-regression analyses were conducted to appraise which clinical or technical variables yielded a significant impact on ECV.

RESULTS

Overall, 19 studies were included. Study populations ranged from 9 to 236 patients, for a total of 1123 individuals, with an average age ranging from 12.5 to 74 years. Most studies included patients with breast or esophageal cancer, treated with anthracyclines and chest radiotherapy. Pooled ECV was 28.44% (95% confidence interval, CI, 26.85-30.03%) among subjects who had undergone cardiotoxic cancer therapy, versus 25.23% (95%CI 23.31-27.14%) among those who had not (p = .003).

CONCLUSION

A higher ECV in patients who underwent cardiotoxic treatment could imply subclinical changes in the myocardium, present even before overt cardiac pathology is detectable.

CLINICAL RELEVANCE STATEMENT

The ability to detect subclinical changes in the myocardium displayed by ECV suggests its use as an early biomarker of cancer therapy-related cardiotoxicity.

KEY POINTS

• Cardiotoxicity is a common adverse effect of cancer therapy; therefore, its prompt detection could improve patient outcomes. • Pooled MRI-derived myocardial extracellular volume was higher in patients who underwent cardiotoxic cancer therapy than in those who did not (28.44% versus 25.23%, p = .003). • MRI-derived myocardial extracellular volume represents a potential early biomarker of cancer therapy cardiotoxicity.

Liver T1 and T2 mapping in a large cohort of healthy subjects: normal ranges and correlation with age and sex

OBJECTIVE

We established normal ranges for native T1 and T2 values in the human liver using a 1.5 T whole-body imager (General Electric) and we evaluated their variation across hepatic segments and their association with age and sex.

MATERIALS AND METHODS

One-hundred healthy volunteers aged 20-70 years (50% females) underwent MRI. Modified Look-Locker inversion recovery and multi-echo fast-spin-echo sequences were used to measure hepatic native global and segmental T1 and T2 values, respectively.

RESULTS

T1 and T2 values exhibited good intra- and inter-observer reproducibility (coefficient of variation < 5%). T1 value over segment 4 was significantly lower than the T1 values over segments 2 and 3 (p < 0.0001). No significant regional T2 variability was detected. Segmental and global T1 values were not associated with age or sex. Global T2 values were independent from age but were significantly lower in males than in females. The lower and upper limits of normal for global T1 values were, respectively, 442 ms and 705 ms. The normal range for global T2 values was 35 ms-54 ms in males and 39 ms-54 ms in females.

DISCUSSION

Liver T1 and T2 mapping is feasible and reproducible and the provided normal ranges may help to establish diagnosis and progression of various liver diseases.

Accuracy of free-breathing multi-parametric SASHA in identifying T1 and T2 elevations in pediatric orthotopic heart transplant patients

T1/T2 parametric mapping may reveal patterns of elevation ("hotspots") in myocardial diseases, such as rejection in orthotopic heart transplant (OHT) patients. This study aimed to evaluate the diagnostic accuracy of free-breathing (FB) multi-parametric SAturation recovery single-SHot Acquisition (mSASHA) T1/T2 mapping in identifying hotspots present on conventional Breath-held Modified Look-Locker Inversion recovery (BH MOLLI) T1 and T2-prepared balanced steady-state free-precession (BH T2p-bSSFP) maps in pediatric OHT patients. Pediatric OHT patients underwent noncontrast 1.5T CMR with BH MOLLI T1 and T2p-bSSFP and prototype FB mSASHA T1/T2 mapping in 8 short-axis slices. FB and BH T1/T2 hotspots were segmented using semi-automated thresholding (ITK-SNAP) and their 3D coordinate locations were collected (3-Matic, Materialise, Leuven, Belgium). Receiver operator characteristic curve analysis and measures of central tendency were utilized. 40 imaging datasets from 23 pediatric OHT patients were obtained. FB mSASHA yielded a sensitivity of 82.8% for T1 and 80% for T2 maps when compared to the standard BH MOLLI, as well as 100% specificity for both T1 and T2 maps. When identified on both FB and BH maps, hotspots overlapped in all cases, with an average long axis offset between FB and BH hotspot centers of 5.8 mm (IQR 3.5-8.2) on T1 and 5.9 mm (IQR 3.5-8.2) on T2 maps. FB mSASHA T1/T2 maps can identify hotspots present on conventional BH T1/T2 maps in pediatric patients with OHT, with high sensitivity, specificity, and overlap in 3D space. Free-breathing mapping may improve patient comfort and facilitate OHT assessment in younger patient populations.

Cardiovascular magnetic resonance imaging for sequential assessment of cardiac fibrosis in mice: technical advancements and reverse translation

Cardiovascular magnetic resonance (CMR) imaging has become an essential technique for the assessment of cardiac function and morphology, and is now routinely used to monitor disease progression and intervention efficacy in the clinic. Cardiac fibrosis is a common characteristic of numerous cardiovascular diseases and often precedes cardiac dysfunction and heart failure. Hence, the detection of cardiac fibrosis is important for both early diagnosis and the provision of guidance for interventions/therapies. Experimental mouse models with genetically and/or surgically induced disease have been widely used to understand mechanisms underlying cardiac fibrosis and to assess new treatment strategies. Improving the appropriate applications of CMR to mouse studies of cardiac fibrosis has the potential to generate new knowledge, and more accurately examine the safety and efficacy of antifibrotic therapies. In this review, we provide 1) a brief overview of different types of cardiac fibrosis, 2) general background on magnetic resonance imaging (MRI), 3) a summary of different CMR techniques used in mice for the assessment of cardiac fibrosis including experimental and technical considerations (contrast agents and pulse sequences), and 4) provide an overview of mouse studies that have serially monitored cardiac fibrosis during disease progression and/or therapeutic interventions. Clinically established CMR protocols have advanced mouse CMR for the detection of cardiac fibrosis, and there is hope that discovery studies in mice will identify new antifibrotic therapies for patients, highlighting the value of both reverse translation and bench-to-bedside research.

Scanner-Independent MyoMapNet for Accelerated Cardiac MRI T1 Mapping Across Vendors and Field Strengths

BACKGROUND

In cardiac T1 mapping, a series of T1 -weighted (T1 w) images are collected and numerically fitted to a two or three-parameter model of the signal recovery to estimate voxel-wise T1 values. To reduce the scan time, one can collect fewer T1 w images, albeit at the cost of precision or/and accuracy. Recently, the feasibility of using a neural network instead of conventional two- or three-parameter fit modeling has been demonstrated. However, prior studies used data from a single vendor and field strength; therefore, the generalizability of the models has not been established.

PURPOSE

To develop and evaluate an accelerated cardiac T1 mapping approach based on MyoMapNet, a convolution neural network T1 estimator that can be used across different vendors and field strengths by incorporating the relevant scanner information as additional inputs to the model.

STUDY TYPE

Retrospective, multicenter.

POPULATION

A total of 1423 patients with known or suspected cardiac disease (808 male, 57 ± 16 years), from three centers, two vendors (Siemens, Philips), and two field strengths (1.5 T, 3 T). The data were randomly split into 60% training, 20% validation, and 20% testing.

FIELD STRENGTH/SEQUENCE

A 1.5 T and 3 T, Modified Look-Locker inversion recovery (MOLLI) for native and postcontrast T1 .

ASSESSMENT

Scanner-independent MyoMapNet (SI-MyoMapNet) was developed by altering the deep learning (DL) architecture of MyoMapNet to incorporate scanner vendor and field strength as inputs. Epicardial and endocardial contours and blood pool (by manually drawing a large region of interest in the blood pool) of the left ventricle were manually delineated by three readers, with 2, 8, and 9 years of experience, and SI-MyoMapNet myocardial and blood pool T1 values (calculated from four T1 w images) were compared with conventional MOLLI T1 values (calculated from 8 to 11 T1 w images).

STATISTICAL TESTS

Equivalency test with 95% confidence interval (CI), linear regression slope, Pearson correlation coefficient (r), Bland-Altman analysis.

RESULTS

The proposed SI-MyoMapNet successfully created T1 maps. Native and postcontrast T1 values measured from SI-MyoMapNet were strongly correlated with MOLLI, despite using only four T1 w images, at both field-strengths and vendors (all r > 0.86). For native T1 , SI-MyoMapNet and MOLLI were in good agreement for myocardial and blood T1 values in institution 1 (myocardium: 5 msec, 95% CI [3, 8]; blood: -10 msec, 95%CI [-16, -4]), in institution 2 (myocardium: 6 msec, 95% CI [0, 11]; blood: 0 msec, [-18, 17]), and in institution 3 (myocardium: 7 msec, 95% CI [-8, 22]; blood: 8 msec, [-14, 30]). Similar results were observed for postcontrast T1 .

DATA CONCLUSION

Inclusion of field strength and vendor as additional inputs to the DL architecture allows generalizability of MyoMapNet across different vendors or field strength.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 2.

Free-breathing simultaneous native myocardial T1, T2 and T1ρ mapping with Cartesian acquisition and dictionary matching

BACKGROUND

T1, T2 and T1ρ are well-recognized parameters for quantitative cardiac MRI. Simultaneous estimation of these parameters allows for comprehensive myocardial tissue characterization, such as myocardial fibrosis and edema. However, conventional techniques either quantify the parameters individually with separate breath-hold acquisitions, which may result in unregistered parameter maps, or estimate multiple parameters in a prolonged breath-hold acquisition, which may be intolerable to patients. We propose a free-breathing multi-parametric mapping (FB-MultiMap) technique that provides co-registered myocardial T1, T2 and T1ρ maps in a single efficient acquisition.

METHODS

The proposed FB-MultiMap performs electrocardiogram-triggered single-shot Cartesian acquisition over 16 consecutive cardiac cycles, where inversion, T2 and T1ρ preparations are introduced for varying contrasts. A diaphragmatic navigator was used for prospective through-plane motion correction and the in-plane motion was corrected retrospectively with a group-wise image registration method. Quantitative mapping was conducted through dictionary matching of the motion corrected images, where the subject-specific dictionary was created using Bloch simulations for a range of T1, T2 and T1ρ values, as well as B1 factors to account for B1 inhomogeneities. The FB-MultiMap was optimized and validated in numerical simulations, phantom experiments, and in vivo imaging of 15 healthy subjects and six patients with suspected cardiac diseases.

RESULTS

The phantom T1, T2 and T1ρ values estimated with FB-MultiMap agreed well with reference measurements with no dependency on heart rate. In healthy subjects, FB-MultiMap T1 was higher than MOLLI T1 mapping (1218 ± 50 ms vs. 1166 ± 38 ms, p < 0.001). The myocardial T2 and T1ρ estimated with FB-MultiMap were lower compared to the mapping with T2- or T1ρ-prepared 2D balanced steady-state free precession (T2: 41.2 ± 2.8 ms vs. 42.5 ± 3.1 ms, p = 0.06; T1ρ: 45.3 ± 4.4 ms vs. 50.2 ± 4.0, p < 0.001). The pathological changes in myocardial parameters measured with FB-MultiMap were consistent with conventional techniques in all patients.

CONCLUSION

The proposed free-breathing multi-parametric mapping technique provides co-registered myocardial T1, T2 and T1ρ maps in 16 heartbeats, achieving similar mapping quality to conventional breath-hold mapping methods.

Direct synthesis of multi-contrast brain MR images from MR multitasking spatial factors using deep learning

PURPOSE

To develop a deep learning method to synthesize conventional contrast-weighted images in the brain from MR multitasking spatial factors.

METHODS

Eighteen subjects were imaged using a whole-brain quantitative T1 -T2 -T1ρ MR multitasking sequence. Conventional contrast-weighted images consisting of T1 MPRAGE, T1 gradient echo, and T2 fluid-attenuated inversion recovery were acquired as target images. A 2D U-Net-based neural network was trained to synthesize conventional weighted images from MR multitasking spatial factors. Quantitative assessment and image quality rating by two radiologists were performed to evaluate the quality of deep-learning-based synthesis, in comparison with Bloch-equation-based synthesis from MR multitasking quantitative maps.

RESULTS

The deep-learning synthetic images showed comparable contrasts of brain tissues with the reference images from true acquisitions and were substantially better than the Bloch-equation-based synthesis results. Averaging on the three contrasts, the deep learning synthesis achieved normalized root mean square error = 0.184 ± 0.075, peak SNR = 28.14 ± 2.51, and structural-similarity index = 0.918 ± 0.034, which were significantly better than Bloch-equation-based synthesis (p < 0.05). Radiologists' rating results show that compared with true acquisitions, deep learning synthesis had no notable quality degradation and was better than Bloch-equation-based synthesis.

CONCLUSION

A deep learning technique was developed to synthesize conventional weighted images from MR multitasking spatial factors in the brain, enabling the simultaneous acquisition of multiparametric quantitative maps and clinical contrast-weighted images in a single scan.

Using Dictionary Matching to Improve the Accuracy of MOLLI Myocardial T1 Analysis and Measurements of Heart Rate Variability

We analyzed modified Look-Locker inversion recovery (MOLLI) T1 measurements by applying a dictionary matching strategy and aimed to acquire T1 measurements more accurately than those acquired by the conventional three-parameter matching analysis. We particularly clarified the robustness of this method for measuring heart rate (HR) variability. A phantom experiment using a 3T MRI system was performed for various HRs. The ideal MOLLI signal corresponding to the scan parameter in the MRI experiment was simulated over a wide range of T1 values according to the dictionary. The unknown T1 values were determined by finding the simulated signals in the dictionary corresponding to the measured signals using pattern matching. The measured T1 values showed that the proposed analysis improved the accuracy of T1 measurements compared to those acquired by traditional analysis by up to 10%. In addition, the variability of measurements at several HRs was reduced by up to 100 ms.

Practical Guide to Interpreting Cardiac Magnetic Resonance in Patients with Cardiac Masses

It is common for a cardiac mass to be discovered accidentally during an echocardiographic examination. Following the relief of a cardiac mass, being able to evaluate and characterize it using non-invasive imaging methods is critical. Echocardiography, computed tomography (CT), cardiac magnetic resonance imaging (CMR), and positron emission tomography (PET) are the main imaging modalities used to evaluate cardiac masses. Although multimodal imaging often allows for a better assessment, CMR is the best technique for the non-invasive characterization of tissues, as the different MR sequences help in the diagnosis of cardiac masses. This article provides detailed descriptions of each CMR sequence employed in the evaluation of cardiac masses, underlining the potential information it can provide. The description in the individual sequences provides useful guidance to the radiologist in performing the examination.

Fractional myocardial blood volume by ferumoxytol-enhanced MRI: Estimation of ischemic burden

PURPOSE

To investigate model-fitted fractional myocardial blood volume (fMBV) derived from ferumoxytol-enhanced MRI as a measure of myocardial tissue hypoperfusion at rest.

METHODS

We artificially induced moderate to severe focal coronary stenosis in the left anterior descending artery of 19 swine by percutaneous delivery of a 3D-printed coronary implant. Using the MOLLI pulse sequence, we acquired T1 maps at 3 T after multiple incremental ferumoxytol doses (0.0-4.0 mg/kg). We computed pixel-wise fMBV using a multi-compartmental modeling approach in 19 ischemic swine and 4 healthy swine.

RESULTS

Ischemic myocardial segments showed a mean MRI-fMBV of 11.72 ± 3.00%, compared with 8.23 ± 2.12% in remote segments and 8.38 ± 2.23% in normal segments. Ischemic segments showed a restricted transvascular water-exchange rate (ki  = 15.32 ± 8.69 s-1 ) relative to remote segments (ki  = 17.78 [11.60, 26.36] s-1 ). A mixed-effects model found significant difference in fMBV (p = 0.002) and water-exchange rate (p < 0.001) between ischemic and remote myocardial regions after adjusting for biological sex and slice location. Analysis of fMBV as a predictor of impaired myocardial contractility using receiver operating characteristics showed an area under the curve of 0.89 (95% confidence interval [CI] 0.80, 0.95). An MRI-fMBV threshold of 9.60% has a specificity of 90.0% (95% CI 76.3, 97.2) and a sensitivity of 72.5% (95% CI 56.1, 83.4) for prediction of impaired myocardial contractility.

CONCLUSIONS

Model-fitted fMBV derived from ferumoxytol-enhanced MRI can distinguish regions of ischemia from remote myocardium in a swine model of myocardial hypoperfusion.

Native T1 is predictive of cardiovascular death/heart failure events and all-cause mortality irrespective of the patient's volume status

Background

Native T1 has become a pivotal parameter of tissue composition that is assessed by cardiac magnetic resonance (CMR). It characterizes diseased myocardium and can be used for prognosis estimation. Recent publications have shown that native T1 is influenced by short-term fluctuations of volume status due to hydration or hemodialysis.

Methods

Patients from a prospective BioCVI all-comers clinical CMR registry were included, and native T1 and plasma volume status (PVS) were determined according to Hakim's formula as surrogate markers of patient volume status. The primary endpoint was defined as combined endpoint of cardiovascular death or hospitalization for heart failure events, the secondary endpoint was defined as all-cause mortality.

Results

A total of 2,047 patients were included since April 2017 [median (IQR); age 63 (52-72) years, 33% female]. There was a significant although weak influence of PVS on native T1 (β = 0.11, p < 0.0001). Patients with volume expansion (PVS > -13%) showed significantly higher values for tissue markers than non-volume-overloaded patients [PVS ≤ -13%; median (IQR); native T1 1,130 (1,095-1,170) vs. 1,123 (1,086-1,166) ms, p < 0.003; and T2 39 (37-40) vs. 38 (36-40) ms, p < 0.0001]. In Cox regression analysis both native T1 and PVS were independently predictive of the primary endpoint and all-cause mortality.

Conclusion

Despite a weak effect of PVS on native T1, its predictive power was not affected in a large, all-comers cohort.

Pilot tone-based prospective correction of respiratory motion for free-breathing myocardial T1 mapping

OBJECTIVE

To provide respiratory motion correction for free-breathing myocardial T1 mapping using a pilot tone (PT) and a continuous golden-angle radial acquisition.

MATERIALS AND METHODS

During a 45 s prescan the PT is acquired together with a dynamic sagittal image covering multiple respiratory cycles. From these images, the respiratory heart motion in head-feet and anterior-posterior direction is estimated and two linear models are derived between the PT and heart motion. In the following scan through-plane motion is corrected prospectively with slice tracking based on the PT. In-plane motion is corrected for retrospectively. Our method was evaluated on a motion phantom and 11 healthy subjects.

RESULTS

Non-motion corrected measurements using a moving phantom showed T1 errors of 14 ± 4% (p < 0.05) compared to a reference measurement. The proposed motion correction approach reduced this error to 3 ± 4% (p < 0.05). In vivo the respiratory motion led to an overestimation of T1 values by 26 ± 31% compared to breathhold T1 maps, which was successfully corrected to an average difference of 3 ± 2% (p < 0.05) between our free-breathing approach and breathhold data.

DISCUSSION

Our proposed PT-based motion correction approach allows for T1 mapping during free-breathing with the same accuracy as a corresponding breathhold T1 mapping scan.

Cardiac inflammation and fibrosis patterns in systemic sclerosis, evaluated by magnetic resonance imaging: An update

Systemic sclerosis (SSc) presents high morbidity/mortality, due to internal organ fibrosis, including the heart. Cardiac magnetic resonance (CMR) can perform myocardial function and tissue characterization in the same examination. The Lake Louise criteria (LLC) can identify recent myocardial inflammation using CMR. Abnormal values include: (a) myocardial over skeletal muscle ratio in STIRT2-W images >2, (b) early gadolinium enhancement values >4, (c) epicardial/intramyocardial late gadolinium enhancement (LGE). The diagnosis of myocarditis using LLC is considered if 2/3 criteria are positive. Parametric imaging including T2, native T1 mapping and extracellular volume fraction (ECV) has been recently used to diagnose inflammatory cardiomyopathy. According to expert recommendations, myocarditis should be considered if at least 2 indices, one T2 and one T1 parameter are positive, whereas native T1 mapping and ECV assess diffuse fibrosis or oedema, even in the absence of LGE. Moreover, transmural/subendocardial fibrosis following the distribution of coronary arteries and diffuse subendocardial fibrosis not related with epicardial coronary arteries are indicative of epicardial and micro-vascular coronary artery disease, respectively. To conclude, CMR can identify acute/active myocardial inflammation and myocardial infarction using classic and parametric indices in parallel with ventricular function evaluation.

Single breath-hold MR T1 mapping in the heart: Hybrid MOLLI combining saturation and inversion recovery

The native T1 values of the myocardium provide valuable information for tissue characterization and assessment of cardiomyopathies. In this study, we proposed a novel hybrid MOLLI sequence for myocardial T1 mapping. Unlike the two groups of inversion-recovery sampling of the conventional MOLLI5(3 s)3 sequence, the hybrid MOLLI sequence consisted of an inversion-recovery block followed by a saturation-recovery block. Since the second block employed a saturation pulse to spoil the longitudinal magnetization, it did not require a waiting period as MOLLI5(3 s)3 did. As a result, the hybrid MOLLI required less acquisition time leading to a practical application for patients with breath-hold difficulties. Phantom and healthy subject experiments were performed to evaluate the proposed sequence against the MOLLI5(3 s)3 sequence. The phantom study showed that the heart-rate dependency of one variant of the hybrid MOLLI sequences, hbMOLLI4, was comparable to that of MOLLI5(3 s)3. In addition, both hbMOLLI4 and MOLLI53 derived T1 values under 2% variations with simulated heart rates from 50 to 90 beats-per-minute within the range of T1 values for myocardium and blood before contrast administration. Simulation results suggested slightly reduced T1 fitting precision in hbMOLLI4 compared with MOLLI5(3 s)3, but prominently better than saturation recovery. Bland-Altman analysis on accuracy assessment revealed that hbMOLLI4 partially reduced the T1 underestimation of MOLLI5(3 s)3. In the human study, The T1 values of both methods were consistent (hbMOLLI4 vs. MOLLI5(3 s)3, slope = 1.14, R² > 0.97), with equal reproducibility. The results supported that hybrid MOLLI produced comparable T1 mapping results in terms of accuracy, reproducibility, and heart-rate dependency, at the expense of slightly reduced precision. We concluded that the hybrid MOLLI sequence presents a competitive alternative to the MOLLI5(3 s)3 sequence when a speedy acquisition is required.

Quantitative MRI in cardiometabolic disease: From conventional cardiac and liver tissue mapping techniques to multi-parametric approaches

Cardiometabolic disease refers to the spectrum of chronic conditions that include diabetes, hypertension, atheromatosis, non-alcoholic fatty liver disease, and their long-term impact on cardiovascular health. Histological studies have confirmed several modifications at the tissue level in cardiometabolic disease. Recently, quantitative MR methods have enabled non-invasive myocardial and liver tissue characterization. MR relaxation mapping techniques such as T₁, T_1ρ, T₂ and T₂* provide a pixel-by-pixel representation of the corresponding tissue specific relaxation times, which have been shown to correlate with fibrosis, altered tissue perfusion, oedema and iron levels. Proton density fat fraction mapping approaches allow measurement of lipid tissue in the organ of interest. Several studies have demonstrated their utility as early diagnostic biomarkers and their potential to bear prognostic implications. Conventionally, the quantification of these parameters by MRI relies on the acquisition of sequential scans, encoding and mapping only one parameter per scan. However, this methodology is time inefficient and suffers from the confounding effects of the relaxation parameters in each single map, limiting wider clinical and research applications. To address these limitations, several novel approaches have been proposed that encode multiple tissue parameters simultaneously, providing co-registered multiparametric information of the tissues of interest. This review aims to describe the multi-faceted myocardial and hepatic tissue alterations in cardiometabolic disease and to motivate the application of relaxometry and proton-density cardiac and liver tissue mapping techniques. Current approaches in myocardial and liver tissue characterization as well as latest technical developments in multiparametric quantitative MRI are included. Limitations and challenges of these novel approaches, and recommendations to facilitate clinical validation are also discussed.

Confounder-corrected T1 mapping in the liver through simultaneous estimation of T1 , PDFF, R 2 * , and B 1 + in a single breath-hold acquisition

PURPOSE

Quantitative volumetric T₁ mapping in the liver has the potential to aid in the detection, diagnosis, and quantification of liver fibrosis, inflammation, and spatially resolved liver function. However, accurate measurement of hepatic T₁ is confounded by the presence of fat and inhomogeneous B 1 + $$ {B}_1^{+} $$ excitation. Furthermore, scan time constraints related to respiratory motion require tradeoffs of reduced volumetric coverage and/or increased acquisition time. This work presents a novel 3D acquisition and estimation method for confounder-corrected T₁ measurement over the entire liver within a single breath-hold through simultaneous estimation of T₁ , fat and B 1 + $$ {B}_1^{+} $$ .

THEORY AND METHODS

The proposed method combines chemical shift encoded MRI and variable flip angle MRI with a B 1 + $$ {B}_1^{+} $$ mapping technique to enable confounder-corrected T₁ mapping. The method was evaluated theoretically and demonstrated in both phantom and in vivo acquisitions at 1.5 and 3.0T. At 1.5T, the method was evaluated both pre- and post- contrast enhancement in healthy volunteers.

RESULTS

The proposed method demonstrated excellent linear agreement with reference inversion-recovery spin-echo based T₁ in phantom acquisitions at both 1.5 and 3.0T, with minimal bias (5.2 and 45 ms, respectively) over T₁ ranging from 200-1200 ms. In vivo results were in general agreement with reference saturation-recovery based 2D T₁ maps (SMART₁ Map, GE Healthcare).

CONCLUSION

The proposed 3D T₁ mapping method accounts for fat and B 1 + $$ {B}_1^{+} $$ confounders through simultaneous estimation of T₁ , B 1 + $$ {B}_1^{+} $$ , PDFF and R 2 * $$ {R}_2^{\ast } $$ . It demonstrates strong linear agreement with reference T₁ measurements, with low bias and high precision, and can achieve full liver coverage in a single breath-hold.

Free-running 3D whole-heart T1 and T2 mapping and cine MRI using low-rank reconstruction with non-rigid cardiac motion correction

PURPOSE

To introduce non-rigid cardiac motion correction into a novel free-running framework for the simultaneous acquisition of 3D whole-heart myocardial <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> maps and cine images, enabling a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>∼</mml:mo></mml:mrow> <mml:annotation>$$ \sim $$</mml:annotation></mml:semantics> </mml:math> 3-min scan.

METHODS

Data were acquired using a free-running 3D golden-angle radial readout interleaved with inversion recovery and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> -preparation pulses. After correction for translational respiratory motion, non-rigid cardiac-motion-corrected reconstruction with dictionary-based low-rank compression and patch-based regularization enabled 3D whole-heart <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> mapping at any given cardiac phase as well as whole-heart cardiac cine imaging. The framework was validated and compared with established methods in 11 healthy subjects.

RESULTS

Good quality 3D <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> maps and cine images were reconstructed for all subjects. Septal <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> values using the proposed approach ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>1200</mml:mn> <mml:mo>±</mml:mo> <mml:mn>50</mml:mn></mml:mrow> <mml:annotation>$$ 1200\pm 50 $$</mml:annotation></mml:semantics> </mml:math> ms) were higher than those from a 2D MOLLI sequence ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>1063</mml:mn> <mml:mo>±</mml:mo> <mml:mn>33</mml:mn></mml:mrow> <mml:annotation>$$ 1063\pm 33 $$</mml:annotation></mml:semantics> </mml:math> ms), which is known to underestimate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> , while <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> values from the proposed approach ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>51</mml:mn> <mml:mo>±</mml:mo> <mml:mn>4</mml:mn></mml:mrow> <mml:annotation>$$ 51\pm 4 $$</mml:annotation></mml:semantics> </mml:math> ms) were in good agreement with those from a 2D GraSE sequence ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>51</mml:mn> <mml:mo>±</mml:mo> <mml:mn>2</mml:mn></mml:mrow> <mml:annotation>$$ 51\pm 2 $$</mml:annotation></mml:semantics> </mml:math> ms).

CONCLUSION

The proposed technique provides 3D <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> maps and cine images with isotropic spatial resolution in a single <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>∼</mml:mo></mml:mrow> <mml:annotation>$$ \sim $$</mml:annotation></mml:semantics> </mml:math> 3.3-min scan.

Simultaneous multi-slice T1 mapping using MOLLI with blipped CAIPIRINHA bSSFP

BACKGROUND

This study evaluates the possibility for replacing conventional 3 slices, 3 breath-holds MOLLI cardiac T1 mapping with single breath-hold 3 simultaneous multi-slice (SMS3) T1 mapping using blipped-CAIPIRINHA SMS-bSSFP MOLLI sequence. As a major drawback, SMS-bSSFP presents unique artefacts arising from side-lobe slice excitations that are explained by imperfect RF modulation rendering and bSSFP low flip angle enhancement. Amplitude-only RF modulation (AM) is proposed to reduce these artefacts in SMS-MOLLI compared to conventional Wong multi-band RF modulation (WM).

MATERIALS AND METHODS

Phantoms and ten healthy volunteers were imaged at 1.5 T using a modified blipped-CAIPIRINHA SMS-bSSFP MOLLI sequence with 3 simultaneous slices. WM-SMS3 and AM-SMS3 were compared to conventional single-slice (SMS1) MOLLI. First, SNR degradation and T1 accuracy were measured in phantoms. Second, artefacts from side-lobe excitations were evaluated in a phantom designed to reproduce fat presence near the heart. Third, the occurrence of these artefacts was observed in volunteers, and their impact on T1 quantification was compared between WM-SMS3 and AM-SMS3 with conventional MOLLI as a reference.

RESULTS

In the phantom, larger slice gaps and slice thicknesses yielded higher SNR. There was no significant difference of T1 values between conventional MOLLI and SMS3-MOLLI (both WM and AM). Positive banding artefacts were identified from fat neighbouring the targeted FOV due to side-lobe excitations from WM and the unique bSSFP signal profile. AM RF pulses reduced these artefacts by 38%. In healthy volunteers, AM-SMS3-MOLLI showed similar artefact reduction compared to WM-SMS3-MOLLI (3 ± 2 vs 5 ± 3 corrupted LV segments out of 16). In-vivo native T1 values obtained from conventional MOLLI and AM-SMS3-MOLLI were equivalent in LV myocardium (SMS1-T1 = 935.5 ± 36.1 ms; AM-SMS3-T1 = 933.8 ± 50.2 ms; P = 0.436) and LV blood pool (SMS1-T1 = 1475.4 ± 35.9 ms; AM-SMS3-T1 = 1452.5 ± 70.3 ms; P = 0.515). Identically, no differences were found between SMS1 and SMS3 postcontrast T1 values in the myocardium (SMS1-T1 = 556.0 ± 19.7 ms; SMS3-T1 = 521.3 ± 28.1 ms; P = 0.626) and the blood (SMS1-T1 = 478 ± 65.1 ms; AM-SMS3-T1 = 447.8 ± 81.5; P = 0.085).

CONCLUSIONS

Compared to WM RF modulation, AM SMS-bSSFP MOLLI was able to reduce side-lobe artefacts considerably, providing promising results to image the three levels of the heart in a single breath hold. However, few artefacts remained even using AM-SMS-bSSFP due to residual RF imperfections. The proposed blipped-CAIPIRINHA MOLLI T1 mapping sequence provides accurate in vivo T1 quantification in line with those obtained with a single slice acquisition.

MR Fingerprinting for Liver Tissue Characterization: A Histopathologic Correlation Study

Background Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies. Materials and Methods This prospective study included participants with diffuse liver disease undergoing MRI from July 2021 to January 2022. Participants underwent two-dimensional single-section liver MRF and separate reference quantitative MRI. Linear regression, Bland-Altman plots, and coefficients of variation were used to assess the bias and repeatability of liver MRF measurements. For participants undergoing liver biopsy, the association between mapping and histologic grading was evaluated by using the Spearman correlation coefficient. Results Fifty-six participants (mean age, 59 years ± 15 [SD]; 32 women) were included to compare mapping techniques and 23 participants were evaluated with liver biopsy (mean age, 52.7 years ± 12.7; 14 women). The linearity of MRF with reference measurements in participants with diffuse liver disease (R² value) for T1, T2, T2*, and PDFF maps was 0.86, 0.88, 0.54, and 0.99, respectively. The overall coefficients of variation for repeatability in the liver were 3.2%, 5.5%, 7.1%, and 4.6% for T1, T2, T2*, and PDFF maps, respectively. MRF-derived metrics showed high diagnostic performance in differentiating moderate or severe changes from mild or no changes (area under the receiver operating characteristic curve for fibrosis, inflammation, steatosis, and siderosis: 0.62 [95% CI: 0.52, 0.62], 0.92 [95% CI: 0.88, 0.92], 0.97 [95% CI: 0.96, 0.97], and 0.74 [95% CI: 0.57, 0.74], respectively). Conclusion Liver MR fingerprinting provided repeatable T1, T2, T2*, and proton density fat fraction maps in high agreement with reference quantitative mapping and may correlate with pathologic grades in participants with diffuse liver disease. © RSNA, 2022 Online supplemental material is available for this article.

Liver T1 Relaxation Quantification Using a 3-Dimensional Interleaved Look-Locker Acquisition With T2 Preparation Pulse Sequence (3D-QALAS): Comparison With Conventional 2-Dimensional MOLLI

BACKGROUND

Changes in liver magnetic resonance imaging T1 relaxation times are associated with histologic inflammation and fibrosis.

OBJECTIVE

To compare liver T1 measurements obtained using a novel single-breath-hold 3-dimensional (3D) whole-liver T1 estimation method (3D-QALAS) to standard-of-care 2-dimensional (2D) modified Look-Locker (2D-MOLLI) measurements.

METHODS

With institutional review board approval, research magnetic resonance imaging examinations were performed in 19 participants at 1.5 T. T1 relaxometry of the liver was performed using a novel 3D whole-liver T1 estimation method (3D-QALAS) as well as a 2D modified Look-Locker (2D-MOLLI) method. The 3D method covered the entire liver in a single breath hold, whereas 2D imaging was performed at 4 anatomic levels in 4 consecutive breath holds. T1 measurements from parametric maps were obtained by a single operator, and region-of-interest area-weighted mean T1 values were calculated. Pearson correlation ( r ) was used to assess correlation between T1 estimation methods, and the paired t test and Bland-Altman analysis were used to compare agreement in T1 measurements.

RESULTS

In 18 participants (1 participant was excluded from analysis because of respiratory motion artifacts on 3D-QALAS images), 2D-MOLLI and 3D-QALAS mean T1 measurements were strongly correlated ( r = 0.95, [95% CI: 0.87-0.98]; P < 0.0001). 2D-MOLLI T1 values were significantly longer than 3D-QALAS values (647.2 ± 87.3 milliseconds vs. 554.7 ± 75.8 milliseconds; P < 0.0001) with mean bias = 92.5 milliseconds (95% limits of agreement, 36.8, 148.2 milliseconds).

CONCLUSION

Whole-liver T1 measurements obtained using a novel single-breath-hold 3D T1 estimation method correlate with a standard-of-care multiple consecutive-breath-hold 2D single-slice method but demonstrate systematic bias that should be considered or corrected when used in a clinical or research setting.

Non-LGE Cardiac Magnetic Resonance Imaging in Patients with Cardiac Amyloidosis

Cardiac involvement is the leading cause of death in patients with cardiac amyloidosis. Early recognition is crucial as it can significantly change the course of the disease. Until now, the imaging modality of choice for diagnosing cardiac amyloidosis has been cardiac magnetic resonance imaging (CMR) with late gadolinium enhancement (LGE). LGE-CMR in patients with cardiac amyloidosis reveals characteristic LGE patterns that lead to a diagnosis while also correlating well with disease prognosis. However, LGE-CMR has numerous drawbacks that the newer CMR modality, T1 mapping, aims to improve. T1 mapping can be further subdivided into native T1 mapping, which does not require the use of contrast, and ECV measurement, which requires the use of contrast. Numerous T1 mapping techniques have been developed, each one with its own advantages and disadvantages when it comes to procedure difficulty and image quality. A literature review to identify relevant published articles was performed by two authors. This review aimed to present the value of T1 mapping in diagnosing cardiac amyloidosis, quantifying the amyloid burden, and evaluating the prognosis of patients with amyloidosis with cardiac involvement.

Cardiovascular Magnetic Resonance Parametric Mapping Techniques for the Assessment of Chronic Coronary Syndromes

The term chronic coronary syndromes encompasses a variety of clinical presentations of coronary artery disease (CAD), ranging from stable angina due to epicardial coronary artery disease to microvascular coronary dysfunction. Cardiac magnetic resonance (CMR) imaging has an established role in the diagnosis, prognostication and treatment planning of patients with CAD. Recent advances in parametric mapping CMR techniques have added value in the assessment of patients with chronic coronary syndromes, even without the need for gadolinium contrast administration. Furthermore, quantitative perfusion CMR techniques have enabled the non-invasive assessment of myocardial blood flow and myocardial perfusion reserve and can reliably identify multivessel coronary artery disease and microvascular dysfunction. This review summarizes the clinical applications and the prognostic value of the novel CMR parametric mapping techniques in the setting of chronic coronary syndromes and discusses their strengths, pitfalls and future directions.

T1 Mapping MOLLI 5(3)3 Acquisition Scheme Yields High Accuracy in 1.5 T Cardiac Magnetic Resonance

Objectives: To systematically compare two modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences and their impact on (1) myocardial T1 values native, (2) post-contrast and (3) extracellular volume (ECV). Methods: 200 patients were prospectively included for 1.5 T CMR for work-up of ischemic or non-ischemic cardiomyopathies. To determine native and post-contrast T1 for ECV calculation, two different T1 mapping MOLLI acquisition schemes, 5(3)3 (designed for native scans with long T1) and 4(1)3(1)2 (designed for post-contrast scans with short T1), were acquired in identical mid-ventricular short-axis slices. Both schemes were acquired in native and post-contrast scans. Results: Datasets from 163 patients were evaluated (age 55 ± 17 years; 38% female). Myocardial T1 native for 5(3)3 was 1017 ± 42 ms vs. 956 ± 40 ms for 4(1)3(1)2, with mean intraindividual difference −61 ms (p < 0.0001). Post-contrast myocardial T1 in patients was similar for both acquisition schemes, with 494 ± 48 ms for 5(3)3 and 490 ± 45 ms for 4(1)3(1)2 and mean intraindividual difference −4 ms. Myocardial ECV for 5(3)3 was 27.6 ± 4% vs. 27 ± 4% for 4(1)3(1)2, with mean difference −0.6 percentage points (p < 0.0001). Conclusions: The T1 MOLLI 5(3)3 acquisition scheme provides a reliable estimation of myocardial T1 for the clinically relevant range of long and short T1 values native and post-contrast. In contrast, the T1 MOLLI 4(1)3(1)2 acquisition scheme may only be used for post-contrast scans according to its designed purpose.

Role of Cardiac MRI Imaging of Focal and Diffuse Inflammation and Fibrosis in Cardiomyopathy Patients Who Have Pacemakers/ICD Devices

PURPOSE OF REVIEW

This focused report aims to discuss and summarize the use of conventional and emerging methods using cardiovascular magnetic resonance (CMR) imaging in cardiomyopathy patients with implanted cardiac devices to identify diffuse and focal inflammation and fibrosis.

RECENT FINDINGS

Many cardiomyopathy patients with diffuse and focal myocardial fibrosis have a unique need for cardiac imaging that is complicated by cardiovascular implantable electronic devices (CIEDs). CMR imaging can accurately image myocardial fibrosis and inflammation using T1 mapping and late gadolinium enhancement (LGE) imaging. CMR imaging in CIED patients, however, has been limited due to severe imaging artifacts associated with the devices. The emergence of wideband imaging variants of LGE and T1 mapping techniques can successfully reduce or eliminate CIED artifacts for the evaluation of myocardial substrate in cardiomyopathy patients. Wideband imaging variants of LGE and T1 mapping techniques provide new tools for imaging focal and diffuse fibrosis and imaging in cardiomyopathy patients with implanted cardiac devices. These emerging techniques have the potential for great impact in clinical care of such patients as well as clinical research where imaging endpoints are desired.

Accelerated cardiac T1 mapping with recurrent networks and cyclic, model-based loss

BACKGROUND

Using the spin-lattice relaxation time (T1) as a biomarker, the myocardium can be quantitatively characterized using cardiac T1 mapping. The modified Look-Locker inversion (MOLLI) recovery sequences have become the standard clinical method for cardiac T1 mapping. However, the MOLLI sequences require an 11-heartbeat breath-hold that can be difficult for subjects, particularly during exercise or pharmacologically induced stress. Although shorter cardiac T1 mapping sequences have been proposed, these methods suffer from reduced precision. As such, there is an unmet need for accelerated cardiac T1 mapping.

PURPOSE

To accelerate cardiac T1 mapping MOLLI sequences by using neural networks to estimate T1 maps using a reduced number of T1-weighted images and their corresponding inversion times.

MATERIALS AND METHODS

In this retrospective study, 911 pre-contrast T1 mapping datasets from 202 subjects (128 males, 56 ± 15 years; 74 females, 54 ± 17 years) and 574 T1 mapping post-contrast datasets from 193 subjects (122 males, 57 ± 15 years; 71 females, 54 ± 17 years) were acquired using the MOLLI-5(3)3 sequence and the MOLLI-4(1)3(1)2 sequence, respectively. All acquisition protocols used similar scan parameters:T R = 2.2 ms $TR\; = \;2.2\;{\rm{ms}}$ ,T E = 1.12 ms $TE\; = \;1.12\;{\rm{ms}}$ , andF A = 35 ∘ $FA\; = \;35^\circ $ , gadoteridol (ProHance, Bracco Diagnostics) dose∼ 0.075 mmol / kg $\sim 0.075\;\;{\rm{mmol/kg}}$ . A bidirectional multilayered long short-term memory (LSTM) network with fully connected output and cyclic model-based loss was used to estimate T1 maps from the first three T1-weighted images and their corresponding inversion times for pre- and post-contrast T1 mapping. The performance of the proposed architecture was compared to the three-parameter T1 recovery model using the same reduction of the number of T1-weighted images and inversion times. Reference T1 maps were generated from the scanner using the full MOLLI sequences and the three-parameter T1 recovery model. Correlation and Bland-Altman plots were used to evaluate network performance in which each point represents averaged regions of interest in the myocardium corresponding to the standard American Heart Association 16-segment model. The precision of the network was examined using consecutively repeated scans. Stress and rest pre-contrast MOLLI studies as well as various disease test cases, including amyloidosis, hypertrophic cardiomyopathy, and sarcoidosis were also examined. Paired t-tests were used to determine statistical significance withp < 0.05 $p < 0.05$ .

RESULTS

Our proposed network demonstrated similar T1 estimations to the standard MOLLI sequences (pre-contrast:1260 ± 94 ms $1260 \pm 94\;{\rm{ms}}$ vs.1254 ± 91 ms $1254 \pm 91\;{\rm{ms}}$ withp = 0.13 $p\; = \;0.13$ ; post-contrast:484 ± 92 ms $484 \pm 92\;{\rm{ms}}$ vs.493 ± 91 ms $493 \pm 91\;{\rm{ms}}$ withp = 0.07 $p\; = \;0.07$ ). The precision of standard MOLLI sequences was well preserved with the proposed network architecture (24 ± 28 ms $24 \pm 28\;\;{\rm{ms}}$ vs.18 ± 13 ms $18 \pm 13\;{\rm{ms}}$ ). Network-generated T1 reactivities are similar to stress and rest pre-contrast MOLLI studies (5.1 ± 4.0 % $5.1 \pm 4.0\;\% $ vs.4.9 ± 4.4 % $4.9 \pm 4.4\;\% $ withp = 0.84 $p\; = \;0.84$ ). Amyloidosis T1 maps generated using the proposed network are also similar to the reference T1 maps (pre-contrast:1243 ± 140 ms $1243 \pm 140\;\;{\rm{ms}}$ vs.1231 ± 137 ms $1231 \pm 137\;{\rm{ms}}$ withp = 0.60 $p\; = \;0.60$ ; post-contrast:348 ± 26 ms $348 \pm 26\;{\rm{ms}}$ vs.346 ± 27 ms $346 \pm 27\;{\rm{ms}}$ withp = 0.89 $p\; = \;0.89$ ).

CONCLUSIONS

A bidirectional multilayered LSTM network with fully connected output and cyclic model-based loss was used to generate high-quality pre- and post-contrast T1 maps using the first three T1-weighted images and their corresponding inversion times. This work demonstrates that combining deep learning with cardiac T1 mapping can potentially accelerate standard MOLLI sequences from 11 to 3 heartbeats.

Reference values of myocardial native T1 and T2 mapping values in normal Indian population at 1.5 Tesla scanner

T1 and T2 mapping techniques on cardiovascular magnetic resonance (CMR) provide insights into the myocardial tissue characterisation. We sought to establish the normal reference values of native T1 and T2 mapping in Indian population which can be used subsequently in clinical practice for addressing various cardiac pathologies. This prospective study included consecutive healthy volunteers (18-60 years) who underwent CMR on a 1.5 Tesla scanner using standard protocol. T1 mapping sequence was performed using MOLLI sequence with two different flip angles (FA) (35° and 50°). T2 mapping was performed using a hybrid gradient and spin-echo sequence sequence with two different FA (70° and 12°). Images were analysed with ROIs drawn in all the 16 AHA myocardial segments. 50 volunteers (average age-34 years, males-72%) were included. All the scans were normal. The mean T1 value at 35-degree FA was 946.86 + 14.16 ms and at 50-degree FA was 941.60 + 11.89 ms. The mean T2 mapping value at 70-degree FA was 45.67 + 1.39 ms and at 12-degree FA was 45.61 + 1.47 ms. The mapping values were not statistically different between males and females (all p > 0.2). The T1 and T2 mapping values did not show any significant correlation with LVEF, age, BMI or heart rate (all r < 0.33). The T1 mapping values significantly differ at 35- and 50-degree FAs (p = 0.002). The results establish the normal reference T1 and T2 mapping value for Indian population in institutes using the same protocol and parameters at 1.5 Tesla and may guide future research.

State of the Art: Quantitative Cardiac MRI in Cardiac Amyloidosis

Cardiac amyloidosis (CA) is characterized by amyloid infiltration in the myocardial extracellular space, causing heart failure. Patients with CA are currently underdiagnosed. Cardiac involvement is significantly associated with the prognosis and treatment decision-making for CA. Early identification and accurate stratification are the crucial first step in patient management. Comprehensive cardiac MRI-based evaluation of the cardiac structure, function, and myocardial tissue characterization assesses cardiac involvement by tracing disease processes. Emerging quantitative tissue characterization techniques have introduced new measures that can identify early staged CA and monitor disease progression or response after treatment. Quantitative cardiac MRI is becoming an instrumental tool in understanding CA, which leads to changes in individualized patient care. This review aimed to discuss the quantitative cardiac MRI-based assessment of CA using established and emerging techniques. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.

Impact of deep learning architectures on accelerated cardiac T1 mapping using MyoMapNet

The objective of the current study was to investigate the performance of various deep learning (DL) architectures for MyoMapNet, a DL model for T1 estimation using accelerated cardiac T1 mapping from four T1 -weighted images collected after a single inversion pulse (Look-Locker 4 [LL4]). We implemented and tested three DL architectures for MyoMapNet: (a) a fully connected neural network (FC), (b) convolutional neural networks (VGG19, ResNet50), and (c) encoder-decoder networks with skip connections (ResUNet, U-Net). Modified Look-Locker inversion recovery (MOLLI) images from 749 patients at 3 T were used for training, validation, and testing. The first four T1 -weighted images from MOLLI5(3)3 and/or MOLLI4(1)3(1)2 protocols were extracted to create accelerated cardiac T1 mapping data. We also prospectively collected data from 28 subjects using MOLLI and LL4 to further evaluate model performance. Despite rigorous training, conventional VGG19 and ResNet50 models failed to produce anatomically correct T1 maps, and T1 values had significant errors. While ResUNet yielded good quality maps, it significantly underestimated T1 . Both FC and U-Net, however, yielded excellent image quality with good T1 accuracy for both native (FC/U-Net/MOLLI = 1217 ± 64/1208 ± 61/1199 ± 61 ms, all p < 0.05) and postcontrast myocardial T1 (FC/U-Net/MOLLI = 578 ± 57/567 ± 54/574 ± 55 ms, all p < 0.05). In terms of precision, the U-Net model yielded better T1 precision compared with the FC architecture (standard deviation of 61 vs. 67 ms for the myocardium for native [p < 0.05], and 31 vs. 38 ms [p < 0.05], for postcontrast). Similar findings were observed in prospectively collected LL4 data. It was concluded that U-Net and FC DL models in MyoMapNet enable fast myocardial T1 mapping using only four T1 -weighted images collected from a single LL sequence with comparable accuracy. U-Net also provides a slight improvement in precision.

Clinical evaluation of the Multimapping technique for simultaneous myocardial T1 and T2 mapping

The Multimapping technique was recently proposed for simultaneous myocardial T₁ and T₂ mapping. In this study, we evaluate its correlation with clinical reference mapping techniques in patients with a range of cardiovascular diseases (CVDs) and compare image quality and inter- and intra-observer repeatability. Multimapping consists of an ECG-triggered, 2D single-shot bSSFP readout with inversion recovery and T₂ preparation modules, acquired across 10 cardiac cycles. The sequence was implemented at 1.5T and compared to clinical reference mapping techniques, modified Look-Locker inversion recovery (MOLLI) and T₂ prepared bSSFP with four echo times (T₂bSSFP), and compared in 47 patients with CVD (of which 44 were analyzed). In diseased myocardial segments (defined as the presence of late gadolinium enhancement), there was a high correlation between Multimapping and MOLLI for native myocardium T₁ (r² = 0.73), ECV (r² = 0.91), and blood T₁ (r² = 0.88), and Multimapping and T₂bSSFP for native myocardial T₂ (r² = 0.80). In healthy myocardial segments, a bias for native T₁ (Multimapping = 1,116 ± 21 ms, MOLLI = 1,002 ± 21, P < 0.001), post-contrast T₁ (Multimapping = 479 ± 31 ms, MOLLI = 426 ± 27 ms, 0.001), ECV (Multimapping = 21.5 ± 1.9%, MOLLI = 23.7 ± 2.3%, P = 0.001), and native T₂ (Multimapping = 48.0 ± 3.0 ms, T₂bSSFP = 53.9 ± 3.5 ms, P < 0.001) was observed. The image quality for Multimapping was scored as higher for all mapping techniques (native T₁, post-contrast T₁, ECV, and T₂bSSFP) compared to the clinical reference techniques. The inter- and intra-observer agreements were excellent (intraclass correlation coefficient, ICC > 0.9) for most measurements, except for inter-observer repeatability of Multimapping native T₁ (ICC = 0.87), post-contrast T₁ (ICC = 0.73), and T₂bSSFP native T₂ (ICC = 0.88). Multimapping shows high correlations with clinical reference mapping techniques for T₁, T₂, and ECV in a diverse cohort of patients with different cardiovascular diseases. Multimapping enables simultaneous T₁ and T₂ mapping and can be performed in a short breath-hold, with image quality superior to that of the clinical reference techniques.

Improving accuracy of myocardial T1 estimation in MyoMapNet

PURPOSE

To improve the accuracy and robustness of T₁ estimation by MyoMapNet, a deep learning-based approach using 4 inversion-recovery T₁ -weighted images for cardiac T₁ mapping.

METHODS

MyoMapNet is a fully connected neural network for T₁ estimation of an accelerated cardiac T₁ mapping sequence, which collects 4 T₁ -weighted images by a single Look-Locker inversion-recovery experiment (LL4). MyoMapNet was originally trained using in vivo data from the modified Look-Locker inversion recovery sequence, which resulted in significant bias and sensitivity to various confounders. This study sought to train MyoMapNet using signals generated from numerical simulations and phantom MR data under multiple simulated confounders. The trained model was then evaluated by phantom data scanned using new phantom vials that differed from those used for training. The performance of the new model was compared with modified Look-Locker inversion recovery sequence and saturation-recovery single-shot acquisition for measuring native and postcontrast T₁ in 25 subjects.

RESULTS

In the phantom study, T₁ values measured by LL4 with MyoMapNet were highly correlated with reference values from the spin-echo sequence. Furthermore, the estimated T₁ had excellent robustness to changes in flip angle and off-resonance. Native and postcontrast myocardium T₁ at 3 Tesla measured by saturation-recovery single-shot acquisition, modified Look-Locker inversion recovery sequence, and MyoMapNet were 1483 ± 46.6 ms and 791 ± 45.8 ms, 1169 ± 49.0 ms and 612 ± 36.0 ms, and 1443 ± 57.5 ms and 700 ± 57.5 ms, respectively. The corresponding extracellular volumes were 22.90% ± 3.20%, 28.88% ± 3.48%, and 30.65% ± 3.60%, respectively.

CONCLUSION

Training MyoMapNet with numerical simulations and phantom data will improve the estimation of myocardial T₁ values and increase its robustness to confounders while also reducing the overall T₁ mapping estimation time to only 4 heartbeats.

Saturation-pulse prepared heart-rate independent inversion-recovery (SAPPHIRE) biventricular T1 mapping: inter-field strength, head-to-head comparison of diastolic, systolic and dark-blood measurements

Background

To assess the feasibility of biventricular SAPPHIRE T₁ mapping in vivo across field strengths using diastolic, systolic and dark-blood (DB) approaches.

Methods

10 healthy volunteers underwent same-day non-contrast cardiovascular magnetic resonance at 1.5 Tesla (T) and 3 T. Left and right ventricular (LV, RV) T₁ mapping was performed in the basal, mid and apical short axis using 4-variants of SAPPHIRE: diastolic, systolic, 0th and 2nd order motion-sensitized DB and conventional modified Look-Locker inversion recovery (MOLLI).

Results

LV global myocardial T₁ times (1.5 T then 3 T results) were significantly longer by diastolic SAPPHIRE (1283 ± 11|1600 ± 17 ms) than any of the other SAPPHIRE variants: systolic (1239 ± 9|1595 ± 13 ms), 0th order DB (1241 ± 10|1596 ± 12) and 2nd order DB (1251 ± 11|1560 ± 20 ms, all p < 0.05). In the mid septum MOLLI and diastolic SAPPHIRE exhibited significant T₁ signal contamination (longer T₁) at the blood-myocardial interface not seen with the other 3 SAPPHIRE variants (all p < 0.025). Additionally, systolic, 0th order and 2nd order DB SAPPHIRE showed narrower dispersion of myocardial T₁ times across the mid septum when compared to diastolic SAPPHIRE (interquartile ranges respectively: 25 ms, 71 ms, 73 ms vs 143 ms, all p < 0.05). RV T₁ mapping was achievable using systolic, 0th and 2nd order DB SAPPHIRE but not with MOLLI or diastolic SAPPHIRE. All 4 SAPPHIRE variants showed excellent re-read reproducibility (intraclass correlation coefficients 0.953 to 0.996).

Conclusion

These small-scale preliminary healthy volunteer data suggest that DB SAPPHIRE has the potential to reduce partial volume effects at the blood-myocardial interface, and that systolic SAPPHIRE could be a feasible solution for right ventricular T₁ mapping. Further work is needed to understand the robustness of these sequences and their potential clinical utility.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00843-0.

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%.

Quantification of changes in myocardial T1 * values with exercise cardiac MRI using a free-breathing non-electrocardiograph radial imaging

PURPOSE

To develop and evaluate a free breathing non-electrocardiograph (ECG) myocardial T₁ * mapping sequence using radial imaging to quantify the changes in myocardial T₁ * between rest and exercise (T₁ *_reactivity ) in exercise cardiac MRI (Ex-CMR).

METHODS

A free-running T₁ * sequence was developed using a saturation pulse followed by three Look-Locker inversion-recovery experiments. Each Look-Locker continuously acquired data as radial trajectory using a low flip-angle spoiled gradient-echo readout. Self-navigation was performed with a temporal resolution of ∼100 ms for retrospectively extracting respiratory motion. The mid-diastole phase for every cardiac cycle was retrospectively detected on the recorded electrocardiogram signal using an empirical model. Multiple measurements were performed to obtain mean value to reduce effects from the free-breathing acquisition. Finally, data acquired at both mid-diastole and end-expiration are picked and reconstructed by a low-rank plus sparsity constraint algorithm. The performance of this sequence was evaluated by simulations, phantoms, and in vivo studies at rest and after physiological exercise.

RESULTS

Numerical simulation demonstrated that changes in T₁ * are related to the changes in T₁ ; however, other factors such as breathing motion could influence T₁ * measurements. Phantom T₁ * values measured using free-running T₁ * mapping sequence had good correlation with spin-echo T₁ values and was insensitive to heart rate. In the Ex-CMR study, the measured T₁ * reactivity was 10% immediately after exercise and declined over time.

CONCLUSION

The free-running T₁ * mapping sequence allows free-breathing non-ECG quantification of changes in myocardial T₁ * with physiological exercise. Although, absolute myocardial T₁ * value is sensitive to various confounders such as B₁ and B₀ inhomogeneity, quantification of its change may be useful in revealing myocardial tissue properties with exercise.

The Road Toward Reproducibility of Parametric Mapping of the Heart: A Technical Review

Parametric mapping of the heart has become an essential part of many cardiovascular magnetic resonance imaging exams, and is used for tissue characterization and diagnosis in a broad range of cardiovascular diseases. These pulse sequences are used to quantify the myocardial T₁, T₂, T2*, and T_1ρ relaxation times, which are unique surrogate indices of fibrosis, edema and iron deposition that can be used to monitor a disease over time or to compare patients to one another. Parametric mapping is now well-accepted in the clinical setting, but its wider dissemination is hindered by limited inter-center reproducibility and relatively long acquisition times. Recently, several new parametric mapping techniques have appeared that address both of these problems, but substantial hurdles remain for widespread clinical adoption. This review serves both as a primer for newcomers to the field of parametric mapping and as a technical update for those already well at home in it. It aims to establish what is currently needed to improve the reproducibility of parametric mapping of the heart. To this end, we first give an overview of the metrics by which a mapping technique can be assessed, such as bias and variability, as well as the basic physics behind the relaxation times themselves and what their relevance is in the prospect of myocardial tissue characterization. This is followed by a summary of routine mapping techniques and their variations. The problems in reproducibility and the sources of bias and variability of these techniques are reviewed. Subsequently, novel fast, whole-heart, and multi-parametric techniques and their merits are treated in the light of their reproducibility. This includes state of the art segmentation techniques applied to parametric maps, and how artificial intelligence is being harnessed to solve this long-standing conundrum. We finish up by sketching an outlook on the road toward inter-center reproducibility, and what to expect in the future.

Diagnostic Value of 11C-PIB PET/MR in Cardiac Amyloidosis

Background

The thioflavin T derivative, 11C-Pittsburgh-B (PIB), is used for Alzheimer's disease imaging because it specifically binds to β-amyloid protein deposits in the brain. The aim of this study was to estimate the diagnostic value of combined 11C-PIB positron emission tomography/magnetic resonance (PET/MR) in cardiac amyloidosis (CA).

Methods

We enrolled 23 heart failure patients with suspected CA based on echocardiographic and electrocardiograph findings. All patients underwent cardiac 11C-PIB PET/MR and non-cardiac biopsy within one week. We also enrolled eight healthy volunteers that underwent cardiac 11C-PIB PET/MR as a control group. The cardiac magnetic resonance (CMR) protocol included cine imaging, late gadolinium enhancement (LGE), and native and post-contrast T1 mapping. Extracellular volume (ECV) was measured using pre- and post-contrast T1 mapping images. LVEF, IVSD, LVPW, LVmass, LVESV, LVEDV, native T1 value, ECV, and maximum uptake of myocardial tissue-to-blood background ratio (TBR) values were obtained from PET/MR images in all patients and healthy subjects.

Results

Thirteen out of twenty-three heart failure patients were clinically diagnosed with CA. The remaining 10 patients were CA-negative (non-CA patient group). Twelve of the thirteen CA patients showed diffuse transmural LGE patterns, whereas LGE was either absent or patchy in the non-CA patients. The diagnostic sensitivity and specificity of TBRmax were 92.3 and 100%, respectively, at a cut-off value of 1.09. Several CMR imaging parameters (LVEF, IVSD, LVmass, LVEDV, LVESV, LVPW, native T1 value and ECV) and TBR showed significant differences between CA patients, non-CA patients, and healthy controls (P &lt; 0.05). Native T1 mapping values positively correlated with TBRmax values in CA and non-CA patients (r = 0.38, P = 0.0004).

Conclusions

11C-PIB PET/MRI is a valuable tool for the accurate and non-invasive diagnosis of CA because it distinguishes CA patients from non-CA patients and healthy subjects with high specificity and sensitivity. Moreover, native T1 mapping values positively correlated with TBRmax values in CA and non-CA patients. In the future, larger cohort studies are necessary to confirm our findings.

Noninvasive Cardiac Imaging in Formerly Preeclamptic Women for Early Detection of Subclinical Myocardial Abnormalities: A 2022 Update

Preeclampsia is a maternal hypertensive disease, complicating 2–8% of all pregnancies. It has been linked to a 2–7-fold increased risk for the development of cardiovascular disease, including heart failure, later in life. A total of 40% of formerly preeclamptic women develop preclinical heart failure, which may further deteriorate into clinical heart failure. Noninvasive cardiac imaging could assist in the early detection of myocardial abnormalities, especially in the preclinical stage, when these changes are likely to be reversible. Moreover, imaging studies can improve our insights into the relationship between preeclampsia and heart failure and can be used for monitoring. Cardiac ultrasound is used to assess quantitative changes, including the left ventricular cavity volume and wall thickness, myocardial mass, systolic and diastolic function, and strain. Cardiac magnetic resonance imaging may be of additional diagnostic value to assess diffuse and focal fibrosis and perfusion. After preeclampsia, sustained elevated myocardial mass along with reduced myocardial circumferential and longitudinal strain and decreased diastolic function is reported. These findings are consistent with the early phases of heart failure, referred to as preclinical (asymptomatic) or B-stage heart failure. In this review, we will provide an up-to-date overview of the potential of cardiac magnetic resonance imaging and echocardiography in identifying formerly preeclamptic women who are at high risk for developing heart failure. The potential contribution to early cardiac screening of women with a history of preeclampsia and the pros and cons of these imaging modalities are outlined. Finally, recommendations for future research are presented.

Myocardial tissue imaging with cardiovascular magnetic resonance

Alteration in myocardial tissue, such as myocardial fibrosis, edema, inflammation, or accumulation with amyloid, lipids, or iron, has an important role in the cardiac remodeling that leads to diastolic and/or systolic dysfunction and the development of chronic heart failure, increasing the risk of adverse cardiovascular events. Thus, the early detection of changes at myocardial tissue level has great diagnostic and prognostic potential. The gold standard technique to assess these myocardial alterations is endomyocardial biopsy. However, this has been limited to a few patients due to the invasive nature, sampling errors, and its inability to assess the entire myocardium. Cardiovascular magnetic resonance (CMR) has emerged as the gold standard imaging not only for assessing cardiac volume, function quantification, and viability but also for noninvasive myocardial tissue characterization over the past decade. Its ability to characterize myocardial tissue composition is unique among noninvasive imaging modalities in cardiovascular disease. Currently, multi-parametric myocardial characterization with T1, T2, and extracellular volume has the potential to identify and track diffuse pathology in various diseases. In this review article, we present the role of established and emerging CMR techniques in myocardial tissue characterization, with an emphasis on T1 and T2 mapping, in clinical practice.

Bias, Repeatability and Reproducibility of Liver T1 Mapping With Variable Flip Angles

Background

Three‐dimensional variable flip angle (VFA) methods are commonly used for T₁ mapping of the liver, but there is no data on the accuracy, repeatability, and reproducibility of this technique in this organ in a multivendor setting.

Purpose

To measure bias, repeatability, and reproducibility of VFA T₁ mapping in the liver.

Study Type

Prospective observational.

Population

Eight healthy volunteers, four women, with no known liver disease.

Field Strength/Sequence

1.5‐T and 3.0‐T; three‐dimensional steady‐state spoiled gradient echo with VFAs; Look‐Locker.

Assessment

Traveling volunteers were scanned twice each (30 minutes to 3 months apart) on six MRI scanners from three vendors (GE Healthcare, Philips Medical Systems, and Siemens Healthineers) at two field strengths. The maximum period between the first and last scans among all volunteers was 9 months. Volunteers were instructed to abstain from alcohol intake for at least 72 hours prior to each scan and avoid high cholesterol foods on the day of the scan.

Statistical Tests

Repeated measures ANOVA, Student t‐test, Levene's test of variances, and 95% significance level. The percent error relative to literature liver T₁ in healthy volunteers was used to assess bias. The relative error (RE) due to intrascanner and interscanner variation in T₁ measurements was used to assess repeatability and reproducibility.

Results

The 95% confidence interval (CI) on the mean bias and mean repeatability RE of VFA T₁ in the healthy liver was 34 ± 6% and 10 ± 3%, respectively. The 95% CI on the mean reproducibility RE at 1.5 T and 3.0 T was 29 ± 7% and 25 ± 4%, respectively.

Data Conclusion

Bias, repeatability, and reproducibility of VFA T₁ mapping in the liver in a multivendor setting are similar to those reported for breast, prostate, and brain.

Level of Evidence

1

Technical Efficacy Stage

1

A Review of the Role of Imaging Modalities in the Evaluation of Viral Myocarditis with a Special Focus on COVID-19-Related Myocarditis

Viral myocarditis is inflammation of the myocardium secondary to viral infection. The clinical presentation of viral myocarditis is very heterogeneous and can range from nonspecific symptoms of malaise and fatigue in subclinical disease to a more florid presentation, such as acute cardiogenic shock and sudden cardiac death in severe cases. The accurate and prompt diagnosis of viral myocarditis is very challenging. Endomyocardial biopsy is considered to be the gold standard test to confirm viral myocarditis; however, it is an invasive procedure, and the sensitivity is low when myocardial involvement is focal. Cardiac imaging hence plays an essential role in the noninvasive evaluation of viral myocarditis. The current coronavirus disease 2019 (COVID-19) pandemic has generated considerable interest in the use of imaging in the early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related myocarditis. This article reviews the role of various cardiac imaging modalities used in the diagnosis and assessment of viral myocarditis, including COVID-19-related myocarditis.

Improved cardiac T1 mapping accuracy and precision with a new hybrid MOLLI and SASHA technique: MOSHA

PURPOSE

To develop and validate a new myocardial T₁ mapping sequence (MOSHA) which is based on a combination of the modified Look-Locker inversion recovery (MOLLI) and the saturation recovery single-shot acquisition (SASHA) sequences.

METHODS

Prior studies have shown that myocardial T₁ mapping by SASHA is more accurate but less precise than MOLLI. A new myocardial T₁ mapping technique (MOSHA) based on single-shot acquisitions is developed by combining the MOLLI and SASHA sequences. Phantom and patient studies on 15 patients (9 males, median age 21 years) were performed to validate and compare MOSHA with the MOLLI and SASHA sequences in terms of accuracy and precision.

RESULTS

In the phantom study, MOSHA was as accurate as SASHA (P-value = 0.88) and as precise as MOLLI (P-value = 0.59). Similar trends were observed in the patient study. Compared to SASHA, MOSHA accuracy was comparable for blood pre-contrast (P-value≥0.10) and post-contrast (P-value≥0.70), and for myocardium pre-contrast (P-value = 0.70) and post-contrast (P-value = 0.09). Compared to MOLLI, MOSHA precision was lower for blood pre-contrast (P-value<0.01) and higher for blood post-contrast (P-value≤0.01), and comparable for myocardium pre-contrast (P-value = 0.24) and post-contrast (P-value = 0.07). Synthetic Extracellular volume fraction (ECV) calculated by MOSHA was more precise than those of SASHA and MOLLI (P-value ≤0.01).

CONCLUSION

In phantom studies and patients, MOSHA has comparable accuracy as SASHA and nearly similar precision as MOLLI for T₁ mapping. Precision of MOSHA was better than MOLLI and SASHA in synthetic ECV measurements. Therefore, it may be a superior choice in clinical practice for a precise and accurate calculation of T₁ and ECV.

Basics of magnetic resonance imaging and quantitative parameters T1, T2, T2*, T1rho and diffusion-weighted imaging

Magnetic resonance imaging is widely available and accepted as the imaging method of choice for many pediatric body imaging applications. Traditionally, it has been used in a qualitative way, where the images are reported non-numerically by radiologists. But now MRI machines have built-in post-processing software connected to the scanner and the database of MR images. This setting enables and encourages simple quantitative analysis of MR images. In this paper, the author reviews the fundamentals of MRI and discusses the most common quantitative MRI techniques for body imaging: T1, T2, T2*, T1rho and diffusion-weighted imaging (DWI). For each quantitative imaging method, this article reviews the technique, its measurement mechanism, and selected clinical applications to body imaging.

Accelerated cardiac T1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T1 estimation approach

PURPOSE

To develop and evaluate MyoMapNet, a rapid myocardial T1 mapping approach that uses fully connected neural networks (FCNN) to estimate T1 values from four T1-weighted images collected after a single inversion pulse in four heartbeats (Look-Locker, LL4).

METHOD

We implemented an FCNN for MyoMapNet to estimate T1 values from a reduced number of T1-weighted images and corresponding inversion-recovery times. We studied MyoMapNet performance when trained using native, post-contrast T1, or a combination of both. We also explored the effects of number of T1-weighted images (four and five) for native T1. After rigorous training using in-vivo modified Look-Locker inversion recovery (MOLLI) T1 mapping data of 607 patients, MyoMapNet performance was evaluated using MOLLI T1 data from 61 patients by discarding the additional T1-weighted images. Subsequently, we implemented a prototype MyoMapNet and LL4 on a 3 T scanner. LL4 was used to collect T1 mapping data in 27 subjects with inline T1 map reconstruction by MyoMapNet. The resulting T1 values were compared to MOLLI.

RESULTS

MyoMapNet trained using a combination of native and post-contrast T1-weighted images had excellent native and post-contrast T1 accuracy compared to MOLLI. The FCNN model using four T1-weighted images yields similar performance compared to five T1-weighted images, suggesting that four T1 weighted images may be sufficient. The inline implementation of LL4 and MyoMapNet enables successful acquisition and reconstruction of T1 maps on the scanner. Native and post-contrast myocardium T1 by MOLLI and MyoMapNet was 1170 ± 55 ms vs. 1183 ± 57 ms (P = 0.03), and 645 ± 26 ms vs. 630 ± 30 ms (P = 0.60), and native and post-contrast blood T1 was 1820 ± 29 ms vs. 1854 ± 34 ms (P = 0.14), and 508 ± 9 ms vs. 514 ± 15 ms (P = 0.02), respectively.

CONCLUSION

A FCNN, trained using MOLLI data, can estimate T1 values from only four T1-weighted images. MyoMapNet enables myocardial T1 mapping in four heartbeats with similar accuracy as MOLLI with inline map reconstruction.