Feasibility of free-breathing quantitative myocardial perfusion using multi-echo Dixon magnetic resonance imaging

Role of pulmonary perfusion magnetic resonance imaging for the diagnosis of pulmonary hypertension: A review

Among five types of pulmonary hypertension, chronic thromboembolic pulmonary hypertension (CTEPH) is the only curable form, but prompt and accurate diagnosis can be challenging. Computed tomography and nuclear medicine-based techniques are standard imaging modalities to non-invasively diagnose CTEPH, however these are limited by radiation exposure, subjective qualitative bias, and lack of cardiac functional assessment. This review aims to assess the methodology, diagnostic accuracy of pulmonary perfusion imaging in the current literature and discuss its advantages, limitations and future research scope.

High-Resolution Free-Breathing Quantitative First-Pass Perfusion Cardiac MR Using Dual-Echo Dixon With Spatio-Temporal Acceleration

Introduction

To develop and test the feasibility of free-breathing (FB), high-resolution quantitative first-pass perfusion cardiac MR (FPP-CMR) using dual-echo Dixon (FOSTERS; Fat-water separation for mOtion-corrected Spatio-TEmporally accelerated myocardial peRfuSion).

Materials and Methods

FOSTERS was performed in FB using a dual-saturation single-bolus acquisition with dual-echo Dixon and a dynamically variable Cartesian k-t undersampling (8-fold) approach, with low-rank and sparsity constrained reconstruction, to achieve high-resolution FPP-CMR images. FOSTERS also included automatic in-plane motion estimation and T2* correction to obtain quantitative myocardial blood flow (MBF) maps. High-resolution (1.6 x 1.6 mm²) FB FOSTERS was evaluated in eleven patients, during rest, against standard-resolution (2.6 x 2.6 mm²) 2-fold SENSE-accelerated breath-hold (BH) FPP-CMR. In addition, MBF was computed for FOSTERS and spatial wavelet-based compressed sensing (CS) reconstruction. Two cardiologists scored the image quality (IQ) of FOSTERS, CS, and standard BH FPP-CMR images using a 4-point scale (1–4, non-diagnostic – fully diagnostic).

Results

FOSTERS produced high-quality images without dark-rim and with reduced motion-related artifacts, using an 8x accelerated FB acquisition. FOSTERS and standard BH FPP-CMR exhibited excellent IQ with an average score of 3.5 ± 0.6 and 3.4 ± 0.6 (no statistical difference, p > 0.05), respectively. CS images exhibited severe artifacts and high levels of noise, resulting in an average IQ score of 2.9 ± 0.5. MBF values obtained with FOSTERS presented a lower variance than those obtained with CS.

Discussion

FOSTERS enabled high-resolution FB FPP-CMR with MBF quantification. Combining motion correction with a low-rank and sparsity-constrained reconstruction results in excellent image quality.

A Patch-Wise Deep Learning Approach for Myocardial Blood Flow Quantification with Robustness to Noise and Nonrigid Motion

Quantitative analysis of dynamic contrast-enhanced cardiovascular MRI (cMRI) datasets enables the assessment of myocardial blood flow (MBF) for objective evaluation of ischemic heart disease in patients with suspected coronary artery disease. State-of-the-art MBF quantification techniques use constrained deconvolution and are highly sensitive to noise and motion-induced errors, which can lead to unreliable outcomes in the setting of high-resolution MBF mapping. To overcome these limitations, recent iterative approaches incorporate spatial-smoothness constraints to tackle pixel-wise MBF mapping. However, such iterative methods require a computational time of up to 30 minutes per acquired myocardial slice, which is a major practical limitation. Furthermore, they cannot enforce robustness to residual nonrigid motion which can occur in clinical stress/rest studies of patients with arrhythmia. We present a non-iterative patch-wise deep learning approach for pixel-wise MBF quantification wherein local spatio-temporal features are learned from a large dataset of myocardial patches acquired in clinical stress/rest cMRI studies. Our approach is scanner-independent, computationally efficient, robust to noise, and has the unique feature of robustness to motion-induced errors. Numerical and experimental results obtained using real patient data demonstrate the effectiveness of our approach.Clinical Relevance- The proposed patch-wise deep learning approach significantly improves the reliability of high-resolution myocardial blood flow quantification in cMRI by improving its robustness to noise and nonrigid myocardial motion and is up to 300-fold faster than state-of-the-art iterative approaches.

Cardiac adiposity as a modulator of cardiovascular disease in HIV

BACKGROUND

With the number of people living with human immunodeficiency virus (HIV) steadily increasing, cardiovascular disease has emerged as a leading cause of non-HIV related mortality. People living with HIV (PLWH) appear to be at increased risk of coronary artery disease and heart failure (HF), while the underlying mechanism appears to be multifactorial. In the general population, ectopic cardiac adiposity has been highlighted as an important modulator of accelerated coronary artery atherosclerosis, arrhythmogenesis and HF with preserved ejection fraction (HFpEF). Cardiac adiposity is also strongly linked with obesity, especially with visceral adipose tissue accumulation.

AIMS

This review aims to summarize the possible role of cardiac fat depositions, assessed by imaging modalities,as potential contributors to the increased cardiac morbidity and mortality seen in PLWH, as well as therapeutic targets in the current ART era.

MATERIALS & METHODS

Review of contemporary literature on this topic.

DISCUSSION

Despite antiretroviral therapy (ART), PLWH have evidence of persistent, HIV-related systemic inflammation and body fat alterations. Cardiac adiposity can play an additional role in the pathogenesis of cardiovascular disease in the HIV setting. Imaging modalities such as echocardiography, cardiac multidetector computed tomography and cardiac magnetic resonance have demonstrated increased adipose tissue. Studies show that high cardiac fat depots play an additive role in promoting coronary artery atherosclerosis and HFpEF in PLWH. Systemic inflammation due to HIV infection, metabolic adverse effects of ART, adipose alterations in the ageing HIV population, inflammation and immune activation are likely important mechanisms for adipose dysfunction and disproportionately occurrence of ectopic fat depots in the heart among PLWH.

CONCLUSIONS

High cardiac adiposity seems to plays an additive role in promoting coronary artery atherosclerosis and HFpEF in PLWH. The underlying mechanisms are multiple and warrant further investigation. Improved understanding of the regulating mechanisms that increase cardiovascular risk in HIV infection may give rise to more tailored therapeutic strategies targeting cardiac fat depots.

Dixon-T2WI magnetic resonance imaging at 3 tesla outperforms conventional imaging for thyroid eye disease

OBJECTIVES

To determine the diagnostic performances of a single Dixon-T2-weighted imaging (WI) sequence compared to a conventional protocol including T1-, T2-, and fat-suppressed T2-weighted MRI at 3 T when assessing thyroid eye disease (TED).

MATERIALS AND METHODS

This IRB-approved prospective single-center study enrolled participants presenting with confirmed TED from April 2015 to October 2019. They underwent an MRI, including a conventional protocol and a Dixon-T2WI sequence. Two neuroradiologists, blinded to all data, read both datasets independently and randomly. They assessed the presence of extraocular muscle (EOM) inflammation, enlargement, fatty degeneration, or fibrosis as well as the presence of artifacts. The Wilcoxon signed-rank test was used.

RESULTS

Two hundred six participants were enrolled (135/206 [66%] women, 71/206 [34%] men, age 52.3 ± 13.2 years). Dixon-T2WI was significantly more likely to detect at least one inflamed EOM as compared to the conventional set (248/412 [60%] versus 228/412 [55%] eyes; (p = 0.02). Dixon-T2WI was more sensitive and specific than the conventional set for assessing muscular inflammation (100% versus 94.7% and 71.2% versus 68.5%, respectively). Dixon-T2WI was significantly less likely to show major or minor artifacts as compared to fat-suppressed T2WI (20/412 [5%] versus 109/412 [27%] eyes, p < 0.001, and 175/412 [42%] versus 257/412 [62%] eyes, p < 0.001). Confidence was significantly higher with Dixon-T2WI than with the conventional set (2.35 versus 2.24, p = 0.003).

CONCLUSION

Dixon-T2WI showed higher sensitivity and specificity and showed fewer artifacts than a conventional protocol when assessing thyroid eye disease, in addition to higher self-reported confidence.

KEY POINTS

• Dixon-T2WI has better sensitivity and specificity than a conventional protocol for assessing inflamed extraocular muscles in patients with thyroid eye disease. • Dixon-T2WI shows significantly fewer artifacts than fat-suppressed T2WI. • Dixon-T2WI is faster and is associated with significantly higher self-reported reader confidence as compared to a conventional protocol when assessing inflammatory extraocular muscles.