In Vivo Quantification of Cardiac Microstructure with Convex Optimized Diffusion Weighted MRI

Diffusion weighted imaging (DWI) is a powerful quantitative magnetic resonance imaging (MRI) technique that can probe tissues in vivo at the microscopic level and provide insight into cellular microstructural environment. Cardiac DWI has great potential value in its ability to answer open questions regarding myocardial structure, dynamics, and remodeling. Unfortunately, several technical limitations of current DWI techniques make its application in the beating heart very challenging, which leads to erroneous or inconsistent results. Amongst the challenges are an extreme sensitivity to bulk physiological motion, low signal to noise ratios (SNR), long scan times, and geometric image distortions. In this dissertation, these limitations are addressed with novel technical developments applied to the DWI pulse sequence including convex optimized diffusion gradient waveform design and multi-parametric tissue characterization.A brief introduction to Nuclear Magnetic Resonance (NMR) and MRI is provided in Chapter 1. This leads into a description of the fundamental components of a DWI acquisition in Chapter 2 and an overview of the current state of cardiac DWI in Chapter 3.In Chapter 4, a novel DWI strategy called Convex Optimized Diffusion Encoding (CODE) is described. CODE is a mathematical framework that formulates diffusion encoding gradient design as a convex optimization problem and automatically generates motion compensated (MOCO) waveforms that achieve the shortest possible echo times (TE) and thus improve SNR. First and second order moment nulled CODE (CODE-M1M2) permits DWI that is robust to cardiac motion with higher SNR than an existing MOCO technique. First order motion compensated CODE-M1 also improves robustness to cardiac induced motion in liver DWI with higher SNR than M1 nulled bipolar DWI. CODE can also be used for non-motion compensated DWI and improves SNR compared with traditional monopolar DWI in the brain.In Chapter 5 we present a multi-parametric DWI strategy that simultaneously yields maps of the apparent diffusion coefficient (ADC) and T2 relaxation time constant in the heart (T2+ADC). Typically, DWI protocols include multiple acquisitions with a range of diffusion encoding strengths (b-value), but with constant TE to isolate the effect of diffusion of the signal. The joint T2+ADC approach varies both b-value and TE within the acquisition to facilitate estimation of both ADC and T2 relaxation. T2+ADC permits joint reconstruction with no increase in scan time compared with DWI alone and no effect on ADC measurement.In Chapter 6 we use CODE-M1M2 diffusion encoding to perform cardiac diffusion tensor imaging (cDTI) and generate maps of myocardial microstructure in healthy volunteers. cDTI can be used to map myocardial fiber and myolaminar sheetlet orientations, which can contribute to our understanding of ventricular microstructure in health and disease and facilitate sophisticated mechanical models of cardiac dynamics. However, it is important to understand the uncertainty underlying these measurements to inform interpretation and define acquisition limitations. We apply a previously described bootstrap technique to measure the uncertainty in the diffusion tensors derived from CODE-M1M2 cDTI and establish achievable levels of precision in clinically feasible scan times.In Chapter 7 the CODE framework is extended to compensate for the effect of eddy currents, which are a common cause of image distortions in DWI and DTI. Diffusion encoding gradients must be very strong to encode microscopic molecular displacements and these strong gradient pulses induce unwanted eddy currents in conductive MRI hardware components. If not addressed, eddy currents lead to distorted images and corrupted diffusion parameter estimates. We incorporate an eddy current model into the CODE optimization framework to develop eddy current nulled CODE (EN-CODE). EN-CODE accomplishes eddy current nulling with TEs that are comparable to traditional monopolar encoding and much shorter than the established twice refocused spin echo (TRSE) technique for eddy current nulling.The developments described in this dissertation represent an improvement in the flexibility, efficiency, and robustness of diffusion encoding. The CODE framework can also be easily modified to address additional constraints and thus may prove useful in currently unforeseen applications

Eddy current-nulled convex optimized diffusion encoding (EN-CODE) for distortion-free diffusion tensor imaging with short echo times.

PurposeTo design and evaluate eddy current-nulled convex optimized diffusion encoding (EN-CODE) gradient waveforms for efficient diffusion tensor imaging (DTI) that is free of eddy current-induced image distortions.MethodsThe EN-CODE framework was used to generate diffusion-encoding waveforms that are eddy current-compensated. The EN-CODE DTI waveform was compared with the existing eddy current-nulled twice refocused spin echo (TRSE) sequence as well as monopolar (MONO) and non-eddy current-compensated CODE in terms of echo time (TE) and image distortions. Comparisons were made in simulations, phantom experiments, and neuro imaging in 10 healthy volunteers.ResultsThe EN-CODE sequence achieved eddy current compensation with a significantly shorter TE than TRSE (78 versus 96 ms) and a slightly shorter TE than MONO (78 versus 80 ms). Intravoxel signal variance was lower in phantoms with EN-CODE than with MONO (13.6 ± 11.6 versus 37.4 ± 25.8) and not different from TRSE (15.1 ± 11.6), indicating good robustness to eddy current-induced image distortions. Mean fractional anisotropy values in brain edges were also significantly lower with EN-CODE than with MONO (0.16 ± 0.01 versus 0.24 ± 0.02, P < 1 x 10-5 ) and not different from TRSE (0.16 ± 0.01 versus 0.16 ± 0.01, P = nonsignificant).ConclusionsThe EN-CODE sequence eliminated eddy current-induced image distortions in DTI with a TE comparable to MONO and substantially shorter than TRSE. Magn Reson Med 79:663-672, 2018. © 2017 International Society for Magnetic Resonance in Medicine

Eddy current-nulled convex optimized diffusion encoding (EN-CODE) for distortion-free diffusion tensor imaging with short echo times.

PurposeTo design and evaluate eddy current-nulled convex optimized diffusion encoding (EN-CODE) gradient waveforms for efficient diffusion tensor imaging (DTI) that is free of eddy current-induced image distortions.MethodsThe EN-CODE framework was used to generate diffusion-encoding waveforms that are eddy current-compensated. The EN-CODE DTI waveform was compared with the existing eddy current-nulled twice refocused spin echo (TRSE) sequence as well as monopolar (MONO) and non-eddy current-compensated CODE in terms of echo time (TE) and image distortions. Comparisons were made in simulations, phantom experiments, and neuro imaging in 10 healthy volunteers.ResultsThe EN-CODE sequence achieved eddy current compensation with a significantly shorter TE than TRSE (78 versus 96 ms) and a slightly shorter TE than MONO (78 versus 80 ms). Intravoxel signal variance was lower in phantoms with EN-CODE than with MONO (13.6 ± 11.6 versus 37.4 ± 25.8) and not different from TRSE (15.1 ± 11.6), indicating good robustness to eddy current-induced image distortions. Mean fractional anisotropy values in brain edges were also significantly lower with EN-CODE than with MONO (0.16 ± 0.01 versus 0.24 ± 0.02, P < 1 x 10-5 ) and not different from TRSE (0.16 ± 0.01 versus 0.16 ± 0.01, P = nonsignificant).ConclusionsThe EN-CODE sequence eliminated eddy current-induced image distortions in DTI with a TE comparable to MONO and substantially shorter than TRSE. Magn Reson Med 79:663-672, 2018. © 2017 International Society for Magnetic Resonance in Medicine

Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted MRI.

PurposeTo evaluate convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted imaging (DWI).MethodsDiffusion-encoding gradient waveforms were designed for a range of b-values and spatial resolutions with and without motion compensation using the CODE framework. CODE, first moment (M1 ) nulled CODE-M1 , and first and second moment (M2 ) nulled CODE-M1 M2 were used to acquire neuro, liver, and cardiac ADC maps in healthy subjects (n=10) that were compared respectively to monopolar (MONO), BIPOLAR (M1  = 0), and motion-compensated (MOCO, M1  + M2  = 0) diffusion encoding.ResultsCODE significantly improved the SNR of neuro ADC maps compared with MONO (19.5 ± 2.5 versus 14.5 ± 1.9). CODE-M1 liver ADCs were significantly lower (1.3 ± 0.1 versus 1.8 ± 0.3 × 10-3 mm2 /s, ie, less motion corrupted) and more spatially uniform (6% versus 55% ROI difference) than MONO and had higher SNR than BIPOLAR (SNR = 14.9 ± 5.3 versus 8.0 ± 3.1). CODE-M1 M2 cardiac ADCs were significantly lower than MONO (1.9 ± 0.6 versus 3.8 ± 0.3 x10-3 mm2 /s) throughout the cardiac cycle and had higher SNR than MOCO at systole (9.1 ± 3.9 versus 7.0 ± 2.6) while reporting similar ADCs (1.5 ± 0.2 versus 1.4 ± 0.6 × 10-3 mm2 /s).ConclusionsCODE significantly improved SNR for ADC mapping in the brain, liver and heart, and significantly improved DWI bulk motion robustness in the liver and heart. Magn Reson Med 77:717-729, 2017. © 2016 International Society for Magnetic Resonance in Medicine

Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted MRI.

PurposeTo evaluate convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted imaging (DWI).MethodsDiffusion-encoding gradient waveforms were designed for a range of b-values and spatial resolutions with and without motion compensation using the CODE framework. CODE, first moment (M1 ) nulled CODE-M1 , and first and second moment (M2 ) nulled CODE-M1 M2 were used to acquire neuro, liver, and cardiac ADC maps in healthy subjects (n=10) that were compared respectively to monopolar (MONO), BIPOLAR (M1  = 0), and motion-compensated (MOCO, M1  + M2  = 0) diffusion encoding.ResultsCODE significantly improved the SNR of neuro ADC maps compared with MONO (19.5 ± 2.5 versus 14.5 ± 1.9). CODE-M1 liver ADCs were significantly lower (1.3 ± 0.1 versus 1.8 ± 0.3 × 10-3 mm2 /s, ie, less motion corrupted) and more spatially uniform (6% versus 55% ROI difference) than MONO and had higher SNR than BIPOLAR (SNR = 14.9 ± 5.3 versus 8.0 ± 3.1). CODE-M1 M2 cardiac ADCs were significantly lower than MONO (1.9 ± 0.6 versus 3.8 ± 0.3 x10-3 mm2 /s) throughout the cardiac cycle and had higher SNR than MOCO at systole (9.1 ± 3.9 versus 7.0 ± 2.6) while reporting similar ADCs (1.5 ± 0.2 versus 1.4 ± 0.6 × 10-3 mm2 /s).ConclusionsCODE significantly improved SNR for ADC mapping in the brain, liver and heart, and significantly improved DWI bulk motion robustness in the liver and heart. Magn Reson Med 77:717-729, 2017. © 2016 International Society for Magnetic Resonance in Medicine

Simultaneous measurement of T2 and apparent diffusion coefficient (T2 +ADC) in the heart with motion-compensated spin echo diffusion-weighted imaging.

PURPOSE:To evaluate a technique for simultaneous quantitative T2 and apparent diffusion coefficient (ADC) mapping in the heart (T2 +ADC) using spin echo (SE) diffusion-weighted imaging (DWI). THEORY AND METHODS:T2 maps from T2 +ADC were compared with single-echo SE in phantoms and with T2 -prepared (T2 -prep) balanced steady-state free precession (bSSFP) in healthy volunteers. ADC maps from T2 +ADC were compared with conventional DWI in phantoms and in vivo. T2 +ADC was also demonstrated in a patient with acute myocardial infarction (MI). RESULTS:Phantom T2 values from T2 +ADC were closer to a single-echo SE reference than T2 -prep bSSFP (-2.3 ± 6.0% vs 22.2 ± 16.3%; P < 0.01), and ADC values were in excellent agreement with DWI (0.28 ± 0.4%). In volunteers, myocardial T2 values from T2 +ADC were significantly shorter than T2 -prep bSSFP (35.8 ± 3.1 vs 46.8 ± 3.8 ms; P < 0.01); myocardial ADC was not significantly (N.S.) different between T2 +ADC and conventional motion-compensated DWI (1.39 ± 0.18 vs 1.38 ± 0.18 mm2 /ms; P = N.S.). In the patient, T2 and ADC were both significantly elevated in the infarct compared with remote myocardium (T2 : 40.4 ± 7.6 vs 56.8 ± 22.0; P < 0.01; ADC: 1.47 ± 0.59 vs 1.65 ± 0.65 mm2 /ms; P < 0.01). CONCLUSION:T2 +ADC generated coregistered, free-breathing T2 and ADC maps in healthy volunteers and a patient with acute MI with no cost in accuracy, precision, or scan time compared with DWI. Magn Reson Med 79:654-662, 2018. © 2017 International Society for Magnetic Resonance in Medicine