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MATI (Microstructural Analysis Toolbox for Imaging) is a versatile MATLAB-based toolbox that combines both simulation and data fitting capabilities for microstructural dMRI research. It provides a user-friendly, GUI-driven interface that enables researchers, including those without programming experience, to perform advanced MRI simulations and data analyses. For simulation, MATI supports arbitrary microstructural modeled tissues and pulse sequences. For data fitting, MATI supports a range of fitting methods including traditional non-linear least squares, Bayesian approaches, machine learning, and dictionary matching methods, allowing users to tailor analyses based on specific research needs. Optimized with vectorized matrix operations and high-performance numerical libraries, MATI achieves high computational efficiency, enabling rapid simulations and data fitting on CPU and GPU hardware. While designed for microstructural dMRI, MATI's generalized framework can be extended to other imaging methods, making it a flexible and scalable tool for quantitative MRI research. By enhancing accessibility and efficiency, MATI offers a significant step toward translating advanced imaging techniques into clinical applications.

Early assessment of tumor therapeutic response is an important topic in precision medicine to optimize personalized treatment regimens and reduce unnecessary toxicity, cost, and delay. Although diffusion MRI (dMRI) has shown potential to address this need, its predictive accuracy is limited, likely due to its unspecific sensitivity to overall pathological changes. In this work, we propose a new quantitative dMRI-based method dubbed EXCHANGE (MRI of water Exchange, Confined and Hindered diffusion under Arbitrary Gradient waveform Encodings) for simultaneous mapping of cell size, cell density, and transcytolemmal water exchange. Such rich microstructural information comprehensively evaluates tumor pathologies at the cellular level. Validations using numerical simulations and in vitro cell experiments confirmed that the EXCHANGE method can accurately estimate mean cell size, density, and water exchange rate constants. The results from in vivo animal experiments show the potential of EXCHANGE for monitoring tumor treatment response. Finally, the EXCHANGE method was implemented in breast cancer patients with neoadjuvant chemotherapy, demonstrating its feasibility in assessing tumor therapeutic response in clinics. In summary, a new, quantitative dMRI-based EXCHANGE method was proposed to comprehensively characterize tumor microstructural properties at the cellular level, suggesting a unique means to monitor tumor treatment response in clinical practice., Comment: 40 pages, 6 figures

The K\"arger model and its derivatives have been widely used to incorporate transcytolemmal water exchange rate, an essential characteristic of living cells, into analyses of diffusion MRI (dMRI) signals from tissues. The K\"arger model consists of two homogeneous exchanging components coupled by an exchange rate constant and assumes measurements are made with sufficiently long diffusion time and slow water exchange. Despite successful applications, it remains unclear whether these assumptions are generally valid for practical dMRI sequences and biological tissues. In particular, barrier-induced restrictions to diffusion produce inhomogeneous magnetization distributions in relatively large-sized compartments such as cancer cells, violating the above assumptions. The effects of this inhomogeneity are usually overlooked. We performed computer simulations to quantify how restriction effects, which in images produce edge enhancements at compartment boundaries, influence different variants of the K\"arger-model. The results show that the edge enhancement effect will produce larger, time-dependent estimates of exchange rates in e.g., tumors with relatively large cell sizes (>10 {\mu}m), resulting in overestimations of water exchange as previously reported. Moreover, stronger diffusion gradients, longer diffusion gradient durations, and larger cell sizes, all cause more pronounced edge enhancement effects. This helps us to better understand the feasibility of the K\"arger model in estimating water exchange in different tissue types and provides useful guidance on signal acquisition methods that may mitigate the edge enhancement effect. This work also indicates the need to correct the overestimated transcytolemmal water exchange rates obtained assuming the K\"arger-model., Comment: 37 pages, 8 figures

Signal to noise ratios (SNR) in magnetic resonance microscopy images are limited by acquisition times and the decreasing number of spins in smaller voxels. Significant SNR gains from cooling of the RF receiver are only realized when the Johnson noise generated within the RF hardware is large compared to the electromagnetic noise produced by the sample. Cryogenic cooling of imaging probes is common in high field systems but proves difficult to insulate the sample from extreme temperatures. We designed a chamber to cool only the tune and match circuitry to show it is possible to achieve much of the available SNR gain available for cooled coils. We designed a microcoil circuit to resonate at 650 MHz for imaging on a 15.2 T scanner. Surface loops and solenoids of varying diameters were tested to determine the largest diameter coil that demonstrated significant SNR gains from cooling. A liquid N2 cryochamber was designed to cool the circuitry while leaving the RF coil in ambient air. As the cryochamber was filled with liquid N2, Q-factors were measured on the bench while monitoring the coil's surface temperature. Improvements of SNR on images of solutions were demonstrated via cooling the tune and match circuit in the magnet bore. At 650 MHz, loops and solenoids < 3 mm in diameter showed significant improvements in quality factor on the bench. The resistance of the variable capacitors and the coaxial cable were measured to be 45% and 32% of room temperature values near the Larmor frequency. Images obtained with a 2 turn, 3 mm diameter loop with the matching circuit at room temperature and then cooled with liquid nitrogen demonstrated SNR improvements of a factor of 2. By cooling the tune and match circuit and leaving the surface loop in ambient air, SNR was improved by a factor of 2. The results are significant because it allows for more space to insulate the sample from extreme temperatures., Comment: 33 pages, 10 figures, 1 table, 4 supplemental figures, 1 supplemental table

Magnetic resonance microscopy images at cellular resolution (< 10 microns) are limited by diffusion. SNR and spatial resolution suffer from the dephasing of transverse magnetization caused by diffusion of spins in strong gradients. Such effects may be reduced by using phase encoding instead of frequency encoding readout gradients. Demonstration of the benefits of phase encoding are lacking, and the conditions in which it is preferred are not clearly established. We quantify when phase encoding outperforms a readout gradient with emphasis on the detrimental effects of diffusion on SNR and resolution. A 15.2T MRI scanner, with 1 T/m gradients, and micro solenoid RF coils < 1 mm in diameter, were used to quantify diffusion effects on resolution and SNR of frequency and phase encoded acquisitions. Frequency and phase encoding resolution and SNR per square root time were calculated and measured for images at the diffusion limited resolution. The point-spread-function was measured for phase and frequency encoding using additional constant time gradients with voxels 3-15 microns. The effect of diffusion during the readout gradient on SNR was experimentally demonstrated. The achieved resolutions of frequency and phase encoded acquisitions were measured via the point-spread-function. SNR per square root time and actual resolution were calculated for a wide range of gradient amplitudes, diffusion coefficients, and relaxation properties. The results provide a practical guide on how to choose between phase and frequency encoding. Images of excised rat spinal cord at 10 x 10 microns in-plane demonstrate benefits of phase encoding in the form of higher measured resolution and SNR vs the same image acquired with a conventional readout. We demonstrate the extent to which phase encoding outperforms readout gradients in SNR and resolution over a wide range of voxel sizes, sample, and hardware properties., Comment: 36 pages, 9 figures, 1 table, and 4 supplemental figures. Submitted to Journal of Magnetic Resonance; cleaned up metadata, fixed heading typo

Purpose: Cell size is a fundamental characteristic of all tissues, and changes in cell size in cancer reflect tumor status and response to treatments, such as apoptosis and cell cycle arrest. Unfortunately, cell size can only be obtained by pathologic evaluation of the tumor in the current standard of care. Previous imaging approaches can be implemented on only animal MRI scanners or require relatively long acquisition times that are undesirable for clinical imaging. There is a need to develop cell size imaging for clinics. Experimental Design: We propose a new method, IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) that can characterize mean cell sizes in solid tumors. We report the use of combined sequences with different gradient waveforms on human MRI and analytical equations that link DWI signals of real gradient waveforms and specific microstructural parameters such as cell size. We also describe comprehensive validations using computer simulations, cell experiments in vitro, and animal experiments in vivo and finally demonstrate applications in pre-operative breast cancer patients. Results: With fast acquisitions (~ 7 mins), IMPULSED can provide high-resolution (1.3 mm in-plane) mapping of mean cell size of human tumors in vivo on currently-available 3T MRI scanners. All validations suggest IMPULSED provide accurate and reliable measurements of mean cell size. Conclusion: The proposed IMPULSED method can assess cell size variations in the tumor of breast cancer patients, which may have the potential to assess early response to neoadjuvant therapy.

Endogenous chemical exchange saturation transfer (CEST) effects are always diluted by competing effects such as direct water proton saturation (spillover) and macromolecular magnetization transfer (MT). This leads to T2-and MT-shine-through effects in the actual biochemical contrast of CEST. Therefore, a simple evaluation algorithm which corrects the CEST signal was searched for. By employing a recent eigenspace theory valid for spinlock and continuous wave (cw) CEST we predict that the inverse Z-spectrum is beneficial to Z-spectrum itself. Based on this we propose a new spillover- and MT-corrected magnetization transfer ratio (MTRRex) yielding Rex, the exchange dependent relaxation rate in the rotating frame. For verification, the amine proton exchange of creatine in solutions with different agar concentration was studied experimentally at clinical field strength of 3T. In contrast to the compared standard evaluation for pulsed CEST experiments, MTRasym, our approach shows no T2 or MT shine through effect. We demonstrate that spillover can be corrected properly and also quantitative evaluation of pH and creatine concentration is possible which proves MTRRex as quantitative CEST-MRI method. A spillover correction is of special interest for clinical static field strengths and protons resonating near the water peak. This is the case for -OH-CEST effects like gagCEST or glucoCEST, but also amine exchange of creatine or glutamate which require high B1. Although, only showed for amine exchange, we propose our normalization to work generally for DIACEST, PARACEST in slow- and fast exchange regime not just as a correction, but also for quantitative CEST-MRI. Applied to acute stroke induced in rat brain, the corrected CEST signal shows significantly higher contrast between stroke area and normal tissue as well as less B1 dependency compared to conventional approaches.