Flexible, 31-Channel breast coil for enhanced parallel imaging performance at 3T

Denoising and Multiple Tissue Compartment Visualization of Multi-b-Valued Breast Diffusion MRI

BACKGROUND

Multi-b-valued/multi-shell diffusion provides potentially valuable metrics in breast MRI but suffers from low signal-to-noise ratio and has potentially long scan times.

PURPOSE

To investigate the effects of model-based denoising with no loss of spatial resolution on multi-shell breast diffusion MRI; to determine the effects of downsampling on multi-shell diffusion; and to quantify these effects in multi-b-valued (three directions per b-value) acquisitions.

STUDY TYPE

Prospective ("fully-sampled" multi-shell) and retrospective longitudinal (multi-b).

SUBJECTS

One normal subject (multi-shell) and 10 breast cancer subjects imaging at four timepoints (multi-b).

FIELD STRENGTH/SEQUENCE

3T multi-shell acquisition and 1.5T multi-b acquisition.

ASSESSMENT

The "fully-sampled" multi-shell acquisition was retrospectively downsampled to determine the bias and error from downsampling. Mean, axial/parallel, radial diffusivity, and fractional anisotropy (FA) were analyzed. Denoising was applied retrospectively to the multi-b-valued breast cancer subject dataset and assessed subjectively for image noise level and tumor conspicuity.

STATISTICAL TESTS

Parametric paired t-test (P < 0.05 considered statistically significant) on mean and coefficient of variation of each metric-the apparent diffusion coefficient (ADC) from all b-values, fast ADC, slow ADC, and perfusion fraction. Paired and two-sample t-tests for each metric comparing normal and tumor tissue.

RESULTS

In the multi-shell data, denoising effectively suppressed FA (-45% to -78%), with small biases in mean diffusivity (-5% in normal, +23% in tumor, and -4% in vascular compartments). In the multi-b data, denoising resulted in small biases to the ADC metrics in tumor and normal contralateral tissue (by -3% to +11%), but greatly reduced the coefficient of variation for every metric (by -1% to -24%). Denoising improved differentiation of tumor and normal tissue regions in most metrics and timepoints; subjectively, image noise level and tumor conspicuity were improved in the fast ADC maps.

DATA CONCLUSION

Model-based denoising effectively suppressed erroneously high FA and improved the accuracy of diffusivity metrics.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY STAGE: 1.

Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer among women worldwide, and early detection remains a principal factor for improved patient outcomes and reduced mortality. Clinically, magnetic resonance imaging (MRI) techniques are routinely used in determining benign and malignant tumor phenotypes and for monitoring treatment outcomes. Static MRI techniques enable superior structural contrast between adipose and fibroglandular tissues, while dynamic MRI techniques can elucidate functional characteristics of malignant tumors. The preferred clinical procedure-dynamic contrast-enhanced MRI-illuminates the hypervascularity of breast tumors through a gadolinium-based contrast agent; however, accumulation of the potentially toxic contrast agent remains a major limitation of the technique, propelling MRI research toward finding an alternative, noninvasive method. Three such techniques are magnetic resonance spectroscopy, chemical exchange saturation transfer, and non-contrast diffusion weighted imaging. These methods shed light on underlying chemical composition, provide snapshots of tissue metabolism, and more pronouncedly characterize microstructural heterogeneity. This review article outlines the present state of clinical MRI for breast cancer and examines several research techniques that demonstrate capacity for clinical translation. Ultimately, multi-parametric MRI-incorporating one or more of these emerging methods-presently holds the best potential to afford improved specificity and deliver excellent accuracy to clinics for the prediction, detection, and monitoring of breast cancer.

A Flexible and Modular Receiver Coil Array for Magnetic Resonance Imaging

We propose a flexible form-fittingMRI receiver coil array assembledby individualcoilmodules. This design targetsMRI applications requiring a receiver array conforming to the anatomy of various shapes or sizes. Coil modules in our proposed array were arranged with gaps between them. Each coil module had a circumferential shielding structure stacked on top of the coil. Together they achieve robust decoupling when the array was bent differently. Two types of the circumferential shielding structure were investigatedby using full-wave electromagnetic simulations and imaging experiments. Results showed that our flexible coil array had good decoupling between coils whether they were on a flat or curved surface with the S21 magnitude ranged between -18.1 dB and -19.9 dB in simulations, and with the average of off-diagonal entries of the noise correlationmatrix less than 0.047 in experimentalmeasurements. Anatomical images of human brain, calf, and knee were acquired by our seven-channel prototype on a 3T MRI system. The maximal and the average SNR within 50 mm from our array surpassed those from the commercial 32-channel head and 4-channel flexible coil arrays by 2.63/1.35-fold and 3.89/1.50-fold, respectively.

Size-adaptable 13-channel receive array for brain MRI in human neonates at 3 T

Neonatal brain injury suffered by preterm infants and newborns with some medical conditions can cause significant neurodevelopmental disabilities. MRI is a preferred method to detect these accidents and perform in vivo evaluation of the brain. However, the commercial availability and optimality of receive coils for the neonatal brain is limited, which in many cases leads to images lacking in quality. As extensively demonstrated, receive arrays closely positioned around the scanned part provide images with high signal-to-noise ratios (SNRs). The present work proposes a pneumatic-based MRI receive array that can physically adapt to infant head dimensions from 27-week premature to 1.5 months old. Average SNR increases of up to 68% in the head region and 122% in the cortex region, compared with a 32-channel commercial head coil, were achieved at 3 T. The consistent SNR distribution obtained through the complete coil size range, specifically in the cortex, allows the acquisition of images with similar quality across a range of head dimensions, which is not possible with fixed-size coils due to the variable coil-to-head distance. The risks associated with mechanical pressure on the neonatal head are minimal and the head motion is restricted. The method could be used in coil designs for other age groups, body parts and subjects.