Shaping and timing gradient pulses to reduce MRI acoustic noise

Improving Patient Comfort in MRI with Predictive Acoustic Noise Cancelling

With sound pressure levels reaching up to 130 dB, acoustic noise in Magnetic Resonance Imaging (MRI) is one of the main sources of patient discomfort in otherwise one of the safest medical imaging modalities. In this work, a noise prediction-based approach, termed predictive noise cancelling (PNC), is applied, for the first time, to suppress noise in MRI. In PN C the noise from the scanner gradient coils is predicted based on linear time-invariant models, which relate the individual gradient coil (X, Y and Z) input to the acoustic noise output. A model setup was constructed of a custom speaker box and MRI -compatible microphone to demonstrate live noise reduction. Additional tuning steps, including output channel equalization and clock mismatch correction, were performed to maximize noise reduction. A calibration sequence was designed to determine the model and tuning parameters. Analysis of actual scanner noise shows an upper limit of 21 dB noise reduction with the proposed linear model. For the components of a clinical example sequence, the setup demonstrated in-bore live noise reduction of up to 10 dB (7.01 ± 0.31 dB, 6.42 ± 2.04 dB and 9.28 ± 0.26 dB for X, Y and Z gradient coils respectively) in the presence of system imperfections. Clinical relevance - The results indicate promising noise attenuation without the need to modify scanner hardware or compromises in acquisition speed or quality. This has potential to substantially and cost effectively improve patient comfort in clinical MRI.

Direct comparison of gradient Fidelity and acoustic noise of the same MRI system at 3 T and 0.75 T

PURPOSE

To analyze the difference between gradient fidelity and acoustic noise of the same MRI scanner operated at product field strength (3 T) and lower field strength (0.75 T).

METHODS

Gradient modulation transfer functions (GMTFs) were measured using a four-slice 2D phase-encoded chirp-based sequence on the same scanner operated at 3 T and, following ramp-down, at 0.75 T with identical gradient specifications (40 mT/m, 200 T/m/s). Calibrated audio measurements were performed at both field strengths to correlate audio spectra with GMTFs.

RESULTS

While eddy currents were independent of field strength, mechanical resonances were substantially decreased at lower field, resulting in a reduction of GMTF distortions by up to 95% (88% on average) at the mechanical resonances of the gradient system. Audio spectra amplitudes were reduced by up to 87% when comparing 0.75 T versus 3 T.

CONCLUSION

Lower static fields lead to reduced Lorentz forces on the gradient coil and, in turn, to reduced mechanical resonances, thereby improving gradient fidelity. Simultaneously, the reduction of acoustic noise may help to improve patient comfort.

Magnetic resonance imaging with gradient sound respiration guide

Respiratory motion management is crucial for high-resolution MRI of the heart, lung, liver and kidney. In this article, respiration guide using acoustic sound generated by pulsed gradient waveforms was introduced in the pulmonary ultrashort echo time (UTE) sequence and validated by comparing with retrospective respiratory gating techniques. The validated sound-guided respiration was implemented in non-contrast enhanced renal angiography. In the sound-guided respiration, breathe−in and–out instruction sounds were generated with sinusoidal gradient waveforms with two different frequencies (602 and 321 Hz). Performance of the sound-guided respiration was evaluated by measuring sharpness of the lung-liver interface with a 10–90% rise distance, w_10-90, and compared with three respiratory motion managements in a free-breathing UTE scan: without respiratory gating (w/o gating), 0-dimensional k-space navigator (k-point navigator), and image-based self-gating (Img-SG). The sound-guided respiration was implemented in stack-of-stars balanced steady-state free precession with inversion recovery preparation for renal angiography. No subjects reported any discomfort or inconvenience with the sound-guided respiration in pulmonary or renal MRI scans. The lung-liver interface of the UTE images for sound-guided respiration (w_10-90 = 6.99 ± 2.90 mm), k-point navigator (8.51 ± 2.71 mm), and Img-SG (7.01 ± 2.06 mm) was significantly sharper than that for w/o gating (17.13 ± 2.91 mm; p < 0.0001 for all of sound-guided respiration, k-point navigator and Img-SG). Sharpness of the lung-liver interface was comparable between sound-guided respiration and Img-SG (p = 0.99), but sound-guided respiration achieved better visualization of pulmonary vasculature. Renal angiography with the sound-guided respiration clearly delineated renal, segmental and interlobar arteries. In conclusion, the gradient sound guided respiration can facilitate a consistent diaphragm position in every breath and achieve performance of respiratory motion management comparable to image-based self-gating.

Acoustic Noise and Magnetic Resonance Imaging: A Narrative/Descriptive Review

Magnetic resonance imaging generates unwanted acoustic noise. This review describes the work characterizing the acoustic noise, and the various solutions to control and attenuate the acoustic noise. There are also discussions about the permissible limits, and guidance regarding acoustic noise exposure for staff, patients, and volunteers. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging

An artificial neural network with multiple hidden layers (known as a deep neural network, or DNN) was employed as a predictive model (DNN_p) for the first time to predict emotional responses using whole-brain functional magnetic resonance imaging (fMRI) data from individual subjects. During fMRI data acquisition, 10 healthy participants listened to 80 International Affective Digital Sound stimuli and rated their own emotions generated by each sound stimulus in terms of the arousal, dominance, and valence dimensions. The whole-brain spatial patterns from a general linear model (i.e., beta-valued maps) for each sound stimulus and the emotional response ratings were used as the input and output for the DNN_P, respectively. Based on a nested five-fold cross-validation scheme, the paired input and output data were divided into training (three-fold), validation (one-fold), and test (one-fold) data. The DNN_P was trained and optimized using the training and validation data and was tested using the test data. The Pearson's correlation coefficients between the rated and predicted emotional responses from our DNN_P model with weight sparsity optimization (mean ± standard error 0.52 ± 0.02 for arousal, 0.51 ± 0.03 for dominance, and 0.51 ± 0.03 for valence, with an input denoising level of 0.3 and a mini-batch size of 1) were significantly greater than those of DNN models with conventional regularization schemes including elastic net regularization (0.15 ± 0.05, 0.15 ± 0.06, and 0.21 ± 0.04 for arousal, dominance, and valence, respectively), those of shallow models including logistic regression (0.11 ± 0.04, 0.10 ± 0.05, and 0.17 ± 0.04 for arousal, dominance, and valence, respectively; average of logistic regression and sparse logistic regression), and those of support vector machine-based predictive models (SVM_ps; 0.12 ± 0.06, 0.06 ± 0.06, and 0.10 ± 0.06 for arousal, dominance, and valence, respectively; average of linear and non-linear SVM_ps). This difference was confirmed to be significant with a Bonferroni-corrected p-value of less than 0.001 from a one-way analysis of variance (ANOVA) and subsequent paired t-test. The weights of the trained DNN_Ps were interpreted and input patterns that maximized or minimized the output of the DNN_Ps (i.e., the emotional responses) were estimated. Based on a binary classification of each emotion category (e.g., high arousal vs. low arousal), the error rates for the DNN_P (31.2% ± 1.3% for arousal, 29.0% ± 1.7% for dominance, and 28.6% ± 3.0% for valence) were significantly lower than those for the linear SVM_P (44.7% ± 2.0%, 50.7% ± 1.7%, and 47.4% ± 1.9% for arousal, dominance, and valence, respectively) and the non-linear SVM_P (48.8% ± 2.3%, 52.2% ± 1.9%, and 46.4% ± 1.3% for arousal, dominance, and valence, respectively), as confirmed by the Bonferroni-corrected p < 0.001 from the one-way ANOVA. Our study demonstrates that the DNN_p model is able to reveal neuronal circuitry associated with human emotional processing - including structures in the limbic and paralimbic areas, which include the amygdala, prefrontal areas, anterior cingulate cortex, insula, and caudate. Our DNN_p model was also able to use activation patterns in these structures to predict and classify emotional responses to stimuli.

Quiet echo planar imaging for functional and diffusion MRI

PURPOSE

To develop a purpose-built quiet echo planar imaging capability for fetal functional and diffusion scans, for which acoustic considerations often compromise efficiency and resolution as well as angular/temporal coverage.

METHODS

The gradient waveforms in multiband-accelerated single-shot echo planar imaging sequences have been redesigned to minimize spectral content. This includes a sinusoidal read-out with a single fundamental frequency, a constant phase encoding gradient, overlapping smoothed CAIPIRINHA blips, and a novel strategy to merge the crushers in diffusion MRI. These changes are then tuned in conjunction with the gradient system frequency response function.

RESULTS

Maintained image quality, SNR, and quantitative diffusion values while reducing acoustic noise up to 12 dB (A) is illustrated in two adult experiments. Fetal experiments in 10 subjects covering a range of parameters depict the adaptability and increased efficiency of quiet echo planar imaging.

CONCLUSION

Purpose-built for highly efficient multiband fetal echo planar imaging studies, the presented framework reduces acoustic noise for all echo planar imaging-based sequences. Full optimization by tuning to the gradient frequency response functions allows for a maximally time-efficient scan within safe limits. This allows ambitious in-utero studies such as functional brain imaging with high spatial/temporal resolution and diffusion scans with high angular/spatial resolution to be run in a highly efficient manner at acceptable sound levels. Magn Reson Med 79:1447-1459, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Image quality assessment of silent T2 PROPELLER sequence for brain imaging in infants

OBJECTIVE

Infants are vulnerable to high acoustic noise. Acoustic noise generated by MR scanning can be reduced by a silent sequence. The purpose of this study is to compare the image quality of the conventional and silent T2 PROPELLER sequences for brain imaging in infants.

METHODS

A total of 36 scans were acquired from 24 infants using a 3 T MR scanner. Each patient underwent both conventional and silent T2 PROPELLER sequences. Acoustic noise level was measured. Quantitative and qualitative assessments were performed with the images taken with each sequence.

RESULTS

The sound pressure level of the conventional T2 PROPELLER imaging sequence was 92.1 dB and that of the silent T2 PROPELLER imaging sequence was 73.3 dB (reduction of 20%). On quantitative assessment, the two sequences (conventional vs silent T2 PROPELLER) did not show significant difference in relative contrast (0.069 vs 0.068, p value = 0.536) and signal-to-noise ratio (75.4 vs 114.8, p value = 0.098). Qualitative assessment of overall image quality (p value = 0.572), grey-white differentiation (p value = 0.986), shunt-related artefact (p value > 0.999), motion artefact (p value = 0.801) and myelination degree in different brain regions (p values ≥ 0.092) did not show significant difference between the two sequences.

CONCLUSION

The silent T2 PROPELLER sequence reduces acoustic noise and generated comparable image quality to that of the conventional sequence. Advances in knowledge: This is the first report to compare silent T2 PROPELLER images with that of conventional T2 PROPELLER images in children.

A Structure Design Method for Reduction of MRI Acoustic Noise

The acoustic problem of the split gradient coil is one challenge in a Magnetic Resonance Imaging and Linear Accelerator (MRI-LINAC) system. In this paper, we aimed to develop a scheme to reduce the acoustic noise of the split gradient coil. First, a split gradient assembly with an asymmetric configuration was designed to avoid vibration in same resonant modes for the two assembly cylinders. Next, the outer ends of the split main magnet were constructed using horn structures, which can distribute the acoustic field away from patient region. Finally, a finite element method (FEM) was used to quantitatively evaluate the effectiveness of the above acoustic noise reduction scheme. Simulation results found that the noise could be maximally reduced by 6.9 dB and 5.6 dB inside and outside the central gap of the split MRI system, respectively, by increasing the length of one gradient assembly cylinder by 20 cm. The optimized horn length was observed to be 55 cm, which could reduce noise by up to 7.4 dB and 5.4 dB inside and outside the central gap, respectively. The proposed design could effectively reduce the acoustic noise without any influence on the application of other noise reduction methods.

Reduced acoustic noise in diffusion tensor imaging on a compact MRI system

PURPOSE

To investigate the feasibility of substantially reducing acoustic noise while performing diffusion tensor imaging (DTI) on a compact 3T (C3T) MRI scanner equipped with a 42-cm inner-diameter asymmetric gradient.

METHODS

A-weighted acoustic measurements were made using 10 mT/m-amplitude sinusoidal waveforms, corresponding to echo-planar imaging (EPI) echo spacing of 0.25 to 5.0 ms, on a conventional, whole-body 3T MRI and on the C3T. Acoustic measurements of DTI with trapezoidal EPI waveforms were then made at peak gradient performance on the C3T (80 mT/m amplitude, 700 T/m/s slew rate) and at derated performance (33 mT/m, 10 to 50 T/m/s) for acoustic noise reduction. DTI was acquired in two different phantoms and in seven human subjects, with and without gradient-derating corresponding to multi- and single-shot acquisitions, respectively.

RESULTS

Sinusoidal waveforms on the C3T were quieter by 8.5 to 15.6 A-weighted decibels (dBA) on average as compared to the whole-body MRI. The derated multishot DTI acquisition noise level was only 8.7 dBA (at 13 T/m/s slew rate) above ambient, and was quieter than non-derated, single-shot DTI by 22.3 dBA; however, the scan time was almost quadrupled. Although derating resulted in negligible diffusivity differences in the phantoms, small biases in diffusivity measurements were observed in human subjects (apparent diffusion coefficient = +9.3 ± 8.8%, fractional anisotropy = +3.2 ± 11.2%, radial diffusivity = +9.4 ± 16.8%, parallel diffusivity = +10.3 ± 8.4%).

CONCLUSION

The feasibility of achieving reduced acoustic noise levels with whole-brain DTI on the C3T MRI was demonstrated. Magn Reson Med 79:2902-2911, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Quiet T1-Weighted Pointwise Encoding Time Reduction with Radial Acquisition for Assessing Myelination in the Pediatric Brain

BACKGROUND AND PURPOSE

T1-weighted pointwise encoding time reduction with radial acquisition (PETRA) sequences require limited gradient activity and allow quiet scanning. We aimed to assess the usefulness of PETRA in pediatric brain imaging.

MATERIALS AND METHODS

We included consecutive pediatric patients who underwent both MPRAGE and PETRA. The contrast-to-noise and contrast ratios between WM and GM were compared in the cerebellar WM, internal capsule, and corpus callosum. The degree of myelination was rated by using 4-point scales at each of these locations plus the subcortical WM in the anterior frontal, anterior temporal, and posterior occipital lobes. Two radiologists made all assessments, and the intra- and interrater agreement was calculated by using intraclass correlation coefficients. Acoustic noise on MPRAGE and PETRA was measured.

RESULTS

We included 56 patients 5 days to 14 years of age (mean age, 36.6 months) who underwent both MPRAGE and PETRA. The contrast-to-noise and contrast ratios for PETRA were significantly higher than those for MPRAGE (P < .05), excluding the signal ratio for cerebellar WM. Excellent intra- and interrater agreement were obtained for myelination at all locations except the cerebellar WM. The acoustic noise on PETRA (58.2 dB[A]) was much lower than that on MPRAGE (87.4 dB[A]).

CONCLUSIONS

PETRA generally showed better objective imaging quality without a difference in subjective image-quality evaluation and produced much less acoustic noise compared with MPRAGE. We conclude that PETRA can substitute for MPRAGE in pediatric brain imaging.

Adaptive speech enhancement using directional microphone in a 4-T MRI scanner

OBJECTIVE

To evaluate the effectiveness of the proposed adaptive speech enhancement (ASE) system for the magnetic resonance imaging (MRI) environment to reduce the loud scanning noise without disrupting the communication between patients and MRI operators.

MATERIALS AND METHODS

The developed system employed the idea of differential directional microphones for measuring and distinguishing the speech signals and MRI acoustic noises simultaneously. Two-stage adaptive filters with normalized least mean square algorithms were adopted. Two common MRI scanning sequences, echo planar imaging (EPI) and gradient echo multi-slice (GEMS), were tested using a 4T MRI scanner.

RESULTS

A total of 1.4 and 3.3 dB speech enhancements quantified by the cepstral distance assessment were achieved for the speech signal contaminated with the EPI and GEMS noises, respectively. The speech signal was noticeably recovered, and a clear speech waveform was observed after treated with the ASE system. Furthermore, a non-adaptive post-processing approach [i.e. simply using spectral subtraction (SS) technique] was also adopted to process the abovementioned results. Additional reductions were achieved for the non-coherent MRI acoustic noises.

CONCLUSION

The results showed that combining the proposed ASE system along with the SS approach has a great potential for treating MRI acoustic noise to guarantee an effective communication from patient to MRI operators.

Quiet PROPELLER MRI techniques match the quality of conventional PROPELLER brain imaging techniques

BACKGROUND AND PURPOSE

Switching of magnetic field gradients is the primary source of acoustic noise in MR imaging. Sound pressure levels can run as high as 120 dB, capable of producing physical discomfort and at least temporary hearing loss, mandating hearing protection. New technology has made quieter techniques feasible, which range from as low as 80 dB to nearly silent. The purpose of this study was to evaluate the image quality of new commercially available quiet T2 and quiet FLAIR fast spin-echo PROPELLER acquisitions in comparison with equivalent conventional PROPELLER techniques in current day-to-day practice in imaging of the brain.

MATERIALS AND METHODS

Thirty-four consecutive patients were prospectively scanned with quiet T2 and quiet T2 FLAIR PROPELLER, in addition to spatial resolution-matched conventional T2 and T2 FLAIR PROPELLER imaging sequences on a clinical 1.5T MR imaging scanner. Measurement of sound pressure levels and qualitative evaluation of relative image quality was performed.

RESULTS

Quiet T2 and quiet T2 FLAIR were comparable in image quality with conventional acquisitions, with sound levels of approximately 75 dB, a reduction in average sound pressure levels of up to 28.5 dB, with no significant trade-offs aside from longer scan times.

CONCLUSIONS

Quiet FSE provides equivalent image quality at comfortable sound pressure levels at the cost of slightly longer scan times. The significant reduction in potentially injurious noise is particularly important in vulnerable populations such as children, the elderly, and the debilitated. Quiet techniques should be considered in these special situations for routine use in clinical practice.

Neuroimaging paradigms for tonotopic mapping (II): the influence of acquisition protocol

Numerous studies on the tonotopic organisation of auditory cortex in humans have employed a wide range of neuroimaging protocols to assess cortical frequency tuning. In the present functional magnetic resonance imaging (fMRI) study, we made a systematic comparison between acquisition protocols with variable levels of interference from acoustic scanner noise. Using sweep stimuli to evoke travelling waves of activation, we measured sound-evoked response signals using sparse, clustered, and continuous imaging protocols that were characterised by inter-scan intervals of 8.8, 2.2, or 0.0 s, respectively. With regard to sensitivity to sound-evoked activation, the sparse and clustered protocols performed similarly, and both detected more activation than the continuous method. Qualitatively, tonotopic maps in activated areas proved highly similar, in the sense that the overall pattern of tonotopic gradients was reproducible across all three protocols. However, quantitatively, we observed substantial reductions in response amplitudes to moderately low stimulus frequencies that coincided with regions of strong energy in the scanner noise spectrum for the clustered and continuous protocols compared to the sparse protocol. At the same time, extreme frequencies became over-represented for these two protocols, and high best frequencies became relatively more abundant. Our results indicate that although all three scanning protocols are suitable to determine the layout of tonotopic fields, an exact quantitative assessment of the representation of various sound frequencies is substantially confounded by the presence of scanner noise. In addition, we noticed anomalous signal dynamics in response to our travelling wave paradigm that suggest that the assessment of frequency-dependent tuning is non-trivially influenced by time-dependent (hemo)dynamics when using sweep stimuli.

Quiet T1-weighted imaging using PETRA: initial clinical evaluation in intracranial tumor patients

PURPOSE

To compare the lesion contrast and signal to noise ratio (SNR) obtained with T1-weighted pointwise encoding time reduction with radial acquisition (PETRA) to those of Magnetization-Prepared RApid Gradient-Echo (MPRAGE) for contrast-enhanced imaging of primary and metastatic intracranial tumors, and to investigate whether PETRA is able to reduce acoustic noise for improved patient comfort.

MATERIALS AND METHODS

Fifteen patients with intracranial tumors underwent 3 Tesla MRI including inversion-prepared PETRA and MPRAGE. The two sequences had comparable scan times, spatial resolution and spatial coverage. "Tumor conspicuity" was rated qualitatively by two radiologists, while enhancing lesion-to-white matter contrast to noise ratio (CNR) and white-matter SNR were analyzed quantitatively using paired t-tests. The acoustic noise generated by each sequence was measured.

RESULTS

Qualitative rating of "tumor conspicuity" by two radiologists resulted in nearly identical average scores for the two sequences. Quantitative analyses revealed that (i) there was no significant difference between the mean CNR values of the two sequences (P = 0.57), (ii) the mean SNR of PETRA was significantly higher than that of MPRAGE (P < 0.01), and (iii) the mean sound level of PETRA was significantly lower than that of MPRAGE (P < 0.01).

CONCLUSION

Inversion-prepared PETRA was found to be viable as a quiet alternative to MPRAGE for contrast-enhanced T1-weighted studies of intracranial tumors.

Evaluation of an independent linear model for acoustic noise on a conventional MRI scanner and implications for acoustic noise reduction

PURPOSE

To evaluate an independent linear model for gradient acoustic noise on a conventional MRI scanner, and to explore implications for acoustic noise reduction in routine imaging.

METHODS

Acoustic noise generated from each physical gradient axis was modeled as the prescribed gradient waveform passed through a linear time-invariant system. Homogeneity and superposition properties were experimentally determined. We also developed a new method to correct relative time shifts between the measured impulse responses for different physical gradient axes. Model accuracy was determined by comparing predicted and measured sound using normalized energy difference. Transfer functions were also measured in subjects with different body habitus and at multiple microphone locations.

RESULTS

Both superposition and homogeneity held for each physical gradient axis with errors less than 3%. When all gradients were on simultaneous sound prediction, error was reduced from 32% to 4% after time-shift correction. Transfer functions also showed high sensitivity to body habitus and microphone location.

CONCLUSION

The independent linear model predicts MRI acoustic noise with less than 4% error. Acoustic transfer functions are highly sensitive to body habitus and position within the bore, making it challenging to produce a general approach to acoustic noise reduction based on avoiding system resonance peaks.