Active cancellation system of acoustic noise in MR imaging

Overview of Methods for Noise and Heat Reduction in MRI Gradient Coils

Magnetic resonance imaging (MRI) gradient coils produce acoustic noise due to coil conductor vibrations caused by large Lorentz forces. Accurate sound pressure levels and modeling of heating are essential for the assessment of gradient coil safety. This work reviews the state-of-the-art numerical methods used in accurate gradient coil modeling and prediction of sound pressure levels (SPLs) and temperature rise. We review several approaches proposed for noise level reduction of high-performance gradient coils, with a maximum noise reduction of 20 decibels (dB) demonstrated. An efficient gradient cooling technique is also presented.

Functional neuroimaging in hearing research and audiology

The various methods of medical imaging are essential for many diagnostic issues in clinical routine, e.g., for the diagnostics and localisation of tumorous diseases, or for the clarification of other lesions in the central nervous system. In addition to these classical roles both positron emission tomography (PET) and magnetic resonance imaging (MRI) allow for the investigation of functional processes in the human brain, when used in a specific way. The last 25 years have seen great progress, especially with respect to functional MRI, in terms of the available experimental paradigms as well as the data analysis strategies, so that a directed investigation of neurophysiological correlates of psychoacoustic performance is possible. This covers fundamental measures of sound perception like loudness and pitch, specific audiological symptoms like tinnitus, which often accompanies hearing disorders, but it also includes experiments on speech perception or on virtual acoustic environments. One important aspect common to many auditory neuroimaging studies is the central question at what stage in the human auditory pathway the sensory coding of the incoming sound is transformed into a universal and context-dependent perceptual representation, which is the basis for what we hear. This overview summarises findings from the literature as well as a few studies from our lab, to discuss the possibilities and the limits of the adoption of functional neuroimaging methods in audiology. Up to this stage, most auditory neuroimaging studies have investigated basic processes in normal hearing listeners. However, the hitherto existing results suggest that the methods of auditory functional neuroimaging - possibly complemented by electrophysiological methods like EEG and MEG - have a great potential to contribute to a deeper understanding of the processes and the impact of hearing disorders.

Convolutional auto-encoder for image denoising of ultra-low-dose CT

OBJECTIVES

The purpose of this study was to validate a patch-based image denoising method for ultra-low-dose CT images. Neural network with convolutional auto-encoder and pairs of standard-dose CT and ultra-low-dose CT image patches were used for image denoising. The performance of the proposed method was measured by using a chest phantom.

MATERIALS AND METHODS

Standard-dose and ultra-low-dose CT images of the chest phantom were acquired. The tube currents for standard-dose and ultra-low-dose CT were 300 and 10 mA, respectively. Ultra-low-dose CT images were denoised with our proposed method using neural network, large-scale nonlocal mean, and block-matching and 3D filtering. Five radiologists and three technologists assessed the denoised ultra-low-dose CT images visually and recorded their subjective impressions of streak artifacts, noise other than streak artifacts, visualization of pulmonary vessels, and overall image quality.

RESULTS

For the streak artifacts, noise other than streak artifacts, and visualization of pulmonary vessels, the results of our proposed method were statistically better than those of block-matching and 3D filtering (p-values < 0.05). On the other hand, the difference in the overall image quality between our proposed method and block-matching and 3D filtering was not statistically significant (p-value = 0.07272). The p-values obtained between our proposed method and large-scale nonlocal mean were all less than 0.05.

CONCLUSION

Neural network with convolutional auto-encoder could be trained using pairs of standard-dose and ultra-low-dose CT image patches. According to the visual assessment by radiologists and technologists, the performance of our proposed method was superior to that of large-scale nonlocal mean and block-matching and 3D filtering.

Comparison of image quality characteristics on Silent MR versus conventional MR imaging of brain lesions at 3 Tesla

OBJECTIVE:

To compare signal- and contrast-to-noise-ratio (SNR, CNR), conspicuity values and subjective image quality characteristics of Silent MRI and conventional MRI in brain disorders at 3 T.

METHODS:

26 patients were prospectively examined with a 3 T MRI. Silent Scan was added to standardized MR protocol. Silenz T₁ weighted (Tlw) and Silent T₂ weighted (T2w) sequences were compared to standard Tlw and T2w. Analysis was performed quantitatively (SNR, CNR, conspicuity values) and by visual assessment on a 4-point scale with regard to lesion visibility, lesion delineation, grey-white differentiation and diagnostic usefulness. Data were analyzed using Wilcoxon signed-rank and Sign test. p ≤ 0.05 was considered significant.

RESULTS:

Silenz Tlw vs Tlw provided decreased SNR, but increased CNR (SNRparenchyma, SNRlesion: p = 0.000, CNRlesion: p = 0.003). Silent T2w vs T2w showed better SNR and CNR values (SNR_parenchyma, p = 0.014; SNR_lesion, p = 0.005; CNR_lesion, p = 0.005). Conspicuity values were not significantly different on Silenz Tlw vs Tlw and Silent T2w vs T2w. The visual assessment revealed Silenz Tlw to be significantly superior to Tlw in terms of grey- white differentiation (p = 0.000), lesion visibility (p = 0.003) and overall diagnostic usefulness (p = 0.001). In terms of Silent T2w vs T2w, there was a significant difference in grey-white differentiation in favour of Silent T2w (p = 0.016).

CONCLUSION:

Silent Scan is suitable for 3 T with image quality characteristics comparable to conventional MRI.

ADVANCES IN KNOWLEDGE:

Silent Scan has a diagnostic value comparable to conventional MRI, with the advantage of a quiet MR exam improving patient MR experience.

Improving quality and intelligibility of speech using single microphone for the broadband fMRI noise at low SNR

Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the patient. In this paper, we propose a single microphone Speech Enhancement (SE) technique which is based on the supervised machine learning technique and a statistical model based SE technique. The proposed algorithm is robust and computationally efficient and has capability to run in real-time. Objective and Subjective evaluations show that the proposed SE method outperforms the existing state-of-the-art algorithms in terms of quality and intelligibility of the recovered speech at low Signal to Noise Ratios (SNRs).

Music-based magnetic resonance fingerprinting to improve patient comfort during MRI examinations

PURPOSE

Unpleasant acoustic noise is a drawback of almost every MRI scan. Instead of reducing acoustic noise to improve patient comfort, we propose a technique for mitigating the noise problem by producing musical sounds directly from the switching magnetic fields while simultaneously quantifying multiple important tissue properties.

THEORY AND METHODS

MP3 music files were converted to arbitrary encoding gradients, which were then used with varying flip angles and repetition times in a two- and three-dimensional magnetic resonance fingerprinting (MRF) examination. This new acquisition method, named MRF-Music, was used to quantify T1 , T2 , and proton density maps simultaneously while providing pleasing sounds to the patients.

RESULTS

MRF-Music scans improved patient comfort significantly during MRI examinations. The T1 and T2 values measured from phantom are in good agreement with those from the standard spin echo measurements. T1 and T2 values from the brain scan are also close to previously reported values.

CONCLUSIONS

MRF-Music sequence provides significant improvement in patient comfort compared with the MRF scan and other fast imaging techniques such as echo planar imaging and turbo spin echo scans. It is also a fast and accurate quantitative method that quantifies multiple relaxation parameters simultaneously. Magn Reson Med 75:2303-2314, 2016. © 2015 Wiley Periodicals, Inc.

FMRI scanner noise interaction with affective neural processes

The purpose of the present study was the investigation of interaction effects between functional MRI scanner noise and affective neural processes. Stimuli comprised of psychoacoustically balanced musical pieces, expressing three different emotions (fear, neutral, joy). Participants (N=34, 19 female) were split into two groups, one subjected to continuous scanning and another subjected to sparse temporal scanning that features decreased scanner noise. Tests for interaction effects between scanning group (sparse/quieter vs continuous/noisier) and emotion (fear, neutral, joy) were performed. Results revealed interactions between the affective expression of stimuli and scanning group localized in bilateral auditory cortex, insula and visual cortex (calcarine sulcus). Post-hoc comparisons revealed that during sparse scanning, but not during continuous scanning, BOLD signals were significantly stronger for joy than for fear, as well as stronger for fear than for neutral in bilateral auditory cortex. During continuous scanning, but not during sparse scanning, BOLD signals were significantly stronger for joy than for neutral in the left auditory cortex and for joy than for fear in the calcarine sulcus. To the authors' knowledge, this is the first study to show a statistical interaction effect between scanner noise and affective processes and extends evidence suggesting scanner noise to be an important factor in functional MRI research that can affect and distort affective brain processes.

A technique to reduce motion artifact for externally triggered cine-MRI(EC-MRI) based on detecting the onset of the articulated word with spectral analysis

One issue in externally triggered cine-magnetic resonance imaging (EC-MRI) for the dynamic observation of speech organs is motion artifact in the phase-encoding direction caused by unstable repetitions of speech during data acquisition. We propose a technique to reduce such artifact by rearranging the k-space data used to reconstruct MR images based on the analysis of recorded speech sounds. We recorded the subject's speech sounds during EC-MRI and used post hoc acoustical processing to reduce scanning noise and detect the onset of each utterance based on analysis of the recorded sounds. We selected each line of k-space from several data acquisition sessions and rearranged them to reconstruct a new series of dynamic MR images according to the analyzed time of utterance onset. Comparative evaluation showed significant reduction in motion artifact signal in the dynamic MR images reconstructed by the proposed method. The quality of the reconstructed images was sufficient to observe the dynamic aspects of speech production mechanisms.

Perspective of functional magnetic resonance imaging in middle ear research

Functional magnetic resonance imaging (MRI) studies have frequently been applied to study sensory system such as vision, language, and cognition, but have proceeded at a considerably slower speed in investigating middle ear and central auditory processing. This is due to several factors, including the intrinsic anatomy of the middle ear system and inherent acoustic noise during acquisition of MRI data. However, accumulating evidences have demonstrated that clarification of some fundamental neural underpinnings of audition associated with middle ear mechanics can be achieved using functional MRI methods. This mini review attempted to take a narrow snapshot of the currently available functional MRI procedures and gave examples of what may be learned about hearing from their application. It is hoped that with these technical advancements, many new high impact applications in audition would follow. In particular, because the fMRI can be used in humans and in animals, fMRI may represent a unique tool that should promote translational research by enabling parallel analyses of physiological and pathological processes in the human and animal auditory system. This article is part of a special issue entitled "MEMRO 2012".

In situ active control of noise in a 4 T MRI scanner

PURPOSE

To evaluate the effectiveness of the proposed active noise control (ANC) system for the reduction of the acoustic noise emission generated by a 4 T MRI scanner during operation and to assess the feasibility of developing an ANC device that can be deployed in situ.

MATERIALS AND METHODS

Three typical scanning sequences, EPI (echo planar imaging), GEMS (gradient echo multislice), and MDEFT (modified driven equilibrium Fourier transform), were used for evaluating the performance of the ANC system, which was composed of a magnetic compatible headset and a multiple reference feedforward filtered-x least mean square controller.

RESULTS

The greatest reduction, about 55 dB, was achieved at the harmonic at a frequency of 1.3 kHz in the GEMS case. Approximately 21 dB and 30 dBA overall reduction was achieved for GEMS noise across the entire audible frequency range. For the MDEFT sequence, the control system achieved 14 dB and 14 dBA overall reduction in the audible frequency range, while 13 dB and 14 dBA reduction was obtained for the EPI case.

CONCLUSION

The result is highly encouraging because it shows great potential for treating magnetic resonance imaging noise with an ANC application during real-time scanning.

An efficient feedback active noise control algorithm based on reduced-order linear predictive modeling of FMRI acoustic noise

Functional magnetic resonance imaging (fMRI) acoustic noise exhibits an almost periodic nature (quasi-periodicity) due to the repetitive nature of currents in the gradient coils. Small changes occur in the waveform in consecutive periods due to the background noise and slow drifts in the electroacoustic transfer functions that map the gradient coil waveforms to the measured acoustic waveforms. The period depends on the number of slices per second, when echo planar imaging (EPI) sequencing is used. Linear predictability of fMRI acoustic noise has a direct effect on the performance of active noise control (ANC) systems targeted to cancel the acoustic noise. It is shown that by incorporating some samples from the previous period, very high linear prediction accuracy can be reached with a very low order predictor. This has direct implications on feedback ANC systems since their performance is governed by the predictability of the acoustic noise to be cancelled. The low complexity linear prediction of fMRI acoustic noise developed in this paper is used to derive an effective and low-cost feedback ANC system.

Medical image analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging.

Simulation study on active noise control for a 4-T MRI scanner

The purpose of this work is to study computationally the possibility of the application of a hybrid active noise control technique for magnetic resonance imaging (MRI) acoustic noise reduction. A hybrid control system combined with both feedforward and feedback loops embedded is proposed for potential application on active MRI noise reduction. A set of computational simulation studies were performed. Sets of MRI acoustic noise emissions measured at the patient's left ear location were recorded and used in the simulation study. By comparing three different control systems, namely, the feedback, the feedforward and the hybrid control, our results revealed that the hybrid control system is the most effective. The hybrid control system achieved approximately a 20-dB reduction at the principal frequency component. We concluded that the proposed hybrid active control scheme could have a potential application for MRI scanner noise reduction.

Repeatability and variability of noise generated during MRI

Acoustic noise has always been associated with MRI and fMRI. During clinical use, the noise provides a source of irritation to both patients and operators. Within research imaging, the noise creates errors in fMRI, especially for fMRI involving auditory stimulus. Prior studies have attempted to reduce the noise received by subjects using active noise cancellation and statistical prediction algorithms to determine what antinoise to emit, resulting in sound pressure level (SPL) attenuation of 4 to 30 dB. This paper proposes that the noise generated during imaging does not vary on a session by session basis. This should allow a recording of the noise to be used in active noise cancellation instead of predictive algorithms.

Extraction of overt verbal response from the acoustic noise in a functional magnetic resonance imaging scan by use of segmented active noise cancellation

A method to extract the subject's overt verbal response from the obscuring acoustic noise in an fMRI scan is developed by applying active noise cancellation with a conventional MRI microphone. Since the EPI scanning and its accompanying acoustic noise in fMRI are repetitive, the acoustic noise in one time segment was used as a reference noise in suppressing the acoustic noise in subsequent segments. However, the acoustic noise from the scanner was affected by the subject's movements, so the reference noise was adaptively adjusted as the scanner's acoustic properties varied in time. This method was successfully applied to a cognitive fMRI experiment with overt verbal responses.

Automated post-hoc noise cancellation tool for audio recordings acquired in an MRI scanner

There are several types of experiment in which it is useful to have subjects speak overtly in a magnetic resonance imaging (MRI) scanner, including those studying the articulatory apparatus and the neural basis of speech production, and fMRI experiments in which speech is used as a response modality. Although it is relatively easy to record sound from the bore, it can be difficult to hear the speech over the very loud acoustic noise from the scanner. This is particularly a problem during echo-planar imaging, which is usually used for fMRI. We present a post-hoc sound cancellation algorithm, and describe a Windows-based tool that implements it. The tool is fast and operates with minimal user intervention. We evaluate cancellation performance in terms of the improvement in signal-to-noise ratio, and investigate the effect of the recording medium. A substantial improvement in audibility was obtained.

Analysis of the sound field in finite length infinite baffled cylindrical ducts with vibrating walls of finite impedance

This paper describes an analytical model of finite cylindrical ducts with infinite flanges. This model is used to investigate the sound radiation characteristics of the gradient coil system of a magnetic resonance imaging (MRI) scanner. The sound field in the duct satisfies both the boundary conditions at the wall and at the open ends. The vibrating cylindrical wall of the duct is assumed to be the only sound source. Different acoustic conditions for the wall (rigid and absorptive) are used in the simulations. The wave reflection phenomenon at the open ends of the finite duct is described by general radiation impedance. The analytical model is validated by the comparison with its counterpart in a commercial code based on the boundary element method (BEM). The analytical model shows significant advantages over the BEM model with better numerical efficiency and a direct relation between the design parameters and the sound field inside the duct.

Verbal communication in MR environments: effect of MR system acoustic noise on speech understanding

PURPOSE

To assess the masking effect of magnetic resonance (MR)-related acoustic noise and the effect of passive hearing protection on speech understanding.

MATERIALS AND METHODS

Acoustic recordings were made at 1.5 T at patient and operator (interventionalist in the MR suite) locations for relevant pulse sequences. In an audiologic laboratory, speech-to-noise ratios (STNRs) were determined, defined as the difference between the absolute sound pressure levels of MR noise and speech. The recorded noise of the MR sequences was played simultaneously with the recorded sentences at various intensities, and 15 healthy volunteers (seven women, eight men; median age, 27 years) repeated these sentences as accurately as possible. The STNR that corresponded with a 50% correct repetition was used as the measure for speech intelligibility. In addition, the effect of passive hearing protection on speech intelligibility was tested by using an earplug model.

RESULTS

Overall, speech understanding was reduced more at operator than at patient location. Most problematic were fast gradient-recalled-echo train and spiral k-space sequences. As the absolute sound pressure level of these sequences was approximately 100 dB at patient location, the vocal effort needed to attain 50% intelligibility was shouting (>77 dB). At operator location, less effort was required because of the lower sound pressure levels of the MR noise. Fast spoiled gradient-recalled-echo and echo-planar imaging sequences showed relatively favorable results with raised voice at operator location and loud speaking at patient location. The use of hearing protection slightly improved STNR.

CONCLUSION

At 1.5 T, the level of MR noise requires that large vocal effort is used, at the operator and especially at the patient location. Depending on the specific MR sequence used, loud speaking or shouting is needed to achieve adequate bidirectional communication with the patient. The wearing of earplugs improves speech intelligibility.

fMRI of the auditory system: understanding the neural basis of auditory gestalt

Functional magnetic resonance imaging (fMRI) has rapidly become the most widely used imaging method for studying brain functions in humans. This is a result of its extreme flexibility of use and of the astonishingly detailed spatial and temporal information it provides. Nevertheless, until very recently, the study of the auditory system has progressed at a considerably slower pace compared to other functional systems. Several factors have limited fMRI research in the auditory field, including some intrinsic features of auditory functional anatomy and some peculiar interactions between fMRI technique and audition. A well known difficulty arises from the high intensity acoustic noise produced by gradient switching in echo-planar imaging (EPI), as well as in other fMRI sequences more similar to conventional MR sequences. The acoustic noise interacts in an unpredictable way with the experimental stimuli both from a perceptual point of view and in the evoked hemodynamics. To overcome this problem, different approaches have been proposed recently that generally require careful tailoring of the experimental design and the fMRI methodology to the specific requirements posed by the auditory research. The novel methodological approaches can make the fMRI exploration of auditory processing much easier and more reliable, and thus may permit filling the gap with other fields of neuroscience research. As a result, some fundamental neural underpinnings of audition are being clarified, and the way sound stimuli are integrated in the auditory gestalt are beginning to be understood.

Acoustic noise concerns in functional magnetic resonance imaging

Magnetic resonance (MR) acoustic scanner noise may negatively affect the performance of functional magnetic resonance imaging (fMRI), a problem that worsens at the higher field strengths proposed to enhance fMRI. We present an overview of the current knowledge on the effects of confounding acoustic MR noise in fMRI experiments. The principles and effectiveness of various methods to reduce acoustic noise in fMRI are discussed, practical considerations are addressed and recommendations are made.

Interventional MR imaging at 1.5 T: quantification of sound exposure

Sound pressure levels (SPLs) during interventional magnetic resonance (MR) imaging may create an occupational hazard for the interventional radiologist (ie, the potential risk of hearing impairment). Therefore, A-weighted and linear continuous-equivalent SPLs were measured at the entrance of a 1.5-T MR imager during cardiovascular and real-time pulse sequences. The SPLs ranged from 81.5 to 99.3 dB (A-weighted scale), and frequencies were from 1 to 3 kHz. SPLs for the interventional radiologist exceeded a safe SPL of 80 dB (A-weighted scale) for all sequences; therefore, hearing protection is recommended.

Active control of the volume acquisition noise in functional magnetic resonance imaging: method and psychoacoustical evaluation

Functional magnetic resonance imaging (fMRI) provides a noninvasive tool for observing correlates of neural activity in the brain while a subject listens to sound. However, intense acoustic noise is generated in the process of capturing MR images. This noise stimulates the auditory nervous system, limiting the dynamic range available for displaying stimulus-driven activity. The noise is potentially damaging to hearing and is distracting for the subject. In an active noise control (ANC) system, a reference sample of a noise is processed to form a sound which adds destructively with the noise at the listener's ear. We describe an implementation of ANC in the electromagnetically hostile and physically compact MRI scanning environment. First, a prototype system was evaluated psychoacoustically in the laboratory, using the electrical drive to a noise-generating loudspeaker as the reference. This system produced 10-20 dB of subjective noise-reduction between 250 Hz and 1 kHz, and smaller amounts at higher frequencies. The system was modified to operate in a real MR scanner where the reference was obtained by recording the acoustic scanner noise. Objective reduction by 30-40 dB of the most intense component in scanner noises was realized between 500 Hz and 3500 Hz, and subjective reduction of 12 dB and 5 dB in tests at frequencies of 600 Hz and at 1.9 kHz, respectively. Although the benefit of ANC is limited by transmission paths to the cochlea other than air-conduction routes from the auditory meatus, ANC achieves worthwhile attenuation even in the frequency range of maximum bone conduction (1.5-2 kHz). ANC should, therefore, be generally useful during auditory fMRI.

Auditory noise associated with MR procedures: a review

This review article discusses the various types of acoustic noise produced during the operation of MR systems, describes the characteristics of the acoustic noise, and presents information regarding noise control techniques. In addition, the problems related to acoustic noise for patients and healthcare workers are discussed.