168th Meeting | Acoustics.org

4pBA3 – Focusing Sound to Disrupt Microorganisms

Timothy A Bigelow – bigelow@iastate.edu
Iowa State University
2113 Coover Hall
Ames, IA 50014

Popular version of paper 4pBA3
Presented Thursday afternoon, October 30, 2014
168th ASA Meeting, Indianapolis

During the civil war, the risk of lethal infection drove surgeons to perform multiple amputations on wounded soldiers. The loss of life from the infection outweighed the loss of the limb. In modern medicine, the occurrence of amputations is much less due to the development of sterile surgical techniques, but a type of “amputation” is still the only treatment option for many patients battling infection.

In modern medicine, numerous implants have been developed to treat many different ailments ranging from basic hernia, to pacemakers, to neuronal implants to control seizures. These implants play a vital role in the restoration of function or quality of life for these patients. However, if an infection grows on the implant despite sterile surgical techniques, then the only treatment option is to remove and replace the infected implant with a new device. The bacteria responsible for the infection protect themselves by forming a biofilm on the surface of the implant. Bacteria in the biofilm are protected from antibiotics and the administration of antibiotics can even cause the formation of antibiotic resistant strains. Recently, however, we have shown that focused ultrasound can precisely target and destroy these biofilms (Figure 1). Therefore, in the future, we hope to develop a noninvasive therapy to treat infections on medical implants based on ultrasound.

bigelow disrupting biofilms - high-intensity focused ultrasound

Fig 1: The surface of graphite plates after growing Pseudomonas aeruginosa biofilms and exposing to high-intensity focused ultrasound. Green shows live cells while red shows dead cells. In the absence of treatment, a live biofilm is clearly visible. The ultrasound exposures resulted in almost complete biofilm destruction with few if any live cells remaining.

There are two primary types of therapy that can be performed with ultrasound. The first uses the energy in the sound to heat the tissue. The second uses the sound to excite microscopic bubbles in the tissue resulting in a mechanical change to the tissue structure. Our technology is based on the generation and subsequent excitation of the microscopic bubbles. The high-intensity of the sound causes the bubbles to violently collapse shredding cells adjacent to the bubbles. In addition to treating biofilm infections, we have also shown that the excitation of these microscopic bubbles can lyse microalgae for the release of lipids. These lipids can then be utilized in the formation of biofuels. The use of focused ultrasound was shown to be more energy efficient than other comparable methods of lysing the microalgae.

1pAA1 – Audible Simulation in the Canadian Parliament

The impact of auralization on design decisions for the House of Commons

Ronald Eligator – religator@ad-ny.com
Acoustic Distinctions, Inc.
145 Huguenot Street
New Rochelle, NY 10801

Popular version of paper 1pAA1
Presented Monday morning, October 27, 2014
168th ASA Meeting, Indianapolis

If the MP’s speeches don’t put you to sleep, at least you should be able to understand what they are saying.

Using state-of-the-art audible simulations, a design team of acousticians, architects and sound system designers is working to ensure that speech within the House of Commons chamber of the Parliament of Canada now in design will be intelligible in either French or English.

The new chamber for the House of Commons is being built in a glass-topped atrium in the courtyard of the West Block building on Parliament Hill in Ottawa. The chamber will be the temporary home of the House of Commons, while their traditional location in the Center Block building is being renovated and restored.

The skylit atrium in the West Block will be about six times the volume of the existing room, resulting in significant challenges for ensuring speech will be intelligibility.

Figure 1 - House_of_Commons Canadian Parliament

Figure 1: Existing Chamber of the House of Commons, Parliament of Canada

The existing House chamber is 21 meters (70 feet) long, 16 meters (53 feet) wide, and has seats for the current 308 Members of Parliament (to increase to 338 in 2015) and 580 people in the upper gallery that runs around the second level of the room. Most surfaces are wood, although the floor is carpeted, and there is an adjustable curtain at the rear of the MP seating area on both sides of the room. The ceiling is a painted stretched linen canvas over the ceiling 14.7 meters (48.5 feet) above the commons floor, resulting in a room volume of approximately 5000 cubic meters.

The new House chamber is being infilled into an existing courtyard that is 44 meters (145 feet) long, 39 meters (129 feet) wide, and 18 meters (59 feet) high. The meeting space itself will retain the same basic footprint as the existing room, including the upper gallery seating, but will be open to the sound reflective glass roof and stone and glass side walls of the courtyard. In the absence of any acoustic treatments, the high level of reverberant sound would make it very difficult to understand speech in the room.

RCOP / FGM ARCHITECTS

Figure 2: Early Design Rendering of Chamber in West Block

In order to help the Public Works and Government Services Canada (PWGSC) and the House of Commons understand the acoustic differences between the existing house chamber and the one under design, and to assure them that excellent speech intelligibility will be achieved in the new chamber, Acoustic Distinctions, the New York-based acoustic consultant, created a computer model of both the new and existing house chambers, and performed acoustic tests in the existing chamber. AD also made comparisons of the two room using sophisticated data analysis and tables of data an produced graphs maps of speech intelligibility in each space.

An early design iteration, for example, included significant areas of sound absorptive materials at the sides of the ceiling areas, as well as sound absorptive materials integrated into the branches of the tree-like structure which supports the roof:

ACOUSTIC DISTINCTIONS

Figure 3: Computer Model of Room Finishes

The dark areas of the image show the location of sound absorptive materials, including triangularly-shaped wedges integrated into the structure which supports the roof.

Using a standardized measure of intelligibility, AD estimated a speech quality of 65% using the Speech Transmission Index (STI), a standardized measure of speech intelligibility, where a minimum of 75% was needed to ensure excellent intelligibility.

The computer analysis done by Acoustic Distinctions also produced colorful images relating to the degree of speech intelligibility that was to be expected:

Figure 4: Speech Transmission Index, single person speaking, no reinforcement (Talker at lower left; Listener at lower right) Dark blue to black color indicates fair to good intelligibility

Figure 5 - E_07_SOUND_SYSTEM_ON_40_STI_Noise

Figure 5: Speech Transmission Index, single person speaking, with sound reinforcement (Talker at upper left; Listener at lower right) Bright pink to red color indicates excellent intelligibility

Not surprisingly, communicating this to the design team and House of Commons in a way that provided a high level of confidence in the results was required. We again used audible simulations to demonstrate the results:

Audio file 3: Speech with Sound System, reduced absorption. STI 0.82

The rendering below shows the space configuration associated with the latest results:

ARCOP / FGM ARCHITECTS

Figure 6 - House of Commons Glass Dome rendering

Figure 6: Rendering, House of Commons, West Block, Parliament Hill Proposed Design Configuration, showing sound absorptive panels integrated into laylight and structure supporting roof

Evaluating kidney stone size in children using the posterior acoustic shadow

Franklin C. Lee¹ – franklee@uw.edu
Jonathan D. Harper¹ – jdharper@uw.edu
Thomas S. Lendvay^1,2 – Thomas.lendvay@seattlechildrens.org
Ziyue Liu³ – ziliu@iupui.edu
Barbrina Dunmire⁴ – mrbean@uw.edu
Manjiri Dighe⁵ – dighe@uw.edu
Michael Bailey⁴ – bailey@apl.washington.edu
Mathew D. Sorensen^1,6 – mathews@uw.edu

University of Washington
¹ Department of Urology, Box 356510
⁵ Department of Radiology, Box 357115
1959 NE Pacific St, Seattle, WA 98195

² Seattle Children’s Hospital
Urology, Developmental Pediatrics
4800 Sand Point WA NE, Seattle, WA 98105

³ Indiana University
Department of Biostatistics
410 W. Tenth St, Suite 3000, Indianapolis, IN 46202

⁴ University of Washington
Applied Physics Lab – Center for Industrial and Medical Ultrasound2
1013 NE 40th St, Seattle, WA 98105

⁶ Department of Veteran Affairs Medical Center
Division of Urology
1660 South Columbian Way, Seattle, WA 98108

Stone disease in the children is becoming more commonplace. Over the past 25 years the incidence has increased approximately 6-10% annually and is now 50 per 100,000 adolescents¹. The diagnosis of kidney stones in children, as in adults, relies primarily on diagnostic imaging. In adults, the most common imaging study performed in the United States for the initial diagnosis of kidney stones is a computed tomography (CT) scan, due to its superior sensitivity and specificity. This is not preferred for children as CT utilizes ionizing radiation and children have an increased sensitivity to radiation effects. In addition, stone formers often have recurrent stone episodes over their lifetime, which is especially relevant to younger stone formers. The repeated exposures of a CT scan could lead to an increased risks of secondary cancers². As a result, ultrasound is often performed in children instead because there is no radiation associated with its use¹. Ultrasound, however, is less sensitive and specific compared with CT, and is known to overestimate kidney stone size^3-5, which is one of the primary determinants of how stones are managed.

We have identified a new technique to improve the accuracy of US stone sizing. Traditionally, a kidney stone will show up as a bright, or hyperechoic, object on US, and radiologists measure the longest linear dimension of the bright area to represent the stone size. We believe that the dark, or hypoechoic, acoustic shadow that appears behind a kidney stone provides additional information for predicting stone size. The resolution of the stone is affected by the distortion of the waves traveling through the intervening tissues; the resolution of the shadow is only affected by the local stone obstruction.

We screened 660 stone diagnoses over an 11 year period (2004 – 2014) at Seattle Children’s Hospital, a tertiary care referral center serving the greater Pacific Northwest. Over the study period, there were 37 patients presenting with an initial diagnosis of a kidney stone, and who had both a US and CT within three months of each other. Two reviewers retrospectively measured both the stone size and the shadow width from the ultrasound image. We compared the results to the stone size measured from the CT scan. A total of 48 stones were included in the study with an average size based on CT imaging of 7.85 mm. The shadow width was present in 88% of the cases, and, on average, was more accurate than measuring the stone itself. Measuring the stone width on ultrasound tended to overestimate the size of the stone by 1.2 ± 2.5 mm (reviewer 1) and 2.0 ± 1.7 mm (reviewer 2), while measuring the shadow width on ultrasound underestimated the size of the stone by -0.6 ± 2.5 mm (reviewer 1) and overestimated the stone size by 0.3 ± 1.2 mm (reviewer 2). In both cases, the shadow was a better predictor of stone size and, for reviewer 2, there was less variability in the data. Stone sizes based on CT are typically considered within 1 mm, with low variability.

Our technique is simple and can be easily adopted by pediatricians, radiologists, and urologists. It improves the accuracy of US and gives physicians more confidence that the reported size is more representative of the true stone size, without having to expose children to the radiation of a CT scan. This also allows the physician to make more accurate decisions about when to perform a surgery for a large stone or continue to observe a small stone that may pass on its own. The findings from this study may also potentially be applicable to stones in adult patients. We believe that with continued advancements in US, we can reduce the number of CT scans for both adults and children. The results in part highlight one of the drawbacks of ultrasound, which is user dependence; two users can have very different results. It is anticipated that future work on automated stone and shadow sizing can reduce this along with standardizing the method in which the shadow measurement is taken.

References
1. Tasian G and Copelovitch L. Evaluation and Management of Kidney Stones in Children. J Urol. 2014: Epub ahead of print
2. Pearce MS, Salotti JA, Little MP, et al. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 2012; 380: 499-505.
3. Ray AA, Ghiculete D, Pace KT, Honey RJD. Limitations to ultrasound in the detection and measurement of urinary tract calculi. Urology 2010; 76(2):295-300.
4. Fowler KAB, Locken JA, Duchesne JH, Williamson MR. US for detecting renal calculi with nonehnanced CT as a reference standard. Radiology 2002; 222(1):109-113.
5. Dunmire B, Lee FC, Hsi RS, Cunitz BW, Paun M, Bailey MR, Sorensen MD, Harper JD. Tools to improve the accuracy of kidney stone sizing with ultrasound. Aug 2014; [Epub ahead of print].

2pBA14 – Waves by Ultrasound help better Breast Cancer Diagnosis

Max Denis – denis.max@mayo.edu 507-266-7449
Mohammad Mehrmohammadi – mehr@wayne.edu
Pengfei Song – song.pengfei@mayo.edu
Duane D. Meixner – meixner.duane@mayo.edu
Robert T. Fazzio – fazzio.robert@mayo.edu
Sandhya Pruthi – pruthi.sandhya@mayo.edu
Shigao Chen – chen.shigao@mayo.edu
Mostafa Fatemi – fatemi.mostafa@mayo.edu
Azra Alizad – alizad.azra@mayo.edu 507-254-5970

Mayo Clinic College of Medicine
200 1st St SW
Rochester, MN 55905

Popular version of paper 2pBA14
Presented Monday morning, October 28, 2014
168^th ASA Meeting, Indianapolis

Currently, a large number of patients with suspicious breast masses undergo biopsy, more than half of which turn out to be benign. The huge number false positive cases results in an enormous unnecessary cost plus psychological and physical trauma to patients. To avoid such biopsies, one needs to use a modality that can better differentiate between the benign and malignant lesions.

Palpation, the examination of tissue through the use of touch, remains one of the simplest yet effective methods for detecting breast tumors. However, the sense of touch is not sensitive enough to detect small or very deep lesions. It is well known that breast tumors are often much harder than the normal tissue, and cancerous masses are harder than the benign ones [1]. Therefore, scientists have been trying to develop new imaging tools that are sensitive to tissue stiffness. Elasticity medical imaging is an emerging field that provides information about a tissue’s stiffness property [2].

This paper presents application of a new tool called “Comb Push ultrasound elastography (CUSE)”, developed in our ultrasound laboratory at Mayo Clinic Rochester [3,4,5] for accurate measurement and imaging of breast mass stiffness. This new tool will help improving detection and differentiation of breast masses, which will eventually help physicians in better diagnosis of breast cancer. We attempt to assess a tissue’s stiffness property noninvasively by applying ultrasound to tap on breast mass and determine its stiffness by measuring the speed of the resulting waves. These waves are called shear waves. Thereafter, a two-dimensional shear wave speed map is reconstructed. Having already identified the region of interest from the ultrasound, the shear wave speed map is overlaid onto the ultrasound image. Therefore, the shear wave speed within the breast mass can be measured which allows us to determine the stiffness of the mass.

Denis_WaveBreastCancerUltrasound_ASA_pictures

Figure 1. Examples of CUSE evaluations of (a) benign and (b) cancerous breast masses.

Hence, the CUSE imaging technique may be useful as a noninvasive method as an adjunct to breast ultrasound for differentiating benign and malignant breast masses, and may help in reducing the number of unnecessary biopsies. This ongoing project is being done under an approved protocol by Mayo Institutional Review Board and funded by grants and R01CA148994- R01CA148994-04S1 from National Institute of Health and is led by Dr. Azra Alizad.

References:

Sewell CW (1995) Pathology of benign and malignant breast disorders. Radiologic Clinics of North America 33: 1067-1080.
Sarvazyan A, Hall TJ, Urban MW, Fatemi M, Aglyamov SR, et al. (2011) An overview of elastography–an emerging branch of medical imaging. Current medical imaging reviews 7: 255.
Song P, Manduca A, Zhao H, Urban MW, Greenleaf JF, et al. (2014) Fast Shear Compounding Using Robust 2-D Shear Wave Speed Calculation and Multi-directional Filtering. Ultrasound in medicine & biology 40: 1343-1355.
Song P, Urban MW, Manduca A, Zhao H, Greenleaf JF, et al. (2013) Comb-push Ultrasound Shear Elastography (CUSE) with Various Ultrasound Push Beams.
Song P, Zhao H, Manduca A, Urban MW, Greenleaf JF, et al. (2012) Comb-push ultrasound shear elastography (CUSE): a novel method for two-dimensional shear elasticity imaging of soft tissues. Medical Imaging, IEEE Transactions on 31: 1821-1832.

5aNS6 – The Perceived Annoyance of Urban Soundscapes

Adam Craig – Adam.Craig@gcu.ac.uk
Don Knox – D.Knox@gcu.ac.uk
David Moore – J.D.Moore@gcu.ac.uk

Glasgow Caledonian University
School of Engineering and Built Environment
70 Cowcaddens Road
Glasgow
United Kingdom
G4 0BA

Popular version of paper 5aNS6
Presented Friday morning, October 31^st 2014
168^th ASA Meeting, Indianapolis

The term ‘soundscape’ is widely used to describe the sonic landscape and can be considered the auditory equivalent of a visual landscape. Current soundscape research looks into the view of sound assessment in terms of perception and has been the subject of large scale projects such as the Positive Soundscapes Project (Davies et al. 2009) i.e. the emotional attributes associated with particular sounds. This research addresses the limitations of current noise assessment methods by taking into account the relationship between the acoustic environment and the emotional responses and behavioural characteristics of people living within it. Related research suggests that a variety of objective and subjective factors influence the effects of exposure to noise, including age, locale, cross-cultural differences (Guyot at el. 2005) and the time of year (Yang and Kang, 2005). A key aspect of this research area is the subjective effect of the soundscape on the listener. This paradigm emphasises the subjective perception of sound in an environment – and whether it is perceived as being positive or negative. This approach dovetails with advancing sound and music classification research which aims to categorise sounds in terms of their emotional impact on the listener.

Annoyance is one of the main factors which contribute to a negative view of environmental noise, and can lead to stress-related health conditions. Subjective perception of environmental sounds is dependent upon a variety of factors related to the sound, the geographical location and the listener. Noise maps used to communicate information to the public about environmental noise in a given geographic location are based on simple noise level measurements, and do not include any information regarding how perceptually annoying or otherwise the noise might be.

Figure 1 Selected locations for recording – image courtesy of Scottish Noise Mapping

This study involved subjective assessment by a large panel of listeners (N=167) of a corpus of sixty pre-recorded urban soundscapes collected from a variety of locations around Glasgow City Centre (see figure 1). Binaural recordings were taken at three points during each 24 hour period in order to capture urban noise during day, evening and night. Perceived annoyance was measured using Likert and numerical scales and each soundscape measured in terms of arousal and positive/negative valence (see figure 2).

Figure 2 Arousal/Valance Circumplex Model Presented in Listening Tests

Coding of each of the soundscapes would be essential process in order to test the effects of the location on the variables provided by the online survey namely annoyance score (verbal), annoyance score (numeric), quadrant score, arousal score, and valence score. The coding was based on the environment i.e. urban (U), semi-open (S), or open (O); the density of traffic i.e. high (H), mid (M), low (L); and the distance form the main noise source (road traffic) using two criteria >10m (10+) and <10m (10-). The coding resulted in eight different location types; UH10-, UH10+, UM10+, UL10-, SM10+, SL10-, SL10+, and OL10+.

To capture quantitative information about the actual audio recordings themselves, the MIRToolkit for MATLAB was used to extract acoustical features from the dataset. Several functions were identified that could be meaningful for measuring the soundscapes in terms of loudness, spectral shape, but also rhythm, which could be thought of in not so musical terms but as the rate and distribution of events within a soundscape.

As expected, correlations between extracted features and locations suggest where there are many transient events, higher energy levels, and where the type of events include harsh and dissonant sounds i.e. heavy traffic, resulted in higher annoyance scores and higher arousal scores but perceived more negatively than quiet areas. In those locations where there are fewer transient events, lower energy levels, and there are less harsh and possibly more positive sounds i.e. birdsong, resulted in lower annoyance scores and lower arousal scores as well as being perceived more positively than busy urban areas. The results shed light on the subjective annoyance of environmental sound in a range of locations and provide the reader with an insight as to what psychoacoustic features may contribute to these views of urban soundscapes.

References

Davies, W., Adams, M., Bruce, N., Cain, R., Jennings, P., Carlyle, A., … Plack, C. (2009, October 26). A positive soundscape evaluation system. Retrieved from http://usir.salford.ac.uk/2468/1/Davies_et_al_soundscape_evaluation_euronoise_2009.pdf

Guyot, F., Nathanail, C., Montignies, F., & Masson, B. (2005). Urban sound environment quality through a physical and perceptive classification of sound sources : a cross-cultural study Methodology.

Scottish Noise Mapping (2014). Scottish Noise Mapping: Map Search [Online] http://gisapps.aecomgis.com/scottishnoisemapping_p2/default.aspx#/Main. [Accessed 20^th June 2014]

Yang, W., & Kang, J. (2005). Soundscape and Sound Preferences in Urban Squares: A Case Study in Sheffield. Journal of Urban Design, 10(1), 61–80. doi:10.1080/13574800500062395

1aSC9 – Challenges when using mobile phone speech recordings as evidence in a court of law

Balamurali B. T. Nair – bbah005@aucklanduni.ac.nz
Esam A. Alzqhoul – ealz002@aucklanduni.ac.nz
Bernard J. Guillemin – bj.guillemin@auckland.ac.nz

Dept. of Electrical & Computer Engineering,
Faculty of Engineering,
The University of Auckland,
Private Bag 92019, Auckland Mail Centre,
Auckland 1142, New Zealand.

Phone: (09) 373 7599 Ext. 88190
DDI: (09) 923 8190
Fax: (09) 373 7461

Popular version of paper 1aSC9 Impact of mismatch conditions between mobile phone recordings on forensic voice comparison
Presented Monday morning, October 27, 2014
168th ASA Meeting, Indianapolis

When Motorola’s vice president, Martin Cooper, made his first call from a mobile phone device, which priced about four thousand dollars back in 1983, one could not have imagined then that in just a few decades mobile phones would become a crucial and ubiquitous part of everyday life. Not surprisingly this technology is also being increasingly misused by the criminal fraternity to coordinate their activities, which range from threatening calls, to ransoms and even bank frauds and robberies.

Recordings of mobile phone conversations can sometimes be presented as major pieces of evidence in a court of law. However, identifying a criminal by their voice is not a straight forward task and poses many challenges. Unlike DNA and finger prints, an individual’s voice is far from constant and exhibits changes as a result of a wide range of factors. For example, the health condition of a person can substantially change his/her voice, and as a result the same words spoken on one occasion would sound different on another.

The process of comparing voice samples and then presenting the outcome to a court of law is technically known as forensic voice comparison. This process begins by extracting a set of features from the available speech recordings of an offender, whose identity obviously is unknown, in order to capture information that is unique to their voice. These features are then compared using various procedures with those of the suspect charged with the offence.

One approach that is becoming widely accepted nowadays amongst forensic scientists for undertaking forensic voice comparison is known as the likelihood ratio framework. The likelihood ratio addresses two different hypotheses and estimates their associated probabilities. First is the prosecution hypothesis which states that suspect and offender voice samples have the same origin (i.e., suspect committed the crime). Second is the defense hypothesis that states that the compared voice samples were spoken by different people who just happen to sound similar.

When undertaking this task of comparing voice samples, forensic practitioners might erroneously assume that mobile phone recordings can all be treated in the same way, irrespective of which mobile phone network they originated from. But this is not the case. There are two major mobile phone technologies currently in use today: the Global System for Mobile Communications (GSM) and Code Division Multiple Access (CDMA), and these two technologies are fundamentally different in the way they process speech. One difference, for example, is that the CDMA network incorporates a procedure for reducing the effect of background noise picked up by the sending-end mobile microphone, whereas the GSM network does not. Therefore, the impact of these networks on voice samples is going to be different, which in turn will impact the accuracy of any forensic analysis undertaken.

Having two mobile phone recordings, one for the suspect and another for the offender that originate from different networks represent a typical scenario in forensic case work. This situation is normally referred to as a mismatched condition (see Figure 1). Researchers at the University of Auckland, New Zealand, have conducted a number of experiments to investigate in what ways and to what extent such mismatch conditions can impact the accuracy and precision of a forensic voice comparison. This study used speech samples from 130 speakers, where the voice of each speaker had been recorded on three occasions, separated by one month intervals. This was important in order to account for the variability in a person’s voice which naturally occurs from one occasion to another. In these experiments the suspect and offender speech samples were processed using the same speech codecs as used in the GSM and CDMA networks. Mobile phone networks use these codecs to compress speech in order to minimize the amount of data required for each call. Not only this, the speech codec dynamically interacts with the network and changes its operation in response to changes occurring in the network. The codecs in these experiments were set to operate in a manner similar to what happens in a real, dynamically changing, mobile phone network.

Typical scenario in a forensic case work

The results suggest that the degradation in the accuracy of a forensic analysis under mismatch conditions can be very significant (as high as 150%). Surprisingly, though, these results also suggest that the precision of a forensic analysis might actually improve. Nonetheless, precise but inaccurate results are clearly undesirable. The researchers have proposed a strategy for lessening the impact of mismatch by passing the suspect’s speech samples through the same speech codec as the offender’s (i.e., either GSM or CDMA) prior to forensic analysis. This strategy has been shown to improve the accuracy of a forensic analysis by about 70%, but performance is still not as good as analysis under matched conditions.

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