March - June 2015 : A review on the technological advances in the area of UNHS

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Category: Guest editorial
Last Updated on Friday, 06 March 2015 17:37
Written by Stavros Hatzopoulos PhD, Lech Sliwa PhD, Piotr H Skarzynski MD, PhD
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About the Guest-Editors

This email address is being protected from spambots. You need JavaScript enabled to view it. is an assistant professor at the Institute of Physiology and Pathology of Hearing in Warsaw, Poland. Dr. Sliwa specializes in biomedical engineering and his professional interests focus on objective testing of hearing. He is also involved in developing and conducting educational programs on audiology in Poland.

This email address is being protected from spambots. You need JavaScript enabled to view it. got his MD degree from the  Medical University of Warsaw in 2008 and a MSc from the  Department of Management (University of Warsaw) in 2010. He received his PhD degree from the  Medical University of Warsaw in 2012. Currently he  works in the Institute of Physiology and Pathology of Hearing as a resident, in Medical University of Warsaw as an Assistant and Academic Teacher and in the Institute of Sensory Organs as Director of Science and Development. He is an active member of many scientific societies. He chairs the vice Chairman position in the Junior European Rhinology Society from 2010. His academic and research work can be summarized by  652 congress presentations and posters, 29 round tables and more than 183 publications. His main interests this period of time are international projects including Asian and African countries.

 

 

About the Editor

Stavros Hatzopoulos PhD, is the web editor of the OAE Portal since 2001. His interests involve biomedical signal processing and applications of neonatal hearing screening technologies in national and international programs.

 

 

Introduction

Otoacoustic emissions (OAEs) or cochlear echoes is a term coined by David Kemp in 1978, describing the transient responses from the inner ear, upon its stimulation by an acoustic click stimulus. The last 20 years OAE protocols have been used in many areas of Audiology and Hearing Science (Robinette and Glattke, 1997). The most significant contribution of OAEs is in the area of Universal Neonatal Hearing Screening (UNHS).

While the main objective of neonatal hearing screening (NHS) is the identification of infants with a hearing deficit (≥ 30 dB HL), the objectives of a UNHS program have a broader vision. Two important phases are considered: (i) the identification of infants with mild and moderate hearing deficits; and (ii) an intervention in terms of hearing improvement (hearing aids, cochlear implants) and neural rehabilitation, aiming at the restoration of hearing and the normalization of the quality of life of the young patient.

Within the last decade, numerous new challenges have appeared in the UNHS arena, such as : (i) the need to validate the automated OAE/ ABR screeners; (ii) the need to qualify the responses from the automated devices; (iii) the need to obtain additional information (i.e. hearing threshold) for the subject under assessment, in a short period of time; (iv) and the need to integrate numerous measurements in a single portable automated device. To respond to these clinical demands, several new methodologies have been introduced to the UNHS clinical practice. In this context, the aim of this editorial  is to provide information on these new technological trends.

 

1. Automated Auditory Brainstem Responses.

 

In the early 2002, the first 4rth generation OAE devices appeared in the market and offered the possibility to integrate information from different testing protocols such as automated OAE (AOAE) and automated ABR (AABR) responses. The combined screening protocols (AOAE + AABR) targeted the identification of auditory neuropathy, most prevalent in the neonatal intensive care (NICU) environment.

         With the introduction of the AABR protocols in the NHS programs, several issues became evident and among those questions related to screening-times and screening costs. The latter is outside the objectives of this paper and will not be addressed.  A previous study of our group, in the context of the regional NHS project CHEAP in Emilia-Romagna, Italy (Ciorba et al, 2007), provided evidence suggesting that in terms of time-requirements, portable ABR (Audioscreener, Viasys; Accuscreen, GN-Otometrics;  Algo 3i, Natus)  and OAE devices were converging to the same time values. Data from the above study suggested that : (i) the average time for AOAE responses is less than 10s in a cooperative subject and less that 120s (2 min) in non-cooperative subjects ; (ii) the test times of AABR, in cooperative subjects, were less than 120 s, while uncooperative subjects were tested within 10 min (per ear). While it takes some minimum expertise to properly handle and position the OAE probe, the ABR electrode placement presents more complications especially in cases where the subject shows high electrode impedance. In the latter case the AABR testing is difficult to complete and the test times are unavoidably longer.

          Theoretically the combined 2-stage approach (i.e. AOAE + AABR) eliminates the risk of not identifying infants with Auditory Neuropathy and assures that the screening sensitivity is high. Contrary to this hypothesis, data from an American study (White et al, 2005) suggest that this is not the case. The study assessed information from 86634 infants and for the infants who were screened for hearing loss, using a typical 2-stage OAE/A-ABR protocol, approximately 23% of those with permanent hearing loss at 8–12 months of age, would have passed the AABR. These data suggest that stringent criteria should be incorporated in the final evaluation of the current OAE and ABR automated devices.

            Another interesting development in the ABR / AABR area is in the area of the evoking stimulus. Traditionally ABR and AABR protocols use click stimuli to synchronize as many neural fibers as possible and to obtain an ABR response of large amplitude with less sweeps. Recently chirp stimuli have been used to optimize the ABR / AABR responses. According to Kristensen and Elberling (2012) upward chirps are often designed to compensate for the cochlear traveling wave delay which is regarded as independent of stimulation level. A chirp based on a traveling wave model is therefore referred to as a level-independent chirp. Another compensation strategy, for instance based on frequency-specific auditory brainstem response (ABR) latencies, results in a chirp that changes with stimulation level and is therefore referred to as a level-dependent chirp. One such strategy, the direct approach, results in a chirp family that is called the level-specific chirp. The data from studies using level-dependent chirps (Ferm et al , 2013; Rodriguez et al , 2013; Zirn et al , 2013;  Cebulla et al, 2014; Rodriguez and Lewis , 2014; Stuart and Kobb, 2015) are very encouraging, reporting ABRs recorded in less time and with higher amplitude values. The latter is very important for the statistical algorithms of the AABR devices, meaning that higher statistical accuracy can be obtained in the chirp-evoked AABRs.

 

2. Middle Ear Reflectance and Middle Ear Power Analysis -MEPA

 

Editors Note : some material in this section is copied from the Mimosa Acoustics website

Data from studies which have evaluated the performance of NHS programs in the well baby clinic or in the NICU  (White et al, 2005; Aithal et al, 2012; Vos et al, 2015) have reported that the majority of “screening refers” are due to transmissive factors such as the amneotic fluid or any substance blocking the propagation of the acoustic stimulus. Usually these conditions are transient (i.e. they last 24-30 h) and infants can pass the OAE test when the fluid is absorbed or when the auditory meatus is clean.

Using a middle ear power analysis (MEPA) testing procedure, it is possible to determine whether the middle ear conducts properly acoustic stimuli, and in this context the OAE screening results can be interpreted more clearly. Data from the literature (Sanford et al,  2009; Hunter et al, 2010) have showed that one of MEPA metrics, the middle ear reflectance,  is more sensitive to Distortion Product OAE (DPOAE) status than the 1 kHz tympanometry values. Power reflectance is a measure of middle-ear inefficiency. It is the ratio or percentage of power reflected from the eardrum to the incident power, as a function of frequency. Acoustic power measurements objectively quantify middle-ear function or malfunction.

Currently there is only one manufacturer (Mimosa Acoustics) offering reflectance measurements. The company offers two devices capable of MEPA, DPOAE and general OAE measurements : the Otostat (handheld) and the HearID research oriented) model. These devices can measure wideband power reflectance up to 6 kHz and most importantly without the need for a pressurized ear canal.

 

To interpret the clinical usefulness of the MEPA approach Hunter et al (2010) constructed normative regions for newborns, relating Middle Ear Reflectance values, evoked by chirp stimuli and DPOAE amplitudes at 1.0, 1.5, 2.0, 3.0, 4.0 and 6.0 kHz. Three regions were described as :

  • (1) a Retest area (where the values of reflectance are high);
  • (2) an Ambiguous area (where the values of reflectance are moderate); and
  • (3) a Pass area (where the values of reflectance are low).

These areas are depicted in Figure 1. In terms of interpretation, If the MEPA reflectance values fall above the "Pass" area, especially around 2 kHz, outer or middle ear problems may be the cause, and a re-screening session after a few hours or a day is recommended prior to diagnostic referral.  If the outcome is still a refer, then clinical assessment is necessary. If the MEPA reflectance values fall within the "Pass" area, especially around 2 kHz, the middle ear is more likely to be normal and associated with a DPOAE pass result. If the DPOAE result is ambiguous or a refer, then middle ear issues are not suspected as a hearing deficit cause and further clinical assessment is necessary.  Table 1 summarizes all these outcomes.

 

Figure 1: Pass, ambiguous, and retest regions for wideband reflectance using chirp (solid regions) and sine (symbols) stimuli. Results above this region, especially at 2 kHz, are associated with false-positive DPOAE refer results. Data from Hunter et al., 2010 taken from the Mimosa Acoustics website

 

Table 1 : How to interpet Distortion Product OAEs and Reflectance Results in Newborns. Data taken from the Mimosa Acoustics website

 

3. Auditory Steady State Responses  (ASSR) in Neonatal Screening

 

Both OAE and ABR technologies utilize as stimuli electrical clicks and the acquired information is clearly more related to the audiometric frequencies of 1.0 and 2.0 kHz. Within this context, there has been a speculation of whether other technologies could be used in a fast hearing assessment of neonates, children and adults. A group of electrophysiological measurements similar to OAEs and AABR  includes electro-cochleography (EcoG), Middle latency  (ML)  and Steady State Responses (SSR). From this group the latter category has shown interesting characteristics due to fact, that by changing the modulation frequency of the stimuli one can get responses from the Auditory cortex (low modulation frequencies around 40 Hz) or from the Brainstem (Cone-Wesson et al; 2002; Dimitrijevic et al , 2002: John and Picton, 2002). The SSR protocol has already passed to an automated one (ASSR) and for the last 10 years numerous publications have been devoted to the threshold estimation via the ASSR technique. The ASSR protocols have been greatly optimized, (Gorga et al, 2004) and the SSR responses are detected in the frequency domain by robust probabilistic algorithms.

In 2002 Conne-Wesson et al,proposed the use of ASSR as a hearing screening tool, with the objective that ASSR could substitute the AABR. A few reports have been available since (Stueve and O’Rourke, 2003; Luts et al, 2004; Swanepoel et al; 2004) indicating a good agreement between ASSR and AABR at 2.0 kHz and various differences at 0.5, 1.0 and 4.0 kHz. Most studies recommended the use of the SSR technique in the clinic but the point of substituting the AABR with ASSR is not fully supported by the available data.

The factors which affect the AABR (ambient noise and electrode impedance) interfere with the ASSR recordings as well. In order to resolve these issues Vivosonic presented in 2010 a new line of devices using preamplifiers at the level of the scalp-electrodes (called amplitrodes) which suppress the level of ambient noise and provide very clean AABR and ASSR traces. It is to be seen how these electrodes will be intergraded in the normal clinical reality since the pre-amplifiers require electrical energy which translates into changing batteries every x tests.

In the context of neonatal screening, an ASSR screening protocol can target a few frequency points (i.e. 1.0 & 2.0 kHz or 2.0  & 4.0 kHz) which show immunity to ambient noise (see the neonatal data in Figures 2 A, B). One of the problems of the early ASSR devices  (Audera by Viasys; Master by Natus) was that the hearing threshold estimates were characterized by large variance.  Recent data from the literature and specifically from the Audix equipment developers (Neuronic)  report significant advances both in terms of software and hardware and a superior performance of a multiple SSR protocol to the conventional ABR (Mijares et al, 2013; Perez-Abalo et al; 2013).

Recently a study (Ciorba et al, 2013) presented data on the relationship between ABR, ASSR estimates and data from Conditioned Orientation Responses (COR), a technique widely diffused in the intervention phase of many UNHS programs. The data suggested a very good relationship between the outcomes of the ASSR and COR techniques, with the ASSR data being closer to the ABR estimates. Data from large-scale studies along this direction (i.e. comparing ASSR with other protocols) could support this hypothesis and eliminate the use of ABR and COR in the intervention phase of a UNHS program.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 2: Panel A : ASSR response from a well baby who was crying using the AUDERA device from VIASYS. The lowest tested frequency of  500 Hz was not available due to noise. The length of the testing procedure was 22 min (14 min longer than the successfully completed  AABR test). Despite the theoretical noise immunity at 2.0 and 4.0 kHz the size of the error bars indicate that the measurements are too variable to be considered. The “x” symbols indicate the mean threshold level of the measurements. Panel B : ASSR response from a well baby using the AUDERA device. The length of this test was also longer that the AABR (16 vs 7 min). The AABR suggested a REFER probably due to conductive complications. In this case the 2.0 and 4.0 kHz frequencies show good noise immunity  (suggested by the small size of the error bars). The “x” symbols indicate the mean threshold level of the measurements.

 

4. Threshold estimation via DPOAE measurements

 

An interesting challenge for otoacoustic emissions has been the relationship between the amplitude of the OAE response and the hearing threshold (Whitehead et al 1995a; 1995b; Shera et al, 1999). For cases where no conductive losses are present there is a good agreement between OAEs and the hearing threshold. In such cases Input-Output distortion product OAE (DPOAE) protocols may offer more information (Whitehead et al, 1995a, Janssen et al, 1998; Dorn et al, 2001; Gorga et al, 2003b). Besides the relationship to pure-tone thresholds, DPOAE I/O-functions provide an estimate of the compression related to the  outer hair cell amplifier. Data supporting this hypothesis are available from animal studies where the hearing of the animals was  impaired with acute furosemide intoxication (Mills and Rubel, 1996) and human studies with subjects suffering from cochlear hearing loss (Janssen et al., 1998; Kummer et al., 1998; Boege and Janssen, 2002; Neely et al., 2003). In these studies the slope of the DPOAE I/O-function increased with increasing hearing loss revealing a loss of compression of the outer hair cell amplifiers. In this context by using numerous combinations of I/O  DPOAE recordings one can obtain very precise information related to the status of the cochlear amplifier (Gorga et al, 2003a, 2003b). Extrapolated DPOAE I/O-functions were constructed from neonates to estimate pure-tone threshold levels and the corresponding cochlear compression values (Janssen et al., 2003). The estimated hearing threshold was found to be increasing within the early postnatal period (average age: 3 days), predominantly at the higher frequencies, and to be normalized in a follow-up measurement (after four weeks). However, the slope of the DPOAE I/O-functions obtained in the first and second measurement was unchanged revealing normal cochlear compression. Consequently, these findings were interpreted as temporary conductive hearing losses due to the presence of amniotic fluid and/or Eustachian tube dysfunction. In this clinical scenario, especially during the first days of life, a hearing screening test may lead to false positive results due to a temporary conductive hearing loss. The use of the slope of DPOAE I/O-functions could be used as an index of conductive losses which might result in less false positives an in less time spent for audiological clinical diagnostics. According to the data of Janssen et al (2003) the values  of the DPOAE slope can discriminate and differentiate  conductive from  sensorineural hearing losses. In addition DPOAE I/O-functions have been reported to be correlated with loudness (Neely et al. 2003), so DPOAE I/O information would also offer the potentiality of assessing information to basic hearing aid fitting.

The research findings from Janssen et al (2003) and Gorga et al (2003a) have been commercialized in a device called Cochlea-Scan (Osvald et al, 2003) by Natus. Hearing threshold can be extrapolated up to values relative to 50 dB HL in the frequency range from 1.5 to 6 kHz. Figure 3 shows a typical hearing threshold profile and the corresponding Cochlea-Scan mediated estimation of hearing threshold. At present, the Cochlea-Scan device offers a platform for a third generation OAE testing (TEOAEs, DPOAEs), I/O DPOAE estimation with hearing threshold extrapolation.

Figure 3: Cochlea-Scan data in comparison to behavioral threshold levels, from an adult subject : Top panel, Cochlea-Scan responses and threshold estimation from the right ear; Middle Panel, behavioral data ; Bottom panel: Cochlea-Scan responses and threshold estimation from the left ear. The Cochlea-Scan panels report the estimated threshold values per frequency.  The acronym “NA” means that no threshold estimation was possible at the tested frequency. 

 

Further analyses  (Hatzopoulos et al, 2009) on the efficacy of the Cochlea-Scan DPOAE algorithm, relating hearing threshold data and Cochlea-Scan estimated thresholds from a group of adult sensorineural cases, suggested a different scenario than the one proposed initially by Janssen (2003). In the Hatzopoulos et al (2009) study behavioral and Cochlea-Scan data were analyzed with logistic regression models in order to find the probability (≤ 0.9) of a robust DPOAE response at 2.0, 3.0, and 4.0 kHz .The data suggested that the max behavioral levels where valid DPOAEs could be detected were equal to of 32.8, 21, and 34 dB respectively. For normal hearing adults the detection levels were lower. Figures 4 and 5 depict the relationship between behavioral data (at 2.0, 3.0 and 4.0 kHz) and Cochlea-Scan estimates from the cases presenting hearing loss. For example in Figure 4 and for 2.0 kHz, a probability of  90% Cochlea-Scan response detection corresponds to a threshold approximately of 15 dB HL.  In this context, it is still possible to have a detection threshold as high as 50 dB HL the corresponding probability falls below 30% and as such, limits the usefulness of the Cochlea-Scan protocol.

 

Figure 4: Logistic regression model for normal hearing threshold Cochlea-Scan data at 2.0 and 3 kHz. The equation relating the two variables (c= Cochlea-Scan data; p= behavioral data)  is shown at the top of each graph. The x axis shows behavioral threshold in dB HL and the y axis the probability of a Cochlea-Scan response. For a fixed response probability of 90% the detectable threshold level is approximately 15  and 20 dB HL, for the data at 2.0 and 3.0 kHz. This implies that in order to obtain a Cochlea-Scan response for a 50 dB HL hearing threshold the probability of finding a true response drops to  40% and 10% respectively ( for 2.0 and 3.0 kHz).

 

 

 Figure 5: Logistic regression model for normal hearing threshold Cochlea-Scan data at 4 kHz. The equation relating the two variables (c= Cochlea-Scan data; p= behavioral data) is shown at the top of each graph. The x axis shows behavioral threshold in dB HL and the y axis the probability of a Cochlea-Scan response. For a fixed response probability of 90% the detectable threshold level is approximately 35 dB HL. For a 50 dB HL threshold the probability of a true response drops to 15%. The relationship between the behavioral and Cochlea-Scan data at 4.0 kHz is optimized, but the sensitivity of the method drops very quickly as we move to higher thresholds 35 dB HL.

 

The authors at this point in time, could not verify if Natus has intentions of developing further this product. Cochlea-Scan threshold estimation could be greatly improved by introducing changes in the device’s algorithms related to : (i) the sample size which was used to calibrate the prototype device. Sampling a larger population can minimize the variance of the average DPOAE amplitude per tested frequency; (ii) by inserting correction factors in the algorithm which extrapolates DPOAE amplitudes to hearing levels. Janssen  (2003) has used a linear regression model to achieve this, but higher order models (quadratic, cubic) can offer higher precision in the threshold estimation.

 

 

5. Integration of multiple hearing assessment protocols into an automated device.

The success of the NHS screening practices challenged another area of pediatric audiology , the area of school-children screening. Data from large-scale screening programs, as in Poland, suggested that in this area different protocols could be applied than in UNHS programs, with emphasis on pure tone behavioral responses, tympanometry and ABR (Sliwa et al, 2009; 2011). The OAEs were found the less effective tool in the battery of screening tests, suffering mainly from the ambient noise present in schools.

       Recently fifth generation OAE equipment appeared in the market. A number of OAE manufacturers  (Natus, Path Medical solutions) proposed hand-held devices capable of testing subjects with OAEs / AOAEs, AABR and ASSR. A tympanometry assessment has not appeared so far due to complications in the probe of the device (canal pressurization issues). Mimosa Acoustics offers wide-reflectance measurements (which can substitute acoustic immitance) and OAEs but not evoked potentials.  

         The proposal from Path Medical Solutions (model: Sentiero - advanced) is a device capable not only of AOAE / AABR/ ASSR protocols, but also of protocols for speech Audiometry. Such a device can be easily implemented in both phases (identification , intervention)  of a UNHS program and it is hoped that other manufacturers will follow this protocol-integration trend.

 

 

Conclusions

The last 10 -15  years significant advances have been made towards  the integration of various protocols and technologies in UNHS strategies. The most important contribution is in the area of Auditory Steady State Responses which have been shown to be well correlated with other metrics in Audiology such as the AABR, ABR, OAEs and COR. The current technological trends call for an integration of even more protocols and algorithms in a hand-held device. The clinical robustness and response-quality of these new entries is yet to be evaluated.

           

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