Correction for Spatial Averaging Artifacts in Hydrophone Measurements of High-Intensity Therapeutic Ultrasound: An Inverse Filter Approach

Nominal Versus Actual Spatial Resolution: Comparison of Directivity and Frequency-Dependent Effective Sensitive Element Size for Membrane, Needle, Capsule, and Fiber-Optic Hydrophones

Frequency-dependent effective sensitive element radius [Formula: see text] is a key parameter for elucidating physical mechanisms of hydrophone operation. In addition, it is essential to know [Formula: see text] to correct for hydrophone output voltage reduction due to spatial averaging across the hydrophone sensitive element surface. At low frequencies, [Formula: see text] is greater than geometrical sensitive element radius a_g . Consequently, at low frequencies, investigators can overrate their hydrophone spatial resolution. Empirical models for [Formula: see text] for membrane, needle, and fiber-optic hydrophones have been obtained previously. In this article, an empirical model for [Formula: see text] for capsule hydrophones is presented, so that models are now available for the four most common hydrophone types used in biomedical ultrasound. The [Formula: see text] value was estimated from directivity measurements (over the range from 1 to 20 MHz) for five capsule hydrophones (three with [Formula: see text] and two with [Formula: see text]). The results suggest that capsule hydrophones behave according to a "rigid piston" model for k a _g ≥ 0.7 ( k = 2π /wavelength). Comparing the four hydrophone types, the low-frequency discrepancy between [Formula: see text] and a_g was found to be greatest for membrane hydrophones, followed by capsule hydrophones, and smallest for needle and fiber-optic hydrophones. Empirical models for [Formula: see text] are helpful for choosing an appropriate hydrophone for an experiment and for correcting for spatial averaging (over the sensitive element surface) in pressure and beamwidth measurements. When reporting hydrophone-based pressure measurements, investigators should specify [Formula: see text] at the center frequency (which may be estimated from the models presented here) in addition to a_g .

Hydrophone Measurements for Biomedical Ultrasound Applications: A Review

This article presents basic principles of hydrophone measurements, including mechanisms of action for various hydrophone designs, sensitivity and directivity calibration procedures, practical considerations for performing measurements, signal processing methods to correct for both frequency-dependent sensitivity and spatial averaging across the hydrophone sensitive element, uncertainty in hydrophone measurements, special considerations for high-intensity therapeutic ultrasound, and advice for choosing an appropriate hydrophone for a particular measurement task. Recommendations are made for information to be included in hydrophone measurement reporting.

Recommendations for Reporting Therapeutic Ultrasound Treatment Parameters

These recommendations are intended to provide guidance and to encourage best practice in reporting therapeutic ultrasound treatment parameters. Detailed uniform reporting will allow testing of therapy ultrasound systems and protocols, cross-comparison of studies between different teams using different systems and validation of therapeutic bio-effects. These recommendations have been divided into two sets, one for clinical and one for preclinical studies, each with stratified reporting categories, to account for the disparities in expertise and access to equipment between sites. The recommendations are intended to be useful for clinicians and researchers, for ethical and funding review boards and for the editors and reviewers of scientific journals.

Spatiotemporal Deconvolution of Hydrophone Response for Linear and Nonlinear Beams-Part I: Theory, Spatial-Averaging Correction Formulas, and Criteria for Sensitive Element Size

This article reports spatiotemporal deconvolution methods and simple empirical formulas to correct pressure and beamwidth measurements for spatial averaging across a hydrophone sensitive element. Readers who are uninterested in hydrophone theory may proceed directly to Appendix A for an easy method to estimate spatial-averaging correction factors. Hydrophones were modeled as angular spectrum filters. Simulations modeled nine circular transducers (1-10 MHz; F/1.4-F/3.2) driven at six power levels and measured with eight hydrophones (432 beam/hydrophone combinations). For example, the model predicts that if a 200- [Formula: see text] membrane hydrophone measures a moderately nonlinear 5-MHz beam from an F/1 transducer, spatial-averaging correction factors are 33% (peak compressional pressure or p_c ), 18% (peak rarefactional pressure or p ), and 18% (full width half maximum or FWHM). Theoretical and experimental estimates of spatial-averaging correction factors to were in good agreement (within 5%) for linear and moderately nonlinear signals. Criteria for maximum appropriate hydrophone sensitive element size as functions of experimental parameters were derived. Unlike the oft-cited International Electrotechnical Commission (IEC) criterion, the new criteria were derived for focusing rather than planar transducers and can accommodate nonlinear signals in addition to linear signals. Responsible reporting of hydrophone-based pressure and beamwidth measurements should always acknowledge spatial-averaging considerations.

Spatiotemporal Deconvolution of Hydrophone Response for Linear and Nonlinear Beams-Part II: Experimental Validation

This article reports experimental validation for spatiotemporal deconvolution methods and simple empirical formulas to correct pressure and beamwidth measurements for spatial averaging across a hydrophone sensitive element. The method was validated using linear and nonlinear beams transmitted by seven single-element spherically focusing transducers (2-10 MHz; F /#: 1-3) and measured with five hydrophones (sensitive element diameters d_g : 85-1000 [Formula: see text]), resulting in 35 transducer/hydrophone combinations. Exponential functions, exp( -αx ), where x = d_g /( λ₁F /#) and λ₁ is the fundamental wavelength, were used to model focal pressure ratios p'/p (where p' is the measured value subjected to spatial averaging and p is the true axial value that would be obtained with a hypothetical point hydrophone). Spatiotemporal deconvolution reduced α (followed by root mean squared difference between data and fit) from 0.29-0.30 (7%) to 0.01 (8%) (linear signals) and from 0.29-0.40 (8%) to 0.04 (14%) (nonlinear signals), indicating successful spatial averaging correction. Linear functions, Cx + 1, were used to model FWHM'/FWHM, where FWHM is full-width half-maximum. Spatiotemporal deconvolution reduced C from 9% (4%) to -0.6% (1%) (linear signals) and from 30% (10%) to 6% (5%) (nonlinear signals), indicating successful spatial averaging correction. Spatiotemporal deconvolution resulted in significant improvement in accuracy even when the hydrophone geometrical sensitive element diameter exceeded the beam FWHM. Responsible reporting of hydrophone-based pressure measurements should always acknowledge spatial averaging considerations.

AAPM Task Group 241: A medical physicist's guide to MRI-guided focused ultrasound body systems

Magnetic resonance-guided focused ultrasound (MRgFUS) is a completely non-invasive technology that has been approved by FDA to treat several diseases. This report, prepared by the American Association of Physicist in Medicine (AAPM) Task Group 241, provides background on MRgFUS technology with a focus on clinical body MRgFUS systems. The report addresses the issues of interest to the medical physics community, specific to the body MRgFUS system configuration, and provides recommendations on how to successfully implement and maintain a clinical MRgFUS program. The following sections describe the key features of typical MRgFUS systems and clinical workflow and provide key points and best practices for the medical physicist. Commonly used terms, metrics and physics are defined and sources of uncertainty that affect MRgFUS procedures are described. Finally, safety and quality assurance procedures are explained, the recommended role of the medical physicist in MRgFUS procedures is described, and regulatory requirements for planning clinical trials are detailed. Although this report is limited in scope to clinical body MRgFUS systems that are approved or currently undergoing clinical trials in the United States, much of the material presented is also applicable to systems designed for other applications.

Optical phase contrast imaging for absolute, quantitative measurements of ultrasonic fields with frequencies up to 20 MHz

The technique of phase contrast imaging, combined with tomographic reconstructions, can rapidly measure ultrasonic fields propagating in water, including ultrasonic fields with complex wavefront shapes, which are difficult to characterize with standard hydrophone measurements. Furthermore, the technique can measure the absolute pressure amplitudes of ultrasonic fields without requiring a pressure calibration. Absolute pressure measurements have been previously demonstrated using optical imaging methods for ultrasonic frequencies below 2.5 MHz. The present work demonstrates that phase contrast imaging can accurately measure ultrasonic fields with frequencies up to 20 MHz and pressure amplitudes near 10 kPa. Accurate measurements at high ultrasonic frequencies are performed by tailoring the measurement conditions to limit optical diffraction as guided by a simple dimensionless parameter. In some situations, differences between high frequency measurements made with the phase contrast method and a calibrated hydrophone become apparent, and the reasons for these differences are discussed. Extending optical imaging measurements to high ultrasonic frequencies could facilitate quantitative applications of ultrasound measurements in nondestructive testing and medical therapeutics and diagnostics such as photoacoustic imaging.

Hydrophone Spatial Averaging Correction for Acoustic Exposure Measurements From Arrays-Part I: Theory and Impact on Diagnostic Safety Indexes

This article reports underestimation of mechanical index (MI) and nonscanned thermal index for bone near focus (TIB) due to hydrophone spatial averaging effects that occur during acoustic output measurements for clinical linear and phased arrays. TIB is the appropriate version of thermal index (TI) for fetal imaging after ten weeks from the last menstrual period according to the American Institute of Ultrasound in Medicine (AIUM). Spatial averaging is particularly troublesome for highly focused beams and nonlinear, nonscanned modes such as acoustic radiation force impulse (ARFI) and pulsed Doppler. MI and variants of TI (e.g., TIB), which are displayed in real-time during imaging, are often not corrected for hydrophone spatial averaging because a standardized method for doing so does not exist for linear and phased arrays. A novel analytic inverse-filter method to correct for spatial averaging for pressure waves from linear and phased arrays is derived in this article (Part I) and experimentally validated in a companion article (Part II). A simulation was developed to estimate potential spatial-averaging errors for typical clinical ultrasound imaging systems based on the theoretical inverse filter and specifications for 124 scanner/transducer combinations from the U.S. Food and Drug Administration (FDA) 510(k) database from 2015 to 2019. Specifications included center frequency, aperture size, acoustic output parameters, hydrophone geometrical sensitive element diameter, etc. Correction for hydrophone spatial averaging using the inverse filter suggests that maximally achievable values for MI, TIB, thermal dose ( t ₄₃ ), and spatial-peak-temporal-average intensity ( [Formula: see text]) for typical clinical systems are potentially higher than uncorrected values by (means ± standard deviations) 9% ± 4% (ARFI MI), 19% ± 15% (ARFI TIB), 50% ± 41% (ARFI t ₄₃ ), 43% ± 39% (ARFI [Formula: see text]), 7% ± 5% (pulsed Doppler MI), 15% ± 11% (pulsed Doppler TIB), 42% ± 31% (pulsed Doppler t ₄₃ ), and 33% ± 27% (pulsed Doppler [Formula: see text]). These values correspond to frequencies of 3.2 ± 1.3 (ARFI) and 4.1 ± 1.4 MHz (pulsed Doppler), and the model predicts that they would increase with frequency. Inverse filtering for hydrophone spatial averaging significantly improves the accuracy of estimates of MI, TIB, t ₄₃ , and [Formula: see text] for ARFI and pulsed Doppler signals.

Hydrophone Spatial Averaging Correction for Acoustic Exposure Measurements From Arrays-Part II: Validation for ARFI and Pulsed Doppler Waveforms

This article reports the experimental validation of a method for correcting underestimates of peak compressional pressure ( pc) , peak rarefactional pressure ( pr) , and pulse intensity integral (pii) due to hydrophone spatial averaging effects that occur during output measurement of clinical linear and phased arrays. Pressure parameters ( pc , pr , and pii), which are used to compute acoustic exposure safety indexes, such as mechanical index (MI) and thermal index (TI), are often not corrected for spatial averaging because a standardized method for doing so does not exist for linear and phased arrays. In a companion article (Part I), a novel, analytic, inverse-filter method was derived to correct for spatial averaging for linear or nonlinear pressure waves from linear and phased arrays. In the present article (Part II), the inverse filter is validated on measurements of acoustic radiation force impulse (ARFI) and pulsed Doppler waveforms. Empirical formulas are provided to enable researchers to predict and correct hydrophone spatial averaging errors for membrane-hydrophone-based acoustic output measurements. For example, for a 400- [Formula: see text] membrane hydrophone, inverse filtering reduced errors (means ± standard errors for 15 linear array/hydrophone pairs) from about 34% ( pc) , 22% ( pr) , and 45% (pii) down to within 5% for all three parameters. Inverse filtering for spatial averaging effects significantly improves the accuracy of estimates of acoustic pressure parameters for ARFI and pulsed Doppler signals.

Correction for Hydrophone Spatial Averaging Artifacts for Circular Sources

This article reports an investigation of an inverse-filter method to correct for experimental underestimation of pressure due to spatial averaging across a hydrophone sensitive element. The spatial averaging filter (SAF) depends on hydrophone type (membrane, needle, or fiber-optic), hydrophone geometrical sensitive element diameter, transducer driving frequency, and transducer F number (ratio of focal length to diameter). The absolute difference between theoretical and experimental SAFs for 25 transducer/hydrophone pairs was 7% ± 3% (mean ± standard deviation). Empirical formulas based on SAFs are provided to enable researchers to easily correct for hydrophone spatial averaging errors in peak compressional pressure ( p_c ), peak rarefactional pressure ( p_r ), and pulse intensity integral. The empirical formulas show, for example, that if a 3-MHz, F /2 transducer is driven to moderate nonlinear distortion and measured at the focal point with a 500- [Formula: see text] membrane hydrophone, then spatial averaging errors are approximately 16% ( p_c ), 12% ( p_r ), and 24% (pulse intensity integral). The formulas are based on circular transducers but also provide plausible upper bounds for spatial averaging errors for transducers with rectangular-transmit apertures, such as linear and phased arrays.

100 MHz bandwidth planar laser-generated ultrasound source for hydrophone calibration

High-frequency calibration of hydrophones is becoming increasingly important, both for clinical and scientific applications of ultrasound, and user safety. At present, the calibrations available routinely to the user community extend to 60 MHz. However, hydrophones that can measure beyond this are available, and ultrasonic fields often contain energy at higher frequencies, e.g., generated through nonlinear propagation of high-amplitude ultrasound used for therapeutic applications, and the increasing use of higher frequencies in imaging. Therefore, there is a need for calibrations up to at least 100 MHz, to allow ultrasonic fields to be accurately characterized, and the risk of harmful bioeffects to be properly assessed. Currently, sets of focused piezoelectric transducers are used to meet the pressure amplitude and bandwidth requirements of Primary Standard calibration facilities. However, when the frequency is high enough such that the size of the ultrasound focus becomes less than the hydrophone element's diameter, the uncertainty due to spatial averaging becomes significant, and can be as high as 20% at 100 MHz. As an alternate to piezoelectric transducers, a laser-generated ultrasound calibration source was designed, fabricated, and characterized. The source consists of an optically absorbing carbon-polymer nanocomposite excited by a large-diameter 1064 nm laser pulse of 2.6 ns duration. Peak pressure amplitudes of several Mega-Pascal were readily achievable, and the signal contained measurable frequency components up to 100 MHz. The variation in the pressure amplitudes was less than 2% from its mean over a three-hour test period. The ultrasound beam was sufficiently broad that the uncertainties due to spatial averaging were negligible.

Hydrophone Spatial Averaging Artifacts for ARFI Beams from Array Transducers

This paper reports underestimation of peak compressional pressure (p _c), peak rarefactional pressure (p _r ), and pulse intensity integral (pii) due to hydrophone spatial averaging of acoustic radiation force impulse (ARFI) beams generated by clinical linear and phased arrays. Although a method exists for correcting for hydrophone spatial averaging for circularly-symmetric beams, there is presently no analogous method for rectangularly-symmetric beams generated by linear and phased arrays. Consequently, pressure parameters (p _c, p _r , and pii) from clinical arrays are often not corrected for spatial averaging. This can lead to errors in Mechanical Index (MI) and Thermal Index (TI), which are derived from pressure measurements and are displayed in real-time during clinical ultrasound scans. ARFI beams were generated using three clinical linear array transducers. Output pressure waveforms for all three transducers were measured using five hydrophones with geometrical sensitive element sizes (d_g) ranging from 85 to 1000 μm. Spatial averaging errors were found to increase with hydrophone sensitive element size. For example, if d_g = 500 μm (typical membrane hydrophone), frequency = 2.25 MHz and F/# = 1.5, then average errors are approximately -20% (p_c), -10% (p_r), and -25% (pii). Therefore, due to hydrophone spatial averaging, typical membrane hydrophones can exhibit significant underestimation of ARFI pressure measurements, which likely compromises exposure safety indexes.

Correction for Spatial Averaging Artifacts for Circularly-Symmetric Pressure Beams Measured with Membrane Hydrophones

This paper investigates experimental underestimation of pressure measurements due to spatial averaging across a hydrophone sensitive element. Empirical relationships are measured to enable correction for hydrophone spatial averaging errors in peak compressional pressure (p _c ), peak rarefactional pressure (p _r ), and pulse intensity integral (pii). The empirical relationships show, for example, that if a 3-MHz, F/2 transducer is driven to moderate nonlinear distortion and measured at the focal point with a 500-μm membrane hydrophone, then spatial averaging errors are approximately 16% (p _c ), 12% (p _r ), and 24% (pii).

Directivity and Frequency-Dependent Effective Sensitive Element Size of Membrane Hydrophones: Theory Versus Experiment

It is important to know hydrophone frequency-dependent effective sensitive element size in order to account for spatial averaging artifacts in acoustic output measurements. Frequency-dependent effective sensitive element size may be obtained from hydrophone directivity measurements. Directivity was measured at 1, 2, 3, 4, 6, 8, and 10 MHz from ±60° in two orthogonal planes for eight membrane hydrophones with nominal geometrical sensitive element radii ( a_g ) ranging from 100 to [Formula: see text]. The mean precision of directivity measurements (obtained from four repeated measurements at each frequency and angle) averaged over all frequencies, angles, and hydrophones was 5.8%. Frequency-dependent effective hydrophone sensitive element radii a_eff(f) were estimated by fitting the theoretical directional response for a disk receiver to directivity measurements using the sensitive element radius ( a ) as an adjustable parameter. For the eight hydrophones in aggregate, the relative difference between effective and geometrical sensitive element radii, ( a_eff - a_g)/a_g , was fit to C /( ka_g)ⁿ , where k = 2π/λ and λ = wavelength. The functional fit yielded C = 1.89 and n = 1.36 . The root mean square difference between the data and the model was 34%. It was shown that for a given value for a_g , [Formula: see text] for membrane hydrophones far exceeds that for needle hydrophones at low frequencies (e.g., < 4 MHz when [Formula: see text]). This empirical model for [Formula: see text] provides information required for the compensation of spatial averaging artifacts in acoustic output measurements and is useful for choosing an appropriate sensitive element size for a given experiment.