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Anand KS, Torres G, Homeister JW, Caughey MC, Gallippi CM. Comparing Focused-Tracked and Plane Wave-Tracked ARFI Log(VoA) In Silico and in Application to Human Carotid Atherosclerotic Plaque, Ex Vivo. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:636-652. [PMID: 37216241 PMCID: PMC10330788 DOI: 10.1109/tuffc.2023.3278495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
A significant risk factor for ischemic stroke is carotid atherosclerotic plaque that is susceptible to rupture, with rupture potential conveyed by plaque morphology. Human carotid plaque composition and structure have been delineated noninvasively and in vivo by evaluating log(VoA), a parameter derived as the decadic log of the second time derivative of displacement induced by an acoustic radiation force impulse (ARFI). In prior work, ARFI-induced displacement was measured using conventional focused tracking; however, this requires a long data acquisition period, thereby reducing framerate. We herein evaluate if ARFI log(VoA) framerate can be increased without a reduction in plaque imaging performance using plane wave tracking instead. In silico, both focused- and plane wave-tracked log(VoA) decreased with increasing echobrightness, quantified as signal-to-noise ratio (SNR), but did not vary with material elasticity for SNRs below 40 dB. For SNRs of 40-60 dB, both focused- and plane wave-tracked log(VoA) varied with SNR and material elasticity. Above 60 dB SNR, both focused- and plane wave-tracked log(VoA) varied with material elasticity alone. This suggests that log(VoA) discriminates features according to a combination of their echobrightness and mechanical property. Further, while both focused- and plane-wave tracked log(VoA) values were artifactually inflated by mechanical reflections at inclusion boundaries, plane wave-tracked log(VoA) was more strongly impacted by off-axis scattering. Applied to three excised human cadaveric carotid plaques with spatially aligned histological validation, both log(VoA) methods detected regions of lipid, collagen, and calcium (CAL) deposits. These findings support that plane wave tracking performs comparably to focused tracking for log(VoA) imaging and that plane wave-tracked log(VoA) is a viable approach to discriminating clinically relevant atherosclerotic plaque features at a 30-fold higher framerate than by focused tracking.
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Wear KA. Spatiotemporal Deconvolution of Hydrophone Response for Linear and Nonlinear Beams-Part I: Theory, Spatial-Averaging Correction Formulas, and Criteria for Sensitive Element Size. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2022; 69:1243-1256. [PMID: 35133964 PMCID: PMC9204706 DOI: 10.1109/tuffc.2022.3150186] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
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 pc ), 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.
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Wear KA. Hydrophone Spatial Averaging Correction for Acoustic Exposure Measurements From Arrays-Part I: Theory and Impact on Diagnostic Safety Indexes. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:358-375. [PMID: 33186102 PMCID: PMC8325172 DOI: 10.1109/tuffc.2020.3037946] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
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.
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Torres G, Czernuszewicz TJ, Homeister JW, Farber MA, Caughey MC, Gallippi CM. Carotid Plaque Fibrous Cap Thickness Measurement by ARFI Variance of Acceleration: In Vivo Human Results. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:4383-4390. [PMID: 32833633 PMCID: PMC7725192 DOI: 10.1109/tmi.2020.3019184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
This study evaluates the performance of an acoustic radiation force impulse (ARFI)-based outcome parameter, the decadic logarithm of the variance of acceleration, or log(VoA), for measuring carotid fibrous cap thickness. Carotid plaque fibrous cap thickness measurement by log(VoA) was compared to that by ARFI peak displacement (PD) in patients undergoing clinically indicated carotid endarterectomy using a spatially-matched histological validation standard. Fibrous caps in parametric log(VoA) and PD images were automatically segmented using a custom clustering algorithm, and a pathologist with expertise in atherosclerosis hand-delineated fibrous caps in histology. Over 10 fibrous caps, log(VoA)-derived thickness was more strongly correlated to histological thickness than PD-derived thickness, with Pearson correlation values of 0.98 for log(VoA) compared to 0.89 for PD. The log(VoA)-derived cap thickness also had better agreement with histology-measured thickness, as assessed by the concordance correlation coefficient (0.95 versus 0.62), and, by Bland-Altman analysis, was more consistent than PD-derived fibrous cap thickness. These results suggest that ARFI log(VoA) enables improved discrimination of fibrous cap thickness relative to ARFI PD and further contributes to the growing body of evidence demonstrating ARFI's overall relevance to delineating the structure and composition of carotid atherosclerotic plaque for stroke risk prediction.
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Torres G, Czernuszewicz TJ, Homeister JW, Caughey MC, Huang BY, Lee ER, Zamora CA, Farber MA, Marston WA, Huang DY, Nichols TC, Gallippi CM. Delineation of Human Carotid Plaque Features In Vivo by Exploiting Displacement Variance. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2019; 66:481-492. [PMID: 30762544 PMCID: PMC7952026 DOI: 10.1109/tuffc.2019.2898628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
While in vivo acoustic radiation force impulse (ARFI)-induced peak displacement (PD) has been demonstrated to have high sensitivity and specificity for differentiating soft from stiff plaque components in patients with carotid plaque, the parameter exhibits poorer performance for distinguishing between plaque features with similar stiffness. To improve discrimination of carotid plaque features relative to PD, we hypothesize that signal correlation and signal-to-noise ratio (SNR) can be combined, outright or via displacement variance. Plaque feature detection by displacement variance, evaluated as the decadic logarithm of the variance of acceleration and termed "log(VoA)," was compared to that achieved by exploiting SNR, cross correlation coefficient, and ARFI-induced PD outcome metrics. Parametric images were rendered for 25 patients undergoing carotid endarterectomy, with spatially matched histology confirming plaque composition and structure. On average, across all plaques, log(VoA) was the only outcome metric with values that statistically differed between regions of lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), collagen (COL), and calcium (CAL). Further, log(VoA) achieved the highest contrast-to-noise ratio (CNR) for discriminating between LRNC and IPH, COL and CAL, and grouped soft (LRNC and IPH) and stiff (COL and CAL) plaque components. More specifically, relative to the previously demonstrated ARFI PD parameter, log(VoA) achieved 73% higher CNR between LRNC and IPH and 59% higher CNR between COL and CAL. These results suggest that log(VoA) enhances the differentiation of LRNC, IPH, COL, and CAL in human carotid plaques, in vivo, which is clinically relevant to improving stroke risk prediction and medical management.
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Czernuszewicz TJ, Homeister JW, Caughey MC, Wang Y, Zhu H, Huang BY, Lee ER, Zamora CA, Farber MA, Fulton JJ, Ford PF, Marston WA, Vallabhaneni R, Nichols TC, Gallippi CM. Performance of acoustic radiation force impulse ultrasound imaging for carotid plaque characterization with histologic validation. J Vasc Surg 2017; 66:1749-1757.e3. [PMID: 28711401 DOI: 10.1016/j.jvs.2017.04.043] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2017] [Accepted: 04/18/2017] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Stroke is commonly caused by thromboembolic events originating from ruptured carotid plaque with vulnerable composition. This study assessed the performance of acoustic radiation force impulse (ARFI) imaging, a noninvasive ultrasound elasticity imaging method, for delineating the composition of human carotid plaque in vivo with histologic validation. METHODS Carotid ARFI images were captured before surgery in 25 patients undergoing clinically indicated carotid endarterectomy. The surgical specimens were histologically processed with sectioning matched to the ultrasound imaging plane. Three radiologists, blinded to histology, evaluated parametric images of ARFI-induced peak displacement to identify plaque features such as necrotic core (NC), intraplaque hemorrhage (IPH), collagen (COL), calcium (CAL), and fibrous cap (FC) thickness. Reader performance was measured against the histologic standard using receiver operating characteristic curve analysis, linear regression, Spearman correlation (ρ), and Bland-Altman analysis. RESULTS ARFI peak displacement was two-to-four-times larger in regions of NC and IPH relative to regions of COL or CAL. Readers detected soft plaque features (NC/IPH) with a median area under the curve of 0.887 (range, 0.867-0.924) and stiff plaque features (COL/CAL) with median area under the curve of 0.859 (range, 0.771-0.929). FC thickness measurements of two of the three readers correlated with histology (reader 1: R2 = 0.64, ρ = 0.81; reader 2: R2 = 0.89, ρ = 0.75). CONCLUSIONS This study suggests that ARFI is capable of distinguishing soft from stiff atherosclerotic plaque components and delineating FC thickness.
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Affiliation(s)
- Tomasz J Czernuszewicz
- Joint Department of Biomedical Engineering, The University of North Carolina, Chapel Hill, and North Carolina State University, Raleigh, NC
| | - Jonathon W Homeister
- Department of Pathology and Laboratory Medicine, The University of North Carolina, Chapel Hill, NC
| | - Melissa C Caughey
- Department of Medicine, The University of North Carolina, Chapel Hill, NC
| | - Yue Wang
- Department of Biostatistics, The University of North Carolina, Chapel Hill, NC
| | - Hongtu Zhu
- Department of Biostatistics, The University of North Carolina, Chapel Hill, NC
| | - Benjamin Y Huang
- Department of Radiology, The University of North Carolina, Chapel Hill, NC
| | - Ellie R Lee
- Department of Radiology, The University of North Carolina, Chapel Hill, NC
| | - Carlos A Zamora
- Department of Radiology, The University of North Carolina, Chapel Hill, NC
| | - Mark A Farber
- Department of Surgery, The University of North Carolina, Chapel Hill, NC
| | - Joseph J Fulton
- Department of Surgery, The University of North Carolina, Chapel Hill, NC
| | - Peter F Ford
- Department of Surgery, The University of North Carolina, Chapel Hill, NC
| | - William A Marston
- Department of Surgery, The University of North Carolina, Chapel Hill, NC
| | | | - Timothy C Nichols
- Department of Pathology and Laboratory Medicine, The University of North Carolina, Chapel Hill, NC; Department of Medicine, The University of North Carolina, Chapel Hill, NC
| | - Caterina M Gallippi
- Joint Department of Biomedical Engineering, The University of North Carolina, Chapel Hill, and North Carolina State University, Raleigh, NC; Department of Radiology, The University of North Carolina, Chapel Hill, NC; Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC.
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Nguyen MM, Ding X, Leers SA, Kim K. Multi-Focus Beamforming for Thermal Strain Imaging Using a Single Ultrasound Linear Array Transducer. ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:1263-1274. [PMID: 28318887 PMCID: PMC5429981 DOI: 10.1016/j.ultrasmedbio.2017.01.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Revised: 01/20/2017] [Accepted: 01/23/2017] [Indexed: 06/06/2023]
Abstract
Ultrasound-induced thermal strain imaging (TSI) has been used successfully to identify lipid- and water-based tissues in atherosclerotic plaques in some research settings. However, TSI faces several challenges to be realized in clinics. These challenges include motion artifacts and displacement tracking accuracy, as well as limited heating capability, which contributes to low thermal strain signal-to-noise ratio, and a limited field of view. Our goal was to address the challenge in heating tissue in TSI. Current TSI systems use separate heating and imaging transducers, which require physical alignment of the heating and imaging beams and result in a bulky setup that limits in vivo operation. We evaluated a new design for heating beams that can be implemented on a linear array imaging transducer and can provide improved heating area and efficiency as compared with previous implementations. The heating beams designed were implemented with a clinical linear array imaging transducer connected to a research ultrasound platform. In vitro experiments using tissue-mimicking phantoms with no blood flow revealed that the new design resulted in an effective heating area of approximately 0.85 cm2 and a 0.3°C temperature rise in 2 s of heating, which compared well with in silico finite-element simulations. With the new heating beams, TSI was found to be able to detect a lipid-mimicking rubber inclusion with a diameter of 1 cm from the water-based gelatin background, with a strain contrast of 2.3 (+0.14% strain in the rubber inclusion and -0.06% strain in the gelatin background). Lastly, lipid-based tissue in a 1-cm-diameter human carotid endarterectomy (CEA) sample was identified in good agreement with histology.
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Affiliation(s)
- Man M Nguyen
- Center for Ultrasound Molecular Imaging and Therapeutics, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, USA
| | - Xuan Ding
- Center for Ultrasound Molecular Imaging and Therapeutics, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Medical Scientist Training Program, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Steven A Leers
- Heart and Vascular Institute, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, Pennsylvania, USA
| | - Kang Kim
- Center for Ultrasound Molecular Imaging and Therapeutics, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Heart and Vascular Institute, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, Pennsylvania, USA; McGowan Institute of Regenerative Medicine, University of Pittsburgh and UPMC, Pittsburgh, Pennsylvania, USA.
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de Korte CL, Fekkes S, Nederveen AJ, Manniesing R, Hansen HRHG. Review: Mechanical Characterization of Carotid Arteries and Atherosclerotic Plaques. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2016; 63:1613-1623. [PMID: 27249826 DOI: 10.1109/tuffc.2016.2572260] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Cardiovascular disease (CVD) is a leading cause of death and is in the majority of cases due to the formation of atherosclerotic plaques in arteries. Initially, thickening of the inner layer of the arterial wall occurs. Continuation of this process leads to plaque formation. The risk of a plaque to rupture and thus to induce an ischemic event is directly related to its composition. Consequently, characterization of the plaque composition and its proneness to rupture are of crucial importance for risk assessment and treatment strategies. The carotid is an excellent artery to be imaged with ultrasound because of its superficial position. In this review, ultrasound-based methods for characterizing the mechanical properties of the carotid wall and atherosclerotic plaque are discussed. Using conventional echography, the intima media thickness (IMT) can be quantified. There is a wealth of studies describing the relation between IMT and the risk for myocardial infarction and stroke. Also the carotid distensibility can be quantified with ultrasound, providing a surrogate marker for the cross-sectional mechanical properties. Although all these parameters are associated with CVD, they do not easily translate to individual patient risk. Another technique is pulse wave velocity (PWV) assessment, which measures the propagation of the pressure pulse over the arterial bed. PWV has proven to be a marker for global arterial stiffness. Recently, an ultrasound-based method to estimate the local PWV has been introduced, but the clinical effectiveness still needs to be established. Other techniques focus on characterization of plaques. With ultrasound elastography, the strain in the plaque due to the pulsatile pressure can be quantified. This technique was initially developed using intravascular catheters to image coronaries, but recently noninvasive methods were successfully developed. A high correlation between the measured strain and the risk for rupture was established. Acoustic radiation force impulse (ARFI) imaging also provides characterization of local plaque components based on mechanical properties. However, both elastography and ARFI provide an indirect measure of the elastic modulus of tissue. With shear wave imaging, the elastic modulus can be quantified, although the carotid artery is one of the most challenging tissues for this technique due to its size and geometry. Prospective studies still have to establish the predictive value of these techniques for the individual patient. Validation of ultrasound-based mechanical characterization of arteries and plaques remains challenging. Magnetic resonance imaging is often used as the "gold" standard for plaque characterization, but its limited resolution renders only global characterization of the plaque. CT provides information on the vascular tree, the degree of stenosis, and the presence of calcified plaque, while soft plaque characterization remains limited. Histology still is the gold standard, but is available only if tissue is excised. In conclusion, elastographic ultrasound techniques are well suited to characterize the different stages of vascular disease.
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