Kibo Nam

Quantitative Ultrasound Assessment of Cervical Microstructure

The objective of this preliminary study was to determine whether quantitative ultrasound (QUS) can provide insight into, and characterization of, uterine cervical microstructure. Throughout pregnancy, cervical collagen reorganizes (from aligned and anisotropic to disorganized and isotropic) as the cervix changes in preparation for delivery. Premature changes in collagen are associated with premature birth in mammals. Because QUS is able to detect structural anisotropy/isotropy, we hypothesized that it may provide a means of noninvasively assessing cervical microstructure. Thorough study of cervical microstructure has been limited by lack of technology to detect small changes in collagen organization, which has in turn limited our ability to detect abnormal and/or premature changes in collagen that may lead to preterm birth. In order to determine whether QUS may be useful for detection of cervical microstructure, radiofrequency (rf) echo data were acquired from the cervices of human hysterectomy specimens (n = 10). The angle between the acoustic beam and tissue was used to assess anisotropic acoustic propagation by control of transmit/receive angles from −20° to +20°. The power spectrum of the echo signals from within a region of interest was computed in order to investigate the microstructure of the tissue. An identical analysis was performed on a homogeneous phantom with spherical scatterers for system calibration. Power spectra of backscattered rf from the cervix were 6 dB higher for normal (0°) than steered (±20°) beams. The spectral power for steered beams decreased monotonically (0.4 dB at +5° to 3.6 dB at +20°). The excess difference (compared to similar analysis for the phantom) in normally-incident (0°) versus steered beams is consistent with scattering from an aligned component of the cervical microstructure. Therefore, QUS appears to reliably identify an aligned component of cervical microstructure; because collagen is ubiquitously and abundantly present in the cervix, this is the most likely candidate. Detection of changes in cervical collagen and microstructure may provide information about normal versus abnormal cervical change and thus guide development of earlier, more specific interventions for preterm birth.

Ultrasonic Attenuation and Backscatter Coefficient Estimates of Rodent-Tumor-Mimicking Structures: Comparison of Results among Clinical Scanners

In vivo estimations of the frequency-dependent acoustic attenuation (α) and backscatter (η) coefficients using radiofrequency (rf) echoes acquired with clinical ultrasound systems must be independent of the data acquisition setup and the estimation procedures. In a recent in vivo assessment of these parameters in rodent mammary tumors, overall agreement was observed among α and η estimates using data from four clinical imaging systems. In some cases, particularly in highly-attenuating heterogeneous tumors, multisystem variability was observed. This paper compares α and η estimates of a well-characterized rodent-tumor-mimicking homogeneous phantom scanned using seven transducers with the same four clinical imaging systems: a Siemens Acuson S2000, an Ultrasonix RP, a Zonare Z.one and a VisualSonics Vevo2100. α and η estimates of lesion-mimicking spheres in the phantom were independently assessed by three research groups, who analyzed their systems rf echo signals. Imaging-system-based estimates of α and η of both lesion-mimicking spheres were comparable to through-transmission laboratory estimates and to predictions using Farans theory, respectively. A few notable variations in results among the clinical systems were observed but the average and maximum percent difference between α estimates and laboratory-assessed values was 11% and 29%, respectively. Excluding a single outlier dataset, the average and maximum average difference between η estimates for the clinical systems and values predicted from scattering theory was 16% and 33%, respectively. These results were an improvement over previous interlaboratory comparisons of attenuation and backscatter estimates. Although the standardization of our estimation methodologies can be further improved, this study validates our results from previous rodent breast-tumor model studies.

Comparison of Ultrasound Attenuation and Backscatter Estimates in Layered Tissue-Mimicking Phantoms among Three Clinical Scanners

Backscatter and attenuation coefficient estimates are needed in many quantitative ultrasound strategies. In clinical applications, these parameters may not be easily obtained because of variations in scattering by tissues overlying a region of interest (ROI). The goal of this study is to assess the accuracy of backscatter and attenuation estimates for regions distal to nonuniform layers of tissue-mimicking materials. In addition, this work compares results of these estimates for “layered” phantoms scanned using different clinical ultrasound machines. Two tissue-mimicking phantoms were constructed, each exhibiting depth-dependent variations in attenuation or backscatter. The phantoms were scanned with three ultrasound imaging systems, acquiring radio frequency echo data for offline analysis. The attenuation coefficient and the backscatter coefficient (BSC) for sections of the phantoms were estimated using the reference phantom method. Properties of each layer were also measured with laboratory techniques on test samples manufactured during the construction of the phantom. Estimates of the attenuation coefficient versus frequency slope, α0, using backscatter data from the different systems agreed to within 0.24 dB/cm-MHz. Bias in the α0 estimates varied with the location of the ROI. BSC estimates for phantom sections whose locations ranged from 0 to 7 cm from the transducer agreed among the different systems and with theoretical predictions, with a mean bias error of 1.01 dB over the used bandwidths. This study demonstrates that attenuation and BSCs can be accurately estimated in layered inhomogeneous media using pulse-echo data from clinical imaging systems.

Quantitative Assessment of In Vivo Breast Masses Using Ultrasound Attenuation and Backscatter

Clinical analysis of breast ultrasound imaging is done qualitatively, facilitated with the ultrasound breast imaging–reporting and data system (US BI-RADS) lexicon, which helps to standardize imaging assessments. Two descriptors in that lexicon, “posterior acoustic features” and the “echo pattern” within a mass, are directly related to quantitative ultrasound (QUS) parameters, namely, ultrasound attenuation and the average backscatter coefficient (BSC). The purpose of this study was to quantify ultrasound attenuation and backscatter in breast masses and to investigate these QUS properties as potential differential diagnostic markers. Radio frequency (RF) echo signals were from patients with breast masses during a special ultrasound imaging session prior to core biopsy. Data were also obtained from a well characterized phantom using identical system settings. Masses include 14 fibroadenomas and 10 carcinomas. Attenuation for the acoustic path lying proximal to the tumor was estimated offline using a least squares method with constraints. BSCs were estimated using a reference phantom method (RPM). The attenuation coefficient within each mass was assessed using both the RPM and a hybrid method, and effective scatterer diameters (ESDs) were estimated using a Gaussian form factor model. Attenuation estimates obtained with the RPM were consistent with estimates done using the hybrid method in all cases except for two masses. The mean slope of the attenuation coefficient versus frequency for carcinomas was 20% greater than the mean slope value for the fibroadenomas. The product of the attenuation coefficient and anteroposterior dimension of the mass was computed to estimate the total attenuation for each mass. That value correlated well with the BI-RADS assessment of “posterior acoustic features” judged qualitatively from gray scale images. Nearly all masses were described as “hypoechoic,” so no strong statements could be made about the correlation of echo pattern findings in BI-RADS with the averaged BSC values. However, most carcinomas exhibited lower values for the frequency-average BSC than fibroadenomas. The mean ESD alone did not differentiate the mass type, but fibroadenomas had greater variability in ESDs within the ROI than that found for invasive ductal carcinomas. This study demonstrates the potential to use attenuation and QUS parameters associated with the BSC as quantitative descriptors.

Cross-imaging system comparison of backscatter coefficient estimates from a tissue-mimicking material

A key step toward implementing quantitative ultrasound techniques in a clinical setting is demonstrating that parameters such as the ultrasonic backscatter coefficient (BSC) can be accurately estimated independent of the clinical imaging system used. In previous studies, agreement in BSC estimates for well characterized phantoms was demonstrated across different laboratory systems. The goal of this study was to compare the BSC estimates of a tissue mimicking sample measured using four clinical scanners, each providing RF echo data in the 1-15 MHz frequency range. The sample was previously described and characterized with single-element transducer systems. Using a reference phantom for analysis, excellent quantitative agreement was observed across the four array-based imaging systems for BSC estimates. Additionally, the estimates from data acquired with the clinical systems agreed with theoretical predictions and with estimates from laboratory measurements using single-element transducers.

Ultrasound Attenuation Measurements Using a Reference Phantom with Sound Speed Mismatch

Ultrasonic attenuation may be measured accurately with clinical systems and array transducers by using reference phantom methods (RPM) to account for diffraction and other system dependencies on echo signals. Assumptions with the RPM are that the speeds of sound in the sample (csam ) and in the reference medium (cref ) are the same and that they match the speed assumed in the system beamformer (cbf ). This work assesses the accuracy of attenuation measurements by the RPM when these assumptions are not met. Attenuation was measured for two homogeneous phantoms, one with a speed of sound of 1500 m/s and the other with a sound speed of 1580 m/s. Both have an attenuation coefficient approximately equal to that of the reference, in which the speed of sound is 1540 m/s. Echo signals from the samples and the reference were acquired from a Siemens S2000 scanner with a 9L4 linear array transducer. Separate acquisitions were obtained with cbf at its default value of 1540 m/s and when it was set at values matching the speeds of sound of the phantoms. Simulations were also performed using conditions matching those of the experiment. RPM-measured attenuation coefficients exhibited spatially-dependent biases when csam differed from cbf and cref Mean errors of 19% were seen for simulated data, with the maximum errors in attenuation measurements occurring for regions of interest near the transmit focus. Biases were minimized (mean error with simulated data was 5.6%) using cbf that matched csam and assuring that power spectra used for attenuation computations in the sample are from precisely the same depth as those from the reference. Setting the transmit focus well beyond the depth range used to compute attenuation values minimized the bias.

Task-Oriented Comparison of Power Spectral Density Estimation Methods for Quantifying Acoustic Attenuation in Diagnostic Ultrasound Using a Reference Phantom Method

Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0fβ, was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch’s periodogram, and Thomson’s multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

Cross-imaging platform comparison of ultrasonic backscatter coefficient measurements of live rat tumors

Objective. To translate quantitative ultrasound (QUS) from the laboratory into the clinic, it is necessary to demonstrate that the measurements are platform independent. Because the backscatter coefficient (BSC) is the fundamental estimate from which additional QUS estimates are calculated, agreement between BSC results using different systems must be demonstrated. This study was an intercomparison of BSCs from in vivo spontaneous rat mammary tumors acquired by different groups using 3 clinical array systems and a single‐element laboratory scanner system. Methods. Radio frequency data spanning the 1‐ to 14‐MHz frequency range were acquired in 3 dimensions from all animals using each system. Each group processed their radio frequency data independently, and the resulting BSCs were compared. The rat tumors were diagnosed as either carcinoma or fibroadenoma. Results. Carcinoma BSC results exhibited small variations between the multiple slices acquired with each transducer, with similar slopes of BSC versus frequency for all systems. Somewhat larger variations were observed in fibroadenomas, although BSC variations between slices of the same tumor were of comparable magnitude to variations between transducers and systems. The root mean squared (RMS) errors between different transducers and imaging platforms were highly variable. The lowest RMS errors were observed for the fibroadenomas between 4 and 5 MHz, with an average RMS error of 4 × 10−5 cm−1Sr−1 and an average BSC value of 7.1 × 10−4 cm−1Sr−1, or approximately 5% error. The highest errors were observed for the carcinoma between 7 and 8 MHz, with an RMS error of 1.1 × 10−1 cm−1Sr−1 and an average BSC value of 3.5 × 10−2 cm−1Sr−1, or approximately 300% error. Conclusions. This technical advance shows the potential for QUS technology to function with different imaging platforms.

Techniques and evaluation from a cross-platform imaging comparison of quantitative ultrasound parameters in an in vivo rodent fibroadenoma model

This contribution demonstrates that quantitative ultrasound (QUS) capabilities are platform independent, using an in vivo model. Frequency-dependent attenuation estimates, backscatter coefficient, and effective scatterer diameter estimates are shown to be comparable across four different ultrasound imaging systems with varied processing techniques. The backscatter coefficient (BSC) is a fundamental material property from which several QUS parameters are estimated; therefore, consistent BSC estimates among different systems must be demonstrated. This study is an intercomparison of BSC estimates acquired by three research groups (UIUC, UW, ISU) from four in vivo spontaneous rat mammary fibroadenomas using three clinical array systems and a single-element laboratory scanner system. Because of their highly variable backscatter properties, fibroadenomas provided an extreme test case for BSC analysis, and the comparison is across systems for each tumor, not across the highly heterogeneous tumors. RF echo data spanning the 1 to 12 MHz frequency range were acquired in three dimensions from all animals using each system. Each research group processed their RF data independently, and the resulting attenuation, BSC, and effective scatterer diameter (ESD) estimates were compared. The attenuation estimates across all systems showed the same trends and consistently fit the power-law dependence on frequency. BSCs varied among the multiple slices of data acquired by each transducer, with variations between transducers being of a similar magnitude as those from slice to slice. Variation between BSC estimates was assessed via functional signal-to-noise ratios derived from backscatter data. These functional signal-to-noise ratios indicated that BSC versus frequency variations between systems ranged from negligible compared with the noise level to roughly twice the noise level. The corresponding functional analysis of variance (fANOVA) indicated statistically significant differences between BSC curves from different systems. However, root mean squared difference errors of the BSC values (in decibels) between different transducers and imaging platforms were less than half of the BSC magnitudes in most cases. Statistical comparison of the effective scatterer diameter (ESD) estimates resulted in no significant differences in estimates from three of the four transducers used for those estimates, demonstrating agreement among estimates based on the BSC. This technical advance demonstrates that these in vivo measurements can be made in a system-independent manner; the necessary step toward clinical implementation of the technology.

Quantitative Ultrasound Comparison of MAT and 4T1 Mammary Tumors in Mice and Rats Across Multiple Imaging Systems.

Quantitative ultrasound estimates such as the frequency‐dependent backscatter coefficient (BSC) have the potential to enhance noninvasive tissue characterization and to identify tumors better than traditional B‐mode imaging. Thus, investigating system independence of BSC estimates from multiple imaging platforms is important for assessing their capabilities to detect tissue differences.