Quantitative Ultrasound Parameters Research Articles

Development and Validation of the Placenta-QUS Model for the Detection of Placenta-mediated Diseases using Quantitative Ultrasound Measurements: An Ex Vivo Proof-of-concept Study

IntroductionPlacenta-mediated diseases are associated with structural changes in the placenta. Quantitative Ultrasound (QUS) imaging measures the acoustic properties of the tissue, which are correlated to the underlying tissue structure. We aimed to develop and validate a diagnostic prediction model using QUS measurements for pre-eclampsia (PE) and small-for-gestational-age (SGA) fetuses/neonates. MethodsFor this prospective case-control study, placentas were collected from a group of women who delivered via cesarean section at BC Women's Hospital, Vancouver, Canada. Ultrasound data were collected and processed to compute three QUS parameters, namely, attenuation coefficient estimate (ACE), integrated backscatter coefficient (IBC), and effective scatterer diameter (ESD) from the placentas. We developed a logistic regression model using QUS parameters as predictors. The primary outcome was the occurrence of SGA and PE. ResultsThe dataset consisted of 47 placentas, of which 25 placentas were complicated by SGA/PE. The final placenta-QUS model included quadratic and interaction terms of ACE, IBC, and ESD parameters. The placenta-QUS model was well-calibrated, with a calibration slope of 0.99 (0.57 – 1.05) and a calibration intercept of 0.003 (-0.02 − 0.22). The model predicted the SGA/PE complicated pregnancies with an apparent Area Under the Receive Operating Characteristic Curve (AUROC) of 0.89 (95% CI: 0.78-0.98). The optimism-adjusted AUROC was 0.88 (95% CI: 0.78-0.98). DiscussionA model for SGA and PE has been developed using QUS measures from the placenta ex vivo. The model showed promising performance in detecting SGA/PE. Future studies will be performed to assess the model performance using QUS measures in utero.

Reproducibility of ultrasound-derived fat fraction in measuring hepatic steatosis

PurposeSteatotic liver disease (SLD) has become the most common cause of chronic liver disease. Nevertheless, the non-invasive quantitative diagnosis of steatosis is still lacking in clinical practice. This study aimed to evaluate the reproducibility of the new parameter for steatosis quantification named ultrasound-derived fat fraction (UDFF).Materials and methodsThe UDFF values were independently executed by two operators in two periods. In the process, repeated measurements of the same patient were performed by the same operator under different conditions (liver segments, respiration, positions, and dietary). Finally, the results of some subjects (28) were compared with the MRI-derived proton density fat fraction (PDFF). The concordance analysis was mainly achieved by the intraclass correlation coefficient (ICC) and Bland–Altman.ResultsOne hundred-five participants were included in the study. UDFF had good reliability in measuring the adult liver (ICCintra-observer = 0.96, ICCinter-observer = 0.94). Meanwhile, the ICC of the two operators increased over time. The variable measurement states did not influence the UDFF values on the surface, but they affected the coefficient of variation (Cov) of the results. Segment 8 (S8), end-expiratory, supine, and fasting images had the most minor variability. On the other hand, the UDFF value of S8 displayed satisfied consistency with PDFF (mean difference, −0.24 ± 1.44), and the results of both S5 (mean difference: −0.56 ± 3.95) and S8 (mean difference: 0.73 ± 1.87) agreed well with the whole-liver PDFF.ConclusionUDFF measurements had good reproducibility. Furthermore, the state of S8, end-expiration, supine, and fasting might be the more stable measurement approach.Critical relevance statementUDFF is the quantitative ultrasound parameter of hepatic steatosis and has good reproducibility. It can show more robust performance under specific measurement conditions (S8, end-expiratory, supine, and fasting).Trial registrationThe research protocol was registered at the Chinese Clinical Trial Registry on October 9, 2023 (http://www.chictr.org.cn/). The registration number is ChiCTR 2300076457.Key PointsThere is a lack of non-invasive quantitative measurement options for hepatic steatosis.UDFF demonstrated excellent reproducibility in measuring hepatic steatosis.S8, end-expiratory, supine, and fasting may be the more stable measuring condition.Training could improve the operators’ measurement stability.Variable measurement state affects the repeatability of the UDFF values (Cov).Graphical

Prospective comparative diagnostic performance of quantitative ultrasound parameters for the measurement of hepatic steatosis in a biopsy-proven MASLD cohort.

The aim of this study was to compare the diagnostic performance of attenuation imaging (ATI), shear wave elastography (SWE) and shear wave dispersion (SWD) for detecting and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). 66 patients with MASLD (mean age, 41 years ± 12; 36 men, 30 women) confirmed histopathologically and 34 healthy volunteers (mean age, 39 years ± 15; 18 men, 16 women) who were age/sex-matched were prospectively enrolled in this study. ATI, SWE and SWD examinations were performed. Fibrosis stage, necroinflammatory activity and steatosis grade were confirmed histopathologically. Steatosis was graded as follows: S0 (<5%); S1 (5-32%); S2 (33-66%) to S3 (>66%). We compared the diagnostic performance of ATI, SWE and SWD for detecting and grading hepatic steatosis. Both attenuation coefficient (AC) and SWD values were significantly different among the different hepatic steatosis, and both were correlated with hepatic steatosis. SWE could not distinguish hepatic steatosis. ATI had better diagnostic performance than SWD for detecting and grading hepatic steatosis. The area under the receiver operating characteristic (ROC) curve of ATI for detecting ≥ S1, ≥ S2, and = S3 were 0.917 (cut-off value of 0.69 dB/cm/MHz), 0.933 (cut-off value of 0.74 dB/cm/MHz), and 0.870 (cut-off value of 0.82 dB/cm/MHz), respectively. The area under the ROC curve of SWD value was 0.758 (cut-off value of 10.79 m/s/kHz), 0.685 (cut-off value of 12.64 m/s/kHz), and 0.722 (cut-off value of 13.24 m/s/kHz), respectively. ATI technology is a reliable method for detecting and grading hepatic steatosis in patients with MASLD than SWE and SWD. We compared the diagnostic performance of ATI, SWE, SWD for detecting and grading hepatic steatosis in patients with MASLD in order to find the best diagnostic parameters.

Comparing the efficacy of multiple quantitative and qualitative ultrasound parameters for the diagnosis of carpal tunnel syndrome.

Carpal tunnel syndrome (CTS) is a compression neuropathy causing significant morbidity. Over the years, ultrasound has been evaluated as an alternative to nerve conduction study (NCS) for diagnosing CTS, however, there is no consensus as to which ultrasound parameter is the best. Our study aimed to determine and compare the efficacy of various ultrasound-based variables for diagnosis of CTS. 80 patients with clinical suspicion of CTS underwent ultrasound examination with calculation of cross-sectional area (CSA), delta CSA, wrist forearm ratio (WFR), palmer bowing (PB), flattening ratio (FR), flexor retinaculum thickness (FT), and evaluation of echogenicity and vascularity of median nerve. NCS was taken as the gold standard and the diagnostic efficacy of all these variables was compared, followed by receiver operator curve (ROC) analysis. Delta CSA had the highest accuracy (91.25%), followed by CSAc (80%), WFR (78.75%), and PB (73.75%). Youden's index and sensitivity were highest for delta CSA (0.783 and 96.15% respectively), while specificity was highest for FT (89.29%). The highest area under the curve was noted for delta CSA (97.1%), followed by WFR (AUC = 87.4%) and CSAc (AUC = 86.0%). Delta CSA was found to be the best ultrasound parameter for diagnosis of CTS, followed by CSAc, WFR, and PB, and can be used as an alternative to NCS. Using ROC analysis this study also predicted the best cut-off values for these parameters which could improve their diagnostic accuracy and further research is needed to confirm these findings.

Influences of Variability in Attenuation Compensation on the Estimation of Backscatter Coefficient of Median Nerves in Vivo.

Peripheral nerves remain a challenging target for medical imaging, given their size, anatomical complexity, and structural heterogeneity. Quantitative ultrasound (QUS) applies a set of techniques to estimate tissue acoustic parameters independent of the imaging platform. Many useful medical and laboratory applications for QUS have been reported, but challenges remain for deployment in vivo, especially for heterogeneous tissues. Several phenomena introduce variability in attenuation estimates, which may influence the estimation of other QUS parameters. For example, estimating the backscatter coefficient (BSC) requires compensation for the attenuation of overlying tissues between the transducer and the underlying tissue of interest. The purpose of this study is to extend prior studies by investigating the efficacy of several analytical methods of estimating attenuation compensation on QUS outcomes in the human median nerve. Median nerves were imaged at the volar wrist in vivo and beam-formed radiofrequency (RF) data were acquired. Six analytical approaches for attenuation compensation were compared: 1-2) attenuation estimated by applying spectral difference method (SDM) and spectral log difference method (SLDM) independently to regions of interest (ROIs) overlying the nerve and to the nerve ROI itself; 3-4) attenuation estimation by applying SDM and SLDM to ROIs overlying the nerve, and transferring these properties to the nerve ROI; and 5-6) methods that apply previously published values of tissue attenuation to the measured thickness of each overlying tissue. Mean between-subject estimates of BSC-related outcomes as well as within-subject variability of these outcomes were compared among the 6 methods. Compensating for attenuation using SLDM and values from the literature reduced variability in BSC-based outcomes, compared to SDM. Variability in attenuation coefficients contributes substantially to variability in backscatter measurements. This work has implications for the application of QUS to in vivo diagnostic assessments in peripheral nerves and possibly other heterogeneous tissues.

Quantitative ultrasound for steatosis assessment using Hepatoscope®: Confounding technical factors

Quantitative ultrasound (QUS) is a well-suited modality to address large-scale screening and monitoring of liver steatosis as it is low-cost, non-invasive, and point-of-care. However, technical and biological confounders lead to difficulties in establishing universal cutoff values for diagnosis. Hepatoscope® remedies this issue as it integrates a unique QUS measurement technique enabling the simultaneous measurements of the backscattering coefficient, the attenuation coefficient and the speed of sound. Such measurements are performed in a large two-dimensional region of interest (ROI) and in a free breathing regime such that a relatively large portion of the liver is sampled. We studied the influence of the size of the ROI, its depth and the number of measurements on the QUS parameters with Hepatoscope® both in vitro on four calibrated phantoms and clinically on 60 participants referred to a hepatology consultation for chronic liver disease. We demonstrated that using large ROIs consistently improves the system reliability and the clinical applicability. We did not observe any systematic effect related to the depth of the ROI. We also showed that averaging consecutive measurements leads to better system reliability and better clinical applicability.

Clinical value of multiparameteric quantitative ultrasound for assessing high-risk steatohepatitis

Objective: To investigate the clinical value of multiparameteric quantitative ultrasound combined with a non-invasive prediction model for assessing high-risk steatohepatitis. Methods: One hundred and ninety-four cases with metabolic-associated fatty liver disease (MAFLD) who underwent liver biopsy in Huashan Hospital, Fudan University, from June 2021 to September 2022 were selected. Shear wave elastography (SWE), shear wave dispersion (SWD) imaging, and attenuation imaging (ATI) examinations were conducted in all patients before biopsy. High-risk steatohepatitis was defined as a total activity score of ≥4 in patients with steatohepatitis, hepatocellular ballooning, and liver lobular inflammation based on pathological hepatic steatosis, inflammatory activity, and fibrosis scoring system (SAF), and fibrosis stage≥F2. Binary logistic regression analysis was used to identify the factors influencing high-risk steatohepatitis. A predictive model for diagnosing high-risk steatohepatitis was constructed using R language. The DeLong test was used to compare the area under the curve between groups. Measurement data was compared between groups using the t-test or rank-sum test, and count data were compared between groups using the χ2 test. Results: There were 46 cases (23.7%) with high-risk steatohepatitis. The quantitative ultrasound parameters included elastic modulus (OR=2.958, 95%CI: 1.889-4.883, P<0.001), dispersion coefficient (OR=1.786, 95%CI: 1.424-2.292, P<0.001) and attenuation coefficient (OR=42.642, 95%CI: 3.463-640.451, P=0.004). Serological indexes of fasting blood glucose (OR=1.196, 95%CI: 1.048-1.392, P=0.011), alanine aminotransferase (OR=1.012, 95%CI: 1.006-1.019, P<0.001), aspartate aminotransferase (OR=1.027, 95%CI: 1.014-1.042, P<0.001), γ-glutamyl transferase (OR=1.008, 95%CI: 1.001-1.017, P=0.041) and HDL cholesterol (OR=0.087, 95%CI: 0.016-0.404, P=0.003) were the factors influencing its progression. The AUCs of elastic modulus, dispersion coefficient, attenuation coefficient, multiparametric ultrasound model, serological index model, and ultrasound combined with serology model for the diagnosis of high-risk steatohepatitis were 0.764, 0.758, 0.634, 0.786, 0.773 and 0.825, respectively. The results of the DeLong test showed that the ultrasound combined with the serological model was significantly better than the serological index model and the elastic modulus, dispersion coefficient, and attenuation coefficient alone (P=0.024, 0.027, 0.038 and <0.001). Conclusion: The combination of multiparametric quantitative ultrasound is helpful for the non-invasive diagnosis of high-risk steatohepatitis and possesses great clinical significance.

Handrim kinetics and quantitative ultrasound parameters for assessment of subacromial impingement in wheelchair users with pediatric-onset spinal cord injury

BackgroundMost manual wheelchair users with pediatric-onset spinal cord injury (SCI) will experience shoulder pain or pathology at some point in their life. However, guidelines for preservation of the upper limb in children with SCI are limited. Research questionWhat are the relationships between manual wheelchair handrim kinetics and quantitative ultrasound parameters related to subacromial impingement in individuals with pediatric-onset SCI? MethodsSubacromial impingement risk factors including supraspinatus tendon thickness (SST), acromiohumeral distance (AHD), and occupation ratio (OR; SST/AHD) were measured with ultrasound in 11 manual wheelchair users with pediatric-onset SCI. Handrim kinetics were acquired during the stroke cycle, including peak resultant force (FR), peak rate of rise of resultant force (ROR) and fractional effective force (FEF). Variability of handrim kinetics was computed using the coefficient of variation and linear regression was performed to assess correlations between handrim metrics and quantitative ultrasound parameters. ResultsPeak resultant force significantly increased 1.4 % and variability of FEF significantly decreased 8.0 % for every 0.1 cm increase in AHD. FEF decreased 3.5 % for every 0.1 cm increase in SST. Variability of peak resultant force significantly increased 3.6 % and variability of peak ROR of resultant force significantly increased 7.3 % for every 0.1 cm increase in SST. FEF variability significantly decreased 11.6 % for every 0.1 cm increase in SST. Peak ROR significantly decreased 1.54 % with every 10 % increase in OR. FEF variability significantly decreased 1.5 % with every 10 % increase in OR. SignificanceThis is the first study to investigate relationships among handrim kinetics and shoulder structure in manual wheelchair users with pediatric-onset SCI. Associations were identified between subacromial impingement risk factors and magnitude and variability of wheelchair handrim kinetics. These results indicate the critical need to further explore the relationships among wheelchair handrim kinetics, shoulder joint dynamics, and shoulder pathology in manual wheelchair users with pediatric-onset SCI.

Ultrasound normalized cumulative residual entropy imaging: Theory, methodology, and application

Background and Objective:Ultrasound information entropy imaging is an emerging quantitative ultrasound technique for characterizing local tissue scatterer concentrations and arrangements. However, the commonly used ultrasound Shannon entropy imaging based on histogram-derived discrete probability estimation suffers from the drawbacks of histogram settings dependence and unknown estimator performance. In this paper, we introduced the information-theoretic cumulative residual entropy (CRE) defined in a continuous distribution of cumulative distribution functions as a new entropy measure of ultrasound backscatter envelope uncertainty or complexity, and proposed ultrasound CRE imaging for tissue characterization. Methods:We theoretically analyzed the CRE for Rayleigh and Nakagami distributions and proposed a normalized CRE for characterizing scatterer distribution patterns. We proposed a method based on an empirical cumulative distribution function estimator and a trapezoidal numerical integration for estimating the normalized CRE from ultrasound backscatter envelope signals. We presented an ultrasound normalized CRE imaging scheme based on the normalized CRE estimator and the parallel computation technique. We also conducted theoretical analysis of the differential entropy which is an extension of the Shannon entropy to a continuous distribution, and introduced a method for ultrasound differential entropy estimation and imaging. Monte-Carlo simulation experiments were performed to evaluate the estimation accuracy of the normalized CRE and differential entropy estimators. Phantom simulation and clinical experiments were conducted to evaluate the performance of the proposed normalized CRE imaging in characterizing scatterer concentrations and hepatic steatosis (n = 204), respectively. Results:The theoretical normalized CRE for the Rayleigh distribution was π/4, corresponding to the case where there were ≥10 randomly distributed scatterers within the resolution cell of an ultrasound transducer. The theoretical normalized CRE for the Nakagami distribution decreased as the Nakagami parameter m increased, corresponding to that the ultrasound backscattered statistics varied from pre-Rayleigh to Rayleigh and to post-Rayleigh distributions. Monte-Carlo simulation experiments showed that the proposed normalized CRE and differential entropy estimators can produce a satisfying estimation accuracy even when the size of the test samples is small. Phantom simulation experiments showed that the proposed normalized CRE and differential entropy imaging can characterize scatterer concentrations. Clinical experiments showed that the proposed ultrasound normalized CRE imaging is capable to quantitatively characterize hepatic steatosis, outperforming ultrasound differential entropy imaging and being comparable to ultrasound Shannon entropy and Nakagami imaging. Conclusion:This study sheds light on the theory and methodology of ultrasound normalized CRE. The proposed ultrasound normalized CRE can serve as a new, flexible quantitative ultrasound envelope statistics parameter. The proposed ultrasound normalized CRE imaging may find applications in quantified characterization of biological tissues. Our code will be made available publicly at https://github.com/zhouzhuhuang.

Methods and validation of velacur determined fat fraction in patients with MASLD

IntroductionAs prevalence of patients with steatotic liver diseases increases throughout the world, it is necessary to have accurate and accessible methods to estimate liver fat content. Using quantitative ultrasound parameters, such as attenuation and backscatter, it is possible to estimate liver fat with MRI proton density fat fraction as the reference standard. Velacur determined fat fraction (VDFF) is a new output measurement on Velacur (Sonic Incytes Medical Corp, Vancouver, BC). MethodsThis study described the results of parameter fitting and validation of VDFF, which is a combination of quantitative ultrasound parameters. Patients were recruited from sites within the US and Canada. All patients had contemporaneous Velacur and MRI proton density fat fraction scans. The quantitative ultrasound parameter fitting was completed using linear regression on a random sub-sample approach, and a separate cohort was used for validation. The AUC for detection of 5 % liver fat based on MRI-PDFF and the correlation between MRI-PDFF and VDFF was measured in both cohorts. ResultsVDFF had an AUROC of 0.97 for the detection of MRI-PDFF >5 % in the parameter fitting cohort, and 0.99 in the validation cohort. The correlation [95 % CI] between MRI-PDFF and VDFF was r = 0.84 [0.78–0.89] for the parameter fitting cohort and r = 0.90 [0.82–0.95] for the validation cohort. ConclusionThe Velacur Determined Fat Fraction (VDFF) is an accurate and accessible way to estimate steatosis as measured by MRI-PDFF. Velacur VDFF can fill the unmet need of an accurate means to diagnosis hepatic steatosis and serve as a potential alternative to biopsy or MRI-PDFF.

Lung quantitative ultrasound to stage and monitor interstitial lung diseases

Chronic interstitial lung diseases (ILDs) require frequent point-of-care monitoring. X-ray-based methods lack resolution and are ionizing. Chest computerized tomographic (CT) scans are expensive and provide more radiation. Conventional ultrasound can detect severe lung damage via vertical artifacts (B-lines). However, this information is not quantitative, and the appearance of B-lines is operator- and system-dependent. Here we demonstrate novel ultrasound-based biomarkers to assess severity of ILDs. Lung alveoli scatter ultrasound waves, leading to a complex acoustic signature, which is affected by changes in alveolar density due to ILDs. We exploit ultrasound scattering in the lung and combine quantitative ultrasound (QUS) parameters, to develop ultrasound-based biomarkers that significantly correlate (p = 1e−4 for edema and p = 3e−7 for fibrosis) to the severity of pulmonary fibrosis and edema in rodent lungs. These innovative QUS biomarkers will be very significant for monitoring severity of chronic ILDs and response to treatment, especially in this new era of miniaturized and highly portable ultrasound devices.

In-vivo high-frequency quantitative ultrasound-derived parameters of the anterior sclera correlated with level of myopia and presence of staphyloma.

A high-frequency point-of-care (POC) ultrasound instrument was used to evaluate the microstructural and biomechanical properties of the anterior sclera in vivo using parameters computed from quantitative ultrasound (QUS) methods. In this cross-sectional study, both eyes of 85 enrolled patients were scanned with the POC instrument and ultrasound data were processed to obtain QUS parameters. Pearson correlation and multi-linear regression were used to identify relationships between QUS parameters and refractive error (RE) or axial length. After categorising eyes based on RE, binary support vector machine (SVM) classifiers were trained using the QUS or ophthalmic parameters (anterior chamber depth, central corneal thickness, corneal power, and intraocular pressure) to classify each eye. Classifier performance was evaluated by computing the area under the receiver-operating characteristic curve (AUC). Individual QUS parameters correlated with RE and axial length (p < 0.05). Multi-linear regression revealed significant correlation between the set of QUS parameters and both RE (R = 0.49, p < 0.001) and axial length (R = 0.46, p = 0.001). Classifiers trained with QUS parameters achieved higher AUC (𝑝 = 0.06) for identifying myopic eyes (AUC = 0.71) compared to classifiers trained with ophthalmic parameters (AUC = 0.63). QUS-based classifiers attained the highest AUC when identifying highly myopic eyes (AUC = 0.77). QUS parameters correlate with progressing myopia and may be indicative of myopia-induced microstructural and biomechanical changes in the anterior sclera. These methods may provide critical clinical information complementary to standard ophthalmic measurements for predicting myopia progression and risk assessment for posterior staphyloma formation.

A magnetic phantom technique for investigating structural effects on quantitative ultrasound parameters.

Media that contain ultrasound scatterers arranged in a regular spatial distribution can be considered as structured. Structural effects affect quantitative ultrasound parameters that reflect the microstructure properties. Prior studies examined structural effects using simulations or phantoms with fixed microarchitecture, focusing on a limited set of ultrasound parameters, with limited attention given to their underlying physical significance. This study aims to investigate the concordance of the physical interpretations of multiple quantitative ultrasound parameters experimentally by introducing a phantom type with an adjustable microarchitecture. The phantom consists of an aqueous solution containing superparamagnetic microspheres, acting as scatterers. The spatial arrangement of the magnetic particles is modified by applying an external magnetic field, therefore changing the degree of structure of the phantom. Quantitative ultrasound parameters are estimated in three different configurations: the magnetic field intensity is varied over time, strength, and orientation. In each experiment, the backscatter coefficient and the envelope quantitative ultrasound parameters are successfully extracted (R2 ≈ 0.94). Their physical interpretations are supported by microphotographs and geometrical considerations through concordant hypotheses. This study paves the way for the use of magnetic phantoms. This methodology could be followed to validate theoretical scattering models and the physical meanings of quantitative ultrasound parameters.

Contrast-enhanced ultrasound features as a potential biomarker for the prediction of breast cancer recurrence.

To investigate the associations between contrast-enhanced ultrasound imaging features and disease recurrence among patients with locally advanced breast cancer treated with neoadjuvant chemotherapy. In the study, pre- and post-neoadjuvant chemotherapy contrast-enhanced ultrasound images of 43 patients with breast cancer were retrospectively analysed. Post-acquisition image processing involved the placement of freehand-drawn regions of interest, followed by the generation of blood flow kinetics representing blood volume and velocity for these regions of interest. Qualitative and quantitative contrast-enhanced ultrasound parameters were compared to predict recurrence, and receiver operating characteristic analysis was used to evaluate predictive ability. Among the 43 patients, 10 (23%) exhibited disease recurrence (median [range]: 27 [4-68] months). Post-neoadjuvant chemotherapy peak enhancement, wash-in area under the curve, wash-out area under the curve, and wash-in and wash-out area under the curve (p=0.003, p=0.004, p=0.026, and p=0.014, respectively) differed between the no-recurrence and recurrence groups. The area under the receiver operating characteristic curve (0.88; 95% confidence interval: 0.75-1.00) for post-neoadjuvant chemotherapy peak enhancement was the highest among the contrast-enhanced ultrasound parameters, with a cut-off of 13.33 arbitrary units. Higher peak enhancement on post-neoadjuvant chemotherapy contrast-enhanced ultrasound images was associated with recurrence in women with locally advanced breast cancer and is a potential biomarker of tumor recurrence.

The influence of cortical end plate upon ultrasound transit time spectroscopy estimated bone assessment

Quantitative ultrasound (QUS) is considered a reliable tool for routine assessment of bone. However, none of the QUS parameters has a direct measure of bone quantity or quality. The concept of ultrasound transit time spectroscopy (UTTS) has recently offered the possibility of effective estimates of bone volume fraction (BVF) as an indicator of bone density. This study aimed to investigate the influence of cortical end plate thickness around the cancellous bone on the measurement accuracy of UTTS solid volume fraction (UTTS-SVF). Two categories of cortical discs were designed and three-dimensional printed; category (I) is planer discs of constant different thickness and category (II) is variable-thickness step-wedge discs. In this experimental and simulated study, the discs were placed coaxially with the 3D-printed cylindrical iliac crest cancellous bone sample. A through-transmission 1 MHz ultrasound pulses were recorded, from which the deconvoluted TTS were derived. Then UTTS-SVF was determined and compared with the measured SVF via microcomputed tomography (μCT-SVF) showing a high agreement with an average of 94% ± 3.7% and 95% ± 4% for the planar cortical discs and 95.3% ± 5.5% and 96.5% ± 3.7% for variable-thickness step-wedge cortical discs for experiment and simulation respectively. The variations between the derived UTTS_SVF and the standard μCT-SVF are assumed to be due to the existence of phase interference within the cortical discs. Hence, the cortical end plate creates a negative influence on the derived UTTS-SVF.

Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions

Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns, such as scatterer concentrations and arrangements. In this study, we proposed a machine learning approach to integrate the strength of multimodality quantitative ultrasound envelope statistics imaging techniques and applied it to detecting microwave ablation induced thermal lesions in porcine liver ex vivo. The quantitative ultrasound parameters included were homodyned-K α which is a scatterer clustering parameter related to the effective scatterer number per resolution cell, Nakagami m which is a shape parameter of the envelope probability density function, and Shannon entropy which is a measure of signal uncertainty or complexity. Specifically, the homodyned-K log10(α), Nakagami-m, and horizontally normalized Shannon entropy parameters were combined as input features to train a support vector machine (SVM) model to classify thermal lesions with higher scatterer concentrations from normal tissues with lower scatterer concentrations. Through heterogeneous phantom simulations based on Field II, the proposed SVM model showed a classification accuracy above 0.90; the area accuracy and Dice score of higher-scatterer-concentration zone identification exceeded 83% and 0.86, respectively, with the Hausdorff distance <26. Microwave ablation experiments of porcine liver ex vivo at 60–80 W, 1–3 min showed that the SVM model achieved a classification accuracy of 0.85; compared with single log10(α),m, or hNSE parametric imaging, the SVM model achieved the highest area accuracy (89.1%) and Dice score (0.77) as well as the smallest Hausdorff distance (46.38) of coagulation zone identification. We concluded that the proposed multimodality quantitative ultrasound envelope statistics imaging based SVM approach can enhance the capability to characterize tissue scatterer distribution patterns and has the potential to detect the thermal lesions induced by microwave ablation.

Effects of Size Polydispersity and Dense Media on Quantitative Ultrasound Estimates.

Quantitative ultrasound (QUS) techniques based on the backscatter coefficient (BSC) aim to characterize the scattering properties of biological tissues. A scattering model is fit to the measured BSC, and the fitted QUS parameters can provide local tissue microstructure, namely, scatterer size and acoustic concentration. However, these techniques may fail to provide a correct description of tissue microstructure when the medium is polydisperse and/or dense. The objective of this study is to investigate the effects of scatterer size polydispersity in sparse or dense media on the QUS estimates. Four scattering models (i.e., the monodisperse and polydisperse sparse models, and the monodisperse and polydisperse concentrated models based on the structure factor) are compared to assess their accuracy and reliability in quantifying the QUS estimates. Simulations are conducted with different scatterer size distributions for sparse, moderately dense, and dense media (volume fractions of 1%, 20%, and 73%, respectively). The QUS parameters are estimated by using model-based inverse methods at different center frequencies between 8 and 50 MHz. Experimental data are also analyzed using colon adenocarcinoma HT29 cell pellet biophantoms to further validate the results obtained from simulations at the volume fraction of 73%. Our findings reveal that the choice of scattering model has a significant impact on the accuracy of QUS estimates. For sufficiently high frequencies and dense media, the polydisperse concentrated model outperforms the other models and enables more accurate quantification. Furthermore, our results contribute to advancing our understanding of the complexities associated with scatterer size polydispersity and dense media in spectral-based QUS techniques.

Quantitative Ultrasound Spectroscopy for Screening Cylindrical Lithium‐Ion Batteries for Second‐Life Applications

AbstractDiagnosing lithium‐ion battery degradation is a crucial part of managing energy storage systems. Recent research has explored ultrasonic testing for non‐invasive health assessment as an alternative to traditional, time‐consuming, electrical‐only methods. Assessing the state of health is vital for determining quality at end of ‘first’ life, with retired batteries at 70–80 % health still holding value for secondlife applications. Over the coming years, tens of GWh of salvaged batteries will hit the market, requiring rapid noninvasive methods to classify retired batteries according to their state of health. This study uses a 64 – element ultrasonic array to obtain mid‐band quantitative ultrasound spectroscopy parameters – including mid‐band fit, spectral slope, and intercept – from circumferential waves around cylindrical batteries. Thirteen cylindrical cells were used to evaluate the methodology: three pristine and ten retired from the same source. The mid‐band fit showed the ability to track the state of charge and discriminate between the state of health levels in accelerated degradation experiments both with pristine batteries, and also with recovered secondlife batteries with unknown historical use. Linear‐array ultrasonic transducers, coupled with quantitative spectral parameters, show promise for future non‐destructive battery health screening methods, offering valuable insights for the emerging used battery market.

Relationship between transmission/reception conditions of high-frequency plane wave compounding and evaluation accuracy of extended amplitude envelope statistics

The double–Nakagami (DN) model provides a method for analyzing the amplitude envelope statistics of quantitative ultrasound (QUS). In this study, the relationship between the sound field characteristics and the robustness of QUS evaluation was evaluated using five HF linear array probes and tissue-mimicking phantoms. Compound plane-wave imaging (CPWI) was used to acquire echo data. Five phantoms containing two types of scatterers were used to mimic fatty liver tissue. After clarifying the relationship between the sound field characteristics of the probes and QUS parameters, DN QUS parameters in 10 rat livers with different lipidification were evaluated using one HF linear array probe. For both phantom and in situ liver analyses, correlations between fat content and multiple QUS parameters were confirmed, suggesting that the combination of CPWI using a HF linear array probe with the DN model is a robust method for quantifying fatty liver and has potential clinical diagnostic applications.

Characterization of the invivo transient responses of the femoral cartilage by means of quantitative ultrasound imaging techniques.

Quantitative ultrasound (QUS) techniques are new diagnostic tools able to identify changes in structural and material properties of the investigated tissue. For the first time, we evaluated the capability of QUS techniques in determining the invivo transient changes in knee joint cartilage after a stressful task. An ultrasound scanner collecting B-mode and radiofrequency data simultaneously was used to collect data from the femoral cartilage of the right knee in 15 participants. Cartilage thickness (CTK), ultrasound roughness index (URI), average magnitude ratio (AMR), and Nakagami parameters (NA) were evaluated before, immediately after and every 5 min up to 45 min a stressful task (30 min of running on a treadmill with a negative slope of 5%). CTK was affected by time (main effect: p < 0.001). Post hoc test showed significant differences with CTK at rest, which were observed up to 30 min after the run. AMR and NA were affected by time (p < 0.01 for both variables), while URI was unaffected by it. For AMR, post hoc test showed significant differences with rest values in the first 35 min of recovery, while NA was increased compared to rest values in all time points. Data suggest that a single running trial is not able to modify the integrity of the femoral cartilage, as reported by URI data. Invivo evaluation of QUS parameters of the femoral cartilage (NA, AMR, and URI) are able to characterize changes in cartilage properties over time.