Mahdi Bayat

Effect of calcifications on breast ultrasound shear wave elastography: An investigational study

Purpose To investigate the effects of macrocalcifications and clustered microcalcifications associated with benign breast masses on shear wave elastography (SWE). Methods SuperSonic Imagine (SSI) and comb-push ultrasound shear elastography (CUSE) were performed on three sets of phantoms to investigate how calcifications of different sizes and distributions influence measured elasticity. To demonstrate the effect in vivo, three female patients with benign breast masses associated with mammographically-identified calcifications were evaluated by CUSE. Results Apparent maximum elasticity (Emax) estimates resulting from individual macrocalcifications (with diameters of 2mm, 3mm, 5mm, 6mm, 9mm, 11mm, and 15mm) showed values over 50 kPa for all cases, which represents more than 100% increase over background (~21kPa). We considered a 2cm-diameter circular region of interest for all phantom experiments. Mean elasticity (Emean) values varied from 26 kPa to 73 kPa, depending on the macrocalcification size. Highly dense clusters of microcalcifications showed higher Emax values than clusters of microcalcification with low concentrations, but the difference in Emean values was not significant. Conclusions Our results demonstrate that the presence of large isolated macrocalcifications and highly concentrated clusters of microcalcifications can introduce areas with apparent high elasticity in SWE. Considering that benign breast masses normally have significantly lower elasticity values than malignant tumors, such areas with high elasticity appearing due to presence of calcification in benign breast masses may lead to misdiagnosis.

Noninvasive Evaluation of Bladder Wall Mechanical Properties as a Function of Filling Volume: Potential Application in Bladder Compliance Assessment.

Purpose We propose a novel method to monitor bladder wall mechanical properties as a function of filling volume, with the potential application to bladder compliance assessment. The proposed ultrasound bladder vibrometry (UBV) method uses ultrasound to excite and track Lamb waves on the bladder wall from which its mechanical properties are derived by fitting measurements to an analytical model. Of particular interest is the shear modulus of bladder wall at different volumes, which we hypothesize, is similar to measuring the compliance characteristics of the bladder. Materials and Methods Three experimental models were used: 1) an ex vivo porcine model where normal and aberrant (stiffened by formalin) bladders underwent evaluation by UBV; 2) an in vivo study to evaluate the performance of UBV on patients with clinically documented compliant and noncompliant bladders undergoing UDS; and 3) a noninvasive UBV protocol to assess bladder compliance using oral hydration and fractionated voiding on three healthy volunteers. Results The ex vivo studies showed a high correlation between the UBV parameters and direct pressure measurement (R2 = 0.84–0.99). A similar correlation was observed for 2 patients with compliant and noncompliant bladders (R2 = 0.89–0.99) undergoing UDS detrusor pressure-volume measurements. The results of UBV on healthy volunteers, performed without catheterization, were comparable to a compliant bladder patient. Conclusion The utility of UBV as a method to monitor changes in bladder wall mechanical properties is validated by the high correlation with pressure measurements in ex vivo and in vivo patient studies. High correlation UBV and UDS in vivo studies demonstrated the potential of UBV as a bladder compliance assessment tool. Results of studies on healthy volunteers with normal bladders demonstrated that UBV could be performed noninvasively. Further studies on a larger cohort are needed to fully validate the use of UBV as a clinical tool for bladder compliance assessment.

Update on breast cancer detection using comb-push ultrasound shear elastography

In this work, tissue stiffness estimates are used to differentiate between benign and malignant breast masses in a group of pre-biopsy patients. The rationale is that breast masses are often stiffer than healthy tissue; furthermore, malignant masses are stiffer than benign masses. The comb-push ultrasound shear elastography (CUSE) method is used to noninvasively assess a tissues mechanical properties. CUSE utilizes a sequence of simultaneous multiple laterally spaced acoustic radiation force (ARF) excitations and detection to reconstruct the region of interest (ROI) shear wave speed map, from which a tissue stiffness property can be quantified. In this study, the tissue stiffnesses of 73 breast masses were interrogated. The mean shear wave speeds for benign masses (3.42 ± 1.32 m/s) were lower than malignant breast masses (6.04 ± 1.25 m/s). These speed values correspond to higher stiffness in malignant breast masses (114.9 ± 40.6 kPa) than benign masses (39.4 ± 28.1 kPa and p <; 0.001), when tissue elasticity is quantified by Youngs modulus. A Youngs modulus >83 kPa is established as a cut-off value for differentiating between malignant and benign suspicious breast masses, with a receiver operating characteristic curve (ROC) of 89.19% sensitivity, 88.69% specificity, and 0.911 for the area under the curve (AUC).

Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation

Background Lesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses. Methods With written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19–85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young’s modulus. In correlation to pathology results, statistical analyses were performed. Results Pathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21). Conclusion CUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness.

Correlation of ultrasound bladder vibrometry assessment of bladder compliance with urodynamic study results

Purpose or objective The objective of this study is to assess correlation between bladder wall mechanical properties obtained by ultrasound bladder vibrometry (UBV) and urodynamic study (UDS) measurements in a group of patients undergoing clinical UDS procedure. Materials and methods Concurrent UBV and UDS were performed on 70 patients with neurogenic bladders (56 male and 14 female). Bladder wall mechanical properties measured by UBV at different filling volumes were correlated with recorded detrusor pressure (Pdet) values. Mean, median and standard deviation of correlation values were calculated and the significance of these observations was tested. Results Bladder wall mechanical properties obtained by UBV as group velocity squared and elasticity showed high correlations with Pdet measured at different volumes (median correlation 0.73, CI: 0.64–0.80 and 0.72, CI: 0.56–0.82 respectively). The correlation of group velocity squared and elasticity with Pdet were both significantly higher than 0.5. Conclusions The results of this study suggest that UBV can closely monitor changes in bladder wall mechanical properties at different volumes in a group of patients undergoing UDS. The high correlation between UBV parameters and detrusor pressure measurements suggests that UBV can be utilized as a reliable and cost-effective tool for assessment of the bladder wall mechanical changes in a noninvasive fashion.

Automated In Vivo Sub-Hertz Analysis of Viscoelasticity (SAVE) for Evaluation of Breast Lesions

We present an automated method for acquiring images and contrast parameters based on mechanical properties of breast lesions and surrounding tissue at load frequencies less than 1 Hz. The method called sub-Hertz analysis of viscoelasticity (SAVE) uses a compression device integrated with ultrasound imaging to perform in vivo ramp-and-hold uniaxial creep-like test on human breast in vivo. It models the internal deformations of tissues under constant surface stress as a linear viscoelastic response. We first discuss different aspects of our unique measurement approach and the expected variability of the viscoelastic parameters estimated based on a simplified one-dimensional reconstruction model. Finite-element numerical analysis is used to justify the advantages of using imaging contrast over viscoelasticity values. We then present the results of SAVE applied to a group of patients with breast masses undergoing biopsy.

Differentiation of Benign and Malignant Thyroid Nodules by Using Comb-push Ultrasound Shear Elastography: A Preliminary Two-plane View Study

RATIONALE AND OBJECTIVES Low specificity of traditional ultrasound in differentiating benign from malignant thyroid nodules leads to a great number of unnecessary (ie, benign) fine-needle aspiration biopsies that causes a significant financial and physical burden to the patients. Ultrasound shear wave elastography is a technology capable of providing additional information related to the stiffness of tissues. In this study, quantitative stiffness values acquired by ultrasound shear wave elastography in two different imaging planes were evaluated for the prediction of malignancy in thyroid nodules. In addition, the association of elasticity measurements with sonographic characteristics of thyroid gland and nodules is presented. MATERIALS AND METHODS A total number of 155 patients (106 female and 49 male) (average age 57.48 ± 14.44 years) with 173 thyroid nodules (average size 24.89 ± 15.41 mm, range 5-68 mm) scheduled for fine-needle aspiration biopsy were recruited from March 2015 to May 2017. Comb-push shear elastography imaging was performed at longitudinal and transverse anatomic planes. Mean (Emean) and maximum (Emax) elasticity values were obtained. RESULTS Measurements at longitudinal view were statistically significantly higher than measurements at transverse view. Nodules with calcifications were associated with increased elasticity, and nodules with a vascular component or within an enlarged thyroid gland (goiter) were associated with a lower elasticity value. Receiver operating characteristic curve analysis was performed for Emean and Emax at each imaging plane and for the average of both planes. Sensitivity of 95.45%, specificity of 86.61%, 0.58 positive predictive value, and 0.99 negative predictive value were achieved by the average of the two planes for each Emean and Emax parameters, with area under the curve of 92% and 93%, and a cutoff value of 49.09 kPa and 105.61 kPa, respectively. CONCLUSIONS The elastic properties of thyroid nodules showed promise to be a good discriminator between malignant and benign nodules (P < .0001). However, probe orientation and internal features such as calcifications, vascular component, and goiter may influence the final elastography measurements. A larger number of malignant nodules need to be studied to further validate our results.

Background-free visualization of microvasculature networks

Recent studies have shown the ability of concurrent spatial-temporal processing methods such as singular value decomposition (SVD) filtering in visualization of the small vessels without using any type of contrast agents. The vessel images resulting from SVD filtering suffer from local and global residual background that limit the visibility of the entire vessel networks within a fixed dynamic range. This mainly stems from ultrasonic intensity variations which are not accounted for in obtaining dominant singular values representing clutter signals. In this study, we present a novel approach for removal of local and global background signals and enhancement of the vascular objects. The final images present superb vessel background separation and make them suitable for further processing such as quantitative morphology analysis.

Automated and real-time segmentation of suspicious breast masses using convolutional neural network

In this work, a computer-aided tool for detection was developed to segment breast masses from clinical ultrasound (US) scans. The underlying Multi U-net algorithm is based on convolutional neural networks. Under the Mayo Clinic Institutional Review Board protocol, a prospective study of the automatic segmentation of suspicious breast masses was performed. The cohort consisted of 258 female patients who were clinically identified with suspicious breast masses and underwent clinical US scan and breast biopsy. The computer-aided detection tool effectively segmented the breast masses, achieving a mean Dice coefficient of 0.82, a true positive fraction (TPF) of 0.84, and a false positive fraction (FPF) of 0.01. By avoiding positioning of an initial seed, the algorithm is able to segment images in real time (13–55 ms per image), and can have potential clinical applications. The algorithm is at par with a conventional seeded algorithm, which had a mean Dice coefficient of 0.84 and performs significantly better (P< 0.0001) than the original U-net algorithm.

Multi-resolution rank analysis for non-contrast ultrasound imaging of slow flow

While conventional filtering techniques can effectively exclude tissue-related Doppler shifts from those resulting from blood motions in large vessels (flow rates ~ cm/s), significant spectral overlap can hinder proper clutter filtering in imaging slow flows (flow rates ~ mm/s or tenths of mm/s). Recently, several groups have proposed clutter filtering via processing of echo ensembles in the rank space instead of frequency domain. Though significant Doppler content can result from fast moving tissues, global coherence of the induced variations enables a low rank representation. In this talk, we first provide a brief overview of the low rank clutter removal methods. We then present a new framework for the analysis of Doppler ensembles using multi-linear decomposition of a tensor comprising Doppler ensembles at different rates. The model results in a high dimensional tensor from which, after proper rank selection, images of flow at different speeds can be extracted along different fibers. Using simulation m...