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.

Singular value based spatiotemporal clutter filtering (SVD-STF) can significantly improve the sensitivity of blood flow imaging in small vessels without using contrast agents. However, despite effective clutter filtering, large physiological motion in thyroid imaging can impact coherent integration of the Doppler signal and degrade the visualization of the underlying vasculature. In this study, we hypothesize that motion correction of the clutter filtered Doppler ensemble, prior to the power Doppler estimation, can considerably improve the visualization of smalls vessels in suspicious thyroid nodules. We corroborated this hypothesis by conducting in vivo experiments on 10 female patients in the age group 44–82 yrs, with at least one thyroid nodule suspicious of malignancy, with recommendation for fine needle aspiration biopsy. Ultrasound images were acquired using a clinical ultrasound scanner, implemented with compounded plane wave imaging. Axial and lateral displacements associated with the thyroid nodules were estimated using 2D normalized cross-correlation. Subsequently, the tissue clutter associated with the Doppler ensemble was suppressed using SVD-STF. Motion correction of the clutter-filtered Doppler ensemble was achieved using a spline based sub-pixel interpolation. The results demonstrated that power Doppler images of thyroid nodules were noticeably degraded due to large physiological motion of the pulsating carotid artery in the proximity. The resultant power Doppler images were corrupted with signal distortion, motion blurring and occurrence of artificial shadow vessels and displayed visibly low signal-to-background contrast. In contrast, the power Doppler images obtained from the motion corrected ultrasound data addressed the issue and considerabley improved the visualization of blood flow. The signal-to-noise ratio and the contrast-to-noise ratio increased by up to 15.2 dB and 12.1 dB, respectively. Across the ten subjects, the highest improvement was observed for the nodule with the largest motion. These preliminary results show the ability of using motion correction to improve the visualization of small vessel blood flow in thyroid, without using any contrast agents. The results of this feasibility study were encouraging, and warrant further development and more in vivo validation in moving tissues and organs.

Reliable assessment of small vessel blood flow in the thyroid, without using any contrast agents, can be challenging because of increased physiological motion resulting from its proximity to the pulsating carotid artery. In this study, we hypothesized that correction of tissue motion prior to singular value decomposition (SVD)-based clutter filtering can improve the coherency of the tissue components and, thus, may allow better clutter suppression and visualization of small vessels in the thyroid. We corroborated this hypothesis by conducting phantom and in vivo studies using a clinical ultrasound scanner implemented with compounded plane wave imaging. The phantom studies were conducted using a homogeneous tissue-mimicking phantom to study the impact of motion on the covariance of the spatiotemporal Doppler data, in the absence of blood activity. The non-invasive in vivo study was conducted on a 74-y-old woman with a thyroid nodule suspicious of malignancy. A rigid body-based motion correction was performed using tissue displacements obtained from 2-D normalized cross-correlationÀbased speckle tracking. Subsequently, the power Doppler images were computed using SVD-based spatiotemporal clutter filtering. The results from the phantom study revealed that motion can considerably reduce the covariance of the spatiotemporal data and, thus, increase the rank of the tissue components. When the phantom was subjected to a total translation displacement of 6 pixels over the entire ensemble, in each direction (axial and lateral), the covariance dropped by more than 25%. The results obtained from the non-invasive in vivo study indicated that visualization of small vessel blood flow improved with motion correction of the power Doppler ensemble. The contrast-to-noise ratio of the blood signal in motion-corrected power Doppler images was considerably higher (8.17 and 8.32 dB), compared with that obtained using the standard SVD approach at an optimal threshold (0.87 and 4.33 dB) and a lower singular value threshold (1.92 and 3.05 dB). Further, the covariance of the in vivo thyroid spatiotemporal data increased by approximately 10% with motion correction. These preliminary results indicate that motion correction can be used to improve the visualization of small vessel blood flow in the thyroid, without using any contrast agents. The results of this feasibility study were encouraging, and warrant further development and more in vivo validation in moving tissues and organs.

Rationale and Objectives Low specificity of traditional ultrasound in differentiating benign from malignant thyroid nodules leads to a great number of unnecessary (i.e. 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±15.41mm, range 5–68mm) 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 anatomical 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. 95.45% sensitivity, 86.61% specificity, 0.58 PPV, and 0.99 NPV 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<0.0001). 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.

Non-invasive, contrast-free microvascular imaging of human thyroids can be potentially beneficial in reducing the large number of benign biopsies of suspicious nodules. However, motion incurred by thyroid due to its proximity to the pulsating carotid artery significantly impacts the visualization of blood flow in small vessels. Singular value based spatiotemporal clutter filtering (SVD-STF) improves the performance of tissue rejection in the presence of motion. However, despite effective clutter filtering, motion in thyroid imaging can impact coherent integration of the Doppler ensemble and degrade the visualization of the underlying vasculature. Recently studies have demonstrated that motion correction using 2D normalized cross-correlation based speckle tracking can address this issue, however, only in-plane motion can be tracked and corrected. Given the natural anatomical orientation of the rigid trachea, thyroid and the pulsating carotid artery, we hypothesize that imaging of thyroid microvessels may be more reliable in the longitudinal view than in the transverse. Specifically, distal presence of rigid trachea can limit out-of-plane motion in the longitudinal view. We tested this hypothesis on 48 acquisitions obtained from 24 thyroid patients having at least one suspicious nodule. In each patient, ultrasound images of the thyroid were acquired in both longitudinal and transverse views. compounded plane-wave imaging was used to acquire the ultrasound images at high frame-rate, which is important for contrast-free small vessel blood flow imaging. Thyroid motion was tracked using 2D normalized cross-correlation based speckle tracking. tissue clutter was rejected using singular value decomposition based spatiotemporal clutter filtering. The clutter-filtered Doppler ensemble was motion corrected prior to slow-time power Doppler integration. Signal-to-noise and contrast-to-noise ratios were computed to assess the improvement in quality of the power Doppler images. Out-of-plane motion was detected by estimating normalized ensemble cross-correlation coefficient. The results demonstrated that motion associated with the thyroid due to the carotid artery was primarily in the lateral direction, which could be estimated and corrected using 2D speckle tracking. However, the motion in the transverse view displayed increased speckle decorrelation. The average ensemble cross-correlation coefficient of the thyroid ultrasound images were significantly higher (p < 0.05) in the longitudinal view than in the transverse view. The largest improvement in SNR and CNR of the estimated PD images upon motion correction was observed in the longitudinal view (12.95 ± 3.76 dB and 16.48 ± 4.6 dB) than in the transverse view (3.72 ± 0.894 dB and 6.217 ± 1.689 dB). These preliminary results show that motion encountered by the thyroid due to carotid pulsations can be effectively tracked and corrected in the longitudinal view relative to transverse, which is important for reliably visualizing the underlying blood flow. Non-invasive microvascular...