TY - JOUR
T1 - Non-invasive Small Vessel Imaging of Human Thyroid Using Motion-Corrected Spatiotemporal Clutter Filtering
AU - Nayak, Rohit
AU - Kumar, Viksit
AU - Webb, Jeremy
AU - Fatemi, Mostafa
AU - Alizad, Azra
N1 - Funding Information:
This study was supported by National Institutes of Health (NIH) grants R01CA148994, R01CA168575, R01CA195527, R01CA174723 and R01EB17213. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH. We also thank Nvidia Corporation for donating the GPU that was used for motion tracking in this study.
Funding Information:
This study was supported by National Institutes of Health (NIH) grants R01CA148994 , R01CA168575 , R01CA195527 , R01CA174723 and R01EB17213 . The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH. We also thank Nvidia Corporation for donating the GPU that was used for motion tracking in this study.
Publisher Copyright:
© 2018 The Authors
PY - 2019/4
Y1 - 2019/4
N2 - 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-correlation–based 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.
AB - 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-correlation–based 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.
KW - Compounded plane wave imaging
KW - Cross-correlation
KW - Microvasculature
KW - Motion correction
KW - Power Doppler
KW - Small vessel imaging
KW - Thyroid
KW - displacement tracking
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U2 - 10.1016/j.ultrasmedbio.2018.10.028
DO - 10.1016/j.ultrasmedbio.2018.10.028
M3 - Article
C2 - 30718145
AN - SCOPUS:85060888596
SN - 0301-5629
VL - 45
SP - 1010
EP - 1018
JO - Ultrasound in Medicine and Biology
JF - Ultrasound in Medicine and Biology
IS - 4
ER -