Non-invasive Small Vessel Imaging of Human Thyroid Using Motion-Corrected Spatiotemporal Clutter Filtering

Custom-made flow phantoms for quantitative ultrasound microvessel imaging

Morphologically realistic flow phantoms are essential experimental tools for quantitative ultrasound-based microvessel imaging. As new quantitative flow imaging tools are developed, the need for more complex vessel-mimicking phantoms is indisputable. In this article, we propose a method for fabricating phantoms with sub-millimeter channels consisting of branches and curvatures in various shapes and sizes suitable for quantifying vessel morphological features. We used different tissue-mimicking materials (TMMs) compatible with ultrasound imaging as the base and metal wires of different diameters (0.15-1.25 mm) to create wall-less channels. The TMMs used are silicone rubber, plastisol, conventional gelatin, and medical gelatin. Mother channels in these phantoms were made in diameters of 1.25 mm or 0.3 mm and the daughter channels in diameters 0.3 mm or 0.15 mm. Bifurcations were created by soldering wires together at branch points. Quantitative parameters were assessed, and accuracy of measurements from the ground truth were determined. Channel diameters were seen to have increased (76-270%) compared to the initial state in the power Doppler images, partly due to blood mimicking fluid pressure. Amongst the microflow phantoms made from the different TMMs, the medical gelatin phantom was selected as the best option for microflow imaging, fulfilling the objective of being easy to fabricate with high transmittance while having a speed of sound and acoustic attenuation close to human tissue. A flow velocity of 0.85 ± 0.01 mm/s, comparable to physiological flow velocity was observed in the smallest diameter phantom (medical gelatin branch) presented here. We successfully constructed more complex geometries, including tortuous and multibranch channels using the medical gelatin as the TMM. We anticipate this will create new avenues for validating quantitative ultrasound microvessel imaging techniques.

Noninvasive prediction of axillary lymph node breast cancer metastasis using morphometric analysis of nodal tumor microvessels in a contrast-free ultrasound approach

PURPOSE

Changes in microcirculation of axillary lymph nodes (ALNs) may indicate metastasis. Reliable noninvasive imaging technique to quantify such variations is lacking. We aim to develop and investigate a contrast-free ultrasound quantitative microvasculature imaging technique for detection of metastatic ALN in vivo.

EXPERIMENTAL DESIGN

The proposed ultrasound-based technique, high-definition microvasculature imaging (HDMI) provides superb images of tumor microvasculature at sub-millimeter size scales and enables quantitative analysis of microvessels structures. We evaluated the new HDMI technique on 68 breast cancer patients with ultrasound-identified suspicious ipsilateral axillary lymph nodes recommended for fine needle aspiration biopsy (FNAB). HDMI was conducted before the FNAB and vessel morphological features were extracted, analyzed, and the results were correlated with the histopathology.

RESULTS

Out of 15 evaluated quantitative HDMI biomarkers, 11 were significantly different in metastatic and reactive ALNs (10 with P << 0.01 and one with 0.01 < P < 0.05). We further showed that through analysis of these biomarkers, a predictive model trained on HDMI biomarkers combined with clinical information (i.e., age, node size, cortical thickness, and BI-RADS score) could identify metastatic lymph nodes with an area under the curve of 0.9 (95% CI [0.82,0.98]), sensitivity of 90%, and specificity of 88%.

CONCLUSIONS

The promising results of our morphometric analysis of HDMI on ALNs offer a new means of detecting lymph node metastasis when used as a complementary imaging tool to conventional ultrasound. The fact that it does not require injection of contrast agents simplifies its use in routine clinical practice.

Monitoring Muscle Perfusion in Rodents During Short-Term Ischemia Using Power Doppler Ultrasound

OBJECTIVE

The aim of this work was to evaluate the reliability of power Doppler ultrasound (PD-US) measurements made without contrast enhancement to monitor temporal changes in peripheral blood perfusion.

METHODS

On the basis of pre-clinical rodent studies, we found that combinations of spatial registration and clutter filtering techniques applied to PD-US signals reproducibly tracked blood perfusion in skeletal muscle. Perfusion is monitored while modulating hindlimb blood flow. First, in invasive studies, PD-US measurements in deep muscle with laser speckle contrast imaging (LSCI) of superficial tissues made before, during and after short-term arterial clamping were compared. Then, in non-invasive studies, a pressure cuff was employed to generate longer-duration hindlimb ischemia. Here, B-mode imaging was also applied to measure flow-mediated dilation of the femoral artery while, simultaneously, PD-US was used to monitor downstream muscle perfusion to quantify reactive hyperemia. Measurements in adult male and female mice and rats, some with exercise conditioning, were included to explore biological variables.

RESULTS

PD-US methods are validated through comparisons with LSCI measurements. As expected, no significant differences were found between sexes or fitness levels in flow-mediated dilation or reactive hyperemia estimates, although post-ischemic perfusion was enhanced with exercise conditioning, suggesting there could be differences between the hyperemic responses of conduit and resistive vessels.

CONCLUSION

Overall, we found non-contrast PD-US imaging can reliably monitor relative spatiotemporal changes in muscle perfusion. This study supports the development of PD-US methods for monitoring perfusion changes in patients at risk for peripheral artery disease.

Quantitative Biomarkers Derived from a Novel Contrast-Free Ultrasound High-Definition Microvessel Imaging for Distinguishing Thyroid Nodules

Low specificity in current ultrasound modalities for thyroid cancer detection necessitates the development of new imaging modalities for optimal characterization of thyroid nodules. Herein, the quantitative biomarkers of a new high-definition microvessel imaging (HDMI) were evaluated for discrimination of benign from malignant thyroid nodules. Without the help of contrast agents, this new ultrasound-based quantitative technique utilizes processing methods including clutter filtering, denoising, vessel enhancement filtering, morphological filtering, and vessel segmentation to resolve tumor microvessels at size scales of a few hundred microns and enables the extraction of vessel morphological features as new tumor biomarkers. We evaluated quantitative HDMI on 92 patients with 92 thyroid nodules identified in ultrasound. A total of 12 biomarkers derived from vessel morphological parameters were associated with pathology results. Using the Wilcoxon rank-sum test, six of the twelve biomarkers were significantly different in distribution between the malignant and benign nodules (all p < 0.01). A support vector machine (SVM)-based classification model was trained on these six biomarkers, and the receiver operating characteristic curve (ROC) showed an area under the curve (AUC) of 0.9005 (95% CI: [0.8279,0.9732]) with sensitivity, specificity, and accuracy of 0.7778, 0.9474, and 0.8929, respectively. When additional clinical data, namely TI-RADS, age, and nodule size were added to the features, model performance reached an AUC of 0.9044 (95% CI: [0.8331,0.9757]) with sensitivity, specificity, and accuracy of 0.8750, 0.8235, and 0.8400, respectively. Our findings suggest that tumor vessel morphological features may improve the characterization of thyroid nodules.

Morphometric analysis of tumor microvessels for detection of hepatocellular carcinoma using contrast-free ultrasound imaging: A feasibility study

Introduction

A contrast-free ultrasound microvasculature imaging technique was evaluated in this study to determine whether extracting morphological features of the vascular networks in hepatic lesions can be beneficial in differentiating benign and malignant tumors (hepatocellular carcinoma (HCC) in particular).

Methods

A total of 29 lesions from 22 patients were included in this work. A post-processing algorithm consisting of clutter filtering, denoising, and vessel enhancement steps was implemented on ultrasound data to visualize microvessel structures. These structures were then further characterized and quantified through additional image processing. A total of nine morphological metrics were examined to compare different groups of lesions. A two-sided Wilcoxon rank sum test was used for statistical analysis.

Results

In the malignant versus benign comparison, six of the metrics manifested statistical significance. Comparing only HCC cases with the benign, only three of the metrics were significantly different. No statistically significant distinction was observed between different malignancies (HCC versus cholangiocarcinoma and metastatic adenocarcinoma) for any of the metrics.

Discussion

Obtained results suggest that designing predictive models based on such morphological characteristics on a larger sample size may prove helpful in differentiating benign from malignant liver masses.

Combining Spatial Registration With Clutter Filtering for Power-Doppler Imaging in Peripheral Perfusion Applications

Power-Doppler ultrasonic (PD-US) imaging is sensitive to echoes from blood cell motion in the microvasculature but generally nonspecific because of difficulties with filtering nonblood-echo sources. We are studying the potential for using PD-US imaging for routine assessments of peripheral blood perfusion without contrast media. The strategy developed is based on an experimentally verified computational model of tissue perfusion that simulates typical in vivo conditions. The model considers directed and diffuse blood perfusion states in a field of moving clutter and noise. A spatial registration method is applied to minimize tissue motion prior to clutter and noise filtering. The results show that in-plane clutter motion is effectively minimized. While out-of-plane motion remains a strong source of clutter-filter leakage, those registration errors are readily minimized by straightforward modification of scanning techniques and spatial averaging.

Improving coronary ultrafast Doppler angiography using fractional moving blood volume and motion-adaptive ensemble length

Coronary microperfusion assessment is a key parameter for understanding cardiac function. Currently, coronary ultrafast Doppler angiography is the only non-invasive clinical imaging technique able to assess coronary microcirculation quantitatively in humans. In this study, we propose to use fractional moving blood volume (FMBV), proportional to the red blood cell concentration, as a metric for perfusion. FMBV compares the power Doppler in a region of interest (ROI) inside the myocardium to the power Doppler of a reference area in the heart chamber, fully filled with blood. This normalization gives then relative values of the ROI blood filling. However, due to the impact of ultrasound attenuation and elevation focus on power Doppler values, the reference area and the ROI need to be at the same depth to allow this normalization. This condition is rarely satisfied in vivo due to the cardiac anatomy. Hereby, we propose to locally compensate the attenuation between the ROI and the reference, by measuring the attenuation law on a phantom. We quantified the efficiency of this approach by comparing FMBV with and without compensation on a flow phantom. Compensated FMBV was able to estimate the ground-truth FMBV with less than 5% variation. This method was then adapted to the in vivo case of myocardial perfusion imaging during heart surgery on human neonates. The translation from in vitro to in vivo required an additional clutter filtering step to ensure that blood signals could be correctly identified in the fast-moving myocardium. We applied the singular value decomposition filter on temporal sliding windows whose lengths were a function of myocardium motion. This motion-adaptive temporal sliding window approach was able to improve blood and tissue separation in terms of contrast-to-noise ratio, as compared to well-established constant-length sliding window approaches. Therefore, compensated FMBV and singular value decomposition assisted with motion-adaptive temporal sliding windows improves the quantification of blood volume in coronary ultrafast Doppler angiography.

Volumetric imaging and morphometric analysis of breast tumor angiogenesis using a new contrast-free ultrasound technique: a feasibility study

BACKGROUND

There is a strong correlation between the morphological features of new tumor vessels and malignancy. However, angiogenic heterogeneity necessitates 3D microvascular data of tumor microvessels for more reliable quantification. To provide more accurate information regarding vessel morphological features and improve breast lesion characterization, we introduced a quantitative 3D high-definition microvasculature imaging (q3D-HDMI) as a new easily applicable and robust tool to morphologically characterize microvasculature networks in breast tumors using a contrast-free ultrasound-based imaging approach.

METHODS

In this prospective study, from January 2020 through December 2021, a newly developed q3D-HDMI technique was evaluated on participants with ultrasound-identified suspicious breast lesions recommended for core needle biopsy. The morphological features of breast tumor microvessels were extracted from the q3D-HDMI. Leave-one-out cross-validation (LOOCV) was applied to test the combined diagnostic performance of multiple morphological parameters of breast tumor microvessels. Receiver operating characteristic (ROC) curves were used to evaluate the prediction performance of the generated pooled model.

RESULTS

Ninety-three participants (mean age 52 ± 17 years, 91 women) with 93 breast lesions were studied. The area under the ROC curve (AUC) generated with q3D-HDMI was 95.8% (95% CI 0.901-1.000), yielding a sensitivity of 91.7% and a specificity of 98.2%, that was significantly higher than the AUC generated with the q2D-HDMI (p = 0.02). When compared to q2D-HDMI, the tumor microvessel morphological parameters obtained from q3D-HDMI provides distinctive information that increases accuracy in differentiating breast tumors.

CONCLUSIONS

The proposed quantitative volumetric imaging technique augments conventional breast ultrasound evaluation by increasing specificity in differentiating malignant from benign breast masses.

Dynamic Filtering of Adherent and Non-adherent Microbubble Signals Using Singular Value Thresholding and Normalized Singular Spectrum Area Techniques

Ultrasound molecular imaging techniques rely on the separation and identification of three types of signals: static tissue, adherent microbubbles and non-adherent microbubbles. In this study, the image filtering techniques of singular value thresholding (SVT) and normalized singular spectrum area (NSSA) were combined to isolate and identify vascular endothelial growth factor receptor 2-targeted microbubbles in a mouse hindlimb tumor model (n = 24). By use of a Verasonics Vantage 256 imaging system with an L12-5 transducer, a custom-programmed pulse inversion sequence employing synthetic aperture virtual source element imaging was used to collect contrast images of mouse tumors perfused with microbubbles. SVT was used to suppress static tissue signals by 9.6 dB while retaining adherent and non-adherent microbubble signals. NSSA was used to classify microbubble signals as adherent or non-adherent with high accuracy (receiver operating characteristic area under the curve [ROC AUC] = 0.97), matching the classification performance of differential targeted enhancement. The combined SVT + NSSA filtering method also outperformed differential targeted enhancement in differentiating MB signals from all other signals (ROC AUC = 0.89) without necessitating destruction of the contrast agent. The results from this study indicate that SVT and NSSA can be used to automatically segment and classify contrast signals. This filtering method with potential real-time capability could be used in future diagnostic settings to improve workflow and speed the clinical uptake of ultrasound molecular imaging techniques.

Quantitative assessment of ensemble coherency in contrast-free ultrasound microvasculature imaging

Purpose

Contrast‐free visualization of microvascular blood flow (MBF) using ultrasound can play a valuable role in diagnosis and detection of diseases. In this study, we demonstrate the importance of quantifying ensemble coherence for robust MBF imaging. We propose a novel approach to quantify ensemble coherence by estimating the local spatiotemporal correlation (LSTC) image, and evaluate its efficacy through simulation and in vivo studies.

Methods

The in vivo patient studies included three volunteers with a suspicious breast tumor, 15 volunteers with a suspicious thyroid tumor, and two healthy volunteers for renal MBF imaging. The breast data displayed negligible prior motion and were used for simulation analysis involving synthetically induced motion, to assess its impact on ensemble coherency and motion artifacts in MBF images. The in vivo thyroid data involved complex physiological motion due to its proximity to the pulsating carotid artery, which was used to assess the in vivo efficacy of the proposed technique. Further, in vivo renal MBF images demonstrated the feasibility of using the proposed ensemble coherence metric for curved array‐based MBF imaging involving phase conversion. All ultrasound data were acquired at high imaging frame rates and the tissue signal was suppressed using spatiotemporal clutter filtering. Thyroid tissue motion was estimated using two‐dimensional normalized cross correlation‐based speckle tracking, which was subsequently used for ensemble motion correction. The coherence of the MBF image was quantified based on Casorati correlation of the Doppler ensemble.

Results

The simulation results demonstrated that an increase in ensemble motion corresponded with a decrease in ensemble coherency, which reciprocally degraded the MBF images. Further the data acquired from breast tumors demonstrated higher ensemble coherency than that from thyroid tumors. Motion correction improved the coherence of the thyroid MBF images, which substantially improved its visualization. The proposed coherence metrics were also useful in assessing the ensemble coherence for renal MBF imaging. The results also demonstrated that the proposed coherence metric can be reliably estimated from downsampled ensembles (by up to 90%), thus allowing improved computational efficiency for potential applications in real‐time MBF imaging.

Conclusions

This pilot study demonstrates the importance of assessing ensemble coherency in contrast‐free MBF imaging. The proposed LSTC image quantified coherence of the Doppler ensemble for robust MBF imaging. The results obtained from this pilot study are promising, and warrant further development and in vivo validation.

Enhancement of in vivo cardiac photoacoustic signal specificity using spatiotemporal singular value decomposition

SIGNIFICANCE

Photoacoustic imaging (PAI) can be used to infer molecular information about myocardial health non-invasively in vivo using optical excitation at ultrasonic spatial resolution. For clinical and preclinical linear array imaging systems, conventional delay-and-sum (DAS) beamforming is typically used. However, DAS cardiac PA images are prone to artifacts such as diffuse quasi-static clutter with temporally varying noise-reducing myocardial signal specificity. Typically, multiple frame averaging schemes are utilized to improve the quality of cardiac PAI, which affects the spatial and temporal resolution and reduces sensitivity to subtle PA signal variation. Furthermore, frame averaging might corrupt myocardial oxygen saturation quantification due to the presence of natural cardiac wall motion. In this paper, a spatiotemporal singular value decomposition (SVD) processing algorithm is proposed to reduce DAS PAI artifacts and subsequent enhancement of myocardial signal specificity.

AIM

Demonstrate enhancement of PA signals from myocardial tissue compared to surrounding tissues and blood inside the left-ventricular (LV) chamber using spatiotemporal SVD processing with electrocardiogram (ECG) and respiratory signal (ECG-R) gated in vivo murine cardiac PAI.

APPROACH

In vivo murine cardiac PAI was performed by collecting single wavelength (850 nm) photoacoustic channel data on eight healthy mice. A three-dimensional (3D) volume of complex PAI data over a cardiac cycle was reconstructed using a custom ECG-R gating algorithm and DAS beamforming. Spatiotemporal SVD was applied on a two-dimensional Casorati matrix generated using the 3D volume of PAI data. The singular value spectrum (SVS) was then filtered to remove contributions from diffuse quasi-static clutter and random noise. Finally, SVD processed beamformed images were derived using filtered SVS and inverse SVD computations.

RESULTS

Qualitative comparison with DAS and minimum variance (MV) beamforming shows that SVD processed images had better myocardial signal specificity, contrast, and target detectability. DAS, MV, and SVD images were quantitatively evaluated by calculating contrast ratio (CR), generalized contrast-to-noise ratio (gCNR), and signal-to-noise ratio (SNR). Quantitative evaluations were done at three cardiac time points (during systole, at end-systole (ES), and during diastole) identified from co-registered ultrasound M-Mode image. Mean CR, gCNR, and SNR values of SVD images at ES were 245, 115.15, and 258.17 times higher than DAS images with statistical significance evaluated with one-way analysis of variance.

CONCLUSIONS

Our results suggest that significantly better-quality images can be realized using spatiotemporal SVD processing for in vivo murine cardiac PAI.

Texture Analysis on Ultrasound: The Effect of Time Gain Compensation on Histogram Metrics and Gray-Level Matrices

Aims:

Texture analysis (TA) is becoming an increasingly used tool in radiological research. Some papers have been published on its use in ultrasound (US), but the way in which the machine settings affect the features has not yet been fully explored. With this research, we analyze how the time gain compensation (TGC) influences the features of the gray-level matrices in the abdominal US setting.

Subjects and Methods:

We analyzed the images acquired from the hepatorenal acoustic window of a healthy 29-year-old volunteer acquired with different TGC settings. TA was carried out using the LifeX software.

Results:

Several both 1^st and 2^nd order gray-level matrices features showed a strong correlation with TGC settings.

Conclusions:

TGC settings must be accounted for when carrying out further TA studies.

Ultrasound Imaging of Injections in Masseter Muscle without Contrast Agent Using Strain Elastography and a Novel B-Mode Spatiotemporal Filter

Botulinum toxin type A (BTX-A) injections in masseter muscle can alleviate muscle tightness and aching pain caused by idiopathic masticatory myalgia, a subform of the myofascial pain syndrome. Yet the injection procedure (number, amount) is currently empirical. In this ex vivo study, we determined the feasibility of using contrast-free ultrasound imaging to visualize the short-term injectate propagation. Ultrasound annotations of BTX-A injectate spread in N = 12 porcine masseter muscles were compared with the histopathology of the excised masseter. BTX-A presence was automatically detected in the ultrasound cine by: compensating tissue motion and deformation during injection with a novel spatiotemporal filtering (SF) algorithm, and by imaging tissue swelling strains with strain elastography (SE). BTX-A injectate introduced 6.5% (standard deviation = 5.0%) echogenicity contrast and 13.9% (standard deviation = 3.7%) tissue swelling strain. Muscle fasciae were a border for BTX-A distribution. The SF algorithm achieved significantly higher noise rejection (contrast-to-noise ratio = 4.63) than SE (2.56, p = 0.01), and state-of-the-art 2-D digital image correlation (1.81, p < 0.001) and direct image subtraction (1.29, p < 0.001) methods. Histopathology agreed well with ultrasound (Dice coefficient = 0.48), with deviations mainly explained by the three-dimensional inhomogeneous distribution of BTX-A. Preliminary in vivo patient results indicated that SF and SE discard artifactual BTX-A detection outside the injection region. The proposed methods contribute to objectivize ultrasound-guided injections, with additional applications, for instance, to monitor injectate spread of local anesthetics.

A Spatial Coherence Beamformer Design for Power Doppler Imaging

Acoustic clutter is a primary source of image degradation in ultrasound imaging. In the context of flow imaging, tissue and acoustic clutter signals are often much larger in magnitude than the blood signal, which limits the sensitivity of conventional power Doppler in SNR-limited environments. This has motivated the development of coherence-based beamformers, including Coherent Flow Power Doppler (CFPD), which have demonstrated efficacy in mitigating sources of diffuse clutter. However, CFPD uses a measure of normalized coherence, which incurs a non-linear relationship between image intensity and the magnitude of the blood echo. As a result, CFPD is not a robust approach to study gradation of blood signal energy, which depicts the fractional moving blood volume. We propose the application of mutual intensity, rather than normalized coherence, to retain the clutter suppression capability inherent in coherence beamforming, while preserving the underlying signal energy. Feasibility of this approach was shown via Field II simulations, phantoms, and in vivo human liver data. In addition, we derive an adaptive statistical threshold for the suppression of residual noise signals. Overall, this beamformer design shows promise as an alternative technique to depict flow volume gradation in cluttered imaging environments.

Impact of imaging cross-section on visualization of thyroid microvessels using ultrasound: Pilot study

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.

Adaptive background noise bias suppression in contrast-free ultrasound microvascular imaging

Non-invasive, contrast-free imaging of small vessel blood flow is diagnostically invaluable for detection, diagnosis and monitoring of disease. Recent advances in ultrafast imaging and tissue clutter-filtering have considerably improved the sensitivity of power Doppler (PD) imaging in detecting small vessel blood flow. However, suppression of tissue clutter exposes the depth-dependent time-gain compensated noise bias that noticeably degrades the PD image. We hypothesized that background suppression of PD images based on noise bias estimated from the entire clutter-filtered singular value spectrum can considerably improve flow signal visualization compared to currently existing techniques. To test our hypothesis, in vivo experiments were conducted on suspicious breast lesions in 10 subjects and deep-seated hepatic and renal microvasculatures in four healthy volunteers. Ultrasound PD images were acquired using a clinical ultrasound scanner, implemented with compounded plane wave imaging. The time gain compensated noise field was computed from the clutter-filtered Doppler ensemble (CFDE) based on its local spatio-temporal correlation, combined with low-rank signal estimation. Subsequently, the background bias in the PD images was suppressed by subtracting the estimated noise field. Background-suppressed PD images obtained using the proposed technique substantially improved visualization of the blood flow signal. The background bias in the noise suppressed PD images varied  <0.6 dB, independent of depth, which otherwise increased up to 13.8 dB. Further, the results demonstrated that the proposed technique efficaciously suppressed the background noise bias associated with smaller Doppler ensembles, which are challenging due to increased overlap between blood flow and noise components in the singular value spectrum. These preliminary results demonstrate the utility of the proposed technique to improve the visualization of small vessel blood flow in contrast-free PD images. The results of this feasibility study were encouraging, and warrant further development and additional in vivo validation.