Super-Resolution Ultrasound Imaging

Noninvasive detection of molecular markers at high resolution remains an open problem in medicine. We are seeking to achieve this elusive goal by combining the dynamics of new phase-change nanoparticles with advanced image processing techniques. This method - which draws inspiration from recent Nobel-winning advances in optical microscopy - has the potential to dramatically improve our understanding of disease on a molecular level.

We have developed highly dynamic contrast agents - called laser-activated nanodroplets (LANDs) - which consist of a perfluorocarbon core, an encapsulated dye, a stabilizing shell, and targeting antibodies. The dye acts as a fuse and, upon radiation with a pulsed laser, the LANDs can be remotely triggered to undergo a liquid to gas phase transition, forming transient microbubbles. While in their microbubble form, the LANDs generate high ultrasound contrast, enabling single-particle detection sensitivity. The boiling point of the perfluorocarbon core (55 °C) is much higher than the surrounding tissue, resulting in the eventual recondensation of the particles to return to their nanodroplet form. In this manner, the vaporization/recondensation cycle can be repeated tens to hundreds of times for each individual particle.

By capturing high frame rate (kHz) ultrasound images, individual "blinking" LANDs can be isolated and their location can be pinpointed with much greater precision than the resolution of the imaging system. We have used this technique to localize individual nanodroplets to within 5-12 μm in vitro and 7-15 μm in vivo. This will enable high-resolution imaging of the microvasculature. Furthermore, in cancer applications, the small size of the LANDs allows them to escape the vasculature via the enhanced permeability and retention effect, and molecular targeting will enable near-single-cell resolution dynamic molecular profiling. Overall, this technology has the potential to be a valuable new tool in understanding the development, progression, and treatment response of tumors.

 1) The tissue is pulsed with a nanosecond laser. 2) Photoabsorbers within the body convert the optical energy to localized heating. 3) Elevated temperature results in a thermoelastic expansion of the tissue., which generates a broadband ultrasound wave centered at the absorber. Image graphic design by Patricio Sarzosa.

1) The tissue is pulsed with a nanosecond laser. 2) Photoabsorbers within the body convert the optical energy to localized heating. 3) Elevated temperature results in a thermoelastic expansion of the tissue., which generates a broadband ultrasound wave centered at the absorber. Image graphic design by Patricio Sarzosa.

Translational Photoacoustic Imaging

Photoacoustic imaging (also known as optoacoustic imaging) is a rapidly emerging biomedical imaging modality which combines optical excitation with acoustic detection. The acoustic detection allows us to circumvent the loss of imaging resolution associated with the diffuse propagation of light in tissue (at depths exceeding 1-2 mm). Therefore, high resolution images with optical contrast can be achieved centimeters deep in tissue.

Photoacoustic imaging can be used to visualize endogenous optical absorbers, including hemoglobin, melanin, and lipids. Furthermore, by tuning the wavelength of laser light, spectroscopic information can be obtained and tissue components can be separated. This makes the technology applicable to a variety of clinical applications, including cancer and cardiovascular disease.

This unique set of features makes photoacoustic imaging a useful tool in the growing field of molecular imaging. In fact, optical contrast agents, including dyes, nanoparticles, and genetically expressed chromophores, can be harnessed to achieve molecular and/or cellular specificity. This is critical as the medical community continues to move towards personalized medicine and highly targeted therapeutics. Despite the promise of this technology and the progress over the last two decades, photoacoustic imaging has not yet made a significant impact on the clinical care of disease.

In the FMI Lab, we are actively working to push photoacoustic imaging into the clinic. We are identifying clinical applications where the technology can yield a significant improvement over the current standard of care. Once we gain a foothold with initial clinical success, we will expand to apply photoacoustic imaging to other promising areas.

Our initial thrust is in the area of detecting lymph node metastasis noninvasively in breast cancer patients. This work is funded by the Department of Defense Breast Cancer Research Program through a Breakthrough Award. We are developing a clinical imaging system which is capable of acquiring and displaying real-time ultrasound and photoacoustic images. We will use this system to analyze the lymph nodes of breast cancer patients undergoing the sentinel lymph node biopsy procedure. Our preclinical results have indicated that metastatic lymph nodes exhibit a large drop in blood oxygenation at very early stages of disease progression. We hope to apply this effect to noninvasively detect micrometastases in breast cancer patients. The end result could be improved diagnosis/staging and reduced need for the invasive sentinel lymph node biopsy procedure.

We plan to expand from this initial project into related clinical applications, including targeting new disease sites, monitoring the outcome of therapy, and leading the effort to bring molecular imaging into the clinic.

 

Oxygenated Nanoparticles to Increase Radiation Therapy Efficacy in Head and Neck Tumors

  a ) Diagram of optically triggered O2­-carrying nanoparticles made from clinically approved materials.  b ) Upon activation the nanoparticles expel their contents

a) Diagram of optically triggered O2­-carrying nanoparticles made from clinically approved materials. b) Upon activation the nanoparticles expel their contents

In the FMI Lab, we are constantly exploring new applications for photoacoustic imaging that can be clinically relevant. We believe that photoacoustic imaging can play a role in the treatment of head and neck cancers. Radiation therapy is oftentimes the first-line treatment for tumors and metastases in the head and neck. The non-invasive technique generates free radicals in the DNA of the cancer cells, inducing cell death. The presence of oxygen enhances the therapeutic effect by increasing the extent of DNA damage. However, tumors are highly heterogeneous environments with large spatial and temporal variations in oxygen concentrations, creating radiation resistant hypoxic areas within the tumor.

 Partial pressure of oxygen released from nanoparticles overtime. Upon laser activation, partial pressure of oxygen in the environment increased.

Partial pressure of oxygen released from nanoparticles overtime. Upon laser activation, partial pressure of oxygen in the environment increased.

To re-oxygenate the hypoxic areas of the tumor for better radiation therapy outcomes, we are developing nanodroplets that can deliver oxygen to tumor sites while also acting as imaging contrast agents. The nanodroplets act as oxygen carriers and can be activated using a light source at a specific wavelength corresponding to an embedded optical dye in the nanodroplets. The activation causes the particles to phase change from a liquid nanodroplet to a gaseous microbubble, releasing the oxygen payload into the surroundings.

 

Sparsity-based Photoacoustic Image Reconstruction (SPAIR)

Photoacoustic (PA) imaging is an emerging imaging technique for many clinical applications. One of the challenges posed by clinical translation is that imaging systems often rely on a finite-aperture transducer rather than a full tomography system. This results in imaging artifacts arising from an underdetermined reconstruction of the initial pressure distribution (IPD). Furthermore, clinical applications often require deep imaging resulting in a low signal-to-noise ratio for the acquired signal because of strong light attenuation in tissue. Conventional approaches to reconstruct the IPD such as back projection and time-reversal do not adequately suppress the artifacts and noise.

Here, we propose a sparsity-based optimization approach that improves the reconstruction of IPD in PA imaging with a linear array ultrasound transducer. In simulation studies, the forward model matrix was measured from k-Wave simulations and the approach was applied to reconstruct the Shepp-Logan phantom. The results were compared with the conventional back projection, time-reversal approach, frequency-domain reconstruction and the iterative least-squares (LSQR) approaches. In experimental studies, the forward model of our imaging system was directly measured by scanning a graphite point source through the imaging field of view. Experimental images of graphite inclusions in tissue-mimicking phantoms were reconstructed and compared with the back projection and iterative least-squares approaches. Overall these results show that our proposed optimization approach can leverage the sparsity of the PA images to improve the reconstruction of the IPD and outperform the existing popular reconstruction approaches.

 Fig. 1 Simulation on the Shepp-Logan phantom using an ultrasound transducer with 6MHz center frequency and 4.8MHz bandwidth. (a) Ground truth of the Shepp-Logan phantom; (b) Reconstructed IPD image from back projection; (c) Reconstructed IPD image from the time-reversal approach; (d) Reconstructed IPD image from the frequency-domain approach; (e) Reconstructed IPD image from the LSQR; (f) Reconstructed IPD image from SPAIR; (g) The corresponding noisy RF data with an SNR of 15dB; (h) Line plots of the white dotted line in (a) for all the reconstructed IPD images and the ground truth. The scale bar is 5mm.

Fig. 1 Simulation on the Shepp-Logan phantom using an ultrasound transducer with 6MHz center frequency and 4.8MHz bandwidth. (a) Ground truth of the Shepp-Logan phantom; (b) Reconstructed IPD image from back projection; (c) Reconstructed IPD image from the time-reversal approach; (d) Reconstructed IPD image from the frequency-domain approach; (e) Reconstructed IPD image from the LSQR; (f) Reconstructed IPD image from SPAIR; (g) The corresponding noisy RF data with an SNR of 15dB; (h) Line plots of the white dotted line in (a) for all the reconstructed IPD images and the ground truth. The scale bar is 5mm.

 Fig. 2 Experimental results on tissue-mimicking phantoms with two graphite inclusions. (a~c) 3D perspectives of the tissue-mimicking phantom with two graphite inclusions; (d) Experimentally collected RF data at the first scanning location in (b); (e) Reconstructed IPD image from the back projection approach at the first scanning location in (b); (f) Reconstructed IPD image from the LSQR approach at the first scanning location in (b); (g) Reconstructed IPD image from SPAIR with TV regularization at the first scanning location in (b); (h) Reconstructed IPD image from SPAIR with L1 regularization at the first scanning location in (b); (i) Experimentally collected RF data at the second scanning location in (b); (j) Reconstructed IPD image from the back projection approach at the second scanning location in (b); (k) Reconstructed IPD image from the LSQR approach at the second scanning location in (b); (L) Reconstructed IPD image from SPAIR with TV regularization at the second scanning location in (b); (h) Reconstructed IPD image from SPAIR with L1 regularization at the second scanning location in (b). The scale bar is 5mm.

Fig. 2 Experimental results on tissue-mimicking phantoms with two graphite inclusions. (a~c) 3D perspectives of the tissue-mimicking phantom with two graphite inclusions; (d) Experimentally collected RF data at the first scanning location in (b); (e) Reconstructed IPD image from the back projection approach at the first scanning location in (b); (f) Reconstructed IPD image from the LSQR approach at the first scanning location in (b); (g) Reconstructed IPD image from SPAIR with TV regularization at the first scanning location in (b); (h) Reconstructed IPD image from SPAIR with L1 regularization at the first scanning location in (b); (i) Experimentally collected RF data at the second scanning location in (b); (j) Reconstructed IPD image from the back projection approach at the second scanning location in (b); (k) Reconstructed IPD image from the LSQR approach at the second scanning location in (b); (L) Reconstructed IPD image from SPAIR with TV regularization at the second scanning location in (b); (h) Reconstructed IPD image from SPAIR with L1 regularization at the second scanning location in (b). The scale bar is 5mm.