There are several features of ultrasound as an imaging modality that make it attractive to clinicians and preclinical researchers today, including its relatively low cost, real-time imaging capability, safety, and portability. These facets make it a particularly accessible imaging technique for rural and lower-income communities, and thus ultrasonic diagnostic approaches have potential for broad reaching impact. Ultrasound imaging is widely used for anatomical imaging and blood flow measurements in the heart and large vessels;however this ubiquitous modality is underutilized as a diagnostic tool in oncology. One reason for this is that aside of assessment of tumor size, ultrasound has relatively poor quantitative capability with respect to tumor morphology or malignancy. New contrast enhanced ultrasound technologies are now enabling detailed images of tissue vascular structure;and the opportunity to interrogate vascular morphology as an indicator of malignancy based on ultrasound data is presented. Prior work by PI Aylward and Kitware has developed algorithms to glean quantifiable vascular morphology metrics from Magnetic Resonance Imaging data, which have then been shown to be reliable predictors of tumor malignancy and response to therapy in humans. In this project, Kitware will extend this diagnostic capability to the more widely available modality of contrast enhanced ultrasound. Co-PI Dayton has recently demonstrated ultrasonic microvascular mapping using a new type of ultrasound probe which enables the rapid acquisition of 3D high-contrast and high-resolution images of blood vessel structure. Proposed herein is a collaboration between these two leaders in industry and academia, combining their expertise to create a robust platform for disease assessment using non-invasive ultrasound imaging. If successful, this project will provide a novel and efficient method for clinical ultrasound system manufacturers to implement to assess tumor response to therapy.
Ultrasound is a relatively safe, low cost, portable, real-time imaging device;however its images are relatively poor for detecting and diagnosing tumors. New micro-bubble contrast agents have been developed that enhance the appearance of vessels within ultrasound images. We have developed a new ultrasound imaging probe that is tuned for capturing contrast-enhanced ultrasound images, and herein we propose to integrate it with a novel vascular image analysis algorithm we have also developed. Together they are able to visualize the vasculature within tumors, make measurements on those vessels, and analyze those measurements to assess the malignancy of tumors and monitor their response to treatment.
| Rao, Sneha R; Shelton, Sarah E; Dayton, Paul A (2016) The ""Fingerprint"" of Cancer Extends Beyond Solid Tumor Boundaries: Assessment With a Novel Ultrasound Imaging Approach. IEEE Trans Biomed Eng 63:1082-6 |
| Liu, Xiaoxiao; Niethammer, Marc; Kwitt, Roland et al. (2015) Low-Rank Atlas Image Analyses in the Presence of Pathologies. IEEE Trans Med Imaging 34:2583-91 |
| Shelton, Sarah E; Lee, Yueh Z; Lee, Mike et al. (2015) Quantification of Microvascular Tortuosity during Tumor Evolution Using Acoustic Angiography. Ultrasound Med Biol 41:1896-904 |
| Dayton, Paul A; Gessner, Ryan C; Phillips, Linsey et al. (2014) The implementation of acoustic angiography for microvascular and angiogenesis imaging. Conf Proc IEEE Eng Med Biol Soc 2014:4283-5 |
| Gessner, Ryan C; Frederick, C Brandon; Foster, F Stuart et al. (2013) Acoustic angiography: a new imaging modality for assessing microvasculature architecture. Int J Biomed Imaging 2013:936593 |
| Kwitt, Roland; Pace, Danielle; Niethammer, Marc et al. (2013) Studying cerebral vasculature using structure proximity and graph kernels. Med Image Comput Comput Assist Interv 16:534-41 |
| Gessner, Ryan C; Hanson, Ariel D; Feingold, Steven et al. (2013) Functional ultrasound imaging for assessment of extracellular matrix scaffolds used for liver organoid formation. Biomaterials 34:9341-51 |
| Pace, Danielle F; Aylward, Stephen R; Niethammer, Marc (2013) A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs. IEEE Trans Med Imaging 32:2114-26 |
