Session: Rising Stars of Mechanical Engineering Celebration & Showcase

Paper Number: 149665

149665 - Molecular Contrast Agents for Gene Delivery and Super-Resolution Ultrasound Imaging 

Introduction: 

Ultrasound has been widely used in biomedical imaging and clinical applications as a first line of diagnosis of disease. However, the major role of ultrasound imaging has been limited to the visualization of structure of targets with low resolution. Despite the correlation between specific subtypes of immune cells and cancer cells and their interplay to promote cancer growth, the complexity of immune cells and cancer cells within tumor microenvironment remains poorly understood. A reliable real-time and longitudinal tumor imaging modality improves the clinical trial design and impacts the overall patient outcome. Safe and efficient delivery approaches ensure the utilization of programmable gene editing materials, thereby improving the therapeutic potential of gene therapy. We are developing molecular ultrasound contrast agents by engineering gas vesicles chemically and genetically. We engineer wavefront for ultrasound imaging to achieve high resolution imaging.

 

Contribution toward advancing science and engineering: 

Imaging and gene delivery approaches we develop have the potential to visualize dynamic behavior and interaction of different types of cells in vivo and deliver various types of macromolecules efficiently and safely for cell engineering. 

The advancement of my research in ultrasound imaging and gene delivery potentially guide clinical decision-making and prevent and treat lethal metastases by providing approaches to monitor tumor evolutions noninvasively and catch early signs of drug resistance with a molecular level precision.

 

Methodology:

Gas vesicles were grown and purified from Anabaena flos-aquae [Ana]. For the final experiment, GVs were separately labelled with both fluorescent dyes and antibodies by chemical conjugation and dialysis. The triple conjugated gas vesicle complex was used to target human epidermal growth factor receptor 2 (HER2) and programmed death ligand 1 (PD-L1) expressing cells. 

We injected 150 μL microbubbles (MB) at 0.75 – 2.0 x 10⁹ MBs/mL into tumor mass of a tumor-bearing B6 mouse. We used an ultrasound imaging system connected with 128 element linear arrays to collect pulse echo radiofrequency (RF) data at 500 Hz. We applied singular value decomposition (SVD) to remove noise. We compared elbow point method, hard thresholding, and proposed eigen-image based methods when selecting appropriate singular values for clean images to reconstruct high resolution microvasculature of tumors in mouse model. 

 

Preliminary results and conclusions:

Preliminary antibody targeting showed statistically significant protein expression and antibody targeting. The preliminary results confirm the HER2 and PD-L1 protein expression and the antibody binding ability needed for the ultrasound imaging and targeted gene and drug delivery using gas vesicle based molecular contrast agents. The next step is to optimize the triple GV complex to target cells for ultrasound imaging and then to image after cross-targeting to prove exclusivity. This study will increase our understanding of gas vesicles as contrast agents for molecular imaging and targeted delivery. 

The elbow point method lacks specific threshold criterion which might lead to an ambiguous decision boundary. The hard thresholding method requires multiple processing steps to extract MB signal. We performed a two-step process by extract clutter signal and mouse movement and tissue scattering and depth dependent noise. The frames with MB signals were extracted based on the behavior of eigen images. Finally, the extracted blood signals were further processed to generate super-resolution ultrasound images. The super-resolution ultrasound image reconstructed by the eigen image-based method detects more vessels within mouse tumor region. The eigen image-based method proves to be the most effective approach for extracting the blood signal and generating high-density super-resolution ultrasound images of the blood vessel by detecting MB signals more efficiently compared to widely used elbow point method and newly developed hard thresholding. This method offers promising implications for enhancing the accuracy and efficiency of ultrasound imaging techniques in biomedical applications.

 

Presenting Author: Sangpil Yoon University of Oklahoma

Presenting Author Biography: I received a Ph.D from Department of Mechanical Engineering at the University of Texas at Austin. My long-term career goal is to utilize engineering principles to develop novel technologies and approaches for disease diagnosis and therapy and to integrate research within an inclusive culture focused on mentoring and training the future engineering workforce. Towards that goal, the overarching research goal is to develop a streamlined strategy for cancer diagnosis and therapy. Having been trained at the nexus of ultrasound imaging, biology and molecular and cellular engineering, I am uniquely positioned to successfully achieve overarching goals by developing a vibrant research laboratory if I join University of Washington. I have proved my innovativeness and strong track records on ultrasound imaging and ultrasound-based cellular engineering by developing novel techniques for tissue elastography, intravascular ultrasound (IVUS) imaging, ultrasound activatable CAR T cells for immunotherapy, acoustic-transfection for sustained intracellular delivery technique for stem cell engineering and immunotherapy, compressed-sensing based algorithm for super-resolution ultrasound imaging to improve image quality and acquisition time, and ultrasound molecular contrast agents using gas vesicles (GV). Due to my strong qualifications, I have been an awardee of a NIH Pathway to Independence Award (K99/R00) in my independent work on acoustic-transfection. I developed my research team by facilitating interdisciplinary laboratory space for the development of super-resolution ultrasound imaging algorithms and targeted therapy using ultrasound and GV under the support of multiple extramural grant supports including NSF CAREER AWARD and NIH R01.

Authors:

Sydney Turner University of Oklahoma
Musarrat Amin University of Oklahoma
Bhattacharjee Adree University of Oklahoma
Sangpil Yoon University of Oklahoma