Development of a mobile and automated platform for multiplexed multi-modality imaging

Period of Performance: 03/03/2017 - 02/28/2018

$1.01MM

Phase 2 SBIR

Recipient Firm

SonoVol, LLC
CHAPEL HILL, NC 27514
Principal Investigator

Abstract

Abstract Bioluminescence imaging (BLI) systems are installed in thousands of facilities and labs, and with their straightforward and low cost workflow for longitudinal studies, are the most commonly used preclinical modality for assessing tumor models in rodents. There currently is no high throughput and low cost system enabling BLI images to be combined with anatomical images of soft tissue to confirm tumor volume, context, or vascularity. In our Phase I work, we demonstrated the feasibility of mapping data from our whole body ultrasound (US) system to 2D BLI images. The additional US data dramatically reduced inter-user quantification variability of the BLI signal (>80%). Furthermore, we showed that our clinically translatable microvessel imaging technology, acoustic angiography, can be mapped to the BLI data. Those tumor microvessels were analyzed using patented vessel analysis algorithms, yielding quantifiable vascular morphology metrics, previously shown to be reliable predictors of tumor malignancy and response to therapy in humans. Thus our commercialized hybrid modality US+BLI device, the Alpheidae Platform, will allow angiogenic tumors and anti-angiogenic therapies to be studied in ways current in vivo imaging tools do not allow. In Phase II, we propose to bring the Alpheidae Platform to market, leveraging whole body tissue and vascular US imaging to improve cancer research with BLI. The team includes experts in optical imaging system design, photoacoustic system design, and US imaging system design. Specifically, in Phase II, we will address the following aims: (Aim 1) Hardware R&D for multi-animal tri-modality imaging. Six animals will be scanned sequentially by our robotic system in each of the three modes. Throughput for six animals will be <15 min. (Aim 2) Software and algorithm R&D to enable automated targeted US and PA acquisitions based on BLI images, and leveraging algorithms for improved spatial resolution in both US and PA datasets. (Aim 3) Validation studies within in vivo tumor drug response study. Device performance will be assessed by comparison to standard BLI in a murine breast cancer model. Its capacity to reliably predict eventual drug response within one week of starting therapy will be the criteria for success. Once Phase II is completed we will have created a novel high throughput and portable tool enabling tumor tissue and microvessel images to be mapped to BLI data. Importantly from a commercial perspective, the Alpheidae Platform can be sold for a fraction of what competitive systems cost. From a translational research perspective, the device includes a clinically translatable US microvessel imaging approach for tumor assessment, and thus forms a direct link between preclinical findings in mice and actionable clinical cancer assessment protocols.