This technology is a platform for development and validation of quantitative imaging biomarkers that can be used to monitor the effects of chemo-, targeted and immuno-therapies on tumor progression.
Recently, the field of medical imaging has focused on leveraging quantitative imaging biomarkers to evaluate tumor response to targeted and immunotherapies. In addition, quantitative imaging biomarkers also provide an objectively and reproducibly measured characteristic that can predict disease course and severity for diagnosis and prognosis purposes. Identification of tumor response has typically relied on Response Evaluation Criteria In Solid Tumors (RECIST), which is largely based on change in tumor diameter. However, this unidimensional method can be inaccurate and unreliable for quantifying tumor change, particularly when tumor changes size asymmetrically or does not change size but density, highlighting the need for imaging biomarkers capable of assessing tumor response to targeted and/or immunotherapies in various cancers.
This technology consists of a platform for development, validation and application of quantitative imaging biomarkers in oncology. It offers efficient and accurate 3D tumor segmentation and quantification algorithms to promote imaging biomarker development. It is built based on an open source image-viewing platform that integrated proprietary advanced 3D segmentation algorithms for solid tumors (e.g., in lung, liver and lymph nodes) and also contains a database with tumor segmentation and measurement results. This technology could facilitate the assessment of quantitative imaging biomarkers for measuring response to treatment in a variety of clinical settings.
This technology is currently being used in the research setting, and in numerous clinical trials to determine if CT volumetry-, density- and texture-based techniques can assess tumor response to targeted and immunotherapies more accurately and quickly than conventional RECIST method.
IR CU20185
Licensing Contact: Joan Martinez
