HealthMyne Enters Joint Development Agreement with Mayo Clinic

By Neal Miller | September 7, 2018 | Press Release

Mayo Clinic Evaluates Therapy Response Assessment Module of HealthMyne QIDS Platform

HealthMyne has signed a joint development agreement with Mayo Clinic to evaluate the Quantitative Imaging Decision Support (QIDS)® platform in their Scottsdale, AZ facility for Therapy Response Assessments, which allows for a standardized method of determining the effectiveness of various treatment protocols used in cancer care. In current practice, due to significant inefficiencies in the process, these assessments are generally limited to patients involved in clinical trials.

HealthMyne’s QIDS platform enables better patient management decisions for hospital providers worldwide by connecting the Point-of-Read (Radiology) with the Point-of-Care starting with Oncology and expanding to other specialties over time. The QIDS platform drives collaboration by providing the multidisciplinary care team with intuitive, workflow-integrated software that leverages imaging and clinical data to enhance the quality and cost of care. The Clinical Decision Support (CDS) modules in the platform--Cancer Screening, Tumor Conferences, Therapy Response, Incidental Findings, Thoracic, others--significantly automate and streamline inefficient and cost-intensive clinical processes to allow busy clinicians to focus their energies on precise patient management.

Dr. Linda Peitzman, CMIO for HealthMyne, states, “The QIDS platform provides an easy way to consistently measure Therapy Response for all cancer patients enabling clinicians to understand much earlier if a patient is responding to treatment and make appropriate adjustments in their protocols. This can result in better care and lower costs. Extracting additional volumetric and radiomic data during the clinical read can also significantly advance biomarker discovery and move us closer to personalized medicine.”

HealthMyne’s proprietary algorithms automate the extraction of quantitative imaging metrics at the Point-of-Read, minimizing inter- and intra-reader variability. The Therapy Response Module automates response scoring and the tracking of cancerous lesions across studies and time-points, greatly reducing the manual work effort. Protocols can be based on standards such as RECIST or iRECIST, but the module is extremely flexible allowing for custom parameters. The entire module is managed in a web-based environment making it easy to setup and use.