Mayo, Healthmyne to work on module to assess treatment effectiveness
The Mayo Clinic is working with a vendor to fine-tune a platform to aid care decisions based on radiological images.
Healthmyne has signed a joint development agreement with the Rochester, Minn.-based delivery system to evaluate a new module in the company’s Quantitative Imaging Decision Support platform in its Scottsdale, Ariz., facility.
The intent of the collaboration is to use the platform to measure therapy responses for cancer patients, using Healthmyne’s proprietary algorithms automate the extraction of quantitative imaging metrics when images are being read by radiologists.
The platform being developed uses a module to automate response scoring and the tracking of cancerous lesions across several studies that typically occur over time, enabling radiologists to more easily compare images of cancerous lesions, helping them to assess if treatment is having an effect. These assessments typically take time for radiologists, who often estimate visual changes in lesions to assess treatment effectiveness.
“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,” says Linda Peitzman, MD, CMIO for HealthMyne. “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.
HealthMyne contends its platform enables better patient management decisions by connecting the point-of-read (radiology) with the point-of-care, starting with oncology and expanding to other specialties over time. The 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 modules in the platform—cancer screening, tumor conferences, therapy response, incidental findings, thoracic and others—significantly automate and streamline inefficient and cost-intensive clinical processes to enable clinicians to focus energies on precise patient management.