Setting a Quality Standard for Neurological Imaging

Join us in establishing the world’s first quality standard for diffusion-weighted MR imaging.

Surgeon checking brain scans

Quality MRI data enables deeper insight, better planning and improved outcomes

The Journal of Neurosurgery estimates that, globally each year, more than 13.8 million neurosurgeries are performed. It’s a clinical specialty where many procedures are high risk.

Positive outcomes can help patients return to a high quality of life and increase operational efficiency for healthcare systems. Yet target tissues, such as cancers, are often surrounded by healthy tissue that must be traversed to access and remove diseased tissue, making the margin for error narrow.

Unfortunately, neural tissue does not heal and repair itself like muscle. If errors are made in a given procedure, their effects can be permanent, profound and debilitating. The negative effects of these errors diminish quality of life for patients and leave neurological teams demoralised, at the same time as raising costs and slowing throughput for healthcare systems.

Clinical teams want to increase their diagnostic capabilities. But that accuracy requires standardized evaluated metrics.

Enabling better decisions through quality data

Currently, there’s no accepted standard to assess the quality of DTI data. Building this quality standard would ensure that only high quality, validated MRI data is used to plan patient interventions, monitor recovery and perform longitudinal and multi-centre studies. 

PreOperative Performance was founded to support neurological communities in their mission to provide personalized and high-quality care. 

We want to set this baseline to support advancements in the standard of patient care.

Brain Scan

Why?


Standardizing MR data for interventions could lead to greater consistency and more standardized approaches that would contribute to better outcomes for patients, and provide the tools for detailed retrospectives that help neurological communities learn and iterate.

Clinical applications include

  • Neuro Oncological surgical and radiation treatment planning
  • Traumatic brain injury
  • Stroke care
  • Neurodegenerative diseases
  • Cervical spine diseases investigation

And: 

  • MRI method development
  • Neuropharmaceutical drug development
  • Medical device development

For clinicians, better access to data-driven tools may lead to better clinical outcomes and lowered costs to healthcare systems and institutions.

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