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FRINATEK-Fri prosj.st. mat.,naturv.,tek

Tracking cancer growth by intelligent displacement biomaps

Alternative title: Bruk av kunstig intelligens til å oppdage tidlige, strukturelle forandringer i MR-bilder av hjernekreft

Awarded: NOK 12.0 mill.

Project Number:

325971

Application Type:

Project Period:

2021 - 2025

Location:

Partner countries:

Brain tumors are one of the deadliest forms of cancer and the primary goal of treatment is simply to decelerate tumor growth. Still, after decades of research, the survival outcome for this patient group has hardly improved. A reason for this paradox is a one-size-fits-all approach to diagnosis and treatment that does not do justice to the time of diagnosis and inherent heterogeneity of the disease. Instead, the patients own data and disease on an individual level should help guide the treatment decision making process, so-called personalized medicine. Until now, this approach has not been technically feasible for radiographic images, and Magnetic Resonance imaging (MRI) in particular. Assessing the share number of images acquired during a standard MRI exam constitute an overwhelming task for any human, even for an expert radiologist. The TrackGrowth project takes advantage of artificial intelligence to reach the goal of personalized medicine. By use of state-of-the-art deep learning technology, we will obtain new knowledge that will help stratify patients with brain cancer to receive the best personalized treatment option - at the right time. We present a new paradigm for tumor diagnostics, coined displacement biomaps, where deep learning brings to life hidden information on cancer growth stored in the MRI data. Our preliminary data show how a growing tumor change the entire architecture of the brain more than half a year before these changes are observed by traditional diagnostic means. This new information will allow physicians to make early decisions on treatment – a critical step for the patients in terms of improved quality of life and prolonged survival. To assess the impact of our displacement biomaps in a real clinical setting, we will apply our technology in an ongoing clinical trial at Oslo University Hospital aiming to reduce the pressure a brain tumor exerts on its surroundings and thereby improve therapy.

Brain tumors are one of the deadliest forms of cancer and the primary goal of treatment is simply to decelerate tumor growth. Still, after decades of research, the survival outcome for this patient group has hardly improved. A reason for this paradox is a one-size-fits-all approach to diagnosis and treatment that does not do justice to the time of diagnosis and inherent heterogeneity of the disease. The TrackGrowth project takes advantage of state-of-the-art deep learning technology to obtain new knowledge that will help stratify patients with brain cancer to receive the best personalized treatment option - at the right time. We present a new paradigm for tumor diagnostics, coined displacement biomaps, where deep learning brings to life hidden information on cancer growth stored in the imaging data. Our preliminary data show how a growing tumor change the entire architecture of the brain more than half a year before these changes are observed by traditional diagnostic means. This new information will allow physicians to make early decisions on treatment – a critical step for the patients in terms of improved quality of life and prolonged survival. Our network of key stakeholders at Oslo University Hospital (OUH) constitutes a powerhouse for imaging-based diagnostics and artificial intelligence (AI) in clinical oncology. We possess a unique computational infrastructure made ready for AI that allows us to assess the impact of the displacement biomaps directly in the clinical workflow.

Activity:

FRINATEK-Fri prosj.st. mat.,naturv.,tek