Developing AI-based software to identify prostate cancer in MR images.

Highlights 2021

The purpose of the project is to develop artificial intelligence (AI)-based software to support the detection and characterization of prostate cancer on MR images.

One highlight of 2021 is to see the hard work through the previous year’s coming together in exciting results. Our tumor probability maps and deep learning approaches for cancer detection and biopsy targeting are currently being investigated for patentability. This process will form the base for the further development of the commercial strategy of our decision support software.

What is fake, and what is real? The Generative Adversarial Network optimized for prostate cancer detection and location in our project involves discovery and learning of the patterns in input data in such a way that the model can be used to generate new, fake images indistinguishable from the original dataset. Which ones do you think are fake? (Real: A, D; Fake: B, C, E, F) Figure credit: Alexandros Patsanis, PhD candidate PROVIZ

During 2021, our research focused on further development of the analytical pipelines for the project. We are continuously expanding the extensive database of MRI scans and clinical information. This is important to ensure generalizability and robustness of our final algorithms. Routines for image co-registration, normalization, segmentation with quality control and image cropping are now embedded as flexible elements of the pipeline. Finally, the machine and deep learning-based classification algorithms have been further refined. On retrospective data we have shown that the models can complement radiological reading in detection of clinically significant prostate cancers and guide targeted biopsy sampling. The next step is to perform a prospective proof-of-concept study, which will benchmark our approach to current clinical practice. Regarding the responsible research and innovation aspects of PROVIZ, many men have taken part in discussion groups about AI. This will provide important information on how they understand AI and its potential in prostate diagnostics, and how it could influence their trust in health services. For us, the added value of being part of a transdisciplinary center is the available expertise from life, data and social sciences, as well as the possibility to directly explore the relevance of this expertise through a direct link with the clinic. This is important to our project as the problems to be solved evolve from real-world clinical limitations, are of complex nature, and require out-of-the-box thinking.


Scientific publications 2021: 3

Project overview

Project lead: Tone Frost Bathen
Institution: NTNU
Partners: St. Olav's Hospital and Norwegian University of Life Sciences (NMBU)
Duration: 2019–2022

Research group

1 in 8 men will have prostate cancer in their lives. PROVIZ is developing AI-based software to correctly identify prostate cancer in MR images, reducing the time and cost of diagnosis.

Norway was the first country to implement an integrated cancer care pathway that uses multi-parametric magnetic resonance imaging (mpMRI) as the first diagnostic tool for men with suspected prostate cancer based on elevated levels of prostate specific antigen (PSA) in their blood. However, the PSA blood test has a high false-positive rate, leading many men to get unnecessary mpMRI’s. The popularity of this blood test has created an excess of images for radiologists to analyze.

PROVIZ’s research will support radiologists by expediting the process of detecting cancer in the mpMRI images and by guiding biopsy targets. Today, radiologists rely on their training and experience to identify whether cancer is present and to guide biopsies to further test cancer aggressiveness. PROVIZ’s AI analyzes the quantitative information in mpMRI images (anatomy, vascularization, and cellularity) and builds 3D models to identify and visualize potential cancer risk, reducing the burden on radiologists and lowering biopsy risks. 

The software PROVIZ is developing is based on a unique Norwegian dataset of MRI and clinical information from over 1600 patients with and without cancer, as well as collaboration with international teams collecting data in The Netherlands and Taiwan. This large data set allows the team to account for variation between clinical sites and create a truly universal diagnostic platform.  

Clinicians, patients, and research participants have been involved in development from the start of the project to ensure the research aligns with stakeholder and social needs. This inclusive team has the background to anticipate both positive and negative outcomes of their work. In addition to experts in MRI technology, information analysis, radiology, oncology and communication between researchers and clinicians, the PROVIZ team includes a doctoral candidate specifically focused on ensuring that responsible research and innovation is integrated into the project. 

Adaptable AI-based software has the potential to reduce health care costs, ease the burden on medical personnel, and obtain better treatment outcomes. Once the project is complete, PROVIZ aims to share their data set and invite others to use it to educate the field and develop additional tools. 

PROVIZ is headed by Tone Bathen at the Norwegian University of Science and Technology in Trondheim. This lab is funded by the Research Council of Norway and is one of the multidisciplinary research projects within Centre for Digital Life Norway.

By Matthew Davidson