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Artificial intelligence and a new type of surgery can improve the treatment of bladder cancer

Professor Jørgen Bjerggaard Jensen from Aarhus University and Aarhus University Hospital has two scientific projects in the pipeline, and both will benefit patients with bladder cancer. One involves a new surgical method, while the other focuses on new technology. The projects receive financial support in the form of generous grants from the Novo Nordisk Foundation and the Innovation Fund Denmark, respectively.

2020.01.16 | Lise Wendel Eriksen

Professor Jørgen Bjerggaard Jensen from the Department of Clinical Medicine has received grants for two projects to improve the treatment of bladder cancer and reduce the number of relapses. Photo: Lars Kruse, Aarhus University.

Professor Jørgen Bjerggaard Jensen from the Department of Clinical Medicine has received grants for two projects to improve the treatment of bladder cancer and reduce the number of relapses. Photo: Lars Kruse, Aarhus University.

Bladder cancer is the tenth most frequent cancer in the world, with approx. 35 per cent of patients suffering relapses after having the primary tumour surgically removed. At present, the tumour is removed from the bladder by cutting it into small pieces and removing it through the urinary tract with the help of a standard surgical instrument. However, this technique risks spreading the tumour cells around the bladder, and this may be one of the causes of the many relapses.

Professor Jørgen Bjerggaard Jensen has received DKK 1.7 million from the Novo Nordisk Foundation to study a new surgical method known as ‘en bloc’ resection, which removes the tumour in one piece. Together with his research colleagues, he has developed a new method and the project will now test new equipment for this method. Jørgen Bjerggaard Jensen expects the new type of surgery to prove itself superior to the conventional surgical method in terms of cancer relapses.

Artificial intelligence helps during the operation

The type of tumour is critical for how much or how little of the surrounding tissue the surgeon must remove with both the ‘en bloc’ resection surgical technique and the standard method. In the case of tumours with non-aggressive growth, it is only necessary to remove the tumour itself so as to avoid unnecessary damage to the bladder, while for tumours with aggressive growth more of the surrounding tissue must be removed to avoid relapses or worsening of the disease. However, the surgeon does not know what type of tumour he or she is dealing with prior to the operation, and it is difficult to determine the tumour type with the naked eye during the operation.

The Innovation Fund Denmark has allocated almost DKK 1.5 million to the project in which Jørgen Bjerggaard Jensen and MD Jacob Elmose Jensen from Aarhus University Hospital will further develop a model based on a special version of artificial intelligence known as deep learning. With deep learning technology, it is possible to distinguish between bladder tumours with aggressive and non-aggressive growth during the operation itself, helping the surgeon to assess the type and extent of surgery required. This results in a much more targeted and less intrusive treatment for patients and helps surgical precision.

Contact

Professor & Consultant Jørgen Bjerggaard Jensen
Aarhus University, Department of Clinical Medicine and
Aarhus University Hospital, Department of Urology
Tel.: (+45) 7845 2617
Email: bjerggaard@clin.au.dk

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