The goal of developing virtual computer models of organs or organ systems in the human body (i.e. ‘virtual organs’ or ‘digital twins’) is to increase understanding of human anatomy and physiology, and assist in therapy planning. In this thesis, the aim is to develop a so-called digital twin of the kidneys, to assist in surgical treatment planning of kidney cancer.

The standard treatment for patients with stage I and II kidney cancer is partial nephrectomy. In this procedure, the kidney tumour is resected, while as much healthy kidney tissue as possible is kept intact. The complexity of this procedure depends on various patient-specific parameters, such as the tumour’s diameter and location, as well as its interaction with the blood vessels and excretion system. Surrounding ‘sticky fat’ can also complicate tumour resection. To get an insight in the procedure’s complexity, several scoring systems (eg. PADUA (see Fig. 1), RENAL, MAP, …) already exist in literature, all with the same drawback: they have to be calculated manually. This can be time-consuming and is therefore not always taken into account during preoperative planning.

Over the last couple of years, the urology department of Ghent University Hospital and the Biommeda research group have been collaborating to create a virtual planning tool for partial nephrectomies. This tool is build around a 3D model of the patient-specific anatomy, but does not include the complexity scoring systems yet.