PRIMORDIAL – An artificial intelligence (AI) driven prediction model to detect risk factors for medication-related osteonecrosis of the jaws.

Bone health equilibrium can be altered by disease and the use of
medication. Antiresorptive drugs are frequently used and highly
effective to prevent bone metastasis in patients with cancer. Yet,
their use is associated with the occurrence of medication-related
osteonecrosis of the jaw (MRONJ), a potentially debilitating side
effect characterized by exposed necrotic bone in the oral cavity,
infection, and pain
Although research on advanced MRONJ lesions have been
published, so far little is known on the early disease stages, the initial
imaging features and potential preventive measures related to early
detection and disease prediction. Likewise, radiological risk factors to
identify a successful outcome or therapy resistance have not yet
been described. Therefore, the main objective of this project is to
build an automated prediction model (radiomics) to allow prediction
of MRONJ induction and its response to treatment. This could be
reached by the following subobjectives:
1. To identify the radiological and genetically predisposing factors to
develop MRONJ
2. To describe risk factors influencing treatment outcome in patients
with MRONJ
In order to obtain the subobjectives, 2 studies will be carried out:
o A prospective cohort study to follow-up patients at risk for MRONJ
development enabling to identify risk factors.
o A retrospective cohort study in patients MRONJ that underwent
surgical or conservative treatment to identify radiological features
associated with treatment
Title of your research proposal
English Title PRIMORDIAL – An artificial intelligence (AI) driven prediction model
to detect risk factors for medication-related osteonecrosis of the jaws.
Dutch Title PRIMORDIAL – Een voorspellingsmodel op basis van artificiële
intelligentie (AI) om risicofactoren voor medicatie-gerelateerde
osteonecrose van de kaken op te sporen.
GENERAL
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