Inez Verpalen

Amsterdam UMC

In short, Inez Verpalen's research entails the following:

Development and implementation of Image-based machine-learning models to Determine the response to neoadjuvant therApy in panCreatic ducTal adenocarcinoma (DIDACT)

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal form of cancer, and surgery is the only curative option. Neoadjuvant therapy (NAT) is administered before surgery for local tumor control and to target micrometastasis. Despite NAT, 40% of patients experience early diseases recurrence (within 12 months post-surgery), resulting in poor survival. Currently, there, is no reliable preoperative biomarker to predict these unfavorable survival outcomes.

In this project, we aim to develop a model using artificial intelligence (AI) to predict NAT response in PDAC patients based on computed tomography (CT) imaging. CT imaging may contain relevant information not visible to the human eye. By using AI, we hope to identify therapy-induced changes and to predict survival based on CT data. We will develop and validate this model using multicenter data from the Netherlands and international data from our consortium PHAIR-consortium partners. Applying this model is expected to lead to improved patient selection for surgery and chemotherapy, ultimately enhancing the quality of life for PDAC patients.