- PhD publication A. Rifi
- PhD publication L. Kerkhove
- Latest news
- PhD publication C. Raets
- Best poster award A. Rifi
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Latest news
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PhD publication A. Rifi
Radiomic features are typically used in machine learning models and are proven to generate reliable results when predicting tumor grade and responses to treatment. In Amir’s new paper, an innovative approach is proposed where dedicated in vivo experiments are used to correlate biological meaning to specific radiomic features.
Read all about it in:
A.L. Rifi, I. Dufait, C. El Aisati; M. De Ridder; K. Barbé. Interpretability and Repeatability of Radiomic Features: Applied on In Vivo Tumor Models. IEEE Transactions on Instrumentation and Measurement (2023).
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PhD publication L. Kerkhove
Radiotherapy is a cornerstone for the treatment of colorectal cancer. Tumor cells present in an environment lacking oxygen (hypoxia) are resistant, leading to patient relapse. Altering redox homeostasis and inducing cell death of hypoxic cancer cells is a promising strategy to overcome radioresistance. In this study, redox homeostasis was targeted, and cell death (ferroptosis) was induced in colorectal cancer cells by treating them with the FDA-approved drug sulfasalazine. Overall, sulfasalazine treatment improved the response to radiotherapy in a model system of human colorectal cancer cells.
Lisa’s publication reveals sulfasalazine as a promising radiosensitizer of hypoxic human colorectal cancer through the disturbance of redox homeostasis and ferroptosis induction.
L. Kerkhove, F. Geirnaert, A.L. Rifi, K.L. Law, A. Gutiérrez, I. Oudaert, C. Corbet, T. Gevaert, I. Dufait, M. De Ridder. Repurposing Sulfasalazine as a Radiosensitizer in Hypoxic Human Colorectal Cancer. Cancers (2023). 15(8):2363.
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PhD publication C. Raets
CT scan images and their Dworak tumor regression grade can now be predicted in a more automated way by the use of customized random forests and give fairly good predictions (67% accuracy).
The Dworak tumor regression grade is a typical diagnostic tool to assess the tumor response of colorectal cancer patients. However, the Dworak grade is determined by a pathologist by inspection of the tumor biopsy without a dedicated measurement instrument. This work will further improve training and support for scoring the Dworak’s in a more correct manner.
C. Raets, C. El Aisati, M. De Ridder, A. Sermeus, K. Barbé. An Evolutionary Random Forest to measure the Dworak tumor regression grade applied to colorectal cancer. Measurement (2022). 205:112131, https://doi.org/10.1016/j.measurement.2022.112131.
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Best poster award A. Rifi
At the Royal Statistical Society Belgium meeting of 20-21 October 2022 one of our PhD students obtained the best poster award for junior researchers for his outstanding work entitled:
Factor analysis to unravel the biological meaning of radiomic features
Promotors: Prof. Dr. De Ridder & Prof. Dr. Barbé
Interview for Belgian Journal of Medical Oncology:
In the UZ Brussel optimal cancer care remained a top priority during the pandemic.
Prof Dr Mark De Ridder
Access the interview: