Groups

The key lines of research in the Abbasinejad Enger lab are Novel Patient-Specific Brachytherapy Technology, Novel Detector Technology,  Artificial Intelligence-based Image Segmentation, and Dosimetry & Treatment Outcome Prediction. The overall aim of our research is to make radiation therapy treatment of cancer, patient-specific and move towards patient-specific radiation dosimetry and delivery. By developing and introducing new radiation sources, fast model-based radiation calculation engines/dose planning algorithms, new radiation detectors, and artificial intelligence-based solutions, we hope to reduce the side effects related to radiation therapy and improve the outcomes, with a better quality of life for the patients.

Artificial Intelligence

The Artificial Intelligence Group at the EngerLab, part of Mila – Quebec AI Institute, develops advanced machine learning methods to improve cancer diagnosis, treatment, and outcome prediction. Using multimodal patient data, including diagnostic imaging, digital pathology, and clinical text, we build models for organ segmentation, dose prediction, and optimization of treatment planning, with a particular focus on automating brachytherapy workflows. In parallel, we design outcome prediction models that apply broadly across all treatment types, supporting more personalized and effective cancer care. A major initiative is the development of a province-wide, AI-enabled data platform that harmonizes imaging, molecular, and clinical data to advance precision oncology across Quebec. Through our research and training activities such as the McMedHacks summer school, we are shaping the future of AI-driven personalized medicine.
 


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Radiobiology and Microdosimetry

The Radiobiology and Microdosimetry Group at EngerLab studies how ionizing radiation interacts with biological systems to improve the safety and effectiveness of radiotherapy. We focus on understanding relative biological effectiveness (RBE), which depends not only on radiation type but also on the size of cellular targets, recognizing that nuclei vary between patients and even within a tumor in the same patient. By combining experimental irradiation studies with microdosimetric modeling of patient histopathology images, we aim to define patient-specific RBEs. Our goal is to integrate these insights into multiscale treatment planning, enabling more precise, individualized cancer therapy.


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Detector Development

The Detector Development Group at EngerLab develops innovative radiation detectors that improve quality assurance and streamline clinical workflows to ensure radiotherapy is delivered safely and accurately. We develop tissue-equivalent detectors with high spatial resolution for radiotherapy, and compact detectors for monitoring radioactivity in PET radiopharmaceutical synthesis. We also develop a non-invasive detector to measure the arterial input function from the radial artery, aiming to replace invasive sampling in dynamic PET imaging. By advancing detection technologies that are precise, reliable, and practical, we accelerate their translation into routine patient care.
 


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Novel Brachytherapy Technology

The Novel Brachytherapy Technology Group at EngerLab develops advanced treatment planning systems, novel radiation sources, and delivery methods to enhance the precision and effectiveness of brachytherapy. Using Monte Carlo simulations, novel radiation sources, intensity-modulated delivery technologies, and AI-assisted algorithms, we design treatments that conform radiation dose more closely to the tumour while protecting surrounding healthy tissue. Our goal is to increase tumour control, reduce side effects, and improve quality of life for patients receiving brachytherapy and related treatments such as intravascular brachytherapy.


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