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Novel AI technique able to distinguish between progressive brain tumours and radiation necrosis, 91��ɫ U study finds

egamulin — Mon, 08 Dec 2025 16:00:00 +0000

Professor says this could lead to better treatments for late-stage cancer patients

TORONTO, Dec. 8 2025 — While targeted radiation can be an effective treatment for brain tumours, subsequent potential necrosis of the treated areas can be hard to distinguish from the tumours on a standard MRI. led by a 91��ɫ professor in the Lassonde School of Engineering found that a novel AI-based method is better able to distinguish between the two types of lesions on advanced MRI than the human eye alone, a discovery that could help clinicians more accurately identify and treat the issues.

91��ɫ Research Chair and Professor Ali Sadeghi Naini, lead author on the study.

“The study shows, for the first time, that novel attention-guided AI methods coupled with advanced MRI can differentiate, with high accuracy, between tumour progression and radiation necrosis in patients with brain metastasis treated with stereotactic radiosurgery,” says 91��ɫ Research Chair Ali Sadeghi-Naini, senior author of the paper and associate professor of biomedical engineering and computer science. “Timely differentiation between tumour progression and radiation necrosis after radiotherapy in brain tumours is a crucial challenge in cancer centers, since these two conditions require quite different treatment approaches.”

The proposed AI model architecture. The model processes multi-channel 3D input volumes. Within each block, attention is computed through four mechanisms.

The study, published in the International Journal of Radiation Oncology, Biology, Physics, was conducted in close collaboration with imaging scientists, neuro-oncologists and neuro-radiologists at Sunnybrook Health Sciences Centre using data acquired from more than 90 cancer patients whose original cancer had metastasized to the brain.

Sadeghi-Naini says the incidence of brain metastasis is rising as treatments improve and survival rates increase. Stereotactic radiosurgery (SRS), where a concentrated doses of radiation are applied to the cancer lesions only, is effective at controlling the tumours. In up to 30 per cent of cases, SRS is not able to control the tumour and it continues to grow. Where it is successful, healthy brain tissue immediately surrounding the tumour may also die off, called brain radiation necrosis, and it can come with significant side effects.

Sadeghi-Naini and his colleagues introduced a 3D deep learning AI model with two advanced attention mechanisms to differentiate between tumour progression and radiation necrosis using a specialized MRI technique, called chemical exchange saturation transfer (CEST), and found that the AI was able to differentiate between the two conditions with over 85 per accuracy. Sadeghi-Naini says with a standard MRI the two conditions are accurately diagnosed about 60 per cent of the time, and with more advanced MRI techniques alone, the rate increases to about 70 per cent.

“Differentiating tumour progression and radiation necrosis is very important — one needs more anti-cancer therapies and may need to be aggressively treated with more radiation, sometimes surgery. The other may require observation, anti-inflammatory drugs, so getting this right is crucial for patients.”

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91��ɫ is a modern, multi-campus, urban university located in Toronto, Ontario. Backed by a diverse group of students, faculty, staff, alumni and partners, we bring a uniquely global perspective to help solve societal challenges, drive positive change, and prepare our students for success. 91��ɫ's fully bilingual Glendon Campus is home to Southern Ontario's Centre of Excellence for French Language and Bilingual Postsecondary Education. 91��ɫ’s campuses in Costa Rica and India offer students exceptional transnational learning opportunities and innovative programs. Together, we can make things right for our communities, our planet, and our future.

Media Contact:

Emina Gamulin, 91��ɫ Media Relations, 437-217-6362, egamulin@yorku.ca

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91��ɫ prof answers the question 'is anyone truly healthy?'

egamulin — Thu, 06 Jul 2023 20:08:25 +0000

The post 91��ɫ prof answers the question 'is anyone truly healthy?' appeared first on News@91��ɫ.

91��ɫ research: AI better than human eye at predicting brain metastasis outcomes

egamulin — Mon, 19 Dec 2022 15:08:30 +0000

Lassonde engineers create novel technique they hope will provide cancer patients and clinicians with better, faster information

A recent study by 91��ɫ researchers suggests an innovative artificial intelligence (AI) technique they developed is considerably more effective than the human eye when it comes to predicting therapy outcomes in patients with brain metastases. The team hopes the new research and technology could eventually lead to more tailored treatment plans and better health outcomes for cancer patients.

“This is a sophisticated and comprehensive analysis of MRIs to find features and patterns that are not usually captured by the human eye,” says , associate professor of biomedical engineering and computer science in the , and lead on the study.

“We hope our technique, which is a novel AI-based predictive method of detecting radiotherapy failure in brain metastasis, will be able to help oncologists and patients make better informed decisions and adjust treatment in a situation where time is of the essence.”

Previous studies have shown that using standard practices, such as MRI imaging – assessing the size, location — and number of brain metastases — well as the primary cancer type and condition of the patient, oncologists are able to predict treatment failure (defined as continued growth of the tumour) about 65 per cent of the time. The researchers created and tested several AI models and their best one had an 83 per cent accuracy.

Brain metastases are a type of cancerous tumour that develops when primary cancers in the lungs, breasts, colon or other parts of the body are spread to the brain via the bloodstream or lymphatic system. While there are various treatment options, stereotactic radiotherapy is one of the more common, with treatment consisting of concentrated doses of radiation targeted at the area with the tumour.

“Not all of the tumours respond to radiation — up to 30 per cent of these patients have continued growth of their tumour, even after treatment,” Sadeghi-Naini says. “This is often not discovered until months after treatment via follow-up MRI.”

This delay is time patients with brain metastases cannot afford, as it is a particularly debilitating condition with most people succumbing to the disease between three months to five years after diagnosis. “It’s very important to predict therapy response even before that therapy begins,” Sadeghi-Naini continues.

Using a machine-learning technique known as deep learning, the researchers created artificial neural networks trained on a large pool of data, then taught the AI to pay more attention to specific areas.

“When you look at an MRI, you see areas within or surrounding the tumour where the intensity and pattern is different, so you attend to those parts with your vision system more,” explains Sadeghi-Naini. “But an AI algorithm is blind to this. The attention mechanism we incorporated into the algorithm helps these AI tools to learn which part of these images are more important and put more weight on that for analysis and prediction.”

91��ɫ Research Chair and Professor Ali Sadeghi Naini, lead author on the study.

The study,, has been published in the IEEE Journal of Translational Engineering in Health and Medicine. Partially funded by the Terry Fox Research Institute (TFRI), the modelling work was done at Sadeghi-Naini’s lab at 91��ɫ’s Keele Campus with 91��ɫ PhD student Ali Jalalifar, first author on the study. When it came to data acquisition and interpreting the results from more than 120 patients, the team was able to leverage 91��ɫ’s long-standing collaborative relationship with Sunnybrook Health Sciences Centre in Toronto. Other funders of the study included the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Hatch Memorial Foundation.

Sadeghi-Naini says that while more research needs to be done, the findings point to AI being a potentially significant tool in precision management of brain metastasis and even other types of cancer down the line.

The next step to adopting this as a clinical practice would be looking at a larger cohort with a multi-institutional data set, from there a clinical trial could be developed. “If standard treatments can be tailored for patients based on their response to treatments – that can be predicted before treatment even starts – there's a good chance that the overall survival of the patients can be improved,” he concludes.

As part of its long‐standing program involving the best cancer researchers across Canada, , TFRI by Sadeghi-Naini and a team of clinicians and scientists based out of Sunnybrook Health Sciences Centre to the tune of $6 million over the next six years. Sadeghi-Naini is leading the biomedical computational-AI core of the program, receiving $900,000 of that funding.

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Media Contact:

Emina Gamulin, 91��ɫ Media Relations, 437-217-6362, egamulin@yorku.ca

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Scientists discover novel genes responsible for regulating muscle cells

roshanp — Wed, 22 May 2019 13:36:42 +0000

91��ɫ research could lead to new muscle cancer therapy

TORONTO, May 22, 2019 – 91��ɫ scientists have uncovered a unique set of genes that play a role in muscle cellular gene expression and differentiation which could lead to new therapeutic targets to prevent the spread of muscle cancer.

The researchers analyzed gene networks in muscle cells and found that the Smad7 and β-catenin proteins work cooperatively inside the body to regulate muscle cell differentiation, growth and repair. When these regulatory proteins work in harmony, they control the pathway for normal gene expression, resulting in normal skeletal muscle cells.

Professor John McDermott and a team of scientists have discovered a set of genes which could lead to new muscle cancer therapy.

The study, published in the journal , indicates that a dysfunctional relationship between the Smad7 and β-catenin complex can lead to a situation of impaired muscle cell differentiation – a hallmark of some soft tissue cancers such as Rhabdomyosarcoma (RMS). This rare cancer, which most often affects children, forms in soft tissue, mostly skeletal muscle tissue, and sometimes in hollow organs like the bladder or uterus.

“What happens in those rhabdomyosarcoma cells is that they have a muscle cell-like character, but the difference is that normal muscle cells stop dividing,” said , a professor in the Department of Biology in the Faculty of Science, who supervised the study and is a contributing author.

McDermott said these cells look like muscle cells, in terms of the way they function and their phenotype, but they don’t stop dividing, which is why they form tumors at various sites in the body.

“Our idea is that part of the reason why those cells are defective in the differentiation program, which would mean that they would stop dividing, is that the β-catenin complex is being degraded in those cells because of an anomaly in the signaling pathway that controls that,” said McDermott. “If we can stabilize the β-catenin and Smad7 complex in those cells, you could potentially encourage them to differentiate and stop proliferating, which would mean that you’d stop those cells from growing in the tumor.”

The research was conducted in 91��ɫ’s – the first of its kind in Canada – which focuses on the importance of skeletal muscle to the overall health and well-being of Canadians. This new molecular genetic finding could lead to strategies for cancer treatments that target these specific molecules.

The study also defines new molecular targets for therapeutic interventions in muscle wasting and cancer.

“Until you know how things work normally, it’s very hard to target anything specific, so identifying the normal function of molecules is essential before assessing abnormal function in cancer cells,” said McDermott. “This then allows therapeutic targeting of specific molecules in order to develop pharmacology to treat the condition, or in some cases pre-existing pharmacology would be used.”

The research team – led by PhD student Soma Tripathi and including Tetsuaki Miyake, a research associate and PhD – focused on understanding the role of transcription factors in orchestrating tissue-specific gene expression and differentiation. They did this by identifying DNA binding proteins that are involved in transcriptional regulation during muscle development. The study also identified new regulators of muscle regeneration which could also open doors for the pharmaceutical industry to develop new treatments to address the normal but debilitating loss of muscle in the aging population.

“Muscle regeneration is a highly complex process and is regulated by a variety of transcription factors which are essentially proteins that help turn genes on or off by binding to specific genes within the genome,” said Tripathi. “We believe two such transcription factors, Smad7 and β-catenin, play a key role in the specific pattern of gene expression required for muscle development and repair.”

Funding for the study was provided by the Canadian Institutes of Health Research (CIHR).

91��ɫ champions new ways of thinking that drive teaching and research excellence. Our students receive the education they need to create big ideas that make an impact on the world. Meaningful and sometimes unexpected careers result from cross-disciplinary programming, innovative course design and diverse experiential learning opportunities. 91��ɫ students and graduates push limits, achieve goals and find solutions to the world’s most pressing social challenges, empowered by a strong community that opens minds. 91��ɫ U is an internationally recognized research university – our 11 faculties and 25 research centres have partnerships with 200+ leading universities worldwide. Located in Toronto, 91��ɫ is the third largest university in Canada, with a strong community of 53,000 students, 7,000 faculty and administrative staff, and more than 300,000 alumni.

91��ɫ U's fully bilingual Glendon Campus is home to Southern Ontario's Centre of Excellence for French Language and Bilingual Postsecondary Education.

Media Contact: Vanessa Thompson, 91��ɫ Media Relations, 416-736-2100 ext. 22097, vthomps@yorku.ca

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