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research & innovation

Paper of the Month

Quantitative Susceptibility Mapping – Quest for a CT-free Cancer Treatment Workflow

By Clara Wong

Reyhaneh Nosrati
Reyhaneh Nosrati

40% – Four years ago, the Canadian Cancer Society cited that as country’s predicted increase in new cancer cases by 2030. Grim numbers for what’s already the leading cause of death among Canadians. But the rise of a developing treatment modality may provide counterbalancing reason for optimism. 

A recent market intelligence report predicts a decade of vigorous activity in an already hot US$221 million market for the new technology. The innovation is called Magnetic Resonance guided Radiation Therapy (MRgRT), and it’s been a focal point in Medical Physics PhD candidate Reyhaneh Nosrati’s research work since 2015. 

Jointly supervised by Sunnybrook Research Institute senior scientist Dr. Greg Stanisz and Ryerson Physics professor Dr. Ana Pejovic-Milic, Nosrati and collaborators Dr. Moti Paudel, Dr. Ananth Ravi and Dr. Gerard Morton published the findings of their research on MRgRT. Now, the young PhD candidate is being courted by the likes of Varian, Philips and GE to bring the research to market.  

Critical Blind Spot in MRI

As patient preferences move toward non-invasive treatments, so does the call for greater accuracy in radiation-based methods. Clearer imaging of the tumour’s size, shape and location lets doctors accurately determine dosage – and aim radioactive beams at the right spot. 

“Of all imaging modalities, MRI has the best soft tissue contrast, so it’s the modality of choice by radiation oncologists for target delineation in radiation therapy treatment planning,” explains Nosrati. There’s just one shortfall: “The only thing missing in MRI is to show up implanted metallic devices.”

Devices such as gynecological catheters or prostate brachytherapy seeds are indispensable components of certain cancer treatments. Identifying the existence and location of these metal-based devices is critical in treatment planning and delivery, Yet, MRI shows up the devices as mysterious voids – difficult to distinguish from calcium or empty cavities. 

Removing CT from the Workflow

The current clinical workflow requires a computed tomography (CT) scan for its superior positive contrast in identifying “MR-invisible” metallic devices. After an MRI, patients are transferred to another room for a CT scan. The images are later registered together into one. 

The problem: “The patient is never in exactly the same position during the two scans,” Nosrati explains. “Errors in image registration and dose calculations can happen.” 

The two-step MR-CT based workflow does the job, but with a host of other drawbacks – time, cost and increased secondary cancer risk from radiation administered for CT scans. 

The solution: Combine the strengths of both into a single, MR-only process. Ideal concept, but actualizing it has been a moving target – various techniques coming close, but with logistical complications, inordinate expense or other encumbrances. 

Nosrati proposed a new method: Create positive contrast, and automate the identification of metal devices by using magnetic susceptibility as the source of positive contrast, and thus eliminate CT from the current workflow.

The method: Quantitative Susceptibility Mapping (QSM). Metal has positive magnetic susceptibility whereas biological tissues are negative. QSM is a relatively novel MR post-processing technique that quantifies magnetic susceptibility of different substances using MR images acquired by a specific protocol.


QSM – Making MR-Invisible Devices Visible

The team created phantoms (water-based models mimicking human tissue), and ran them through MR pulse sequences on 1.5T and 3T MR scanners. After developing QSM algorithms tailored to various types of metal devices, they processed the scans offline, measuring magnetic susceptibility at different voxels within the MR imaging volume. 

The result: images rivaling the fidelity of CT in visualizing and localizing metal devices, while preserving the superior soft-tissue contrast of MR. 

“The advantage of our technique is that it relies only on offline image post-processing,” Nosrati points out. “No extra cost, no extra radiation, and only five to ten minutes of extra MR scan time for the patient.”

Bringing the Research to Market

Having successfully demonstrated QSM’s feasibility and reliability on phantoms, the team is evaluating the process on patients. The impacts are promising: increased treatment accuracy, better use of resources, and improved patient outcomes.

“When we finished the study, it felt so great,” recalls Nosrati. “The best project for any PhD candidate is one that goes from phantoms and theories to actual clinic. Seeing this transition – how excited other oncologists and physicists are, how companies are interested – it’s very satisfying.”

Nosrati concludes: “Every improvement to the treatment process helps, but when you’ve developed something from scratch, something that will soon benefit patients – that’s rewarding.”  

Nosrati has been funded by the NSERC Alexander Graham Bell Canada Graduate Scholarships-Doctoral Program.