Researchers at the University of Waterloo have developed a new form of magnetic resonance imaging (MRI) that makes cancerous tissue glow in medical images, and could aid in more accurately detecting and tracking the progression of cancer. Known as synthetic correlated diffusion imaging (CDI), the new technology highlights the differences in the way water molecules move in cancerous tissue compared to healthy tissue, doing so by capturing, synthesizing, and mixing MRI signals at different gradient pulse strengths and timings.
In collaboration with the Lunenfeld-Tanenbaum Research Institute, the Ontario Institute for Cancer Research, and a number of Toronto-area hospitals, the team of Waterloo researchers applied the technology to 200 patients with prostate cancer.
In a study that appeared in Scientific Reports, the authors note that MRI has grown significantly in prevalence for the purpose of prostate cancer (PCa) screening, with preliminary studies demonstrating the potential of CDI for delineating between cancerous and non-cancerous tissues (2022; https://doi.org/10.1038/s41598-022-06872-7).
"However, the scope of these studies are limited in terms of patient cohort size and diversity, e.g., a patient cohort of 20 patient cases," the researchers wrote. "Furthermore, a number of limitations exist in CDI, as first introduced with respect to signal-to-noise ratio (SNR) and acquisition time, as well as SI variability amongst inter-patient and intra-patient acquisitions."
With a cohort of 200 cases, the Waterloo-led study represents the largest of its kind for exploring the relationship between the presence of PCa and CDI signal hyperintensity. CDI leverages a hybrid of native and synthetic diffusion signal acquisitions and signal calibration for greater consistency in dynamic range across machines and protocols. The researchers compared the performance of CDI for prostate cancer delineation to current standard MRI techniques-T2w imaging, diffusion-weighted imaging, and dynamic contrast enhanced imaging-with the aim of providing insights on the potential clinical impact of CDI as a diagnostic aid for improving prostate cancer screening.
The researchers investigated CDI's efficacy from two different perspectives. The authors studied the relationship between CDI and the presence of prostate cancer, both clinically significant prostate cancer tissue and clinically insignificant prostate cancer tissue. The researchers also studied the performance of CDI in delineating cancerous tissue from healthy tissue. Overall, they found that CDI was better at differentiating significant cancerous tissue from healthy tissue.
"MRI has been one of the main go-to technologies for detecting, localizing and tracking cancer, especially prostate cancer, given its sensitivity to different tissue types," noted lead study author Alexander Wong, PhD, PEng, SMIEEE, Professor in the Department of Systems Design Engineering at the University of Waterloo.
One of the key challenges faced in MRI-based cancer imaging, however, is that there are many cases in which certain tumor tissue characteristics exhibit very similar visual appearance in images captured using existing MRI modalities, he noted.
"This makes them appear 'invisible' to the radiologist and clinician looking at images produced using these modalities, as well as makes it hard to accurately localize the margins of the tumors," Wong explained. "Motivated by this, we tried to think out of the box and come up with a new form of MRI that would be tailored specifically for detecting and localizing cancer."
Wong and his colleagues hypothesized that the irregular cell densities exhibited in cancerous tumors leads to differences in the way water molecules move in cancerous tissue compared to healthy tissue. "Therefore, based on this hypothesis, we were hoping to design a new form of MRI that specifically captures these differences to make it easy to detect and localize cancer."
By using CDI to capture and mix MRI signals at the right water motion sensitivities and properly mixing them together, the researchers can capture and highlight differences in tissue cell density heterogeneities in the range that matters for differentiating between cancerous and healthy tissues.
"Using this new form of MRI allows cancerous tumors to 'light up' compared to surrounding healthy tissues in a clear and localized way, making it not only easier to detect the presence of cancer, but also accurately localize its margins," Wong stated.
Looking ahead, he envisions synthetic correlated diffusion imaging being used in "a very impactful way across the entire cancer care workflow." Starting from early screening of cancer to improve recovery and success rates, he also foresees CDI being able to monitor tumors as they progress over time to better comprehend the types of treatments that are most appropriate, as well as understanding the prognosis of a patient at different screening and monitoring steps.
CDI could also prove advantageous "for localizing tumors and their tumor margins for higher precision focal therapy," Wong explained, "as well as tracking changes to understand treatment response so radiation oncology teams can adjust treatment strategies and dosages for very precise, personalized cancer treatment."
Mark McGraw is a contributing writer.