Researchers at Boston University“s Chobanian & Avedisian School of Medicine and the College of Engineering have developed a groundbreaking imaging technique that accurately detects myelin damage in brain tissue. Utilizing a specialized microscope known as birefringence microscopy (BRM) along with an automated deep learning algorithm, the team can now efficiently count and map myelin damage across entire brain sections, a feat that previous methods were unable to achieve.
Myelin serves as an insulating layer around brain cells, crucial for maintaining optimal brain function. Damage to myelin is commonly observed in various neurodegenerative diseases, as well as in the aging process and following traumatic injuries. Traditionally, electron microscopy has been regarded as the gold standard for imaging myelin structures, yet its impracticality for large-scale studies has limited its use due to its narrow field of view and the labor-intensive sample preparation it requires.
According to Alex Gray, the corresponding author and a recent PhD graduate in Biomedical Engineering from Boston University, “A major advantage of BRM over conventional imaging methods is its ability to rapidly image large areas at high resolution without special staining, making it uniquely suited for studying widespread myelin pathology.” Gray”s background in biomedical optics, honed under the mentorship of Professor Irving Bigio, has significantly contributed to this research. He is currently a research scientist at Analog Devices, focusing on innovative healthcare technologies.
In their study, Gray and his colleagues combined BRM with deep learning techniques to investigate myelin damage in various neurodegenerative models, specifically examining conditions where such damage is linked to cognitive impairments and loss of motor functions. In experiments simulating stroke-like brain injury, this innovative approach enabled rapid scanning of extensive brain tissue areas and facilitated automatic quantification of myelin damage, eliminating the need for complex staining processes.
The findings revealed that treatment with stem-cell-derived vesicles could effectively reduce myelin damage or promote its repair. Such outcomes, which would be challenging to ascertain via other imaging modalities, underscore the potential of this technique to assist researchers in understanding the mechanisms behind myelin damage across different neurodegenerative diseases. This method may also aid in evaluating therapies for conditions such as stroke, Alzheimer”s disease, and multiple sclerosis.
For more details, the complete study is available in the journal Neurophotonics.
