AI detects gender differences in brain structure with MRI: study

Machine Learning


The microscopic connections between brain cells change based on biological sex, according to a new study that used machine learning to analyze MRI data from hundreds of healthy volunteers.

Researchers said the findings may help explain why neurological diseases such as multiple sclerosis (MS) often differ by gender.

“Our findings provide a clearer picture of how the living human brain is structured, and thereby provide insight into how many psychiatric and neurological disorders develop and This could provide new insights into why symptoms manifest differently in men and women.” Yvonne Louissaid study lead author M.D. from New York University (NYU) in a press release.

the study, “Deep learning using diffusion MRI as well as intravital microscopy reveals gender-related differences in human white matter microstructure” was published. scientific report.

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A scientist works in a laboratory with a Petri dish next to a rack containing four vials of liquid.

MS is more common in women than men

Multiple sclerosis is more common in women than men, but other neurological conditions such as Tourette syndrome and autism spectrum disorders are diagnosed more often in men. The reasons for gender and gender-based differences in neurological conditions are not fully understood.

Previous studies have investigated large-scale brain structural differences between men and women, such as the size of various brain regions. Although there is much variation and overlap, some important trends have been observed that suggest biological sex may influence large-scale brain development.

In this study, the researchers wanted to examine whether biological sex also influences small-scale brain structures (individual connections between nerve cells) using an imaging technique called diffusion MRI. I thought about it.

“A better understanding of the underlying sex differences in the microstructure of the brain could help us understand how biological sex influences brain health and disease,” the researchers wrote.

The researchers analyzed data from 471 men and 560 women, all of whom were cisgender (meaning men were assigned male at birth and women were assigned female at birth). Ages ranged from 22 to 37 years.

To examine brain differences between genders, the researchers used three different machine learning tools. These tools work by inputting some of the MRI data, along with information about each scan's biological sex, into a computer that uses mathematical rules called algorithms to “learn” patterns. identify.

The computer then applies those “learned” patterns to the rest of the data set, attempting to predict biological sex based solely on the brain scan.

AI tools reveal brain characteristics that tend to differ based on biological sex

The researchers found that the accuracy ranged from 92% to 98%, depending on the specific machine learning tool used. Therefore, although no model has been able to completely distinguish between men and women based on the brain alone, it is likely that there are brain characteristics that tend to differ based on biological sex.

“These results highlight the importance of diversity when studying diseases that occur in the human brain.” Junbo Chena doctoral candidate at New York University and lead author of the study.

The main limitation of machine learning is that you can't share what patterns computers are “seeing” to make decisions. As such, these findings suggest that there are meaningful differences between the sexes, but it is not clear what exactly those differences are.

To gain insight, the researchers conducted occlusion analysis and retrained machine learning tools using incomplete MRI data. The results showed that removing data about central or anterior brain regions significantly reduced accuracy. This means that these areas are the main areas where differences exist.

“When men are used as the standard model for various diseases, as has been the case historically, researchers can miss important insights,” said study co-author Vara, a graduate research assistant at New York University.・Lakshmi Bayanagari said.

The researchers stressed that the specific differences still need to be determined, and further research is needed to determine whether they influence the development of diseases such as MS. Because this study was limited to cisgender youth, more research is needed to examine how biological sex affects brain development in other age groups.



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