MRI resolution enhanced at cellular level in key INI study
Danny JJ Wang, PhD, director of imaging technology innovation at INI, used a new cell-labeling technique to improve the visualization capacity of MRI. While each voxel in an MRI image typically represents tens of thousands of cells, Wang and his team were able to view clusters of less than 100 cells. The new method can be used to monitor the effectiveness of immune and stem-cell therapies used to treat various cancers. The results were published in the International Journal of Nanomedicine this spring.
Virtual reality tool designed at INI corrects errors in brain scan data
INI’s Virtual Brain Segmenter (VBS) turns segmentation—a tedious step in the analysis of brain scan data—into an immersive experience. The tool, developed by Dominique Duncan, PhD, Tyler Ard, PhD, Arthur W. Toga, PhD and RareFaction Interactive, allows researchers to use a VR headset and joystick to edit larger-than-life images of the brain derived from MRI data. In July, the team published its first assessment of VBS in the Journal of Digital Imaging, showing that the tool saves time and preserves accuracy in the segmentation process.
Exploring the link between inflammation, metabolic risk and brain aging
Paul M. Thompson, PhD, INI’s associate director and Meredith Braskie, PhD, coauthored a new study of age-related brain degeneration, published in NeuroImage in May. The study used MRI and clinical measures over a nine-year period to examine the link between physical activity, metabolic risk, genetic risk and brain aging. Results indicate that metabolic risk and peripheral inflammation both play a key role in the neurodegeneration central to Alzheimer’s disease and other dementias.
The genetic architecture of the human cerebral cortex
Neda Jahanshad, PhD, co-led a massive meta-analysis of the genetic architecture underlying the cerebral cortex in more than 15,500 people. Her team, which also included ENIGMA leader Paul M. Thompson and INI Director Arthur W. Toga, found 206 significant genetic loci and identified genetic correlations associated with altered brain structure in Parkinson’s disease, ADHD, insomnia and depression. A preprint of the article was posted online in September.
A systematic bias in diffusion tensor imaging (DTI) findings
INI researchers Farshid Sepehrband, PhD, Ryan Cabeen, PhD, Jeiran Choupan, PhD, Giuseppe Barisano and Arthur W. Toga, PhD, released a preprint of their latest paper in September. Their research shows how a systematic bias in DTI measures may compromise past findings, but also suggests a way to strengthen the clinical and scientific value of diffusion MRI by slightly altering how calculations are made.
Ben Duffy (left) earned his PhD in biomedical imaging from University College London. He is currently working on applying state-of-the-art machine learning methods for automated quality control and biomarker discovery. This year, he received the 2018 Mistletoe Foundation Fellowship as well as a Canadian Institute for Advanced Research (CIFAR) travel grant for the International Conference on Medical Imaging with Deep Learning.
Joey Contreras is a California native who received her PhD in medical neuroscience from Indiana University in 2017. Her research focuses on using connectomics and neuroimaging data to investigate the relationship between functional connectivity, structural connectivity and biomarkers for Alzheimer’s disease. In particular, she aims to identify the earliest stages of neurodegeneration and explore how various treatments can affect functional and structural connections in the brain. Her recent project explores the relationship between elevated levels of TNF-alpha, an inflammatory CSF marker, and aberrant functional connectivity in regions important for memory and cognition within APOE4 carriers.
Fabian Corlier obtained his PhD in neurobiology from the Sorbonne in Paris, France, where he used biomedical imaging and cellular biology tools to study the diagnosis and pathology of Alzheimer's disease. In his current role as a postdoctoral scholar at INI, Corlier studies the impact of systemic inflammation on brain structure using statistical modeling tools. In the future, he aims to integrate all levels of observation of the aging brain to reach a general understanding of aging, including how environmental effects and genetic background eventually lead to cognitive decline.