Sethu K Boopathy Jegathambal, Stefano Bambace, Sarah Kim, Junqi Wang, Angela Xiaomeng Zhu, Gurucharan Marthi Krishna Kumar, Ziqi Hao, Han Ru Liu, Aleksandra Bortel, Jérémie P Fouquet, David A Rudko, Amir Shmuel
Our proposed methods optimize the placement of the specimen, control the roll of the specimen, streamline the process, significantly shorten the setup time of ex vivo MRI, and increase the quality and utility of the data.
PURPOSE: Positioning and stabilizing a specimen in a container in preparation for ex vivo MRI are challenging. In addition, ex vivo MRI is often performed using preclinical scanners with gradient nonlinearity and nonhomogeneous sensitivity, requiring optimal placement.
METHODS: We present methods and software for streamlining the positioning of a specimen in preparation for ex vivo MRI using a specimen-specific and container-specific 3D-printed model for holding the brain. We use a 3D laser scanner to map the surface of the brain. Then, a 3D-printed brain-specific and container-specific model is created, with profiles that match the surface of the brain on one end and the inner surface of the container on the other end. The brain holder is designed to maintain the brain stable while allowing sufficient contact with the immersion fluid. Moreover, by applying a design that controls the specimen's roll, the method allows for determining the orientation of the brain relative to a template and/or the axes of the scanner and imaging the brain in this predetermined orientation. The positioning of the brain is optimized to achieve minimal distortions and/or high signal intensity.
RESULTS: We demonstrate these novel methods using macaque, marmoset, and rat brains; however, the methods and software can be easily generalized to brains of other specimens, including human brains or parts of a human brain.
CONCLUSION: Our proposed methods optimize the placement of the specimen, control the roll of the specimen, streamline the process, significantly shorten the setup time of ex vivo MRI, and increase the quality and utility of the data.