Optical microscopy imaging is one of the most powerful approaches for probing the organization of brain tissue at a cellular and sub-cellular level. Several techniques are available, each with their own advantages and disadvantages in terms of spatial resolution, field-of-view, molecular specificity, and invasiveness of sample preparation.
The SMART BRAIN project proposes to advance the complementary measurement of neuronal tissue by different optical imaging technologies, and to develop the subsequent in silico integration of different images by means of data-driven multimodal image fusion.
This process will combine advantages from the different source modalities into a single predictive imaging modality. We will integrate 3-D multiphoton microscopy (MPM) data with 3-D light-sheet microscopy (LSM) measurements to deliver a single ‘fused’ predictive imaging modality that delivers the molecular specificity of LSM, but with the less invasive sample preparation of MPM. The fused modality thus avoids the invasive clearing procedure, when tissue needs to be safeguarded for different analyses, or allows further molecular targeting in post- multiphoton light-sheet. We will explore other modality combinations, such as the fusion of MPM with super-resolution microscopy (STED), seeking to predict 2-D multiphoton tissue observations at up to 10x the diffraction limit. This project’s unique multidisciplinary approach has the potential to provide an organizational description of brain tissue that surpasses what any single imaging technique can provide. The proposed approach is based on advanced algorithms originally developed for integration between proteomic and lipidomic 2-D imaging mass spectrometry and standard 2-D stained microscopy, for which proof-of-concepts were demonstrated in murine brain tissue. In the SMART BRAIN project, these mathematical methods will be extended for fusion of multiphoton, light-sheet and STED microscopy.
The goal is to discover and model relationships between observations in the different modalities and predict morphological information either with spatial resolutions lying beyond physical limitations or in tissue areas where not all data types are available. Fusion of different datasets will be initially demonstrated in murine brain tissue, and subsequently extended to human brain samples. Specimens, provided by the neurosurgery partners in the consortium will be obtained from patients showing temporal lobe epilepsy and block of hippocampus and amygdala, as well as from autopsy of healthy subjects.
The SMART BRAIN project will: i) provide an innovative tool significantly improving currently available performances of optical microscopy ii) support the HBP consortium with a previously unavailable datasets and information on the morphology of the human brain iii) provide an instrument to be combined with clinical imaging for an advanced diagnostic tool.
Time frame: 2020 to 2022
Origin: FLAG-ERA JTC2019
Funding: MIUR, ANR, NOW