Details

Autor(en) / Beteiligte

• Goubran, Maged
• Leuze, Christoph
• Hsueh, Brian
• Aswendt, Markus
• Ye, Li
• Tian, Qiyuan
• Cheng, Michelle Y.
• Crow, Ailey
• Steinberg, Gary K.
• McNab, Jennifer A.
• Deisseroth, Karl
• Zeineh, Michael

Titel

Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI

Ist Teil von

• Nature communications, 2019-12, Vol.10 (1), p.5504-17, Article 5504

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2019

Quelle

MEDLINE

Beschreibungen/Notizen

• 3D histology, slice-based connectivity atlases, and diffusion MRI are common techniques to map brain wiring. While there are many modality-specific tools to process these data, there is a lack of integration across modalities. We develop an automated resource that combines histologically cleared volumes with connectivity atlases and MRI, enabling the analysis of histological features across multiple fiber tracts and networks, and their correlation with in-vivo biomarkers. We apply our pipeline in a murine stroke model, demonstrating not only strong correspondence between MRI abnormalities and CLARITY-tissue staining, but also uncovering acute cellular effects in areas connected to the ischemic core. We provide improved maps of connectivity by quantifying projection terminals from CLARITY viral injections, and integrate diffusion MRI with CLARITY viral tracing to compare connectivity maps across scales. Finally, we demonstrate tract-level histological changes of stroke through this multimodal integration. This resource can propel investigations of network alterations underlying neurological disorders. Many approaches exist to process data from individual imaging modalities, but integrating them is challenging. The authors develop an automated resource that enables co-registered network- and tract-level analysis of macroscopic in-vivo imaging and microscopic imaging of cleared tissue.