Longitudinal Awake Imaging of Deep Mouse Brain Microvasculature with Super-resolution Ultrasound Localization Microscopy

核心概念

ULM imaging in awake mice reveals significant vascular changes from anesthesia to awake states, enabling longitudinal studies.

摘要

• Abstract: Introduces ULM imaging in awake mouse brains to address confounding effects of anesthesia.
• Introduction: Discusses the importance of brain imaging and the challenges in neuroscience research.
• Data Extraction:
  • "ULM quantifications may be confounded by anesthesia, undermining its usefulness."
  • "Pupillary monitoring confirms the awake state during ULM imaging."
  • "Significant reduction in venous blood flow velocity across different brain regions under awake conditions."
• Quotations:
  • "This is the first study demonstrating longitudinal ULM imaging in the awake mouse brain."
• Results:
  • Demonstrates motion-free ULM brain imaging using a head-fixed platform.
  • Utilizes microbubble count as a quantitative metric for ULM image reconstruction.
• Discussion:
  • Addresses limitations and challenges of ULM imaging in awake mice.
  • Highlights the potential of longitudinal awake ULM for neuroscience research.

统计

"ULM quantifications may be confounded by anesthesia, undermining its usefulness."
"Pupillary monitoring confirms the awake state during ULM imaging."
"Significant reduction in venous blood flow velocity across different brain regions under awake conditions."

引用

"This is the first study demonstrating longitudinal ULM imaging in the awake mouse brain."

从中提取的关键见解

Longitudinal Awake Imaging of Deep Mouse Brain Microvasculature with Super-resolution Ultrasound Localization Microscopy

by Wang,Y., Low... 在 www.biorxiv.org 09-05-2023

https://www.biorxiv.org/content/10.1101/2023.09.01.555789v1

更深入的查询

How does long-term longitudinal ULM imaging impact our understanding of cerebral vasculature dynamics

Long-term longitudinal ULM imaging significantly impacts our understanding of cerebral vasculature dynamics by providing insights into the structural and functional changes that occur over time. This type of imaging allows researchers to track alterations in vessel diameter, density, and blood flow velocity within the same subject across multiple time points. By observing these changes longitudinally, researchers can gain a deeper understanding of how cerebral vasculature adapts and responds to various physiological conditions or interventions.
Furthermore, longitudinal ULM imaging enables the identification of trends and patterns in vascular dynamics that may not be apparent from single-time-point studies. Researchers can analyze how different regions of the brain respond differently over time, leading to a more comprehensive understanding of cerebrovascular physiology.

What are potential implications of these findings for clinical applications involving cerebral microvasculature

The findings from long-term longitudinal ULM imaging studies have significant implications for clinical applications involving cerebral microvasculature. Understanding the dynamic changes in vessel diameter, density, and blood flow velocity over time can provide valuable information for diagnosing and monitoring neurological disorders such as stroke, Alzheimer's disease, or vascular dementia.
For example, these findings could help clinicians assess the progression of neurodegenerative diseases by tracking changes in cerebral blood flow patterns longitudinally. Additionally, insights gained from longitudinal ULM studies could aid in developing personalized treatment strategies based on individual variations in cerebrovascular dynamics.
Moreover, advancements in awake and longitudinal ULM imaging techniques offer new possibilities for studying drug effects on cerebral microvasculature without confounding factors introduced by anesthesia. This has implications for preclinical research aimed at evaluating novel therapies targeting cerebrovascular function.

How might advancements in 3D ULM technology enhance longitudinal studies and classification accuracy of vessels

Advancements in 3D ULM technology have the potential to enhance longitudinal studies and improve classification accuracy of vessels by addressing some limitations associated with 2D imaging techniques. With 3D ULM technology, researchers can capture volumetric data sets that allow for better visualization of complex vascular networks throughout the entire brain volume.
In terms of longitudinal studies using 3D ULM technology, researchers can overcome challenges related to identifying identical coronal planes across different imaging sessions by reconstructing consistent 3D images with accurate alignment between scans taken at different time points. This ensures precise comparisons of vascular features over time without misalignment issues common with traditional 2D approaches.
Additionally, advancements in 3D ULM technology enable more accurate classification of vessels into arteries, veins,
and capillaries based on their spatial relationships within a three-dimensional space rather than relying solely on directional flow information as done with conventional 2D methods.
This enhanced classification accuracy contributes to a more detailed characterization
of cerebrovascular networks during awake
and behaving states across multiple weeks,
providing valuable insights into dynamic
changes occurring within these intricate systems over extended periods.