Evidence map›Paper›PMID 31394180›Full record

ArticleNeuroImage2019

Dynamic Contrast Optical Coherence Tomography reveals laminar microvascular hemodynamics in the mouse neocortex in vivo.

Conrad W Merkle, Jun Zhu, Marcel T Bernucci, Vivek J Srinivasan

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Circumscribing Laser Cuts Attenuate Seizure Propagation in a Mouse Model of Focal Epilepsy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  6. Review
  7. Optical measurement of microvascular oxygenation and blood flow responses in awake mouse cortex during functional activation.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
    Article
  8. Review
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Conrad W MerkleDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Jun ZhuDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Marcel T BernucciDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Vivek J SrinivasanDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA; Department of Ophthalmology and Vision Science, University of California Davis School of Medicine, Sacramento, CA, 95817, USA. Electronic address: vjsriniv@ucdavis.edu.
University of California, Davis · US

Funding

UC Davis Alzheimer's Disease Core CenterP30AG010129 · NIA · UNIVERSITY OF CALIFORNIA DAVIS · PI DECARLI, CHARLES · 1991 to 2020
$28.3M
Imaging Neuronal and Capillary Dysfunction Deep in the Rodent Brain in vivo Using 1700 NM Optical Coherence Microscopy and Tracer-Based KineticsR01NS094681 · NINDS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SRINIVASAN, VIVEK JAY · 2015 to 2019
$1.6M
Development, Validation and Application of Metabolic Imaging in GlaucomaR01EY028287 · NEI · STANFORD UNIVERSITY · PI DUBRA, ALFREDO, GOLDBERG, JEFFREY L · 2017 to 2019
$1.1M
Interferometric Near-Infrared Spectroscopy for Tissue Flowmetry and OximetryR21NS105043 · NINDS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SRINIVASAN, VIVEK JAY · 2017 to 2018
$432k
Improving penetration depth and spatial resolution for in vivo deep imaging of mouse brain using 2200 nm Optical Coherence MicroscopyR03EB023591 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SRINIVASAN, VIVEK JAY · 2017 to 2018
$157k
NEI NIH HHS R01 EY028287NIA NIH HHS P30 AG010129NIBIB NIH HHS R03 EB023591NINDS NIH HHS R01 NS094681NINDS NIH HHS R21 NS105043
6 · The paper itself

Abstract

Studies of flow-metabolism coupling often presume that microvessel architecture is a surrogate for blood flow. To test this assumption, we introduce an in vivo Dynamic Contrast Optical Coherence Tomography (DyC-OCT) method to quantify layer-resolved microvascular blood flow and volume across the full depth of the mouse neocortex, where the angioarchitecture has been previously described. First, we cross-validate average DyC-OCT cortical flow against conventional Doppler OCT flow. Next, with laminar DyC-OCT, we discover that layer 4 consistently exhibits the highest microvascular blood flow, approximately two-fold higher than the outer cortical layers. While flow differences between layers are well-explained by microvascular volume and density, flow differences between subjects are better explained by transit time. Finally, from layer-resolved tracer enhancement, we also infer that microvascular hematocrit increases in deep cortical layers, consistent with predictions of plasma skimming. Altogether, our results show that while the cortical blood supply derives mainly from the pial surface, laminar hemodynamics ensure that the energetic needs of individual cortical layers are met. The laminar trends reported here provide data that links predictions based on the cortical angioarchitecture to cerebrovascular physiology in vivo.

Indexed as

Models, NeurologicalAnimalsCerebrovascular CirculationHemodynamicsMaleMiceMice, Inbred C57BLMicrovesselsNeocortexTomography, Optical CoherenceCortexDynamic contrastHematocritMicrovascular blood flowMicrovascular blood volumeOptical imaging

Identifiers

PMID31394180
PMCPMC6819266
OpenAlexW2965293317

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.