Evidence map›Paper›PMID 38781243›Full record

ArticlePloS one2024

High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry.

Rohan Nadkarni, Zay Yar Han, Robert J Anderson, Alex J Allphin, Darin P Clark, Alexandra Badea, Cristian T Badea

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. 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

7 authors.

Rohan NadkarniQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
Zay Yar HanQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
Robert J AndersonQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
Alex J AllphinQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
Darin P ClarkQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
Alexandra BadeaQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
Cristian T BadeaQuantitative Imaging and Analysis Lab, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.ORCID 0000-0002-1850-2522

Funding

Sex and APOE genotype interact to alter immune regulated metabolism in ADRF1AG057895 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA, COLTON, CAROL ANNE · 2019 to 2019
$5.8M
Brain networks in mouse models of agingR01AG066184 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA · 2019 to 2023
$3.8M
Cardiac photon counting CT and its application in studying interactions between Alzheimer's and heart diseaseRF1AG070149 · NIA · DUKE UNIVERSITY · PI BADEA, CRISTIAN T · 2021 to 2022
$2.1M
Multiorgan Photon Counting CT and Machine Learning to Elucidate Aging Mechanisms and InterventionsR01AG070149 · NIA · DUKE UNIVERSITY · PI CRISTIAN T BADEA, Alexandra Badea · 2024 to 2026
$2.1M
Sex and APOE genotype interact to alter immune regulated metabolism in ADR56AG057895 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA, COLTON, CAROL ANNE · 2017 to 2017
$1.1M
NIA NIH HHS R01 AG066184NIA NIH HHS R01 AG070149NIA NIH HHS R56 AG057895NIA NIH HHS RF1 AG057895NIA NIH HHS RF1 AG070149
6 · The paper itself

Abstract

backgroundBrain region segmentation and morphometry in humanized apolipoprotein E (APOE) mouse models with a human NOS2 background (HN) contribute to Alzheimer's disease (AD) research by demonstrating how various risk factors affect the brain. Photon-counting detector (PCD) micro-CT provides faster scan times than MRI, with superior contrast and spatial resolution to energy-integrating detector (EID) micro-CT. This paper presents a pipeline for mouse brain imaging, segmentation, and morphometry from PCD micro-CT.

methodsWe used brains of 26 mice from 3 genotypes (APOE22HN, APOE33HN, APOE44HN). The pipeline included PCD and EID micro-CT scanning, hybrid (PCD and EID) iterative reconstruction, and brain region segmentation using the Small Animal Multivariate Brain Analysis (SAMBA) tool. We applied SAMBA to transfer brain region labels from our new PCD CT atlas to individual PCD brains via diffeomorphic registration. Region-based and voxel-based analyses were used for comparisons by genotype and sex.

resultsTogether, PCD and EID scanning take ~5 hours to produce images with a voxel size of 22 μm, which is faster than MRI protocols for mouse brain morphometry with voxel size above 40 μm. Hybrid iterative reconstruction generates PCD images with minimal artifacts and higher spatial resolution and contrast than EID images. Our PCD atlas is qualitatively and quantitatively similar to the prior MRI atlas and successfully transfers labels to PCD brains in SAMBA. Male and female mice had significant volume differences in 26 regions, including parts of the entorhinal cortex and cingulate cortex. APOE22HN brains were larger than APOE44HN brains in clusters from the hippocampus, a region where atrophy is associated with AD.

conclusionsThis work establishes a pipeline for mouse brain analysis using PCD CT, from staining to imaging and labeling brain images. Our results validate the effectiveness of the approach, setting a foundation for research on AD mouse models while reducing scanning durations.

Indexed as

BrainX-Ray MicrotomographyAlzheimer DiseaseAnimalsApolipoproteins EFemaleHumansImage Processing, Computer-AssistedMaleMiceMice, TransgenicApolipoproteins E

Identifiers

PMID38781243
PMCPMC11115241

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LicenceCC BY
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Registered trials

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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.