Evidence map›Paper›PMID 31367547›Full record

ArticleQuantitative imaging in medicine and surgery2019

Cortical bone vessel identification and quantification on contrast-enhanced MR images.

Po-Hung Wu, Matthew Gibbons, Sarah C Foreman, Julio Carballido-Gamio, Misung Han, Roland Krug, Jing Liu, Thomas M Link, Galateia J Kazakia

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PubMed Full text at PMC Publisher
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Augmenting Osteoporosis Imaging with Machine Learning.Current osteoporosis reports · 2021
    Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

9 authors.

Po-Hung WuDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Matthew GibbonsDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Sarah C ForemanDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Julio Carballido-GamioDepartment of Radiology, University of Colorado Denver, Denver, CO, USA.
Misung HanDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Roland KrugDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Jing LiuDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Thomas M LinkDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Galateia J KazakiaDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.

Funding

UCSF Core Center for Musculoskeletal Biology and MedicineP30AR066262 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MAJUMDAR, SHARMILA · 2014 to 2018
$3.0M
Progression and etiology of cortical porosity in diabetic bone diseaseR01AR069670 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAZAKIA, GALATEIA J · 2017 to 2023
$2.9M
In vivo imaging of cortical porosity in the peripheral skeletonK01AR056734 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAZAKIA, GALATEIA J · 2009 to 2013
$594k
Visualizing Cortical Pore Space ConstituentsR03AR064004 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KAZAKIA, GALATEIA J · 2013 to 2015
$186k
NIAMS NIH HHS K01 AR056734NIAMS NIH HHS P30 AR066262NIAMS NIH HHS R01 AR069670NIAMS NIH HHS R03 AR064004
6 · The paper itself

Abstract

backgroundCortical bone porosity is a major determinant of bone strength. Despite the biomechanical importance of cortical bone porosity, the biological drivers of cortical porosity are unknown. The content of cortical pore space can indicate pore expansion mechanisms; both of the primary components of pore space, vessels and adipocytes, have been implicated in pore expansion. Dynamic contrast-enhanced MRI (DCE-MRI) is widely used in vessel detection in cardiovascular studies, but has not been applied to visualize vessels within cortical bone. In this study, we have developed a multimodal DCE-MRI and high resolution peripheral QCT (HR-pQCT) acquisition and image processing pipeline to detect vessel-filled cortical bone pores.

methodsFor this

resultsIn the human study, mean vessel volume fraction was 2.2%±1.0%, mean vessel density was 0.68±0.27 vessel/mm

conclusionsWe have a developed a multi-modal image acquisition and processing pipeline that successfully detects vessels within cortical bone pores. The performance of this technique degrades for vessel diameters below the in-plane spatial resolution of the DCE-MRI acquisition. This approach can be applied to investigate the biological systems associated with cortical pore expansion.

Indexed as

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)high resolution peripheral quantitative computed tomography (HR-pQCT)kmeans clustering methodmagnetic resonance imaging phantom (MRI phantom)vessel detection

Identifiers

PMID31367547
PMCPMC6629562

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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.