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Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings

Overview of attention for article published in Frontiers in oncology, February 2018
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Title
Microstructure Characterization of Bone Metastases from Prostate Cancer with Diffusion MRI: Preliminary Findings
Published in
Frontiers in oncology, February 2018
DOI 10.3389/fonc.2018.00026
Pubmed ID
Authors

Colleen Bailey, David J. Collins, Nina Tunariu, Matthew R. Orton, Veronica A. Morgan, Thorsten Feiweier, David J. Hawkes, Martin O. Leach, Daniel C. Alexander, Eleftheria Panagiotaki

Abstract

To examine the usefulness of rich diffusion protocols with high b-values and varying diffusion time for probing microstructure in bone metastases. Analysis techniques including biophysical and mathematical models were compared with the clinical apparent diffusion coefficient (ADC). Four patients were scanned using 13 b-values up to 3,000 s/mm2 and diffusion times ranging 18-52 ms. Data were fitted to mono-exponential ADC, intravoxel incoherent motion (IVIM), Kurtosis and Vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT) models. Parameters from the models were compared using correlation plots. ADC and IVIM did not fit the data well, failing to capture the signal at high b-values. The Kurtosis model best explained the data in many voxels, but in voxels exhibiting a more time-dependent signal, the VERDICT model explained the data best. The ADC correlated significantly (p < 0.004) with the intracellular diffusion coefficient (r = 0.48), intracellular volume fraction (r = -0.21), and perfusion fraction (r = 0.46) parameters from VERDICT, suggesting that these factors all contribute to ADC contrast. The mean kurtosis correlated with the intracellular volume fraction parameter (r = 0.26) from VERDICT, consistent with the hypothesis that kurtosis relates to cellularity, but also correlated weakly with the intracellular diffusion coefficient (r = 0.18) and cell radius (r = 0.16) parameters, suggesting that it may be difficult to attribute physical meaning to kurtosis. Both Kurtosis and VERDICT explained the diffusion signal better than ADC and IVIM, primarily due to poor fitting at high b-values in the latter two models. The Kurtosis and VERDICT models captured information at high b using parameters (Kurtosis or intracellular volume fraction and radius) that do not have a simple relationship with ADC and that may provide additional microstructural information in bone metastases.

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Mendeley readers

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The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 25%
Student > Ph. D. Student 10 25%
Student > Bachelor 3 8%
Student > Postgraduate 2 5%
Student > Master 2 5%
Other 4 10%
Unknown 9 23%
Readers by discipline Count As %
Medicine and Dentistry 10 25%
Physics and Astronomy 5 13%
Engineering 3 8%
Computer Science 2 5%
Neuroscience 1 3%
Other 1 3%
Unknown 18 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 March 2018.
All research outputs
#20,688,303
of 25,411,814 outputs
Outputs from Frontiers in oncology
#11,335
of 22,484 outputs
Outputs of similar age
#274,209
of 350,348 outputs
Outputs of similar age from Frontiers in oncology
#69
of 94 outputs
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