A light-fluence-independent method for the quantitative analysis of dynamic contrast-enhanced multispectral optoacoustic tomography (DCE MSOT)

Thumbnail
Name:
1-s2.0-S2213597917300496-main.pdf
Size:
2.804Mb
Format:
PDF
Description:
Final Published version
Download
Author
Hupple, Clinton W.
Morscher, Stefan
Burton, Neal C.
Pagel, Mark D.
McNally, Lacey R.
Cárdenas-Rodríguez, Julio
Affiliation
Univ Arizona, Dept Med Imaging
Issue Date
2018-06
Keywords
Dynamic contrast enhanced imaging
Multispectral optoacoustic tomography
Pharmacokinetics models
Linear models
Permeability

Metadata
Show full item record
Publisher
ELSEVIER GMBH, URBAN & FISCHER VERLAG
Citation
Hupple, C. W., Morscher, S., Burton, N. C., Pagel, M. D., McNally, L. R., & Cárdenas-Rodríguez, J. (2018). A light-fluence-independent method for the quantitative analysis of dynamic contrast-enhanced multispectral optoacoustic tomography (DCE MSOT). Photoacoustics, 10, 54-64.
Journal
PHOTOACOUSTICS
Rights
© 2018 The Authors. Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
Abstract
MultiSpectral Optoacoustic Tomography (MSOT) is an emerging imaging technology that allows for data acquisition at high spatial and temporal resolution. These imaging characteristics are advantageous for Dynamic Contrast Enhanced (DCE) imaging that can assess the combination of vascular flow and permeability. However, the quantitative analysis of DCE MSOT data has not been possible due to complications caused by wavelength-dependent light attenuation and variability in light fluence at different anatomical locations. In this work we present a new method for the quantitative analysis of DCE MSOT data that is not biased by light fluence. We have named this method the two-compartment linear standard model (2C-LSM) for DCE MSOT. (C) 2018 The Authors. Published by Elsevier GmbH.
Note
Open access journal.
ISSN
22135979
PubMed ID
29988890
DOI
10.1016/j.pacs.2018.04.003
Version
Final published version
Sponsors
University of Arizona Cancer Center; National Institute of Health [R01CA167183, R01CA169774, P30CA023074]
Additional Links
https://linkinghub.elsevier.com/retrieve/pii/S2213597917300496
Collections
© 2018 The Authors. Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Except where otherwise noted, this item's license is described as © 2018 The Authors. Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).