PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques

Journal article


Lillington, J., Brusaferri, L., Klaser, K., Shmueli, K., Neji, R., Hutton, B.F., Fraioli, F., Arridge, S., Cardoso, M.J., Ourselin, S., Thielemans, K. and Atkinson, D. (2019). PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques. Medical Physics. 47 (2), pp. 790-811. https://doi.org/10.1002/mp.13943
AuthorsLillington, J., Brusaferri, L., Klaser, K., Shmueli, K., Neji, R., Hutton, B.F., Fraioli, F., Arridge, S., Cardoso, M.J., Ourselin, S., Thielemans, K. and Atkinson, D.
Abstract

Positron emission tomography/magnetic resonance imaging (PET/MRI) potentially offers several advantages over positron emission tomography/computed tomography (PET/CT), for example, no CT radiation dose and soft tissue images from MR acquired at the same time as the PET. However, obtaining accurate linear attenuation correction (LAC) factors for the lung remains difficult in PET/MRI. LACs depend on electron density and in the lung, these vary significantly both within an individual and from person to person. Current commercial practice is to use a single-valued population-based lung LAC, and better estimation is needed to improve quantification. Given the under-appreciation of lung attenuation estimation as an issue, the inaccuracy of PET quantification due to the use of single-valued lung LACs, the unique challenges of lung estimation, and the emerging status of PET/MRI scanners in lung disease, a review is timely. This paper highlights past and present methods, categorizing them into segmentation, atlas/mapping, and emission-based schemes. Potential strategies for future developments are also presented.

Year2019
JournalMedical Physics
Journal citation47 (2), pp. 790-811
PublisherWiley
ISSN0094-2405
2473-4209
Digital Object Identifier (DOI)https://doi.org/10.1002/mp.13943
Web address (URL)http://dx.doi.org/10.1002/mp.13943
Publication dates
Online03 Dec 2019
Publication process dates
Accepted20 Nov 2019
Deposited08 Feb 2024
Publisher's version
License
File Access Level
Open
Permalink -

https://openresearch.lsbu.ac.uk/item/9654x

  • 13
    total views
  • 2
    total downloads
  • 2
    views this month
  • 1
    downloads this month

Export as

Related outputs

An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction
Twyman, R., Arridge, S., Kereta, Z., Jin, B., Brusaferri, L., Ahn, S., Stearns, C.W., Hutton, B., Burger, I.A., Kotasidis, F. and Thielemans, K. (2023). An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction. IEEE Transactions on Medical Imaging. pp. 29 - 41. https://doi.org/10.1109/tmi.2022.3203237
Neuroimmune activation and increased brain aging in chronic pain patients after the COVID-19 pandemic onset
Brusaferri, L., Alshelh, Z., Schnieders, J.H., Sandström, A., Mohammadian, M., Morrissey, E.J., Kim, M., Chane, C.A., Grmek, G.C., Murphy, J.P., Bialobrzewski, J., DiPietro, A., Klinke, J., Zhang, Y., Torrado-Carvajal, A., Mercaldo, N., Akeju, O., Wu, O., Rosen, B.R., Napadow, V., Hadjikhani, N. and Loggia, M.L. (2023). Neuroimmune activation and increased brain aging in chronic pain patients after the COVID-19 pandemic onset. Brain, Behavior and Immunity. 116, pp. 259-266. https://doi.org/10.1016/j.bbi.2023.12.016
The pandemic brain: Neuroinflammation in non-infected individuals during the COVID-19 pandemic
Brusaferri, L., Alshelh, Z., Martins, D., Kim, M., Weerasekera, A., Housman, H., Morrissey, E.J., Knight, P.C., Castro-Blanco, K.A., Albrecht, D.S., Tseng, C-E., Zürcher, N.R., Ratai, E-M., Akeju, O., Makary, M.M., Catana, C., Mercaldo, N.D., Hadjikhani, N., Veronese, M., Turkheimer, F., Rosen, B.R., Hooker, J.M. and Loggia, M.L. (2022). The pandemic brain: Neuroinflammation in non-infected individuals during the COVID-19 pandemic. Brain, behavior, and immunity. 102, pp. 89-87. https://doi.org/10.1016/j.bbi.2022.02.018
Improved PET/CT Respiratory Motion Compensation by Incorporating Changes in Lung Density
Emond, E.C., Bousse, A., Brusaferri, L., Hutton, B.F. and Thielemans, K. (2020). Improved PET/CT Respiratory Motion Compensation by Incorporating Changes in Lung Density. IEEE Transactions on Radiation and Plasma Medical Sciences. pp. 594 - 602. https://doi.org/10.1109/trpms.2020.3001094
Joint Activity and Attenuation Reconstruction From Multiple Energy Window Data With Photopeak Scatter Re-Estimation in Non-TOF 3-D PET
Brusaferri, L., Bousse, A., Emond, E.C., Brown, R., Tsai, Y-J., Atkinson, D., Ourselin, S., Watson, C.C., Hutton, B.F., Arridge, S. and Thielemans, K. (2020). Joint Activity and Attenuation Reconstruction From Multiple Energy Window Data With Photopeak Scatter Re-Estimation in Non-TOF 3-D PET. IEEE Transactions on Radiation and Plasma Medical Sciences. pp. 410 - 421. https://doi.org/10.1109/trpms.2020.2978449