Feasibility study of a new approach for reducing of partial volume averaging artifact in CT scanner

Author(s):  
Hosein Arabi ◽  
Ali Reza Kamali Asl
1996 ◽  
Vol 16 (4) ◽  
pp. 650-658 ◽  
Author(s):  
Carolyn Cidis Meltzer ◽  
Jon Kar Zubieta ◽  
Jonathan M. Links ◽  
Paul Brakeman ◽  
Martin J. Stumpf ◽  
...  

Partial volume and mixed tissue sampling errors can cause significant inaccuracy in quantitative positron emission tomographic (PET) measurements. We previously described a method of correcting PET data for the effects of partial volume averaging on gray matter (GM) quantitation; however, this method may incompletely correct GM structures when local tissue concentrations are highly heterogeneous. We have extended this three-compartment algorithm to include a fourth compartment: a GM volume of interest (VOI) that can be delineated on magnetic resonance (MR) imaging. Computer simulations of PET images created from human MR data demonstrated errors of up to 120% in assigned activity values in small brain structures in uncorrected data. Four-compartment correction achieved full recovery of a wide range of coded activity in GM VOIs such as the amygdala, caudate, and thalamus. Further validation was performed in an agarose brain phantom in actual PET acquisitions. Implementation of this partial volume correction approach in [18F]fluorodeoxyglucose and [11C]-carfentanil PET data acquired in a healthy elderly human subject was also performed. This newly developed MR-based partial volume correction algorithm permits the accurate determination of the true radioactivity concentration in specific structures that can be defined by MR by accounting for the influence of heterogeneity of GM radioactivity.


2015 ◽  
Vol 42 (6Part34) ◽  
pp. 3620-3621
Author(s):  
P Xu ◽  
X Xing ◽  
J Zheng ◽  
S Chen ◽  
Y Zhang ◽  
...  

2012 ◽  
Vol 31 (2) ◽  
pp. 405-416 ◽  
Author(s):  
S. C. Moore ◽  
S. Southekal ◽  
Mi-Ae Park ◽  
S. J. McQuaid ◽  
M. F. Kijewski ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Julien Poublanc ◽  
Reema Shafi ◽  
Olivia Sobczyk ◽  
Kevin Sam ◽  
Daniel M. Mandell ◽  
...  

Cerebrovascular reactivity (CVR) is defined as the change in cerebral blood flow induced by a change in a vasoactive stimulus. CVR using BOLD MRI in combination with changes in end-tidal CO2 is a very useful method for assessing vascular performance. In recent years, this technique has benefited from an advanced gas delivery method where end-tidal CO2 can be targeted, measured very precisely, and validated against arterial blood gas sampling (Ito et al., 2008). This has enabled more precise comparison of an individual patient against a normative atlas of healthy subjects. However, expected control ranges for CVR metrics have not been reported in the literature. In this work, we calculate and report the range of control values for the magnitude (mCVR), the steady state amplitude (ssCVR), and the speed (TAU) of the BOLD response to a standard step stimulus, as well as the time delay (TD) as observed in a cohort of 45 healthy controls. These CVR metrics maps were corrected for partial volume averaging for brain tissue types using a linear regression method to enable more accurate quantitation of CVR metrics. In brief, this method uses adjacent voxel CVR metrics in combination with their tissue composition to write the corresponding set of linear equations for estimating CVR metrics of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). After partial volume correction, mCVR and ssCVR increase as expected in gray matter, respectively, by 25 and 19%, and decrease as expected in white matter by 33 and 13%. In contrast, TAU and TD decrease in gray matter by 33 and 13%. TAU increase in white matter by 24%, but TD surprisingly decreased by 9%. This correction enables more accurate voxel-wise tissue composition providing greater precision when reporting gray and white matter CVR values.


2003 ◽  
pp. 6-11 ◽  
Author(s):  
John M. Boone ◽  
Karen K. Lindfors ◽  
James A. Seibert ◽  
Thomas R. Nelson

Sign in / Sign up

Export Citation Format

Share Document