Literature DB >> 8964805

MR-based correction of brain PET measurements for heterogeneous gray matter radioactivity distribution.

C C Meltzer1, J K Zubieta, J M Links, P Brakeman, M J Stumpf, J J Frost.   

Abstract

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.

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Year:  1996        PMID: 8964805     DOI: 10.1097/00004647-199607000-00016

Source DB:  PubMed          Journal:  J Cereb Blood Flow Metab        ISSN: 0271-678X            Impact factor:   6.200


  27 in total

1.  Fusion of coregistered cross-modality images using a temporally alternating display method.

Authors:  J S Lee; B Kim; Y Chee; C Kwark; M C Lee; K S Park
Journal:  Med Biol Eng Comput       Date:  2000-03       Impact factor: 2.602

2.  Noise propagation in resolution modeled PET imaging and its impact on detectability.

Authors:  Arman Rahmim; Jing Tang
Journal:  Phys Med Biol       Date:  2013-09-13       Impact factor: 3.609

3.  Aging and the interaction of sensory cortical function and structure.

Authors:  Ann M Peiffer; Christina E Hugenschmidt; Joseph A Maldjian; Ramon Casanova; Ryali Srikanth; Satoru Hayasaka; Jonathan H Burdette; Robert A Kraft; Paul J Laurienti
Journal:  Hum Brain Mapp       Date:  2009-01       Impact factor: 5.038

Review 4.  Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls.

Authors:  Arman Rahmim; Jinyi Qi; Vesna Sossi
Journal:  Med Phys       Date:  2013-06       Impact factor: 4.071

5.  Different partial volume correction methods lead to different conclusions: An (18)F-FDG-PET study of aging.

Authors:  Douglas N Greve; David H Salat; Spencer L Bowen; David Izquierdo-Garcia; Aaron P Schultz; Ciprian Catana; J Alex Becker; Claus Svarer; Gitte M Knudsen; Reisa A Sperling; Keith A Johnson
Journal:  Neuroimage       Date:  2016-02-23       Impact factor: 6.556

6.  Characterizing regional correlation, laterality and symmetry of amyloid deposition in mild cognitive impairment and Alzheimer's disease with Pittsburgh Compound B.

Authors:  Cyrus A Raji; James T Becker; Nicholas D Tsopelas; Julie C Price; Chester A Mathis; Judith A Saxton; Brian J Lopresti; Jessica A Hoge; Scott K Ziolko; Steven T DeKosky; William E Klunk
Journal:  J Neurosci Methods       Date:  2008-05-16       Impact factor: 2.390

7.  Partial-volume effect correction in positron emission tomography brain scan image using super-resolution image reconstruction.

Authors:  T Meechai; S Tepmongkol; C Pluempitiwiriyawej
Journal:  Br J Radiol       Date:  2014-12-10       Impact factor: 3.039

8.  Relative 11C-PiB Delivery as a Proxy of Relative CBF: Quantitative Evaluation Using Single-Session 15O-Water and 11C-PiB PET.

Authors:  Yin J Chen; Bedda L Rosario; Wenzhu Mowrey; Charles M Laymon; Xueling Lu; Oscar L Lopez; William E Klunk; Brian J Lopresti; Chester A Mathis; Julie C Price
Journal:  J Nucl Med       Date:  2015-06-04       Impact factor: 10.057

Review 9.  Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods.

Authors:  Tonghe Wang; Yang Lei; Yabo Fu; Walter J Curran; Tian Liu; Jonathon A Nye; Xiaofeng Yang
Journal:  Phys Med       Date:  2020-07-29       Impact factor: 2.685

10.  Multimodal partial volume correction: Application to [11C]PIB PET/MRI myelin imaging in multiple sclerosis.

Authors:  Elisabetta Grecchi; Mattia Veronese; Benedetta Bodini; Daniel García-Lorenzo; Marco Battaglini; Bruno Stankoff; Federico E Turkheimer
Journal:  J Cereb Blood Flow Metab       Date:  2017-06-01       Impact factor: 6.200

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