Database of normal human cerebral blood flow measured by SPECT: II. Quantification of I-123-IMP studies with ARG method and effects of partial volume correction

2006 ◽  
Vol 20 (2) ◽  
pp. 139-146 ◽  
Author(s):  
Kentaro Inoue ◽  
Hiroshi Ito ◽  
Miho Shidahara ◽  
Ryoi Goto ◽  
Shigeo Kinomura ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Partial Volume Correction ◽  
Partial Volume ◽  
Volume Correction ◽  
Normal Human

Cerebral blood flow in temporal lobe epilepsy: a partial volume correction study

2007 ◽  
Vol 34 (12) ◽  
pp. 2066-2072 ◽  
Author(s):  
Giampiero Giovacchini ◽  
Robert Bonwetsch ◽  
Peter Herscovitch ◽  
Richard E. Carson ◽  
William H. Theodore
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Partial Volume Correction ◽  
Partial Volume ◽  
Volume Correction

scholarly journals Corrigendum

2018 ◽  
Vol 38 (6) ◽  
pp. 1120-1120
Keyword(s):  
Blood Flow ◽  
Partial Volume Correction ◽  
Automatic Extraction ◽  
Reference Region ◽  
Partial Volume ◽  
Volume Correction ◽  
Cereb Blood Flow ◽  
Reproducibility Study ◽  
Positron Emission ◽  
Myelin Imaging

Grecchi E, Veronese M, Bodini B, et al. Multimodal partial volume correction: Application to [11C]PIB PET/MRI myelin imaging in multiple sclerosis. J Cereb Blood Flow Metab 2017; 37: 3803–3817. Three references in the above article appeared with typesetting coding when published online and in print. The references should have appeared as follows: 8. Aston JAD, Cunningham VJ, Asselin M-C, et al. Positron emission tomography partial volume correction: estimation and algorithms. J Cereb Blood Flow Metab 2002; 22: 1019–1034. 20. Veronese M, Bodini B, García-Lorenzo D, et al. Quantification of [11C]PIB PET for imaging myelin in the human brain: a test–retest reproducibility study in high-resolution research tomography. J Cereb Blood Flow Metab 2015; 35: 1771–1782. 30. Ikoma Y, Edison P, Ramlackhansingh A, et al. Reference region automatic extraction in dynamic [11C]PIB. J Cereb Blood Flow Metab 2013; 33: 1725–1731.

3D phase contrast MRI: Partial volume correction for robust blood flow quantification in small intracranial vessels

2017 ◽  
Vol 79 (1) ◽  
pp. 129-140 ◽  
Author(s):  
Pierre Bouillot ◽  
Bénédicte M. A. Delattre ◽  
Olivier Brina ◽  
Rafik Ouared ◽  
Mohamed Farhat ◽  
...  
Keyword(s):  
Blood Flow ◽  
Phase Contrast ◽  
Partial Volume Correction ◽  
Flow Quantification ◽  
Phase Contrast Mri ◽  
Blood Flow Quantification ◽  
Partial Volume ◽  
Volume Correction

scholarly journals Corrigendum

2018 ◽  
Vol 38 (6) ◽  
pp. 1119-1119
Keyword(s):  
Multiple Sclerosis ◽  
Blood Flow ◽  
Myelin Sheath ◽  
Partial Volume Correction ◽  
Partial Volume ◽  
Volume Correction ◽  
Cereb Blood Flow ◽  
Myelin Imaging

Grecchi E, Veronese M, Bodini B, et al. Multimodal partial volume correction: Application to [11C]PIB PET/MRI myelin imaging in multiple sclerosis. J Cereb Blood Flow Metab 2017; 37: 3803–3817. The label to Figure 1 in the above article should have read ‘Myelin Sheath’, not ‘Myelin Sheat’. The figure with the correct label appears below. This error also appeared on the reproduction of the figure on the cover of the December 2017 issue of the journal, volume 37, issue 12.

Segmentation-Based Partial Volume Correction for Volume Estimation of Solid Lesions in CT

2014 ◽  
Vol 33 (2) ◽  
pp. 462-480 ◽  
Author(s):  
Frank Heckel ◽  
Hans Meine ◽  
Jan H. Moltz ◽  
Jan-Martin Kuhnigk ◽  
Johannes T. Heverhagen ◽  
...  
Keyword(s):  
Volume Estimation ◽  
Partial Volume Correction ◽  
Partial Volume ◽  
Volume Correction ◽  
Solid Lesions

scholarly journals The effect of calibration factors and recovery coefficients on 177Lu SPECT activity quantification accuracy: a Monte Carlo study

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Keamogetswe Ramonaheng ◽  
Johannes A. van Staden ◽  
Hanlie du Raan
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Partial Volume Correction ◽  
Detector Response ◽  
Physical Size ◽  
Partial Volume ◽  
Volume Correction ◽  
Radioactive Water ◽  
Quantification Accuracy ◽  
Cylindrical Volume

Abstract Background Different gamma camera calibration factor (CF) geometries have been proposed to convert SPECT data into units of activity concentration. However, no consensus has been reached on a standardised geometry. The CF is dependent on the selected geometry and is further affected by partial volume effects. This study investigated the effect of two CF geometries and their corresponding recovery coefficients (RCs) on the quantification accuracy of 177Lu SPECT images using Monte Carlo simulations. Methods The CF geometries investigated were (i) a radioactive-sphere surrounded by non-radioactive water (sphere-CF) and (ii) a cylindrical phantom uniformly filled with radioactive water (cylinder-CF). Recovery coefficients were obtained using the sphere-CF and cylinder-CF, yielding the sphere-RC and cylinder-RC values, respectively, for partial volume correction (PVC). The quantification accuracy was evaluated using four different-sized spheres (15.6–65.4 ml) and a kidney model with known activity concentrations inside a cylindrical, torso and patient phantom. Images were reconstructed with the 3D OS-EM algorithm incorporating attenuation, scatter and detector-response corrections. Segmentation was performed using the physical size and a small cylindrical volume inside the cylinder for the sphere-CF and cylinder-CF, respectively. Results The sphere quantification error (without PVC) was better for the sphere-CF (≤ − 5.54%) compared to the cylinder-CF (≤ − 20.90%), attributed to the similar geometry of the quantified and CF spheres. Partial volume correction yielded comparable results for the sphere-CF-RC (≤ 3.47%) and cylinder-CF-RC (≤ 3.53%). The accuracy of the kidney quantification was poorer (≤ 22.34%) for the sphere-CF without PVC compared to the cylinder-CF (≤ 2.44%). With PVC, the kidney quantification results improved and compared well for the sphere-CF-RC (≤ 3.50%) and the cylinder-CF-RC (≤ 3.45%). Conclusion The study demonstrated that upon careful selection of CF-RC combinations, comparable quantification errors (≤ 3.53%) were obtained between the sphere-CF-RC and cylinder-CF-RC, when all corrections were applied.

scholarly journals MR-Based Correction of Brain PET Measurements for Heterogeneous Gray Matter Radioactivity Distribution

1996 ◽  
Vol 16 (4) ◽  
pp. 650-658 ◽  
Author(s):  
Carolyn Cidis Meltzer ◽  
Jon Kar Zubieta ◽  
Jonathan M. Links ◽  
Paul Brakeman ◽  
Martin J. Stumpf ◽  
...  
Keyword(s):  
Gray Matter ◽  
Accurate Determination ◽  
Brain Structures ◽  
Volume Averaging ◽  
Partial Volume Correction ◽  
Sampling Errors ◽  
Partial Volume ◽  
Volume Correction ◽  
Healthy Elderly ◽  
Wide Range

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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