scholarly journals The Effect of Calibration Factors and Recovery Coefficients on 177Lu SPECT Activity Quantification Accuracy: A Monte Carlo Study

2020 ◽  
Author(s):  
Keamogetswe Ramonaheng ◽  
Johan 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 standardized geometry. The CF is dependent on the selected geometry and 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 ml – 65.4 ml) and a kidney model with known activity concentrations inside a cylindrical, torso and patient phantom. Images were reconstructed with the 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 (≤ 3.47%) and cylinder-CF (≤ 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 (≤ 3.50%) and the cylinder-CF (≤ 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 and cylinder-CF, when all corrections were applied.

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

2017 ◽  
Vol 37 (12) ◽  
pp. 3803-3817 ◽  
Author(s):  
Elisabetta Grecchi ◽  
Mattia Veronese ◽  
Benedetta Bodini ◽  
Daniel García-Lorenzo ◽  
Marco Battaglini ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Partial Volume Correction ◽  
Control Group ◽  
Resolution Recovery ◽  
Partial Volume ◽  
Volume Correction ◽  
Pet Tracer ◽  
Quantification Accuracy ◽  
Myelin Imaging ◽  
Phantom Experiments

The [11C]PIB PET tracer, originally developed for amyloid imaging, has been recently repurposed to quantify demyelination and remyelination in multiple sclerosis (MS). Myelin PET imaging, however, is limited by its low resolution that deteriorates the quantification accuracy of white matter (WM) lesions. Here, we introduce a novel partial volume correction (PVC) method called Multiresolution–Multimodal Resolution-Recovery (MM-RR), which uses the wavelet transform and a synergistic statistical model to exploit MRI structural images to improve the resolution of [11C]PIB PET myelin imaging. MM-RR performance was tested on a phantom acquisition and in a dataset comprising [11C]PIB PET and MR T1- and T2-weighted images of 8 healthy controls and 20 MS patients. For the control group, the MM-RR PET images showed an average increase of 5.7% in WM uptake while the grey-matter (GM) uptake remained constant, resulting in +31% WM/GM contrast. Furthermore, MM-RR PET binding maps correlated significantly with the mRNA expressions of the most represented proteins in the myelin sheath (R2 = 0.57 ± 0.09). In the patient group, MM-RR PET images showed sharper lesion contours and significant improvement in normal-appearing tissue/WM-lesion contrast compared to standard PET (contrast improvement > +40%). These results were consistent with MM-RR performances in phantom experiments.

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 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.

Sign in / Sign up

Export Citation Format

Share Document