Accuracy and Precision of Radioactivity Quantification in Nuclear Medicine Images

Frey, Eric; Humm, John L.; Ljungberg, Michael

doi:10.1053/j.semnuclmed.2011.11.003

Cited by 76 publications

(67 citation statements)

References 44 publications

(39 reference statements)

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“…Zeintl et al [31] used a cylinder uniformly filled with 99m Tc and reported CNF values similar to those obtained by our group using planar scans of point sources [26]. Frey et al [32] suggests that the use of a phantom tomographic acquisition, instead of a planar scan of a small source, is the optimal approach. Lastly, D’Arienzo et al [33] performed tomographic scans of point sources in air and extended phantoms and showed better quantification accuracy for CNF determined from phantom studies than from point sources.…”

Section: Discussionsupporting

confidence: 66%

Accuracy of 177Lu activity quantification in SPECT imaging: a phantom study

et al. 2017

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BackgroundThe aim of the study is to assess accuracy of activity quantification of 177Lu studies performed according to recommendations provided by the committee on Medical Internal Radiation Dose (MIRD) pamphlets 23 and 26. The performances of two scatter correction and three segmentation methods were compared. Additionally, the accuracy of tomographic and planar methods for determination of the camera normalization factor (CNF) was evaluated.Eight phantoms containing inserts of different sizes and shapes placed in air, water, and radioactive background were scanned using a Siemens SymbiaT SPECT/CT camera. Planar and tomographic scans with 177Lu sources were used to measure CNF. Images were reconstructed with our SPEQToR software using resolution recovery, attenuation, and two scatter correction methods (analytical photon distribution interpolated (APDI) and triple energy window (TEW)). Segmentation was performed using a fixed threshold method for both air and cold water scans. For hot water experiments three segmentation methods were compared as folows: a 40% fixed threshold, segmentation based on CT images, and our iterative adaptive dual thresholding (IADT). Quantification error, defined as the percent difference between experimental and true activities, was evaluated.ResultsQuantification error for scans in air was better for TEW scatter correction (<6%) than for APDI (<11%). This trend was reversed for scans in water (<10% for APDI and <14% for TEW). For hot water, the best results (<18% for small objects and <5% for objects >100 ml) were obtained when APDI and IADT were used for scatter correction and segmentation, respectively. Additionally, we showed that planar acquisitions with scatter correction and tomographic scans provide similar CNF values. This is an important finding because planar acquisitions are easier to perform than tomographic scans. TEW and APDI resulted in similar quantification errors with APDI showing a small advantage for objects placed in medium with non-uniform density.ConclusionsFollowing the MIRD recommendations for data acquisition and reconstruction resulted in accurate activity quantification (errors <5% for large objects). However, techniques for better organ/tumor segmentation must still be developed.Electronic supplementary materialThe online version of this article (doi:10.1186/s40658-016-0170-3) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 66%

Accuracy of 177Lu activity quantification in SPECT imaging: a phantom study

et al. 2017

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“…40,41 Corrections for clinical factors, including involuntary (e.g., respiration), or voluntary motions, were only recently proposed. 40,42,43 Hence, the more sophisticated methods to correct SPECT counts to activity are not yet in widespread use, as full corrections of physical factors are not always available, and correction to respiratory motion is possible only in few research centers. Moreover, the hybrid SPECT-CT scanners are not available in all centers.…”

Section: Introductionmentioning

confidence: 99%

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

et al. 2016

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Purpose: Many centers aim to plan liver transarterial radioembolization (TARE) with dosimetry, even without CT-based attenuation correction (AC), or with unoptimized scatter correction (SC) methods. This work investigates the impact of presence vs absence of such corrections, and limited spatial resolution, on 3D dosimetry for TARE. Methods: Three voxelized phantoms were derived from CT images of real patients with different body sizes. Simulations of 99m Tc-SPECT projections were performed with the SIMIND code, assuming three activity distributions in the liver: uniform, inside a "liver's segment," or distributing multiple uptaking nodules ("nonuniform liver"), with a tumoral liver/healthy parenchyma ratio of 5:1. Projection data were reconstructed by a commercial workstation, with OSEM protocol not specifically optimized for dosimetry (spatial resolution of 12.6 mm), with/without SC (optimized, or with parameters predefined by the manufacturer; dual energy window), and with/without AC. Activity in voxels was calculated by a relative calibration, assuming identical microspheres and 99m Tc-SPECT counts spatial distribution. 3D dose distributions were calculated by convolution with lesions and healthy parenchyma from different reconstructions were compared with those obtained from the reference biodistribution (the "gold standard," GS), assessing differences for D95%, D70%, and D50% (i.e., minimum value of the absorbed dose to a percentage of the irradiated volume). γ tool analysis with tolerance of 3%/13 mm was used to evaluate the agreement between GS and simulated cases. The influence of deep-breathing was studied, blurring the reference biodistributions with a 3D anisotropic gaussian kernel, and performing the simulations once again. Results: Differences of the dosimetric indicators were noticeable in some cases, always negative for lesions and distributed around zero for parenchyma. Application of AC and SC reduced systematically the differences for lesions by 5%-14% for a liver segment, and by 7%-12% for a nonuniform liver. For parenchyma, the data trend was less clear, but the overall range of variability passed from −10%/40% for a liver segment, and −10%/20% for a nonuniform liver, to −13%/6% in both cases. Applying AC, SC with preset parameters gave similar results to optimized SC, as confirmed by γ tool analysis. Moreover, γ analysis confirmed that solely AC and SC are not sufficient to obtain accurate 3D dose distribution. With breathing, the accuracy worsened severely for all dosimetric indicators, above all for lesions: with AC and optimized SC, −38%/−13% in liver's segment, −61%/−40% in the nonuniform liver. For parenchyma, D50% resulted always less sensitive to breathing and sub-optimal correction methods (difference overall range: −7%/13%). Conclusions: Reconstruction protocol optimization, AC, SC, PVE and respiratory motion corrections should be implemented to obtain the best possible dosimetric accuracy. On the other side, thanks to the relative calibration, D50% inaccuracy for the healthy paren...

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“…SUVmax may be the most widely used PET parameter due to its easy access with commercial workstations. SUVmax might be most advantageous in small tumors with less dependency on partialvolume effects [5], however, it can be substantially affected by image noise and therefore depend on reconstruction parameters [1]. Although SUVmean might provide a more representative value for the whole tumor, it will vary depending on which voxels are included in ROI [1,9].…”

Section: Pet Parametersmentioning

confidence: 99%

“…To plan targeted therapy or to assess the response of treatment, measurement of tumor size or estimation of radioactivity concentrations in regions of interest (ROI) are essential [1]. However, anatomic size changes often come later and less specific than functional and molecular changes [2].…”

Section: Introductionmentioning

confidence: 99%

What Do We Measure in Oncology PET?

Pak

Kim

2016

Nucl Med Mol Imaging

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Positron emission tomography (PET) has come to the practice of oncology. It is known that F-fluorodeoxyglucose (FDG) PET is more sensitive for the assessment of treatment response than conventional imaging. In addition, PET has an advantage in the use of quantitative analysis of the study. Nowadays, various PET parameters are adopted in clinical settings. In addition, a wide range of factors has been known to be associated with FDG uptake. Therefore, there has been a need for standardization and harmonization of protocols and PET parameters. We will introduce PET parameters and discuss major issues in this review.

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Accuracy and Precision of Radioactivity Quantification in Nuclear Medicine Images

Cited by 76 publications

References 44 publications

Accuracy of 177Lu activity quantification in SPECT imaging: a phantom study

Accuracy of 177Lu activity quantification in SPECT imaging: a phantom study

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

What Do We Measure in Oncology PET?

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