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. 2024 Nov 19;24(1):47-56.
doi: 10.1055/s-0044-1795102. eCollection 2025 Mar.

Comparative Assessment of Agreement in Uniformity Analyses across Quality Control Software Platforms

Thasmeera T Supramaniam  1 , Muhammad Y Udin  2 , Marianie Musarudin  1
Affiliations

Comparative Assessment of Agreement in Uniformity Analyses across Quality Control Software Platforms

Thasmeera T Supramaniam et al. World J Nucl Med. .

Abstract

Objective In nuclear medicine, quality control (QC) activities adhere to international standards, yet their complexity can pose challenges. Gamma camera manufacturers have introduced integrated QC software, offering instantaneous results. However, the agreement of these automated processes with established protocols remains uncertain. This study aims to clarify this uncertainty by comparatively analyzing uniformity from various software solutions for a dual-head gamma camera. Methods The study utilized integrated QC analysis software and three free QC analysis tools (IAEA-NMQC Toolkit, NM Toolkit, and Fiji) for uniformity analyses. Following the National Electrical Manufacturers Association standards, NEMA Standards Publication NU 1-2018, the intrinsic uniformity test was performed on a GE Discovery NM/CT 670 Pro system. Ten uniformity QC images underwent analysis with both integrated QC software and alternative software. Data agreements were tested using the Blant-Altman regression-based analysis. Results Significant differences were observed in integral and differential uniformities ( p < 0.001). The central field of view (useful field of view) integral uniformity mean differences for NMQC Toolkit, NM Toolkit, and Fiji were 2.46% (2.34%), 2.44% (2.31%), and 2.56% (2.64%), respectively. Conversely, x-differential and y-differential uniformity mean differences were consistently under 2%. Regression-based analysis confirmed good agreement between computed values. Conclusion The integrated QC software of Discovery NM/CT 670 Pro provides reliable uniformity analysis, aligned with the NEMA standards. Variations in computed values may stem from differences in pixel values and applied data corrections.

Keywords: ImageJ; NM Toolkit; NMQC Toolkit; SPECT; uniformity.

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Conflict of interest statement

Conflict of Interest None declared.

Figures

Fig. 1
Fig. 1
The intrinsic uniformity setup. 99m Tc point source was positioned in a holder (pointed by the red arrow ) at a distance of ≥5 times the largest dimension of the uniform field of view (UFOV) of the detector, adhering to the NEMA guidelines.
Fig. 2
Fig. 2
Comparison of the uniformities computed using integrated QC software and free QC software. ( a, b ) Integral uniformity. ( c, d ) X-differential uniformity. ( e, f ) Y-differential uniformity. Left panels: central field of view. Right panels: uniform field of view.
Fig. 3
Fig. 3
Bland–Altman regression-based limits of agreement for integral uniformity computed between ( a, b ) integrated quality control (QC) software and NMQC Toolkit; ( c, d ) integrated QC software and NM Toolkit; ( e–f ) integrated QC software and Fiji. A good level of agreement was observed, with the data falling within the 95% limits of agreement. The solid line indicates the mean difference (bias), and the dotted lines represent 95% limit of agreement. Left panels: central field of view. Right panels: uniform field of view.
Fig. 4
Fig. 4
Bland–Altman regression-based limits of agreement for x-differential uniformity computed between ( a, b ) integrated quality control (QC) software and IAEA-NMQC Toolkit; ( b, c ) integrated QC software and NM Toolkit; ( e, f ) integrated QC software and Fiji. A good level of agreement was observed, with the data falling within the 95% limits of agreement. The solid line indicates the mean difference (bias), and the dotted lines represent 95% limit of agreement. Left: central field of view. Right panels: uniform field of view.
Fig. 5
Fig. 5
Bland–Altman regression-based limits of agreement for y-differential uniformity computed between ( a, b ) integrated quality control (QC) software and IAEA-NMQC Toolkit; ( b, c ) integrated QC software and NM Toolkit; ( e, f ) integrated QC software and Fiji. Left panels: A good level of agreement was observed, with the data falling within the 95% limits of agreement. The solid line indicates the mean difference (bias), and the dotted lines represent 95% limit of agreement. Left panels: central field of view. Right: uniform field of view.
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