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CC BY 4.0 · World J Nucl Med 2025; 24(02): 097-106
DOI: 10.1055/s-0044-1795105
Original Article

Elucidation of FDG-PET Imaging Characteristics that Reflect the Heterogeneity within Tumors Due to Variability in Metabolic Activity: A Phantom Study

Junpei Suzuki
1   Department of Radiological Technology, Graduate School of Health Science, Juntendo University, Tokyo, Japan
,
Keisuke Tsuda
1   Department of Radiological Technology, Graduate School of Health Science, Juntendo University, Tokyo, Japan
,
Kazuya Koyama
1   Department of Radiological Technology, Graduate School of Health Science, Juntendo University, Tokyo, Japan
,
Tomoya Harada
2   Department of Radiology, LSI Sapporo Clinic, Hokkaido, Japan
,
Shota Takemoto
3   Department of Radiology, Juntendo University Hospital, Tokyo, Japan
,
Satoshi Kimura
3   Department of Radiology, Juntendo University Hospital, Tokyo, Japan
,
Koji Murakami
3   Department of Radiology, Juntendo University Hospital, Tokyo, Japan
› Author Affiliations
Funding This work was supported by JSPS KAKENHI, grant number JP22K07259.
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Abstract

Objective Focusing on the heterogeneity within cancer lesions and revealing cancer lesions with a high signal-to-noise ratio will help improve the quality of positron emission tomography (PET) images. This study aimed to understand how glucose metabolic activity can be shown with less statistical noise using a quality assessment phantom modeled after cancer lesions with a two-layer structure and a Clear adaptive Low-noise Method (CaLM) filter.

Materials and Methods A National Electrical Manufacturers Association phantom with two spheres with a two-layer structure filled with 2-deoxy-2[18F]fluoro-D-glucose (inner and outer diameters of the spheres were 13/22 and 22/37 mm, respectively; radioactivity ratio of the background [BG] to outer sphere layer was 1:4; and BG-to-inner sphere layer ratios were 1:1, 1:2, and 1:3) was evaluated. The acquisition time was set at 120 seconds, and imaging was repeated five times. The image data in photomultiplier tube (PMT)-PET were reconstructed using a time-of-flight (TOF) ordered subset expectation maximization (OSEM) algorithm (point spread function [PSF] − , iteration: 3, subset: 10) with a 4-mm Gaussian filter (GF) for normal images. Silicon photomultiplier (SiPM)-PET data were reconstructed using a TOF OSEM algorithm (PSF − , iteration: 2, subset: 12) and a 3-mm GF for normal images. The target images were reconstructed using three CaLM parameters (mild, standard, and strong). All the obtained images were investigated quantitatively, with calculation of maximum standard uptake value (SUVmax), coefficient of variation (CV), and contrast-to-noise ratio (CNR), after setting regions of interest on the lesions. Statistical analysis using the Dunnett's test compared normal images (control group) and target images (treatment group). Statistical significance was considered at p < 0.05.

Results Quantitative assessment revealed that the SUVmax of target images (standard and strong) was equivalent to that of normal images in PMT-PET, with SUVmax of 3 to 3.5 for both layers. The SUVmax in SiPM-PET was similar across all CaLM types, ranging from 3 to 4 for all spheres. The target images (standard and strong) had a significantly reduced CV and improved CNR compared with normal images.

Conclusion The boundary of the 22/37-mm spheres was visible with CaLM (strong) at radioactivity ratios of 1:4:1 and 1:4:2 on both scanners. For the 13/22-mm sphere boundary, visibility with CaLM (strong) was observed only with SiPM-PET, with the SUVmax equivalent to normal images. CaLM (strong) was deemed the optimal postprocessing filter for PMT-PET due to significant improvements in CV and CNR, while CaLM (standard) was suggested as the optimal filter for SiPM-PET due to excessive BG smoothing.

Keywords

silicon photomultipliers-positron emission tomography - statistical noise reduction - postprocessing filter - heterogeneity - partial volume effect

Authors' Contributions

J.S. and K.T. contributed to the concepts and literature search. All authors contributed to the design, definition of intellectual content, manuscript preparation, manuscript editing, and manuscript review. J.S., K.T., and K.K. contributed to the data analysis and statistical analysis. J.S., K.T., K.K., T.H., S.T., and S.K. contributed to the experimental studies and data acquisition. K.T. is the guarantor.




Publication History

Article published online:
19 November 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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