Daniëlle Koopman1, Jorn A van Dalen2, Martine C M Lagerweij2, Hester Arkies3, Jaep de Boer3, Ad H J Oostdijk3, Cornelis H Slump4, Pieter L Jager3. 1. MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands Department of Nuclear Medicine, Isala Hospital, Zwolle, The Netherlands; and d.koopman@isala.nl. 2. Department of Medical Physics, Isala Hospital, Zwolle, The Netherlands. 3. Department of Nuclear Medicine, Isala Hospital, Zwolle, The Netherlands; and. 4. MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands.
Abstract
UNLABELLED: A major disadvantage of (18)F-FDG PET involves poor detection of small lesions and lesions with low metabolism, caused by limited spatial resolution and relatively large image voxel size. As spatial resolution and sensitivity are better in new PET systems, it is expected that small-lesion detection could be improved using smaller voxels. The aim of this study was to test this hypothesis using a state-of-the-art time-of-flight PET/CT device. METHODS: (18)F-FDG PET scans of 2 image-quality phantoms (sphere sizes, 4-37 mm) and 39 consecutive patients with lung cancer were analyzed on a time-of-flight PET/CT system. Images were iteratively reconstructed with standard 4 × 4 × 4 mm voxels and smaller 2 × 2 × 2 mm voxels. For the phantom study, we determined contrast-recovery coefficients and signal-to-noise ratios (SNRs). For the patient study, (18)F-FDG PET-positive lesions in the chest and upper abdomen with a volume less than 3.0 mL (diameter, <18 mm) were included. Lesion mean and maximum standardized uptake values (SUVmean and SUVmax, respectively) were determined in both image sets. SNRs were determined by comparing SUVmax and SUVmean with background noise levels. A subanalysis was performed for lesions less than 0.75 mL (diameter, <11 mm). For qualitative analysis of patient data, 3 experienced nuclear medicine physicians gave their preference after visual side-by-side analysis. RESULTS: For phantom spheres 13 mm or less, we found higher contrast-recovery coefficients and SNRs using small-voxel reconstructions. For 66 included (18)F-FDG PET-positive lesions, the average increase in SUVmean and SUVmax using the small-voxel images was 17% and 32%, respectively (P < 0.01). For lesions less than 0.75 mL (21 in total), the average increase was 21% and 44%, respectively. Moreover, averaged over all lesions, the mean and maximum SNR increased by 20% and 27%, respectively (P < 0.01). For lesions less than 0.75 mL, these values increased up to 23% and 46%, respectively. The physicians preferred the small-voxel reconstructions in 76% of cases. CONCLUSION: Supported by a phantom study, there was a visual preference toward (18)F-FDG PET images reconstructed with 2 × 2 × 2 mm voxels and a profound increase in standardized uptake value and SNR for small lesions. Hence, it is expected that small-lesion detection improves using small-voxel reconstructions.
UNLABELLED: A major disadvantage of (18)F-FDG PET involves poor detection of small lesions and lesions with low metabolism, caused by limited spatial resolution and relatively large image voxel size. As spatial resolution and sensitivity are better in new PET systems, it is expected that small-lesion detection could be improved using smaller voxels. The aim of this study was to test this hypothesis using a state-of-the-art time-of-flight PET/CT device. METHODS: (18)F-FDG PET scans of 2 image-quality phantoms (sphere sizes, 4-37 mm) and 39 consecutive patients with lung cancer were analyzed on a time-of-flight PET/CT system. Images were iteratively reconstructed with standard 4 × 4 × 4 mm voxels and smaller 2 × 2 × 2 mm voxels. For the phantom study, we determined contrast-recovery coefficients and signal-to-noise ratios (SNRs). For the patient study, (18)F-FDG PET-positive lesions in the chest and upper abdomen with a volume less than 3.0 mL (diameter, <18 mm) were included. Lesion mean and maximum standardized uptake values (SUVmean and SUVmax, respectively) were determined in both image sets. SNRs were determined by comparing SUVmax and SUVmean with background noise levels. A subanalysis was performed for lesions less than 0.75 mL (diameter, <11 mm). For qualitative analysis of patient data, 3 experienced nuclear medicine physicians gave their preference after visual side-by-side analysis. RESULTS: For phantom spheres 13 mm or less, we found higher contrast-recovery coefficients and SNRs using small-voxel reconstructions. For 66 included (18)F-FDG PET-positive lesions, the average increase in SUVmean and SUVmax using the small-voxel images was 17% and 32%, respectively (P < 0.01). For lesions less than 0.75 mL (21 in total), the average increase was 21% and 44%, respectively. Moreover, averaged over all lesions, the mean and maximum SNR increased by 20% and 27%, respectively (P < 0.01). For lesions less than 0.75 mL, these values increased up to 23% and 46%, respectively. The physicians preferred the small-voxel reconstructions in 76% of cases. CONCLUSION: Supported by a phantom study, there was a visual preference toward (18)F-FDG PET images reconstructed with 2 × 2 × 2 mm voxels and a profound increase in standardized uptake value and SNR for small lesions. Hence, it is expected that small-lesion detection improves using small-voxel reconstructions.
Authors: Spencer C Behr; Emma Bahroos; Randall A Hawkins; Lorenzo Nardo; Vahid Ravanfar; Emily V Capbarat; Youngho Seo Journal: Mol Imaging Biol Date: 2018-06 Impact factor: 3.488
Authors: Daniëlle Koopman; Maureen Groot Koerkamp; Pieter L Jager; Hester Arkies; Siert Knollema; Cornelis H Slump; Pedro G Sanches; Jorn A van Dalen Journal: EJNMMI Phys Date: 2017-01-31
Authors: Charlotte S van der Vos; Daniëlle Koopman; Sjoerd Rijnsdorp; Albert J Arends; Ronald Boellaard; Jorn A van Dalen; Mark Lubberink; Antoon T M Willemsen; Eric P Visser Journal: Eur J Nucl Med Mol Imaging Date: 2017-07-08 Impact factor: 9.236
Authors: J W Dankbaar; T J Snijders; P A Robe; T Seute; W Eppinga; J Hendrikse; B De Keizer Journal: J Neurooncol Date: 2015-09-18 Impact factor: 4.130
Authors: Daniëlle Koopman; Jochen A C van Osch; Pieter L Jager; Carlijn J A Tenbergen; Siert Knollema; Cornelis H Slump; Jorn A van Dalen Journal: EJNMMI Phys Date: 2016-09-29
Authors: Daniëlle Koopman; Jorn A van Dalen; Hester Arkies; Ad H J Oostdijk; Anne Brecht Francken; Jos Bart; Cornelis H Slump; Siert Knollema; Pieter L Jager Journal: EJNMMI Res Date: 2018-01-16 Impact factor: 3.138