Leek, F; Anderson, C; Robinson, AP; Moss, RM; Porter, JC; Garthwaite, HS; Groves, AM; ... Thielemans, K; + view all Leek, F; Anderson, C; Robinson, AP; Moss, RM; Porter, JC; Garthwaite, HS; Groves, AM; Hutton, BF; Thielemans, K; - view fewer (2023) Optimisation of the air fraction correction for lung PET/CT: addressing resolution mismatch. EJNMMI Physics , 10 , Article 77. 10.1186/s40658-023-00595-y.

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Abstract

Background: Increased pulmonary 18 F-FDG metabolism in patients with idiopathic pulmonary fibrosis, and other forms of diffuse parenchymal lung disease, can predict measurements of health and lung physiology. To improve PET quantification, voxel-wise air fractions (AF) determined from CT can be used to correct for variable air content in lung PET/CT. However, resolution mismatches between PET and CT can cause artefacts in the AF-corrected image. Methods: Three methodologies for determining the optimal kernel to smooth the CT are compared with noiseless simulations and non-TOF MLEM reconstructions of a patient-realistic digital phantom: (i) the point source insertion-and-subtraction method, hpts ; (ii) AF-correcting with varyingly smoothed CT to achieve the lowest RMSE with respect to the ground truth (GT) AF-corrected volume of interest (VOI), hAFC ; iii) smoothing the GT image to match the reconstruction within the VOI, hPVC . The methods were evaluated both using VOI-specific kernels, and a single global kernel optimised for the six VOIs combined. Furthermore, hPVC was implemented on thorax phantom data measured on two clinical PET/CT scanners with various reconstruction protocols. Results: The simulations demonstrated that at < 200 iterations (200 i), the kernel width was dependent on iteration number and VOI position in the lung. The hpts method estimated a lower, more uniform, kernel width in all parts of the lung investigated. However, all three methods resulted in approximately equivalent AF-corrected VOI RMSEs (<10%) at ≥ 200i. The insensitivity of AF-corrected quantification to kernel width suggests that a single global kernel could be used. For all three methodologies, the computed global kernel resulted in an AF-corrected lung RMSE <10% at ≥ 200i, while larger lung RMSEs were observed for the VOI–specific kernels. The global kernel approach was then employed with the hPVC method on measured data. The optimally smoothed GT emission matched the reconstructed image well, both within the VOI and the lung background. VOI RMSE was <10%, pre-AFC, for all reconstructions investigated. Conclusions: Simulations for non-TOF PET indicated that around 200i were needed to approach image resolution stability in the lung. In addition, at this iteration number, a single global kernel, determined from several VOIs, for AFC, performed well over the whole lung. The hPVC method has the potential to be used to determine the kernel for AFC from scans of phantoms on clinical scanners.

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