Quantitative assessment of kidney split function and mean transit time in healthy patients using dynamic 18F-FDG PET/MRI studies with denoising and deconvolution methods making use of Legendre polynomials
Year: 2024
Type: article
Abstract: Our objective was to assess a deconvolution and denoising technique based on Legendre polynomials compared to matrix deconvolution on dynamic 18 F-FDG renography of healthy patients. The study was carried out and compared to the data of 24 healthy patients from a published study who underwent examinations with 99m Tc-MAG3 planar scintigraphy and 18 F-FDG PET/MRI. Due to corruption issues in some data used in the published article, post-publication measurements were provided. We have been warned that post-publication data were treated differently. The smoothing method switched from Bezier to Savitzky–Golay and the deconvolution from matrix-based (with Tikhonov Regularization) to Richardson–Lucy. A comparison of the split function and mean transit times of the published and post-publication data against our method based on Legendre polynomials was performed. For split function, we only observed a good agreement between the processing methods for the 99m Tc-MAG 3 and the post-published data. No correlation was found between the split functions obtained on the 99m Tc-MAG 3 and the 18 F-FDG, contrary to the published study. However, all calculated split function values for 18 F-FDG and 99m Tc-MAG 3 were within the established normal range. For the mean transit time, the correlation was moderate with published data and very good with the post-publication measurements for both 99m Tc-MAG 3 and 18 F-FDG. Bias of the Bland–Altman analysis of the mean transit times for 99m Tc-MAG 3 versus 18 F-FDG was 1.1 min (SD 1.7 min) for the published data, − 0.11 min (SD 1.9 min) for the post-publication results and .05 min (SD 1.9 min) for our method. The processing methods used in the original publication and in the post-publication work were quite complex and required adaptation of the fitting parameters for each individual and each type of examination. Our method did not require any specific adjustment; the same unmodified and fully automated algorithm was successfully applied to all data.
Source: EJNMMI Reports
Authors: Michel Destine, Alain Seret
Institution: University of Liège
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,337
OpenAlex ID: W4403384607