Universität zu Köln

Lerche, Christoph W., Radomski, Timon, Lohmann, Philipp ORCID: 0000-0002-5360-046X, Caldeira, Liliana ORCID: 0000-0002-9530-5899, Brambilla, Claudia Regio, Tellmann, Lutz ORCID: 0000-0002-1154-2847, Scheins, Juergen, Kops, Elena Rota, Galldiks, Norbert, Langen, Karl-Josef ORCID: 0000-0003-1101-5075, Herzog, Hans and Shah, N. Jon (2021). A Linearized Fit Model for Robust Shape Parameterization of FET-PET TACs. IEEE Trans. Med. Imaging, 40 (7). S. 1852 - 1863. PISCATAWAY: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. ISSN 1558-254X

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Abstract

The kinetic analysis of F-18-FET time-activity curves (TAC) can provide valuable diagnostic information in glioma patients. The analysis is most often limited to the average TAC over a large tissue volume and is normally assessed by visual inspection or by evaluating the time-topeak and linear slope during the late uptake phase. Here, we derived and validated a linearized model for TACs of F-18-FET in dynamic PET scans. Emphasis was put on the robustness of the numerical parameters and how reliably automatic voxel-wise analysis of TAC kineticswas possible. The diagnostic performance of the extracted shape parameters for the discrimination between isocitrate dehydrogenase (IDH) wildtype (wt) and IDH-mutant (mut) glioma was assessed by receiver-operating characteristic in a group of 33 adult glioma patients. A high agreement between the adjusted model and measured TACs could be obtained and relative, estimated parameter uncertainties were small. The best differentiation between IDH-wt and IDH-mut gliomas was achieved with the linearized model fitted to the averaged TAC values from dynamic FET PET data in the time interval 4-50 min p.i.. When limiting the acquisition time to 20-40 min p.i., classification accuracy was only slightly lower (-3%) and was comparable to classification based on linear fits in this time interval. Voxel-wise fitting was possible within a computation time similar to 1 min per image slice. Parameter uncertainties smaller than 80% for all fits with the linearized model were achieved. The agreement of best-fit parameters when comparing voxel-wise fits and fits of averaged TACs was very high (p < 0.001).

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Lerche, Christoph W. UNSPECIFIED UNSPECIFIED UNSPECIFIED Radomski, Timon UNSPECIFIED UNSPECIFIED UNSPECIFIED Lohmann, Philipp UNSPECIFIED orcid.org/0000-0002-5360-046X UNSPECIFIED Caldeira, Liliana UNSPECIFIED orcid.org/0000-0002-9530-5899 UNSPECIFIED Brambilla, Claudia Regio UNSPECIFIED UNSPECIFIED UNSPECIFIED Tellmann, Lutz UNSPECIFIED orcid.org/0000-0002-1154-2847 UNSPECIFIED Scheins, Juergen UNSPECIFIED UNSPECIFIED UNSPECIFIED Kops, Elena Rota UNSPECIFIED UNSPECIFIED UNSPECIFIED Galldiks, Norbert UNSPECIFIED UNSPECIFIED UNSPECIFIED Langen, Karl-Josef UNSPECIFIED orcid.org/0000-0003-1101-5075 UNSPECIFIED Herzog, Hans UNSPECIFIED UNSPECIFIED UNSPECIFIED Shah, N. Jon UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-585238
DOI:	10.1109/TMI.2021.3067169
Journal or Publication Title:	IEEE Trans. Med. Imaging
Volume:	40
Number:	7
Page Range:	S. 1852 - 1863
Date:	2021
Publisher:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Place of Publication:	PISCATAWAY
ISSN:	1558-254X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language DYNAMIC F-18-FET PET; NOISE PROPERTIES; UPTAKE KINETICS; GRADE GLIOMA; EM ALGORITHM; TUMORS; CLASSIFICATION; SYSTEM Multiple languages Computer Science, Interdisciplinary Applications; Engineering, Biomedical; Engineering, Electrical & Electronic; Imaging Science & Photographic Technology; Radiology, Nuclear Medicine & Medical Imaging Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/58523