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:
CreatorsEmailORCIDORCID Put Code
Lerche, Christoph W.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Radomski, TimonUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lohmann, PhilippUNSPECIFIEDorcid.org/0000-0002-5360-046XUNSPECIFIED
Caldeira, LilianaUNSPECIFIEDorcid.org/0000-0002-9530-5899UNSPECIFIED
Brambilla, Claudia RegioUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Tellmann, LutzUNSPECIFIEDorcid.org/0000-0002-1154-2847UNSPECIFIED
Scheins, JuergenUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kops, Elena RotaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Galldiks, NorbertUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Langen, Karl-JosefUNSPECIFIEDorcid.org/0000-0003-1101-5075UNSPECIFIED
Herzog, HansUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Shah, N. JonUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
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:
KeywordsLanguage
DYNAMIC F-18-FET PET; NOISE PROPERTIES; UPTAKE KINETICS; GRADE GLIOMA; EM ALGORITHM; TUMORS; CLASSIFICATION; SYSTEMMultiple languages
Computer Science, Interdisciplinary Applications; Engineering, Biomedical; Engineering, Electrical & Electronic; Imaging Science & Photographic Technology; Radiology, Nuclear Medicine & Medical ImagingMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/58523

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