Bonte, Stijn

Goethals, Ingeborg

Hallaert, Giorgio

Henrotte, Michaël

Kalala Okito, Jean-Pierre

English

Ghent University Academic Bibliography

VALIDATION OF DIFFERENT STATIC [18F]FET-PET PARAMETERS IN THE DISCRIMINATION OF LOW- AND HIGH-GRADE GLIOMASDEPARTMENT OF NUCLEAR MEDICINE – DEPARTMENT OF NEUROSURGERYMichaël M.D.M. Henrotte1, Stijn D.M. Bonte1,2, Giorgio G.G. Hallaert³, Jean-Pierre Kalala Okito³, Ingeborg M. Goethals1Contactmichael.henrotte@ugent.behttps://telefoonboek.ugent.be/en/department/ge16Universiteit Gent@ugentGhent University1 Department of Nuclear Medicine, Ghent University Hospital, Ghent, Belgium2 IBiTech-MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium3 Department of Neurosurgery, Ghent University Hospital, Ghent, BelgiumThough considered rare, primary brain tumours (PBTs) contribute importantly to cancer mortality and morbidity. Proper treatment planning of PBTs relies on an accuratediagnosis, for which postoperatively acquired histopathology is the gold standard. Because biopsy and resection, two sampling methods for acquiring histopathologicallyvalidated diagnosis, bear certain risks, which ought to be avoided when possible, and since histopathological tumour evaluation is prone to bias due to tumour heterogeneityand observer variability, there is an increasing interest in non-invasive diagnostic tools to support preoperative treatment planning. Over 75 % of all malignant PBTs are eitherlow-grade gliomas (LGG, WHO grades I and II) or high-grade gliomas (HGG, WHO grades III and IV). Hence, this retrospective cohort study aims to evaluate the role ofdifferent static O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) positron emission tomography (PET) parameters in discriminating LGG from HGG.Subject recruitment33 subjects with untreated low- (n = 16) or high-grade (n = 17) glioma and with availability of at least a pretreatment [18F]FET-PET scan and histopathologically validated diagnosis (type and grade) were retrospectively recruited between 1 January 2005 and 31 December 2017 at the Ghent University Hospital, a tertiary care hospital in Ghent, Belgium.Scan processingMaximal tumour standardised uptake value (SUVmax, in g · mL-1) is determined. Mean background SUV (SUVMB) is the averaged SUV of all voxels within a spherical volume of interest (VOI) (∅ = 3.0 cm) manually placed in unaffected brain tissue.SUVpeak is the averaged SUV of all voxels within a spherical VOI (∅ = 1.2 cm)manually placed in the tumour, such that this averaged SUV is maximised [1].SUV isocontours define respective VOIs (VOIx), which hold all voxels with an SUV greater than or equal to the isocontour SUV value (Figure 1, Table 1):Static parametersAn overview of the parameters determined in this study is given in Table 1.Figure 1. Example of VOI definition by SUV isocontoursTransverse [18F]FET-PET scan slice in a 25-year-old male subject with anaplastic astrocytoma (WHO grade III HGG)(a). The black circle in the right hemisphere represents the background VOI. The black circle in the left hemisphererepresents VOIpeak. Detailed view of the tumour shows the different predefined SUV isocontours defining respectiveVOIs (b). Dark red, isocontour A1.3; bright red, isocontour A41; orange, isocontour A1.5; yellow, isocontour A1.6; white,isocontour A50. VOIx is defined by all voxels externally bordered by isocontour Ax. A, anterior; L, left; P, posterior; R,right. Case courtesy of the Departments of Neurosurgery and Nuclear Medicine of the Ghent University Hospital,Ghent, Belgium.GHENTUNIVERSITY HOSPITALBACKGROUND AND GOALMATERIALS AND METHODSRESULTSDistributions of SUVmax, SUVpeak, SUV41, SUV50, TBRmax, and TBR50 satisfyparametric conditions among both groups, while all other parameters do not (p <0.05). Results of comparisons between LGG and HGG, and ROC analysis, aresummarised in Table 2. AUC is highest for MTV1.5 (0.85), and lowest for TBR1.5(0.78). At their respective optimal COV, Youden’s index is highest for MTV1.5(J = 0.691), and lowest for TBR1.3 (J = 0.449).Table 2. Diagnostic strength of static PET parameters significantly differing between LGG and HGGMean (SD) or median (IQR)*p** AUC (95 % CI) Optimal COV SN (%) SP (%)LGG HGGTBRmax 2.64 (1.16) 4.33 (1.59) 0.002 0.82 (0.68-0.97) 3.38 70.60 81.30TBR50 1.67 (0.69) 2.68 (0.97) 0.002 0.81 (0.66-0.96) 2.25 70.60 81.30MTV1.3 (mL) 4.47 (24.13) 60.08 (122.00) 0.001 0.84 (0.69-0.98) 18.53 88.20 75.00MTV1.5 (mL) 1.62 (18.10) 38.46 (56.70) < 0.001 0.85 (0.71-0.99) 7.95 94.10 75.00MTV1.6 (mL) 0.93 (15.88) 28.58 (31.10) 0.001 0.84 (0.69-0.98) 6.68 88.20 75.00TLU1.3 (g) 8.01 (29.65) 90.62 (95.08) 0.002 0.81 (0.64-0.97) 15.41 94.10 68.80TLU1.5 (g) 2.08 (17.11) 48.66 (81.31) 0.001 0.82 (0.67-0.98) 19.76 76.50 81.30TLU1.6 (g) 1.48 (14.99) 31.49 (60.01) 0.002 0.81 (0.65-0.97) 16.69 76.50 81.30TBRpeak 1.26 (1.01) 2.29 (1.32) 0.004 0.79 (0.64-0.95) 1.55 82.40 68.80TBR41 1.31 (0.75) 2.26 (1.31) 0.002 0.80 (0.65-0.95) 1.91 70.60 81.30TBR1.3 1.48 (0.33) 1.75 (0.42) 0.004 0.79 (0.63-0.94) 1.58 82.40 62.50TBR1.5 1.68 (0.39) 1.98 (0.40) 0.005 0.78 (0.63-0.94) 1.94 70.60 75.00TBR1.6 1.77 (0.41) 2.12 (0.48) 0.002 0.81 (0.67-0.96) 2.06 70.60 75.00Parameters that did not significantly differ between LGG and HGG were excluded from this table. * Mean (95 % CI) for TBRmax and TBR50, median (IQR) for all other parameters.** Based on an unpaired Student’s t test for TBRmax and TBR50 (equal variances assumed, p > 0.05), and on a Mann–Whitney U test for all other parameters.AUC, area under the ROC curve; COV, cut-off value (value for which SN + SP is maximised) HGG, high-grade glioma;MTV, metabolic tumour volume; LGG, low-grade glioma; SD, standard deviation; SN, sensitivity; SP, specificity; TBR,tumour-to-background ratio; TLU, total lesion tracer uptake.CONCLUSIONThis present study suggests a potentially valuable role for at least 13 SUV-basedstatic [18F]FET-PET parameters, for the differentiation of LGG and HGG, with AUCsranging from 0.78 to 0.85. Further statistical analyses may combine multiple suchparameters into one diagnostic tool for more precise differentiation of LGG andHGG. However, due to the limited sample size and subsequent power of this study,our results must be corroborated in larger populations. We emphasise that to date,PET parameters, including those mentioned in this study, are at mostsemiautomatically computed, in essence still depending on manual input (such asarbitrarily chosen thresholds and manual placement of background and peakVOIs), prone to bias due to both intra- and inter-observer variability. Hence, westress the need for fully automated diagnostic tools in the typing and staging ofprimary brain tumours in clinical settings, to minimise bias.REFERENCES1. Boellaard R, Delgado-Bolton R, Oyen WJG, Giammarile F, Tatsch K, Eschner W, et al. FDG PET/CT: EANMprocedure guidelines for tumor imaging: version 2.0. Eur J Nucl Med Mol Imaging. 2015;42:328-354.2. Floeth FW, Pauleit D, Sabel M, Stoffels G, Reifenberger G, Riemenschneider MJ, et al. Prognostic value of O-(2-18F-fluoroethyl)-L-tyrosine PET and MRI in low-grade glioma. J Nucl Med. 2006;48:519-527.3. Unterrainer M, Vetterman F, Brendel M, Holzgreve A, Lifschitz M, Zähringer M, et al. Towards standardization of18F-FET PET imaging: do we need a consistent method of background activity assessment? EJNMMI Research.2017; 7:48-55.a bA APPLR R LTable 1. Overview of defined VOIs and associated static parametersVOIx VOI criteria (threshold) Mean SUV = SUVx TLUx = SUVx · MTVxTBRx =SUVxSUVMBVOIMBSphere (∅ = 3.0 cm) in unaffected tissue SUVMB - * -VOImax (1 voxel) SUV = SUVmax SUVmax - * TBRmaxVOIpeakSphere (∅ = 1.2 cm) with maximal mean SUV SUVpeak - * TBRpeakVOI1.3 SUV ≥ 1.3 · SUVMB SUV1.3 TLU1.3 TBR1.3VOI1.5 SUV ≥ 1.5 · SUVMB SUV1.5 TLU1.5 TBR1.5VOI1.6 SUV ≥ 1.6 · SUVMB SUV1.6 TLU1.6 TBR1.6VOI41 SUV ≥ 41 % SUVmax SUV41 TLU41 TBR41VOI50 SUV ≥ 50 % SUVmax SUV50 TLU50 TBR50* TLU was not calculated for background, maximal, and peak VOIs, since the corresponding volumes are fixed (3.0-cm-diameter sphere, 1 voxel, and 1.2-cm-diameter sphere, respectively).MB, mean background; SUV, standardised uptake value; TBR, tumour-to-background ratio; TLU, total lesion traceruptake; VOI, volume of interestStatistical analysisSatisfaction of parametric conditions is assessed with a Shapiro–Wilk and Levenetest. Parameters are compared between LGG and HGG with an unpaired Student’st test (parametric conditions satisfied) or with a Mann–Whitney U test (parametricconditions not satisfied). Parameters significantly differing between LGG and HGGare subjected to receiver-operating characteristic (ROC) analysis. Parametermeans or medians are assessed to determine whether higher values correspond tohigher or lower grade. Optimal parameter cut-off value (COV) is the value at whichYouden’s index (J) = sensitivity (SN) + specificity (SP) – 1 is maximised. All resultswith p < 0.05 are considered significant.

Validation of different static [18F]FET-PET parameters in the discrimination of low- and high-grade gliomas

https://biblio.ugent.be/publication/8552075/file/8557738.pdf

Validation of different static [18F]FET-PET parameters in the discrimination of low- and high-grade gliomas

Abstract

Similar works

Full text

Available Versions

Ghent University Academic Bibliography