Comparison of 18F-Choline PET/CT and MRI functional parameters in prostate cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09-15

AUTHORS

Xavier Palard-Novello, Luc Beuzit, Giulio Gambarota, Florence Le Jeune, Etienne Garin, Pierre-Yves Salaün, Anne Devillers, Solène Querellou, Patrick Bourguet, Hervé Saint-Jalmes

ABSTRACT

Aim18F-Choline (FCH) uptake parameters are strong indicators of aggressive disease in prostate cancer. Functional parameters derived by magnetic resonance imaging (MRI) are also correlated to aggressive disease. The aim of this work was to evaluate the relationship between metabolic parameters derived by FCH PET/CT and functional parameters derived by MRI.Materials and methodsFourteen patients with proven prostate cancer who underwent FCH PET/CT and multiparametric MRI were enrolled. FCH PET/CT consisted in a dual phase: early pelvic list-mode acquisition and late whole-body acquisition. FCH PET/CT and multiparametric MRI examinations were registered and tumoral volume-of-interest were drawn on the largest lesion visualized on the apparent diffusion coefficient (ADC) map and projected onto the different multiparametric MR images and FCH PET/CT images. Concerning the FCH uptake, kinetic parameters were extracted with the best model selected using the Akaike information criterion between the one- and two-tissue compartment models with an imaging-derived plasma input function. Other FCH uptake parameters (early SUVmean and late SUVmean) were extracted. Concerning functional parameters derived by MRI scan, cell density (ADC from diffusion weighting imaging) and vessel permeability (Ktrans and Ve using the Tofts pharmakinetic model from dynamic contrast-enhanced imaging) parameters were extracted. Spearman’s correlation coefficients were calculated to compare parameters.ResultsThe one-tissue compartment model for kinetic analysis of PET images was selected. Concerning correlation analysis between PET parameters, K1 was highly correlated with early SUVmean (r = 0.83, p < 0.001) and moderately correlated with late SUVmean (r = 0.66, p = 0.010) and early SUVmean was highly correlated with late SUVmean (r = 0.90, p < 0.001). No significant correlation was found between functional MRI parameters. Concerning correlation analysis between PET and functional MRI parameters, K1 (from FCH PET/CT imaging) was moderately correlated with Ktrans (from perfusion MR imaging) (r = 0.55, p = 0.041).ConclusionsNo significant correlation was found between FCH PET/CT and multiparametric MRI metrics except FCH influx which is moderately linked to the vessel permeability in prostate cancer. More... »

PAGES

47-54

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12149-018-1302-8

DOI

http://dx.doi.org/10.1007/s12149-018-1302-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107037352

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30219990


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31 CT
32 CT images
33 ConclusionsNo significant correlation
34 FCH PET/CT
35 FCH PET/CT images
36 FCH influx
37 FCH uptake
38 FCH uptake parameters
39 K1
40 Ktrans
41 MR images
42 MRI examinations
43 MRI functional parameters
44 MRI metrics
45 MRI parameters
46 MRI scans
47 PET
48 PET images
49 PET parameters
50 PET/CT
51 PET/CT images
52 SUVmean
53 Spearman correlation coefficient
54 acquisition
55 aggressive disease
56 aim
57 analysis
58 apparent diffusion coefficient (ADC) maps
59 best model
60 cancer
61 cell density
62 coefficient
63 coefficient (ADC) maps
64 comparison
65 compartment model
66 correlation
67 correlation analysis
68 correlation coefficient
69 criteria
70 density
71 different multiparametric MR images
72 diffusion coefficient (ADC) maps
73 disease
74 dual phase
75 early SUVmean
76 early pelvic list-mode acquisition
77 examination
78 function
79 functional MRI parameters
80 functional parameters
81 images
82 imaging
83 imaging-derived plasma input function
84 indicators
85 influx
86 information criterion
87 input function
88 interest
89 kinetic analysis
90 kinetic parameters
91 large lesions
92 late SUVmean
93 late whole-body acquisition
94 lesions
95 list-mode acquisition
96 magnetic resonance imaging
97 maps
98 materials
99 metabolic parameters
100 methodsFourteen patients
101 metrics
102 model
103 multiparametric MR images
104 multiparametric MRI examination
105 multiparametric MRI metrics
106 multiparametric magnetic resonance imaging
107 one-tissue compartment model
108 parameters
109 patients
110 pelvic list-mode acquisition
111 permeability
112 permeability parameters
113 phase
114 plasma input function
115 prostate cancer
116 relationship
117 resonance imaging
118 scans
119 significant correlation
120 strong indicator
121 tumoral volume
122 two-tissue compartment model
123 uptake
124 uptake parameters
125 vessel permeability
126 vessel permeability (Ktrans and Ve using the Tofts pharmakinetic model from dynamic contrast-enhanced imaging) parameters
127 volume
128 whole-body acquisition
129 work
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