000864919 001__ 864919
000864919 005__ 20210130002752.0
000864919 037__ $$aFZJ-2019-04522
000864919 1001_ $$0P:(DE-Juel1)145110$$aLohmann, Philipp$$b0$$eCorresponding author$$ufzj
000864919 1112_ $$aJahrestagung der Deutschen Gesellschaft für Nuklearmedizin 2019$$cBremen$$d2019-04-03 - 2019-04-06$$wGermany
000864919 245__ $$aCombined FET PET/MRI radiomics differentiates radiation injury from brain metastasis recurrence
000864919 260__ $$c2019
000864919 3367_ $$0PUB:(DE-HGF)1$$2PUB:(DE-HGF)$$aAbstract$$babstract$$mabstract$$s1567761646_26832
000864919 3367_ $$033$$2EndNote$$aConference Paper
000864919 3367_ $$2BibTeX$$aINPROCEEDINGS
000864919 3367_ $$2DRIVER$$aconferenceObject
000864919 3367_ $$2DataCite$$aOutput Types/Conference Abstract
000864919 3367_ $$2ORCID$$aOTHER
000864919 520__ $$aL6Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasisP. Lohmann1, M. Kocher1, G. Ceccon2, E. K. Bauer2, G. Stoffels1, S. Viswanathan1, M. I. Ruge3, B. Neumaier1, N. J. Shah1, G. R. Fink2, K. Langen1, N. Galldiks21Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich; 2University of Cologne, Dept. of Neurology, Cologne; 3University of Cologne, Dept. of Stereotaxy and Functional Neurosurgery, CologneZiel/Aim:The aim of this study was to investigate the potential of combined textural feature analysis of contrast-enhanced MRI (CE-MRI) and static O-(2-[F-18]fluoroethyl)-L-tyrosine (FET) PET for the differentiation between local recurrent brain metastasis and radiation injury since CE-MRI often remains inconclusive.Methodik/Methods:Fifty-two patients with new or progressive contrast-enhancing brain lesions on MRI after radiotherapy (predominantly stereotactic radiosurgery) of brain metastases were additionally investigated using FET PET. Based on histology (n = 19) or clinicoradiological follow-up (n = 33), local recurrent brain metastases were diagnosed in 21 patients (40%) and radiation injury in 31 patients (60%). Forty-two textural features were calculated on both unfiltered and filtered CE-MRI and summed FET PET images (20 - 40 min p.i.), using the software LIFEx. After feature selection, logistic regression models using a maximum of five features to avoid overfitting were calculated for each imaging modality separately and for the combined FET PET/MRI features. The resulting models were validated using cross-validation. Diagnostic accuracies were calculated for each imaging modality separately as well as for the combined model.Ergebnisse/Results:For the differentiation between radiation injury and recurrence of brain metastasis, textural features extracted from CE-MRI had a diagnostic accuracy of 81% (sensitivity, 67%; specificity, 90%). FET PET textural features revealed a slightly higher diagnostic accuracy of 83% (sensitivity, 88%; specificity, 75%). However, the highest diagnostic accuracy was obtained when combining CE-MRI and FET PET features (accuracy, 89%; sensitivity, 85%; specificity, 96%).Schlussfolgerungen/Conclusions:Our findings suggest that combined FET PET/MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.
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000864919 7001_ $$0P:(DE-Juel1)173675$$aKocher, M.$$b1$$ufzj
000864919 7001_ $$0P:(DE-HGF)0$$aCeccon, G.$$b2
000864919 7001_ $$0P:(DE-HGF)0$$aBauer, E. K.$$b3
000864919 7001_ $$0P:(DE-Juel1)131627$$aStoffels, G.$$b4$$ufzj
000864919 7001_ $$0P:(DE-Juel1)162395$$aViswanathan, S.$$b5$$ufzj
000864919 7001_ $$0P:(DE-HGF)0$$aRuge, M. I.$$b6
000864919 7001_ $$0P:(DE-Juel1)166419$$aNeumaier, B.$$b7$$ufzj
000864919 7001_ $$0P:(DE-Juel1)131794$$aShah, N. J.$$b8$$ufzj
000864919 7001_ $$0P:(DE-Juel1)131720$$aFink, G. R.$$b9$$ufzj
000864919 7001_ $$0P:(DE-Juel1)131777$$aLangen, K. J.$$b10$$ufzj
000864919 7001_ $$0P:(DE-Juel1)143792$$aGalldiks, N.$$b11$$ufzj
000864919 8564_ $$uhttps://www.nuklearmedizin.de/jahrestagungen/abstr_online2019/abstract_detail.php?navId=227&aId=10
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000864919 9131_ $$0G:(DE-HGF)POF3-572$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$v(Dys-)function and Plasticity$$x0
000864919 9141_ $$y2019
000864919 920__ $$lyes
000864919 9201_ $$0I:(DE-Juel1)INM-3-20090406$$kINM-3$$lKognitive Neurowissenschaften$$x0
000864919 9201_ $$0I:(DE-Juel1)INM-4-20090406$$kINM-4$$lPhysik der Medizinischen Bildgebung$$x1
000864919 9201_ $$0I:(DE-Juel1)INM-5-20090406$$kINM-5$$lNuklearchemie$$x2
000864919 980__ $$aabstract
000864919 980__ $$aVDB
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