000851404 001__ 851404
000851404 005__ 20220930130156.0
000851404 0247_ $$2doi$$a10.1016/j.nicl.2018.08.024
000851404 0247_ $$2Handle$$a2128/19679
000851404 0247_ $$2pmid$$apmid:30175040
000851404 0247_ $$2WOS$$aWOS:000450799000058
000851404 0247_ $$2altmetric$$aaltmetric:47104564
000851404 037__ $$aFZJ-2018-05053
000851404 082__ $$a610
000851404 1001_ $$0P:(DE-Juel1)145110$$aLohmann, Philipp$$b0$$eCorresponding author
000851404 245__ $$aCombined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
000851404 260__ $$a[Amsterdam u.a.]$$bElsevier$$c2018
000851404 3367_ $$2DRIVER$$aarticle
000851404 3367_ $$2DataCite$$aOutput Types/Journal article
000851404 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1536837249_30556
000851404 3367_ $$2BibTeX$$aARTICLE
000851404 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000851404 3367_ $$00$$2EndNote$$aJournal Article
000851404 520__ $$aBackground<br>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-[18F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation between local recurrent brain metastasis and radiation injury since CE-MRI often remains inconclusive.<br>Methods<br>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.<br>Results<br>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%).<br>Conclusions<br>Our findings suggest that combined FET PET/CE-MRI radiomics using textural feature analysis offers a great potential to contribute significantly to the management of patients with brain metastases.
000851404 536__ $$0G:(DE-HGF)POF3-572$$a572 - (Dys-)function and Plasticity (POF3-572)$$cPOF3-572$$fPOF III$$x0
000851404 588__ $$aDataset connected to CrossRef
000851404 7001_ $$0P:(DE-Juel1)173675$$aKocher, Martin$$b1$$ufzj
000851404 7001_ $$0P:(DE-HGF)0$$aCeccon, Garry$$b2
000851404 7001_ $$0P:(DE-HGF)0$$aBauer, Elena K.$$b3
000851404 7001_ $$0P:(DE-Juel1)131627$$aStoffels, Gabriele$$b4$$ufzj
000851404 7001_ $$0P:(DE-Juel1)162395$$aViswanathan, Shivakumar$$b5
000851404 7001_ $$0P:(DE-HGF)0$$aRuge, Maximilian I.$$b6
000851404 7001_ $$0P:(DE-Juel1)166419$$aNeumaier, Bernd$$b7$$ufzj
000851404 7001_ $$0P:(DE-Juel1)131794$$aShah, Nadim J.$$b8$$ufzj
000851404 7001_ $$0P:(DE-Juel1)131720$$aFink, Gereon R.$$b9$$ufzj
000851404 7001_ $$0P:(DE-Juel1)131777$$aLangen, Karl-Josef$$b10$$ufzj
000851404 7001_ $$0P:(DE-Juel1)143792$$aGalldiks, Norbert$$b11$$ufzj
000851404 773__ $$0PERI:(DE-600)2701571-3$$a10.1016/j.nicl.2018.08.024$$gp. S2213158218302651$$p537 - 542$$tNeuroImage: Clinical$$v20$$x2213-1582$$y2018
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/17210CV5.pdf
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/1-s2.0-S2213158218302651-main.pdf$$yOpenAccess
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/17210CV5.gif?subformat=icon$$xicon
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/17210CV5.jpg?subformat=icon-1440$$xicon-1440
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/17210CV5.jpg?subformat=icon-180$$xicon-180
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/17210CV5.jpg?subformat=icon-640$$xicon-640
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/17210CV5.pdf?subformat=pdfa$$xpdfa
000851404 8564_ $$uhttps://juser.fz-juelich.de/record/851404/files/1-s2.0-S2213158218302651-main.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000851404 8767_ $$817210CV5$$92018-08-22$$d2018-08-22$$eAPC$$jZahlung erfolgt$$p13463$$zFZJ-2018-05047
000851404 909CO $$ooai:juser.fz-juelich.de:851404$$popenCost$$pVDB$$pdriver$$pOpenAPC$$popen_access$$popenaire$$pdnbdelivery
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145110$$aForschungszentrum Jülich$$b0$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)173675$$aForschungszentrum Jülich$$b1$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131627$$aForschungszentrum Jülich$$b4$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)162395$$aForschungszentrum Jülich$$b5$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)166419$$aForschungszentrum Jülich$$b7$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131794$$aForschungszentrum Jülich$$b8$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131720$$aForschungszentrum Jülich$$b9$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131777$$aForschungszentrum Jülich$$b10$$kFZJ
000851404 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)143792$$aForschungszentrum Jülich$$b11$$kFZJ
000851404 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
000851404 9141_ $$y2018
000851404 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000851404 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000851404 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNEUROIMAGE-CLIN : 2015
000851404 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000851404 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000851404 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000851404 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000851404 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000851404 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000851404 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000851404 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine
000851404 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000851404 920__ $$lyes
000851404 9201_ $$0I:(DE-Juel1)INM-3-20090406$$kINM-3$$lKognitive Neurowissenschaften$$x0
000851404 9201_ $$0I:(DE-Juel1)INM-4-20090406$$kINM-4$$lPhysik der Medizinischen Bildgebung$$x1
000851404 9201_ $$0I:(DE-Juel1)INM-5-20090406$$kINM-5$$lNuklearchemie$$x2
000851404 980__ $$ajournal
000851404 980__ $$aVDB
000851404 980__ $$aUNRESTRICTED
000851404 980__ $$aI:(DE-Juel1)INM-3-20090406
000851404 980__ $$aI:(DE-Juel1)INM-4-20090406
000851404 980__ $$aI:(DE-Juel1)INM-5-20090406
000851404 980__ $$aAPC
000851404 9801_ $$aAPC
000851404 9801_ $$aFullTexts