TY  - JOUR
AU  - Lohmann, Philipp
AU  - Kocher, Martin
AU  - Ceccon, Garry
AU  - Bauer, Elena K.
AU  - Stoffels, Gabriele
AU  - Viswanathan, Shivakumar
AU  - Ruge, Maximilian I.
AU  - Neumaier, Bernd
AU  - Shah, Nadim J.
AU  - Fink, Gereon R.
AU  - Langen, Karl-Josef
AU  - Galldiks, Norbert
TI  - Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
JO  - NeuroImage: Clinical
VL  - 20
SN  - 2213-1582
CY  - [Amsterdam u.a.]
PB  - Elsevier
M1  - FZJ-2018-05053
SP  - 537 - 542
PY  - 2018
AB  - Background<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.
LB  - PUB:(DE-HGF)16
C6  - pmid:30175040
UR  - <Go to ISI:>//WOS:000450799000058
DO  - DOI:10.1016/j.nicl.2018.08.024
UR  - https://juser.fz-juelich.de/record/851404
ER  -