Nuklearmedizin 2019; 58(02): 106-107
DOI: 10.1055/s-0039-1683475
Wissenschaftliches Programm: Leuchtturm-Sitzungen
Leuchtturm-Sitzung 2: Radiomics
Georg Thieme Verlag KG Stuttgart · New York

Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

P Lohmann
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
M Kocher
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
G Ceccon
2   University of Cologne, Dept. of Neurology, Cologne
,
EK Bauer
2   University of Cologne, Dept. of Neurology, Cologne
,
G Stoffels
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
S Viswanathan
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
MI Ruge
3   University of Cologne, Dept. of Stereotaxy and Functional Neurosurgery, Cologne
,
B Neumaier
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
NJ Shah
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
GR Fink
2   University of Cologne, Dept. of Neurology, Cologne
,
KJ Langen
1   Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich
,
N Galldiks
2   University of Cologne, Dept. of Neurology, Cologne
› Author Affiliations
Further Information

Publication History

Publication Date:
27 March 2019 (online)

Also available at
 
 

    Ziel/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.


    #