Journal Article

FZJ-2018-05053

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis

Lohmann, P. (Corresponding author)FZJ* ; Kocher, M.FZJ* ; Ceccon, G. ; Bauer, E. K. ; Stoffels, G.FZJ* ; Viswanathan, S.FZJ* ; Ruge, M. I. ; Neumaier, B.FZJ* ; Shah, N. J.FZJ* ; Fink, G. R.FZJ* ; Langen, K.-J.FZJ* ; Galldiks, N.FZJ*

2018
Elsevier [Amsterdam u.a.]

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Please use a persistent id in citations: http://hdl.handle.net/2128/19679  doi:10.1016/j.nicl.2018.08.024

Abstract: 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.

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Contributing Institute(s):

1. Kognitive Neurowissenschaften (INM-3)
2. Physik der Medizinischen Bildgebung (INM-4)
3. Nuklearchemie (INM-5)

Research Program(s):

1. 572 - (Dys-)function and Plasticity (POF3-572) (POF3-572)

Appears in the scientific report 2018

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Database coverage:
; ; ; ; Current Contents - Clinical Medicine ; DOAJ Seal ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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