This title appears in the Scientific Report :
2018
Please use the identifier:
http://dx.doi.org/10.1016/j.nicl.2018.08.024 in citations.
Please use the identifier: http://hdl.handle.net/2128/19679 in citations.
Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis
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...
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Personal Name(s): | Lohmann, Philipp (Corresponding author) |
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Kocher, Martin / Ceccon, Garry / Bauer, Elena K. / Stoffels, Gabriele / Viswanathan, Shivakumar / Ruge, Maximilian I. / Neumaier, Bernd / Shah, Nadim J. / Fink, Gereon R. / Langen, Karl-Josef / Galldiks, Norbert | |
Contributing Institute: |
Nuklearchemie; INM-5 Physik der Medizinischen Bildgebung; INM-4 Kognitive Neurowissenschaften; INM-3 |
Published in: | NeuroImage: Clinical, 20 (2018) S. 537 - 542 |
Imprint: |
[Amsterdam u.a.]
Elsevier
2018
|
PubMed ID: |
30175040 |
DOI: |
10.1016/j.nicl.2018.08.024 |
Document Type: |
Journal Article |
Research Program: |
(Dys-)function and Plasticity |
Link: |
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Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/19679 in citations.
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. |