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| Hauptseite > Publikationsdatenbank > Radiomics derived from amino acid PET and conventional MRI in patients with high-grade gliomas > print |
| Hauptseite > Publikationsdatenbank > Radiomics derived from amino acid PET and conventional MRI in patients with high-grade gliomas > print |
| 001 | 850813 | ||
| 005 | 20210129234634.0 | ||
| 024 | 7 | _ | |a 10.23736/S1824-4785.18.03095-9 |2 doi |
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| 037 | _ | _ | |a FZJ-2018-04584 |
| 082 | _ | _ | |a 570 |
| 100 | 1 | _ | |a Lohmann, Philipp |0 P:(DE-Juel1)145110 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Radiomics derived from amino acid PET and conventional MRI in patients with high-grade gliomas |
| 260 | _ | _ | |a Torino |c 2018 |b Ed. Minerva Medica |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Radiomics is a technique that uses high-throughput computing to extract quantitative features from tomographic medical images such as MRI and PET that usually are beyond visual perception. Importantly, the radiomics approach can be performed using neuroimages that have already been acquired during the routine follow-up of the patients allowing an additional data evaluation at low cost. In Neuro-Oncology, these features can potentially be used for differential diagnosis of newly diagnosed cerebral lesions suggestive for brain tumors or for the prediction of response to a neurooncological treatment option. Furthermore, especially in the light of the recent update of the World Health Organization classification of brain tumors, radiomics also has the potential to non-invasively assess important prognostic and predictive molecular markers such as a mutation in the isocitrate dehydrogenase gene or a 1p/19q codeletion which are not accessible by conventional visual interpretation of MRI or PET findings. This review summarizes the current status of the rapidly evolving field of radiomics with a special focus on patients with high-grade gliomas. |
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| 773 | _ | _ | |a 10.23736/S1824-4785.18.03095-9 |0 PERI:(DE-600)2083933-9 |n 3 |p 272-80 |t The quarterly journal of nuclear medicine and molecular imaging |v 62 |y 2018 |x 0392-0208 |
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