Artikel
Abnormality of functional connectivity measured by resting state functional MRI in glioma patients is associated with WHO grade, IDH-mutation status and neurocognitive performance
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Autoren
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Veit Stöcklein
- Klinikum der Universität München, Neurochirurgische Klinik und Poliklinik, München, Deutschland; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Standort München, Heidelberg, Deutschland
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Sophia Stöcklein
- Klinikum der Universität München, Klinik und Poliklinik für Radiologie, München, Deutschland
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Niklas Thon
- Klinikum der Universität München, Neurochirurgische Klinik und Poliklinik, München, Deutschland; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Standort München, Heidelberg, Deutschland
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Friedrich-Wilhelm Kreth
- Klinikum der Universität München, Neurochirurgische Klinik und Poliklinik, München, Deutschland; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Standort München, Heidelberg, Deutschland
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Jörg-Christian Tonn
- Klinikum der Universität München, Neurochirurgische Klinik und Poliklinik, München, Deutschland; Deutsches Konsortium für Translationale Krebsforschung (DKTK), Standort München, Heidelberg, Deutschland
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Hesheng Liu
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Boston, MA, Vereinigte Staaten
| Veröffentlicht: | 18. Juni 2018 |
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Gliederung
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Objective: Gliomas are malignant brain tumors that diffusely infiltrate the brain parenchyma. We hypothesized that this could lead to disturbances in neuronal connections and that the degree of damage to neuronal connections is correlated with the aggressiveness of the tumor as indicated by WHO grade. We used resting state functional MRI (rsfMRI) to test this hypothesis.
Methods: 34 patients with de-novo gliomas were prospectively included and rsfMRI data were obtained. Patients underwent neuropsychological testing at the same time using the Montreal Cognitive Assessment test. We developed a standardized score to evaluate the abnormality of functional connectivity in glioma patients by comparing each patient’s data to data obtained from 1000 healthy individuals. Abnormality was quantified at each voxel of the brain, resulting in an individual measure for abnormality (abnormality index AI). Furthermore, data was projected onto a standardized brain template, resulting in an individual abnormality map.
Results: Tumors were diagnosed as WHO grade II tumors (n=13), WHO grade III (n=6) and IV (n=15). 17/34 patients had IDH1/2-mutations. We found that abnormality index is significantly associated with WHO grade: patients with grade III and IV displayed higher AI with the strongest association seen in the non-lesional hemisphere (p=0.0294). Additionally, the AI was significantly increased in patients with IDH-wildtype gliomas again with strongest effect in the non-lesional hemisphere (p=0.013). Neurocognitive performance and AI was significantly correlated, this was most pronounced in the lesional hemisphere.
Conclusion: Abnormality index (AI) is a novel method to investigate functional connectivity in glioma patients on an individual basis. AI is significantly associated with WHO grade and IDH mutation status (especially in the non-lesional hemisphere) and correlates significantly with neurocognitive performance. Individual AI maps show the potential of this technique to gain information beyond conventional structural MRI.
