journal article·2023-09-22Open access

Histogram-Based Analysis of Low- and High-Grade Glioma and Its Surrounding Edema Using Arterial Spin Labeling Magnetic Resonance Imaging

Thomas Lindner, Lasse Dührsen, Anna Andriana Kyselyova, Wiebke Entelmann, Luis Hau, Jens Fiehler

Applied Sciences· Volume 13· Issue 19

Abstract

A glioma is a type of intra-axial brain tumor originating from the glial cells. Making up about one-third of all brain tumors, a timely diagnosis alongside correct grading and subsequent therapy planning is crucial. Magnetic Resonance Imaging is an established method for the diagnosis of tumors. Arterial Spin Labeling (ASL) Perfusion Imaging allows for the non-contrast enhanced visualization of tumor hyper- or hypoperfusion. Commonly, cell swelling occurs around the tumor that causes edema, which subsequently puts healthy tissue at risk by potentially reducing regional perfusion. The patient collective in this study consists of 495 patients (501 scans) with histopathologically confirmed grade II-IV diffuse gliomas. The aim of this study was to evaluate the potential of histogram analysis of the ASL data to find biomarkers for the pathological diagnosis, grading, MGMT, and mutation status of the tumors as well as the analysis of tumor-surrounding edema. The analysis showed statistically significant results for the pathological diagnosis and grading but not for MGMT status or mutation. The differentiation between tumor and edema showed highly significant results yet did not show differences between edema and perfusion on the contralateral hemisphere.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Glioma Diagnosis and Treatment · Advanced MRI Techniques and Applications · MRI in cancer diagnosis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, 20246 Hamburg, Germany

Department of Neurosurgery, University Hospital Hamburg-Eppendorf, 20246 Hamburg, Germany

Funding

German Research Foundation (DFG)

References (32)

Show source-provided references
1. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012–201610.1093/neuonc/noz150 ↗
2. The 2021 WHO Classification of Tumors of the Central Nervous System: A summary10.1093/neuonc/noab106 ↗
3. Nehring, S.M., Tadi, P., and Tenny, S. (2023, August 24). Cerebral Edema, StatPearls [Internet], Available online: https://www.ncbi.nlm.nih.gov/books/NBK537272/.
4. Edema and tumor perfusion: Characterization by quantitative 1H MR imaging10.2214/ajr.158.2.1729777 ↗
5. Diagnostic Accuracy of PET for Recurrent Glioma Diagnosis: A Meta-Analysis10.3174/ajnr.A3324 ↗
6. Diagnostic Accuracy of PET for Differentiating True Glioma Progression From Post Treatment-Related Changes: A Systematic Review and Meta-Analysis10.3389/fneur.2021.671867 ↗
7. Diagnostic Accuracy of PET Tracers for the Differentiation of Tumor Progression from Treatment-Related Changes in High-Grade Glioma: A Systematic Review and Metaanalysis10.2967/jnumed.119.233809 ↗
8. Role of Magnetic Resonance Imaging (MRI) in grading gliomas comparable with pathology: A cross-sectional study from Syria10.1016/j.amsu.2022.104679 ↗
9. MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: A systematic review and meta-analysis10.1007/s10143-017-0906-0 ↗
10. Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences10.3389/fonc.2021.694498 ↗
11. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia10.1002/mrm.25197 ↗
12. Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging10.1002/mrm.29572 ↗
13. Arterial spin labeling MR imaging for differentiation between high- and low-grade glioma—A meta-analysis10.1093/neuonc/noy095 ↗
14. The value of arterial spin labelling in adults glioma grading: Systematic review and meta-analysis10.18632/oncotarget.26674 ↗
15. Perfusion imaging with arterial spin labeling (ASL)–MRI predicts malignant progression in low-grade (WHO grade II) gliomas10.1007/s00234-021-02737-4 ↗
16. Systematic review and meta-analysis of arterial spin-labeling imaging to distinguish between glioma recurrence and post-treatment radiation effect10.21037/apm-21-3319 ↗
17. The diagnostic value of quantitative analysis of ASL, DSC-MRI and DKI in the grading of cerebral gliomas: A meta-analysis10.1186/s13014-020-01643-y ↗
18. Kang, X.-W., Xi, Y.-B., Liu, T.-T., Wang, N., Zhu, Y.-Q., Wang, X.-R., and Guo, F. (2020). Grading of Glioma: Combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging. BMC Med. Imaging, 20.10.1186/s12880-020-00450-x ↗
19. A meta-analysis of arterial spin labelling perfusion values for the prediction of glioma grade10.1016/j.crad.2016.10.016 ↗
20. Based on arterial spin labeling helps to differentiate high-grade gliomas from brain solitary metastasis: A systematic review and meta-analysis10.1097/MD.0000000000015580 ↗
21. The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset10.1148/ryai.220058 ↗
22. Baid, U., Ghodasara, S., Mohan, S., Bilello, M., Calabrese, E., Colak, E., Farahani, K., Kalpathy-Cramer, J., Kitamura, F.C., and Pati, S. (2021). The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification. arXiv.
23. Arterial Spin Labeling for Glioma Grade Discrimination: Correlations with IDH1 Genotype and 1p/19q Status10.1016/j.tranon.2019.02.013 ↗
24. Diagnostic Accuracy of Arterial Spin Labeling in Comparison With Dynamic Susceptibility Contrast-Enhanced Perfusion for Brain Tumor Surveillance at 3T MRI10.3389/fonc.2022.849657 ↗
25. Gihr, G., Horvath-Rizea, D., Kohlhof-Meinecke, P., Ganslandt, O., Henkes, H., Härtig, W., Donitza, A., Skalej, M., and Schob, S. (2022). Diffusion Weighted Imaging in Gliomas: A Histogram-Based Approach for Tumor Characterization. Cancers, 14.10.3390/cancers14143393 ↗
26. Han, L., and Kamdar, M.R. (2018, January 3–7). MRI to MGMT: Predicting methylation status in glioblastoma patients using convolutional recurrent neural networks. Proceedings of the 2018 Pacific Symposium on Biocomputing, Fairmont Orchid, HI, USA.10.1142/9789813235533_0031 ↗
27. Sakai, Y., Yang, C., Kihira, S., Tsankova, N., Khan, F., Hormigo, A., Lai, A., Cloughesy, T., and Nael, K. (2020). MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting. Int. J. Mol. Sci., 21.10.26226/morressier.5e8335ba7cb08a046ef7c713 ↗
28. Perfusion-weighted imaging of peritumoral edema can aid in the differential diagnosis of glioblastoma mulltiforme versus brain metastasis
29. Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas10.3389/fnins.2022.787755 ↗
30. A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging10.1186/s13244-022-01230-7 ↗
31. The 39 steps: Evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI10.1002/nbm.2833 ↗
32. Feasibility of generalised diffusion kurtosis imaging approach for brain glioma grading10.1007/s00234-020-02613-7 ↗