Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas

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Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas. / Griessmair, Michael; Delbridge, Claire; Ziegenfeuter, Julian; Bernhardt, Denise; Gempt, Jens; Schmidt-Graf, Friederike; Kertels, Olivia; Thomas, Marie; Meyer, Hanno S; Zimmer, Claus; Meyer, Bernhard; Combs, Stephanie E; Yakushev, Igor; Wiestler, Benedikt; Metz, Marie-Christin.

In: CANCERS, Vol. 15, No. 8, 2355, 18.04.2023.

Research output: SCORING: Contribution to journalSCORING: Journal articleResearchpeer-review

Harvard

Griessmair, M, Delbridge, C, Ziegenfeuter, J, Bernhardt, D, Gempt, J, Schmidt-Graf, F, Kertels, O, Thomas, M, Meyer, HS, Zimmer, C, Meyer, B, Combs, SE, Yakushev, I, Wiestler, B & Metz, M-C 2023, 'Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas', CANCERS, vol. 15, no. 8, 2355. https://doi.org/10.3390/cancers15082355

APA

Griessmair, M., Delbridge, C., Ziegenfeuter, J., Bernhardt, D., Gempt, J., Schmidt-Graf, F., Kertels, O., Thomas, M., Meyer, H. S., Zimmer, C., Meyer, B., Combs, S. E., Yakushev, I., Wiestler, B., & Metz, M-C. (2023). Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas. CANCERS, 15(8), [2355]. https://doi.org/10.3390/cancers15082355

Vancouver

Bibtex

@article{cdb0a17fa5854487974fc1808d846006,
title = "Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas",
abstract = "BACKGROUND: The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated.MATERIALS AND METHODS: We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4.RESULTS: Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA).CONCLUSIONS: This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.",
author = "Michael Griessmair and Claire Delbridge and Julian Ziegenfeuter and Denise Bernhardt and Jens Gempt and Friederike Schmidt-Graf and Olivia Kertels and Marie Thomas and Meyer, {Hanno S} and Claus Zimmer and Bernhard Meyer and Combs, {Stephanie E} and Igor Yakushev and Benedikt Wiestler and Marie-Christin Metz",
year = "2023",
month = apr,
day = "18",
doi = "10.3390/cancers15082355",
language = "English",
volume = "15",
journal = "CANCERS",
issn = "2072-6694",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "8",

}

RIS

TY - JOUR

T1 - Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas

AU - Griessmair, Michael

AU - Delbridge, Claire

AU - Ziegenfeuter, Julian

AU - Bernhardt, Denise

AU - Gempt, Jens

AU - Schmidt-Graf, Friederike

AU - Kertels, Olivia

AU - Thomas, Marie

AU - Meyer, Hanno S

AU - Zimmer, Claus

AU - Meyer, Bernhard

AU - Combs, Stephanie E

AU - Yakushev, Igor

AU - Wiestler, Benedikt

AU - Metz, Marie-Christin

PY - 2023/4/18

Y1 - 2023/4/18

N2 - BACKGROUND: The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated.MATERIALS AND METHODS: We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4.RESULTS: Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA).CONCLUSIONS: This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.

AB - BACKGROUND: The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated.MATERIALS AND METHODS: We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4.RESULTS: Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA).CONCLUSIONS: This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.

U2 - 10.3390/cancers15082355

DO - 10.3390/cancers15082355

M3 - SCORING: Journal article

C2 - 37190283

VL - 15

JO - CANCERS

JF - CANCERS

SN - 2072-6694

IS - 8

M1 - 2355

ER -