A repository of grade 1 and 2 meningioma MRIs in a public dataset for radiomics reproducibility tests

Author:

Vassantachart April12,Cao Yufeng2,Shen Zhilei2,Cheng Karen12,Gribble Michael3,Ye Jason C.2,Zada Gabriel4,Hurth Kyle5,Mathew Anna5,Guzman Samuel5,Yang Wensha2

Affiliation:

1. Department of Radiation Oncology LAC+USC Medical Center Los Angeles California USA

2. Department of Radiation Oncology Keck School of Medicine University of Southern California Los Angeles California USA

3. Keck School of Medicine University of Southern California Los Angeles California USA

4. Department of Neurological Surgery Keck School of Medicine University of Southern California Los Angeles California USA

5. Department of Pathology Keck School of Medicine University of Southern California Los Angeles California USA

Abstract

AbstractPurposeMeningiomas are the most common primary brain tumors in adults with management varying widely based on World Health Organization (WHO) grade. However, there are limited datasets available for researchers to develop and validate radiomic models. The purpose of our manuscript is to report on the first dataset of meningiomas in The Cancer Imaging Archive (TCIA).Acquisition and validation methodsThe dataset consists of pre‐operative MRIs from 96 patients with meningiomas who underwent resection from 2010–2019 and include axial T1post and T2‐FLAIR sequences—55 grade 1 and 41 grade 2. Meningioma grade was confirmed based on the 2016 WHO Bluebook classification guideline by two neuropathologists and one neuropathology fellow. The hyperintense T1post tumor and hyperintense T2‐FLAIR regions were manually contoured on both sequences and resampled to an isotropic resolution of 1 × 1 × 1 mm3. The entire dataset was reviewed by a certified medical physicist.Data format and usage notesThe data was imported into TCIA for storage and can be accessed at https://doi.org/10.7937/0TKV‐1A36. The total size of the dataset is 8.8GB, with 47 519 individual Digital Imaging and Communications in Medicine (DICOM) files consisting of 384 image series, and 192 structures.Potential applicationsGrade 1 and 2 meningiomas have different treatment paradigms and are often treated based on radiologic diagnosis alone. Therefore, predicting grade prior to treatment is essential in clinical decision‐making. This dataset will allow researchers to create models to auto‐differentiate grade 1 and 2 meningiomas as well as evaluate for other pathologic features including mitotic index, brain invasion, and atypical features. Limitations of this study are the small sample size and inclusion of only two MRI sequences. However, there are no meningioma datasets on TCIA and limited datasets elsewhere although meningiomas are the most common intracranial tumor in adults.

Publisher

Wiley

Subject

General Medicine

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