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[Preprint]. 2023 Sep 12:arXiv:2309.05053v2.

A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information

Divya Ramakrishnan¹, Leon Jekel^{1

2}, Saahil Chadha¹, Anastasia Janas^{1

3}, Harrison Moy^{1

4}, Nazanin Maleki¹, Matthew Sala^{1

5}, Manpreet Kaur^{1

6}, Gabriel Cassinelli Petersen^{1

7}, Sara Merkaj^{1

8}, Marc von Reppert^{1

9}, Ujjwal Baid^{10

11}, Spyridon Bakas^{10

11}, Claudia Kirsch^{1

12

13}, Melissa Davis¹, Khaled Bousabarah¹⁴, Wolfgang Holler¹⁴, MingDe Lin^{1

15}, Malte Westerhoff¹⁴, Sanjay Aneja^{16

17}, Fatima Memon¹, Mariam S Aboian¹

Affiliations

¹ Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA.
² University of Essen School of Medicine, Essen, Germany.
³ Charité University School of Medicine, Berlin, Germany.
⁴ Wesleyan University, Middletown, CT, USA.
⁵ Tulane University School of Medicine, New Orleans, LA, USA.
⁶ Ludwig Maximilian University School of Medicine, Munich, Germany.
⁷ University of Göttingen School of Medicine, Göttingen, Germany.
⁸ Ulm University School of Medicine, Ulm, Germany.
⁹ University of Leipzig School of Medicine, Leipzig, Germany.
¹⁰ Division of Computational Pathology, Department of Pathology & Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
¹¹ Department of Radiology and Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
¹² School of Clinical Dentistry, University of Sheffield, Sheffield, England.
¹³ Diagnostic, Molecular and Interventional Radiology, Biomedical Engineering Imaging, Mount Sinai Hospital, New York City, NY, USA.
¹⁴ Visage Imaging, GmbH, Berlin, Germany.
¹⁵ Visage Imaging, Inc., San Diego, CA, USA.
¹⁶ Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA.
¹⁷ Center for Outcomes Research and Evaluation (CORE), Yale School of Medicine, New Haven, CT, USA.

PMID: 37744461
PMCID: PMC10516117

A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information

Divya Ramakrishnan et al. ArXiv. 2023.

[Preprint]. 2023 Sep 12:arXiv:2309.05053v2.

Authors

Affiliations

¹ Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA.
² University of Essen School of Medicine, Essen, Germany.
³ Charité University School of Medicine, Berlin, Germany.
⁴ Wesleyan University, Middletown, CT, USA.
⁵ Tulane University School of Medicine, New Orleans, LA, USA.
⁶ Ludwig Maximilian University School of Medicine, Munich, Germany.
⁷ University of Göttingen School of Medicine, Göttingen, Germany.
⁸ Ulm University School of Medicine, Ulm, Germany.
⁹ University of Leipzig School of Medicine, Leipzig, Germany.
¹⁰ Division of Computational Pathology, Department of Pathology & Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
¹¹ Department of Radiology and Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
¹² School of Clinical Dentistry, University of Sheffield, Sheffield, England.
¹³ Diagnostic, Molecular and Interventional Radiology, Biomedical Engineering Imaging, Mount Sinai Hospital, New York City, NY, USA.
¹⁴ Visage Imaging, GmbH, Berlin, Germany.
¹⁵ Visage Imaging, Inc., San Diego, CA, USA.
¹⁶ Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, USA.
¹⁷ Center for Outcomes Research and Evaluation (CORE), Yale School of Medicine, New Haven, CT, USA.

PMID: 37744461
PMCID: PMC10516117

Update in

A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information.
Ramakrishnan D, Jekel L, Chadha S, Janas A, Moy H, Maleki N, Sala M, Kaur M, Petersen GC, Merkaj S, von Reppert M, Baid U, Bakas S, Kirsch C, Davis M, Bousabarah K, Holler W, Lin M, Westerhoff M, Aneja S, Memon F, Aboian MS. Ramakrishnan D, et al. Sci Data. 2024 Feb 29;11(1):254. doi: 10.1038/s41597-024-03021-9. Sci Data. 2024. PMID: 38424079 Free PMC article.

Abstract

Resection and whole brain radiotherapy (WBRT) are the standards of care for the treatment of patients with brain metastases (BM) but are often associated with cognitive side effects. Stereotactic radiosurgery (SRS) involves a more targeted treatment approach and has been shown to avoid the side effects associated with WBRT. However, SRS requires precise identification and delineation of BM. While many AI algorithms have been developed for this purpose, their clinical adoption has been limited due to poor model performance in the clinical setting. Major reasons for non-generalizable algorithms are the limitations in the datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models to improve generalizability. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and whole tumor (including peritumoral edema) 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging feature information. We used a streamlined approach to database-building leveraging a PACS-integrated segmentation workflow.

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Conflict of interest statement

M.S.A. has collaborations with Visage Imaging, Inc., Blue Earth Diagnostics, Telix, and AAA. She also has a KL2 TR00186 grant from the NCATS foundation. M.L. is an employee and stockholder of Visage Imaging, Inc., and unrelated to this work, receives funding from NIH/NCI R01 CA206180 and NIH/NCI R01 CA275188. W.H. and M.W. are employees and stockholders of Visage Imaging GmbH. K.B. is an employee of Visage Imaging GmbH. C.K. receives royalties from Primal Pictures 3D Informa, has grant funding from the NIH, and has received the Core Curriculum grant from the American Society of Head and Neck Radiology, all unrelated to this work. The remaining co-authors do not have any competing interests.

Figures

**Fig 1.**
Research PACS annotation layout with T1, T1 post-contrast, FLAIR, and T2 sequences aligned. The PACS interface incorporates a 3D volumetric tool (white circle / rectangle) and displays labeled segmentations for two metastases in the display window (red rectangle).

**Fig 2.**
Segmentations performed in research PACS for one patient. FLAIR (A) included segmentation of whole tumor (“Whole2_FLAIR”), including peritumoral edema, and T1 post-contrast (B) included segmentations of the contrast-enhancing lesion (“Core2_PGGE”) and necrotic portions within the contrast-enhancing lesion (“Necrosis2_PGGE”). (C) Combined segmentation mask overlaid on FLAIR sequence in NIfTI format with the green region representing peritumoral edema, the blue region representing contrast-enhancing tumor, and the red region representing necrotic tumor.

See this image and copyright information in PMC

References

1. Kotecha R, Gondi V, Ahluwalia MS, et al. Recent advances in managing brain metastasis. F1000Res. 2018;7:F1000 Faculty Rev-1772. - PMC - PubMed
1. Boire A, Brastianos PK, Garzia L, et al. Brain metastasis. Nat Rev Cancer. 2020;20(1):4–11. - PubMed
1. Buecker R, Hong ZY, Liu XM, et al. Risk factors to identify patients who may not benefit from whole brain irradiation for brain metastases - a single institution analysis. Radiation Oncology. 2019;14(1):41. - PMC - PubMed
1. Park YW, Choi D, Park JE, et al. Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation. Sci Rep. 2021;11(1):2913. - PMC - PubMed
1. Xue J, Kubicek GJ, Grimm J, et al. Biological implications of whole-brain radiotherapy versus stereotactic radiosurgery of multiple brain metastases. J Neurosurg. 2014;121 Suppl:60–68. - PubMed

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This is a preprint.

A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information

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A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information

Authors

Affiliations

Update in

Abstract

Conflict of interest statement

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References

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