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Development of a “Geo-Tagged” tumor sample registry: intra-operative linkage of sample location to imaging

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Abstract

Purpose

There is a growing body of literature documenting glioma heterogeneity in terms of radiographic, histologic, molecular, and genetic characteristics. Incomplete spatial specification of intraoperative tumor samples may contribute to variability in the results of pathological and biological investigations. We have developed a system, termed geo-tagging, for routine intraoperative linkage of each tumor sample to its location via neuronavigation.

Methods

This is a single-institution, IRB approved, prospective database of undergoing clinically indicated surgery. We evaluated relevant factors affecting data collection by this registry, including tumor and surgical factors (e.g. tumor volume, location, grade and surgeon).

Results

Over a 2-year period, 487 patients underwent craniotomy for an intra-axial tumor. Of those, 214 underwent surgery for a newly diagnosed or recurrent glioma. There was significant variation in the average number of samples collected per registered case, with a range of samples from 2.53 to 4.75 per tumor type. Histology and grade impacted on sampling with a range of 2.0 samples per tumor in Grade four, IDH-WT gliomas to 4.5 samples in grade four, IDH-mutant gliomas. The range of cases with sampling per surgeon was 6 to 99 with a mean of 47.6 cases and there was a statistically significant differences between surgeons. Tumor grade did not have a statistically significant impact on number of samples per case. No significant correlation was found between the number of samples collected and enhancing tumor volume, EOR, or volume of tumor resected.

Conclusion

We are using the results of this analysis to develop a prospective sample collection protocol.

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Data Availability

Deidentified data may be made available upon request.

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Funding

The authors declare that no funds, grants or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Department of Neurosurgery, Medstar Georgetown Hospital, Washington, DC, USA

    John Lynes

  2. Georgetown University School of Medicine, Washington, DC, USA

    John Lynes, Irfan Khan & Carlos Aguilera

  3. Northwell Health Physician Partners Neurosurgery at Seaview Avenue, Staten Island, NY, USA

    Sebastian Rubino

  4. Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL, 33612, USA

    Zachary Thompson

  5. Department of NeuroOncology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL, 33612, USA

    Arnold B. Etame, James K. C. Liu, Andre Beer-Furlan, Nam D. Tran & Michael A. Vogelbaum

  6. Department of Pathology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL, 33612, USA

    Robert J. B. Macaulay

Authors
  1. John Lynes
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  2. Irfan Khan
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  3. Carlos Aguilera
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  4. Sebastian Rubino
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  5. Zachary Thompson
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  11. Michael A. Vogelbaum
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by JL, ZT and MAV. Initial drafting of the manuscript was performed by JL and MAV. All authors commented on previous versions of the manuscript, and have read and approved the final manuscript.

Corresponding author

Correspondence to Michael A. Vogelbaum.

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Competing interests

The authors have no financial interests that are relevant to the subject matter of this work. MAV has financial interests that are unrelated to this work, and include honoraria from Olympus, Midatech, and Chimerix.

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Lynes, J., Khan, I., Aguilera, C. et al. Development of a “Geo-Tagged” tumor sample registry: intra-operative linkage of sample location to imaging. J Neurooncol 165, 449–458 (2023). https://doi.org/10.1007/s11060-023-04493-2

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  • DOI: https://doi.org/10.1007/s11060-023-04493-2

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