
==== Front
Neurooncol Adv
Neurooncol Adv
noa
Neuro-Oncology Advances
2632-2498
Oxford University Press US

10.1093/noajnl/vdae090.064
vdae090.064
Final Category: Neuroimaging/Radiologic Advances
AcademicSubjects/MED00300
AcademicSubjects/MED00310
NIRL-03 REGRESSION ANALYSIS OF NON-CATEGORICAL IMAGING PARAMETERS IN PATIENTS WITH BRAIN METASTASES
Paruchuri Venkata University of Queensland - Ochsner Clinical School, New Orleans, LA, USA

Patel Dhaval University of Queensland - Ochsner Clinical School, New Orleans, LA, USA

Hafeez-Baig M Ahmed University of Queensland Mayne Medical School, Brisbane, QLD, Australia

8 2024
02 8 2024
02 8 2024
6 Suppl 1 2024 SNO/ASCO CNS Metastases Conference i20i20
© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Abstract

BACKGROUND

Estimating survival of patients who have brain metastases (BM) based on risk factors and properties of the metastasis would be useful in clinical practice. Imaging data routinely provides significant variables such as volumes of the tumor, surrounding necrosis, and associated edema. These values could be used to create models that could predict patient survival. Our work applied regression analysis to see how imaging parameters correlated to survival in BM patients.

METHODS

The open-access dataset Pretreat-MetsToBrain-Masks1,2 from the Yale Department of Radiology and Biomedical Imaging featuring 200 BM patients was accessed through the Cancer Imaging Archive. We utilized the Analysis TookPak in Microsoft Excel to perform regression analysis of all non-categorical variables with respect to survival. We performed multivariate regression between survival, edema volume, and necrosis volume. Patients with missing data were omitted from the regression analysis.

RESULTS

There is low correlation between survival and the individual parameters of necrosis ratio (R = 0.12), edema ratio (R = 0.06), necrosis volume (R = 0.02), edema volume (R = 0.06), enhancing tumor (ET) volume (R = 0.18), number of edema lesions (R = 0.10), number of necrotic lesions (R = 0.07), or number of ET lesions (R = 0.05). However, the relationship between enhancing tumor volume and survival does show significance (p = 0.01). The multivariate regression between survival, edema volume, and necrosis volume showed low correlation (0.05) and no statistical significance.

CONCLUSION

There is a significant need to estimate survival in BM patients. However, based on our analysis, we did not find utility in the assessed imaging parameters to estimate survival via a linear model. Still, ET volume was shown to have a significant relationship with survival, and a different model needs to be used to evaluate that relationship.
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