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Volumetric analysis: Rethinking brain metastases response assessment
Beatriz Ocaña-Tienda1, Julián Pérez-Beteta1, José Antonio Romero-Rosales1
1Mathematical Oncology Laboratory, University of Castilla-La Mancha, Ciudad Real, Spain.
Neuro-Oncology Advances
|January 8, 2024
Summary
Volumetric measurements improve brain metastases (BMs) response assessment over RANO-BM criteria. This new method evaluates all lesions, classifies responses better, and detects recurrence earlier for neuro-oncology patients.
Area of Science:
- Neuro-oncology
- Radiology
- Medical imaging analysis
Background:
- The Response Assessment in Neuro-Oncology for Brain Metastases (RANO-BM) criteria are standard for evaluating brain metastases (BMs) treatment response.
- Current RANO-BM criteria rely on 1D measurements, despite high-resolution 3D MRI scans being routinely used for BMs.
- This limitation highlights the need for improved assessment methods that can leverage 3D imaging data.
Purpose of the Study:
- To investigate the efficacy of volumetric measurements in enhancing the assessment of treatment response in patients with brain metastases.
- To compare the performance of volumetric criteria against the established RANO-BM criteria.
Main Methods:
- Retrospective analysis of 783 brain metastases (BMs) from 132 patients treated with stereotactic radiotherapy.
- Utilized T1-weighted MRI scans to calculate lesion volumes.
- Defined progressive disease as a ≥30% volume increase and partial response as a 20% volume reduction for volumetric criteria.
Main Results:
- Volumetric criteria evaluated all lesions, unlike RANO-BM which missed 9.2%.
- Effectively classified response in 140 lesions compared to 72 by RANO-BM.
- Identified BM recurrences a median of 3.3 months earlier than RANO-BM.
Conclusions:
- Volumetric criteria demonstrate superiority over RANO-BM for assessing brain metastases treatment response.
- Proposed volumetric criteria offer a standardized, reliable, and objective tool for evaluating all lesions, improving classification, and enabling earlier detection of disease progression.
