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Probabilistic independent component analysis of dynamic susceptibility contrast perfusion MRI in metastatic brain

Ararat Chakhoyan1,2, Catalina Raymond1,2, Jason Chen3

  • 1UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.

Cancer Imaging : the Official Publication of the International Cancer Imaging Society
|March 20, 2019
PubMed
Abstract

Insights

Advanced MRI techniques reveal distinct perfusion patterns in brain metastases. Independent component analysis (ICA) identified differences in arterial and venous components not seen with standard measurements, aiding in understanding tumor vasculature.

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Brain metastases represent a significant clinical challenge.
  • Accurate characterization of metastatic brain lesions is crucial for treatment planning.
  • Standard MRI metrics may not fully capture the heterogeneity of tumor vasculature.

Purpose of the Study:

  • To identify clinically relevant magnetic resonance imaging (MRI) features of different metastatic brain lesion types.
  • To compare standard anatomical, diffusion-weighted imaging (DWI), and dynamic susceptibility contrast (DSC) perfusion MRI findings.
  • To explore advanced analysis techniques for characterizing brain metastases.

Main Methods:

  • Retrospective assessment of MRI scans from 114 patients with brain metastases (breast, NSCLC, other).
  • Segmentation of 346 contrast-enhancing tumors.
  • Analysis included tumor volume, apparent diffusion coefficients (ADC), relative cerebral blood volume (rCBV), and independent component analysis (ICA) of DSC data.
  • ICA assessed arterio-venous components, volume of overlap (AVOL), and time to peak (TTP).

Main Results:

  • 'Other' primary tumors showed significantly higher volumes than breast or NSCLC metastases.
  • No significant differences in median ADC or rCBV were observed across tumor types.
  • ICA revealed significantly higher 'arterial' proportions in breast and NSCLC tumors compared to 'other'.
  • Breast tumors exhibited a higher 'venous' proportion than NSCLC and 'other' lesions.
  • AVOL correlated positively with rCBV; arterial and venous components did not correlate with rCBV.
  • Median TTP for arterial and venous components were 8.4s and 12.6s, respectively, with no inter-group differences.

Conclusions:

  • Advanced ICA-derived component analysis reveals perfusion differences between metastatic brain tumor types.
  • These perfusion differences are not observable with classical ADC and rCBV measurements.
  • The findings highlight the complex relationship between brain tumor vasculature and primary tumor site.
Keywords:
BiomarkerBrain metastasisDiffusionICAPerfusion

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