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Investigating the potential of segmented echo-planar imaging-based susceptibility-weighted imaging for glioma grading
Satyajit Maurya1, Rakesh Kumar Gupta2, Anup Singh3,4,5
1Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India.
Background:
Susceptibility-weighted imaging (SWI) has shown potential in glioma grading using features like intratumoral susceptibility signals (ITSS). Segmented echo-planar imaging-based SWI (SWI-EPI) sequence offers good spatial coverage and a high signal-to-noise ratio.
Objective:
To evaluate segmented echo-planar imaging-based susceptibility-weighted imaging (SWI-EPI) for glioma grading utilizing ITSS volume (ITV) and a proposed new metric, normalized ITV (nITV), calculated as the ratio of ITV to total tumor volume, to improve grading accuracy.
Methods:
ITSS were segmented from the SWI-EPI sequence. ITV was computed and normalized by whole tumor volume to derive nITV. Statistical analysis included Shapiro-Wilk, Mann-Whitney, Kruskal-Wallis, and receiver-operating-characteristic (ROC) curve analyses to assess the effectiveness of both the metrics in glioma grading.
Results:
The proposed nITV metric significantly enhanced glioma grading accuracy. The area under the ROC curve (AUC) for nITV was consistently higher than for ITV when differentiating between grades 2 vs. 3 (0.886 vs. 0.818), 2 vs. 4 (0.969 vs. 0.939), and 3 vs. 4 (0.832 vs. 0.788). For differentiating low- vs. high-grade gliomas, nITV achieved an AUC of 0.95. Confusion matrices confirmed nITV led to fewer misclassifications.
Conclusion:
ITSS quantification from SWI-EPI is effective for tumor evaluation. The proposed nITV metric provides superior glioma grading efficiency compared to ITV.
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