Date of Award

January 2020

Document Type

Thesis

Degree Name

Medical Doctor (MD)

Department

Medicine

First Advisor

Daniel Coman

Abstract

Aims: Given increasing interest in laser interstitial thermotherapy to treat brain tumor

patients, we explored if examining multiple MRI contrasts per laser patient can impact

predictive accuracy of survival post-LITT.

Methods: MRI contrasts included FALIR, T1 pre-gadolinium (T1pre), T1 postgadolinium (T1Gd), T2, DWI, ADC, SWI, and MPRAGE. The latter was used for MRI

data registration across preoperative to postoperative scans. Two ROIs were identified by

thresholding preoperative FLAIR (large ROI) and T1Gd (small ROI) images. For each

MRI contrast, a numerical score was assigned based on changing image intensity of both

ROIs (vs. a normal ROI) from preoperative to postoperative stages. The fully-quantitative

method was based on changing image intensity across scans at different stages without

any human intervention, whereas the semi-quantitative method was based on subjective

criteria of cumulative trends across scans at different stages. A fully-quantitative/semiquantitative score per patient was obtained by averaging scores for each MRI contrast. A

standard neuroradiological reading score per patient was obtained from radiological

interpretation of MRI data. Scores from all 3 methods per patient were compared against

patient survival, and re-examined for comorbidity and pathology effects.

Results: Patient survival correlated best with semi-quantitative scores obtained from

T1Gd, ADC, and T2 data, and these correlations improved when biopsy and comorbidity

were included.3

Conclusion: These results suggest interfacing neuroradiological readings with semiquantitative image analysis can improve predictive accuracy of patient survival.

Comments

This thesis is restricted to Yale network users only. This thesis is permanently embargoed from public release.

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