CT-perfusion imaging of the human brain: advanced deconvolution analysis using circulant singular value decomposition

Area of Science:

• Medical Imaging
• Radiology
• Biophysics

Background:

• Accurate perfusion imaging requires deconvolution of tissue time-concentration curves with arterial input curves.
• Existing methods may be sensitive to variations in tracer arrival time.

Purpose of the Study:

• To adapt and validate a deconvolution method from magnetic resonance imaging (MRI) for computed tomography (CT) perfusion imaging.
• To improve the accuracy of dynamic contrast-enhanced CT perfusion calculations.

Main Methods:

• Applied a block-circulant matrix approach for singular value decomposition.
• Adapted an MRI-derived deconvolution technique for dynamic contrast-enhanced CT perfusion.
• Validated the method for perfusion imaging analysis.

Main Results:

• The adapted deconvolution method provides valid perfusion results.
• The block-circulant matrix approach makes the analysis independent of tracer arrival time.
• Improved accuracy in dynamic contrast-enhanced CT perfusion imaging.

Conclusions:

• The adapted deconvolution method is effective for dynamic contrast-enhanced CT perfusion imaging.
• Independence from tracer arrival time enhances the reliability of perfusion calculations.
• This technique offers a valuable tool for quantitative perfusion assessment.