While perfusion imaging is a well established diagnostic imaging technique, until now, it could not be performed
using angiographic equipment. The ability to assess information about tissue perfusion in the angiographic suite
should help to optimize management of patients with neurovascular diseases. We present a technique to measure
cerebral blood volume (CBV) for the entire brain using an angiographic C-arm system. Combining a rotational
acquisition protocol similar to that used for standard three-dimensional rotational angiography (3D DSA) in
conjunction with a modified injection protocol providing a steady state of tissue contrast during the acquisition
the data necessary to calculate CBV is acquired. The three-dimensional (3D) CBV maps are generated using a
special reconstruction scheme which includes the automated detection of an arterial input function and several
correction steps. For evaluation we compared this technique with standard perfusion CT (PCT) measurements
in five healthy canines. Qualitative comparison of the CBV maps as well as quantitative comparison using 12
ROIs for each map showed a good correlation between the new technique and traditional PCT. In addition we
evaluated the technique in a stroke model in canines. The presented technique provides the first step toward
providing information about tissue perfusion available during the treatment of neurovascular diseases in the
angiographic suite.
KEYWORDS: Sensors, Imaging systems, X-rays, Detection and tracking algorithms, Data acquisition, 3D modeling, Image quality, Reconstruction algorithms, Signal attenuation, Visualization
The integration of 3D-imaging functionality into C-arm systems combines advantages of interventional X-ray systems, e.g. good patient access and live fluoroscopy, with 3D imaging capabilities similar to those of a CT-scanner. To date 3D-imaging with a C-arm system has been mainly used to visualize high contrast objects. However, the advent of high quality flat panel detectors improves the low contrast imaging capabilities. We discuss the influence of scattered radiation, beam hardening, truncated projections, quantization and detector recording levels on the image quality.
Subsequently, we present algorithms and methods to correct these effects in order to achieve low contrast resolution. The performance of our pre- and post-reconstructive correction procedures is demonstrated by first clinical cases.
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