Detector system comparison using relative CNR for specific imaging tasks related to neuro-endovascular image-guided interventions (neuro-EIGIs).

Neuro-EIGIs require visualization of very small endovascular devices and small vessels. A Microangiographic Fluoroscope (MAF) x-ray detector was developed to improve on the standard flat panel detector's (FPD's) ability to visualize small objects during neuro-EIGIs. To compare the performance of FPD and MAF imaging systems, specific imaging tasks related to those encountered during neuro-EIGIs were used to assess contrast to noise ratio (CNR) of different objects. A bar phantom and a stent were placed at a fixed distance from the x-ray focal spot to mimic a clinical imaging geometry and both objects were imaged by each detector system. Imaging was done without anti-scatter grids and using the same conditions for each system including: the same x-ray beam quality, collimator position, source to imager distance (SID), and source to object distance (SOD). For each object, relative contrasts were found for both imaging systems using the peak and trough signals. The relative noise was found using mean background signal and background noise for varying detector exposures. Next, the CNRs were found for these values for each object imaged and for each imaging system used. A relative CNR metric is defined and used to compare detector imaging performance. The MAF utilizes a temporal filter to reduce the overall image noise. The effects of using this filter with the MAF while imaging the clinical object's CNRs are reported. The relative CNR for the detectors demonstrated that the MAF has superior CNRs for most objects and exposures investigated for this specific imaging task.

Design considerations for a new, high resolution Micro-Angiographic Fluoroscope based on a CMOS sensor (MAF-CMOS).

The detectors that are used for endovascular image-guided interventions (EIGI), particularly for neurovascular interventions, do not provide clinicians with adequate visualization to ensure the best possible treatment outcomes. Developing an improved x-ray imaging detector requires the determination of estimated clinical x-ray entrance exposures to the detector. The range of exposures to the detector in clinical studies was found for the three modes of operation: fluoroscopic mode, high frame-rate digital angiographic mode (HD fluoroscopic mode), and DSA mode. Using these estimated detector exposure ranges and available CMOS detector technical specifications, design requirements were developed to pursue a quantum limited, high resolution, dynamic x-ray detector based on a CMOS sensor with 50 µm pixel size. For the proposed MAF-CMOS, the estimated charge collected within the full exposure range was found to be within the estimated full well capacity of the pixels. Expected instrumentation noise for the proposed detector was estimated to be 50-1,300 electrons. Adding a gain stage such as a light image intensifier would minimize the effect of the estimated instrumentation noise on total image noise but may not be necessary to ensure quantum limited detector operation at low exposure levels. A recursive temporal filter may decrease the effective total noise by 2 to 3 times, allowing for the improved signal to noise ratios at the lowest estimated exposures despite consequent loss in temporal resolution. This work can serve as a guide for further development of dynamic x-ray imaging prototypes or improvements for existing dynamic x-ray imaging systems.

New head equivalent phantom for task and image performance evaluation representative for neurovascular procedures occurring in the Circle of Willis.

Phantom equivalents of different human anatomical parts are routinely used for imaging system evaluation or dose calculations. The various recommendations on the generic phantom structure given by organizations such as the AAPM, are not always accurate when evaluating a very specific task. When we compared the AAPM head phantom containing 3 mm of aluminum to actual neuro-endovascular image guided interventions (neuro-EIGI) occurring in the Circle of Willis, we found that the system automatic exposure rate control (AERC) significantly underestimated the x-ray parameter selection. To build a more accurate phantom for neuro-EIGI, we reevaluated the amount of aluminum which must be included in the phantom. Human skulls were imaged at different angles, using various angiographic exposures, at kV's relevant to neuro-angiography. An aluminum step wedge was also imaged under identical conditions, and a correlation between the gray values of the imaged skulls and those of the aluminum step thicknesses was established. The average equivalent aluminum thickness for the skull samples for frontal projections in the Circle of Willis region was found to be about 13 mm. The results showed no significant changes in the average equivalent aluminum thickness with kV or mAs variation. When a uniform phantom using 13 mm aluminum and 15 cm acrylic was compared with an anthropomorphic head phantom the x-ray parameters selected by the AERC system were practically identical. These new findings indicate that for this specific task, the amount of aluminum included in the head equivalent must be increased substantially from 3 mm to a value of 13 mm.

Evaluation of intracranial aneurysm coil embolization in phantoms and patients using a high-resolution Microangiographic Fluoroscope (MAF).

Intracranial aneurysm (IA) embolization using Gugliemi Detachable Coils (GDC) under x-ray fluoroscopic guidance is one of the most important neuro-vascular interventions. Coil deposition accuracy is key and could benefit substantially from higher resolution imagers such as the micro-angiographic fluoroscope (MAF). The effect of MAF guidance improvement over the use of standard Flat Panels (FP) is challenging to assess for such a complex procedure. We propose and investigate a new metric, inter-frame cross-correlation sensitivity (CCS), to compare detector performance for such procedures. Pixel (P) and histogram (H) CCS's were calculated as one minus the cross-correlation coefficients between pixel values and histograms for the region of interest at successive procedure steps. IA treatment using GDC's was simulated using an anthropomorphic head phantom which includes an aneurysm. GDC's were deposited in steps of 3 cm and the procedure was imaged with a FP and the MAF. To measure sensitivity to detect progress of the procedure by change in images of successive steps, an ROI was selected over the aneurysm location and pixel-value and histogram changes were calculated after each step. For the FP, after 4 steps, the H and P CCSs between successive steps were practically zero, indicating that there were no significant changes in the observed images. For the MAF, H and P CCSs were greater than zero even after 10 steps (30 cm GDC), indicating observable changes. Further, the proposed quantification method was applied for evaluation of seven patients imaged using the MAF, yielding similar results (H and P CCSs greater than zero after the last GDC deposition). The proposed metric indicates that the MAF can offer better guidance during such procedures.