Brendan Loughran

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 family of generalized metrics for comparative imaging system evaluation

A family of imaging task-specific metrics designated Relative Object Detectability (ROD) metrics was developed to enable objective, quantitative comparisons of different x-ray systems. Previously, ROD was defined as the integral over spatial frequencies of the Fourier Transform of the object function, weighted by the detector DQE for one detector, divided by the comparable integral for another detector. When effects of scatter and focal spot unsharpness are included, the generalized metric, GDQE, is substituted for the DQE, resulting in the G-ROD metric. The G-ROD was calculated for two different detectors with two focal spot sizes using various-sized simulated objects to quantify the improved performance of new high-resolution CMOS detector systems. When a measured image is used as the object, a Generalized Measured Relative Object Detectability (GM-ROD) value can be generated. A neuro-vascular stent (Wingspan) was imaged with the high-resolution Micro-Angiographic Fluoroscope (MAF) and a standard flat panel detector (FPD) for comparison using the GM-ROD calculation. As the lower integration bound increased from 0 toward the detector Nyquist frequency, increasingly superior performance of the MAF was evidenced. Another new metric, the R-ROD, enables comparing detectors to a reference detector of given imaging ability. R-RODs for the MAF, a new CMOS detector and an FPD will be presented. The ROD family of metrics can provide quantitative more understandable comparisons for different systems where the detector, focal spot, scatter, object, techniques or dose are varied and can be used to optimize system selection for given imaging tasks.

Workflow for the use of a high-resolution image detector in endovascular interventional procedures

Endovascular image-guided intervention (EIGI) has become the primary interventional therapy for the most widespread vascular diseases. These procedures involve the insertion of a catheter into the femoral artery, which is then threaded under fluoroscopic guidance to the site of the pathology to be treated. Flat Panel Detectors (FPDs) are normally used for EIGIs; however, once the catheter is guided to the pathological site, high-resolution imaging capabilities can be used for accurately guiding a successful endovascular treatment. The Micro-Angiographic Fluoroscope (MAF) detector provides needed high-resolution, high-sensitivity, and real-time imaging capabilities. An experimental MAF enabled with a Control, Acquisition, Processing, Image Display and Storage (CAPIDS) system was installed and aligned on a detector changer attached to the C-arm of a clinical angiographic unit. The CAPIDS system was developed and implemented using LabVIEW software and provides a user-friendly interface that enables control of several clinical radiographic imaging modes of the MAF including: fluoroscopy, roadmap, radiography, and digital-subtraction-angiography (DSA). Using the automatic controls, the MAF detector can be moved to the deployed position, in front of a standard FPD, whenever higher resolution is needed during angiographic or interventional vascular imaging procedures. To minimize any possible negative impact to image guidance with the two detector systems, it is essential to have a well-designed workflow that enables smooth deployment of the MAF at critical stages of clinical procedures. For the ultimate success of this new imaging capability, a clear understanding of the workflow design is essential. This presentation provides a detailed description and demonstration of such a workflow design.

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.

SU-E-I-83: Parallel Programming Upgrades for the Control Acquisition, Processing and Image Display System (CAPIDS) of the Micro Angiographic Fluoroscope (MAF)

PURPOSE CAPIDS is a unique software platform designed to control and acquire images from the high-resolution MAF detector, process them and display them in a clinical environment. The images are then stored for optional playback at a later stage. CAPIDS also acquires and records the exposure parameters from the x-ray unit. We present new parallel programming modifications using the host computer systems Graphics Processing Unit (GPU) and Central Processing unit (CPU) to improve the system performance for the various MAF imaging tasks. METHODS Multicore CPUs allow for concurrent tasks to be executed at the same time in parallel. During runtime, CAPIDS has three concurrent tasks: image acquisition and processing, image saving, and exposure parameter acquisition. Parallel programming constructs from LabVIEW allow each tasks to be executed on a separate core.GPUs allow for the same task to be performed on independent data sets in parallel. During runtime, all the image processing including flat-field correction, digital image subtraction, image averaging, and temporal recursive filtering are performed on the GPU. RESULTS The new version of CAPIDS with all the parallel programming updates was successfully used for the first time to control the MAF, acquire the images, process the images and display the images during an actual clinical intervention. The images were acquired under fluoroscopy, digital subtraction angiography, and roadmap modes. CONCLUSION Distributing concurrent tasks to different cores of a multicore CPU results in an efficient utilization of resources, efficient power management and increases operation speed. Use of GPUs for image processing further enhances the speed of operation. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

SU-E-I-40: New Method for Measurement of Task-Specific, High-Resolution Detector System Performance

PURPOSE Although generalized linear system analytic metrics such as GMTF and GDQE can evaluate performance of the whole imaging system including detector, scatter and focal-spot, a simplified task-specific measured metric may help to better compare detector systems. METHODS Low quantum-noise images of a neuro-vascular stent with a modified ANSI head phantom were obtained from the average of many exposures taken with the high-resolution Micro-Angiographic Fluoroscope (MAF) and with a Flat Panel Detector (FPD). The square of the Fourier Transform of each averaged image, equivalent to the measured product of the system GMTF and the object function in spatial-frequency space, was then divided by the normalized noise power spectra (NNPS) for each respective system to obtain a task-specific generalized signal-to-noise ratio. A generalized measured relative object detectability (GM-ROD) was obtained by taking the ratio of the integral of the resulting expressions for each detector system to give an overall metric that enables a realistic systems comparison for the given detection task. RESULTS The GM-ROD provides comparison of relative performance of detector systems from actual measurements of the object function as imaged by those detector systems. This metric includes noise correlations and spatial frequencies relevant to the specific object. Additionally, the integration bounds for the GM-ROD can be selected to emphasis the higher frequency band of each detector if high-resolution image details are to be evaluated. Examples of this new metric are discussed with a comparison of the MAF to the FPD for neuro-vascular interventional imaging. CONCLUSION The GM-ROD is a new direct-measured task-specific metric that can provide clinically relevant comparison of the relative performance of imaging systems. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

TU‐A‐116‐07: Comparison and Evaluation of Commercially Available CMOS X‐Ray Detectors for Neurological Endovascular Image Guided Interventions (neuro‐EIGI' s)

PURPOSE To evaluate three commercially available CMOS x-ray detector systems as potential dual fluoroscopic and angiographic, high-resolution, ROI detectors for neuro-endovascular image-guided interventions (neuro-EIGIs) and to compare them to other experimentally evaluated or simulated neuro-EIGI detectors. METHODS Each CMOS detector was exposed to a standard RQA5 x-ray spectrum obtained by adding 21 mm of aluminum to a 70 kVp x-ray beam. Flat-field images were acquired by each detector and exposure per frame was determined using an ion chamber. From these images and exposures, sensitivity in digital numbers (DN/μR) and instrumentation noise-equivalent exposure (INEE) was found for each detector. These values were used to compare the three commercial detectors to other neuro-EIGI detectors previously built or simulated. RESULTS Detector A has a 12-bit ADC, a pixel size of 100 μm, and a full well capacity (FWC) of 2.2 million electrons (Me-). The sensitivity was found to be 5.8 DN/μR and the INEE was found to be 7.58 μR. Detector B has a 14-bit ADC, a pixel size of 75 μm, and a FWC of 0.36 Me-for the high sensitivity mode and 1.4 Me-for the high saturation mode. The sensitivity was found to be 28.9 DN/μR and the INEE was found to be 2.04 μR in the high sensitivity mode. Detector C has a 14-bit ADC, a pixel size of 100 μm and a FWC of 1.5 Me-. The sensitivity was found to be 15.1 DN/μR and the INEE was found to be 3.04 μR. The previous neuro-EIGI detectors had similar sensitivities of 10s-100s DN/μR, but much lower INEEs of <0.2 μR. CONCLUSION While the commercial CMOS x-ray detectors are improving, it remains a desirable goal to further reduce the commercial detector pixel size and instrumentation noise to approach the values seen with the previously built and simulated neuro-EIGI detectors. Supported by NIH Grant 2R01EB002873 and an equipment grant from Toshiba Corporation.

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 kVs 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) CCSs 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 GDCs was simulated using an anthropomorphic head phantom which includes an aneurysm. GDCs 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.

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 kVs 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.