The importance of three dimensional coronary artery reconstruction accuracy when computing virtual fractional flow reserve from invasive angiography

Three dimensional (3D) coronary anatomy, reconstructed from coronary angiography (CA), is now being used as the basis to compute ‘virtual’ fractional flow reserve (vFFR), and thereby guide treatment decisions in patients with coronary artery disease (CAD). Reconstruction accuracy is therefore important. Yet the methods required remain poorly validated. Furthermore, the magnitude of vFFR error arising from reconstruction is unkown. We aimed to validate a method for 3D CA reconstruction and determine the effect this had upon the accuracy of vFFR. Clinically realistic coronary phantom models were created comprosing seven standard stenoses in aluminium and 15 patient-based 3D-printed, imaged with CA, three times, according to standard clinical protocols, yielding 66 datasets. Each was reconstructed using epipolar line projection and intersection. All reconstructions were compared against the real phantom models in terms of minimal lumen diameter, centreline and surface similarity. 3D-printed reconstructions (n = 45) and the reference files from which they were printed underwent vFFR computation, and the results were compared. The average error in reconstructing minimum lumen diameter (MLD) was 0.05 (± 0.03 mm) which was < 1% (95% CI 0.13–1.61%) compared with caliper measurement. Overall surface similarity was excellent (Hausdorff distance 0.65 mm). Errors in 3D CA reconstruction accounted for an error in vFFR of ± 0.06 (Bland Altman 95% limits of agreement). Errors arising from the epipolar line projection method used to reconstruct 3D coronary anatomy from CA are small but contribute to clinically relevant errors when used to compute vFFR.

Automatic target matching

Many photogrametric processes require a large number of points to be collected from numerous digital images. It is imperative that these points be collected accurately, so that precise real-world coordinates may be assigned to points captured in the image. To this end, many techniques have been developed to locate, track and identify image targets. This thesis outlines many of these techniques and presents a target matching solution that has been developed in C++, for the subpixel target location program INDMET . The target matching solution is composed of three elements: an epipolar line program, a cross correlation program and a template least squares matching program. The epipolar line program is used to limit the search area in the right image of a given stereo pair, to the vicinity of a single line. The cross correlation program searches this line to locate possible targets and the template least squares matching program is used to determine the target centre of a black and white image target, once it has been located. It was found that these three programs, working together, had between a 20 and 70 percent chance of locating the correct target, depending on the similarity of elliptical targets in each image. Once found, the program could calculate the target centre to an accuracy of approximately 1/10th of a pixel.

Automatic target matching

Many photogrametric processes require a large number of points to be collected from numerous digital images. It is imperative that these points be collected accurately, so that precise real-world coordinates may be assigned to points captured in the image. To this end, many techniques have been developed to locate, track and identify image targets. This thesis outlines many of these techniques and presents a target matching solution that has been developed in C++, for the subpixel target location program INDMET . The target matching solution is composed of three elements: an epipolar line program, a cross correlation program and a template least squares matching program. The epipolar line program is used to limit the search area in the right image of a given stereo pair, to the vicinity of a single line. The cross correlation program searches this line to locate possible targets and the template least squares matching program is used to determine the target centre of a black and white image target, once it has been located. It was found that these three programs, working together, had between a 20 and 70 percent chance of locating the correct target, depending on the similarity of elliptical targets in each image. Once found, the program could calculate the target centre to an accuracy of approximately 1/10th of a pixel.

The Accuracy of Virtual Fractional Flow Reserve From Invasive Angiography: Importance of the Method of Reconstructing Three-dimensional Coronary Artery Anatomy

Background Three dimensional (3D) coronary anatomy, reconstructed from coronary angiography (CA), is now being used as the basis to compute ‘virtual’ fractional flow reserve (vFFR), and thereby guide treatment decisions in patients with coronary artery disease (CAD). Reconstruction accuracy is therefore important. Yet these methods remain poorly validated. Furthermore, the magnitude of vFFR error arising from reconstruction is unkown. We aimed to validate a new method for 3D CA reconstruction and determine the effect this had upon the accuracy of vFFR.Methods Clinically realistic coronary phantom models were created (seven standard stenoses in aluminium and 15 patient-based 3D-printed) and imaged with CA, three times, according to clinical protocols, yielding 66 datasets. Each was reconstructed using epipolar line projection and intersection. All reconstructions were compared against the phantom models in terms of minimal lumen diameter, centreline and surface similarity. 3D-printed reconstructions (n=45) and the reference files from which they were printed underwent vFFR computation, and the results were compared. Results The average error in reconstructing minimum lumen diameter (MLD) was 0.05 (±0.03 mm) which was <1% (95%CI 0.13-1.61%) compared with caliper measurement. Overall surface similarity was excellent (Hausdorff distance 0.65 mm). Errors in 3D CA reconstruction accounted for an error in vFFR of ±0.06 (95% limits of agreement).Conclusions Errors arising from the epipolar line projection method used to reconstruct 3D coronary anatomy from CA are small but result in clinically relevant errors in vFFR simulation, amounting to approximately 40% of the total error associated with vFFR.