Coronary Intervention Planning Using Hybrid 3D Reconstruction

Wink, Onno; Kemkers, Richard; Chen, S.-Y. James; Carroll, John D.

doi:10.1007/3-540-45786-0_75

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…Possible improvements for overcoming these drawbacks could be the extension of the method with prior knowledge, e.g. by favoring viewpoints that are empirically known to produce good results (see for example [5,15]).…”

Section: Outlook and Discussionmentioning

confidence: 99%

“…Viewpoint planning for coronary angiography was discussed in literature to obtain optimal viewpoints [7,12] or create view-maps which can be used as a heuris-tic look-up-table to identify angulations that are probably best suitable for a particular vessel segment [5,15]. Fallavollita et al presented the highly related concept of 'desired view' in angiographic interventions [4].…”

Section: Introductionmentioning

confidence: 99%

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Viewpoint planning for quantitative coronary angiography

et al. 2018

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We introduce an algorithm for optimal viewpoint planning from a single angiographic X-ray image. The quality of the second viewpoint-i.e., vessel foreshortening and true rotation around vessel-depends on the first viewpoint selected by the physician; however, our computed viewpoint is guaranteed to reduce the initial foreshortening. Our novel approach uses fluoroscopy images only and, thus, seamlessly integrates with the current clinical workflow for coronary assessment. In addition, it can be implemented in the QCA workflow without increasing user interaction, making vessel-shape reconstruction more stable by standardizing viewpoints.

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Section: Outlook and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Viewpoint planning for quantitative coronary angiography

et al. 2018

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“…The projection overlap between two surface representations, M 1 and M 2 , can be very quickly calculated using modern graphics hardware and the OpenGL graphics language [10,11]. The calculation is based on the use of stencil buffers.…”

Section: Overlap Calculationmentioning

confidence: 99%

Automated determination of optimal angiographic viewing angles for coronary artery bifurcations from CTA data

Kitslaar

Marquering

Jukema

et al. 2008

Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling

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For optimal diagnosis and treatment of lesions at coronary artery bifurcations using x-ray angiography, it is of utmost importance to determine proper angiographic viewing angles. Due to the increasing use of CTA as a first line diagnostic tool, 3D CTA data is more frequently available before x-ray angiographic procedures take place. Motivated by this, we propose to use available CTA data for the determination of patient specific optimal x-ray viewing angles. A semi-automatic iterative region growing scheme is developed for the segmentation of the coronary arterial tree. From the segmented arterial tree, a complete hierarchical surface and centerline representation, including bifurcation points, is automatically obtained. The optimal viewing angle for a selected bifurcation is determined as the view rendering the least amount of foreshortening and vessel overlap. For 83 bifurcation areas, viewing angles were automatically determined. The sensitivity of the method to patient positioning in the x-ray system was also studied. Next, the automatically determined angels were both quantitatively and qualitatively compared with angles determined by two experts. The method was found not to be sensitive to the positioning of the patient in the angiographic x-ray system. In 95% of the cases our method produced a clinically usable view (mean score of 8.4 out of 10) as compared to 98% for the experts (mean score of 8.7). Our method produced angiographic views with significantly less foreshortening (mean difference of 10 percentage points) than the angiographic views set by the experts.

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“…As coronary angiographers, we are used to looking at two‐dimensional displays and interpreting images as three‐dimensional structures, but we are often left wondering if our interpretation was right. In my opinion, our chief limitations, in order of frequency, are 1 difficulty laying out the views we need to assess, when a suspect area is hiding behind another vessel in every view tried, 2 limited cranial and caudal angles available for imaging (a problem that has not improved much with recent iterations of angiographic cameras and gantries), which creates obligatory foreshortening of some segments, 3 physics limitations with some patients, particularly the morbidly obese, which cause image resolution to fall off sharply, and 4 inattentiveness to a suspect area that gets missed, the embarrassing but not uncommon malady of the overly busy practitioner. When these pitfalls can be avoided, we do pretty well at integrating the two‐dimensional image sets, recreating three‐dimensional pictures in our brains and sorting out whether significant disease is or is not present.…”

mentioning

confidence: 99%

Twisting Two into Three: What Problem Does It Solve?

Garratt¹

2009

J Interven Cardiology

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Three dimensions should be better than two for interpreting images. As coronary angiographers, we are used to looking at two-dimensional displays and interpreting images as three-dimensional structures, but we are often left wondering if our interpretation was right. In my opinion, our chief limitations, in order of frequency, are 1 difficulty laying out the views we need to assess, when a suspect area is hiding behind another vessel in every view tried, 2 limited cranial and caudal angles available for imaging (a problem that has not improved much with recent iterations of angiographic cameras and gantries), which creates obligatory foreshortening of some segments, 3 physics limitations with some patients, particularly the morbidly obese, which cause image resolution to fall off sharply, and 4 inattentiveness to a suspect area that gets missed, the embarrassing but not uncommon malady of the overly busy practitioner. When these pitfalls can be avoided, we do pretty well at integrating the two-dimensional image sets, recreating three-dimensional pictures in our brains and sorting out whether significant disease is or is not present. Our high procedural success rates and low complication rates speak to the consistency and effectiveness of our current approach.Still, we would like to be better at what we do, and we are sensitive to the limitations of angiography. IVUS has taught us unequivocally that we miss important lesions from time to time. Expect for item number 4, the list above consists of limitations imposed by the Address for reprints: Kirk Garratt, Fax: XXX; e-mail: kgarratt@ lenoxhill.net two-dimensional x-ray imaging systems we use. There is a sense that rendering angiographic images in three dimensions will help us avoid some of the pitfalls of a two-dimensional experience.For the most part, we have tried to enhance the three-dimensionality of our angiographic viewing experiences through trickery. Before leaving Mayo Clinic and moving east a few years ago, I was skilled at use of the patient cradle, a now nearly defunct tool for rotating a patient during angiography. With the cradle system, a patient could be positioned with more LAO or RAO angulation than could be achieved with the gantry alone, especially when the camera was also placed in a steep cranial or caudal position. In addition, the patient could be rolled much faster than most cameras could be rotated; so, quick adjustments on the fly were easy. However, patients hated the sensation of being tipped up on their sides and rolled around; and so, cradles have largely disappeared. Still, I found adding rotation to the image greatly helps the sense of three dimensions of the coronary tree.Some imaging companies have sought to improve the three dimensionality of angiograms by enhancing gantry system performance and, in addition, integrating imaging data to create more of a three-dimensional picture. This is possible largely because labs are going digital, and digital image processing has matured. For example, the Philips Integris line can employ a...

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Coronary Intervention Planning Using Hybrid 3D Reconstruction

Cited by 3 publications

References 8 publications

Viewpoint planning for quantitative coronary angiography

Viewpoint planning for quantitative coronary angiography

Automated determination of optimal angiographic viewing angles for coronary artery bifurcations from CTA data

Twisting Two into Three: What Problem Does It Solve?

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