University of Groningen
Novel diagnostic and imaging techniques in endovascular iliac artery procedures
De Boer, Sanne W.; Heinen, Stefan G. H.; Goudeketting, Seline R.; De Haan, Michiel W.;
Mees, Barend M.; Van Den Heuvel, Daniel A. F.; De Vries, Jean-Paul P. M.
Published in:
Expert Review of Cardiovascular Therapy DOI:
10.1080/14779072.2020.1780916
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date: 2020
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
De Boer, S. W., Heinen, S. G. H., Goudeketting, S. R., De Haan, M. W., Mees, B. M., Van Den Heuvel, D. A. F., & De Vries, J-P. P. M. (2020). Novel diagnostic and imaging techniques in endovascular iliac artery procedures. Expert Review of Cardiovascular Therapy, 18(7), 395-404.
https://doi.org/10.1080/14779072.2020.1780916
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
Full Terms & Conditions of access and use can be found at
https://www.tandfonline.com/action/journalInformation?journalCode=ierk20
Expert Review of Cardiovascular Therapy
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/ierk20
Novel diagnostic and imaging techniques in
endovascular iliac artery procedures
Sanne W. De Boer , Stefan G.H. Heinen , Seline R. Goudeketting , Michiel W.
De Haan , Barend M. Mees , Daniel A. F. Van Den Heuvel & Jean-Paul P. M. De
Vries
To cite this article: Sanne W. De Boer , Stefan G.H. Heinen , Seline R. Goudeketting , Michiel W. De Haan , Barend M. Mees , Daniel A. F. Van Den Heuvel & Jean-Paul P. M. De Vries (2020) Novel diagnostic and imaging techniques in endovascular iliac artery procedures, Expert Review of Cardiovascular Therapy, 18:7, 395-404, DOI: 10.1080/14779072.2020.1780916
To link to this article: https://doi.org/10.1080/14779072.2020.1780916
© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Published online: 19 Jul 2020.
Submit your article to this journal
Article views: 216
View related articles
REVIEW
Novel diagnostic and imaging techniques in endovascular iliac artery procedures
Sanne W. De Boer a,b, Stefan G.H. Heinenc, Seline R. Goudekettingd, Michiel W. De Haana,b, Barend M. Meesb,e, Daniel A. F. Van Den Heuvelc and Jean-Paul P. M. De Vriesf
aDepartment of Radiology, Maastricht University Medical Center+, Maastricht, The Netherlands; bCARIM School for Cardiovascular Diseases,
Maastricht University, Maastricht, The Netherlands; cDepartment of Radiology, St. Antonius Hospital, Nieuwegein, The Netherlands; dDepartment of
Vascular Surgery, St. Antonius Hospital, Nieuwegein, The Netherlands; eDepartment of Vascular Surgery, Maastricht University Medical Center+,
Maastricht, The Netherlands; fDepartment of Surgery, Division of Vascular Surgery, University Medical Center Groningen, Groningen, The
Netherlands
ABSTRACT
Introduction: Endovascular revascularization has become the preferred treatment for most patients
with iliac artery obstructions, with a high rate of clinical and technical success.
Areas covered: This review will describe novel developments in the diagnosis and treatment of iliac
artery obstructions including the augmentation of preprocedural imaging with advanced flow models, image fusion techniques, and state-of-the-art device-tracking capabilities.
Expert opinion: The combination of these developments will change the endovascular field within the
next 5 years, allowing targeted iliac treatment without the need for radiographic imaging or iodinated contrast media. ARTICLE HISTORY Received 19 February 2020 Accepted 8 June 2020 KEYWORDS Angiography; contrast media; iliac artery disease; image fusion; pressure measurement; radiation dose; stenosis; tracking
1. Introduction
In up to one-third of patients with peripheral arterial occlusive disease (PAOD), the iliac arteries are involved [1]. Since the first angiogram [2], technological improve-ments in endovascular procedures have been substantial. Endovascular revascularization has now become the pre-ferred treatment for most patients with iliac artery obstruc-tions [3] suffering severe claudication or chronic limb- threatening ischemia.
Optimal treatment planning using computed tomography angiography (CTA), magnetic resonance angiography (MRA), or a combination of the two, is of paramount importance. Despite innovations in imaging and therapeutic options, some hurdles still have to be taken to optimize treatment of iliac artery disease. In the majority of patients a hemodynamic significant stenosis or occlusion can be seen on diagnostic imaging, but in the case of equivocal iliac artery stenoses or multilevel disease, the diagnostic accuracy of current imaging modalities is not always sufficient to translate lesion diameter reduction (or stenosis) into hemodynamic parameters such as the translesional pressure gradient [4,5].
Treatment planning solely based on standard imaging could lead to both under- and overtreatment of equivocal stenoses. Overtreatment of hemodynamically nonsignificant stenosis can potentially lead to higher costs and unnecessary complications, whereas treatment of these lesions is unlikely to improve clinical symptoms [6]. In these circumstances, enhancement of standard imaging with functional assessment by calculating the pressure gradient across an equivocal iliac
artery stenosis and predictive modeling [7–11] could play a major role in a targeted treatment strategy for the individual patient.
In addition to this, radiation exposure remains an issue requiring attention due to the possible negative effects on patients and endovascular specialists as well as the effects of iodinated contrast media (CM) use on patients. Imaging pro-tocols to reduce radiation and the amount of iodinated CM have already been globally implemented, but further improve-ments are mandatory [12–18].
Image fusion guidance has been introduced to reduce radiation exposure and the amount of iodinated CM [19]. With image fusion guidance, 2 single-shot orthogonal exposures or periprocedurally acquired three-dimensional (3D) cone-beam computed tomography (CBCT) images are fused with preprocedural cross-sectional CTA or MRA ima-ging. Techniques using image-guided fusion have already proven to reduce the use of iodinated CM in endovascular aneurysm repair (EVAR) [19–22], but not in iliac procedures.
Traditionally, 3D fusion is used together with fluoroscopy, but more recently, other imaging and visualization techniques, such as fiber optic technology and electromagnetic tracking [23–26], are finding their way to the angiography suites and hybrid endovascular rooms. This review discusses the current drawbacks of the diagnostic work-up in iliac artery disease and the potential benefits of targeted iliac artery lesion selection with the aid of more advanced functional imaging. Novel techniques to decrease radiation exposure and the amount of CM are also discussed.
CONTACT Sanne W. De Boer s.de.boer@mumc.nl Department of Radiology, Maastricht University Medical Center, The Netherlands EXPERT REVIEW OF CARDIOVASCULAR THERAPY
2020, VOL. 18, NO. 7, 395–404
https://doi.org/10.1080/14779072.2020.1780916
© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
2. Contemporary diagnostics of equivocal iliac artery stenoses
When clinical symptoms justify further evaluation nonin-vasive imaging methods to screen patients with PAOD are DUS, CTA, and MRA [27–32]. These techniques provide the physician with detailed anatomic information of the vas-cular tree and the extent and location of the lesions. A major limitation of CTA and MRA is that these techni-ques only provide an anatomic assessment but offer no hemodynamic information [33]. The hemodynamic signifi-cance of a single stenosis or serial stenoses depends on a combination of unique physiological and anatomical characteristics, such as flow (pattern), stenosis length, wall stiffness and collateral vessels, that are different for each patient. DUS can provide hemodynamic information on iliac stenoses by using the peak systolic velocity (PSV) or the PSV ratio (PSVR), but these measurements can only be performed during rest and do not represent the phy-siological state during maximum hyperemia (exercise) [5]. Furthermore, DUS is operator dependent, can be ham-pered by gaseous interposition of bowels and it is more difficult to determine optimal C-arm settings for treatment planning.
A widely accepted geometric cutoff value to define a hemodynamically significant stenosis is a 50% lumen dia-meter reduction. The geometric cutoff value originates from earlier in-vitro and in-vivo studies that have shown that a ‘critical arterial stenosis’ in iliac arteries occurs at 75–80% lumen area reduction or 50% lumen diameter reduction [34–
36]. These studies have also shown that beyond these points there is a very rapid decrease in flow and rise in pressure gradient.
From a physiological perspective, a stenosis with a mean arterial pressure (MAP) gradient ≥10 mm Hg under hyperemic conditions is considered hemodynamically significant [37,38]. Only a moderate correlation between 50% lumen diameter reduction and intra-arterial pressure gradients exists [5,39], however, due to the great variance in flow decrease and pressure gradients caused by an equivocal stenosis, only a small change in lumen diameter may lead to a completely different hemodynamic outcome [34–36,40–42]. Determining the exact pressure gradient of equivocal stenoses before a patient is planned for an invasive intervention is therefore worthwhile. Categorizing equivocal stenoses as hemodynami-cally significant and nonsignificant lesions allows for targeted treatment.
Several studies investigating the performance of a geometry-based diagnostics of a hemodynamically signifi-cant stenosis have shown limited diagnostic accuracy. Digital subtraction angiography (eyeballing the stenosis), quantitative vascular analysis, and PSVRs on DUS have a diagnostic accu-racy of 71% to 83% [5,39,43] compared with intra-arterial pressure measurements. Therefore, geometric measures alone remain insufficient to determine whether an equivocal stenosis is hemodynamically significant [4,5,44,45].
Intra-arterial translesional pressure measurements (under hyperemic conditions) remain the gold standard for identify-ing stenoses requiridentify-ing treatment [46], but these are invasive
and require more radiation exposure. Major complication rates of 4.3% to 5.2% in endovascular iliac procedures have been reported [47]. Therefore, optimization or enhancement of judgment on noninvasive imaging methods is required to minimize unnecessary invasive imaging procedures and over-treatment of lesions that are not hemodynamically significant.
3. Advanced diagnosis of suspected iliac artery stenotic disease
Several computational fluid models to calculate translesional pressure gradients on pre-procedural imaging have been pro-posed for equivocal stenoses in coronary arteries [8–10,48–51]. Computational fluid models are based on principles of fluid mechanics. Usually 3D models are utilized, but these models are time consuming. 2D models only require several minutes to process, but a 2D model assumes that the vessel and stenoses are axisymmetric. However, an in vitro study has shown that an eccentric stenosis leads to a similar pressure gradient as a circular stenosis of the same area and does not influence the outcome of a 2D model [52].
Recently, a patient-specific two-dimensional (2D) computa-tional fluid model for equivocal iliac artery stenoses was assessed [7]. This model was based on 3D rotational angio-graphic image information and validated with intra-arterial pressure measurements under hyperemic conditions (DETECT- PAD trial; http://www.trialregister.nl; identifier: NTR5085, regis-tered on 9 March 2015). This model enables a prediction of whether the mean arterial pressure gradient across an equi-vocal stenosis is hemodynamically significant (≥10 mm Hg) or not significant (<10 mm Hg), with sensitivity of 95%, specificity of 60%, and overall predictive value of 88% [7].
A major limitation is that 2D and 3D models cannot provide instant results because they are time consuming, and addi-tional computaaddi-tional fluid dynamics software packages are required to perform the calculations. However, geometric models have recently been developed to estimate the intra- arterial pressure gradient in common and external iliac artery stenoses under hyperemic conditions in seconds and without the need for an additional computational fluid dynamics soft-ware package [11,53]. These models were validated with geo-metric input parameters derived from angiographic images from the DETECT PAD trial. The results of these geometry- based models were comparable to those of the more time- consuming 2D model [11,53]. However, a drawback of these models is that the patient-specific geometric properties are still obtained during catheterization at the angiography suite. The next step is therefore to validate the geometric model for preprocedural MRA or CTA. Another potential drawback of these models is that they do not include collateral circulation which is a major source of error in pressure gradient estima-tion. However, the models are built to estimate pressure gra-dients in equivocal stenosis. Collateral formation is almost exclusively seen in chronic total occlusions (CTO) and in very severe stenoses (>75%) and there will be no doubt on pre-procedural imaging or angiography whether these lesions are hemodynamically significant making intra-arterial pressure measurements unnecessary. In general, equivocal stenoses have not yet developed collateral circulation.
Another approach to determine hemodynamic significance without the use of intra-arterial pressure measurements is to use machine learning (ML) [54,55], of which the first reports have been published in the cardiac literature. Machine learn-ing is the study of computer algorithms that allows computer programs to automatically improve through experience [56]. To predict whether the fractional flow reserve (FFR) was ≤0.80, Cho and coworkers [55] used a data set of 1501 patients with coronary angiograms and Lee and coworkers [54] used a data set of 1328 patients with intravascular ultrasound images to train their respective models. Both studies achieved an overall accuracy of 82%. A drawback of these models is that both still require an invasive procedure (angiography). To develop ML models for predicting the hemodynamic significance of an iliac artery stenosis, large amounts of clinical data (preproce-dural imaging and intra-arterial pressure measurements) need to be available. Obtaining sufficient data will be a major chal-lenge, because performing intra-arterial measurements under hyperemic conditions is not a daily routine for iliac artery disease.
4. Periprocedural visualization and fusion techniques to reduce radiation exposure and iodinated CM
A preprocedural CTA or MRA can help to identify challenging anatomy and determine optimal angulation settings of the C-arm during the procedure. Repeated image acquisition as the C-arm is positioned through trial and error, commonly referred to as ‘fluoro-hunting’, must be avoided because it takes time and increases radiation exposure to the patient and the endovascular team [57]. This is one of the major drawbacks of DUS.
Angulation of the C-arm, which results in more mass that needs to be traversed and more scattered radiation, is espe-cially correlated with a significantly higher radiation dose for the patient and the endovascular team [58,59]. Determining the optimal viewing angles of the aortic and iliac bifurcations on preprocedural imaging can avoid unnecessary radiation exposure.
Fusion imaging was introduced in 2011 [19]. The aim of fusion-image guidance is to facilitate navigation with cathe-ters and guidewires by continuously projecting the vascular tree acquired from preoperative imaging (CTA or MRA) onto live fluoroscopic images, thus reducing the need for iodinated CM injection (Figure 1) and periprocedural acquired high resolution imaging, thus reducing radiation dose.
Image fusion can be performed using a 2D/3D or a 3D/3D registration. A 2D/3D fusion is based on 2 single-shot ortho-gonal exposures, whereas the 3D/3D fusion uses a noncontrast-enhanced CBCT scan. During the CBCT scan, fluoroscopic images are continuously acquired over an angle of at least 180° and then reconstructed into a 3D data set. 3D/ 3D registration may lead to better accuracy compared with 2D/3D registration [60], but at the expense of a higher radia-tion dose [61,62]. To correctly match the preprocedurally and periprocedurally acquired images, landmarks have to be defined. When 2D/3D or 3D/3D registration is performed, these landmarks consist of bony structures such as vertebrae, femoral heads, or the iliac crest, and in case of a preoperative CTA, aortic wall calcifications. Acquisition of these images and registration with preprocedural imaging is usually performed in less than 10 minutes.
A drawback of fusion techniques is that the registration is rigid, whereas the position of the patient often changes dur-ing the procedure compared with positiondur-ing durdur-ing the
Figure 1. Example of an iliac image fusion with overlay of a vascular tree.
preprocedural imaging. Also, the introduction of delivery devices and stiff guidewires can challenge the use of image fusion. Deformation and displacement of the iliac arteries will occur and cannot be corrected with a rigid fusion technique.
To overcome these drawbacks of rigid fusion, several solu-tions regarding distortion correction, automatic segmentation and registration have been proposed [63–67]. To our knowl-edge the only commercially available system is a cloud-based artificial intelligence (AI)-assisted 3D fusion technique that has been developed by CYDAR Medical (Barrington, United Kingdom). With this AI-assisted nonrigid registration, the ver-tebral anatomy on fluoroscopy and the preprocedural imaging are compared. An adjusted 3D vascular tree is then overlaid on the fluoroscopy screen, which will continuously update and verify itself [65]. This does not only allow for a translation of a rigid mask, but a deformation of the mask as well. It has been shown that this system could also correct for displace-ments introduced by stiff devices [66]. The efficacy and added value of the novel technique has only been evaluated in a retrospective study [67].
Another periprocedural imaging technique is intravascular ultra-sound (IVUS). IVUS can be very useful for detecting true lumen size, evaluating residual stenosis after plain old balloon angioplasty and detecting technical failure (eg incomplete stent apposition, throm-bosis, residual dissection) [68]. Although IVUS can provide a high- resolution cross-sectional image of the lesion [69], it remains a geometric measure and cannot provide hemodynamic informa-tion. The high costs of IVUS, the extra periprocedural actions that need to be taken and the increasing quality of MRA and CTA is probably why IVUS for iliac procedures has not been incorporated into the guidelines or clinical practice.
4.1. Image fusion in obstructive iliac disease; 3DMR-Iliac-Roadmapping study
The 3DMR-Iliac-Roadmapping study (https://www.trialregister. nl/; identifier NTR5008; registered on 16 December 2014) was
the first prospective, multicenter, randomized trial designed to evaluate whether 3D image fusion during endovascular iliac artery interventions could reduce the amount of administered iodinated CM. The study protocol, which was approved by the Maastricht University Medical Center+ and Maastricht University ethics committee (METC azM/UM), was previously published [70], and all study procedures were conducted in accordance with good clinical practices and applicable laws.
The 3DMR-Iliac-Roadmapping study included 41 patients; of these, 39 were randomized, and 2 were not randomized due to logistic issues. Patients were randomized into 2 groups: treatment with 3D/3D image fusion (n = 19) or without image fusion (n = 20). Demographics, comorbidities, and cardiovas-cular risk factors were similar between the 2 groups (Table 1). Impaired renal function, defined as estimated glomerular fil-tration rate (eGFR) ≤60 mL/min/1.73 m2, and bodyweight (≤90 or >90 kg) were used as stratification factors. Each group had 3 patients with an eGFR ≤60 mL/min/1.73 m2 and 3 patients with a body weight >90 kg. After inclusion of 40 patients, as defined in the study protocol, an interim analysis was per-formed by an independent safety committee.
Total median volume of CM used was 32 mL (range, 7–112 mL) in the group with fusion and 42 mL (range, 20–197 mL) in the group without fusion (P = 0.254). All end-points are listed in Table 2. Technical success, defined as the ability to successfully perform plain balloon angioplasty or stent placement with a residual stenosis <30%, was achieved in treated patients. 2 patients in the group without fusion were not treated; in 1 patient it was decided after DSA to replan the patient for a hybrid approach, in the other patient it was concluded the stenosis was non-significant. Similarly, fluoroscopy time, procedure time, and radiation dose did not differ significantly between the groups. Fusion accuracy regis-tration in the fusion group (n = 19) was scored in 6 patients as accurate (<2 mm difference), in 10 patients as mismatch (2–5 mm difference), in 2 patients as inaccurate (>5 mm dif-ference) and was missing for 1 patient.
Table 1. Baseline characteristics of the 3DMR-Iliac-Roadmapping study populationa,b,c.
group with fusion (n = 19) Group without fusion (n = 20) P
Age (years) 67.0 [50–88] 66.5 [50–86] 0.767 c Sex Male 13/19 15/20 0.731 b Rutherford categories Rutherford category 1 1/19 5/19 1/20 1.000 b Rutherford category 2 5/19 6/20 1.000 b Rutherford category 3 9/19 9/20 1.000 b Rutherford category 4 3/19 4/20 0.106 b Rutherford category 5 1/19 0/20 0.342 b Functional parameters ABI in rest 0.6 [0.4–0.9] 0.6 [0.3–0.9] 0.55 c
ABI after exercise 0.2 [0.1–0.8] 0.3 [0.1–0.8] 0.94 c
Pain-free walking distance meter 85 [10–300] 100 [30–2000] 0.44 c
Creatinine µmol/l 81 [59–247] 90 [45–120] 0.51 c
Risk factors
Diabetes Yes 5/19 3/20 0.45 b
Smoking, current or recent Yes 13/19 13/20 1.00 b
BMI Kg/m2 26.5 [18.6–34.7] 24.4 [18.3–34.9] 0.24 c
ABI, ankle brachial index; BMI, Body Mass Index.
aContinuous data are shown as median [range] b
Pierson’s Chi-square and Fisher’s Exact test where appropriate, unless otherwise indicated
The primary end point showed no significant decrease in the total volume of iodinated CM used in the fusion group at the mandatory interim analysis. The committee reported that even if statistical significance might be reached, the amount of iodinated CM reduction was unlikely to lead to a clinically relevant reduction in CM. Based on the estimate, the study was terminated prematurely.
4.2. Dilution of iodinated CM
The use of iodinated CM should always be prospectively mon-itored and evaluated in order to facilitate improvement and a potential reduction in volumes used. Current guidelines recommend the use of either low-osmolar contrast media (LOCM) or iso-osmolar contrast media (IOCM) for endovascular use since there is no difference in incidence of post contrast acute kidney injury, acute reactions or acute adverse events [15,71].
An alternative to reduce the total CM volume is to dilute the CM with saline. With the current standard of digital flat- panel detectors, dilution of CM should be considered and is possible without losing diagnostic information or image qual-ity. Unfortunately data to justify this claim is scarce. A randomized controlled trial showed non-inferiority for using CM with 140 mgI/mL instead of 300 mgI/mL for infra-inguinal angioplasty [72].
Furthermore, the use of a single-head injector can reduce the total CM volume when compared to manual injections, since they are more precise. With dual-head injectors it is possible to adjust CM dilution to patient and procedural char-acteristics (e.g. obese patient or a lateral view) by adjusting the dilution per injection.
4.3. Device visualization and tracking
Fluoroscopy has traditionally been used to visualize guide-wires, catheters, and other endovascular devices. With image fusion guidance, it is possible to decrease catheterization time, leading to a shorter fluoroscopy time and reduced radiation dose [73]. The next step would be to track catheters and guidewires without the need for fluoroscopy.
A not yet commercially available and new visualization tech-nique, called Fiber Optic RealShape (FORS), was recently intro-duced by Philips Medical Systems Nederland (Best, The Netherlands). By incorporating hair-thin optical fibers into
catheters and guidewires, the shape of these endovascular devices can be visualized using light pulse reflection (Figure 2). This provides a real-time 3D visualization of the shape of the device, which can be projected on a preprocedural or peripro-cedural acquired image. The image volume needs to be regis-tered to the patient using a conventional 2D/3D or 3D/3D X-ray registration, which is performed using dedicated software for the FORS technology [74]. When the image volume is aligned with the patient, the FORS enabled devices need to be regis-tered. This is done similarly to the image volume registration using a 2D/3D registration.
The possible major advantage of this novel technique is that it provides real-time 3D feedback on the position of the guidewire or catheter. The endovascular specialist will be able to navigate a guidewire or catheter without the use of fluoro-scopy in combination with 3D information, resulting in a reduction of radiation exposure and iodinated CM use. The 3D projection capabilities also exceed those of conventional 2D fluoroscopy in a complex and elongated anatomy, because the endovascular specialist can use different views of the tracked device simultaneously. Current drawbacks are that only 2 devices can be tracked at the same time, and only FORS enabled devices can be tracked using the proprietary hardware and software.
Preclinical and first-in-man feasibility results were pre-sented at Aortic Live 2018 and at the Leipzig Interventional Course (LINC) 2019 and 2020 and showed promising results regarding several navigation tasks [23–25]. Clinical trials are expected to start shortly.
Another new kid on the block uses electromagnetic fields to track catheters and is termed electromagnetic tracking. Tracking is performed by using a field generator that creates a magnetic field of known geometry and sensors that measure magnetic flux or magnetic fields. Because the geometry of the emitting coil and the current through the coil are known, the shape and properties of the reference field can be calculated using the law of Biot-Savart [26]. This allows for the calculation of the field strength at various points. By incorporating a magnetic sensor into a medical device, the exact location of the sensor can be calculated in relation to the reference field, and movement tracking is possible with 6 degrees of freedom (along the x, y, and z axis and rotation on each axis).
Registration of preprocedural images can be performed in various ways, including 2D/3D, 3D/3D, with the use of external fiducials, and more recently an original registration method
Table 2. Study end points of the 3DMR-iliac-roadmapping study populationa,b,c.
Group with fusion
(n = 19) Group without fusion (n = 20) P Primary endpoint
Volume iodinated contrast ml 32 [7–112] 42 [20–137] 0.25 c
Secondary endpoints
Technical success (<30% residual stenosis) Yes 19 18 0.49 b
Fluoroscopy time mm:ss 05:27 [01:29–32:25] 04:12 [01:11–45:48] 0.93 c
Procedure time minutes 46 [13–111] 37 [13–124] 0.93 c
Radiation dose (DAP) mGycm2 48,955 [1430–15,900] 23,986 [1717–95,782] 0.96 c
Air Kerma (AK) mGy 188 [71–754] 144 [25–3355] 0.83 c
DAP, dose area product; AK, air kerma
aContinuous data are shown as median [range] b
Pierson’s Chi-square and Fisher’s Exact test where appropriate, unless otherwise indicated
cOne-tailed Mann-Whitney U test
has been proposed using only catheters with incorporated electromagnetic sensors [75]. With this method, a catheter pull-back is performed in the iliac axis. The recorded path and the preprocedural images can be used for fusion registra-tion. The recorded mean registration error in a phantom setup was 1.3 mm (range, 0.88–1.89 mm) [75]. A potential drawback of electromagnetic tracking is that only the sensor, and not the whole catheter, can be tracked. Catheters can be projected onto the screen using its known dimensions in relation to the sensor, but bending or curves of the catheter are not tracked. Several preclinical animal and phantom studies have been published [75–79], but to our knowledge, no in human studies have been published so far for endovascular indications.
Endovascular specialists have familiarized themselves with the different properties of various guidewires and catheters, and their behavior in different situations regarding steerability and push. Companies introducing new, trackable devices will be challenged to not sacrifice the abilities endovascular specialists are used to work with. Open vessel navigation will most likely not be a problem, but it remains questionable how these new tools will behave in challenging situations like long CTOs.
5. Conclusion
Targeted treatment for the individual patient by using a combination of predictive modeling, image fusion, and device visualization or device tracking will play a major role in the next years of iliac endovascular procedures. It may allow endovascular specialists to reduce unneces-sary, invasive procedures. Owing to the already low CM volumes used in iliac procedures, image fusion alone has no relevant impact on the reduction of the use of iodinated CM in straightforward iliac procedures.
6. Expert opinion
An endovascular approach has become the preferred treat-ment for iliac artery disease, with good technical and long- term outcomes. The number of procedures for iliac artery stenotic disease is gradually increasing each year [80] and
the need to improve and develop new endovascular (imaging) techniques to minimize the risks for patients and endovascular specialists is important.
In the era of personalized medicine, the preprocedural workup for endovascular iliac procedures should incorporate a targeted and patient-specific treatment plan. Currently, opti-mal treatment planning in case of equivocal stenoses should include intra-arterial pressure measurements, but this techni-que is not commonly used [81]. The dominance in clinicians’ decisions by visual estimation, weakly correlated to intra- arterial pressure gradients, may lead to a higher rate of unne-cessary iliac artery interventions. By using predictive modeling, either computational flow modeling or machine learning, lesion selection can be performed on preprocedural imaging. However, the question of which and when a model is judged good enough to be implemented in daily practice remains.
Fryback and Thornbury describe a hierarchical model of efficacy for diagnostic imaging. The model outlines the opti-mal level of evidence necessary to prove the value of a diagnostic imaging test. It addresses factors related to tech-nical quality and diagnostic accuracy, diagnostic and thera-peutic impact, and patient and societal outcomes [82]. Applying this to the computational model as described in the DETECT-PAD trial, technical efficacy has been proven, but much more clinical data, ranging up to 200 to 300 patients, will have to be acquired from new studies.
Radiation exposure during endovascular procedures is an invisible threat, and attention to protection can be easily forgotten, especially in complex procedures. Body mass index and lesion complexity are associated with significantly higher radiation exposures during the procedure [83,84]. With an increase in procedure numbers, an increase in patient obesity and multimorbidity, and more complex lesions, the cumulative lifetime dose of the endovascular staff will increase. The ALARA (as low as reasonably achievable) princi-ple is important to maintain. For the first time, radiation has been shown to cause DNA damage in endovascular specialists [85]. However, in light of the growing evidence that the use of image fusion can reduce the radiation dose for both the
patient and endovascular team, the observation that image fusion has not been adapted in international scientific guide-lines or clinical workflows is remarkable but we expect that this will be amended in coming updates of various interna-tional guidelines.
Workflow issues often arise with the introduction of new technology. When radiation reduction technology is not directly in line with the expectations of the endovascular team, or using a new technology is cumbersome, adaptation will be less likely [86] and may even lead to neglect of the harmful effects to both the patient and staff. Rigorous and continuous training is required to safely and effectively intro-duce a new workflow or technology.
The 3DMR-Iliac-Roadmapping study is the first multicen-ter randomized controlled trial of image fusion compared with regular imaging in an endovascular iliac artery proce-dure. The results show that image fusion in endovascular iliac artery procedures is feasible and safe. With image fusion the main focus has been to fuse preprocedural CT images. The 3DMR-Iliac-Roadmapping study shows it is fea-sible to use preprocedural MRA for image fusion. No other iliac fusion studies have been published, and the CYDAR Iliac trial, focused on patient and staff safety regarding radiation dose using CYDAR AI, was expected to complete inclusion in January 2020 (https://clinicaltrials.gov/; identi-fier NCT03713450).
The 3DMR-Iliac-Roadmapping study showed a median dif-ference in the administered volume of iodinated CM of 10 mL, but how much CM reduction justifies a complete overhaul of clinical workflow? Contrast-induced nephropathy (CIN) is dose-related to the amount of iodinated CM in very high-risk patients [87], and multiple efforts have been done to deter-mine safe procedural doses [88–91]. Yoon and Hurr suggested the use of grams of iodine to the eGFR ratio and analyzed that a ratio of 1.42 g iodine/eGFR had a sensitivity and specificity of 81.3% and 80% for developing CIN [91]. The difference in grams of iodine in our study was only 3.0 g (based on median administered volume of CM and a concentration of 300 mg/ mL), and this is unlikely to have a relevant clinical effect, even in high-risk patients. This suggests that image fusion in straightforward iliac procedures has no relevant impact on the reduction of the use of iodinated CM.
We believe that the current developments regarding pre-dictive modeling and catheter visualization or tracking, in combination with image fusion, are very promising and will change the current endovascular field in the next 5 to 10 years. Endovascular specialists will only use augmented diagnostics tools, and eyeballing may become obsolete. Imaging systems will be able to determine a hemodynamic gradient instantaneously and include it in a report. Also, to a certain degree, it should be technically feasible to perform endovascular procedures without the need for CM or radia-tion like with the FORS technology. Failure rates for complex lesions like CTOs will become less. Often these lesions need to be transversed in the subintimal plane and reentering the true lumen can be challenging. By being able to track the wire position relative to the true lumen, determining an
optimal reentry angle will become easier. We do believe that fluoroscopy guided interventions will stay around for a long time to come, but the need for endovascular specia-lists to solely rely on fluoroscopy will become less and less. A big challenge however, will be the lack of reimburse-ment or insufficient reimbursereimburse-ment to compensate for the introduction of new devices and the early adaptation to new technology and workflows. Generally new technologies come at a premium price, while often initially lacking suffi-cient data that demonstrates better patient outcomes. Often medical doctors are dependent on medical device compa-nies for the (co-)development of new technologies like CYDAR or FORS. We would like to challenge medical device companies to provide more quality and efficacy data upon market introduction while maintaining an affordable price level. This data is needed to support a systematic evaluation process and informed decision-making by healthcare provi-ders. Only then can healthcare providers invest into new technologies in a financially sustainable way while having the biggest impact on patient outcome.
Funding
This paper was not funded.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
ORCID
Sanne W. De Boer http://orcid.org/0000-0002-5800-0025
References
Papers of special note have been highlighted as either of interest (•) or of considerable interest (••) to readers.
1. Zeller T. Current state of endovascular treatment of femoro-popliteal artery disease. Vasc Med. 2007;12:223–234. 2. Moniz E. L’encephalographie arterielle, son importance dans la
localisation des tumeurs cerebrales. Rev Neurol. 1927;2:72. 3. Aboyans V, Ricco J-B, Bartelink M-LE-L, et al. 2017 ESC guidelines on
the diagnosis and treatment of peripheral arterial diseases, in collaboration with the European Society for Vascular Surgery (ESVS): document covering atherosclerotic disease of extracranial carotid and vertebral, mesenteric, renal, upper and lower extremity arteriesEndorsed by: the European Stroke Organization (ESO)the task force for the diagnosis and treatment of peripheral arterial diseases of the European Society of Cardiology (ESC) and of the European Society for Vascular Surgery (ESVS). Eur Heart J.
2018;39:763–816.
4. Wikström J, Holmberg A, Johansson L, et al. Gadolinium-enhanced magnetic resonance angiography, digital subtraction angiography and duplex of the iliac arteries compared with intra-arterial pres-sure gradient meapres-surements. Eur J Vasc Endovasc Surg.
2000;19:516–523.
5. Legemate DA, Teeuwen C, Hoeneveld H, et al. Value of duplex scanning compared with angiography and pressure measurement in the assessment of aortoiliac arterial lesions. Br J Surg.
1991;78:1003–1008.
6. Bosch JL, Tetteroo E, Mali WP, et al. Iliac arterial occlusive disease: cost-effectiveness analysis of stent placement versus percutaneous transluminal angioplasty. Dutch iliac stent trial study group. Radiology. 1998;208:641–648.
7. Heinen SGH, van den Heuvel DAF, Huberts W, et al. In vivo valida-tion of patient-specific pressure gradient calculavalida-tions for iliac artery stenosis severity assessment [Internet]. J Am Heart Assoc. 2017;6. DOI:10.1161/jaha.117.007328.
8. Morris PD, Silva Soto DA, Feher JFA, et al. Fast virtual fractional flow reserve based upon steady-state computational fluid dynamics analysis: results from the VIRTU-fast study. JACC Basic Transl Sci.
2017;2:434–446.
9. Papafaklis MI, Muramatsu T, Ishibashi Y, et al. Fast virtual functional assessment of intermediate coronary lesions using routine angio-graphic data and blood flow simulation in humans: comparison with pressure wire - fractional flow reserve. EuroIntervention.
2014;10:574–583.
10. Nørgaard BL, Leipsic J, Gaur S, et al. Diagnostic performance of noninvasive fractional flow reserve derived from coronary com-puted tomography angiography in suspected coronary artery dis-ease: the NXT trial (Analysis of coronary blood flow using CT angiography: next steps). J Am Coll Cardiol. 2014;63:1145–1155. 11. Heinen SGH, van den Heuvel DAF, de Vries JPPM, et al. A
geometry-based model for non-invasive estimation of pressure gradients over iliac artery stenoses. J Biomech. 2019;92:67–75. 12. European Society of Radiology (ESR). White paper on radiation
protection by the European society of radiology. Insights Imaging. 2011;2:357–362.
13. American College of Radiology. Radiation protection protocols [Internet]. [cited 2019 Dec 17]. Available from: https://www.acr. org/Clinical-Resources/Radiology-Safety/Radiation-Safety
14. Committee on Drugs and Contrast Media. American College of Radiology (ACR) manual on contrast media, version 10.3 [Internet]. [cited 2019 Dec 17]. Available from: http://www.acr. org/quality-safety/resources/contrast-manual
15. European Society of Urogenital Radiology. ESUR guidelines on contrast media, version 10.0; 2018 Mar [Internet]. [cited 2019 Dec 17]. Available from: http://www.esur.org/esur-guidelines/
16. Solomon R, Dumouchel W. Contrast media and nephropathy: find-ings from systematic analysis and food and drug administration reports of adverse effects. Invest Radiol. 2006;41:651–660. 17. Brooks CE, Middleton A, Dhillon R, et al. Predictors of creatinine rise
post-endovascular abdominal aortic aneurysm repair [Internet]. ANZ J Surg. 2011;81:827–830.
18. Kawatani Y, Nakamura Y, Mochida Y, et al. Contrast medium induced nephropathy after endovascular stent graft placement: an examination of its prevalence and risk factors [Internet]. Radiol Res Pract. 2016;2016:1–5.
19. Dijkstra ML, Eagleton MJ, Greenberg RK, et al. Intraoperative C-arm cone-beam computed tomography in fenestrated/branched aortic endografting. J Vasc Surg. 2011;53:583–590.
20. Kobeiter H, Nahum J, Becquemin J-P. Zero-contrast thoracic endo-vascular aortic repair using image fusion. Circulation. 2011;124: e280–e282.
21. Sadek M, Berland TL, Maldonado TS, et al. Use of preoperative magnetic resonance angiography and the artis zeego fusion pro-gram to minimize contrast during endovascular repair of an iliac artery aneurysm [Internet]. Ann Vasc Surg. 2014;28:261.e1–e261.e5. 22. Sailer AM, de Haan MW, Peppelenbosch AG, et al. CTA with fluoro-scopy image fusion guidance in endovascular complex aortic aneurysm repair. Eur J Vasc Endovasc Surg. 2014;47:349–356.
23. Van Herwaarden JA Pre-clinical results of a 3D navigation innova-tion: fiber optic realShape (FORS) technology [Internet]. [cited 2018
Oct 29–30]. Available from: https://www.aortic-live.com/wp- content/uploads/2018/11/1740_v-Herwaarden-Aortic-Live-2018_ 201018_Approved-NEWLpic.pdf
24. van Herwaarden JA Innovation in 3D navigation: results from the FORS - fiber optic realShape first-in-human clinical study [Internet];
2019. Available from: https://linc2019.cncptdlx.com/media/ 20190122_LINC_FINAL_JvH_PRESENTED.pdf
25. van Herwaarden JA Modern imaging systems will revolutionize EVAR techniques [Internet]; 2020. Available from: https://linc2020. cncptdlx.com/media/van%20Herwaarden_LINC2020.pdf
26. Franz AM, Haidegger T, Birkfellner W, et al. Electromagnetic track-ing in medicine–a review of technology, validation, and applica-tions. IEEE Trans Med Imaging. 2014;33:1702–1725.
27. Jens S, Koelemay MJW, Reekers JA, et al. Diagnostic performance of computed tomography angiography and contrast-enhanced mag-netic resonance angiography in patients with critical limb ischae-mia and intermittent claudication: systematic review and meta-analysis. Eur Radiol. 2013;23:3104–3114.
28. Met R, Bipat S, Legemate DA, et al. Diagnostic performance of computed tomography angiography in peripheral arterial disease: a systematic review and meta-analysis. JAMA. 2009;301:415–424. 29. Visser K, Hunink MGM. Peripheral arterial disease: gadolinium-
enhanced MR angiography versus color-guided duplex US—a meta-analysis. Radiology. 2000;216:67–77.
30. Menke J, Larsen J. Meta-analysis: accuracy of contrast-enhanced magnetic resonance angiography for assessing steno-occlusions in peripheral arterial disease. Ann Intern Med. 2010;153:325–334. 31. Koelemay MJ, den Hartog D, Prins MH, et al. Diagnosis of arterial
disease of the lower extremities with duplex ultrasonography. Br J Surg. 1996;83:404–409.
32. Pollak AW, Norton PT, Kramer CM. Multimodality imaging of lower extremity peripheral arterial disease: current role and future directions. Circ Cardiovasc Imaging. 2012;5:797–807.
33. Zhang H, Prince MR. Improving interpretation of MRA and CTA in patients with suspected renal artery stenosis. Vascular Dis Manage.
2011;8:E34–E37.
34. May AG, de Weese JA, Rob CG. Hemodynamic effects of arterial stenosis. Surgery. 1963;53:513–524.
35. Berguer R, Hwang NH. Critical arterial stenosis: a theoretical and experimental solution. Ann Surg. 1974;180:39–50.
36. May AG, Van de Berg L, Deweese JA, et al. Critical arterial stenosis. Surgery. 1963;54:250–259.
37. Klein WM, van der Graaf Y, Seegers J, et al. Dutch iliac stent trial: long-term results in patients randomized for primary or selective stent placement. Radiology. 2006;238:734–744.
38. Tetteroo E, van der Graaf Y, Bosch JL, et al. Randomised compar-ison of primary stent placement versus primary angioplasty fol-lowed by selective stent placement in patients with iliac-artery occlusive disease. Lancet. 1998;351:1153–1159.
39. Breslau PJ, Jörning PJ, Greep JM. Assessment of aortoiliac disease using hemodynamic measures. Arch Surg. 1985;120:1050–1052. 40. Kinney TB, Rose SC. Intraarterial pressure measurements during
angiographic evaluation of peripheral vascular disease: techniques, interpretation, applications, and limitations. AJR Am J Roentgenol.
1996;166:277–284.
41. Moore WS, Malone JM. Effect of flow rate and vessel calibre on critical arterial stenosis. J Surg Res. 1979;26:1–9.
42. Udoff EJ, Barth KH, Harrington DP, et al. Hemodynamic significance of iliac artery stenosis: pressure measurements during angiography. Radiology. 1979;132:289–293.
43. Heinen SG, de Boer SW, van den Heuvel DA, et al. Hemodynamic significance assessment of equivocal iliac artery stenoses by com-paring duplex ultrasonography with intra-arterial pressure measurements. J Cardiovasc Surg. 2018;59:37–44.
44. Fischer JJ, Samady H, McPherson JA, et al. Comparison between visual assessment and quantitative angiography versus fractional flow reserve for native coronary narrowings of moderate severity. Am J Cardiol. 2002;90:210–215.
45. Tetteroo E, van Engelen AD, Spithoven JH, et al. Stent placement after iliac angioplasty: comparison of hemodynamic and angio-graphic criteria. Dutch iliac stent trial study group. Radiology.
1996;201:155–159.
46. Knuuti J, Wijns W, Saraste A, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. [Internet]. 2019. DOI:10.1093/eurheartj/ehz425.
47. Bosch JL, Hunink MG. Meta-analysis of the results of percutaneous transluminal angioplasty and stent placement for aortoiliac occlu-sive disease. Radiology. 1997;204:87–96.
48. Westra J, Tu S, Winther S, et al. Evaluation of coronary artery stenosis by quantitative flow ratio during invasive coronary angio-graphy: the WIFI II study (Wire-free functional imaging II). Circ Cardiovasc Imaging. 2018;11:e007107.
49. Tu S, Westra J, Yang J, et al. Diagnostic accuracy of fast computa-tional approaches to derive fraccomputa-tional flow reserve from diagnostic coronary angiography [Internet]. JACC Cardiovasc Interv.
2016;2024–2035. DOI:10.1016/j.jcin.2016.07.013.
50. Xu B, Tu S, Qiao S, et al. Diagnostic accuracy of angiography-based quantitative flow ratio measurements for online assessment of coronary stenosis [Internet]. J Am Coll Cardiol. 2017;70:3077–3087.
51. Douglas PS, De Bruyne B, Pontone G, et al. 1-year outcomes of FFRCT-guided care in patients with suspected coronary disease: the PLATFORM study. J Am Coll Cardiol. 2016;68:435–445.
52. Dodds SR. The haemodynamics of asymmetric stenoses. Eur J Vasc Endovasc Surg. 2002;24:332–337.
53. Heinen S, Gashi K, van den Heuvel D, et al. A metamodeling approach for instant severity assessment and uncertainty quantifi-cation of iliac artery stenoses. J Biomech Eng. [Internet]. 2019. DOI:10.1115/1.4044502.
54. Lee J-G, Ko J, Hae H, et al. Intravascular ultrasound-based machine learning for predicting fractional flow reserve in inter-mediate coronary artery lesions [Internet]. Atherosclerosis.
2020;292:171–177.
55. Cho H, Lee J-G, Kang S-J, et al. Angiography-based machine learn-ing for predictlearn-ing fractional flow reserve in intermediate coronary artery lesions. J Am Heart Assoc. 2019;8:e011685.
56. Mitchell T. Machine learning. New York, NY: McGraw-Hill; 1997. ISBN: 0070428077.
57. De Silva T, Punnoose J, Uneri A, et al. Virtual fluoroscopy for intraoperative C-arm positioning and radiation dose reduction. J Med Imaging (Bellingham). 2018;5:015005.
58. Agarwal S, Parashar A, Bajaj NS, et al. Relationship of beam angula-tion and radiaangula-tion exposure in the cardiac catheterizaangula-tion laboratory. JACC Cardiovasc Interv. 2014;7:558–566.
59. Schueler BA, Vrieze TJ, Bjarnason H, et al. An investigation of operator exposure in interventional radiology. Radiographics.
2006;26:1533–1541. . discussion 1541.
60. Schulz CJ, Schmitt M, Böckler D, et al. Feasibility and accuracy of fusion imaging during thoracic endovascular aortic repair. J Vasc Surg. 2016;63:314–322.
61. van den Berg JC. Update on new tools for three-dimensional navigation in endovascular procedures. Aorta (Stamford).
2014;2:279–285.
62. Sailer AM, Schurink GWH, Wildberger JE, et al. Radiation exposure of abdominal cone beam computed tomography. Cardiovasc Intervent Radiol. 2015;38:112–120.
63. Toth D, Pfister M, Maier A, et al. Adaption of 3D models to 2D X-ray images during endovascular abdominal aneurysm repair. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. Munich, Germany: Springer International Publishing; 2015. p. 339–346.
64. Lessard S, Kauffmann C, Pfister M, et al. Automatic detection of selective arterial devices for advanced visualization during abdom-inal aortic aneurysm endovascular repair. Med Eng Phys.
2015;37:979–986.
65. Varnavas A, Carrell T, Penney G. Fully automated 2D-3D registration and verification. Med Image Anal. 2015;26:108–119.
66. Modarai B Podium 1st: new developments in fusion imaging - artificial intelligence that deforms anatomy to maintain accuracy [Internet]; 2019. Available from: https://youtu.be/Yq9f-_YR43U
67. Southerland KW, Nag U, Turner M, et al. IF09. Image-based three-dimensional fusion computed tomography decreases radia-tion exposure, fluoroscopy time, and procedure time during endo-vascular aortic aneurysm repair. J Vasc Surg. 2018;67:e61. 68. Buckley CJ, Arko FR, Lee S, et al. Intravascular ultrasound scanning
improves long-term patency of iliac lesions treated with balloon angioplasty and primary stenting. J Vasc Surg. 2002;35:316–323. 69. Kumakura H, Kanai H, Araki Y, et al. 15-year patency and life
expectancy after primary stenting guided by intravascular ultra-sound for iliac artery lesions in peripheral arterial disease. JACC Cardiovasc Interv. 2015;8:1893–1901.
70. Goudeketting SR, Heinen SGH, de Haan MW, et al. Fluoroscopy with MRA fusion image guidance in endovascular iliac artery inter-ventions: study protocol for a randomized controlled trial (3DMR-Iliac-roadmapping study). Trials. 2018;19:603.
71. van der Molen AJ, Reimer P, Dekkers IA, et al. Post-contrast acute kidney injury - Part 1: definition, clinical features, incidence, role of contrast medium and risk factors: recommendations for updated ESUR contrast medium safety committee guidelines. Eur Radiol.
2018;28:2845–2855.
72. Jens S, Schreuder SM, De Boo DW, et al. Lowering iodinated contrast concentration in infrainguinal endovascular interventions: a three-armed randomized controlled non-inferiority trial. Eur Radiol. 2016;26:2446–2454. 73. McNally MM, Scali ST, Feezor RJ, et al. Three-dimensional fusion
computed tomography decreases radiation exposure, procedure time, and contrast use during fenestrated endovascular aortic repair. J Vasc Surg. 2015;61:309–316.
74. Philips Medical Systems Nederland B.V. AltaTrack - table side launch base instructions for use [Internet]. [cited 2019 Dec 29]. Available from: https://fcc.report/FCC-ID/2AQ4B-432207025350
75. de Lambert A, Esneault S, Lucas A, et al. Electromagnetic tracking for registration and navigation in endovascular aneurysm repair: a phantom study. Eur J Vasc Endovasc Surg. 2012;43:684–689. 76. Schwein A, Kramer B, Chinnadurai P, et al. Electromagnetic tracking
of flexible robotic catheters enables “assisted navigation” and brings automation to endovascular navigation in an in vitro study. J Vasc Surg. 2018;67:1274–1281.
77. Solomon SB, Magee CA, Acker DE, et al. Experimental nonfluoro-scopic placement of inferior vena cava filters: use of an electro-magnetic navigation system with previous CT data. J Vasc Interv Radiol. 1999;10:92–95.
78. Schwein A, Kramer B, Chinnadurai P, et al. Flexible robotics with electromagnetic tracking improves safety and efficiency during in vitro endovascular navigation. J Vasc Surg. 2017;65:530–537. 79. Wood BJ, Zhang H, Durrani A, et al. Navigation with
electromag-netic tracking for interventional radiology procedures: a feasibility study. J Vasc Interv Radiol. 2005;16:493–505.
80. Goode SD, Keltie K, Burn J, et al. Effect of procedure volume on outcomes after iliac artery angioplasty and stenting. Br J Surg.
2013;100:1189–1196.
81. de Boer SW, Heinen S, van den Heuvel D, et al. How to define the hemodynamic significance of an equivocal iliofemoral artery ste-nosis: review of literature and outcomes of an international questionnaire. Vascular. 2017;25:598–608.
82. Fryback DG, Thornbury JR. The efficacy of diagnostic imaging. Med Decis Making. 1991;11:88–94.
83. Ketteler ER, Brown KR. Radiation exposure in endovascular procedures. J Vasc Surg. 2011;53:35S– 38S.
84. Majewska N, Blaszak MA, Juszkat R, et al. Patients’ radiation doses during the implantation of stents in carotid, renal, iliac, femoral and popliteal arteries. Eur J Vasc Endovasc Surg. 2011;41:372–377. 85. El-Sayed T, Patel AS, Cho JS, et al. Radiation-induced DNA damage
in operators performing endovascular aortic repair. Circulation.
2017;136:2406–2416.
86. Horsky J. Cognitive behavior and clinical workflows. In: Zheng K, Westbrook J, Kannampallil TG, et al., editors. Cognitive informatics EXPERT REVIEW OF CARDIOVASCULAR THERAPY 403
reengineering clinical workflow for safer and more efficient care. Berlin, Germany: Springer International Publishing. 2019; p. 9–29. 87. Manske CL, Sprafka JM, Strony JT, et al. Contrast nephropathy in azotemic
diabetic patients undergoing coronary angiography. Am J Med.
1990;89:615–620.
88. Cigarroa RG, Lange RA, Williams RH, et al. Dosing of contrast material to prevent contrast nephropathy in patients with renal disease. Am J Med. 1989;86:649–652.
89. Laskey WK, Jenkins C, Selzer F, et al. Volume-to-creatinine clearance ratio: a pharmacokinetically based risk factor for prediction of early
creatinine increase after percutaneous coronary intervention. J Am Coll Cardiol. 2007;50:584–590.
90. Gurm HS, Dixon SR, Smith DE, et al. Renal function-based contrast dosing to define safe limits of radiographic contrast media in patients undergoing percutaneous coronary interventions. J Am Coll Cardiol. 2011;58:907–914.
91. Yoon H-J, Hur S-H. Determination of safe contrast media dosage to estimated glomerular filtration rate ratios to avoid contrast-induced nephropathy after elective percutaneous coron-ary intervention. Korean Circ J. 2011;41:265–271.
