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  1. Article ; Online: Blood Flow Patterns of Risk in Aortic Dissection: Time to Go With the Flow?

    Burris, Nicholas S / Fleischmann, Dominik / Hope, Michael D

    Journal of the American College of Cardiology

    2022  Volume 79, Issue 24, Page(s) 2428–2430

    MeSH term(s) Aortic Dissection/diagnostic imaging ; Aortic Dissection/epidemiology ; Aortic Aneurysm, Thoracic ; Blood Flow Velocity ; Hemodynamics ; Humans ; Magnetic Resonance Imaging
    Language English
    Publishing date 2022-06-16
    Publishing country United States
    Document type Editorial ; Comment
    ZDB-ID 605507-2
    ISSN 1558-3597 ; 0735-1097
    ISSN (online) 1558-3597
    ISSN 0735-1097
    DOI 10.1016/j.jacc.2022.04.023
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1846: Show issues Location:
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  2. Article ; Online: Imaging Thoracic Aortic Aneurysm.

    Kallianos, Kimberly G / Burris, Nicholas S

    Radiologic clinics of North America

    2020  Volume 58, Issue 4, Page(s) 721–731

    Abstract: High-quality aortic imaging plays a central role in the management of patients with thoracic aortic aneurysm. Computed tomography angiography and magnetic resonance angiography are the most commonly used techniques for thoracic aortic aneurysm diagnosis ... ...

    Abstract High-quality aortic imaging plays a central role in the management of patients with thoracic aortic aneurysm. Computed tomography angiography and magnetic resonance angiography are the most commonly used techniques for thoracic aortic aneurysm diagnosis and imaging surveillance, with each having unique strengths and limitations that should be weighed when deciding patient-specific applications. To ensure optimal patient care, imagers must be familiar with potential sources of artifact and measurement error, and dedicate effort to ensure high-quality and reproducible aortic measurements are generated. This review summarizes the imaging evaluation and underlying pathology relevant to the diagnosis of thoracic aortic aneurysm.
    MeSH term(s) Aortic Aneurysm, Thoracic/diagnostic imaging ; Humans ; Magnetic Resonance Angiography ; Tomography, X-Ray Computed/methods
    Language English
    Publishing date 2020-05-12
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 215712-3
    ISSN 1557-8275 ; 0033-8389
    ISSN (online) 1557-8275
    ISSN 0033-8389
    DOI 10.1016/j.rcl.2020.02.009
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  3. Article: Natural history and clinical significance of aortic focal intimal flaps.

    Maas, Austin / van Bakel, Pieter A J / Ahmed, Yunus / Patel, Himanshu J / Burris, Nicholas S

    Frontiers in cardiovascular medicine

    2022  Volume 9, Page(s) 959517

    Abstract: Objective: Focal intimal flaps (FIF) are a variety of defects of the aorta that result in a short, flap-like projection into the lumen, and are often encountered in asymptomatic patients undergoing computed tomography angiography (CTA) surveillance for ... ...

    Abstract Objective: Focal intimal flaps (FIF) are a variety of defects of the aorta that result in a short, flap-like projection into the lumen, and are often encountered in asymptomatic patients undergoing computed tomography angiography (CTA) surveillance for aortic aneurysm, but the natural history and clinical significance of such lesions has not yet been studied.
    Methods: We retrospectively identified patients with an asymptomatic FIF and available imaging follow-up (>1 year). FIF was defined as flap-like intimal irregularity < 4 cm in length involving the thoracic aorta (TA), abdominal aorta (AA) or common iliac arteries (CIA). FIF characteristics included length and circumferential extent as well as the presence and size (width and depth) of associated penetrating aortic ulcers (PAUs). Patient characteristics, adverse events and history of surgical repair was determined by chart review. FIFs and associated PAUs were assessed for progression by comparing baseline and follow-up CTA studies.
    Results: A total of 84 FIFs were identified in 77 patients. Average age was 69.2 ± 10.1 years, and 81% were male (81%). Common co-morbidities included: hypertension (78%), hyperlipidemia (68%), smoking (60%), coronary artery disease (41%), aortic aneurysm (34%), type II diabetes mellitus (27%) and prior cardiovascular surgery (25%). FIFs were most commonly located in the abdominal aorta (
    Conclusion: Focal intimal flaps identified in asymptomatic patients with aortic disease were co-localized with atherosclerotic plaque and PAUs, and demonstrated indolent behavior, not leading to significant growth or acute aortic events, supporting a conservative management approach.
    Language English
    Publishing date 2022-10-04
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2781496-8
    ISSN 2297-055X
    ISSN 2297-055X
    DOI 10.3389/fcvm.2022.959517
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  4. Article ; Online: Validation of a robust method for quantification of three-dimensional growth of the thoracic aorta using deformable image registration.

    Bian, Zhangxing / Zhong, Jiayang / Dominic, Jeffrey / Christensen, Gary E / Hatt, Charles R / Burris, Nicholas S

    Medical physics

    2022  Volume 49, Issue 4, Page(s) 2514–2530

    Abstract: Purpose: Accurate assessment of thoracic aortic aneurysm (TAA) growth is important for appropriate clinical management. Maximal aortic diameter is the primary metric that is used to assess growth, but it suffers from substantial measurement variability. ...

    Abstract Purpose: Accurate assessment of thoracic aortic aneurysm (TAA) growth is important for appropriate clinical management. Maximal aortic diameter is the primary metric that is used to assess growth, but it suffers from substantial measurement variability. A recently proposed technique, termed vascular deformation mapping (VDM), is able to quantify three-dimensional aortic growth using clinical computed tomography angiography (CTA) data using an approach based on deformable image registration (DIR). However, the accuracy and robustness of VDM remains undefined given the lack of ground truth from clinical CTA data, and, furthermore, the performance of VDM relative to standard manual diameter measurements is unknown.
    Methods: To evaluate the performance of the VDM pipeline for quantifying aortic growth, we developed a novel and systematic evaluation process to generate 76 unique synthetic CTA growth phantoms (based on 10 unique cases) with variable degrees and locations of aortic wall deformation. Aortic deformation was quantified using two metrics: area ratio (AR), defined as the ratio of surface area in triangular mesh elements and the magnitude of deformation in the normal direction (DiN) relative to the aortic surface. Using these phantoms, we further investigated the effects on VDM's measurement accuracy resulting from factors that influence the quality of clinical CTA data such as respiratory translations, slice thickness, and image noise. Lastly, we compare the measurement error of VDM TAA growth assessments against two expert raters performing standard diameter measurements of synthetic phantom images.
    Results: Across our population of 76 synthetic growth phantoms, the median absolute error was 0.063 (IQR: 0.073-0.054) for AR and 0.181 mm (interquartile range [IQR]: 0.214-0.143 mm) for DiN. Median relative error was 1.4% for AR and
    Conclusions: VDM yields an accurate, three-dimensional assessment of aortic growth in TAA patients and is robust to factors such as image noise, respiration-induced translations, and differences in patient position. Further, VDM significantly outperformed two expert manual raters in assessing the magnitude and location of aortic growth despite optimized experimental measurement conditions. These results support validation of the VDM technique for accurate quantification of aortic growth in patients and highlight several important advantages over diameter measurements.
    MeSH term(s) Algorithms ; Aorta ; Aorta, Thoracic/diagnostic imaging ; Computed Tomography Angiography ; Humans ; Image Processing, Computer-Assisted/methods ; Phantoms, Imaging ; Tomography, X-Ray Computed
    Language English
    Publishing date 2022-02-17
    Publishing country United States
    Document type Journal Article
    ZDB-ID 188780-4
    ISSN 2473-4209 ; 0094-2405
    ISSN (online) 2473-4209
    ISSN 0094-2405
    DOI 10.1002/mp.15496
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    Zs.A 1210: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  5. Article: Evolving treatment options for valve and aortic disease with bicuspid aortic valve.

    Burris, Nicholas S / Hope, Michael D

    Annals of translational medicine

    2017  Volume 5, Issue 16, Page(s) 333

    Language English
    Publishing date 2017-08-16
    Publishing country China
    Document type Editorial ; Comment
    ZDB-ID 2893931-1
    ISSN 2305-5847 ; 2305-5839
    ISSN (online) 2305-5847
    ISSN 2305-5839
    DOI 10.21037/atm.2017.04.26
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  6. Article: Fully automated pipeline for measurement of the thoracic aorta using joint segmentation and localization neural network.

    Katakol, Sudeep / Baker, Timothy J / Bian, Zhangxing / Lu, Yanglong / Spahlinger, Greg / Hatt, Charles R / Burris, Nicholas S

    Journal of medical imaging (Bellingham, Wash.)

    2023  Volume 10, Issue 5, Page(s) 51810

    Abstract: Purpose: Diagnosis and surveillance of thoracic aortic aneurysm (TAA) involves measuring the aortic diameter at various locations along the length of the aorta, often using computed tomography angiography (CTA). Currently, measurements are performed by ... ...

    Abstract Purpose: Diagnosis and surveillance of thoracic aortic aneurysm (TAA) involves measuring the aortic diameter at various locations along the length of the aorta, often using computed tomography angiography (CTA). Currently, measurements are performed by human raters using specialized software for three-dimensional analysis, a time-consuming process, requiring 15 to 45 min of focused effort. Thus, we aimed to develop a convolutional neural network (CNN)-based algorithm for fully automated and accurate aortic measurements.
    Approach: Using 212 CTA scans, we trained a CNN to perform segmentation and localization of key landmarks jointly. Segmentation mask and landmarks are subsequently used to obtain the centerline and cross-sectional diameters of the aorta. Subsequently, a cubic spline is fit to the aortic boundary at the sinuses of Valsalva to avoid errors related inclusions of coronary artery origins. Performance was evaluated on a test set of 60 scans with automated measurements compared against expert manual raters.
    Result: Compared to training separate networks for each task, joint training yielded higher accuracy for segmentation, especially at the boundary (
    Conclusion: Fully automated aortic diameter measurements in TAA are feasible using a CNN-based algorithm. Automated measurements demonstrated low errors that are comparable in magnitude to those with manual raters; however, measurement error was highest in the aortic root and arch.
    Language English
    Publishing date 2023-10-31
    Publishing country United States
    Document type Journal Article
    ISSN 2329-4302
    ISSN 2329-4302
    DOI 10.1117/1.JMI.10.5.051810
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  7. Article: Three-Dimensional Characterization of Aortic Root Motion by Vascular Deformation Mapping.

    Kim, Taeouk / Tjahjadi, Nic S / He, Xuehuan / van Herwaarden, J A / Patel, Himanshu J / Burris, Nicholas S / Figueroa, C Alberto

    Journal of clinical medicine

    2023  Volume 12, Issue 13

    Abstract: The aorta is in constant motion due to the combination of cyclic loading and unloading with its mechanical coupling to the contractile left ventricle (LV) myocardium. This aortic root motion has been proposed as a marker for aortic disease progression. ... ...

    Abstract The aorta is in constant motion due to the combination of cyclic loading and unloading with its mechanical coupling to the contractile left ventricle (LV) myocardium. This aortic root motion has been proposed as a marker for aortic disease progression. Aortic root motion extraction techniques have been mostly based on 2D image analysis and have thus lacked a rigorous description of the different components of aortic root motion (e.g., axial versus in-plane). In this study, we utilized a novel technique termed vascular deformation mapping (VDM(D)) to extract 3D aortic root motion from dynamic computed tomography angiography images. Aortic root displacement (axial and in-plane), area ratio and distensibility, axial tilt, aortic rotation, and LV/Ao angles were extracted and compared for four different subject groups: non-aneurysmal, TAA, Marfan, and repair. The repair group showed smaller aortic root displacement, aortic rotation, and distensibility than the other groups. The repair group was also the only group that showed a larger relative in-plane displacement than relative axial displacement. The Marfan group showed the largest heterogeneity in aortic root displacement, distensibility, and age. The non-aneurysmal group showed a negative correlation between age and distensibility, consistent with previous studies. Our results revealed a strong positive correlation between LV/Ao angle and relative axial displacement and a strong negative correlation between LV/Ao angle and relative in-plane displacement. VDM(D)-derived 3D aortic root motion can be used in future studies to define improved boundary conditions for aortic wall stress analysis.
    Language English
    Publishing date 2023-07-04
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662592-1
    ISSN 2077-0383
    ISSN 2077-0383
    DOI 10.3390/jcm12134471
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  8. Book ; Online: LitCall

    Bian, Zhangxing / Zhong, Jiayang / Lu, Yanglong / Hatt, Charles R. / Burris, Nicholas S.

    Learning Implicit Topology for CNN-based Aortic Landmark Localization

    2023  

    Abstract: Landmark detection is a critical component of the image processing pipeline for automated aortic size measurements. Given that the thoracic aorta has a relatively conserved topology across the population and that a human annotator with minimal training ... ...

    Abstract Landmark detection is a critical component of the image processing pipeline for automated aortic size measurements. Given that the thoracic aorta has a relatively conserved topology across the population and that a human annotator with minimal training can estimate the location of unseen landmarks from limited examples, we proposed an auxiliary learning task to learn the implicit topology of aortic landmarks through a CNN-based network. Specifically, we created a network to predict the location of missing landmarks from the visible ones by minimizing the Implicit Topology loss in an end-to-end manner. The proposed learning task can be easily adapted and combined with Unet-style backbones. To validate our method, we utilized a dataset consisting of 207 CTAs, labeling four landmarks on each aorta. Our method outperforms the state-of-the-art Unet-style architectures (ResUnet, UnetR) in terms of localization accuracy, with only a light (#params=0.4M) overhead. We also demonstrate our approach in two clinically meaningful applications: aortic sub-region division and automatic centerline generation.

    Comment: Accepted to Medical Imaging 2022: Image Processing
    Keywords Electrical Engineering and Systems Science - Image and Video Processing
    Subject code 006
    Publishing date 2023-04-15
    Publishing country us
    Document type Book ; Online
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  9. Article: Vascular Deformation Mapping (VDM) of thoracic aortic aneurysm: an application for color 3D printing in aortic disease.

    Burris, Nicholas S / Hoff, Benjamin A / Ross, Brian D

    Annals of translational medicine

    2019  Volume 6, Issue Suppl 2, Page(s) S123

    Language English
    Publishing date 2019-01-22
    Publishing country China
    Document type Editorial ; Comment
    ZDB-ID 2893931-1
    ISSN 2305-5847 ; 2305-5839
    ISSN (online) 2305-5847
    ISSN 2305-5839
    DOI 10.21037/atm.2018.12.16
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  10. Article ; Online: Retrograde flow in the false lumen: Marker of a false lumen under stress?

    Burris, Nicholas S / Patel, Himanshu J / Hope, Michael D

    The Journal of thoracic and cardiovascular surgery

    2018  Volume 157, Issue 2, Page(s) 488–491

    MeSH term(s) Aneurysm, Dissecting ; Aortic Aneurysm, Thoracic ; Humans
    Language English
    Publishing date 2018-07-29
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 3104-5
    ISSN 1097-685X ; 0022-5223
    ISSN (online) 1097-685X
    ISSN 0022-5223
    DOI 10.1016/j.jtcvs.2018.06.092
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    Uk I Zs.104: Show issues Location:
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