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254 results for “Abdominal aortic aneurysm”
Histopathological Evaluation of Abdominal Aortic Aneurysms with Deep Learning: The HistAAA Dataset
<p>This dataset accompanies our manuscript "Histopathological Evaluation of Abdominal Aortic Aneurysms with Deep Learning" (<a title="Histopathological evaluation of abdominal aortic aneurysms with deep learning" href="https://www.medrxiv.org/content/10.1101/2024.04.23.24306178v1">1</a>) and comprises feature vectors extracted from digital whole-slide images (WSI) of abdominal aortic aneurysm (AAA) wall samples from 369 patients treated at three European centers and corresponding expert pathologist annotations. This dataset is intended to be used for computational modelling tasks including automated prediction of pathology-related variables such as inflammation, degradation of elastic fibers, and fibrosis (<a title="Histopathological evaluation of abdominal aortic aneurysms with deep learning" href="https://www.medrxiv.org/content/10.1101/2024.04.23.24306178v1">1</a>). </p> <p>Code for preprocessing is available at <a href="https://github.com/KatherLab/STAMP">https://github.com/KatherLab/STAMP</a>. Code for modeling is available at <a href="https://github.com/KatherLab/marugoto">https://github.com/KatherLab/marugoto</a>. Code for spatial heatmaps and top-attention tiles is available at <a href="https://github.com/KatherLab/highres-WSI-heatmaps/tree/AAA_heatmaps">https://github.com/KatherLab/highres-WSI-heatmaps/tree/AAA_heatmaps</a>. </p> <h3>Patient Cohort</h3> <p>Data from a total of 369 patients (84.6% male, mean age 69.1 ± 8.0 years, average maximum diameter 62.9 ± 15.7 mm) undergoing open AAA repair at the Technical University Munich (TUM, n = 287), the University Hospital Würzburg (UHW, n = 36) and the Medical University Vienna (MUV, n = 46), between 2005 and 2019, are included in this dataset. </p> <p>To generate annotations, aneurysm samples from the left anterior wall were independently analyzed by three pathologists as described previously (<a title="Abdominal aortic aneurysms harbor different histomorphology not associated with classic risk factors &ndash; the HistAAA study" href="https://www.medrxiv.org/content/10.1101/2024.04.16.24305904v1">2</a>). In brief, the following histopathological parameters were evaluated: Grade of inflammation in tunica media [none, minor, intermediate, major], grade of inflammation in adventitia [none, minor, intermediate, major], type of inflammation in adventitia and tunica media [none, acute, chronic], Histological Inflammation Scale of Aneurysms (HISA) grade (<a title="Inflammation of the abdominal aortic aneurysm wall" href="https://www.sciencedirect.com/science/article/abs/pii/S0950821X05801185">3</a>) [0, 1, 2, 3, 4], angiogenesis in tunica media [present, not present], calcification in tunica media [present, not present], grade of fibrosis in adventitia [minor, intermediate, major], remaining elastic fibers in tunica media [< 25%, > 25%]. In case of disagreement, consensus was reached through discussion. Hematoxylin and Eosin (HE)- and Elastica van Gieson (EvG)-stained slides were digitized using an Aperio AT2 (Leica, Wetzlar, Germany) slide scanner. Patient sex and smoking history were gathered as binary clinical parameters. </p> <h3>Preprocessing and Feature Extraction</h3> <p>The STAMP protocol was utilized to process the WSIs (<a title="From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology" href="https://arxiv.org/abs/2312.10944">4</a>). In brief, WSI were preprocessed by tessellation into 224 x 224 pixel patches at a magnification of 256 µm per pixel, followed by computational background rejection, and color normalization of HE-stained slides. EvG-stained slides were not color-normalized as no color normalization protocols exist for this staining. Subsequently, features were extracted using CTranspath (<a title="Transformer-based unsupervised contrastive learning for histopathological image classification" href="https://www.sciencedirect.com/science/article/abs/pii/S1361841522002043">5</a>), a pre-trained histology image encoder. </p> <p> </p> <h3>References</h3> <p>1. Kolbinger, F. R. et al. Histopathological Evaluation of Abdominal Aortic Aneurysms with Deep Learning. medRxiv 2024.04.23.24306178 (2024) doi:10.1101/2024.04.23.24306178. </p> <p>2. Nackenhorst, M. C. et al. Abdominal aortic aneurysms harbor different histomorphology not associated with classic risk factors – the HistAAA study. medRxiv 2024.04.16.24305904 (2024) doi:10.1101/2024.04.16.24305904. </p> <p>3. Rijbroek, A., Moll, F. L., von Dijk, H. A., Meijer, R. & Jansen, J. W. Inflammation of the abdominal aortic aneurysm wall. Eur. J. Vasc. Surg. 8, 41–46 (1994).</p> <p>4. El Nahhas, O. S. M. et al. From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology. arXiv [cs.CV] (2023).</p> <p>5. Wang, X. et al. Transformer-based unsupervised contrastive learning for histopathological image classification. Med. Image Anal. 81, 102559 (2022).</p>
AAA-100: A Curated Dataset of 3D Watertight Abdominal Aortic Aneurysm Models
<p>An abdominal aortic aneurysm (AAA) is a local dilatation of the abdominal aorta exceeding 30 mm that might rupture, with fatal outcomes in 70-80% of cases. Personalized 3D models of AAAs, including surrounding vasculature such as iliac and renal arteries play an important role in tailored clinical decision-making for AAA patients. Models could be used for, e.g., AAA growth modeling, stentgraft sizing and positioning for endovascular aorta repair (EVAR) procedures, or 3D printing for surgical practice. Extracting high-quality 3D arterial models from imaging modalities such as computed tomography angiography (CTA) is a time-consuming and challenging problem. For downstream applications such as computational fluid dynamics (CFD) or shape analysis, models should have sub-voxel accuracy, be watertight, and adhere to topological constraints. We present the AAA-100 dataset, containing 100 detailed 3D AAA models with consistent anatomical boundaries acquired semi-automatically from pre-operative CTA scans. These models span a wide range of possible AAA pathology. Moreover, all models are carefully curated to be anatomically and topologically correct. </p> <p>A detailed description of the data set and file structure is provided in description.pdf.</p> <p>We kindly ask you to cite the following works when using the AAA-100 dataset in your research</p> <blockquote> <p>Alblas, D., Suk, J., Brune, C., Yeung, K. K., & Wolterink, J. M. (2025). SIRE: Scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks. <em>Medical Image Analysis</em>, 103467.</p> <p>Rygiel, P., Alblas, D., Brune, C., Yeung, K. K., & Wolterink, J. M. (2024). Global Control for Local SO (3)-Equivariant Scale-Invariant Vessel Segmentation. <em>arXiv preprint arXiv:2403.15314</em>.</p> </blockquote>
Imaging dataset for "Angiotensin II infusion into ApoE-/- mice: a model for aortic dissection rather than abdominal aortic aneurysm?"
<p>This dataset contains imaging files of the manuscript "Angiotensin II infusion into ApoE-/- mice: a model for aortic dissection rather than abdominal aortic aneurysm?", published in Cardiovascular Research in 2017. All published files are to be opened in Mimics (Materialise, Leuven, Belgium). All files are named as follows: "technique_id_timepoint_abd.mcs". The technique can be either in vivo micro-CT, or ex-vivo synchrotron-based PCXTM. The mouse ID corresponds to the ID that was used during the experiments. Mice were distributed at random into 2 groups (G1 and G2) and sacrificed after 1 of 4 possible timepoints. TP0 corresponds to baseline (prior to Ang II infusion), TP1 corresponds to 3 days of Ang II infusion, TP2 corresponds to 10 days of Ang II infusion, TP3 corresponds to 18 days of Ang II infusion and TP4 corresponds to 28 days of Ang II infusion. Image files from PCXTM are ex vivo and always correspond to the latest timepoint available with micro-CT of that animal. Histology data are zipped and stored in .vsi format. They can be opened with the Olympus software package OlyVIA or with the BIOP-plugin "vsi-reader" to the open source software package fiji.</p>
Search strategies for screening for abdominal aortic aneurysm (AAA) in men: a health technology assessment
<p>The dataset includes the complete, reproducible search strategies for all literature databases searched during this project. The search strategies address the following research question: </p><p>What is the clinical effectiveness and safety of population-based ultrasound screening for AAA in men compared with no systematic screening?</p>
Dataset for "Dissecting abdominal aortic aneurysm in Ang II-infused mice: suprarenal branch ruptures and apparent luminal dilatation"
<p>This dataset contains histology, synchrotron and ultrasound data for the manuscript "Dissecting abdominal aortic aneurysm<br> in Ang II-infused mice: suprarenal branch ruptures and apparent luminal dilatation", published in Cardiovascular Research in 2014.</p> <p>Histology data are zipped and to be opened using the Olympus-software OlyVIA, or with the BIOP-tool called VSI-reader, which is a plugin to the open-source software Fiji. Imaging data are saved in .mcs format and can be opened with the commercial software Mimics (Materialise, Leuven, Belgium). Filenames correspond to the mouse ID as it was used in the study.</p>
Preferences for Open Vs. Endovascular Repair for Abdominal Aortic Aneurysm
ClinicalTrials.gov study NCT03115346. IPD Sharing: NO. Countries: 1. Publications: 33.
HORIZON CE Pivotal Study to Treat Abdominal Aortic Aneurysm
ClinicalTrials.gov study NCT02087501. IPD Sharing: Not stated. Countries: 4. Publications: 1.
Non-Invasive Treatment of Abdominal Aortic Aneurysm Clinical Trial
ClinicalTrials.gov study NCT01756833. IPD Sharing: YES. Countries: 1. Publications: 7.
Standard Open Surgery Versus Endovascular Repair of Abdominal Aortic Aneurysm (AAA)
ClinicalTrials.gov study NCT00094575. IPD Sharing: Not stated. Countries: 1. Publications: 15.
European (EU) Post Approval Study of the INCRAFT® AAA Stent Graft System in Subjects With Abdominal Aortic Aneurysms
ClinicalTrials.gov study NCT02477111. IPD Sharing: UNDECIDED. Countries: 8. Publications: 2.
Safety and Effectiveness Study of Endovascular Abdominal Aortic Aneurysm Repair Using the Nellix® System
ClinicalTrials.gov study NCT01726257. IPD Sharing: Not stated. Countries: 4. Publications: 5.
34mm Cuff Study for Endovascular Repair of Abdominal Aortic Aneurysms
ClinicalTrials.gov study NCT00706394. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Multicenter, Open Label, Prospective, Non-randomized Study of the InCraft® Stent Graft System in Subjects With Abdominal Aortic Aneurysms (INSPIRATION)
ClinicalTrials.gov study NCT01664078. IPD Sharing: NO. Countries: 2. Publications: 1.
Comparison of Outcomes of Complex Abdominal Aortic Aneurysm Treatment
ClinicalTrials.gov study NCT04773223. IPD Sharing: NO. Countries: 1. Publications: 4.
Intraocular Pressure During Abdominal Aortic Aneurysm (AAA) Repair
ClinicalTrials.gov study NCT00450294. IPD Sharing: Not stated. Countries: 1. Publications: 15.
Suprarenal Proximal Cuff Study for Treatment of Abdominal Aortic Aneurysm
ClinicalTrials.gov study NCT00739401. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Detecting Abdominal Aortic Aneurysms in First Degree Relatives (Adult Offsprings) to AAA Patients (DAAAD)
ClinicalTrials.gov study NCT04623268. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Assessment of the GORE® EXCLUDER® Conformable AAA Endoprosthesis in the Treatment of Abdominal Aortic Aneurysms
ClinicalTrials.gov study NCT02489539. IPD Sharing: NO. Countries: 1. Publications: 0.
Endovascular Exclusion of Abdominal Aortic Aneurysms in High Risk Patients
ClinicalTrials.gov study NCT00583414. IPD Sharing: NO. Countries: 1. Publications: 2.
Temporal effects of sympathetic denervation on aortic remodeling and rupture in experimental abdominal aortic aneurysm
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