References
- Raskob GE, Angchaisuksiri P, Blanco AN, et al; ISTH Steering Committee for World Thrombosis Day. Thrombosis: a major contributor to global disease burden. Arterioscler Thromb Vasc Biol. 2014 Nov;34(11):2363–71. doi: 10.1161/ATVBAHA.114.304488
- Wendelboe AM, Raskob GE. Global Burden of Thrombosis: Epidemiologic Aspects. Circ Res. 2016 Apr 29;118(9):1340–7. doi: 10.1161/CIRCRESAHA.115.306841
- Cohen AT, Agnelli G, Anderson FA, et al. Venous thromboembolism (VTE) in Europe. Thrombosis and Haemostasis. 2007 Oct;98(10):756–64. doi: 10.1160/TH07-03-0212
- Keller K, Hobohm L, Ebner M, et al. Trends in thrombolytic treatment and outcomes of acute pulmonary embolism in Germany. Eur Heart J. 2020 Jan 21;41(4):522–529. doi: 10.1093/eurheartj/ehz236
- Dentali F, Ageno W, Pomero F, Fenoglio L, Squizzato A, Bonzini M. Time trends and case fatality rate of in-hospital treated pulmonary embolism during 11 years of observation in Northwestern Italy. Thromb Haemost. 2016 Jan;115(2):399–405. doi: 10.1160/TH15-02-0172
- de Miguel-Díez J, Jiménez-García R, Jiménez D, et al. Trends in hospital admissions for pulmonary embolism in Spain from 2002 to 2011. Eur Respir J. 2014 Oct;44(4):942–50. doi: 10.1183/09031936.00194213
- Katsoularis I, Fonseca-Rodríguez O, Farrington P, et al. Risks of deep vein thrombosis, pulmonary embolism, and bleeding after covid-19: nationwide self-controlled cases series and matched cohort study. BMJ. 2022 Apr 6;377:e069590. doi: 10.1136/bmj-2021-069590
- Estrada-Y-Martin RM, Oldham SA. CTPA as the gold standard for the diagnosis of pulmonary embolism. Int J Comput Assist Radiol Surg. 2011 Jul;6(4):557–63. doi: 10.1007/s11548-010-0526-4
- Kocher KE, Meurer WJ, Fazel R, Scott PA, Krumholz HM, Nallamothu BK. National trends in use of computed tomography in the emergency department. Ann Emerg Med. 2011 Nov;58(5):452–62.e3. doi: 10.1016/j.annemergmed.2011.05.020
- Portoghese I, Galletta M, Coppola RC, Finco G, Campagna M. Burnout and workload among health care workers: the moderating role of job control. Saf Health Work. 2014 Sep;5(3):152–7. doi: 10.1016/j.shaw.2014.05.004
- Bouma H, Sonnemans JJ, Vilanova A, Gerritsen FA. Automatic detection of pulmonary embolism in CTA images. IEEE Trans Med Imaging. 2009 Aug;28(8):1223–1230. doi: 10.1109/TMI.2009.2013618
- Pichon E, Novak CL, Kiraly AP, Naidich DP. A novel method for pulmonary emboli visualization from high-resolution CT images. In: SPIE Proceedings Volume 5367. Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, 2004; p. 161.
- LeCun Y, Bottou L, Bengio L, Haffner P. Gradient-based learning applied to document recognition. Proceedings of the IEEE. 1998;86(11):2278–2324. doi: 10.1109/5.726791
- Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. Communications of the ACM. 2017;60(6):84–90. doi: 10.1145/3065386
- Johnson PT. Artifacts mimicking pulmonary embolism. Pearls and Pitfalls in Cardiovascular Imaging: Pseudolesions, Artifacts and Other Difficult Diagnoses. Cambridge University Press, 2015. pp. 134–136. doi: 10.1017/CBO9781139152228.044
- Ritchie G, McGurk S, McCreath C, Graham C, Murchison JT. Prospective evaluation of unsuspected pulmonary embolism on contrast enhanced multidetector CT (MDCT) scanning. Thorax. 2007 Jun;62(6):536–40. doi: 10.1136/thx.2006.062299
- Stefanidis K, Green J, Konstantelou E, Robbie H. Flow artefact mimicking pulmonary embolism in pulmonary hypertension. BMJ Case Rep. 2020 Feb 26;13(2):e234652. doi: 10.1136/bcr-2020-234652
- Ajmera P, Kharat A, Seth J, et al. A deep learning approach for automated diagnosis of pulmonary embolism on computed tomographic pulmonary angiography. BMC Med Imaging. 2022 Nov 11;22(1):195. doi: 10.1186/s12880-022-00916-0
- Moore AJE, Wachsmann J, Chamarthy MR, Panjikaran L, Tanabe Y, Rajiah P. Imaging of acute pulmonary embolism: an update. Cardiovasc Diagn Ther. 2018 Jun;8(3):225–243. doi: 10.21037/cdt.2017.12.01
- Huang SC, Huo Z, Steinberg E, et al. INSPECT: A multimodal dataset for pulmonary embolism diagnosis and prognosis. arXiv:2311.10798 [Preprint]. 2023. Available from:
https://arxiv.org/abs/2311.10798 - Zhou Y, Huang SC, Fries JA, et al. Radfusion: RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and HER. arXiv:2111.11665 [Preprint]. 2021. Available from:
https://arxiv.org/abs/2111.11665 - Colak E, Kitamura FC, Hobbs SB, et al; RSNA-STR Annotators and Dataset Curation Contributors. The RSNA Pulmonary Embolism CT Dataset. Radiol Artif Intell. 2021 Jan 20;3(2):e200254. doi: 10.1148/ryai.2021200254
- Callejas MF, Lin HM, Howard T, et al. Augmentation of the RSNA Pulmonary Embolism CT Dataset with Bounding Box Annotations and Anatomic Localization of Pulmonary Emboli. Radiol Artif Intell. 2023 May 3;5(3):e230001. doi: 10.1148/ryai.230001
- Masoudi M, Pourreza HR, Saadatmand-Tarzjan M, Eftekhari N, Zargar FS, Rad MP. A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism. Sci Data. 2018 Sep 4;5:180180. doi: 10.1038/sdata.2018.180
- Lanza E, Ammirabile A, Francone M. nnU-Net-based deep-learning for pulmonary embolism: detection, clot volume quantification, and severity correlation in the RSPECT dataset. Eur J Radiol. 2024 Aug;177:111592. doi: 10.1016/j.ejrad.2024.111592
- Masutani Y, MacMahon H, Doi K. Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis. IEEE Transactions on Medical Imaging. 2002 Dec;21(12):1517–23. doi: 10.1109/TMI.2002.806586
- Engelke C, Schmidt S, Bakai A, Auer F, Marten K. Computer-assisted detection of pulmonary embolism: performance evaluation in consensus with experienced and inexperienced chest radiologists. European Radiology. 2008 Feb;18(2):298–307. doi: 10.1007/s00330-007-0770-3
- Tajbakhsh N, Gotway MB, Liang J. Computer-aided pulmonary embolism detection using a novel vessel-aligned multi-planar image representation and convolutional neural networks. In Hornegger J, Frangi AF, Wells WM, Frangi AF, Navab N, Hornegger J, Navab N, Wells WM, Wells WM, Frangi AF, Hornegger J, Navab N, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. Springer Verlag. 2015. p. 62–69. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-24571-3_8
- Huang SC, Kothari T, Banerjee I, et al. PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. NPJ Digital Medicine. 2020 Jan 24;3(1):61. doi: 10.1038/s41746-020-0266-y
- Kahraman AT, Fröding T, Toumpanakis D, Gustafsson CJ, Sjöblom T. Enhanced classification performance using deep learning based segmentation for pulmonary embolism detection in CT angiography. Heliyon. 2024;10(19):e38118. doi: 10.1016/j.heliyon.2024.e38118
- Weikert T, Winkel DJ, Bremerich J, et al. Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm. Eur Radiol. 2020 Dec;30(12):6545–6553. doi: 10.1007/s00330-020-06998-0
- Condrea F, Rapaka S, Itu L, et al. Anatomically aware dual-hop learning for pulmonary embolism detection in CT pulmonary angiograms. Comput Biol Med. 2024 May;174:108464. doi: 10.1016/j.compbiomed.2024.108464
- Maizlin ZV, Vos PM, Godoy MC, Cooperberg PL. Computer-aided detection of pulmonary embolism on CT angiography: initial experience. J Thorac Imaging. 2007 Nov;22(4):324–9. doi: 10.1097/RTI.0b013e31815b89ca. Erratum in: J Thorac Imaging. 2008 Feb;23(1):59. Godoy, Myrna B [corrected to Godoy, Myrna C].
- Wittenberg R, Peters JF, Sonnemans JJ, Prokop M, Schaefer-Prokop CM. Computer-assisted detection of pulmonary embolism: evaluation of pulmonary CT angiograms performed in an on-call setting. Eur Radiol. 2010 Apr;20(4):801–6. doi: 10.1007/s00330-009-1628-7
- Das M, Mühlenbruch G, Helm A, et al. Computer-aided detection of pulmonary embolism: influence on radiologists' detection performance with respect to vessel segments. Eur Radiol. 2008 Jul;18(7):1350–5. doi: 10.1007/s00330-008-0889-x
- Zhou C, Chan HP, Patel S, et al. Preliminary investigation of computer-aided detection of pulmonary embolism in three-dimensional computed tomography pulmonary angiography images. Acad Radiol. 2005 Jun;12(6):782–92. doi: 10.1016/j.acra.2005.01.014
- Ma X, Ferguson EC, Jiang X, Savitz SI, Shams S. A multitask deep learning approach for pulmonary embolism detection and identification. Sci Rep. 2022 Jul 29;12(1):13087. doi: 10.1038/s41598-022-16976-9
- Doğan K, Selçuk T, Alkan A. An Enhanced Mask R-CNN Approach for Pulmonary Embolism Detection and Segmentation. Diagnostics (Basel). 2024 May 26;14(11):1102. doi: 10.3390/diagnostics14111102
- Huhtanen H, Nyman M, Mohsen T, Virkki A, Karlsson A, Hirvonen J. Automated detection of pulmonary embolism from CT-angiograms using deep learning. BMC Med Imaging. 2022 Mar 14;22(1):43. doi: 10.1186/s12880-022-00763-z
- Long K, Tang L, Pu X, et al. Probability-based mask r-cnn for pulmonary embolism detection. Neurocomputing. 2021;422:345–353. doi: 10.1016/j.neucom.2020.10.022
- Kiourt C, Feretzakis G, Dalamarinis K, et al. Pulmonary embolism identification in computerized tomography pulmonary angiography scans with deep learning technologies in COVID-19 patients. arXiv:2105.11187 [Preprint]. 2021. Dataset: 673 images. Available from:
https://arxiv.org/abs/2105.11187 - Xu H, Li H, Xu Q, et al. Automatic detection of pulmonary embolism in computed tomography pulmonary angiography using Scaled-YOLOv4. Med Phys. 2023 Jul;50(7):4340–4350. doi: 10.1002/mp.16218
- Bushra F, Chowdhury MEH, Sarmun R, et al. Deep learning in computed tomography pulmonary angiography imaging: A dual-pronged approach for pulmonary embolism detection. Expert Systems with Applications. 2024;245:123029. doi: 10.1016/j.eswa.2023.123029
- Özkan H, Osman O, Şahin S, Boz AF. A novel method for pulmonary embolism detection in CTA images. Computer Methods and Programs in Biomedicine. 2014 Mar;113(3):757–66. doi: 10.1016/j.cmpb.2013.12.014
- Tajbakhsh N, Shin JY, Gotway MB, Liang J. Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. Med Image Anal. 2019 Dec;58:101541. doi: 10.1016/j.media.2019.101541
- Pu J, Gezer NS, Ren S, et al. Automated detection and segmentation of pulmonary embolisms on computed tomography pulmonary angiography (CTPA) using deep learning but without manual outlining. Med Image Anal. 2023 Oct;89:102882. doi: 10.1016/j.media.2023.102882
- Zhu H, Tao G, Jiang Y, et al. Automatic detection of pulmonary embolism on computed tomography pulmonary angiogram scan using a three-dimensional convolutional neural network. Eur J Radiol. 2024 Aug;177:111586. doi: 10.1016/j.ejrad.2024.111586
- Condrea F, Rapaka S, Leordeanu M. Label up: Learning pulmonary embolism segmentation from image level annotation through model explainability. arXiv:2412.07384 [Preprint]. 2024. Available from
https://arxiv.org/abs/2412.07384 - Aghayev A, Furlan A, Patil A, et al. The rate of resolution of clot burden measured by pulmonary CT angiography in patients with acute pulmonary embolism. AJR Am J Roentgenol. 2013 Apr;200(4):791–7. doi: 10.2214/AJR.12.8624
- Zhang H, Cheng Y, Chen Z, et al. Clot burden of acute pulmonary thromboembolism: comparison of two deep learning algorithms, Qanadli score, and Mastora score. Quant Imaging Med Surg. 2022 Jan;12(1):66–79. doi: 10.21037/qims-21-140
- Liu Z, Yuan H, Wang H. CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation. Med Phys. 2022 Aug;49(8):5294–5303. doi: 10.1002/mp.15719
- Cano-Espinosa C, Cazorla M, González G. Computer aided detection of pulmonary embolism using multi-slice multi-axial segmentation. Applied Sciences. 2020;10(8):2945. doi: 10.3390/app10082945
- Han J, He N, Zheng Q, Li L, Ma C. 3d pulmonary vessel segmentation based on improved residual attention u-net. Medicine in Novel Technology and Devices. 2023;20:100268. doi: 10.1016/j.medntd.2023.100268
- Olescki G, Clementin de Andrade JMC, Escuissato DL, Oliveira LF. A two step workflow for pulmonary embolism detection using deep learning and feature extraction. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 2023;11(3):341–350. doi: 10.1080/21681163.2022.2060866
- Furlan A, Aghayev A, Chang CC, et al. Short-term mortality in acute pulmonary embolism: clot burden and signs of right heart dysfunction at CT pulmonary angiography. Radiology. 2012 Oct;265(1):283–93. doi: 10.1148/radiol.12110802
- Shen C, Yu N, Wen L, et al. Risk stratification of acute pulmonary embolism based on the clot volume and right ventricular dysfunction on CT pulmonary angiography. Clin Respir J. 2019 Nov;13(11):674–682. doi: 10.1111/crj.13064
- Huang WM, Wu WJ, Yang SH, et al. Quantitative volumetric computed tomography embolic analysis, the Qanadli score, biomarkers, and clinical prognosis in patients with acute pulmonary embolism. Sci Rep. 2022 May 10;12(1):7620. doi: 10.1038/s41598-022-11812-6
- Medrek S, Safdar Z. Epidemiology and Pathophysiology of Chronic Thromboembolic Pulmonary Hypertension: Risk Factors and Mechanisms. Methodist Debakey Cardiovasc J. 2016 Oct–Dec;12(4):195–198. doi: 10.14797/mdcj-12-4-195
- Ende-Verhaar YM, Cannegieter SC, Vonk Noordegraaf A, et al. Incidence of chronic thromboembolic pulmonary hypertension after acute pulmonary embolism: a contemporary view of the published literature. Eur Respir J. 2017 Feb 23;49(2):1601792. doi: 10.1183/13993003.01792-2016