[1]兰贝蒂 王瑞涛.人工智能及3D打印技术在心血管疾病诊疗中的应用进展[J].心血管病学进展,2021,(4):292-296.[doi:10.16806/j.cnki.issn.1004-3934.2021.04.002]
 LAN Beidi,WANG Ruitao.Application Progress of Artificial Intelligence and 3D Printing Technology in the Diagnosis and Treatment of Cardiovascular Diseases[J].Advances in Cardiovascular Diseases,2021,(4):292-296.[doi:10.16806/j.cnki.issn.1004-3934.2021.04.002]
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人工智能及3D打印技术在心血管疾病诊疗中的应用进展()
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《心血管病学进展》[ISSN:51-1187/R/CN:1004-3934]

卷:
期数:
2021年4期
页码:
292-296
栏目:
综述
出版日期:
2021-04-25

文章信息/Info

Title:
Application Progress of Artificial Intelligence and 3D Printing Technology in the Diagnosis and Treatment of Cardiovascular Diseases
作者:
兰贝蒂1 王瑞涛 2
1.西安交通大学第一附属医院结构性心脏病科,陕西 西安 7100612.西安交通大学第一附属医院肝胆外科,陕西 西安 710061)
Author(s):
LAN Beidi1WANG Ruitao2
(1.Department of Structural Heart Disease,The First Affiliated Hospital of Xi’an Jiaotong University,Xi’an 710061,Shanxi,China2. Department of Hepatobiliary Surgery ,The First Affiliated Hospital of Xi’an Jiaotong University,Xi’an 710061,Shanxi,China)
关键词:
心血管疾病人工智能3D打印
Keywords:
Cardiovascular diseaseArtificial intelligence3D printing technology
DOI:
10.16806/j.cnki.issn.1004-3934.2021.04.002
摘要:
在大数据和开放科学时代,人工智能和3D打印技术蓬勃发展,其在心血管医学领域的探索应用突飞猛进。现代影像及检验技术积累了充分的原始数据,是人工智能探索的基础;心血管系统腔内结构复杂多变,充分利用人工智能和3D打印技术可以革新当前诊疗习惯和模式,提升服务效率和水平。现就人工智能技术和3D打印技术在心血管医学领域的应用进展做一综述。
Abstract:
In the era of big data and open science,artificial intelligence and 3D printing technology are booming,and their application in the field of cardiovascular disease is growing. Modern imaging and inspection technology has accumulated sufficient raw data,which is the basis of artificial intelligence exploration. On the other hand,the intracavitary structure of the cardiovascular system is complex and variable. Utilize of artificial intelligence and 3D printing technology can innovate current diagnosis and treatment habits and models,and improve service efficiency and level. This article reviews the application progress of artificial intelligence and 3D printing technology in the field of cardiovascular disease.

参考文献/References:




[1] Topol EJ. High-performance medicine:the convergence of human and artificial intelligence[J]. Nat Med,2019,25(1):44-56.

[2] Esteva A,Robicquet A,Ramsundar B,et al. A guide to deep learning in healthcare[J]. Nat Med,2019,25(1):24-29.

[3] Krittanawong C,Zhang H,Wang Z,et al. Artificial intelligence in precision?cardiovascular medicine[J]. J Am Coll Cardiol,2017,69(21):2657-2664.

[4] Lopez-Jimenez F,Attia Z,Arruda-Olson AM,et al. Artificial intelligence in cardiology:present and future[J]. Mayo Clin Proc,2020,95(5):1015-1039.

[5] Avendi MR,Kheradvar A,Jafarkhani H. A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI[J]. Med Image Anal,2016,30:108-119.

[6] Narula S,Shameer K,Salem Omar AM,et al. Machine learning algorithms to automate morphological and functional assessments in 2d echocardiography[J]. J Am Coll Cardiol,2016,68(21):2287-2295.

[7] Hannun AY,Rajpurkar P,Haghpanahi M,et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network[J]. Nat Med,2019,25(1):65-69.

[8] Attia ZI,Kapa S,Lopez-Jimenez F,et al. Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram[J]. Nat Med,2019,25(1):70-74.

[9] Martin G,Anton G,Borut B,et al. Machine learning and End-to-End deep learning for the detection of chronic heart failure from heart sounds[J]. IEEE Access,2020,8:20313-20324.

[10] Lin S,Li Z,Fu B,et al. Feasibility of using deep learning to detect coronary artery disease based on facial photo[J]. Eur Heart J,2020,41(46):4400-4411.

[11] Yan BP,Lai W,Chan C,et al. High-throughput,contact-free detection of atrial fibrillation from video with deep learning[J]. JAMA Cardiol,2019,5(1):105-107.

[12] Diller GP,Kempny A,Babu-Narayan SV,et al. Machine learning algorithms estimating prognosis and guiding therapy in adult congenital heart disease:data from a single tertiary centre including 10019 patients[J]. Eur Heart J,2019,40(13):1069-1077.

[13] Zack CJ,Senecal C,Kinar Y,et al. Leveraging machine learning techniques to forecast patient prognosis after percutaneous coronary intervention[J]. JACC Cardiovasc Interv,2019,12(14):1304-1311.

[14] Cikes M,Sanchez-Martinez S,Claggett B,et al. Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy[J]. Eur J Heart Fail,2019,21(1):74-85.

[15] Kakadiaris IA,Vrigkas M,Yen AA,et al. Machine learning outperforms ACC/AHA CVD risk calculator in MESA[J]. J Am Heart Assoc,2018,7(22):e009476.

[16] Arruda-Olson AM,Afzal N,Priya Mallipeddi V,et al. Leveraging the electronic health record to create an automated real-time prognostic tool for peripheral arterial disease[J]. J Am Heart Assoc,2018,7(23):e009680.

[17] Green A. Outcomes of congenital heart disease:a review[J]. Pediatr Nurs,2004,30:280-284.

[18] Pace DF,Dalca AV,Geva T,et al. Interactive whole-heart segmentation in congenital heart disease[J]. Med Image Comput Comput Assist Interv,2015,9351:80-88.

[19] Anwar S, Singh GK, Miller J,et al. 3D printing is a transformative technology in congenital heart disease[J].JACC Basic Transl Sci,2018,3(2):294-312.

[20] Yoo JS,Reddy YNV,Kim KH. Heart transplantation for dextrocardia:preoperative planning using 3D printing[J]. Eur Heart J Cardiovasc Imaging,2020,21(3):346.

[21] Anwar S,Singh GK,Varughese J,et al. 3D printing in complex congenital heart?disease:across a spectrum of age,pathology,and imaging?techniques[J]. JACC Cardiovasc Imaging,2017,10(8):953-956.

[22] Stepanenko A,Redondo Diéguez A,di Stefano S,et al. 3D-printing for planning an intrapericardial ventricular assist device placement in case of complex anatomy[J]. Eur Heart J Cardiovasc Imaging,2020,21(7):821.

[23] Colbert CM,Shao J,Hollowed JJ,et al. 3D-Printed coronary implants are effective for percutaneous creation of swine models with focal coronary stenosis[J]. J Cardiovasc Transl Res,202013(6):1033-1043.

[24] So CY,Fan Y,Wu EB,et al. Anticipating coronary obstruction with three-dimensional printing in transcatheter aortic valve implantation[J]. EuroIntervention,2020,15(16):1424-1425.

[25] El Sabbagh A, Eleid MF, Matsumoto JM,et al.?Three-dimensional prototyping for procedural simulation of transcatheter mitral valve replacement in patients with mitral annular calcification[J].Catheter Cardiovasc Interv,2018,92(7):E537-E549.

[26] Hansen JH, Duong P, Jivanji SGM,et al. Transcatheter correction of superior sinus venosus atrial septal defects as an alternative to surgical treatment[J]. JACC,2020,75(11):1266-1278.

[27] Yan CW,Wang C,Pan XB,et al. Three-dimensional printing assisted transcatheter closure of atrial septal defect with deficient posterior-inferior rim[J]. Catheter Cardiovasc Interv,2018,92(7):1309-1314.

[28] Chaowu Y,Hua L,Xin S. Three-dimensional printing as an aid in transcatheter closure of secundum atrial septal defect with rim deficiency:in vitro trial occlusion based on a personalized heart model[J]. Circulation,2016,133(17):e608-610.

[29] Bhatla P,Mosca RS,Tretter JT. Altering management decisions with gained anatomical insight from a 3D printed model of a complex ventricular septal defect[J]. Cardiol Young,2017,27(2):377-380.

[30] Robinson SS, Alaie S, Sidoti H,et al. Patient-specific design of a soft occluder for the left atrial appendage[J]. Nat Biomed Eng,2018,2(1):8-16.

[31] Wang C,Zhang L,Qin T,et al. 3D printing in adult cardiovascular surgery and interventions:a systematic review[J]. J Thorac Dis,2020,12(6):3227-3237.

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备注/Memo

备注/Memo:
通信作者:王瑞涛,E-mail:wruitao2008@163.com 收稿日期:2020-09-07
更新日期/Last Update: 2021-07-01