Imaging in Interventional Radiology: 2043 and Beyond

被引:7
作者
Brock, Kristy K. [1 ]
Chen, Stephen R. [2 ]
Sheth, Rahul A. [2 ]
Siewerdsen, Jeffrey H. [1 ,3 ,4 ]
机构
[1] Univ Texas MD Anderson Canc Ctr, Dept Imaging Phys, 1400 Pressler St,FCT14 6050 Pickens Acad Tower, Houston, TX 77030 USA
[2] Univ Texas MD Anderson Canc Ctr, Dept Intervent Radiol, 1400 Pressler St,FCT14 6050 Pickens Acad Tower, Houston, TX 77030 USA
[3] Univ Texas MD Anderson Canc Ctr, Dept Neurosurg, 1400 Pressler St,FCT14 6050 Pickens Acad Tower, Houston, TX 77030 USA
[4] Univ Texas MD Anderson Canc Ctr, Dept Radiat Phys, 1400 Pressler St,FCT14 6050 Pickens Acad Tower, Houston, TX 77030 USA
关键词
ARTIFICIAL-INTELLIGENCE; CHALLENGES; ABLATION; PITFALLS;
D O I
10.1148/radiol.230146
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Since its inception in the early 20th century, interventional radiology (IR) has evolved tremendously and is now a distinct clinical discipline with its own training pathway. The arsenal of modalities at work in IR includes x-ray radiography and fluoroscopy, CT, MRI, US, and molecular and multimodality imaging within hybrid interventional environments. This article briefly reviews the major developments in imaging technology in IR over the past century, summarizes technologies now representative of the standard of care, and reflects on emerging advances in imaging technology that could shape the field in the century ahead. The role of emergent imaging technologies in enabling high-precision interventions is also briefly reviewed, including image-guided ablative therapies. (c) RSNA, 2023
引用
收藏
页数:10
相关论文
共 56 条
  • [1] COMPUTED TOMOGRAPHY OF THORAX AND ABDOMEN - PRELIMINARY REPORT
    ALFIDI, RJ
    HAAGA, J
    MEANEY, TF
    MACINTYRE, WJ
    GONZALEZ, L
    TARAR, R
    ZELCH, MG
    BOLLER, M
    COOK, SA
    JELDEN, G
    [J]. RADIOLOGY, 1975, 117 (02) : 257 - 264
  • [2] Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991-2020
    Alizadehsani, Roohallah
    Khosravi, Abbas
    Roshanzamir, Mohamad
    Abdar, Moloud
    Sarrafzadegan, Nizal
    Shafie, Davood
    Khozeimeh, Fahime
    Shoeibi, Afshin
    Nahavandi, Saeid
    Panahiazar, Maryam
    Bishara, Andrew
    Beygui, Ramin E.
    Puri, Rishi
    Kapadia, Samir
    Tan, Ru-San
    Acharya, U. Rajendra
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2021, 128
  • [3] Almansour H, 2023, RADIOLOGY, V308
  • [4] A novel use of biomechanical model-based deformable image registration (DIR) for assessing colorectal liver metastases ablation outcomes
    Anderson, Brian M.
    Lin, Yuan-Mao
    Lin, Ethan Y.
    Cazoulat, Guillaume
    Gupta, Sanjay
    Kyle Jones, A.
    Odisio, Bruno C.
    Brock, Kristy K.
    [J]. MEDICAL PHYSICS, 2021, 48 (10) : 6226 - 6236
  • [5] Initial Experience of Utilizing Real-Time Intra-Procedural PET/CT Biopsy
    Aparici, Carina Mari
    Aslam, Rizwan
    Win, Aung Zaw
    [J]. JOURNAL OF CLINICAL IMAGING SCIENCE, 2014, 4
  • [6] Beyer T, 2010, MAGNETOM FLASH, V3, P19
  • [7] Ultrasound-Guided Photoacoustic Imaging: Current State and Future Development
    Bouchard, Richard
    Sahin, Onur
    Emelianov, Stanislav
    [J]. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 2014, 61 (03) : 450 - 466
  • [8] Brooks Barney., 1924, JAMA, V82, P1016
  • [9] A survey on deep learning applied to medical images: from simple artificial neural networks to generative models
    Celard, P.
    Iglesias, E. L.
    Sorribes-Fdez, J. M.
    Romero, R.
    Vieira, A. Seara
    Borrajo, L.
    [J]. NEURAL COMPUTING & APPLICATIONS, 2023, 35 (03) : 2291 - 2323
  • [10] Wave-Encoded Model-Based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction
    Cho, Jaejin
    Gagoski, Borjan
    Kim, Tae Hyung
    Tian, Qiyuan
    Frost, Robert
    Chatnuntawech, Itthi
    Bilgic, Berkin
    [J]. BIOENGINEERING-BASEL, 2022, 9 (12):