Literature DB >> 33188560

Synthetic MRI: Technologies and Applications in Neuroradiology.

Sooyeon Ji1, Dongjin Yang2, Jongho Lee1, Seung Hong Choi1,3,4, Hyeonjin Kim4, Koung Mi Kang4.   

Abstract

Synthetic MRI is a technique that synthesizes contrast-weighted images from multicontrast MRI data. There have been advances in synthetic MRI since the technique was introduced. Although a number of synthetic MRI methods have been developed for quantifying one or more relaxometric parameters and for generating multiple contrast-weighted images, this review focuses on several methods that quantify all three relaxometric parameters (T1 , T2 , and proton density) and produce multiple contrast-weighted images. Acquisition, quantification, and image synthesis techniques are discussed for each method. We discuss the image quality and diagnostic accuracy of synthetic MRI methods and their clinical applications in neuroradiology. Based on this analysis, we highlight areas that need to be addressed for synthetic MRI to be widely implemented in the clinic. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.
© 2020 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  image synthesis; neuroradiology; quantification; relaxometry; synthetic MRI

Mesh:

Year:  2020        PMID: 33188560     DOI: 10.1002/jmri.27440

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  9 in total

1.  Simultaneous T1 -weighted and T2 -weighted 3D MRI using RF phase-modulated gradient echo imaging.

Authors:  Daiki Tamada; Aaron S Field; Scott B Reeder
Journal:  Magn Reson Med       Date:  2021-11-09       Impact factor: 4.668

2.  Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer.

Authors:  Lidi Ma; Shanshan Lian; Huimin Liu; Tiebao Meng; Weilong Zeng; Rui Zhong; Linchang Zhong; Chuanmiao Xie
Journal:  Quant Imaging Med Surg       Date:  2022-07

3.  Ultrafast lumbar spine MRI protocol using deep learning-based reconstruction: diagnostic equivalence to a conventional protocol.

Authors:  Masahiro Fujiwara; Nobuo Kashiwagi; Chisato Matsuo; Hitoshi Watanabe; Yoshimori Kassai; Atsushi Nakamoto; Noriyuki Tomiyama
Journal:  Skeletal Radiol       Date:  2022-10-01       Impact factor: 2.128

Review 4.  Pediatric magnetic resonance imaging: faster is better.

Authors:  Sebastian Gallo-Bernal; M Alejandra Bedoya; Michael S Gee; Camilo Jaimes
Journal:  Pediatr Radiol       Date:  2022-10-20

5.  The Preoperative Diagnostic Performance of Multi-Parametric Quantitative Assessment in Rectal Carcinoma: A Preliminary Study Using Synthetic Magnetic Resonance Imaging.

Authors:  Kexin Zhu; Zhicheng Chen; Lingling Cui; Jinli Zhao; Yi Liu; Jibin Cao
Journal:  Front Oncol       Date:  2022-05-25       Impact factor: 5.738

6.  Clinical adaptation of synthetic MRI-based whole brain volume segmentation in children at 3 T: comparison with modified SPM segmentation methods.

Authors:  So Mi Lee; Eunji Kim; Sun Kyoung You; Hyun-Hae Cho; Moon Jung Hwang; Myong-Hun Hahm; Seung Hyun Cho; Won Hwa Kim; Hye Jung Kim; Kyung Min Shin; Byunggeon Park; Yongmin Chang
Journal:  Neuroradiology       Date:  2021-08-12       Impact factor: 2.804

7.  Acceleration of Magnetic Resonance Fingerprinting Reconstruction Using Denoising and Self-Attention Pyramidal Convolutional Neural Network.

Authors:  Jia-Sheng Hong; Ingo Hermann; Frank Gerrit Zöllner; Lothar R Schad; Shuu-Jiun Wang; Wei-Kai Lee; Yung-Lin Chen; Yu Chang; Yu-Te Wu
Journal:  Sensors (Basel)       Date:  2022-02-07       Impact factor: 3.576

8.  Qualitative and Quantitative Performance of Magnetic Resonance Image Compilation (MAGiC) Method: An Exploratory Analysis for Head and Neck Imaging.

Authors:  Amaresha Shridhar Konar; Ramesh Paudyal; Akash Deelip Shah; Maggie Fung; Suchandrima Banerjee; Abhay Dave; Nancy Lee; Vaios Hatzoglou; Amita Shukla-Dave
Journal:  Cancers (Basel)       Date:  2022-07-26       Impact factor: 6.575

9.  Synthetic MRI improves radiomics-based glioblastoma survival prediction.

Authors:  Elisa Moya-Sáez; Rafael Navarro-González; Santiago Cepeda; Ángel Pérez-Núñez; Rodrigo de Luis-García; Santiago Aja-Fernández; Carlos Alberola-López
Journal:  NMR Biomed       Date:  2022-05-21       Impact factor: 4.478

  9 in total

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