Literature DB >> 15070262

Phantoms for texture analysis of MR images. Long-term and multi-center study.

Daniel Jirák1, Monika Dezortová, Milan Hájek.   

Abstract

The application of texture analysis (TA) in magnetic resonance imaging (MRI) requires the availability of texture phantoms for use in the standardization of in vivo measurements. The aims of our study were (a) to develop a new type of phantoms suitable for MRI and TA and test their long-term stability; (b) to optimize the choice of texture parameters describing the phantoms; (c) to compare different MR imagers according to texture parameters in a multi-center study. A long-term study performed at 4.7 T proved that the developed phantom based on polystyrene spheres and an agar gel solution is stable at least 12 months. This phantom, with nodular patterns, was found useful for the modeling of structural differences. The comparison of TA parameters at 4.7 and 7 T proved that the same parameters can be used for the separation of structures. The proposed algorithm of the selection of TA parameters shows that there exists a part of texture parameters which can be measured with high reproducibility (1-3%); on the other hand, their absolute values can differ by more than 30% if the textures differ. Results obtained from the multi-center study of whole body MR imagers show the wide variation in the misclassification rates at the different sites and point out the importance of the set up of MR sequences.

Entities:  

Mesh:

Substances:

Year:  2004        PMID: 15070262     DOI: 10.1118/1.1646231

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  12 in total

1.  Classification of suspicious lesions on prostate multiparametric MRI using machine learning.

Authors:  Deukwoo Kwon; Isildinha M Reis; Adrian L Breto; Yohann Tschudi; Nicole Gautney; Olmo Zavala-Romero; Christopher Lopez; John C Ford; Sanoj Punnen; Alan Pollack; Radka Stoyanova
Journal:  J Med Imaging (Bellingham)       Date:  2018-09-06

2.  Magnetic resonance imaging texture analysis classification of primary breast cancer.

Authors:  S A Waugh; C A Purdie; L B Jordan; S Vinnicombe; R A Lerski; P Martin; A M Thompson
Journal:  Eur Radiol       Date:  2015-06-12       Impact factor: 5.315

3.  Comparison Study of Myocardial Radiomics Feature Properties on Energy-Integrating and Photon-Counting Detector CT.

Authors:  Isabelle Ayx; Hishan Tharmaseelan; Alexander Hertel; Dominik Nörenberg; Daniel Overhoff; Lukas T Rotkopf; Philipp Riffel; Stefan O Schoenberg; Matthias F Froelich
Journal:  Diagnostics (Basel)       Date:  2022-05-23

Review 4.  Physical imaging phantoms for simulation of tumor heterogeneity in PET, CT, and MRI: An overview of existing designs.

Authors:  Alejandra Valladares; Thomas Beyer; Ivo Rausch
Journal:  Med Phys       Date:  2020-02-12       Impact factor: 4.071

5.  Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics.

Authors:  Alexandre Carré; Guillaume Klausner; Myriam Edjlali; Marvin Lerousseau; Jade Briend-Diop; Roger Sun; Samy Ammari; Sylvain Reuzé; Emilie Alvarez Andres; Théo Estienne; Stéphane Niyoteka; Enzo Battistella; Maria Vakalopoulou; Frédéric Dhermain; Nikos Paragios; Eric Deutsch; Catherine Oppenheim; Johan Pallud; Charlotte Robert
Journal:  Sci Rep       Date:  2020-07-23       Impact factor: 4.379

Review 6.  Magnetic resonance imaging (MRI)-based radiomics for prostate cancer radiotherapy.

Authors:  Fei Yang; John C Ford; Nesrin Dogan; Kyle R Padgett; Adrian L Breto; Matthew C Abramowitz; Alan Dal Pra; Alan Pollack; Radka Stoyanova
Journal:  Transl Androl Urol       Date:  2018-06

7.  Quantitative Radiomics: Impact of Pulse Sequence Parameter Selection on MRI-Based Textural Features of the Brain.

Authors:  John Ford; Nesrin Dogan; Lori Young; Fei Yang
Journal:  Contrast Media Mol Imaging       Date:  2018-07-30       Impact factor: 3.161

Review 8.  The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges.

Authors:  Zhenyu Liu; Shuo Wang; Di Dong; Jingwei Wei; Cheng Fang; Xuezhi Zhou; Kai Sun; Longfei Li; Bo Li; Meiyun Wang; Jie Tian
Journal:  Theranostics       Date:  2019-02-12       Impact factor: 11.556

9.  Influence of Magnetic Field Strength on Magnetic Resonance Imaging Radiomics Features in Brain Imaging, an In Vitro and In Vivo Study.

Authors:  Samy Ammari; Stephanie Pitre-Champagnat; Laurent Dercle; Emilie Chouzenoux; Salma Moalla; Sylvain Reuze; Hugues Talbot; Tite Mokoyoko; Joya Hadchiti; Sebastien Diffetocq; Andreas Volk; Mickeal El Haik; Sara Lakiss; Corinne Balleyguier; Nathalie Lassau; Francois Bidault
Journal:  Front Oncol       Date:  2021-01-20       Impact factor: 6.244

Review 10.  The application of texture quantification in hepatocellular carcinoma using CT and MRI: a review of perspectives and challenges.

Authors:  Ismail Bilal Masokano; Wenguang Liu; Simin Xie; Dama Faniriantsoa Henrio Marcellin; Yigang Pei; Wenzheng Li
Journal:  Cancer Imaging       Date:  2020-09-22       Impact factor: 3.909

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.