Literature DB >> 35419668

MR fingerprinting of the prostate.

Wei-Ching Lo1,2, Ananya Panda3, Yun Jiang4, James Ahad5, Vikas Gulani4, Nicole Seiberlich6,7.   

Abstract

Multiparametric magnetic resonance imaging (mpMRI) has been adopted as the key tool for detection, localization, characterization, and risk stratification of patients suspected to have prostate cancer. Despite advantages over systematic biopsy, the interpretation of prostate mpMRI has limitations including a steep learning curve, leading to considerable interobserver variation. There is growing interest in clinical translation of quantitative imaging techniques for more objective lesion assessment. However, traditional mapping techniques are slow, precluding their use in the clinic. Magnetic resonance fingerprinting (MRF) is an efficient approach for quantitative maps of multiple tissue properties simultaneously. The T1 and T2 values obtained with MRF have been validated with phantom studies as well as in normal volunteers and patients. Studies have shown that MRF-derived T1 and T2 along with ADC values are all significant independent predictors in the differentiation between normal prostate tissue and prostate cancer, and hold promise in differentiating low and intermediate/high-grade cancers. This review seeks to introduce the basics of the prostate MRF technique, discuss the potential applications of prostate MRF for the characterization of prostate cancer, and describes ongoing areas of research.
© 2022. The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB).

Entities:  

Keywords:  Magnetic resonance fingerprinting; Magnetic resonance imaging; Prostate; Quantitative imaging

Mesh:

Year:  2022        PMID: 35419668     DOI: 10.1007/s10334-022-01012-8

Source DB:  PubMed          Journal:  MAGMA        ISSN: 0968-5243            Impact factor:   2.533


  81 in total

Review 1.  Radiologist, be aware: ten pitfalls that confound the interpretation of multiparametric prostate MRI.

Authors:  Andrew B Rosenkrantz; Samir S Taneja
Journal:  AJR Am J Roentgenol       Date:  2014-01       Impact factor: 3.959

2.  Changes in Epithelium, Stroma, and Lumen Space Correlate More Strongly with Gleason Pattern and Are Stronger Predictors of Prostate ADC Changes than Cellularity Metrics.

Authors:  Aritrick Chatterjee; Geoffrey Watson; Esther Myint; Paul Sved; Mark McEntee; Roger Bourne
Journal:  Radiology       Date:  2015-06-23       Impact factor: 11.105

Review 3.  Multiparametric MRI for prostate cancer diagnosis: current status and future directions.

Authors:  Armando Stabile; Francesco Giganti; Andrew B Rosenkrantz; Samir S Taneja; Geert Villeirs; Inderbir S Gill; Clare Allen; Mark Emberton; Caroline M Moore; Veeru Kasivisvanathan
Journal:  Nat Rev Urol       Date:  2019-07-17       Impact factor: 14.432

Review 4.  The Evolution of MRI of the Prostate: The Past, the Present, and the Future.

Authors:  Francesco Giganti; Andrew B Rosenkrantz; Geert Villeirs; Valeria Panebianco; Armando Stabile; Mark Emberton; Caroline M Moore
Journal:  AJR Am J Roentgenol       Date:  2019-04-30       Impact factor: 3.959

5.  Reproducibility of dynamic contrast-enhanced MR imaging. Part I. Perfusion characteristics in the female pelvis by using multiple computer-aided diagnosis perfusion analysis solutions.

Authors:  Tobias Heye; Matthew S Davenport; Jeffrey J Horvath; Sebastian Feuerlein; Steven R Breault; Mustafa R Bashir; Elmar M Merkle; Daniel T Boll
Journal:  Radiology       Date:  2012-12-06       Impact factor: 11.105

6.  What You Need to Know Before Reading Multiparametric MRI for Prostate Cancer.

Authors:  Stephanie M Walker; Peter L Choyke; Baris Turkbey
Journal:  AJR Am J Roentgenol       Date:  2020-04-07       Impact factor: 3.959

Review 7.  The Current State of MR Imaging-targeted Biopsy Techniques for Detection of Prostate Cancer.

Authors:  Sadhna Verma; Peter L Choyke; Steven C Eberhardt; Aytekin Oto; Clare M Tempany; Baris Turkbey; Andrew B Rosenkrantz
Journal:  Radiology       Date:  2017-11       Impact factor: 11.105

8.  Reproducibility of dynamic contrast-enhanced MR imaging. Part II. Comparison of intra- and interobserver variability with manual region of interest placement versus semiautomatic lesion segmentation and histogram analysis.

Authors:  Tobias Heye; Elmar M Merkle; Caecilia S Reiner; Matthew S Davenport; Jeffrey J Horvath; Sebastian Feuerlein; Steven R Breault; Peter Gall; Mustafa R Bashir; Brian M Dale; Atilla P Kiraly; Daniel T Boll
Journal:  Radiology       Date:  2012-12-06       Impact factor: 11.105

9.  Magnetic resonance imaging for the detection, localisation, and characterisation of prostate cancer: recommendations from a European consensus meeting.

Authors:  Louise Dickinson; Hashim U Ahmed; Clare Allen; Jelle O Barentsz; Brendan Carey; Jurgen J Futterer; Stijn W Heijmink; Peter J Hoskin; Alex Kirkham; Anwar R Padhani; Raj Persad; Philippe Puech; Shonit Punwani; Aslam S Sohaib; Bertrand Tombal; Arnauld Villers; Jan van der Meulen; Mark Emberton
Journal:  Eur Urol       Date:  2010-12-21       Impact factor: 20.096

10.  Magnetic resonance fingerprinting.

Authors:  Dan Ma; Vikas Gulani; Nicole Seiberlich; Kecheng Liu; Jeffrey L Sunshine; Jeffrey L Duerk; Mark A Griswold
Journal:  Nature       Date:  2013-03-14       Impact factor: 49.962

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