Literature DB >> 25547670

Characterization of prostate cancer using T2 mapping at 3T: a multi-scanner study.

A Hoang Dinh1, R Souchon1, C Melodelima2, F Bratan3, F Mège-Lechevallier4, M Colombel5, O Rouvière6.   

Abstract

RATIONALE AND
OBJECTIVES: To assess the prostate T2 value as a predictor of malignancy on two different 3T scanners. PATIENTS AND METHODS: Eighty-three pre-prostatectomy multiparametric MRIs were retrospectively evaluated [67 obtained on a General Electric MRI (scanner 1) and 16 on a Philips MRI (scanner 2)]. After correlation with prostatectomy specimens, readers measured the T2 value of regions-of-interest categorized as "cancers", "false positive lesions", or "normal tissue".
RESULTS: On scanner 1, in PZ, cancers had significantly lower T2 values than false positive lesions (P=0.02) and normal tissue (P=2×10(-9)). Gleason≥6 cancers had similar T2 values than false positive lesions and significantly higher T2 values than Gleason≥7 cancers (P=0.009). T2 values corresponding to a 25% and 75% risk of Gleason≥7 malignancy were respectively 132 ms (95% CI: 129-135 ms) and 77 ms (95% CI: 74-81 ms). In TZ, cancers had significantly lower T2 values than normal tissue (P=0.008), but not than false positive findings. Mean T2 values measured on scanner 2 were not significantly different than those measured on scanner 1 for all tissue classes.
CONCLUSION: All tested tissue classes had similar mean T2 values on both scanners. In PZ, the T2 value was a significant predictor of Gleason≥7 cancers.
Copyright © 2014 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Prostate cancer; Prostate cancer aggressiveness; Prostate multiparametric MRI; T2

Mesh:

Year:  2014        PMID: 25547670     DOI: 10.1016/j.diii.2014.11.016

Source DB:  PubMed          Journal:  Diagn Interv Imaging        ISSN: 2211-5684            Impact factor:   4.026


  17 in total

1.  Performance of T2 Maps in the Detection of Prostate Cancer.

Authors:  Aritrick Chatterjee; Ajit Devaraj; Melvy Mathew; Teodora Szasz; Tatjana Antic; Gregory S Karczmar; Aytekin Oto
Journal:  Acad Radiol       Date:  2018-05-03       Impact factor: 3.173

Review 2.  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

3.  Fast and accurate compensation of signal offset for T2 mapping.

Authors:  Jan Michálek; Pavla Hanzlíková; Tuan Trinh; Dalibor Pacík
Journal:  MAGMA       Date:  2019-02-07       Impact factor: 2.310

4.  Development of a Combined MR Fingerprinting and Diffusion Examination for Prostate Cancer.

Authors:  Alice C Yu; Chaitra Badve; Lee E Ponsky; Shivani Pahwa; Sara Dastmalchian; Matthew Rogers; Yun Jiang; Seunghee Margevicius; Mark Schluchter; William Tabayoyong; Robert Abouassaly; Debra McGivney; Mark A Griswold; Vikas Gulani
Journal:  Radiology       Date:  2017-02-10       Impact factor: 11.105

5.  Characterization of gradient echo signal decays in healthy and cancerous prostate at 3T improves with a Gaussian augmentation of the mono-exponential (GAME) model.

Authors:  Pelin Aksit Ciris; Mukund Balasubramanian; Ravi T Seethamraju; Junichi Tokuda; Jonathan Scalera; Tobias Penzkofer; Fiona M Fennessy; Clare M Tempany-Afdhal; Kemal Tuncali; Robert V Mulkern
Journal:  NMR Biomed       Date:  2016-05-31       Impact factor: 4.044

6.  Development and validation of a logistic regression model to distinguish transition zone cancers from benign prostatic hyperplasia on multi-parametric prostate MRI.

Authors:  Yuji Iyama; Takeshi Nakaura; Kazuhiro Katahira; Ayumi Iyama; Yasunori Nagayama; Seitaro Oda; Daisuke Utsunomiya; Yasuyuki Yamashita
Journal:  Eur Radiol       Date:  2017-03-13       Impact factor: 5.315

7.  MR Fingerprinting and ADC Mapping for Characterization of Lesions in the Transition Zone of the Prostate Gland.

Authors:  Ananya Panda; Verena C Obmann; Wei-Ching Lo; Seunghee Margevicius; Yun Jiang; Mark Schluchter; Indravadan J Patel; Dean Nakamoto; Chaitra Badve; Mark A Griswold; Irina Jaeger; Lee E Ponsky; Vikas Gulani
Journal:  Radiology       Date:  2019-07-23       Impact factor: 11.105

Review 8.  Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications.

Authors:  Lizhi Liu; Zhiqiang Tian; Zhenfeng Zhang; Baowei Fei
Journal:  Acad Radiol       Date:  2016-04-25       Impact factor: 3.173

9.  Performance of a fast and high-resolution multi-echo spin-echo sequence for prostate T2 mapping across multiple systems.

Authors:  Petra J van Houdt; Harsh K Agarwal; Laurens D van Buuren; Stijn W T P J Heijmink; Søren Haack; Henk G van der Poel; Ghazaleh Ghobadi; Floris J Pos; Johannes M Peeters; Peter L Choyke; Uulke A van der Heide
Journal:  Magn Reson Med       Date:  2017-07-03       Impact factor: 4.668

10.  Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping.

Authors:  Ananya Panda; Gregory OʼConnor; Wei Ching Lo; Yun Jiang; Seunghee Margevicius; Mark Schluchter; Lee E Ponsky; Vikas Gulani
Journal:  Invest Radiol       Date:  2019-08       Impact factor: 6.016

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