Literature DB >> 22371381

Clinical utility of apparent diffusion coefficient values obtained using high b-value when diagnosing prostate cancer using 3 tesla MRI: comparison between ultra-high b-value (2000 s/mm²) and standard high b-value (1000 s/mm²).

Kazuhiro Kitajima1, Satoru Takahashi, Yoshiko Ueno, Takeshi Yoshikawa, Yoshiharu Ohno, Makoto Obara, Hideaki Miyake, Masato Fujisawa, Kazuro Sugimura.   

Abstract

PURPOSE: To determine whether the apparent diffusion coefficient (ADC) obtained using b = 2000 s/mm(2) upon 3 Tesla (T) diffusion-weighted MRI is superior to b = 1000 s/mm(2) for discriminating malignant from normal prostate tissue and predicting the aggressiveness of prostate cancer, using histopathological findings of radical prostatectomy as a reference.
MATERIALS AND METHODS: Eighty prostate cancer patients underwent preoperative 3T MRI including diffusion weighted imaging with b-values of 0, 1000, and 2000 s/mm(2) . ADCs were measured for malignant lesions and normal sites on three sets of ADC maps calculated with monoexponential fitting between b = 0 and 1000, 0 and 2000, and 1000 and 2000, respectively. The relationship between the ADC and Gleason score was evaluated.
RESULTS: The areas under the ROC curves for b = 0,1000, b = 0,2000, and b = 1000,2000 were 0.896, 0.937, and 0.857, respectively, in the peripheral zone (PZ) and 0.877, 0.889, and 0.731, respectively, in the transition zone (TZ). The difference between b = 0,1000 and b = 0,2000 was significant in PZ (P = 0.033), but not in TZ (P = 0.84). Weak but significant negative correlations were identified between ADCs and Gleason score in both PZ and TZ cancer at b = 0,1000 and b = 0,2000 (r = -0.323 to -0.341).
CONCLUSION: For 3T MRI, ADCs using b = 0,2000 are more accurate than b = 0,1000 for diagnosing PZ cancer, and as accurate for TZ cancer.
Copyright © 2012 Wiley Periodicals, Inc.

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Mesh:

Year:  2012        PMID: 22371381     DOI: 10.1002/jmri.23627

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


  22 in total

1.  Computed diffusion-weighted imaging using 3-T magnetic resonance imaging for prostate cancer diagnosis.

Authors:  Yoshiko Ueno; Satoru Takahashi; Kazuhiro Kitajima; Tokunori Kimura; Ikuo Aoki; Fumi Kawakami; Hideaki Miyake; Yoshiharu Ohno; Kazuro Sugimura
Journal:  Eur Radiol       Date:  2013-07-25       Impact factor: 5.315

2.  Computed diffusion-weighted imaging of the prostate at 3 T: impact on image quality and tumour detection.

Authors:  Andrew B Rosenkrantz; Hersh Chandarana; Nicole Hindman; Fang-Ming Deng; James S Babb; Samir S Taneja; Christian Geppert
Journal:  Eur Radiol       Date:  2013-06-12       Impact factor: 5.315

3.  Apparent diffusion coefficient maps obtained from high b value diffusion-weighted imaging in the preoperative evaluation of gliomas at 3T: comparison with standard b value diffusion-weighted imaging.

Authors:  Qiang Zeng; Fei Dong; Feina Shi; Chenhan Ling; Biao Jiang; Jianmin Zhang
Journal:  Eur Radiol       Date:  2017-06-21       Impact factor: 5.315

4.  Automated prostate cancer detection using T2-weighted and high-b-value diffusion-weighted magnetic resonance imaging.

Authors:  Jin Tae Kwak; Sheng Xu; Bradford J Wood; Baris Turkbey; Peter L Choyke; Peter A Pinto; Shijun Wang; Ronald M Summers
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

5.  Potential of hybrid ¹⁸F-fluorocholine PET/MRI for prostate cancer imaging.

Authors:  Thomas de Perrot; Olivier Rager; Max Scheffler; Martin Lord; Marc Pusztaszeri; Christophe Iselin; Osman Ratib; Jean-Paul Vallee
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-05-20       Impact factor: 9.236

6.  Diffusion-weighted imaging of the prostate: should we use quantitative metrics to better characterize focal lesions originating in the peripheral zone?

Authors:  Thibaut Pierre; Francois Cornud; Loïc Colléter; Frédéric Beuvon; Frantz Foissac; Nicolas B Delongchamps; Paul Legmann
Journal:  Eur Radiol       Date:  2017-11-22       Impact factor: 5.315

Review 7.  Prostate cancer detection and diagnosis: the role of MR and its comparison with other diagnostic modalities--a radiologist's perspective.

Authors:  Tobias Penzkofer; Clare M Tempany-Afdhal
Journal:  NMR Biomed       Date:  2013-09-03       Impact factor: 4.044

Review 8.  Current role of multiparametric magnetic resonance imaging for prostate cancer.

Authors:  Romaric Loffroy; Olivier Chevallier; Morgan Moulin; Sylvain Favelier; Pierre-Yves Genson; Pierre Pottecher; Gilles Crehange; Alexandre Cochet; Luc Cormier
Journal:  Quant Imaging Med Surg       Date:  2015-10

Review 9.  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

10.  Estimation of optimal b-value sets for obtaining apparent diffusion coefficient free from perfusion in non-small cell lung cancer.

Authors:  Kishor Karki; Geoffrey D Hugo; John C Ford; Kathryn M Olsen; Siddharth Saraiya; Robert Groves; Elisabeth Weiss
Journal:  Phys Med Biol       Date:  2015-09-25       Impact factor: 3.609

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