Literature DB >> 11442457

Prostatic MR imaging. Accuracy in differentiating cancer from other prostatic disorders.

S Ikonen1, L Kivisaari, P Tervahartiala, T Vehmas, K Taari, S Rannikko.   

Abstract

PURPOSE: We assessed the accuracy of MR imaging in differentiating between cancer and other prostatic disorders, and evaluated the diagnostic criteria for various prostatic diseases.
MATERIAL AND METHODS: A total of 74 endorectal coil MR studies were performed on 72 patients. Twenty patients had prostatic cancer, 20 benign prostatic hyperplasia (BPH), 4 acute bacterial prostatitis, 5 chronic bacterial prostatitis (2 also belonging to the previous category), 19 chronic non-bacterial prostatitis/chronic pelvic pain syndrome, and 6 were symptomless voluntary controls. All studies were interpreted by two experienced radiologists in random order. Radiologists were blinded to all clinical data including the age of the patients. Based on MR findings, both radiologists filled in a form covering diagnostic criteria and diagnosis.
RESULTS: Accuracy in diagnosing prostate cancer was 74%. Sensitivity was 50% and specificity 83%, and positive and negative predictive values were 53 and 82%, respectively. Bacterial prostatitis showed some features similar to carcinoma. Abundant BPH rendered cancer detection more difficult. No diagnostic criterion was clearly better than the others. Interobserver agreement on the MR diagnosis ranged from moderate to good.
CONCLUSION: Without knowledge of accurate clinical data, MR seems to be too insensitive in detecting prostate cancer to be used as a primary diagnostic tool.

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Year:  2001        PMID: 11442457     DOI: 10.1080/028418501127346972

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.701


  18 in total

Review 1.  Perspectives for preventive screening with total body MRI.

Authors:  Susanne C Ladd; Mark E Ladd
Journal:  Eur Radiol       Date:  2007-06-05       Impact factor: 5.315

2.  Diffusion tensor imaging of the normal prostate at 3 Tesla.

Authors:  Bengi Gürses; Neslihan Kabakci; Arzu Kovanlikaya; Zeynep Firat; Ali Bayram; Aziz Müfit Uluğ; Aziz Müfit Uluo; Ilhami Kovanlikaya
Journal:  Eur Radiol       Date:  2007-10-25       Impact factor: 5.315

3.  Determination of the cutoff level of apparent diffusion coefficient values for detection of prostate cancer.

Authors:  Masako Nagayama; Yuji Watanabe; Akito Terai; Tohru Araki; Kenji Notohara; Akira Okumura; Yoshiki Amoh; Takayoshi Ishimori; Satoru Nakashita; Yoshihiro Dodo
Journal:  Jpn J Radiol       Date:  2011-09-01       Impact factor: 2.374

Review 4.  Multiparametric MRI in prostate cancer management.

Authors:  Linda M Johnson; Baris Turkbey; William D Figg; Peter L Choyke
Journal:  Nat Rev Clin Oncol       Date:  2014-05-20       Impact factor: 66.675

5.  Are histopathological features of prostate cancer lesions associated with identification of extracapsular extension on magnetic resonance imaging?

Authors:  Liang Wang; Oguz Akin; Yousef Mazaheri; Nicole M Ishill; Kentaro Kuroiwa; Jingbo Zhang; Hedvig Hricak
Journal:  BJU Int       Date:  2010-11       Impact factor: 5.588

Review 6.  Imaging prostate cancer: an update on positron emission tomography and magnetic resonance imaging.

Authors:  Kirsten Bouchelouche; Baris Turkbey; Peter Choyke; Jacek Capala
Journal:  Curr Urol Rep       Date:  2010-05       Impact factor: 3.092

7.  3D proton MR spectroscopic imaging of prostate cancer using a standard spine coil at 1.5 T in clinical routine: a feasibility study.

Authors:  Matthias P Lichy; Jörg Pintaske; Raimund Kottke; Jürgen Machann; Aristotelis Anastasiadis; Stefan Roell; Jörg Hennenlotter; Till Diergarten; Fritz Schick; Arnulf Stenzl; Claus D Claussen; Heinz-Peter Schlemmer
Journal:  Eur Radiol       Date:  2004-12-31       Impact factor: 5.315

Review 8.  Imaging techniques for prostate cancer: implications for focal therapy.

Authors:  Baris Turkbey; Peter A Pinto; Peter L Choyke
Journal:  Nat Rev Urol       Date:  2009-04       Impact factor: 14.432

9.  In vivo MRI based prostate cancer localization with random forests and auto-context model.

Authors:  Chunjun Qian; Li Wang; Yaozong Gao; Ambereen Yousuf; Xiaoping Yang; Aytekin Oto; Dinggang Shen
Journal:  Comput Med Imaging Graph       Date:  2016-02-27       Impact factor: 4.790

10.  A meta-analysis of the accuracy of prostate cancer studies which use magnetic resonance spectroscopy as a diagnostic tool.

Authors:  Peng Wang; You-min Guo; Min Liu; Yong-qian Qiang; Xiao-juan Guo; Yi-li Zhang; Xiao-Yi Duan; Qiu-Juan Zhang; Weifeng Liang
Journal:  Korean J Radiol       Date:  2008 Sep-Oct       Impact factor: 3.500

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