Literature DB >> 25559231

Dynamic Contrast-enhanced MR Imaging Curve-type Analysis: Is It Helpful in the Differentiation of Prostate Cancer from Healthy Peripheral Zone?

Barry G Hansford1, Yahui Peng, Yulei Jiang, Michael W Vannier, Tatjana Antic, Stephen Thomas, Stephanie McCann, Aytekin Oto.   

Abstract

PURPOSE: To evaluate the performance and interobserver agreement of qualitative dynamic contrast material enhanced magnetic resonance (MR) imaging curve analysis as described in the Prostate Imaging Reporting and Data System (PI-RADS) for the differentiation of prostate cancer (PCa) from healthy prostatic tissue in the peripheral zone (PZ).
MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act-compliant institutional review board-approved retrospective analysis included 120 consecutive pretreatment dynamic contrast-enhanced (DCE) MR imaging PCa examinations. Regions of interest (ROIs) were placed in 251 spots, including 95 (37.8%) in healthy PZ tissue and 156 (62.2%) in PCa, by using detailed histologic-multiparametric MR correlation review. Three radiologists reviewed the DCE time curves and assessed qualitative curve types as described in PI-RADS: type 1 (progressive), type 2 (plateau), or type 3 (washout). Receiver operating characteristic curve analysis was used to assess accuracy in differentiating PCa from healthy tissue on the basis of curve type, and κ was calculated to assess interobserver agreement.
RESULTS: Receiver operating characteristic curves were similar for all observers, but mean areas under the receiver operating characteristic curve were poor (0.58 ± 0.04 [standard deviation] to 0.63 ± 0.04). No differences in accuracy were seen for varying DCE time resolution and imaging length. Observer agreement in assessment of type 3 versus types 1 or 2 curves was substantial (0.66 < κ < 0.79), better for PCa ROIs than for healthy-tissue ROIs. The agreement between type 1 and type 2 curves was moderate to substantial (0.49 < κ < 0.78).
CONCLUSION: Qualitative DCE MR imaging time-curve-type analysis performs poorly for differentiation of PCa from healthy prostatic tissue. Interobserver agreement is excellent in assessment of type 3 curves but only moderate for type 1 and 2 curves. (©) RSNA, 2015.

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Year:  2015        PMID: 25559231     DOI: 10.1148/radiol.14140847

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  22 in total

1.  Multiparametric MRI Features and Pathologic Outcome of Wedge-Shaped Lesions in the Peripheral Zone on T2-Weighted Images of the Prostate.

Authors:  Aritrick Chatterjee; Sevil Tokdemir; Alexander J Gallan; Ambereen Yousuf; Tatjana Antic; Gregory S Karczmar; Aytekin Oto
Journal:  AJR Am J Roentgenol       Date:  2018-11-07       Impact factor: 3.959

2.  PIRADS 2.0: what is new?

Authors:  Baris Turkbey; Peter L Choyke
Journal:  Diagn Interv Radiol       Date:  2015 Sep-Oct       Impact factor: 2.630

3.  Role of MRI for the detection of prostate cancer.

Authors:  Richard C Wu; Amir H Lebastchi; Boris A Hadaschik; Mark Emberton; Caroline Moore; Pilar Laguna; Jurgen J Fütterer; Arvin K George
Journal:  World J Urol       Date:  2021-01-04       Impact factor: 4.226

4.  Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations?

Authors:  Daniel Junker; Fabian Steinkohl; Veronika Fritz; Jasmin Bektic; Theodoros Tokas; Friedrich Aigner; Thomas R W Herrmann; Michael Rieger; Udo Nagele
Journal:  World J Urol       Date:  2018-08-04       Impact factor: 4.226

5.  Contrast-ing opinions: biparametric versus multiparametric prostate MRI.

Authors:  Tristan Barrett
Journal:  Diagn Interv Radiol       Date:  2016 May-Jun       Impact factor: 2.630

Review 6.  PI-RADS v2: Current standing and future outlook.

Authors:  Clayton P Smith; Barış Türkbey
Journal:  Turk J Urol       Date:  2018-05-01

7.  A direct comparison of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging for prostate cancer detection and prediction of aggressiveness.

Authors:  Alexander D J Baur; Julia Schwabe; Julian Rogasch; Andreas Maxeiner; Tobias Penzkofer; Carsten Stephan; Marc Rudl; Bernd Hamm; Ernst-Michael Jung; Thom Fischer
Journal:  Eur Radiol       Date:  2017-12-13       Impact factor: 5.315

8.  Diagnostic performance of multi-parametric MRI to differentiate benign sex cord stromal tumors from malignant (non-stromal and stromal) testicular neoplasms.

Authors:  Maneesh Khanna; Abdul Rahman Abualruz; Santosh K Yadav; Mustafa Mafraji; Khalid Al-Rumaihi; Issam Al-Bozom; Devendra Kumar; Athina C Tsili; Nicola Schieda
Journal:  Abdom Radiol (NY)       Date:  2020-06-22

Review 9.  Prostate imaging reporting and data system version 2 (PI-RADS v2): a pictorial review.

Authors:  Elmira Hassanzadeh; Daniel I Glazer; Ruth M Dunne; Fiona M Fennessy; Mukesh G Harisinghani; Clare M Tempany
Journal:  Abdom Radiol (NY)       Date:  2017-01

Review 10.  Functional MR Imaging Techniques in Oncology in the Era of Personalized Medicine.

Authors:  Matthias R Benz; Hebert Alberto Vargas; Evis Sala
Journal:  Magn Reson Imaging Clin N Am       Date:  2015-09-26       Impact factor: 2.266

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