Literature DB >> 28438871

Multiparametric MRI Apparent Diffusion Coefficient (ADC) Accuracy in Diagnosing Clinically Significant Prostate Cancer.

Pietro Pepe1, Davide D'Urso2, Antonio Garufi3, Giandomenico Priolo3, Michele Pennisi1, Giorgio Russo4, Maria Gabriella Sabini5, Lucia Maria Valastro5, Antonio Galia6, Filippo Fraggetta6.   

Abstract

AIM: To evaluate the accuracy of multiparametric magnetic resonance imaging apparent diffusion coefficient (mpMRI ADC) in the diagnosis of clinically significant prostate cancer (PCa). PATIENTS AND METHODS: From January 2016 to December 2016, 44 patients who underwent radical prostatectomy for PCa and mpMRI lesions suggestive of cancer were retrospectively evaluated at definitive specimen. The accuracy of suspicious mpMRI prostate imaging reporting and data system (PI-RADS ≥3) vs. ADC values in the diagnosis of Gleason score ≥7 was evaluated.
RESULTS: Receiver operating characteristics (ROC) curve analysis gave back an ADC threshold of 0.747×10-3 mm2/s to separate between Gleason Score 6 and ≥7. The diagnostic accuracy of ADC value (cut-off 0.747×10-3 mm2/s) vs. PI-RADS score ≥3 in diagnosing PCa with Gleason score ≥7 was equal to 84% vs. 63.6% with an area under the curve (AUC) ROC of 0.81 vs. 0.71, respectively.
CONCLUSION: ADC evaluation could support clinicians in decision making of patients with PI-RADS score <3 at risk for PCa. Copyright
© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Entities:  

Keywords:  Multiparametric MRI and prostate cancer; apparent diffusion coefficient (ADC); diffusion-weighted imaging (DWI)

Mesh:

Year:  2017        PMID: 28438871      PMCID: PMC5461453          DOI: 10.21873/invivo.11075

Source DB:  PubMed          Journal:  In Vivo        ISSN: 0258-851X            Impact factor:   2.155


  20 in total

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2.  Utility of computed diffusion-weighted MRI for predicting aggressiveness of prostate cancer.

Authors:  Yuma Waseda; Soichiro Yoshida; Taro Takahara; Thomas Christian Kwee; Yoh Matsuoka; Kazutaka Saito; Kazunori Kihara; Yasuhisa Fujii
Journal:  J Magn Reson Imaging       Date:  2017-02-02       Impact factor: 4.813

3.  Risk stratification of prostate cancer utilizing apparent diffusion coefficient value and lesion volume on multiparametric MRI.

Authors:  Simpa S Salami; Eran Ben-Levi; Oksana Yaskiv; Baris Turkbey; Robert Villani; Ardeshir R Rastinehad
Journal:  J Magn Reson Imaging       Date:  2016-07-13       Impact factor: 4.813

4.  Incremental value of high b value diffusion-weighted magnetic resonance imaging at 3-T for prediction of extracapsular extension in patients with prostate cancer: preliminary experience.

Authors:  Ayumu Kido; Tsutomu Tamada; Teruki Sone; Naoki Kanomata; Yoshiyuki Miyaji; Akira Yamamoto; Katsuyoshi Ito
Journal:  Radiol Med       Date:  2016-12-09       Impact factor: 3.469

5.  The Prevalence of Clinically Significant Prostate Cancer According to Commonly Used Histological Thresholds in Men Undergoing Template Prostate Mapping Biopsies.

Authors:  M Valerio; C Anele; S R J Bott; S C Charman; J van der Meulen; H El-Mahallawi; A M Emara; A Freeman; C Jameson; R G Hindley; B S I Montgomery; P B Singh; H U Ahmed; M Emberton
Journal:  J Urol       Date:  2015-11-26       Impact factor: 7.450

6.  Diffusion-weighted endorectal MR imaging at 3T for prostate cancer: correlation with tumor cell density and percentage Gleason pattern on whole mount pathology.

Authors:  Daniel I Glazer; Elmira Hassanzadeh; Andriy Fedorov; Olutayo I Olubiyi; Shayna S Goldberger; Tobias Penzkofer; Trevor A Flood; Paul Masry; Robert V Mulkern; Michelle S Hirsch; Clare M Tempany; Fiona M Fennessy
Journal:  Abdom Radiol (NY)       Date:  2017-03

7.  Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer.

Authors:  Thomas Hambrock; Diederik M Somford; Henkjan J Huisman; Inge M van Oort; J Alfred Witjes; Christina A Hulsbergen-van de Kaa; Thomas Scheenen; Jelle O Barentsz
Journal:  Radiology       Date:  2011-05       Impact factor: 11.105

8.  Prostate cancer detection with magnetic resonance-ultrasound fusion biopsy: The role of systematic and targeted biopsies.

Authors:  Christopher P Filson; Shyam Natarajan; Daniel J A Margolis; Jiaoti Huang; Patricia Lieu; Frederick J Dorey; Robert E Reiter; Leonard S Marks
Journal:  Cancer       Date:  2016-01-07       Impact factor: 6.860

9.  Correlation of Gleason scores with diffusion-weighted imaging findings of prostate cancer.

Authors:  Rajakumar Nagarajan; Daniel Margolis; Steven Raman; Ke Sheng; Christopher King; Robert Reiter; M Albert Thomas
Journal:  Adv Urol       Date:  2011-12-15

10.  Predicting biochemical recurrence in patients with high-risk prostate cancer using the apparent diffusion coefficient of magnetic resonance imaging.

Authors:  Min Young Yoon; Juhyun Park; Jeong Yeon Cho; Chang Wook Jeong; Ja Hyeon Ku; Hyeon Hoe Kim; Cheol Kwak
Journal:  Investig Clin Urol       Date:  2017-01-09
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  5 in total

1.  Quantitative characterisation of clinically significant intra-prostatic cancer by prostate-specific membrane antigen (PSMA) expression and cell density on PSMA-11.

Authors:  Liran Domachevsky; Natalia Goldberg; Hanna Bernstine; Meital Nidam; David Groshar
Journal:  Eur Radiol       Date:  2018-05-30       Impact factor: 5.315

2.  Prostate cancer GTV delineation with biparametric MRI and 68Ga-PSMA-PET: comparison of expert contours and semi-automated methods.

Authors:  Nathan Hearn; John Blazak; Philip Vivian; Dinesh Vignarajah; Katelyn Cahill; Daisy Atwell; Jim Lagopoulos; Myo Min
Journal:  Br J Radiol       Date:  2021-01-28       Impact factor: 3.039

3.  DW-MRI for esophageal squamous cell carcinoma, correlations between ADC values with histologic differentiation and VEGF expression: A retrospective study.

Authors:  Qingxue Cong; Guang Li; Yongfeng Wang; Shanguo Zhang; Hao Zhang
Journal:  Oncol Lett       Date:  2019-01-15       Impact factor: 2.967

4.  MRI Radiomics in Prostate Cancer: A Reliability Study.

Authors:  Fabrizio Urraro; Valerio Nardone; Alfonso Reginelli; Carlo Varelli; Antonio Angrisani; Vittorio Patanè; Luca D'Ambrosio; Pietro Roccatagliata; Gaetano Maria Russo; Luigi Gallo; Marco De Chiara; Lucia Altucci; Salvatore Cappabianca
Journal:  Front Oncol       Date:  2021-12-21       Impact factor: 6.244

5.  Radio-pathomic mapping model generated using annotations from five pathologists reliably distinguishes high-grade prostate cancer.

Authors:  Sean D McGarry; John D Bukowy; Kenneth A Iczkowski; Allison K Lowman; Michael Brehler; Samuel Bobholz; Andrew Nencka; Alex Barrington; Kenneth Jacobsohn; Jackson Unteriner; Petar Duvnjak; Michael Griffin; Mark Hohenwalter; Tucker Keuter; Wei Huang; Tatjana Antic; Gladell Paner; Watchareepohn Palangmonthip; Anjishnu Banerjee; Peter S LaViolette
Journal:  J Med Imaging (Bellingham)       Date:  2020-09-09
  5 in total

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