Literature DB >> 24059373

Utility of diffusional kurtosis imaging as a marker of adverse pathologic outcomes among prostate cancer active surveillance candidates undergoing radical prostatectomy.

Andrew B Rosenkrantz1, Vinay Prabhu, Eric E Sigmund, James S Babb, Fang-Ming Deng, Samir S Taneja.   

Abstract

OBJECTIVE: The purpose of this study was to compare findings at nongaussian diffusional kurtosis imaging and conventional diffusion-weighted MRI as markers of adverse pathologic outcomes among prostate cancer patients who are active surveillance candidates and choose to undergo prostatectomy.
MATERIALS AND METHODS: Fifty-eight active surveillance candidates (prostate-specific antigen concentration, < 10 ng/mL; clinical tumor category less than T2a; Gleason score, 3 + 3; ≤ 25% of biopsy cores positive for tumor; ≤ 50% tumor involvement of any individual core; ≤ 20% tumor involvement across all cores) who underwent prostatectomy and preoperative 3-T MRI including diffusional kurtosis imaging (b values, 0, 500, 1000, 1500, and 2000 s/mm(2)) were included. Adverse pathologic features at prostatectomy were defined using two schemes of varying stringency. One scheme (less stringent) was presence of a Gleason score greater than 6 or extracapsular extension (n = 19). The other scheme (more stringent) was presence of a Gleason score greater than 6, extracapsular extension, or an index tumor 10 mm or larger (n = 35). Parametric maps displaying standard apparent diffusion coefficient (ADC), kurtosis (K) representing nongaussian diffusion behavior, and diffusion (D) representing a diffusion coefficient adjusted for nongaussian (kurtosis) behavior were reviewed, and the most abnormal region was recorded for each metric. Associations between these metrics and the presence of adverse final pathologic findings were assessed with unpaired Student t tests and receiver operating characteristic analyses.
RESULTS: For both schemes, only D was significantly lower in patients with adverse final pathologic findings (p = 0.006, p = 0.025). K tended to be greater in patients with adverse final pathologic findings for the more stringent scheme (p = 0.072). ADC was not significantly different in the presence of adverse final pathologic findings for either scheme (p = 0.357, p = 0.383). With either scheme, D had a larger area under the receiver operating characteristics curve (AUC) for predicting adverse final pathologic results (AUC, 0.691 and 0.743) than did ADC (AUC, 0.569 and 0.655) or K (AUC, 0.617 and 0.714), but the difference was not significant (p = 0.183, p = 0.734).
CONCLUSION: Preliminary results suggest that diffusional kurtosis imaging findings may have more value than findings at conventional diffusion-weighted MRI as a marker of adverse final pathologic outcome among active surveillance candidates.

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Year:  2013        PMID: 24059373     DOI: 10.2214/AJR.12.10397

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  15 in total

1.  Updates in advanced diffusion-weighted magnetic resonance imaging techniques in the evaluation of prostate cancer.

Authors:  Hebert Alberto Vargas; Edward Malnor Lawrence; Yousef Mazaheri; Evis Sala
Journal:  World J Radiol       Date:  2015-08-28

2.  Diffusion-weighted magnetic resonance imaging for prediction of insignificant prostate cancer in potential candidates for active surveillance.

Authors:  Tae Heon Kim; Jae Yong Jeong; Sin Woo Lee; Chan Kyo Kim; Byung Kwan Park; Hyun Hwan Sung; Hwang Gyun Jeon; Byong Chang Jeong; Seong Il Seo; Hyun Moo Lee; Han Yong Choi; Seong Soo Jeon
Journal:  Eur Radiol       Date:  2015-01-31       Impact factor: 5.315

3.  Management of prostate cancer: NYU Case of the Month, July 2017.

Authors:  Samir S Taneja
Journal:  Rev Urol       Date:  2017

4.  Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer.

Authors:  Jing Wang; Chen-Jiang Wu; Mei-Ling Bao; Jing Zhang; Xiao-Ning Wang; Yu-Dong Zhang
Journal:  Eur Radiol       Date:  2017-04-03       Impact factor: 5.315

Review 5.  Diffusion and quantification of diffusion of prostate cancer.

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Journal:  Br J Radiol       Date:  2021-09-19       Impact factor: 3.039

6.  Functional magnetic resonance imaging for distinguishing type of papillary renal cell carcinoma: a preliminary study.

Authors:  Qingqiang Zhu; Jing Ye; Wenrong Zhu; Jingtao Wu; Wenxin Chen; Jun Ling
Journal:  Br J Radiol       Date:  2021-09-07       Impact factor: 3.629

7.  Longitudinal evaluation of apparent diffusion coefficient values as a predictor of Prostate Cancer Research International Active Surveillance reclassification.

Authors:  Eri Ota; Naoko Mori; Shinichi Yamashita; Shunji Mugikura; Akihiro Ito; Kei Takase
Journal:  Abdom Radiol (NY)       Date:  2021-12-09

Review 8.  The expanding landscape of diffusion-weighted MRI in prostate cancer.

Authors:  Andreas G Wibmer; Evis Sala; Hedvig Hricak; Hebert Alberto Vargas
Journal:  Abdom Radiol (NY)       Date:  2016-05

9.  Characterization of breast tumors using diffusion kurtosis imaging (DKI).

Authors:  Dongmei Wu; Guanwu Li; Junxiang Zhang; Shixing Chang; Jiani Hu; Yongming Dai
Journal:  PLoS One       Date:  2014-11-18       Impact factor: 3.240

10.  Evaluating Prostate Cancer Using Fractional Tissue Composition of Radical Prostatectomy Specimens and Pre-Operative Diffusional Kurtosis Magnetic Resonance Imaging.

Authors:  Edward M Lawrence; Anne Y Warren; Andrew N Priest; Tristan Barrett; Debra A Goldman; Andrew B Gill; Vincent J Gnanapragasam; Evis Sala; Ferdia A Gallagher
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

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