Literature DB >> 24475824

Prostate cancer aggressiveness: assessment with whole-lesion histogram analysis of the apparent diffusion coefficient.

Olivio F Donati1, Yousef Mazaheri, Asim Afaq, Hebert A Vargas, Junting Zheng, Chaya S Moskowitz, Hedvig Hricak, Oguz Akin.   

Abstract

PURPOSE: To evaluate the relationship between prostate cancer aggressiveness and histogram-derived apparent diffusion coefficient (ADC) parameters obtained from whole-lesion assessment of diffusion-weighted magnetic resonance (MR) imaging of the prostate and to determine which ADC metric may help best differentiate low-grade from intermediate- or high-grade prostate cancer lesions.
MATERIALS AND METHODS: The institutional review board approved this retrospective HIPAA-compliant study of 131 men (median age, 60 years) who underwent diffusion-weighted MR imaging before prostatectomy for prostate cancer. Clinically significant tumors (tumor volume > 0.5 mL) were identified at whole-mount step-section histopathologic examination, and Gleason scores of the tumors were recorded. A volume of interest was drawn around each significant tumor on ADC maps. The mean, median, and 10th and 25th percentile ADCs were determined from the whole-lesion histogram and correlated with the Gleason score by using the Spearman correlation coefficient (ρ). The ability of each parameter to help differentiate tumors with a Gleason score of 6 from those with a Gleason score of at least 7 was assessed by using the area under the receiver operating characteristic curve (Az).
RESULTS: In total, 116 clinically significant lesions (89 in the peripheral zone, 27 in the transition zone) were identified in 85 of the 131 patients (65%). Forty-six patients did not have a clinically significant lesion. For mean ADC, median ADC, 10th percentile ADC, and 25th percentile ADC, the Spearman ρ values for correlation with Gleason score were -0.31, -0.30, -0.36, and -0.35, respectively, whereas the Az values for differentiating lesions with a Gleason score of 6 from those with a Gleason score of at least 7 were 0.704, 0.692, 0.758, and 0.723, respectively. The Az of 10th percentile ADC was significantly higher than that of the mean ADC for all lesions and peripheral zone lesions (P = .0001).
CONCLUSION: When whole-lesion histograms were used to derive ADC parameters, 10th percentile ADC correlated with Gleason score better than did other ADC parameters, suggesting that 10th percentile ADC may prove to be optimal for differentiating low-grade from intermediate- or high-grade prostate cancer with diffusion-weighted MR imaging. RSNA, 2013

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Year:  2013        PMID: 24475824     DOI: 10.1148/radiol.13130973

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


  93 in total

1.  Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: Preliminary results.

Authors:  Koji Sagiyama; Yuji Watanabe; Ryotaro Kamei; Sungtak Hong; Satoshi Kawanami; Yoshihiro Matsumoto; Hiroshi Honda
Journal:  Eur Radiol       Date:  2017-06-20       Impact factor: 5.315

2.  Intravoxel Incoherent Motion-derived Histogram Metrics for Assessment of Response after Combined Chemotherapy and Radiation Therapy in Rectal Cancer: Initial Experience and Comparison between Single-Section and Volumetric Analyses.

Authors:  Stephanie Nougaret; Hebert Alberto Vargas; Yulia Lakhman; Romain Sudre; Richard K G Do; Frederic Bibeau; David Azria; Eric Assenat; Nicolas Molinari; Marie-Ange Pierredon; Philippe Rouanet; Boris Guiu
Journal:  Radiology       Date:  2016-02-26       Impact factor: 11.105

3.  Assessment of Prostate Cancer Aggressiveness by Use of the Combination of Quantitative DWI and Dynamic Contrast-Enhanced MRI.

Authors:  Andreas M Hötker; Yousef Mazaheri; Ömer Aras; Junting Zheng; Chaya S Moskowitz; Tatsuo Gondo; Kazuhiro Matsumoto; Hedvig Hricak; Oguz Akin
Journal:  AJR Am J Roentgenol       Date:  2016-02-22       Impact factor: 3.959

4.  Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores.

Authors:  Andreas Wibmer; Hedvig Hricak; Tatsuo Gondo; Kazuhiro Matsumoto; Harini Veeraraghavan; Duc Fehr; Junting Zheng; Debra Goldman; Chaya Moskowitz; Samson W Fine; Victor E Reuter; James Eastham; Evis Sala; Hebert Alberto Vargas
Journal:  Eur Radiol       Date:  2015-05-21       Impact factor: 5.315

5.  Diagnostic value of semi-quantitative and quantitative analysis of functional parameters in multiparametric MRI of the prostate.

Authors:  Elke Hauth; Daniela Halbritter; Horst Jaeger; Horst Hohmuth; Meinrad Beer
Journal:  Br J Radiol       Date:  2017-07-27       Impact factor: 3.039

6.  Relationship between Gleason score and apparent diffusion coefficients of diffusion-weighted magnetic resonance imaging in prostate cancer patients.

Authors:  Tae Heon Kim; Chan Kyo Kim; Byung Kwan Park; Hwang Gyun Jeon; Byung Chang Jeong; Seong Il Seo; Hyun Moo Lee; Han Yong Choi; Seong Soo Jeon
Journal:  Can Urol Assoc J       Date:  2016-11-10       Impact factor: 1.862

7.  Pre-TACE kurtosis of ADCtotal derived from histogram analysis for diffusion-weighted imaging is the best independent predictor of prognosis in hepatocellular carcinoma.

Authors:  Li-Fang Wu; Sheng-Xiang Rao; Peng-Ju Xu; Li Yang; Cai-Zhong Chen; Hao Liu; Jian-Feng Huang; Cai-Xia Fu; Alice Halim; Meng-Su Zeng
Journal:  Eur Radiol       Date:  2018-06-19       Impact factor: 5.315

8.  Pituitary macroadenoma: Accuracy of apparent diffusion coefficient magnetic resonance imaging in grading tumor aggressiveness.

Authors:  Mariko Doai; Hisao Tonami; Munetaka Matoba; Osamu Tachibana; Hideaki Iizuka; Satoko Nakada; Sohuske Yamada
Journal:  Neuroradiol J       Date:  2019-01-16

Review 9.  Restriction spectrum imaging: An evolving imaging biomarker in prostate MRI.

Authors:  Ryan L Brunsing; Natalie M Schenker-Ahmed; Nathan S White; J Kellogg Parsons; Christopher Kane; Joshua Kuperman; Hauke Bartsch; Andrew Karim Kader; Rebecca Rakow-Penner; Tyler M Seibert; Daniel Margolis; Steven S Raman; Carrie R McDonald; Nikdokht Farid; Santosh Kesari; Donna Hansel; Ahmed Shabaik; Anders M Dale; David S Karow
Journal:  J Magn Reson Imaging       Date:  2016-08-16       Impact factor: 4.813

10.  Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images.

Authors:  Duc Fehr; Harini Veeraraghavan; Andreas Wibmer; Tatsuo Gondo; Kazuhiro Matsumoto; Herbert Alberto Vargas; Evis Sala; Hedvig Hricak; Joseph O Deasy
Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-02       Impact factor: 11.205

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