Literature DB >> 26220861

Diffusion-weighted imaging of prostate cancer: effect of b-value distribution on repeatability and cancer characterization.

Harri Merisaari1, Jussi Toivonen2, Marko Pesola3, Pekka Taimen4, Peter J Boström5, Tapio Pahikkala6, Hannu J Aronen7, Ivan Jambor8.   

Abstract

PURPOSE: To evaluate the effect of b-value distribution on the repeatability and Gleason score (GS) prediction of prostate cancer (PCa).
METHODS: Fifty PCa patients underwent two repeated 3T diffusion-weighted imaging (DWI) examinations using 12 b values in the range from 0 to 2000s/mm(2) and diffusion time of 20.3ms. Mean signal intensities of regions of interest, placed in PCa using whole mount prostatectomy sections as the reference, were fitted using monoexponential, kurtosis, stretched exponential, and biexponential models. In total, 4083 different b-value combinations consisting of 2 to 12 b values were evaluated. Repeatability was assessed by intraclass correlation coefficient, ICC(3,1), and coefficient of repeatability (CoR). Areas under receiver operating characteristic curve (AUCs) for PCa characterization were estimated while the correlation of the fitted values with GS groups (3+3, 3+4, >3+4) was evaluated by using the Spearman correlation coefficient (ρ).
RESULTS: The parameters of monoexponential, kurtosis, and stretched exponential models estimated using only 4-5, 5-7, 5-7 b values, respectively, had similar ICC(3,1), CoR, AUC, and ρ values as the parameters estimated using all 12 b values. Optimized b-value distributions demonstrated improved ICC(3,1) and CoR values but failed to improve AUC and ρ values. The parameters of biexponential model demonstrated the worst repeatability and diagnostic performance.
CONCLUSION: B-value distribution influences mainly the repeatability of DWI-derived parameters rather than the diagnostic performance.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Diffusion-weighted imaging; Gleason score; Intraclass correlation coefficient; Prostate cancer; Repeatability; b values

Mesh:

Year:  2015        PMID: 26220861     DOI: 10.1016/j.mri.2015.07.004

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  13 in total

1.  Preliminary study of diffusion kurtosis imaging in thyroid nodules and its histopathologic correlation.

Authors:  Ruo-Yang Shi; Qiu-Ying Yao; Qin-Yi Zhou; Qing Lu; Shi-Teng Suo; Jun Chen; Wen-Jie Zheng; Yong-Ming Dai; Lian-Ming Wu; Jian-Rong Xu
Journal:  Eur Radiol       Date:  2017-06-14       Impact factor: 5.315

2.  Prospective evaluation of 18F-FACBC PET/CT and PET/MRI versus multiparametric MRI in intermediate- to high-risk prostate cancer patients (FLUCIPRO trial).

Authors:  Ivan Jambor; Anna Kuisma; Esa Kähkönen; Jukka Kemppainen; Harri Merisaari; Olli Eskola; Jarmo Teuho; Ileana Montoya Perez; Marko Pesola; Hannu J Aronen; Peter J Boström; Pekka Taimen; Heikki Minn
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-11-16       Impact factor: 9.236

3.  Contribution of mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging in the diagnosis and differentiation of uterine cervical carcinoma.

Authors:  Meng Lin; Xiaoduo Yu; Yan Chen; Han Ouyang; Bing Wu; Dandan Zheng; Chunwu Zhou
Journal:  Eur Radiol       Date:  2016-09-27       Impact factor: 5.315

4.  Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps.

Authors:  Amogh Hiremath; Rakesh Shiradkar; Harri Merisaari; Prateek Prasanna; Otto Ettala; Pekka Taimen; Hannu J Aronen; Peter J Boström; Ivan Jambor; Anant Madabhushi
Journal:  Eur Radiol       Date:  2020-07-23       Impact factor: 5.315

5.  Tournament leave-pair-out cross-validation for receiver operating characteristic analysis.

Authors:  Ileana Montoya Perez; Antti Airola; Peter J Boström; Ivan Jambor; Tapio Pahikkala
Journal:  Stat Methods Med Res       Date:  2018-08-20       Impact factor: 3.021

6.  Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer.

Authors:  EunJu Kim; Chan Kyo Kim; Hyun Soo Kim; Dong Pyo Jang; In Young Kim; Jinwoo Hwang
Journal:  Br J Radiol       Date:  2020-01-09       Impact factor: 3.039

7.  Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer.

Authors:  Harri Merisaari; Pekka Taimen; Rakesh Shiradkar; Otto Ettala; Marko Pesola; Jani Saunavaara; Peter J Boström; Anant Madabhushi; Hannu J Aronen; Ivan Jambor
Journal:  Magn Reson Med       Date:  2019-11-08       Impact factor: 4.668

8.  Parameter Estimation Error Dependency on the Acquisition Protocol in Diffusion Kurtosis Imaging.

Authors:  Nima Gilani; Paul N Malcolm; Glyn Johnson
Journal:  Appl Magn Reson       Date:  2016-09-17       Impact factor: 0.831

9.  Evaluation of different mathematical models and different b-value ranges of diffusion-weighted imaging in peripheral zone prostate cancer detection using b-value up to 4500 s/mm2.

Authors:  Zhaoyan Feng; Xiangde Min; Daniel J A Margolis; Caohui Duan; Yuping Chen; Vivek Kumar Sah; Nabin Chaudhary; Basen Li; Zan Ke; Peipei Zhang; Liang Wang
Journal:  PLoS One       Date:  2017-02-15       Impact factor: 3.240

Review 10.  Optimization of prostate MRI acquisition and post-processing protocol: a pictorial review with access to acquisition protocols.

Authors:  Ivan Jambor
Journal:  Acta Radiol Open       Date:  2017-12-08
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