Literature DB >> 25046482

Evaluation of different mathematical models for diffusion-weighted imaging of normal prostate and prostate cancer using high b-values: a repeatability study.

Ivan Jambor1, Harri Merisaari, Pekka Taimen, Peter Boström, Heikki Minn, Marko Pesola, Hannu J Aronen.   

Abstract

PURPOSE: To evaluate monoexponential, stretched exponential, kurtosis, and biexponential models for diffusion-weighted imaging (DWI) of normal prostate and prostate cancer (PCa), using b-values up to 2000 s/mm(2) , in terms of fitting quality and repeatability.
METHODS: Eight healthy volunteers and 16 PCa patients underwent a total of four repeated 3T DWI examinations using 16 and 12 b-values, respectively. The highest b-value was 2000 s/mm(2) . The normalized mean signal intensities of regions of interest, placed in normal tissue and PCa using anatomical images and prostatectomy sections, were fitted using the four models. The fitting quality was evaluated using Akaike information criteria and F-ratio. Repeatability of the fitted parameters was evaluated using intraclass correlation coefficient ICC(3,1).
RESULTS: The biexponential model provided the best fit to normal prostate and PCa DWI data. The parameters of the monoexponential, kurtosis, and stretched exponential (with the exception of the α parameter) models had higher ICC(3,1) values compared with the biexponential model. The kurtosis model provided a better fit to DWI data of normal prostate and PCa than the monoexponential model, whereas these models had comparable reliability and repeatability based on ICC(3,1) values.
CONCLUSION: Considering the model fit and repeatability, the kurtosis model seems to be the preferred model for characterization of normal prostate and PCa DWI using b-values up to 2000 s/mm(2) .
© 2014 Wiley Periodicals, Inc.

Entities:  

Keywords:  Akaike information criteria; diffusion-weighted imaging; intraclass correlation coefficient; normal prostate; prostate cancer; repeatability

Mesh:

Year:  2014        PMID: 25046482     DOI: 10.1002/mrm.25323

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  30 in total

1.  Evaluation of fitting models for prostate tissue characterization using extended-range b-factor diffusion-weighted imaging.

Authors:  Fredrik Langkilde; Thiele Kobus; Andriy Fedorov; Ruth Dunne; Clare Tempany; Robert V Mulkern; Stephan E Maier
Journal:  Magn Reson Med       Date:  2017-07-17       Impact factor: 4.668

2.  Comparison of methods for estimation of the intravoxel incoherent motion (IVIM) diffusion coefficient (D) and perfusion fraction (f).

Authors:  Oscar Jalnefjord; Mats Andersson; Mikael Montelius; Göran Starck; Anna-Karin Elf; Viktor Johanson; Johanna Svensson; Maria Ljungberg
Journal:  MAGMA       Date:  2018-08-16       Impact factor: 2.310

3.  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

4.  Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization.

Authors:  Jussi Toivonen; Ileana Montoya Perez; Parisa Movahedi; Harri Merisaari; Marko Pesola; Pekka Taimen; Peter J Boström; Jonne Pohjankukka; Aida Kiviniemi; Tapio Pahikkala; Hannu J Aronen; Ivan Jambor
Journal:  PLoS One       Date:  2019-07-08       Impact factor: 3.240

5.  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

6.  The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer.

Authors:  Yu-Dong Zhang; Qing Wang; Chen-Jiang Wu; Xiao-Ning Wang; Jing Zhang; Hui Liu; Xi-Sheng Liu; Hai-Bin Shi
Journal:  Eur Radiol       Date:  2014-11-28       Impact factor: 5.315

7.  Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

Authors:  Yanfen Cui; Xiaotang Yang; Xiaosong Du; Zhizheng Zhuo; Lei Xin; Xintao Cheng
Journal:  Eur Radiol       Date:  2017-10-23       Impact factor: 5.315

8.  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

9.  Diffusion kurtosis imaging (DKI) of hepatocellular carcinoma: correlation with microvascular invasion and histologic grade.

Authors:  Likun Cao; Jie Chen; Ting Duan; Min Wang; Hanyu Jiang; Yi Wei; Chunchao Xia; Xiaoyue Zhou; Xu Yan; Bin Song
Journal:  Quant Imaging Med Surg       Date:  2019-04

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.