Literature DB >> 27193792

Evaluation of the impact of computed high b-value diffusion-weighted imaging on prostate cancer detection.

Sadhna Verma1, Saradwata Sarkar2, Jason Young3, Rajesh Venkataraman2, Xu Yang2, Anil Bhavsar3, Nilesh Patil4, James Donovan4, Krishnanath Gaitonde4.   

Abstract

PURPOSE: The purpose of this study was to compare high b-value (b = 2000 s/mm(2)) acquired diffusion-weighted imaging (aDWI) with computed DWI (cDWI) obtained using four diffusion models-mono-exponential (ME), intra-voxel incoherent motion (IVIM), stretched exponential (SE), and diffusional kurtosis (DK)-with respect to lesion visibility, conspicuity, contrast, and ability to predict significant prostate cancer (PCa).
METHODS: Ninety four patients underwent 3 T MRI including acquisition of b = 2000 s/mm(2) aDWI and low b-value DWI. High b = 2000 s/mm(2) cDWI was obtained using ME, IVIM, SE, and DK models. All images were scored on quality independently by three radiologists. Lesions were identified on all images and graded for lesion conspicuity. For a subset of lesions for which pathological truth was established, lesion-to-background contrast ratios (LBCRs) were computed and binomial generalized linear mixed model analysis was conducted to compare clinically significant PCa predictive capabilities of all DWI.
RESULTS: For all readers and all models, cDWI demonstrated higher ratings for image quality and lesion conspicuity than aDWI except DK (p < 0.001). The LBCRs of ME, IVIM, and SE were significantly higher than LBCR of aDWI (p < 0.001). Receiver Operating Characteristic curves obtained from binomial generalized linear mixed model analysis demonstrated higher Area Under the Curves for ME, SE, IVIM, and aDWI compared to DK or PSAD alone in predicting significant PCa.
CONCLUSION: High b-value cDWI using ME, IVIM, and SE diffusion models provide better image quality, lesion conspicuity, and increased LBCR than high b-value aDWI. Using cDWI can potentially provide comparable sensitivity and specificity for detecting significant PCa as high b-value aDWI without increased scan times and image degradation artifacts.

Entities:  

Keywords:  Diffusional kurtosis model; High b-value diffusion-weighted imaging; IVIM model; Mono-exponential model; Prostate cancer; Stretched exponential model

Mesh:

Substances:

Year:  2016        PMID: 27193792     DOI: 10.1007/s00261-015-0619-1

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  8 in total

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Authors:  Xiangsheng Li; Ping Wang; Dechang Li; Hongxian Zhu; Limin Meng; Yunlong Song; Lizhi Xie; Jianping Zhu; Tao Yu
Journal:  Eur Radiol       Date:  2017-12-08       Impact factor: 5.315

Review 2.  Computed Diffusion-Weighted Imaging in Prostate Cancer: Basics, Advantages, Cautions, and Future Prospects.

Authors:  Yoshiko R Ueno; Tsutomu Tamada; Satoru Takahashi; Utaru Tanaka; Keitaro Sofue; Tomonori Kanda; Munenobu Nogami; Yoshiharu Ohno; Nobuyuki Hinata; Masato Fujisawa; Takamichi Murakami
Journal:  Korean J Radiol       Date:  2018-08-06       Impact factor: 3.500

3.  Comparison of Computed and Acquired DWI in the Assessment of Rectal Cancer: Image Quality and Preoperative Staging.

Authors:  Yihan Xia; Lan Wang; Zhiyuan Wu; Jingwen Tan; Meng Fu; Caixia Fu; Zilai Pan; Lan Zhu; Fuhua Yan; Hailin Shen; Qianchen Ma; Gang Cai
Journal:  Front Oncol       Date:  2022-03-18       Impact factor: 6.244

4.  AutoProstate: Towards Automated Reporting of Prostate MRI for Prostate Cancer Assessment Using Deep Learning.

Authors:  Pritesh Mehta; Michela Antonelli; Saurabh Singh; Natalia Grondecka; Edward W Johnston; Hashim U Ahmed; Mark Emberton; Shonit Punwani; Sébastien Ourselin
Journal:  Cancers (Basel)       Date:  2021-12-06       Impact factor: 6.639

5.  Improved Visualization of Prostate Cancer Using Multichannel Computed Diffusion Images: Combining ADC and DWI.

Authors:  Matthias Hammon; Marc Saake; Frederik B Laun; Rafael Heiss; Nicola Seuss; Rolf Janka; Alexander Cavallaro; Michael Uder; Hannes Seuss
Journal:  Diagnostics (Basel)       Date:  2022-06-30

6.  Feasibility Study of Synthetic Diffusion-Weighted MRI in Patients with Breast Cancer in Comparison with Conventional Diffusion-Weighted MRI.

Authors:  Bo Hwa Choi; Hye Jin Baek; Ji Young Ha; Kyeong Hwa Ryu; Jin Il Moon; Sung Eun Park; Kyungsoo Bae; Kyung Nyeo Jeon; Eun Jung Jung
Journal:  Korean J Radiol       Date:  2020-09       Impact factor: 3.500

7.  Image quality and diagnostic value of diffusion-weighted breast magnetic resonance imaging: Comparison of acquired and computed images.

Authors:  Hye Shin Ahn; Sung Hun Kim; Ji Youn Kim; Chang Suk Park; Robert Grimm; Yohan Son
Journal:  PLoS One       Date:  2021-02-22       Impact factor: 3.240

Review 8.  Prostate MRI quality: a critical review of the last 5 years and the role of the PI-QUAL score.

Authors:  Francesco Giganti; Veeru Kasivisvanathan; Alex Kirkham; Shonit Punwani; Mark Emberton; Caroline M Moore; Clare Allen
Journal:  Br J Radiol       Date:  2021-07-08       Impact factor: 3.039

  8 in total

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