Literature DB >> 30599864

Repeatability of diffusion-weighted MRI of the prostate using whole lesion ADC values, skew and histogram analysis.

Tristan Barrett1, Edward M Lawrence2, Andrew N Priest3, Anne Y Warren4, Vincent J Gnanapragasam5, Ferdia A Gallagher6, Evis Sala6.   

Abstract

PURPOSE: To investigate the repeatability of diffusion-weighted imaging parameter including ADC-derived histogram values in prostate cancer.
METHODS: 10 patients with prostate cancer were prospectively recruited to a retest cohort. 3 T diffusion-weighted MRI of the prostate was acquired consecutively with patient getting off the scanner between studies. Prostatectomy-histopathology defined tumour regions-of-interest were outlined on ADC maps and diffusion-weighted metrics including histograms were calculated. The coefficient of reproducibility (CoR) and Bland-Altman plots were used to assess repeatability.
RESULTS: 10th centile, 90th centile, and median ADC showed good repeatability with mean difference ranging from -0.005 to -0.025 × 103 mm2s-1, and CoR ranging from 0.271-0.294 × 103 mm2s-1 of scan 1 mean). Two measures of heterogeneity and simplified texture, IQR and mean local range, had only moderate repeatability. IQR had a mean difference of -0.032 × 103 mm2s-1 between scans with CoR 0.181 × 103 mm2s-1 (56% of scan 1 mean). Mean local range had a mean difference -0.008 × 103 mm2s-1 between scans (37% of scan 1 mean). Bland-Altman plots showed good repeatability for test and re-test analysis for median, percentile and mean range values. All ADC values had good reliability regardless of whether the tumour border was included in quantitative analysis. ADC histogram skew had poor repeatability, CoR 0.78 × 103 mm2s-1 (373% of scan 1 mean).
CONCLUSION: 10th and 90th centile ADC demonstrated sufficient repeatability for clinical use. However, more advanced measures of heterogeneity such as histogram skew, IQR, or mean local range may be limited by their repeatability.
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Magnetic resonance imaging; Prostate cancer diffusion; Reproducibility of results

Mesh:

Year:  2018        PMID: 30599864     DOI: 10.1016/j.ejrad.2018.11.014

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  12 in total

Review 1.  [Diffusion-weighted imaging-diagnostic supplement or alternative to contrast agents in early detection of malignancies?]

Authors:  S Bickelhaupt; C Dreher; F König; K Deike-Hofmann; D Paech; H P Schlemmer; T A Kuder
Journal:  Radiologe       Date:  2019-06       Impact factor: 0.635

2.  Accelerating Prostate Diffusion-weighted MRI Using a Guided Denoising Convolutional Neural Network: Retrospective Feasibility Study.

Authors:  Elena A Kaye; Emily A Aherne; Cihan Duzgol; Ida Häggström; Erich Kobler; Yousef Mazaheri; Maggie M Fung; Zhigang Zhang; Ricardo Otazo; Hebert A Vargas; Oguz Akin
Journal:  Radiol Artif Intell       Date:  2020-08-26

3.  Semi-automatic quantitative analysis of the pelvic bony structures on apparent diffusion coefficient maps based on deep learning: establishment of reference ranges.

Authors:  Xiang Liu; Chao Han; Ziying Lin; Zhaonan Sun; Yaofeng Zhang; Xiangpeng Wang; Xiaodong Zhang; Xiaoying Wang
Journal:  Quant Imaging Med Surg       Date:  2022-01

4.  Whole tumor volumetric ADC analysis: relationships with histopathological differentiation of hepatocellular carcinoma.

Authors:  Ferhat Can Piskin; Huseyin Tugsan Balli; Kivilcim Eren Erdoğan; Sinan Sozutok; Kairgeldy Aikimbaev
Journal:  Abdom Radiol (NY)       Date:  2021-08-20

5.  Reduced field-of-view and multi-shot DWI acquisition techniques: Prospective evaluation of image quality and distortion reduction in prostate cancer imaging.

Authors:  Edward M Lawrence; Yuxin Zhang; Jitka Starekova; Zihan Wang; Ali Pirasteh; Shane A Wells; Diego Hernando
Journal:  Magn Reson Imaging       Date:  2022-08-06       Impact factor: 3.130

6.  Physically implausible signals as a quantitative quality assessment metric in prostate diffusion-weighted MR imaging.

Authors:  Teodora Szasz; Grace Lee; Aritrick Chatterjee; Milica Medved; Ajit Devaraj; Ambereen Yousuf; Xiaobing Fan; Gregory S Karczmar; Aytekin Oto
Journal:  Abdom Radiol (NY)       Date:  2022-05-18

7.  Repeatability and Reproducibility Assessment of the Apparent Diffusion Coefficient in the Prostate: A Trial of the ECOG-ACRIN Research Group (ACRIN 6701).

Authors:  Michael A Boss; Bradley S Snyder; Eunhee Kim; Dena Flamini; Sarah Englander; Karthik M Sundaram; Naveen Gumpeni; Suzanne L Palmer; Haesun Choi; Adam T Froemming; Thorsten Persigehl; Matthew S Davenport; Dariya Malyarenko; Thomas L Chenevert; Mark A Rosen
Journal:  J Magn Reson Imaging       Date:  2022-02-10       Impact factor: 5.119

8.  Diffusion kurtosis MRI as a predictive biomarker of response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

Authors:  Surrin S Deen; Andrew N Priest; Mary A McLean; Andrew B Gill; Cara Brodie; Robin Crawford; John Latimer; Peter Baldwin; Helena M Earl; Christine Parkinson; Sarah Smith; Charlotte Hodgkin; Ilse Patterson; Helen Addley; Susan Freeman; Penny Moyle; Mercedes Jimenez-Linan; Martin J Graves; Evis Sala; James D Brenton; Ferdia A Gallagher
Journal:  Sci Rep       Date:  2019-07-24       Impact factor: 4.379

9.  Reproducibility of magnetic resonance fingerprinting-based T1 mapping of the healthy prostate at 1.5 and 3.0 T: A proof-of-concept study.

Authors:  Nikita Sushentsev; Joshua D Kaggie; Rhys A Slough; Bruno Carmo; Tristan Barrett
Journal:  PLoS One       Date:  2021-01-29       Impact factor: 3.240

10.  The Histogram Analysis of Intravoxel Incoherent Motion-Kurtosis Model in the Diagnosis and Grading of Prostate Cancer-A Preliminary Study.

Authors:  Chunmei Li; Lu Yu; Yuwei Jiang; Yadong Cui; Ying Liu; Kaining Shi; Huimin Hou; Ming Liu; Wei Zhang; Jintao Zhang; Chen Zhang; Min Chen
Journal:  Front Oncol       Date:  2021-10-27       Impact factor: 6.244

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