Literature DB >> 25426656

Microstructural characterization of normal and malignant human prostate tissue with vascular, extracellular, and restricted diffusion for cytometry in tumours magnetic resonance imaging.

Eleftheria Panagiotaki1, Rachel W Chan, Nikolaos Dikaios, Hashim U Ahmed, James O'Callaghan, Alex Freeman, David Atkinson, Shonit Punwani, David J Hawkes, Daniel C Alexander.   

Abstract

OBJECTIVE: The aim of this study was to demonstrate the feasibility of the recently introduced Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours (VERDICT) framework for imaging prostate cancer with diffusion-weighted magnetic resonance imaging (DW-MRI) within a clinical setting.
MATERIALS AND METHODS: The VERDICT framework is a noninvasive microstructure imaging technique that combines an in-depth diffusion MRI acquisition with a mathematical model to estimate and map microstructural tissue parameters such as cell size and density and vascular perfusion. In total, 8 patients underwent 3-T MRI using 9 different b values (100-3000 s/mm). All patients were imaged before undergoing biopsy. Experiments with VERDICT analyzed DW-MRI data from patients with histologically confirmed prostate cancer in areas of cancerous and benign peripheral zone tissue. For comparison, we also fitted commonly used diffusion models such as the apparent diffusion coefficient (ADC), the intravoxel incoherent motion (IVIM), and the kurtosis model. We also investigated correlations of ADC and kurtosis with VERDICT parameters to gain some biophysical insight into the various parameter values.
RESULTS: Eight patients had prostate cancer in the peripheral zone, with Gleason score 3 + 3 (n = 1), 3 + 4 (n = 6), and 4 + 3 (n = 1). The VERDICT model identified a significant increase in the intracellular and vascular volume fraction estimates in cancerous compared with benign peripheral zone, as well as a significant decrease in the volume of the extracellular-extravascular space (EES) (P = 0.05). This is in agreement with manual segmentation of the biopsies for prostate tissue component analysis, which found proliferation of epithelium, loss of surrounding stroma, and an increase in vasculature. The standard ADC and kurtosis parameters were also significantly different (P = 0.05) between tissue types. There was no significant difference in any of the IVIM parameters (P = 0.11 to 0.29). The VERDICT parametric maps from voxel-by-voxel fitting clearly differentiated cancer from benign regions. Kurtosis and ADC parameters correlated most strongly with VERDICT's intracellular volume fraction but also moderately with the EES and vascular fractions.
CONCLUSIONS: The VERDICT model distinguished tumor from benign areas, while revealing differences in microstructure descriptors such as cellular, vascular, and EES fractions. The parameters of ADC and kurtosis models also discriminated between cancer and benign regions. However, VERDICT provides more specific information that disentangles the various microstructural features underlying the changes in ADC and kurtosis. These results highlight the clinical potential of the VERDICT framework and motivate the construction of a shorter, clinically viable imaging protocol to enable larger trials leading to widespread translation of the method.

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Mesh:

Year:  2015        PMID: 25426656     DOI: 10.1097/RLI.0000000000000115

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  53 in total

1.  Magnetic resonance imaging of mean cell size in human breast tumors.

Authors:  Junzhong Xu; Xiaoyu Jiang; Hua Li; Lori R Arlinghaus; Eliot T McKinley; Sean P Devan; Benjamin M Hardy; Jingping Xie; Hakmook Kang; A Bapsi Chakravarthy; John C Gore
Journal:  Magn Reson Med       Date:  2019-11-25       Impact factor: 4.668

2.  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

3.  Diffusion-weighted Imaging of Prostate Cancer: Revisiting Occam's Razor.

Authors:  Eric E Sigmund; Andrew B Rosenkrantz
Journal:  Radiology       Date:  2019-04-02       Impact factor: 11.105

Review 4.  Diffusion MRI of cancer: From low to high b-values.

Authors:  Lei Tang; Xiaohong Joe Zhou
Journal:  J Magn Reson Imaging       Date:  2018-10-12       Impact factor: 4.813

5.  Stimulated echo based mapping (STEM) of T1 , T2 , and apparent diffusion coefficient: validation and protocol optimization.

Authors:  Yuxin Zhang; Shane A Wells; Diego Hernando
Journal:  Magn Reson Med       Date:  2018-07-19       Impact factor: 4.668

6.  Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study.

Authors:  Aritrick Chatterjee; Roger M Bourne; Shiyang Wang; Ajit Devaraj; Alexander J Gallan; Tatjana Antic; Gregory S Karczmar; Aytekin Oto
Journal:  Radiology       Date:  2018-02-02       Impact factor: 11.105

Review 7.  New prostate MRI techniques and sequences.

Authors:  Aritrick Chatterjee; Carla Harmath; Aytekin Oto
Journal:  Abdom Radiol (NY)       Date:  2020-12

8.  In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy.

Authors:  Xiaoyu Jiang; Hua Li; Jingping Xie; Eliot T McKinley; Ping Zhao; John C Gore; Junzhong Xu
Journal:  Magn Reson Med       Date:  2016-08-06       Impact factor: 4.668

Review 9.  [Multiparametric MRI of the prostate : Important radiological findings for urologists].

Authors:  Heinz-Peter Schlemmer
Journal:  Radiologe       Date:  2017-08       Impact factor: 0.635

10.  MRI-cytometry: Mapping nonparametric cell size distributions using diffusion MRI.

Authors:  Junzhong Xu; Xiaoyu Jiang; Sean P Devan; Lori R Arlinghaus; Eliot T McKinley; Jingping Xie; Zhongliang Zu; Qing Wang; A Bapsi Chakravarthy; Yong Wang; John C Gore
Journal:  Magn Reson Med       Date:  2020-09-16       Impact factor: 4.668

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