Information‐based ranking of 10 compartment models of diffusion‐weighted signal attenuation in fixed prostate tissue

Liang, Sisi; Panagiotaki, Eleftheria; Bongers, André; Shi, Ping‐Ping; Sved, Paul; Watson, Geoffrey; Bourne, Roger

doi:10.1002/nbm.3510

Cited by 13 publications

(32 citation statements)

References 32 publications

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“…The model that best explains the data varies in different tumours and regions, which is not unexpected given the diversity of breast cancer microstructure. This variation has also been reported in ex vivo prostate studies . A small fraction of voxels were excluded from fitting as a result of non‐mono‐exponential T 2 decay, and histology revealed that many such voxels were in necrotic regions.…”

Section: Discussionsupporting

confidence: 63%

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study

et al. 2016

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The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin‐fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one‐ and two‐compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.

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Section: Discussionsupporting

confidence: 63%

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study

et al. 2016

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“…As the acinal and epithelial water diffusion is essentially isotropic , variations in anisotropy reflecting stromal tissue changes may be masked or attenuated in voxels of the typical volume used in vivo. This possibility is supported by a recent comparison of seven compartment models of diffusion in (fixed) prostate tissue which found that a two‐compartment model comprising one isotropic and one anisotropic component was the best descriptor of the DWI signal attenuation over a range of diffusion times . It is possible that potentially diagnostic diffusion anisotropy changes are present, but not detectable by the simple monoexponential DTI method due to “masking” by a significant isotropic signal.…”

Section: Discussionmentioning

confidence: 94%

Diffusion anisotropy in fresh and fixed prostate tissue ex vivo

et al. 2015

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“…In the first VERDICT framework, the ICS and ECS diffusivities were fixed based on fit optimization performed on preliminary data [16], and found consistent with values derived from ex vivo studies with high SNR [57]. To further improve the fit robustness, the pseudo-diffusion coefficient of the water inside blood vessels was also fixed when characterizing prostatic tissue lesions in vivo in a later study [49].…”

Section: Fixing Parametersmentioning

confidence: 99%

“…Tissue lesions are often considered isotropic for convenience and practicality [49], potentially at the expense of specificity [57].…”

Section: Time and Hardware Issues Acquisition Timementioning

confidence: 99%

Time-Dependent Diffusion MRI in Cancer: Tissue Modeling and Applications

Reynaud

2017

Front. Phys.

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In diffusion weighted imaging (DWI), the apparent diffusion coefficient (ADC) has been recognized as a useful and sensitive surrogate for cell density, paving the way for non-invasive tumor staging, and characterization of treatment efficacy in cancer. However, microstructural parameters, such as cell size, density and/or compartmental diffusivities affect diffusion in various fashions, making of conventional DWI a sensitive but non-specific probe into changes happening at cellular level. Alternatively, tissue complexity can be probed and quantified using the time dependence of diffusion metrics, sometimes also referred to as temporal diffusion spectroscopy when only using oscillating diffusion gradients. Time-dependent diffusion (TDD) is emerging as a strong candidate for specific and non-invasive tumor characterization. Despite the lack of a general analytical solution for all diffusion times/frequencies, TDD can be probed in various regimes where systems simplify in order to extract relevant information about tissue microstructure. The fundamentals of TDD are first reviewed (a) in the short time regime, disentangling structural and diffusive tissue properties, and (b) near the tortuosity limit, assuming weakly heterogeneous media near infinitely long diffusion times. Focusing on cell bodies (as opposed to neuronal tracts), a simple but realistic model for intracellular diffusion can offer precious insight on diffusion inside biological systems, at all times. Based on this approach, the main three geometrical models implemented so far (IMPULSED, POMACE, VERDICT) are reviewed. Their suitability to quantify cell size, intra-and extracellular spaces (ICS and ECS) and diffusivities are assessed. The proper modeling of tissue membrane permeability-hardly a newcomer in the field, but lacking applications-and its impact on microstructural estimates are also considered. After discussing general issues with tissue modeling and microstructural parameter estimation (i.e., fitting), potential solutions are detailed. The in vivo applications of this new, non-invasive, specific approach in cancer are reviewed, ranging from the characterization of gliomas in rodent brains and observation of time-dependence in breast tissue lesions and prostate cancer, to the recent preclinical evaluation of new treatments efficacy. It is expected that clinical applications of TDD will strongly benefit the community in terms of non-invasive cancer screening.

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Information‐based ranking of 10 compartment models of diffusion‐weighted signal attenuation in fixed prostate tissue

Cited by 13 publications

References 32 publications

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study

Diffusion anisotropy in fresh and fixed prostate tissue ex vivo

Time-Dependent Diffusion MRI in Cancer: Tissue Modeling and Applications

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