Multi-compartmental MR measurements of the prostate

Gilani, Nima (2016) Multi-compartmental MR measurements of the prostate. Doctoral thesis, University of East Anglia.

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A large proportion of the diagnosed prostate cancer patients are suffering from low grade or indolent tumours. Transrectal ultrasound guided biopsy which is conventionally used as the means of diagnosis has a weak correlation with cancer grade or aggressiveness because of its random sampling nature, so that many indolent tumours are treated aggressively with serious side effects. Quantitative magnetic resonance imaging has shown relative success in distinguishing aggressive tumours. It is important to assess the feasibility of different MR modalities such as T2 or diffusion weighted imaging and to optimise them.
A variety of biophysical analyses were performed to find correlations between diffusion and T2 weighted magnetic resonance parameters and the changes in complex compartmental structure of the prostate (consisting of ducts, epithelial and stromal cells, and vascularity) with increasing cancer grade. For this aim, Monte Carlo simulations of a semi-restricted compartment (ductal lumen) and two compartmental exchange model (stromal-epithelial or cellular compartment) were used. Additionally, optimisations were performed for T2 and diffusion weighted imaging protocols.
The biexponential model for diffusion explicitly explained the biophysical changes in prostate cancer. The fast and slow ADC values respectively varied from 2.36 and 0.9 μm2ms-1 in healthy prostate to around 1 and 0.5 μm2ms-1 in the most aggressive tumours. Biexponential T2 acquisitions were optimised to distinguish indolent tumours. There was a 10-20% reduction in estimation errors compared to equally distanced acquisitions, if the target values of T2slow and T2fast were respectively 360 and 60 ms. The optimisations were extended to non-Gaussian diffusion weighted imaging protocols.
In order to substantially improve the diagnostic accuracy of prostate cancer MR acquisitions, it is recommended to consider the biophysical model and the optimised protocols introduced here. Also, diffusion time and other acquisition details should be considered prior to the imaging.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: Jackie Webb
Date Deposited: 24 Jan 2017 13:24
Last Modified: 24 Jan 2017 13:24


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