A carregar...
Publicação
Development of a Osirix plug-in for non-gaussian diffusion MRI data: application to Breast
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 4.86 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Breast cancer is the second leading cause of death by cancer and is the second type of
cancer that is the most common among women, causing the death of 1500 women, every
year, in Portugal. Over the past decades, with the improvement of imaging techniques
and therapeutics, breast cancer mortality rate has been decreasing substantially. One of
the imaging techniques used is diffusion-weighted imaging (DWI), which is the magnetic
resonance imaging method that is the most sensitive in detecting invasive breast cancer.
There are several extensions of this technique that can be based on the premise that the
environment is not homogeneous (non-Gaussian models).
The non-Gaussian models, take into account the presence of barriers and compartments
that restrict the water molecules movement in the biological tissues, allowing the
distinction between malignant and benign lesions in DWI. Taking into account that
diffusion-weighted imaging is a non invasive method, the diagnosis through the application
of these models can become an alternative to biopsy.
The main goal of this dissertation was the development of a OsiriX plug-in that
performs the non-Gaussian diffusion analysis of DWI in magnetic resonance imaging
data. Five non-Gaussian diffusion models were implemented in the application: diffusion
kurtosis imaging, intravoxel incoherent motion, gamma distribution, truncated and
stretched-exponential. Parametric maps and region-of interest (ROI) parametric values
were obtained for each model. In order to fit the various non-Gaussian diffusion models,
the Levenberg-Marquardt algorithm was used. This algorithm finds coefficients x to
best fit the nonlinear function to the data. The x coefficients results in parametric maps
that are able to identify the tumour and also distinguish between malignant and benign
lesions provided a comparison with the literature. During the application development,
these functionalities were also used to study the dependence of fitted parameters on the
number of b-values used and on the image noise.
An interface was developed with Objective-C on Xcode for OsiriX where the user gets
to choose from five diffusion models in order to obtain parameric maps or values. It also
informs on the goodness of fit and it provides fitting plots of the data. The references of
the models and extra information are also available in an help button.
Finally, the application was tested successfully with breast DWI images of benign and malignant tumors.
Descrição
Palavras-chave
Diffusion Kurtosis Imaging Intravoxel Incoherent Motion Gamma Distribution Truncated Stretched-Exponential Plug-in