Radiomics in prostate cancer: an up-to-date review

: Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications

The impact of arterial input function determination variations on prostate dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling: a multicenter data analysis challenge, part II

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study

Relatório de Atividade Profissional

O presente trabalho consiste numa exposição sobre a minha experiência profissional e científica na área da imagem médica na modalidade de ressonância magnética, na empresa Philips Portuguesa S.A, durante os últimos 16 anos. Inicialmente será feito o enquadramento do relatório, onde é descrita a organização e contextualização deste trabalho. Seguidamente, será apresentada toda a minha experiência profissional enquanto Clinical Application Specialist e posteriormente como Clinical Scientist, formação profissional, e competências adquiridas em ressonância magnética. Será também descrito o trabalho científico desenvolvido tendo por base artigos e capítulos de livros publicados, onde é elaborada uma contextualização científica e identificação da minha participação e colaboração em três dos artigos. A escrita deste relatório acabou por ser uma ferramenta de reflexão sobre o meu percurso profissional até à data e sobre o que perspetivo para o meu futuro. Ter-mino o relatório com um balanço profissional e pessoal tendo esta mesma reflexão como base.The present work consists of an exhibition about my professional and scientific experience in medical imaging focused on magnetic resonance imaging, at the company Philips Portuguesa S.A, during the last 16 years. Initially, it will be described the organization and content of this work. All the professional experience as a Clinical Application Specialist and Clinical Scientist, professional training, and skills acquired in MRI will be presented. Afterwards, it will be introduced the scientific work developed with reference to articles and book chapters already published, with a subsequent scientific context and discussion of my participation in three of the articles. The writing of this report turned out to be a tool for reflecting on my professional career to date and what I have in mind for my future. I end the report with a professional and personal balance based on this same reflection

A multicenter study on radiomic features from T2-weighted images of a customized MR pelvic phantom setting the basis for robust radiomic models in clinics

Purpose: To investigate the repeatability and reproducibility of radiomic features extracted from MR images and provide a workflow to identify robust features. Methods: T2-weighted images of a pelvic phantom were acquired on three scanners of two manufacturers and two magnetic field strengths. The repeatability and reproducibility of features were assessed by the intraclass correlation coefficient and the concordance correlation coefficient, respectively, and by the within-subject coefficient of variation, considering repeated acquisitions with and without phantom repositioning, and with different scanner and acquisition parameters. The features showing intraclass correlation coefficient or concordance correlation coefficient >0.9 were selected, and their dependence on shape information (Spearman’s ρ > 0.8) analyzed. They were classified for their ability to distinguish textures, after shuffling voxel intensities of images. Results: From 944 two-dimensional features, 79.9% to 96.4% showed excellent repeatability in fixed position across all scanners. A much lower range (11.2% to 85.4%) was obtained after phantom repositioning. Three-dimensional extraction did not improve repeatability performance. Excellent reproducibility between scanners was observed in 4.6% to 15.6% of the features, at fixed imaging parameters. In addition, 82.4% to 94.9% of the features showed excellent agreement when extracted from images acquired with echo times 5 ms apart, but decreased with increasing echo-time intervals, and 90.7% of the features exhibited excellent reproducibility for changes in pulse repetition time. Of nonshape features, 2.0% was identified as providing only shape information. Conclusion: We showed that radiomic features are affected by MRI protocols and propose a general workflow to identify repeatable, reproducible, and informative radiomic features to ensure robustness of clinical studies