Search results for "Multiparametric"

Intra‐ and interreader reproducibility of PI‐RADSv2: A multireader study

2018

Background The Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) has been in use since 2015; while interreader reproducibility has been studied, there has been a paucity of studies investigating the intrareader reproducibility of PI-RADSv2. Purpose To evaluate both intra- and interreader reproducibility of PI-RADSv2 in the assessment of intraprostatic lesions using multiparametric magnetic resonance imaging (mpMRI). Study type Retrospective. Population/subjects In all, 102 consecutive biopsy-naive patients who underwent prostate MRI and subsequent MR/transrectal ultrasonography (MR/TRUS)-guided biopsy. Field strength/sequences Prostate mpMRI at 3T using endorectal with phased…

Slope units-based flow susceptibility model: using validation tests to select controlling factors

2011

A susceptibility map for an area, which is representative in terms of both geologic setting and slope instability phenomena of large sectors of the Sicilian Apennines, was produced using slope units and a multiparametric univariate model. The study area, extending for approximately 90 km2, was partitioned into 774 slope units, whose expected landslide occurrence was estimated by averaging seven susceptibility values, determined for the selected controlling factors: lithology, mean slope gradient, stream power index at the foot, mean topographic wetness index and profile curvature, slope unit length, and altitude range. Each of the recognized 490 landslides was represented by its centroid po…

Radiomics and Prostate MRI: Current Role and Future Applications

2021

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine …

Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE …

2021

Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between O…

USO DEI PARAMETRI POSIZIONALI E DELL’ANALISI CITOMETRICA MULTIPARAMETRICA PER IDENTIFICARE I CASI DI LEUCEMIA LINFATICA CRONICA

2013

Development of a Multiparametric Cell-based Protocol to Screen and Classify the Hepatotoxicity Potential of Drugs

2012

Hepatotoxicity is a major reason for drug nonapprovals and withdrawals. The multiparametric analysis of xenobiotic toxicity at the single cells level using flow cytometry and cellular imaging-based approaches, such as high-content screening (HCS) technology, could play a key role in the detection of toxicity and the classification of compounds based on patterns of cellular injury. This study aimed to develop and validate a practical, reproducible, in vitro multiparametric cell-based protocol to assess those drugs that are potentially hepatotoxic to humans and to suggest their mechanisms of action. The assay was applied to HepG2 human cell line cultured in 96-well plates and exposed to 78 di…

Cytometric analysis for drug-induced steatosis in HepG2 cells

2009

Drugs are capable of inducing hepatic lipid accumulation. When fat accumulates, lipids are primarily stored as triglycerides which results in steatosis and provides substrates for lipid peroxidation. An in vitro multiparametric flow cytometry assay was performed in HepG2 cells by using fluorescent probes to analyze cell viability (propidium iodide, PI), lipid accumulation (BODIPY493/503), mitochondrial membrane potential (tetramethyl rhodamine methyl ester, TMRM) and reactive oxygen species generation (ROS) (2',7'-dihydrochlorofluorescein diacetate, DHCF-DA) as functional markers. All the measurements were restricted to live cells by gating the cells that excluded PI or those that exhibited…

Multiparametric MRI-based Dosimetric Parameters Best Predict Short-term Time Course of PSA After Iodine 125 Permanent Prostate Implantation for Local…

2012

International audience; D90% and V150% of the entire prostate are recognized as the best dosimetric predictors of outcome after 125 I permanent prostate implantation (PPI). The purpose of this study was 2-fold: 1) to determine the relationship between dose-volume parameters of the Dominant Intraprostatic Lesion (DIL) when compared to the prostate and early biochemical outcome after PPI; 2) to define if dose-volume parameters of the central gland (CG), the peripheral zone (PZ) and the DIL could best predict PSA bounce occurrence. The time course of PSA and mechanisms of bounces still remain unclear after PPI. Patients who had a higher dose in the DIL had a worse PSA level at 1 year which is …

Semi-automated and interactive segmentation of contrast-enhancing masses on breast DCE-MRI using spatial fuzzy clustering

2022

Abstract Multiparametric Magnetic Resonance Imaging (MRI) is the most sensitive imaging modality for breast cancer detection and is increasingly playing a key role in lesion characterization. In this context, accurate and reliable quantification of the shape and extent of breast cancer is crucial in clinical research environments. Since conventional lesion delineation procedures are still mostly manual, automated segmentation approaches can improve this time-consuming and operator-dependent task by annotating the regions of interest in a reproducible manner. In this work, a semi-automated and interactive approach based on the spatial Fuzzy C-Means (sFCM) algorithm is proposed, used to segme…

Maximum likelihood ADC parameter estimates improve selection of metastatic cervical nodes for patients with head and neck squamous cell cancer

2012

The aim of this work was to determine whether classification of benign and metastatic cervical nodes based on diffusion weighted imaging (DWI) could be improved by use of a maximum likelihood algorithm for derivation of ADC parameters. A non linear least squares (LSQ) algorithm is usually used to fit parameters to the measured MR signal intensities as a function of b-value. LSQ assumes that the noise in high b-values is normally distributed whereas in reality it follows a Rice distribution. To account for the Rician noise, maximum likelihood (ML) algorithms have been proposed that provide unbiased ADC estimates. In this work the monoexponential, stretched exponential and biexponential model…