The accuracy of prostate volume measurement from ultrasound images: a quasi-Monte Carlo simulation study using magnetic resonance imaging.

Prostate volume is an important parameter to guide management of patients with benign prostatic hyperplasia (BPH) and to deliver clinical trial endpoints. Generally, simple 2D ultrasound (US) approaches are favoured despite the potential for greater accuracy afforded by magnetic resonance imaging (MRI) or complex US procedures. In this study, different approaches to estimate prostate size are evaluated with a simulation to select multiple organ cross-sections and diameters from 22 MRI-defined prostate shapes. A quasi-Monte Carlo (qMC) approach is used to simulate multiple probe positions and angles within prescribed limits resulting in a range of dimensions. The basic ellipsoid calculation which uses two scanning planes compares well to the MRI volume across the range of prostate shapes and sizes (R=0.992). However, using an appropriate linear regression model, accurate volume estimates can be made using prostate diameters calculated from a single scanning plane.

A mathematical model of the human menstrual cycle for the administration of GnRH analogues.

The paper presents a differential equation model for the feedback mechanisms between gonadotropin-releasing hormone (GnRH), follicle-stimulating hormone (FSH), luteinizing hormone (LH), development of follicles and corpus luteum, and the production of estradiol (E2), progesterone (P4), inhibin A (IhA), and inhibin B (IhB) during the female menstrual cycle. Compared to earlier human cycle models, there are three important differences: The model presented here (a) does not involve any delay equations, (b) is based on a deterministic modeling of the GnRH pulse pattern, and (c) contains less differential equations and less parameters. These differences allow for a faster simulation and parameter identification. The focus is on modeling GnRH-receptor binding, in particular, by inclusion of a pharmacokinetic/pharmacodynamic (PK/PD) model for a GnRH agonist, Nafarelin, and a GnRH antagonist, Cetrorelix, into the menstrual cycle model. The final mathematical model describes the hormone profiles (LH, FSH, P4, E2) throughout the menstrual cycle of 12 healthy women. It correctly predicts hormonal changes following single and multiple dose administration of Nafarelin or Cetrorelix at different stages in the cycle.

Evidence of a pharmacodynamic EEG profile in rats following clonidine administration using a nonlinear analysis.

BACKGROUND: Changes caused by clonidine in rodent electroencephalograms (EEG) have been reported with some inconsistency. For this reason, a pre-clinical study was conducted in order to confirm previous findings with both a standard spectral analysis and a sleep stage scoring procedure. In addition, a nonlinear technique for analysing the time-varying signals was implemented to compare its performance against conventional approaches. RESULTS: The nonlinear method succeeds in quantifying all dose-related responses from the data set relying solely on the EEG trace. CONCLUSIONS: Nonlinear approaches can deliver a suitable alternative to the sleep-stage scoring methods commonly used for drug effect detection.

Characterisation of very low frequency oscillations in laser Doppler perfusion signals with a singular spectrum analysis.

Laser Doppler (LD) perfusion signals consist of a number of superimposed frequencies that span a wide range. Singular spectrum analysis (SSA) was used to characterise the very low frequency (VLF) components as this method can extract frequencies of interest from the time domain. Its utility is demonstrated on a sex health clinical data set where the focus was on VLF oscillations. A significant change in this frequency range can be measured with SSA when the subject is undergoing erotic stimulation.

Visualisation tool for peptide fractionation data in proteomics: application to OFFGEL isoelectric focussing.

BACKGROUND: OFFGEL isoelectric focussing (IEF) has become a popular tool in proteomics to fractionate peptides or proteins. As a consequence there is a need for software solutions supporting data mining, interpretation and characterisation of experimental quality. RESULTS: We can assess performance characteristics of OFFGEL IEF peptide fractionation in proteomics by generating plots of the overall fractionation patterns and the pairwise comparisons of adjacent fractions. CONCLUSIONS: A visualisation tool for peptide fractionation has been developed to support the evaluation of IEF data quality and can be implemented in proteomics research.

Stochastic simulations of the exponential-beta function as an assessment of the validity of the choice of the Wagner-Nelson method for the analysis of ¹³C-octanoic acid breath tests.

A compartmental model that generates the exponential-beta function µkß(1 - e(-kt))(ß - 1) e(-kt) in order to run stochastic simulations has been constructed. The mathematical considerations that lead to the development of the model and the comparison of its performance with real data sets obtained from the studies of gastric emptying in healthy volunteers using ¹³C-octanoic acid breath tests are demonstrated. Stochastic simulations have been used to introduce randomness. These confirmed the choice of an exponential-beta function to model the physiological system, as agreement was obtained between experimental and theoretical data. The comparisons were made by visual inspection only, as the intention was to demonstrate that the stochastic exponential-ß model would generate the full range of observed curve shapes.