The family alliance assessment scales : steps toward validity and reliability of an observational assessment tool for early family interactions

We present the first steps in the validation of an observational tool for father-mother-infant interactions: the FAAS (Family Alliance Assessment Scales). Family-level variables are acknowledged as unique contributors to the understanding of the socio-affective development of the child, yet producing reliable assessments of family-level interactions poses a methodological challenge. There is, therefore, a clear need for a validated and clinically relevant tool. This validation study has been carried out on three samples: one non-referred sample, of families taking part in a study on the transition to parenthood (normative sample; n = 30), one referred for medically assisted procreation (infertility sample; n = 30) and one referred for a psychiatric condition in one parent (clinical sample; n = 15). Results show that the FAAS scales have (1) good inter-rater reliability and (2) good validity, as assessed through known-group validity by comparing the three samples and through concurrent validity by checking family interactions against parents' self-reported marital satisfaction.

Assessing inter-rater reliability when the raters are fixed: two concepts and two estimates.

Intraclass correlation (ICC) is an established tool to assess inter-rater reliability. In a seminal paper published in 1979, Shrout and Fleiss considered three statistical models for inter-rater reliability data with a balanced design. In their first two models, an infinite population of raters was considered, whereas in their third model, the raters in the sample were considered to be the whole population of raters. In the present paper, we show that the two distinct estimates of ICC developed for the first two models can both be applied to the third model and we discuss their different interpretations in this context.

Fast Approximation of Nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Syndromic algorithms for detection of gambiense human african trypanosomiasis in South Sudan.

BACKGROUND: Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. METHODOLOGY/PRINCIPAL FINDINGS: Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9-92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4-8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. CONCLUSIONS/SIGNIFICANCE: In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere.

3D noise power spectrum applied on clinical mdct scanners: effects of reconstruction algorithms and reconstruction filters

The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

Calibration and Reliability of a Nuclear Asphalt Content Gauge, MLR-87-02, 1987

Based on results of an evaluation performed during the winter of 1985-86, six Troxler 3241-B Asphalt Content Gauges were purchased for District use in monitoring project asphalt contents. Use of these gauges will help reduce the need for chemical based extractions. Effective use of the gauges depends on the accurate preparation and transfer of project mix calibrations from the Central Lab to the Districts. The objective of this project was to evaluate the precision and accuracy of a gauge in determining asphalt contents and to develop a mix calibration transfer procedure for implementation during the 1987 construction. The first part of the study was accomplished by preparing mix calibrations in the Central Lab gauge and taking multiple measurements of a sample with known asphalt content. The second part was accomplished by preparing transfer pans, obtaining count data on the pans using each gauge, and transferring calibrations from one gauge to another through the use of calibration transfer equations. The transferred calibrations were tested by measuring samples with a known asphalt content. The study established that the Troxler 3241-B Asphalt Content Gauge yields results of acceptable accuracy and precision as evidenced by a standard deviation of 0.04% asphalt content on multiple measurements of the same sample. The calibration transfer procedure proved feasible and resulted in the calibration transfer portion of Materials I.M. 335 - Method of Test For Determining the Asphalt Content of Bituminous Mixtures by the Nuclear Method.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

A treatment planning method for sequentially combining radiopharmaceutical therapy and external radiation therapy.

PURPOSE: Effective cancer treatment generally requires combination therapy. The combination of external beam therapy (XRT) with radiopharmaceutical therapy (RPT) requires accurate three-dimensional dose calculations to avoid toxicity and evaluate efficacy. We have developed and tested a treatment planning method, using the patient-specific three-dimensional dosimetry package 3D-RD, for sequentially combined RPT/XRT therapy designed to limit toxicity to organs at risk. METHODS AND MATERIALS: The biologic effective dose (BED) was used to translate voxelized RPT absorbed dose (D(RPT)) values into a normalized total dose (or equivalent 2-Gy-fraction XRT absorbed dose), NTD(RPT) map. The BED was calculated numerically using an algorithmic approach, which enabled a more accurate calculation of BED and NTD(RPT). A treatment plan from the combined Samarium-153 and external beam was designed that would deliver a tumoricidal dose while delivering no more than 50 Gy of NTD(sum) to the spinal cord of a patient with a paraspinal tumor. RESULTS: The average voxel NTD(RPT) to tumor from RPT was 22.6 Gy (range, 1-85 Gy); the maximum spinal cord voxel NTD(RPT) from RPT was 6.8 Gy. The combined therapy NTD(sum) to tumor was 71.5 Gy (range, 40-135 Gy) for a maximum voxel spinal cord NTD(sum) equal to the maximum tolerated dose of 50 Gy. CONCLUSIONS: A method that enables real-time treatment planning of combined RPT-XRT has been developed. By implementing a more generalized conversion between the dose values from the two modalities and an activity-based treatment of partial volume effects, the reliability of combination therapy treatment planning has been expanded.

Comparing Random-based and k-Anonymity-Based Algorithms for Graph Anonymization

Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random-ization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in orderto obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.