Model specification and the reliability of fMRI results: Implications for longitudinal neuroimaging studies in psychiatry

Functional Magnetic Resonance Imagine (fMRI) is an important assessment tool in longitudinal studies of mental illness and its treatment. Understanding the psychometric properties of fMRI-based metrics, and the factors that influence them, will be critical for properly interpreting the results of these efforts. The current study examined whether the choice among alternative model specifications affects estimates of test-retest reliability in key emotion processing regions across a 6-month interval. Subjects (N = 46) performed an emotional-faces paradigm during fMRI in which neutral faces dynamically morphed into one of four emotional faces. Median voxelwise intraclass correlation coefficients (mvICCs) were calculated to examine stability over time in regions showing task-related activity as well as in bilateral amygdala. Four modeling choices were evaluated: a default model that used the canonical hemodynamic response function (HRF), a flexible HRF model that included additional basis functions, a modified CompCor (mCompCor) model that added corrections for physiological noise in the global signal, and a final model that combined the flexible HRF and mCompCor models. Model residuals were examined to determine the degree to which each pipeline met modeling assumptions. Results indicated that the choice of modeling approaches impacts both the degree to which model assumptions are met and estimates of test-retest reliability. ICC estimates in the visual cortex increased from poor (mvICC = 0.31) in the default pipeline to fair (mvICC = 0.45) in the full alternative pipeline - an increase of 45%. In nearly all tests, the models with the fewest assumption violations generated the highest ICC estimates. Implications for longitudinal treatment studies that utilize fMRI are discussed. © 2014 Fournier et al

Development patterns of an isolated oligo-mesophotic carbonate buildup, early Miocene, Yadana field, offshore Myanmar

The development history of an oligo-mesophotic, early Miocene, isolated carbonate system (>160 m in thickness), forming the uppermost part of the Oligo-Miocene Yadana buildup (northern Andaman Sea), has been evidenced from the integration of sedimentological core studies from 4 wells (cumulated core length: 343 m), well correlations, seismic interpretation and analysis of the ecological requirements of the main skeletal components. Three types of carbonate factory operated on the top of the platform, depending on water-depth, turbidity and nutrient level: (1) a scleractinian factory developing under mesophotic conditions during periods of high particulate organic matter supplies, (2) an echinodermal factory occupying dysphotic to aphotic area of the platform coevally with the scleractinian factory, (3) a large benthic foraminiferal-coralline algal factories prevailing under oligo-mesophotic and oligo-mesotrophic conditions. The limited lateral changes in facies between wells, together with the seismic expression of the Yadana buildup, suggest deposition on a flat-topped shelf. Carbonate production and accumulation on the Yadana platform was mainly controlled by light penetration, nutrient content and hydrodynamic conditions. Scleractinian-rich facies resulted from transport of coral pieces derived from mesophotic environments (mounds?) and deposited in deeper, low light, mud-rich environments in which lived abundant communities of suspension feeders such as ophiuroids. Changes in monsoonal intensity, terrestrial runoff from the Irrawaddy River, upwelling currents and internal waves activity during the early Miocene are likely responsible for significant variations in water turbidity and nutrient concentration in the Andaman Sea, thus promoting the development of an oligo-mesophotic, incipiently drowned platform

Discovering High-Utility Itemsets at Multiple Abstraction Levels

High-Utility Itemset Mining (HUIM) is a relevant data mining task. The goal is to discover recurrent combinations of items characterized by high prot from transactional datasets. HUIM has a wide range of applications among which market basket analysis and service proling. Based on the observation that items can be clustered into domain-specic categories, a parallel research issue is generalized itemset mining. It entails generating correlations among data items at multiple abstraction levels. The extraction of multiple-level patterns affords new insights into the analyzed data from dierent viewpoints. This paper aims at discovering a novel pattern that combines the expressiveness of generalized and High-Utility itemsets. According to a user-defined taxonomy items are rst aggregated into semantically related categories. Then, a new type of pattern,namely the Generalized High-utility Itemset (GHUI), is extracted. It represents a combinations of items at different granularity levels characterized by high prot (utility). While protable combinations of item categories provide interesting high-level information, GHUIs at lower abstraction levels represent more specic correlationsamong protable items. A single-phase algorithm is proposed to efficiently discover utility itemsets at multiple abstraction levels. The experiments, which were performed on both real and synthetic data, demonstrate the effectiveness and usefulness of the proposed approach

The personalized advantage index: Translating research on prediction into individualized treatment recommendations. A demonstration

Background: Advances in personalized medicine require the identification of variables that predict differential response to treatments as well as the development and refinement of methods to transform predictive information into actionable recommendations. Objective: To illustrate and test a new method for integrating predictive information to aid in treatment selection, using data from a randomized treatment comparison. Method: Data from a trial of antidepressant medications (N = 104) versus cognitive behavioral therapy (N = 50) for Major Depressive Disorder were used to produce predictions of post-treatment scores on the Hamilton Rating Scale for Depression (HRSD) in each of the two treatments for each of the 154 patients. The patient's own data were not used in the models that yielded these predictions. Five pre-randomization variables that predicted differential response (marital status, employment status, life events, comorbid personality disorder, and prior medication trials) were included in regression models, permitting the calculation of each patient's Personalized Advantage Index (PAI), in HRSD units. Results: For 60% of the sample a clinically meaningful advantage (PAI≥3) was predicted for one of the treatments, relative to the other. When these patients were divided into those randomly assigned to their "Optimal" treatment versus those assigned to their "Non-optimal" treatment, outcomes in the former group were superior (d = 0.58, 95% CI .17-1.01). Conclusions: This approach to treatment selection, implemented in the context of two equally effective treatments, yielded effects that, if obtained prospectively, would rival those routinely observed in comparisons of active versus control treatments. © 2014 DeRubeis et al

The script concordance test in radiation oncology: validation study of a new tool to assess clinical reasoning

<p>Abstract</p> <p>Background</p> <p>The Script Concordance test (SCT) is a reliable and valid tool to evaluate clinical reasoning in complex situations where experts' opinions may be divided. Scores reflect the degree of concordance between the performance of examinees and that of a reference panel of experienced physicians. The purpose of this study is to demonstrate SCT's usefulness in radiation oncology.</p> <p>Methods</p> <p>A 90 items radiation oncology SCT was administered to 155 participants. Three levels of experience were tested: medical students (n = 70), radiation oncology residents (n = 38) and radiation oncologists (n = 47). Statistical tests were performed to assess reliability and to document validity.</p> <p>Results</p> <p>After item optimization, the test comprised 30 cases and 70 questions. Cronbach alpha was 0.90. Mean scores were 51.62 (± 8.19) for students, 71.20 (± 9.45) for residents and 76.67 (± 6.14) for radiation oncologists. The difference between the three groups was statistically significant when compared by the Kruskall-Wallis test (p < 0.001).</p> <p>Conclusion</p> <p>The SCT is reliable and useful to discriminate among participants according to their level of experience in radiation oncology. It appears as a useful tool to document the progression of reasoning during residency training.</p

How to Obtain NNT from Cohen's d: Comparison of Two Methods

Background: In the literature we find many indices of size of treatment effect (effect size: ES). The preferred index of treatment effect in evidence-based medicine is the number needed to treat (NNT), while the most common one in the medical literature is Cohen’s d when the outcome is continuous. There is confusion about how to convert Cohen’s d into NNT. Methods: We conducted meta-analyses of individual patient data from 10 randomized controlled trials of second generation antipsychotics for schizophrenia (n = 4278) to produce Cohen’s d and NNTs for various definitions of response, using cutoffs of 10 % through 90 % reduction on the symptom severity scale. These actual NNTs were compared with NNTs calculated from Cohen’s d according to two proposed methods in the literature (Kraemer, et al., Biological Psychiatry, 2006; Furukawa, Lancet, 1999). Results: NNTs from Kraemer’s method overlapped with the actual NNTs in 56%, while those based on Furukawa’s method fell within the observed ranges of NNTs in 97 % of the examined instances. For various definitions of response corresponding with 10 % through 70 % symptom reduction where we observed a non-small number of responders, the degree of agreement for the former method was at a chance level (ANOVA ICC of 0.12, p = 0.22) but that for the latter method was ANOVA ICC of 0.86 (95%CI: 0.55 to 0.95, p,0.01)

Restoration of diaphragmatic function after diaphragm reinnervation by inferior laryngeal nerve; experimental study in rabbits

OBJECTIVES: To assess the possibilities of reinnervation in a paralyzed hemidiaphragm via an anastomosis between phrenic nerve and inferior laryngeal nerve in rabbits. Reinnervation of a paralyzed diaphragm could be an alternative to treat patients with ventilatory insufficiency due to upper cervical spine injuries. MATERIAL AND METHOD: Rabbits were divided into five groups of seven rabbits each. Groups I and II were respectively the healthy and the denervated control groups. The 3 other groups were all reinnervated using three different surgical procedures. In groups III and IV, phrenic nerve was respectively anastomosed with the abductor branch of the inferior laryngeal nerve and with the trunk of the inferior laryngeal nerve. In group V, the fifth and fourth cervical roots were respectively anastomosed with the abductor branch of the inferior laryngeal nerve and with the nerve of the sternothyroid muscle (originating from the hypoglossal nerve). Animals were evaluated 4 months later using electromyography, transdiaphragmatic pressure measurements, sonomicrometry and histological examination. RESULTS: A poor inspiratory activity was found in quiet breathing in the reinnervated groups, with an increasing pattern of activity during effort. In the reinnervated groups, transdiaphragmatic pressure measurements and sonomicrometry were higher in group III with no significant differencewith groups IV and V. CONCLUSION: Inspiratory contractility of an hemidiaphragm could be restored with immediate anastomosis after phrenic nerve section between phrenic nerve and inferior laryngeal nerve

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives.

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology. KEY POINTS:• Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research

Provision of mental health services in resource-poor settings: a randomised trial comparing counselling with routine medical treatment in North Afghanistan (Mazar-e-Sharif)

<p>Abstract</p> <p>Background</p> <p>Psychosocial stress caused by war, ongoing conflict, lack of security, and restricted access to resources promotes mental suffering and diseases in many resource-poor countries. In an exemplary setting, the present study compares the efficacy of psychosocial counselling with routine pharmacological treatment in a randomised trial in Mazar-e-Sharif (Afghanistan).</p> <p>Methods</p> <p>Help seeking Afghan women (N = 61), who were diagnosed with mental health symptoms by local physicians either received routine medical treatment<b/>(treatment as usual) or psychosocial counselling (5-8 sessions) following a specifically developed manualised treatment protocol. Primary outcome measures were symptoms of depression and anxiety assessed before treatment and at follow-up using the Hopkins Symptom Checklist and the Mini-International Neuropsychiatric Interview. Secondary outcome measures were psychosocial stressors and coping mechanisms.</p> <p>Results</p> <p>At 3-month follow-up, psychosocial counselling patients showed high improvements with respect to the severity of symptoms of depression and anxiety. In addition, they reported a reduction of psychosocial stressors and showed an enhancement of coping strategies. At the same time, the severity of symptoms, the quantity of psychosocial stressors and coping mechanisms did not improve in patients receiving routine medical treatment.</p> <p>Conclusion</p> <p>These results indicate that psychosocial counselling can be an effective treatment for mental illnesses even for those living in ongoing unsafe environments.</p> <p>Trial registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01155687">NCT01155687</a></p