Computational neuroanatomy: ontology-based representation of neural components and connectivity

Background: A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results: We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion: Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future

Investigating the missing data mechanism in quality of life outcomes: a comparison of approaches

Background: Missing data is classified as missing completely at random (MCAR), missing at random (MAR) or missing not at random (MNAR). Knowing the mechanism is useful in identifying the most appropriate analysis. The first aim was to compare different methods for identifying this missing data mechanism to determine if they gave consistent conclusions. Secondly, to investigate whether the reminder-response data can be utilised to help identify the missing data mechanism. Methods: Five clinical trial datasets that employed a reminder system at follow-up were used. Some quality of life questionnaires were initially missing, but later recovered through reminders. Four methods of determining the missing data mechanism were applied. Two response data scenarios were considered. Firstly, immediate data only; secondly, all observed responses (including reminder-response). Results: In three of five trials the hypothesis tests found evidence against the MCAR assumption. Logistic regression suggested MAR, but was able to use the reminder-collected data to highlight potential MNAR data in two trials. Conclusion: The four methods were consistent in determining the missingness mechanism. One hypothesis test was preferred as it is applicable with intermittent missingness. Some inconsistencies between the two data scenarios were found. Ignoring the reminder data could potentially give a distorted view of the missingness mechanism. Utilising reminder data allowed the possibility of MNAR to be considered.The Chief Scientist Office of the Scottish Government Health Directorate. Research Training Fellowship (CZF/1/31

Profiling for primary-care presentation, investigation and referral for liver cancers: evidence from a national audit

BACKGROUND AND AIM: The incidence of liver cancer across Europe is increasing. There is a lack of evidence within the current literature on the identification and investigation of liver cancer within primary care. We aimed to profile liver cancer recognition and assessment as well as the timeliness of liver cancer diagnosis from within the primary-care setting in the UK. METHODS: Data were obtained from the National Audit of Cancer Diagnosis in Primary Care 2009–2010 and analysed. We calculated the patient interval, the primary-care interval and the number of prereferral consultations for liver cancer. We then compared these data with prior data on the respective indicators for other common cancers. RESULTS: The median patient interval was 9 days (interquartile range 0–31 days), and the median primary-care interval for liver cancer was 11 days (interquartile range 0–40 days). Of the 90 patients, 21 (23.3%) had three or more consultations with their general practitioner before specialist referral. For the three metrics (patient interval, primary-care interval and number of prereferral consultations), liver cancer has average or longer intervals when compared with other cancers. The most common symptomatic presentation of liver cancer within the primary-care setting was right upper quadrant pain (11%), followed by decompensated liver failure (9%). Of the patients, 12% were diagnosed with liver cancer on the basis of an incidental finding of an abnormal liver function test. CONCLUSION: This study provides a detailed and thorough overview of the recognition of liver cancer and the promptness of liver cancer identification in an English context, and should inform strategies for improving the timeliness of diagnosis

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

AI-based structure-function correlation in age-related macular degeneration

Sensitive and robust outcome measures of retinal function are pivotal for clinical trials in age-related macular degeneration (AMD). A recent development is the implementation of artificial intelligence (AI) to infer results of psychophysical examinations based on findings derived from multimodal imaging. We conducted a review of the current literature referenced in PubMed and Web of Science among others with the keywords 'artificial intelligence' and 'machine learning' in combination with 'perimetry', 'best-corrected visual acuity (BCVA)', 'retinal function' and 'age-related macular degeneration'. So far AI-based structure-function correlations have been applied to infer conventional visual field, fundus-controlled perimetry, and electroretinography data, as well as BCVA, and patient-reported outcome measures (PROM). In neovascular AMD, inference of BCVA (hereafter termed inferred BCVA) can estimate BCVA results with a root mean squared error of ~7-11 letters, which is comparable to the accuracy of actual visual acuity assessment. Further, AI-based structure-function correlation can successfully infer fundus-controlled perimetry (FCP) results both for mesopic as well as dark-adapted (DA) cyan and red testing (hereafter termed inferred sensitivity). Accuracy of inferred sensitivity can be augmented by adding short FCP examinations and reach mean absolute errors (MAE) of ~3-5 dB for mesopic, DA cyan and DA red testing. Inferred BCVA, and inferred retinal sensitivity, based on multimodal imaging, may be considered as a quasi-functional surrogate endpoint for future interventional clinical trials in the future

Propensity score matching in estimating the effect of managerial education on academic planning behavior. Study design: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>In many academic settings teaching a particular topic is applied to every student enrolled in the same academic year, it is a difficult task for researchers to design a randomized control group study. This research aimed to estimate the effect of teaching management and planning on increasing academic planning behavior (APB), using propensity score matching (PSM).</p> <p>Methods</p> <p>In a cross-sectional survey utilizing a self-reported structured questionnaire on a systematic random sample of 421 students in Hanoi Medical University, one of the eight medical schools in Vietnam, this evaluation study adopted regression procedures to assess model fit, then PSM to create a matched control group in order to allow for evaluating the effect of management education.</p> <p>Results</p> <p>The study showed both direct and indirect effects of the education on behavior. After PSM to adjust for the possible confounders to balance statistically two groups - with and without management education, there is statistically a significant difference in APB between these two groups, making a net difference of 18.60% (p < .05). The estimated 18.6 percentage point increase can be translated into the practice of APB by 670 students in the population. This number of academic planners can be attributed to a high recall of important management and planning education.</p> <p>Conclusions</p> <p>The study provided theoretical as well as practical implications to guide the design of the education and evaluation of teaching.</p

Rule-Based Ventral Cavity Multi-organ Automatic Segmentation in CT Scans

We describe a newmethod for the automatic segmentation of multiple organs of the ventral cavity in CT scans. The methodisbasedonasetofrulesthatdeterminetheorderin which theorgansare isolatedand segmented, from the sim- plestonetothemostdifficultone. First,thebodyisisolated from the background. Second, the trachea and the left and right lungsare segmentedbasedon theirair content.Third, thespleenandthekidneys–theorganswithhighbloodcon- tent–aresegmented. Finally,thekidneyissegmentedbased onthesurroundingorganssegmentation. Eachorganisindi- vidually segmentedwitha four-stepprocedure that consists of: 1) definition of an inclusive region of interest; 2) identi- fication of the largest axial cross-section slice; 3) Semoval of background structuresbymorphologicaloperations,and; 4) 3D region growing segmentation. Ourmethod is unique in that ituses the same generic segmentation approach for all organsand in that it relieson the segmentationdifficultyof organs toguide the segmentationprocess. Experimental re- sultson15CTscansoftheVISCERALAnatomy2Challenge trainingdatasetsyieldaDicevolumeoverlapsimilarityscore of 79.1 for the trachea, 97.4 and 97.6 for the left and right lungs, 89.2 for the spleen, and 92.8 for the left kidney. For the5CT scans testdatasets, theDice scoresare97.9,97.0, 85.6, 93.4 and 90.2, respectively. Our method achieved an overallDICE score of 92.8 andwas ranked first among the fivemethodsthatparticipated inthechallenge. Copyright c © by the paper’s authors. Copying permitted only for private and academic purposes

Evaluation of Negation and Uncertainty Detection and its Impact on Precision and Recall in Search

Radiology reports contain information that can be mined using a search engine for teaching, research, and quality assurance purposes. Current search engines look for exact matches to the search term, but they do not differentiate between reports in which the search term appears in a positive context (i.e., being present) from those in which the search term appears in the context of negation and uncertainty. We describe RadReportMiner, a context-aware search engine, and compare its retrieval performance with a generic search engine, Google Desktop. We created a corpus of 464 radiology reports which described at least one of five findings (appendicitis, hydronephrosis, fracture, optic neuritis, and pneumonia). Each report was classified by a radiologist as positive (finding described to be present) or negative (finding described to be absent or uncertain). The same reports were then classified by RadReportMiner and Google Desktop. RadReportMiner achieved a higher precision (81%), compared with Google Desktop (27%; p < 0.0001). RadReportMiner had a lower recall (72%) compared with Google Desktop (87%; p = 0.006). We conclude that adding negation and uncertainty identification to a word-based radiology report search engine improves the precision of search results over a search engine that does not take this information into account. Our approach may be useful to adopt into current report retrieval systems to help radiologists to more accurately search for radiology reports

Does clinical management improve outcomes following self-Harm? Results from the multicentre study of self-harm in England

Background Evidence to guide clinical management of self-harm is sparse, trials have recruited selected samples, and psychological treatments that are suggested in guidelines may not be available in routine practice. Aims To examine how the management that patients receive in hospital relates to subsequent outcome. Methods We identified episodes of self-harm presenting to three UK centres (Derby, Manchester, Oxford) over a 10 year period (2000 to 2009). We used established data collection systems to investigate the relationship between four aspects of management (psychosocial assessment, medical admission, psychiatric admission, referral for specialist mental health follow up) and repetition of self-harm within 12 months, adjusted for differences in baseline demographic and clinical characteristics. Results 35,938 individuals presented with self-harm during the study period. In two of the three centres, receiving a psychosocial assessment was associated with a 40% lower risk of repetition, Hazard Ratios (95% CIs): Centre A 0.99 (0.90–1.09); Centre B 0.59 (0.48–0.74); Centre C 0.59 (0.52–0.68). There was little indication that the apparent protective effects were mediated through referral and follow up arrangements. The association between psychosocial assessment and a reduced risk of repetition appeared to be least evident in those from the most deprived areas. Conclusion These findings add to the growing body of evidence that thorough assessment is central to the management of self-harm, but further work is needed to elucidate the possible mechanisms and explore the effects in different clinical subgroups

Developing and implementing an integrated delirium prevention system of care:a theory driven, participatory research study

Background: Delirium is a common complication for older people in hospital. Evidence suggests that delirium incidence in hospital may be reduced by about a third through a multi-component intervention targeted at known modifiable risk factors. We describe the research design and conceptual framework underpinning it that informed the development of a novel delirium prevention system of care for acute hospital wards. Particular focus of the study was on developing an implementation process aimed at embedding practice change within routine care delivery. Methods: We adopted a participatory action research approach involving staff, volunteers, and patient and carer representatives in three northern NHS Trusts in England. We employed Normalization Process Theory to explore knowledge and ward practices on delirium and delirium prevention. We established a Development Team in each Trust comprising senior and frontline staff from selected wards, and others with a potential role or interest in delirium prevention. Data collection included facilitated workshops, relevant documents/records, qualitative one-to-one interviews and focus groups with multiple stakeholders and observation of ward practices. We used grounded theory strategies in analysing and synthesising data. Results: Awareness of delirium was variable among staff with no attention on delirium prevention at any level; delirium prevention was typically neither understood nor perceived as meaningful. The busy, chaotic and challenging ward life rhythm focused primarily on diagnostics, clinical observations and treatment. Ward practices pertinent to delirium prevention were undertaken inconsistently. Staff welcomed the possibility of volunteers being engaged in delirium prevention work, but existing systems for volunteer support were viewed as a barrier. Our evolving conception of an integrated model of delirium prevention presented major implementation challenges flowing from minimal understanding of delirium prevention and securing engagement of volunteers alongside practice change. The resulting Prevention of Delirium (POD) Programme combines a multi-component delirium prevention and implementation process, incorporating systems and mechanisms to introduce and embed delirium prevention into routine ward practices. Conclusions: Although our substantive interest was in delirium prevention, the conceptual and methodological strategies pursued have implications for implementing and sustaining practice and service improvements more broadly