Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

Development of model observers applied to 3D breast tomosynthesis microcalcifications and masses

The development of model observers for mimicking human detection strategies has followed from symmetric signals in simple noise to increasingly complex backgrounds. In this study we implement different model observers for the complex task of detecting a signal in a 3D image stack. The backgrounds come from real breast tomosynthesis acquisitions and the signals were simulated and reconstructed within the volume. Two different tasks relevant to the early detection of breast cancer were considered: detecting an 8 mm mass and detecting a cluster of microcalcifications. The model observers were calculated using a channelized Hotelling observer (CHO) with dense difference-of-Gaussian channels, and a modified (Partial prewhitening [PPW]) observer which was adapted to realistic signals which are not circularly symmetric. The sustained temporal sensitivity function was used to filter the images before applying the spatial templates. For a frame rate of five frames per second, the only CHO that we calculated performed worse than the humans in a 4-AFC experiment. The other observers were variations of PPW and outperformed human observers in every single case. This initial frame rate was a rather low speed and the temporal filtering did not affect the results compared to a data set with no human temporal effects taken into account. We subsequently investigated two higher speeds at 5, 15 and 30 frames per second. We observed that for large masses, the two types of model observers investigated outperformed the human observers and would be suitable with the appropriate addition of internal noise. However, for microcalcifications both only the PPW observer consistently outperformed the humans. The study demonstrated the possibility of using a model observer which takes into account the temporal effects of scrolling through an image stack while being able to effectively detect a range of mass sizes and distributions.

The genome sequence of taurine cattle: a window to ruminant biology and evolution.

To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Simulated Patient as Co-facilitators: Benefits and Challenges of the Interprofessional Team OSCE (Submission #9350).

Hypothesis: The quality of care for chronic patients depends on the collaborative skills of the healthcare providers.1,2 The literature lacks reports of the use of simulation to teach collaborative skills in non-acute care settings. We posit that simulation offers benefits for supporting the development of collaborative practice in non-acute settings. We explored the benefits and challenges of using an Interprofessional Team - Objective Structured Clinical Examination (IT-OSCE) as a formative assessment tool. IT-OSCE is an intervention which involves an interprofessional team of trainees interacting with a simulated patient (SP) enabling them to practice collaborative skills in non-acute care settings.5 A simulated patient are people trained to portray patients in a simulated scenario for educational purposes.6,7 Since interprofessional education (IPE) ultimately aims to provide collaborative patient-centered care.8,9 We sought to promote patient-centeredness in the learning process. Methods: The IT-OSCE was conducted with four trios of students from different professions. The debriefing was co-facilitated by the SP with a faculty. The participants were final-year students in nursing, physiotherapy and medicine. Our research question focused on the introduction of co-facilitated (SP and faculty) debriefing after an IT-OSCE: 1) What are the benefits and challenges of involving the SP during the debriefing? and 2) To evaluate the IT-OSCE, an exploratory case study was used to provide fine grained data 10, 11. Three focus groups were conducted - two with students (n=6; n=5), one with SPs (n=3) and one with faculty (n=4). Audiotapes were transcribed for thematic analysis performed by three researchers, who found a consensus on the final set of themes. Results: The thematic analysis showed little differentiation between SPs, student and faculty perspectives. The analysis of transcripts revealed more particularly, that the SP's co-facilitation during the debriefing of an IT-OSCE proved to be feasible. It was appreciated by all the participants and appeared to value and to promote patient-centeredness in the learning process. The main challenge consisted in SPs feedback, more particularly in how they could report accurate observations to a students' group rather than individual students. Conclusion: In conclusion, SP methodology using an IT-OSCE seems to be a useful and promising way to train collaborative skills, aligning IPE, simulation-based team training in a non-acute care setting and patient-centeredness. We acknowledge the limitations of the study, especially the small sample and consider the exploration of SP-based IPE in non-acute care settings as strength. Future studies could consider the preparation of SPs and faculty as co-facilitators. References: 1. Borrill CS, Carletta J, Carter AJ, et al. The effectiveness of health care teams in the National Health Service. Aston centre for Health Service Organisational Research. 2001. 2. Reeves S, Lewin S, Espin S, Zwarenstein M. Interprofessional teamwork for health and social care. Oxford: Wiley-Blackwell; 2010. 3. Issenberg S, McGaghie WC, Petrusa ER, Gordon DL, Scalese RJ. Features and uses of high-fidelity medical simulations that lead to effective learning - a BEME systematic review. Medical Teacher. 2005;27(1):10-28. 4. McGaghie W, Petrusa ER, Gordon DL, Scalese RJ. A critical review of simulation-based medical education research: 2003-2009. Medical Education. 2010;44(1):50-63. 5. Simmons B, Egan-Lee E, Wagner SJ, Esdaile M, Baker L, Reeves S. Assessment of interprofessional learning: the design of an interprofessional objective structured clinical examination (iOSCE) approach. Journal of Interprofessional Care. 2011;25(1):73-74. 6. Nestel D, Layat Burn C, Pritchard SA, Glastonbury R, Tabak D. The use of simulated patients in medical education: Guide Supplement 42.1 - Viewpoint. Medical teacher. 2011;33(12):1027-1029. Disclosures: None (C) 2014 by Lippincott Williams & Wilkins, Inc.