Current perspectives in medical image perception

Emerging applications of eye-tracking technology in dermatology

Eye-tracking technology has been used within a multitude of disciplines to provide data linking eye movements to visual processing of various stimuli (i.e., x-rays, situational positioning, printed information, and warnings). Despite the benefits provided by eye-tracking in allowing for the identification and quantification of visual attention, the discipline of dermatology has yet to see broad application of the technology. Notwithstanding dermatologists' heavy reliance upon visual patterns and cues to discriminate between benign and atypical nevi, literature that applies eye-tracking to the study of dermatology is sparse; and literature specific to patient-initiated behaviors, such as skin self-examination (SSE), is largely non-existent. The current article provides a review of eye-tracking research in various medical fields, culminating in a discussion of current applications and advantages of eye-tracking for dermatology research.

Search pattern training for evaluation of central venous catheter positioning on chest radiographs

The goal of this research was to examine whether search pattern training for central line positioning on chest radiographs (CXRs) improves the ability of healthcare trainees and practitioners to identify malpositioned central venous catheters. Two sets of CXRs with central catheters were shown; half of the images contained catheters that were appropriately positioned, half that were malpositioned. Subjects were asked to: mark the tip of the catheter using the simulated radiology workstations, indicate their confidence in tip localization, and state whether the catheter was appropriately positioned or malpositioned. Subjects were also given a survey assessing their thoughts about the usefulness of search pattern training and the simulated radiology workstation. There was a significant improvement in subjects' ability to classify a catheter as malpositioned after training, [Formula: see text]-value = 0.03. There was no significant difference in localization of the catheter tips or in the confidence for tip localization. Subjects' responses to the questionnaire were significantly positive for all statements, indicating that they felt search pattern training using a simulated radiology workstation had a positive impact on their education. These results suggest that our knowledge of medical image perception may be useful for developing rational educational tools for image interpretation, and that simulated radiology workstations may be a helpful means of deploying these tools.

Errors in Mammography Cannot be Solved Through Technology Alone

Mammography has been the frontline screening tool for breast cancer for decades. However, high error rates in the form of false negatives (FNs) and false positives (FPs) have persisted despite technological improvements. Radiologists still miss between 10% and 30% of cancers while 80% of woman recalled for additional views have normal outcomes, with 40% of biopsied lesions being benign. Research show that the majority of cancers missed is actually visible and looked at, but either go unnoticed or are deemed to be benign. Causal agents for these errors include human related characteristics resulting in contributory search, perception and decision-making behaviours. Technical, patient and lesion factors are also important relating to positioning, compression, patient size, breast density and presence of breast implants as well as the nature and subtype of the cancer itself, where features such as architectural distortion and triple-negative cancers remain challenging to detect on screening. A better understanding of these causal agents as well as the adoption of technological and educational interventions, which audits reader performance and provide immediate perceptual feedback, should help. This paper reviews the current status of our knowledge around error rates in mammography and explores the factors impacting it. It also presents potential solutions for maximizing diagnostic efficacy thus benefiting the millions of women who undergo this procedure each year.

A Systematic Review of Fatigue in Radiology: Is It a Problem?

OBJECTIVE

The purpose of this study was to review current literature regarding radiologist fatigue.

MATERIALS AND METHODS

A literature search was performed using PubMed. Key words and Medical Subject Heading terms were used to generate refined queries with inclusion and exclusion criteria, focusing on fatigue and error. Results were selected according to these criteria: examined radiologist fatigue and radiologic error stemming from fatigue; experimental results measured as accuracy, error, or performance; and peer-reviewed publication. The risk of bias was addressed by including both quantitative and qualitative studies.

RESULTS

Twenty-seven articles were included, mainly primary research articles. Common outcome measures included subjective self-reports and tests to measure eyestrain. Reaction time was also recorded, accounting for variables such as age and experience. One group recommended that guidelines should be implemented regarding number of hours worked. Most recommended ergonomic interventions, proposing the implementation of tools to measure and standardize fatigue and optimize workflow, in conjunction with considering radiologists individually. Education in appropriate viewing habits and breaks were also suggested. Only one study with seven participants recommended that radiologists should sleep well to improve their performance and overall well-being, despite the undeniable evidence that radiologists are fatigued.

CONCLUSION

Fatigue is present in radiology and affects diagnostic accuracy.

Getting satisfied with "satisfaction of search": How to measure errors during multiple-target visual search

Visual search studies are common in cognitive psychology, and the results generally focus upon accuracy, response times, or both. Most research has focused upon search scenarios where no more than 1 target will be present for any single trial. However, if multiple targets can be present on a single trial, it introduces an additional source of error because the found target can interfere with subsequent search performance. These errors have been studied thoroughly in radiology for decades, although their emphasis in cognitive psychology studies has been more recent. One particular issue with multiple-target search is that these subsequent search errors (i.e., specific errors which occur following a found target) are measured differently by different studies. There is currently no guidance as to which measurement method is best or what impact different measurement methods could have upon various results and conclusions. The current investigation provides two efforts to address these issues. First, the existing literature is reviewed to clarify the appropriate scenarios where subsequent search errors could be observed. Second, several different measurement methods are used with several existing datasets to contrast and compare how each method would have affected the results and conclusions of those studies. The evidence is then used to provide appropriate guidelines for measuring multiple-target search errors in future studies.

Evaluation of Search Strategies for Microcalcifications and Masses in 3D Images

Medical imaging is quickly evolving towards 3D image modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and digital breast tomosynthesis (DBT). These 3D image modalities add volumetric information but further increase the need for radiologists to search through the image data set. Although much is known about search strategies in 2D images less is known about the functional consequences of different 3D search strategies. We instructed readers to use two different search strategies: drillers had their eye movements restricted to a few regions while they quickly scrolled through the image stack, scanners explored through eye movements the 2D slices. We used real-time eye position monitoring to ensure observers followed the drilling or the scanning strategy while approximately preserving the percentage of the volumetric data covered by the useful field of view. We investigated search for two signals: a simulated microcalcification and a larger simulated mass. Results show an interaction between the search strategy and lesion type. In particular, scanning provided significantly better detectability for microcalcifications at the cost of 5 times more time to search while there was little change in the detectability for the larger simulated masses. Analyses of eye movements support the hypothesis that the effectiveness of a search strategy in 3D imaging arises from the interaction of the fixational sampling of visual information and the signals' visibility in the visual periphery.

Quantifying Novice and Expert Differences in Visual Diagnostic Reasoning in Veterinary Pathology Using Eye-Tracking Technology

Visual diagnostic reasoning is the cognitive process by which pathologists reach a diagnosis based on visual stimuli (cytologic, histopathologic, or gross imagery). Currently, there is little to no literature examining visual reasoning in veterinary pathology. The objective of the study was to use eye tracking to establish baseline quantitative and qualitative differences between the visual reasoning processes of novice and expert veterinary pathologists viewing cytology specimens. Novice and expert participants were each shown 10 cytology images and asked to formulate a diagnosis while wearing eye-tracking equipment (10 slides) and while concurrently verbalizing their thought processes using the think-aloud protocol (5 slides). Compared to novices, experts demonstrated significantly higher diagnostic accuracy (p <.017), shorter time to diagnosis (p <.017), and a higher percentage of time spent viewing areas of diagnostic interest (p <.017). Experts elicited more key diagnostic features in the think-aloud protocol and had more efficient patterns of eye movement. These findings suggest that experts' fast time to diagnosis, efficient eye-movement patterns, and preference for viewing areas of interest supports system 1 (pattern-recognition) reasoning and script-inductive knowledge structures with system 2 (analytic) reasoning to verify their diagnosis.

Minds treating brains: understanding the interpretation of non-contrast CT ASPECTS in acute ischemic stroke

INTRODUCTION

The Alberta Stroke Program Early CT Score on non-contrast CT is a key component of prognostication and treatment selection in acute stroke care. Previous findings show that the reliability of this scale must be improved to maximize its clinical utility. Areas covered: This review discusses technical, patient-level, and reader-level sources of variability in ASPECTS reading; relevant concepts in the psychology of medical image perception; and potential interventions likely to improve inter- and intra-rater reliability. Expert commentary: Approaching variability in medical decision making from a psychological perspective will afford cognitively informed insights into the development of interventions and training techniques aimed at improving this issue.

Automatic CDR Estimation for Early Glaucoma Diagnosis

Glaucoma is a degenerative disease that constitutes the second cause of blindness in developed countries. Although it cannot be cured, its progression can be prevented through early diagnosis. In this paper, we propose a new algorithm for automatic glaucoma diagnosis based on retinal colour images. We focus on capturing the inherent colour changes of optic disc (OD) and cup borders by computing several colour derivatives in CIE L^∗a^∗b^∗ colour space with CIE94 colour distance. In addition, we consider spatial information retaining these colour derivatives and the original CIE L^∗a^∗b^∗ values of the pixel and adding other characteristics such as its distance to the OD centre. The proposed strategy is robust due to a simple structure that does not need neither initial segmentation nor removal of the vascular tree or detection of vessel bends. The method has been extensively validated with two datasets (one public and one private), each one comprising 60 images of high variability of appearances. Achieved class-wise-averaged accuracy of 95.02% and 81.19% demonstrates that this automated approach could support physicians in the diagnosis of glaucoma in its early stage, and therefore, it could be seen as an opportunity for developing low-cost solutions for mass screening programs.

Influence of radiology expertise on the perception of nonmedical images

Identifying if participants with differing diagnostic accuracy and visual search behavior during radiologic tasks also differ in nonradiologic tasks is investigated. Four clinician groups with different radiologic experience were used: a reference expert group of five consultant radiologists, four radiology registrars, five senior house officers, and six interns. Each of the four clinician groups is known to have significantly different performance in the identification of pneumothoraces in chest x-ray. Each of the 20 participants was shown 6 nonradiologic images (3 maps and 3 sets of geometric shapes) and was asked to perform search tasks. Eye movements were recorded with a Tobii TX300 (Tobii Technology, Stockholm, Sweden) eye tracker. Four eye-tracking metrics were analyzed. Variables were compared to identify any differences among the groups. All data were compared by using nonparametric methods of analysis. The average number of targets identified in the maps did not change among groups [mean=5.8 of 6 targets (range 5.6 to 6 p=0.861)]. None of the four eye-tracking metrics investigated varied with experience in either search task (p>0.5). Despite clear differences in radiologic experience, these clinician groups showed no difference in nonradiologic search pattern behavior or skill across complex images. This is another viewpoint adding to the evidence that radiologic image interpretation is a learned skill and is task specific.

The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review

In the field of medical image perception, the holistic processing perspective contends that experts can rapidly extract global information about the image, which can be used to guide their subsequent search of the image (Swensson, 1980; Nodine and Kundel, 1987; Kundel et al., 2007). In this review, we discuss the empirical evidence supporting three different predictions that can be derived from the holistic processing perspective: Expertise in medical image perception is domain-specific, experts use parafoveal and/or peripheral vision to process large regions of the image in parallel, and experts benefit from a rapid initial glimpse of an image. In addition, we discuss a pivotal recent study (Litchfield and Donovan, 2016) that seems to contradict the assumption that experts benefit from a rapid initial glimpse of the image. To reconcile this finding with the existing literature, we suggest that global processing may serve multiple functions that extend beyond the initial glimpse of the image. Finally, we discuss future research directions, and we highlight the connections between the holistic processing account and similar theoretical perspectives and findings from other domains of visual expertise.

Perceptual errors in pediatric radiology

Perceptual errors are common contributors to missed diagnoses in the clinical practice of radiology. While the physical attributes of an image such as image resolution, signal-to-noise characteristics, and anatomic complexity are major causes of poor conspicuity of pathologic lesions, there are major interrelated cognitive contributors to visual errors. The first is satisfaction of search (SOS), where the detection of an abnormality results in premature termination of further search. Another form of incomplete search pattern is visual isolation, where a radiologist's search pattern is truncated to the main areas of an image, while little or no attention is given to peripheral areas. A second cognitive error is inattentional blindness, defined as the failure to notice a fully visible, but unexpected object because attention was otherwise engaged. Strategies for error mitigation have centered around the use of check lists, self prompting routines, and structured reporting within an institutional culture of safety and vigilance.

How visual search relates to visual diagnostic performance: a narrative systematic review of eye-tracking research in radiology

Eye tracking research has been conducted for decades to gain understanding of visual diagnosis such as in radiology. For educational purposes, it is important to identify visual search patterns that are related to high perceptual performance and to identify effective teaching strategies. This review of eye-tracking literature in the radiology domain aims to identify visual search patterns associated with high perceptual performance. Databases PubMed, EMBASE, ERIC, PsycINFO, Scopus and Web of Science were searched using 'visual perception' OR 'eye tracking' AND 'radiology' and synonyms. Two authors independently screened search results and included eye tracking studies concerning visual skills in radiology published between January 1, 1994 and July 31, 2015. Two authors independently assessed study quality with the Medical Education Research Study Quality Instrument, and extracted study data with respect to design, participant and task characteristics, and variables. A thematic analysis was conducted to extract and arrange study results, and a textual narrative synthesis was applied for data integration and interpretation. The search resulted in 22 relevant full-text articles. Thematic analysis resulted in six themes that informed the relation between visual search and level of expertise: (1) time on task, (2) eye movement characteristics of experts, (3) differences in visual attention, (4) visual search patterns, (5) search patterns in cross sectional stack imaging, and (6) teaching visual search strategies. Expert search was found to be characterized by a global-focal search pattern, which represents an initial global impression, followed by a detailed, focal search-to-find mode. Specific task-related search patterns, like drilling through CT scans and systematic search in chest X-rays, were found to be related to high expert levels. One study investigated teaching of visual search strategies, and did not find a significant effect on perceptual performance. Eye tracking literature in radiology indicates several search patterns are related to high levels of expertise, but teaching novices to search as an expert may not be effective. Experimental research is needed to find out which search strategies can improve image perception in learners.

Redefining the Practice of Peer Review Through Intelligent Automation Part 1: Creation of a Standardized Methodology and Referenceable Database

Conventional peer review practice is compromised by a number of well-documented biases, which in turn limit standard of care analysis, which is fundamental to determination of medical malpractice. In addition to these intrinsic biases, other existing deficiencies exist in current peer review including the lack of standardization, objectivity, retrospective practice, and automation. An alternative model to address these deficiencies would be one which is completely blinded to the peer reviewer, requires independent reporting from both parties, utilizes automated data mining techniques for neutral and objective report analysis, and provides data reconciliation for resolution of finding-specific report differences. If properly implemented, this peer review model could result in creation of a standardized referenceable peer review database which could further assist in customizable education, technology refinement, and implementation of real-time context and user-specific decision support.

Colour in digital pathology: a review

Colour is central to the practice of pathology because of the use of coloured histochemical and immunohistochemical stains to visualize tissue features. Our reliance upon histochemical stains and light microscopy has evolved alongside a wide variation in slide colour, with little investigation into the implications of colour variation. However, the introduction of the digital microscope and whole-slide imaging has highlighted the need for further understanding and control of colour. This is because the digitization process itself introduces further colour variation which may affect diagnosis, and image analysis algorithms often use colour or intensity measures to detect or measure tissue features. The US Food and Drug Administration have released recent guidance stating the need to develop a method of controlling colour reproduction throughout the digitization process in whole-slide imaging for primary diagnostic use. This comprehensive review introduces applied basic colour physics and colour interpretation by the human visual system, before discussing the importance of colour in pathology. The process of colour calibration and its application to pathology are also included, as well as a summary of the current guidelines and recommendations regarding colour in digital pathology.

The wisdom of crowds for visual search

Decision-making accuracy typically increases through collective integration of people's judgments into group decisions, a phenomenon known as the wisdom of crowds. For simple perceptual laboratory tasks, classic signal detection theory specifies the upper limit for collective integration benefits obtained by weighted averaging of people's confidences, and simple majority voting can often approximate that limit. Life-critical perceptual decisions often involve searching large image data (e.g., medical, security, and aerial imagery), but the expected benefits and merits of using different pooling algorithms are unknown for such tasks. Here, we show that expected pooling benefits are significantly greater for visual search than for single-location perceptual tasks and the prediction given by classic signal detection theory. In addition, we show that simple majority voting obtains inferior accuracy benefits for visual search relative to averaging and weighted averaging of observers' confidences. Analysis of gaze behavior across observers suggests that the greater collective integration benefits for visual search arise from an interaction between the foveated properties of the human visual system (high foveal acuity and low peripheral acuity) and observers' nonexhaustive search patterns, and can be predicted by an extended signal detection theory framework with trial to trial sampling from a varying mixture of high and low target detectabilities across observers (SDT-MIX). These findings advance our theoretical understanding of how to predict and enhance the wisdom of crowds for real world search tasks and could apply more generally to any decision-making task for which the minority of group members with high expertise varies from decision to decision.

Computing eye gaze metrics for the automatic assessment of radiographer performance during X-ray image interpretation

AIM

To investigate image interpretation performance by diagnostic radiography students, diagnostic radiographers and reporting radiographers by computing eye gaze metrics using eye tracking technology.

METHODS

Three groups of participants were studied during their interpretation of 8 digital radiographic images including the axial and appendicular skeleton, and chest (prevalence of normal images was 12.5%). A total of 464 image interpretations were collected. Participants consisted of 21 radiography students, 19 qualified radiographers and 18 qualified reporting radiographers who were further qualified to report on the musculoskeletal (MSK) system.

OUTCOME MEASURES

Eye tracking data was collected using the Tobii X60 eye tracker and subsequently eye gaze metrics were computed. Voice recordings, confidence levels and diagnoses provided a clear demonstration of the image interpretation and the cognitive processes undertaken by each participant. A questionnaire afforded the participants an opportunity to offer information on their experience in image interpretation and their opinion on the eye tracking technology.

RESULTS

Reporting radiographers demonstrated a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took a mean of 2.4s longer to clinically decide on all features compared to students. Reporting radiographers also had a 15% greater accuracy rate (p≤0.001), were more confident (p≤0.001) and took longer to clinically decide on an image diagnosis (p=0.02) than radiographers. Reporting radiographers had a greater mean fixation duration (p=0.01), mean fixation count (p=0.04) and mean visit count (p=0.04) within the areas of pathology compared to students. Eye tracking patterns, presented within heat maps, were a good reflection of group expertise and search strategies. Eye gaze metrics such as time to first fixate, fixation count, fixation duration and visit count within the areas of pathology were indicative of the radiographer's competency.

CONCLUSION

The accuracy and confidence of each group could be reflected in the variability of their eye tracking heat maps. Participants' thoughts and decisions were quantified using the eye tracking data. Eye tracking metrics also reflected the different search strategies that each group of participants adopted during their image interpretations. This is the first study to use eye tracking technology to assess image interpretation skills between various groups of different levels of experience in radiography, especially on a combination of the MSK system, chest cavity and a variety of pathologies.

Workflows and individual differences during visually guided routine tasks in a road traffic management control room

Road traffic control rooms rely on human operators to monitor and interact with information presented on multiple displays. Past studies have found inconsistent use of available visual information sources in such settings across different domains. In this study, we aimed to broaden the understanding of observer behaviour in control rooms by analysing a case study in road traffic control. We conducted a field study in a live road traffic control room where five operators responded to incidents while wearing a mobile eye tracker. Using qualitative and quantitative approaches, we investigated the operators' workflow using ergonomics methods and quantified visual information sampling. We found that individuals showed differing preferences for viewing modalities and weighting of task components, with a strong coupling between eye and head movement. For the quantitative analysis of the eye tracking data, we propose a number of metrics which may prove useful to compare visual sampling behaviour across domains in future.

Comparative study of computational visual attention models on two-dimensional medical images

Computational modeling of visual attention is an active area of research. These models have been successfully employed in applications such as robotics. However, most computational models of visual attention are developed in the context of natural scenes, and their role with medical images is not well investigated. As radiologists interpret a large number of clinical images in a limited time, an efficient strategy to deploy their visual attention is necessary. Visual saliency maps, highlighting image regions that differ dramatically from their surroundings, are expected to be predictive of where radiologists fixate their gaze. We compared 16 state-of-art saliency models over three medical imaging modalities. The estimated saliency maps were evaluated against radiologists' eye movements. The results show that the models achieved competitive accuracy using three metrics, but the rank order of the models varied significantly across the three modalities. Moreover, the model ranks on the medical images were all considerably different from the model ranks on the benchmark MIT300 dataset of natural images. Thus, modality-specific tuning of saliency models is necessary to make them valuable for applications in fields such as medical image compression and radiology education.

Fractal analysis of visual search activity for mass detection during mammographic screening

PURPOSE

The objective of this study was to assess the complexity of human visual search activity during mammographic screening using fractal analysis and to investigate its relationship with case and reader characteristics.

METHODS

The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) from 10 readers (three board certified radiologists and seven Radiology residents), formed the corpus for this study. The fractal dimension of the readers' visual scanning pattern was computed with the Minkowski-Bouligand box-counting method and used as a measure of gaze complexity. Individual factor and group-based interaction ANOVA analysis was performed to study the association between fractal dimension, case pathology, breast density, and reader experience level. The consistency of the observed trends depending on gaze data representation was also examined.

RESULTS

Case pathology, breast density, reader experience level, and individual reader differences are all independent predictors of the complexity of visual scanning pattern when screening for breast cancer. No higher order effects were found to be significant.

CONCLUSIONS

Fractal characterization of visual search behavior during mammographic screening is dependent on case properties and image reader characteristics.

Exploring eye movements of experienced and novice readers of medical texts concerning the cardiovascular system in making a diagnosis

This study used the eye-tracking method to explore how the level of expertise influences reading, and solving, two written patient cases on cardiac failure and pulmonary embolus. Eye-tracking is a fairly commonly used method in medical education research, but it has been primarily applied to studies analyzing the processing of visualizations, such as medical images or patient video cases. Third-year medical students (n = 39) and residents (n = 13) read two patient case texts in an eye-tracking laboratory. The analysis focused on the diagnosis made, the total visit duration per text slide, and eye-movement indicators regarding task-relevant and task-redundant areas of the patient case text. The results showed that almost all participants (48/52) made the correct diagnosis of the first patient case, whereas all the residents, but only 17 students, correctly diagnosed the second case. The residents were efficient patient-case-solvers: they reached the correct diagnoses, and processed the cases faster and with a lower number of fixations than did the students. Further, the students and residents demonstrated different reading patterns with regard to which slides they proportionally paid most attention. The observed differences could be utilized in medical education to model expert reasoning and to teach the manner in which a good medical text is constructed. Eye-tracking methodology appears to have a great deal of potential in evaluating performance and growing diagnostic expertise in reading medical texts. However, further research using medical texts as stimuli is required. Anat Sci Educ 10: 23-33. © 2016 American Association of Anatomists.

The challenges of studying visual expertise in medical image diagnosis

CONTEXT

Visual expertise is the superior visual skill shown when executing domain-specific visual tasks. Understanding visual expertise is important in order to understand how the interpretation of medical images may be best learned and taught. In the context of this article, we focus on the visual skill of medical image diagnosis and, more specifically, on the methodological set-ups routinely used in visual expertise research.

METHODS

We offer a critique of commonly used methods and propose three challenges for future research to open up new avenues for studying characteristics of visual expertise in medical image diagnosis. The first challenge addresses theory development. Novel prospects in modelling visual expertise can emerge when we reflect on cognitive and socio-cultural epistemologies in visual expertise research, when we engage in statistical validations of existing theoretical assumptions and when we include social and socio-cultural processes in expertise development. The second challenge addresses the recording and analysis of longitudinal data. If we assume that the development of expertise is a long-term phenomenon, then it follows that future research can engage in advanced statistical modelling of longitudinal expertise data that extends the routine use of cross-sectional material through, for example, animations and dynamic visualisations of developmental data. The third challenge addresses the combination of methods. Alternatives to current practices can integrate qualitative and quantitative approaches in mixed-method designs, embrace relevant yet underused data sources and understand the need for multidisciplinary research teams.

CONCLUSION

Embracing alternative epistemological and methodological approaches for studying visual expertise can lead to a more balanced and robust future for understanding superior visual skills in medical image diagnosis as well as other medical fields.

Use-inspired basic research in medical image perception

This journal is dedicated to "use-inspired basic research" where a problem in the world shapes the hypotheses for a study in the laboratory. This brief review presents several examples of "use-inspired basic research" in the area of medical image perception. These are cases where the field of radiology raises an interesting issue in visual cognition. Basic research on those issues may then lead to proposals to improve performance on clinical tasks in medical image perception. Of the six examples given here, the first three ask essentially perceptual questions: How can stereopsis improve medical image perception? How shall we assess the tradeoff between radiation dose and image quality? How does the choice of colors change the interpretation of medical images? The second three examples address attentional issues in those aspects of radiology that can be described as visual search problems: Can eye tracking help us understand errors in radiologic search? What happens if the number of targets in an image is unknown? What happens if, as in radiology screening programs, the target of search is very rare?

Temporal Characteristics of Radiologists' and Novices' Lesion Detection in Viewing Medical Images Presented Rapidly and Sequentially

Although viewing multiple stacks of medical images presented on a display is a relatively new but useful medical task, little is known about this task. Particularly, it is unclear how radiologists search for lesions in this type of image reading. When viewing cluttered and dynamic displays, continuous motion itself does not capture attention. Thus, it is effective for the target detection that observers' attention is captured by the onset signal of a suddenly appearing target among the continuously moving distractors (i.e., a passive viewing strategy). This can be applied to stack viewing tasks, because lesions often show up as transient signals in medical images which are sequentially presented simulating a dynamic and smoothly transforming image progression of organs. However, it is unclear whether observers can detect a target when the target appears at the beginning of a sequential presentation where the global apparent motion onset signal (i.e., signal of the initiation of the apparent motion by sequential presentation) occurs. We investigated the ability of radiologists to detect lesions during such tasks by comparing the performances of radiologists and novices. Results show that overall performance of radiologists is better than novices. Furthermore, the temporal locations of lesions in CT image sequences, i.e., when a lesion appears in an image sequence, does not affect the performance of radiologists, whereas it does affect the performance of novices. Results indicate that novices have greater difficulty in detecting a lesion appearing early than late in the image sequence. We suggest that radiologists have other mechanisms to detect lesions in medical images with little attention which novices do not have. This ability is critically important when viewing rapid sequential presentations of multiple CT images, such as stack viewing tasks.

A simple algorithm for the offline recalibration of eye-tracking data through best-fitting linear transformation

Poor calibration and inaccurate drift correction can pose severe problems for eye-tracking experiments requiring high levels of accuracy and precision. We describe an algorithm for the offline correction of eye-tracking data. The algorithm conducts a linear transformation of the coordinates of fixations that minimizes the distance between each fixation and its closest stimulus. A simple implementation in MATLAB is also presented. We explore the performance of the correction algorithm under several conditions using simulated and real data, and show that it is particularly likely to improve data quality when many fixations are included in the fitting process.

Local diagnostic reference levels for intraoral dental radiography in the public hospitals of Cyprus

PURPOSE

The purpose of this study was to determine local DRLs for children and adults undergoing intraoral dental examinations at the intraoral radiology units of the public hospitals in Cyprus.

METHODS

Measurements were made on all the twenty intraoral X-ray units of the public hospitals in Cyprus with the intention to establish the local DRLs for all the possible intraoral X-ray examinations for children and adults. All units are film based. The measurements were made by a Dose Area Product (DAP) meter (GAMMEX RMI 841-RD) placed at the surface of the dental unit's X-ray shaping cone (FSD 20cm). A diagnostic radiology dosimeter (Dosimax Plus A) was also placed at an FSD of 100cm to compare the dose reading between the two dosimeters.

RESULTS

DRLs were established at the 3rd quartile for 7 exposure settings corresponding to 12 types of teeth (Adult and children mandibular and maxillary incisor, premolar and molar) with values of 197, 163, 128, 102, 81, 65 and 49mGycm^-2 and 7.23, 5.94, 4.75, 3.68, 3.10, 2.41 and 1.88mGy for benchmark nominal exposure times of 1000, 800, 640, 500, 400, 320 and 250ms respectively, at a nominal exposure voltage of 70kVp.

CONCLUSIONS

The local DRLs of the present study compare well with other similar published DRLs.

A 'snapshot' of the visual search behaviours of medical sonographers

Introduction: Visual search is a task that humans perform in everyday life. Whether it involves looking for a pen on a desk or a mass in a mammogram, the cognitive and perceptual processes that underpin these tasks are identical. Radiologists are experts in visual search of medical images and studies on their visual search behaviours have revealed some interesting findings with regard to diagnostic errors. In Australia, within the modality of ultrasound, sonographers perform the diagnostic scan, select images and present to the radiologist for reporting. Therefore the visual task and potential for errors is similar to a radiologist. Our aim was to explore and understand the detection, localisation and eye‐gaze behaviours of a group of qualified sonographers.

Method: We measured clinical performance and analysed diagnostic errors by presenting fifty sonographic breast images that varied on cancer present and degree of difficulty to a group of sonographers in their clinical workplace. For a sub‐set of sonographers we obtained eye‐tracking metrics such as time‐to‐first fixation, total visit duration and cumulative dwell time heat maps. Results: The results indicate that the sonographers' clinical performance was high and the eye‐tracking metrics showed diagnostic error types similar to those found in studies on radiologist visual search.

Conclusion: This study informs us about sonographer visual search patterns and highlights possible ways to improve diagnostic performance via targeted education.

The frequency of incidental pulmonary embolism in different CT examinations

OBJECTIVE

Pulmonary embolism (PE) is commonly found in patients with oncologic and non-oncologic disease. The aim of the present study is to assess how frequently suspected, incidental and unreported PE occurs in particular CT examinations. In addition, differences in embolus distribution are to be considered.

METHODS

In a retrospective, single-centre study that covered a 5.5-year period, every contrast-enhanced CT examination was reviewed. The study group included 7238 patients with 11,747 CT examinations. A detailed pulmonary artery obstruction index (Mastora score) was used to assess thrombus mass and distribution.

RESULTS

PE frequency was 3.9% in oncologic patients and 6.6% in non-oncologic patients. PE was unsuspected in 54% of all PE events. Incidental PE was mostly often found in the following CT examinations: evaluation of acute pulmonary disease and follow-up staging. The thrombus mass was higher in non-oncologic patients than in oncologic patients. Furthermore, the thrombus mass was significantly lower in unsuspected PE than in suspected PE. In addition, the thrombus mass was significantly lower in unreported PE than in incidental PE.

CONCLUSION

The radiologist should pay special attention to pulmonary vessels, even when not asked for PE, in the following CT examinations: evaluation of acute pulmonary disease and follow-up staging.

ADVANCES IN KNOWLEDGE

Particular CT indications are associated with a high frequency of PE. Whether PE is suspected or not and found or not highly depends on thrombus mass.

Multiple-Target Visual Search Errors

Visual search—the ability to locate visual targets among distractors—is a fundamental part of professional performance for many careers, including radiology, airport security screening, cytology, lifeguarding, and more. Successful execution of visual search in these settings is critically important because the consequences of a missed target can be horrific. Unfortunately, many of these professions place high demands on the people performing the searches, and either the task or the environment (or both) could lead to significant errors. One known source of error that exists across many fields is “multiple-target visual search” errors—a target is less likely to be detected if another target was already found in the same search than if the target was the only one present. These errors have proven to be stubborn and not easily eliminated. This article offers a brief overview of the existing research on multiple-target visual search errors and discusses possible policy implications of the errors for airport security screening. The policy suggestions are based on empirical research, with the hope of providing food for thought on using scientific data and theory to improve performance. Specifically, three policy suggestions are raised: shift screening to a remote location away from the checkpoint, reduce the number of prohibited items to lessen the searchers’ cognitive burden, and emphasize search consistency in the training process. Note that the focus here is on airport security screening, as this is a domain most readers can relate to, but the suggestions can equally apply to many search environments.

Error propagation in the characterization of atheromatic plaque types based on imaging

Imaging systems transmit and acquire signals and are subject to errors including: error sources, signal variations or possible calibration errors. These errors are included in all imaging systems for atherosclerosis and are propagated to methodologies implemented for the segmentation and characterization of atherosclerotic plaque. In this paper, we present a study for the propagation of imaging errors and image segmentation errors in plaque characterization methods applied to 2D vascular images. More specifically, the maximum error that can be propagated to the plaque characterization results is estimated, assuming worst-case scenarios. The proposed error propagation methodology is validated using methods applied to real datasets, obtained from intravascular imaging (IVUS) and optical coherence tomography (OCT) for coronary arteries, and magnetic resonance imaging (MRI) for carotid arteries. The plaque characterization methods have recently been presented in the literature and are able to detect the vessel borders, and characterize the atherosclerotic plaque types. Although, these methods have been extensively validated using as gold standard expert annotations, by applying the proposed error propagation methodology a more realistic validation is performed taking into account the effect of the border detection algorithms error and the image formation error into the final results. The Pearson's coefficient of the detected plaques has changed significantly when the method was applied to IVUS and OCT, while there was not any variation when the method was applied to MRI data.

Sustained effect of simulation-based ultrasound training on clinical performance: a randomized trial

OBJECTIVE

To study the effect of initial simulation-based transvaginal sonography (TVS) training compared with clinical training only, on the clinical performance of residents in obstetrics and gynecology (Ob-Gyn), assessed 2 months into their residency.

METHODS

In a randomized study, new Ob-Gyn residents (n = 33) with no prior ultrasound experience were recruited from three teaching hospitals. Participants were allocated to either simulation-based training followed by clinical training (intervention group; n = 18) or clinical training only (control group; n = 15). The simulation-based training was performed using a virtual-reality TVS simulator until an expert performance level was attained, and was followed by training on a pelvic mannequin. After 2 months of clinical training, one TVS examination was recorded for assessment of each resident's clinical performance (n = 26). Two ultrasound experts blinded to group allocation rated the scans using the Objective Structured Assessment of Ultrasound Skills (OSAUS) scale.

RESULTS

During the 2 months of clinical training, participants in the intervention and control groups completed an average ± SD of 58 ± 41 and 63 ± 47 scans, respectively (P = 0.67). In the subsequent clinical performance test, the intervention group achieved higher OSAUS scores than did the control group (mean score, 59.1% vs 37.6%, respectively; P < 0.001). A greater proportion of the intervention group passed a pre-established pass/fail level than did controls (85.7% vs 8.3%, respectively; P < 0.001).

CONCLUSION

Simulation-based ultrasound training leads to substantial improvement in clinical performance that is sustained after 2 months of clinical training. © 2015 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Hidden costs of poor image quality: a radiologist's perspective

Although image quality is a well-recognized component in the successful delivery of medical imaging services, it has arguably declined over the past decade owing to several technical, economic, cultural, and geographic factors. To improve quality, the radiologist community must take a more proactive role in image quality analysis and optimization; these require analysis of not just the single step of image acquisition but the entire imaging chain. Radiologists can benefit through improved report accuracy, diagnostic confidence, and workflow efficiency. The derived data-driven analyses offer an objective means for provider performance analysis, which can help combat commoditization trends and self-referral by nonradiologist providers.