Characterizing search, recognition, and decision in the detection of lung nodules on CT scans: elucidation with eye tracking

Application of eye tracking in medicine: A survey, research issues and challenges

The performance and quality of medical procedures and treatments are inextricably linked to technological development. The application of more advanced techniques provides the opportunity to gain wider knowledge and deeper understanding of the human body and mind functioning. The eye tracking methods used to register eye movement to find the direction and targets of a person's gaze are well in line with the nature of the topic. By providing methods for capturing and processing images of the eye it has become possible not only to reveal abnormalities in eye functioning but also to conduct cognitive studies focused on learning about peoples' emotions and intentions. The usefulness of the application of eye tracking technology in medicine was proved in many research studies. The aim of this paper is to give an insight into those studies and the way they utilize eye imaging in medical applications. These studies were differentiated taking their purpose and experimental paradigms into account. Additionally, methods for eye movement visualization and metrics for its quantifying were presented. Apart from presenting the state of the art, the aim of the paper was also to point out possible applications of eye tracking in medicine that have not been exhaustively investigated yet, and are going to be a perspective long-term direction of research.

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.

Variations in the functional visual field for detection of lung nodules on chest computed tomography: Impact of nodule size, distance, and local lung complexity

PURPOSE

To explore the characteristics that impact lung nodule detection by peripheral vision when searching for lung nodules on chest CT-scans.

METHODS

This study was approved by the local IRB and is HIPAA compliant. A simulated primary (1°) target mass (2 × 2 × 5 cm) was embedded into 5 cm thick subvolumes (SV) extracted from three unenhanced lung MDCT scans (64 row, 1.25 mm thickness, 0.7 mm increment). One of 30 solid, secondary nodules with either 3-4 mm and 5-8 mm diameters were embedded into 192 of 207 SVs. The secondary nodule was placed at a random depth within each SV, a transverse distance of 2.5, 5, 7.5, or 10 mm, and along one of eight rays cast every 45° from the center of the 1° mass. Video recordings of transverse paging in cranio-caudal direction were created for each SV (frame rate three sections/sec). Six radiologists observed each cine-loop once while gaze-tracking hardware assured that gaze was centered on the 1° mass. Each radiologist assigned a confidence rating (0-5) to the detection of a secondary nodule and indicated its location. Detection sensitivity was analyzed relative to secondary nodule size, transverse distance, radial orientation, and lung complexity. Lung complexity was characterized by the number of particles (connected pixels) and the sum of the area of all particles above a -500 HU threshold within regions of interest around the 1° mass and secondary nodule.

RESULTS

Using a proportional odds logistic regression model and eliminating redundant predictors, models fit individually to each reader resulted in the following decreasing order of association based on greatest reduction in Akaike Information Criterion: secondary nodule diameter (6/6 readers, P < 0.001), distance from central mass (6/6 readers, P < 0.001), lung complexity particle count (5/6 readers, P = 0.05), and lung complexity particle area (3/6 readers, P = 0.03). Substantial inter-reader differences in sensitivity to decreasing nodule diameter, distance, and complexity characteristics were observed.

CONCLUSIONS

Of the investigated parameters, secondary nodule size, distance from the gaze center and lung complexity (particle number and area) significantly impact nodule detection with peripheral vision.

Tired in the Reading Room: The Influence of Fatigue in Radiology

Commonly conflated with sleepiness, fatigue is a distinct multidimensional condition with physical and mental effects. Fatigue in health care providers and any secondary effects on patient care are an important societal concern. As medical image interpretation is highly dependent on visual input, visual fatigue is of particular interest to radiologists. Humans analyze their surroundings with rapid eye movements called saccades, and fatigue decreases saccadic velocity. Oculomotor parameters may, therefore, be an objective and reproducible metric of fatigue and eye movement analysis can provide valuable insight into the etiology of fatigue-related error.

Radiology resident MR and CT image analysis skill assessment using an interactive volumetric simulation tool - the RadioLOG project

OBJECTIVE

Assess the use of a volumetric simulation tool for the evaluation of radiology resident MR and CT interpretation skills.

MATERIAL AND METHODS

Forty-three participants were evaluated with a software allowing the visualisation of multiple volumetric image series. There were 7 medical students, 28 residents and 8 senior radiologists among the participants. Residents were divided into two sub-groups (novice and advanced). The test was composed of 15 exercises on general radiology and lasted 45 min. Participants answered a questionnaire on their experience with the test using a 5-point Likert scale. This study was approved by the dean of the medical school and did not require ethics committee approval.

RESULTS

The reliability of the test was good with a Cronbach alpha value of 0.9. Test scores were significantly different in all sub-groups studies (p < 0.0225). The relation between test scores and the year of residency was logarithmic (R² = 0.974). Participants agreed that the test reflected their radiological practice (3.9 ± 0.9 on a 5-point scale) and was better than the conventional evaluation methods (4.6 ± 0.5 on a 5-point scale).

CONCLUSION

This software provides a high quality evaluation tool for the assessment of the interpretation skills in radiology residents.

KEY POINTS

• This tool allows volumetric image analysis of MR and CT studies. • A high reliability test could be created with this tool. • Test scores were strongly associated with the examinee expertise level. • Examinees positively evaluated the authenticity and usability of this tool.

Decision Making and Variation in Radiation Exposure Factor Selection by Radiologic Technologists

The goal of radiographic imaging is to produce a diagnostically useful image while minimizing patient radiation dose. This study aimed to review variations in exposure factor selection by radiologic technologists for virtual patients with varying body mass index characteristics. Eleven technologists were asked to assign exposure parameters (kVp, mAs, source-to-image receptor distance, and grid use) to 10 computer-generated patient images for each of four radiographic examinations (anteroposterior [AP] shoulder; AP lumbar spine; lateral lumbar spine; AP portable chest). The virtual patients represented five body mass index categories-underweight, healthy weight, overweight, obese, and superobese. As participants assigned exposures, their visual patterns were recorded by a Tobii TX300 eye-tracker. Significant (P < .05) correlation was found between radiographer age/experience and assignment of mAs for AP shoulder and lumbar examinations. Greater age/experience correlated with higher mAs for the AP shoulder examination, but with lower values for lumbar examinations. Strong correlations also existed between times to first fixations on relevant anatomic areas, and kVp/mAs values existed for the AP portable chest examination. Exposure selection differences related to age/experience highlight inconsistencies in the practice of exposure parameter setting. The reason for these inconsistencies requires further investigation, and how to address deficiencies in practice requires consideration to optimize safe patient care. Because of the small sample size used, further research into the relationship between visual factors and individual examinations is suggested, after the findings regarding the AP portable chest examination.

Lung nodule and cancer detection in computed tomography screening

Fundamental to the diagnosis of lung cancer in computed tomography (CT) scans is the detection and interpretation of lung nodules. As the capabilities of CT scanners have advanced, higher levels of spatial resolution reveal tinier lung abnormalities. Not all detected lung nodules should be reported; however, radiologists strive to detect all nodules that might have relevance to cancer diagnosis. Although medium to large lung nodules are detected consistently, interreader agreement and reader sensitivity for lung nodule detection diminish substantially as the nodule size falls below 8 to 10 mm. The difficulty in establishing an absolute reference standard presents a challenge to the reliability of studies performed to evaluate lung nodule detection. In the interest of improving detection performance, investigators are using eye tracking to analyze the effectiveness with which radiologists search CT scans relative to their ability to recognize nodules within their search path in order to determine whether strategies might exist to improve performance across readers. Beyond the viewing of transverse CT reconstructions, image processing techniques such as thin-slab maximum-intensity projections are used to substantially improve reader performance. Finally, the development of computer-aided detection has continued to evolve with the expectation that one day it will serve routinely as a tireless partner to the radiologist to enhance detection performance without significant prolongation of the interpretive process. This review provides an introduction to the current understanding of these varied issues as we enter the era of widespread lung cancer screening.