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In online lectures, unlike in face-to-face lectures, teachers lack access to (nonverbal) cues to check if their students are still "with them" and comprehend the lecture. The increasing availability of low-cost eye-trackers provides a promising solution. These devices measure unobtrusively where students look and can visualize these data to teachers. These visualizations might inform teachers about students' level of "with-me-ness" (i.e., do students look at the information that the teacher is currently talking about) and comprehension of the lecture, provided that (1) gaze measures of "with-me-ness" are related to comprehension, (2) people not trained in eye-tracking can predict students' comprehension from gaze visualizations, (3) we understand how different visualization techniques impact this prediction. We addressed these issues in two studies. In Study 1, 36 students watched a video lecture while being eye-tracked. The extent to which students looked at relevant information and the extent to which they looked at the same location as the teacher both correlated with students' comprehension (score on an open question) of the lecture. In Study 2, 50 participants watched visualizations of students' gaze (from Study 1), using six visualization techniques (dynamic and static versions of scanpaths, heatmaps, and focus maps) and were asked to predict students' posttest performance and to rate their ease of prediction. We found that people can use gaze visualizations to predict learners' comprehension above chance level, with minor differences between visualization techniques. Further research should investigate if teachers can act on the information provided by gaze visualizations and thereby improve students' learning., (© 2022 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Radiologists can visually detect abnormalities on radiographs within 2s, a process that resembles holistic visual processing of faces. Interestingly, there is empirical evidence using functional magnetic resonance imaging (fMRI) for the involvement of the right fusiform face area (FFA) in visual-expertise tasks such as radiological image interpretation. The speed by which stimuli (e.g., faces, abnormalities) are recognized is an important characteristic of holistic processing. However, evidence for the involvement of the right FFA in holistic processing in radiology comes mostly from short or artificial tasks in which the quick, 'holistic' mode of diagnostic processing is not contrasted with the slower 'search-to-find' mode. In our fMRI study, we hypothesized that the right FFA responds selectively to the 'holistic' mode of diagnostic processing and less so to the 'search-to-find' mode. Eleven laypeople and 17 radiologists in training diagnosed 66 radiographs in 2s each (holistic mode) and subsequently checked their diagnosis in an extended (10-s) period (search-to-find mode). During data analysis, we first identified individual regions of interest (ROIs) for the right FFA using a localizer task. Then we employed ROI-based ANOVAs and obtained tentative support for the hypothesis that the right FFA shows more activation for radiologists in training versus laypeople, in particular in the holistic mode (i.e., during 2s trials), and less so in the search-to-find mode (i.e., during 10-s trials). No significant correlation was found between diagnostic performance (diagnostic accuracy) and brain-activation level within the right FFA for both, short-presentation and long-presentation diagnostic trials. Our results provide tentative evidence from a diagnostic-reasoning task that the FFA supports the holistic processing of visual stimuli in participants' expertise domain., Competing Interests: The authors have declared that no competing interests exist.

Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts' (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts' changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts' natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts' behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts' automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically., (© 2020 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Structured reporting is advocated as a means of improving reporting in radiology to the ultimate benefit of both radiological and clinical practice. Several large initiatives are currently evaluating its potential. However, with numerous characterizations of the term in circulation, "structured reporting" has become ambiguous and is often confused with "standardization," which may hamper proper evaluation and implementation in clinical practice. This paper provides an overview of interpretations of structured reporting and proposes a clear definition that differentiates structured reporting from standardization. Only a clear uniform definition facilitates evidence-based implementation, enables evaluation of its separate components, and supports (meta-)analyses of literature reports.

Aim: To investigate whether full-field digital mammography (FFDM) and contrast-enhanced mammography (CEM), evaluated by non-experienced high school students, improves detection of missed breast cancer lesions on FFDM, in the same cohort of patients. Methods: Non-experienced first- and second year high school students examined fourteen cases of patients diagnosed with breast cancer. These cases consisted of missed breast cancer lesions on FFDM by a breast radiologist. Sensitivity of assessment of the students on FFDM and CEM was analysed and compared with the initial results of the breast radiologists. Results: A total of 134 high school students participated in this study. Mean age was 12.8 years (range 10-14). Based on FFDM, mean overall sensitivity of the students was 29.2% (18.9 - 39.6%). When recombined CEM images were used, mean overall sensitivity of students improved to 82.6% (74.0 - 91.2%) (p=0.001). Mean overall sensitivity of FFDM exams evaluated by radiologists was 75.7% (64.2 - 87.3%), which was lower when compared to student's evaluations on recombined CEM exams, yet not statistically significant (p=0.098). Conclusions: Contrast-enhanced mammography evaluated by non-experienced high school students might improve detection rate of breast cancer when compared to evaluations of only full-field digital mammography by radiologists., Competing Interests: Competing Interests: The authors have declared that no competing interest exists.

The interpretation of chest radiographs is a complex task that is prone to diagnostic error, especially for medical students. The aim of this study is to investigate the extent to which medical students benefit from the use of a checklist regarding the detection of abnormalities on a chest radiograph. We developed a checklist based on literature and interviews with experienced thorax radiologists. Forty medical students in the clinical phase assessed 18 chest radiographs during a computer test, either with (n = 20) or without (n = 20) the checklist. We measured performance and asked participants for feedback using a survey. Participants that used a checklist detected more abnormalities on images with multiple abnormalities (M = 50.1%) than participants that could not use a checklist (M = 41.9%), p = 0.04. The post-experimental survey shows that on average, participants considered the checklist helpful (M = 3.25 on a five-point scale), but also time consuming (M = 3.30 on a five-point scale). In conclusion, a checklist can help medical students to detect abnormalities in chest radiographs. Moreover, students tend to appreciate the use of a checklist as a helpful tool during the interpretation of a chest radiograph. Therefore, a checklist is a potentially important tool to improve radiology education in the medical curriculum.

People know surprisingly little about their own visual behavior, which can be problematic when learning or executing complex visual tasks such as search of medical images. We investigated whether providing observers with online information about their eye position during search would help them recall their own fixations immediately afterwards. Seventeen observers searched for various objects in "Where's Waldo" images for 3 s. On two-thirds of trials, observers made target present/absent responses. On the other third (critical trials), they were asked to click twelve locations in the scene where they thought they had just fixated. On half of the trials, a gaze-contingent window showed observers their current eye position as a 7.5° diameter "spotlight." The spotlight "illuminated" everything fixated, while the rest of the display was still visible but dimmer. Performance was quantified as the overlap of circles centered on the actual fixations and centered on the reported fixations. Replicating prior work, this overlap was quite low (26%), far from ceiling (66%) and quite close to chance performance (21%). Performance was only slightly better in the spotlight condition (28%, p = 0.03). Giving observers information about their fixation locations by dimming the periphery improved memory for those fixations modestly, at best.

Educators in medical image interpretation have difficulty finding scientific evidence as to how they should design their instruction. We review and comment on 81 papers that investigated instructional design in medical image interpretation. We distinguish between studies that evaluated complete offline courses and curricula, studies that evaluated e-learning modules, and studies that evaluated specific educational interventions. Twenty-three percent of all studies evaluated the implementation of complete courses or curricula, and 44% of the studies evaluated the implementation of e-learning modules. We argue that these studies have encouraging results but provide little information for educators: too many differences exist between conditions to unambiguously attribute the learning effects to specific instructional techniques. Moreover, concepts are not uniformly defined and methodological weaknesses further limit the usefulness of evidence provided by these studies. Thirty-two percent of the studies evaluated a specific interventional technique. We discuss three theoretical frameworks that informed these studies: diagnostic reasoning, cognitive schemas and study strategies. Research on diagnostic reasoning suggests teaching students to start with non-analytic reasoning and subsequently applying analytic reasoning, but little is known on how to train non-analytic reasoning. Research on cognitive schemas investigated activities that help the development of appropriate cognitive schemas. Finally, research on study strategies supports the effectiveness of practice testing, but more study strategies could be applicable to learning medical image interpretation. Our commentary highlights the value of evaluating specific instructional techniques, but further evidence is required to optimally inform educators in medical image interpretation.

Rationale and Objectives: Radiologists commonly use comparison films to improve their differential diagnosis. Educational literature suggests that this technique might also be used to bolster the process of learning to interpret radiographs. We investigated the effectiveness of three comparison techniques in medical students, whom we invited to compare cases of the same disease (same-disease comparison), cases of different diseases (different-disease comparison), disease images with normal images (disease/normal comparison), and identical images (no comparison/control condition). Furthermore, we used eye-tracking technology to investigate which elements of the two cases were compared by the students., Materials and Methods: We randomly assigned 84 medical students to one of four conditions and had them study different diseases on chest radiographs, while their eye movements were being measured. Thereafter, participants took two tests that measured diagnostic performance and their ability to locate diseases, respectively., Results: Students studied most efficiently in the same-disease and different-disease comparison conditions: test 1, F(3, 68) = 3.31, P = .025, ηp(2) = 0.128; test 2, F(3, 65) = 2.88, P = .043, ηp(2) = 0.117. We found that comparisons were effected in 91% of all trials (except for the control condition). Comparisons between normal anatomy were particularly common (45.8%) in all conditions., Conclusions: Comparing cases can be an efficient way of learning to interpret radiographs, especially when the comparison technique used is specifically tailored to the learning goal. Eye tracking provided insight into the comparison process, by showing that few comparisons were made between abnormalities, for example., (Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.)

Background: Treatment of breast cancer with the antiestrogen tamoxifen is effective in approximately one half of the patients with estrogen receptor-positive disease, but tumors recur frequently because of the development of metastases that are resistant to tamoxifen. We have previously shown that mutagenesis of human estrogen-dependent ZR-75-1 breast cancer cells by insertion of a defective retrovirus genome caused the cells to become antiestrogen resistant. In this study, we isolated and characterized the crucial gene at the breast cancer antiestrogen resistance 1 (BCAR1) locus., Methods/results: Transfer of the BCAR1 locus from retrovirus-mutated, antiestrogen-resistant cells to estrogen-dependent ZR-75-1 cells by cell fusion conferred an antiestrogen-resistant phenotype on the recipient cells. The complete coding sequence of BCAR1 was isolated by use of exon-trapping and complementary DNA (cDNA) library screening. Sequence analysis of human BCAR1 cDNA predicted a protein of 870 amino acids that was strongly homologous to rat p130Cas-adapter protein. Genomic analysis revealed that BCAR1 consists of seven exons and is located at chromosome 16q23.1. BCAR1 transcripts were detected in multiple human tissues and were similar in size to transcripts produced by retrovirus-mutated ZR-75-1 cells. Transfection of BCAR1 cDNA into ZR-75-1 cells again resulted in sustained cell proliferation in the presence of antiestrogens, confirming that BCAR1 was the responsible gene in the locus., Conclusions: Overexpression of the BCAR1 gene confers antiestrogen resistance on human ZR-75-1 breast cancer cells. Overexpression of BCAR1 in retrovirus-mutated cells appears to result from activation of the gene's promoter. The isolation and characterization of this gene open new avenues to elucidating mechanisms by which the growth of human breast cancer becomes independent of estrogen.

Background: The product of the Bcar1/p130Cas (breast cancer resistance/p130Crk-associated substrate) gene causes resistance to antiestrogen drugs in human breast cancer cells in vitro. To investigate its role in clinical breast cancer, we determined the levels of Bcar1/p130Cas protein in a large series of primary breast carcinomas., Methods: We measured Bcar1/p130Cas protein in cytosol extracts from 937 primary breast carcinomas by western blot analysis. The levels of Bcar1/p130Cas protein were tested for associations and trends against clinicopathologic and patient characteristics, the lengths of relapse-free survival and overall survival (n = 775), and the efficacy of first-line treatment with tamoxifen for recurrent or metastatic disease (n = 268)., Results: Bcar1/p130Cas levels in primary tumors were associated with age/menopausal status and the levels of estrogen receptor and progesterone receptor. In univariate survival analysis, higher Bcar1/p130Cas levels were associated with poor relapse-free survival and overall survival (both two-sided P =.04; log-rank test for trend). In multivariate analysis, a high level of Bcar1/p130Cas was independently associated with poor relapse-free survival and overall survival. The response to tamoxifen therapy in patients with recurrent disease was reduced in patients with primary tumors that expressed high levels of Bcar1/p130Cas. In multivariate analysis for response, Bcar1/p130Cas was independent of classical predictive factors, such as estrogen receptor status, age/menopausal status, disease-free interval, and dominant site of relapse., Conclusion: Patients with primary breast tumors expressing a high level of Bcar1/p130Cas protein appear to experience more rapid disease recurrence and have a greater risk of (intrinsic) resistance to tamoxifen therapy. Thus, measurement of Bcar1/p130Cas may provide useful prognostic information for patients with primary or metastatic breast cancer.

Duration of response to antiestrogen therapy in metastatic breast cancer is limited due to the development of antiestrogen-resistant tumors. The mechanisms involved are not understood but could originate from (epi)genetic alterations within the tumor cells. We have applied in vitro random insertional mutagenesis with replication defective retroviruses to identify those genes playing a key role in development of antiestrogen resistance in human breast cancer cells. Eighty antiestrogen-resistant cell clones were isolated from 7 x 10(8) estrogen-dependent ZR-75-1 cells, mass-infected with defective retroviruses and subjected to 4-OH-tamoxifen selection. Integration site-specific DNA probes were made by inverse polymerase chain reaction techniques and used to search for common integration sites. Six cell clones were identified with retroviral genome integrations in the same orientation in a single locus, designated breast cancer antiestrogen resistance locus-1 (bcar-1). These bcar-1 cell clones had lost estrogen receptor expression and had become estrogen independent. Our results strongly suggest that alteration of the bcar-1 locus is responsible for development of antiestrogen resistance in human breast cancer cells in vitro. In addition, we have shown that in vitro insertional mutagenesis using defective retroviruses can be applied for gene tagging in human cells.