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Medical image interpretation is moving from using 2D- to volumetric images, thereby changing the cognitive and perceptual processes involved. This is expected to affect medical students' experienced cognitive load, while learning image interpretation skills. With two studies this explorative research investigated whether measures inherent to image interpretation, i.e. human-computer interaction and eye tracking, relate to cognitive load. Subsequently, it investigated effects of volumetric image interpretation on second-year medical students' cognitive load. Study 1 measured human-computer interactions of participants during two volumetric image interpretation tasks. Using structural equation modelling, the latent variable 'volumetric image information' was identified from the data, which significantly predicted self-reported mental effort as a measure of cognitive load. Study 2 measured participants' eye movements during multiple 2D and volumetric image interpretation tasks. Multilevel analysis showed that time to locate a relevant structure in an image was significantly related to pupil dilation, as a proxy for cognitive load. It is discussed how combining human-computer interaction and eye tracking allows for comprehensive measurement of cognitive load. Combining such measures in a single model would allow for disentangling unique sources of cognitive load, leading to recommendations for implementation of volumetric image interpretation in the medical education curriculum. Display Omitted Image interpretation in medicine moved from 2D- to volumetric images.Cognitive load of students interpreting medical images affected.Human computer interaction and time to locate relevant area predict cognitive load.Insights useful for avoiding cognitive overload in medical curriculum.

Diagnostic errors in radiology are frequent and can cause severe patient harm. Despite large performance differences between radiologists and non-radiology physicians, the latter often interpret medical images because electronic health records make images available throughout the hospital. Some people argue that non-radiologists should not diagnose medical images at all, and that medical school should focus on teaching ordering skills instead of image interpretation skills. We agree that teaching ordering skills is crucial as most physicians will need to order medical images in their professional life. However, we argue that the availability of medical images is so ubiquitous that it is important that non-radiologists are also trained in the basics of medical image interpretation and, additionally in recognizing when radiological consultancy should be sought. In acute situations, basic image interpretations skills can be life-saving. We plead for a radiology curriculum for all medical students. This should include the interpretation of common abnormalities on chest and skeletal radiographs and a basic distinction of normal from abnormal images. Furthermore, substantial attention should be given to the correct ordering of radiological images. Finally, it is critical that students are trained in deciding when to consult a radiologist.

Rationale and Objectives In current practice, radiologists interpret digital images, including a substantial amount of volumetric images. We hypothesized that interpretation of a stack of a volumetric data set demands different skills than interpretation of two-dimensional (2D) cross-sectional images. This study aimed to investigate and compare knowledge and skills used for interpretation of volumetric versus 2D images. Materials and Methods Twenty radiology clerks were asked to think out loud while reading four or five volumetric computed tomography (CT) images in stack mode and four or five 2D CT images. Cases were presented in a digital testing program allowing stack viewing of volumetric data sets and changing views and window settings. Thoughts verbalized by the participants were registered and coded by a framework of knowledge and skills concerning three components: perception, analysis, and synthesis. The components were subdivided into 16 discrete knowledge and skill elements. A within-subject analysis was performed to compare cognitive processes during volumetric image readings versus 2D cross-sectional image readings. Results Most utterances contained knowledge and skills concerning perception (46%). A smaller part involved synthesis (31%) and analysis (23%). More utterances regarded perception in volumetric image interpretation than in 2D image interpretation (Median 48% vs 35%; z = −3.9; P

The testing of image interpretation skills within the profession of Radiology (often paper- pencil) lags behind practice. To increase the authenticity of assessment of image interpretation skills, the Dutch national progress test for medical specialists in training to become radiologists, is digitized using the program VQuest. This programme makes it possible to administer a test with 2D and 3D images, in which images can be viewed and processed as they can in practice. During implementation, the entire assessment cycle from test design to assessment analysis and evaluation has been run through twice. Excluding some small improvements, both trainee specialist and organizational members were satisfied with the digitized assessment. Amongst other things, the trainee specialist feel that this application of digital testing is more consistent with the situation in practice than the conventional testing method.