Manipulation of mental models of anatomy in interventional radiology and its consequences for design of human–computer interaction

Varga, Edit; Pattynama, Peter M. T.; Freudenthal, Adinda

doi:10.1007/s10111-012-0227-6

Cited by 14 publications

(8 citation statements)

References 57 publications

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“…Additionally, there is greater understanding of the role of spatial reasoning in anatomy and even the physiology behind its use. The radiology literature is rife with the importance of spatial reasoning to reconstruct three‐dimensional structures from serial axial imaging to the extent that it has been suggested to be a prerequisite for radiologists (Varga et al, ; Birchall, ). There is also some suggestion in the cognitive psychology literature that spatial reasoning ability should be selected for in future physicians for specialties broadly, not just radiology (Hegarty et al, ).…”

Section: Introductionmentioning

confidence: 99%

Student and recent graduate perspectives on radiological imaging instruction during basic anatomy courses

Phillips

Eason

Straus

2017

Anatomical Sciences Ed

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Recently, faculty at Pritzker School of Medicine, The University of Chicago, have made efforts to improve the depth of radiological anatomy knowledge that students have, but no insights exist as to student and resident opinions of how clinically helpful deep anatomical understanding is. A single-institution survey of second- and fourth-year medical students and postgraduate year 1-4 residents from 11 specialties, composed of five-point Likert questions, sample examination questions, and narrative response questions, was distributed in 2015. One hundred seventy-seven of the 466 potential respondents replied (71 residents and 106 students), response rate 38.0%. No nonresponse bias was present in two separate analyses. Respondents generally favored a superficial "identification" question as more relevant to clinical practice, which was positively associated with increasing clinical experience ρ = 0.357, P < 0.001 by point-biserial correlation. Students and residents most commonly used self-directed methods to learn medical imaging during their medical anatomy courses (72.6 and 57.7%, respectively). Small group education was least commonly used by students and residents (45.3 and 39.4%, respectively), but most commonly recommended (62.3 and 69%, respectively). A total of 56.6 and 64.8% of students and residents, respectively, reported that having multiple learning methods was "quite" or "extremely" important. Respondents with more clinical experience were more likely to report that a superficial identification question was more clinically relevant than a question testing deeper radiological anatomy knowledge. Small group learning was preferred among students and residents but was the least commonly employed method of instruction. Both findings contrast starkly with current radiological anatomy instructional understanding and practices. Anat Sci Educ 11: 25-31. © 2017 American Association of Anatomists.

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Section: Introductionmentioning

confidence: 99%

Student and recent graduate perspectives on radiological imaging instruction during basic anatomy courses

Phillips

Eason

Straus

2017

Anatomical Sciences Ed

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“…These later stage corrections can be assumed to correspond to the physicians updating their mental model (Varga et al 2013) and then correcting the contours correspondingly.…”

Section: The Efficiency Of and The Influences On The Contouring Processmentioning

confidence: 99%

The influence of automation on tumor contouring

et al. 2017

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Fully or semi-automatic contouring tools are increasingly being used in the tumor contouring task for radiotherapy. While the fully automatic contouring tools have not reached sufficient efficiency, the semi-automatic contouring tools balance more effectively between the human interaction and automation. This study evaluates the influences of a semi-automation contouring tool, called between-slice interpolation, on the resulting contours and the contouring process. The tumor contouring study was conducted on three patient cases with five physicians in a naturalistic setting. The contouring task consisted of initiating the 2D contour manually or with the interpolation tool and correcting that initial contour. The similarity of the resulting contours was pairwise measured within the manual or the interpolated category. Interactions with the software were recorded, and variations in the contouring workflows steps were compared. Results indicated that using the between-slice interpolation tool for creating the initial contour, instead of initiating it manually, influenced both the contouring process and outcomes. First, it was identified that contours initiated by the interpolation tool showed an increased similarity among themselves compared to the manually initiated contours. At the same time, influences to the resulting contours were below clinical relevance, and toward the desired direction-improved consistency of contours. Second, when interpolation was used, in two cases out of three, the average contouring time also decreased significantly. Therefore, the use of such an automation tool can be encouraged.

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“…These images, which represent (part of) the three-dimensional (3D) human body, are presented on the computer screen as a set of 2D images (i.e., slices). In radiotherapy treatment planning, physicians navigate through these 2D images to construct the mental 3D model of the anatomy [27] for different tasks.…”

Section: The Task -Tumor Contouring For Radiotherapy Planningmentioning

confidence: 99%

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring

Aselmaa

Herk

Laprie

et al. 2017

Journal of Biomedical Informatics

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a b s t r a c tSensemaking theories help designers understand the cognitive processes of a user when he/she performs a complicated task. This paper introduces a two-step approach of incorporating sensemaking support within the design of health information systems by: (1) modeling the sensemaking process of physicians while performing a task, and (2) identifying software interaction design requirements that support sensemaking based on this model. The two-step approach is presented based on a case study of the tumor contouring clinical task for radiotherapy planning. In the first step of the approach, a contextualized sensemaking model was developed to describe the sensemaking process based on the goal, the workflow and the context of the task. In the second step, based on a research software prototype, an experiment was conducted where three contouring tasks were performed by eight physicians respectively. Four types of navigation interactions and five types of interaction sequence patterns were identified by analyzing the gathered interaction log data from those twenty-four cases. Further in-depth study on each of the navigation interactions and interaction sequence patterns in relation to the contextualized sensemaking model revealed five main areas for design improvements to increase sensemaking support. Outcomes of the case study indicate that the proposed two-step approach was beneficial for gaining a deeper understanding of the sensemaking process during the task, as well as for identifying design requirements for better sensemaking support.

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Manipulation of mental models of anatomy in interventional radiology and its consequences for design of human–computer interaction

Cited by 14 publications

References 57 publications

Student and recent graduate perspectives on radiological imaging instruction during basic anatomy courses

Student and recent graduate perspectives on radiological imaging instruction during basic anatomy courses

The influence of automation on tumor contouring

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring

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