Journal of Visual Communication in Medicine最新文献

Colorectal cancers develop from pre-malignant polyps that can be removed during colonoscopy. Detection, assessment, and removal of polyps has a major role in bowel cancer prevention and is an important part of bowel cancer screening programmes. Trainee colonoscopists must acquire skills to recognise and classify colorectal polyps. Accurate classification is based on morphology, surface pit and capillary patterns. It is difficult to teach assessment skills because static polyp images are often of poor quality and cannot show all areas of interest. Based on anonymised, endoscopic reference images, 3D polyp models were created in ZBrush, demonstrating a variety of morphological forms. The models had detailed pit patterns to show the capillary structure, a key predictor of pathology. The models were subsequently uploaded to the online 3D repository and model viewer, Sketchfab, to create an interactive training resource for trainee colonoscopists. The digital models were evaluated by a panel of expert colonoscopists who scored them for realism and potential as aids for training. There was agreement that the digital polyp models would be useful for teaching. Polyp morphology was rated as realistic however representation of pit patterns received a mixed response, highlighting areas for further development.

Introduction: Use of mobile devices with high-quality cameras has expanded medical photography. We investigate the impact of different devices and conditions on photograph quality in a surgical setting.

Methods: Fourteen surgeons across six centres scored photograph quality of kidneys donated for transplantation. Images were captured using an iPhone, iPad, or DSLR camera on automatic modes under varying lighting conditions. In blinded A/B testing, surgeons selected the image perceived more clinically useful for remote organ quality assessment and rated each on a 5-point Likert scale. Quality was objectively analysed using two computer vision referenceless quality assessment tools (BRISQUE & NIMA).

Results: Of 369 photographs, mobile device images were rated higher quality by surgeons (78.4%) compared to DSLR (9.4%, p < 0.001). Multilevel regression using BRISQUE showed higher quality for iPhones (β = -5.86, p < 0.001) and iPads (β = -3.90, p < 0.001) versus DSLR. Room lighting improved quality over direct overhead illumination with theatre lights (β = 17.87, p < 0.001). Inter-rater (Gwet AC = 0.78) and intra-rater (Cohen's κ = 0.86) agreements were high.

Discussion: Smartphones can produce high quality photographs. These findings should reassure clinicians that smartphone devices do not compromise photograph quality and support their use in clinical practice and image analysis research.

Anatomy learning has traditionally relied on drawings, plastic models, and cadaver dissections/prosections to help students understand the three-dimensional (3D) relationships within the human body. However, the landscape of anatomy education has been transformed with the introduction of digital media. In this light, the Open Anatomy Explorer (OPANEX) was developed. It includes two user interfaces (UI): one for students and one for administrators. The administrator UI offers features such as uploading and labelling of 3D models, and customizing 3D settings. Additionally, the OPANEX facilitates content sharing between institutes through its import-export functionality. To evaluate the integration of OPANEX within the existing array of learning resources, a survey was conducted as part of the osteology course at Ghent University, Belgium. The survey aimed to investigate the frequency of use of five learning resources, attitudes towards 3D environments, and the OPANEX user experience. Analysis revealed that the OPANEX was the most frequently used resource. Students' attitudes towards 3D learning environments further supported this preference. Feedback on the OPANEX user experience indicated various reasons for its popularity, including the quality of the models, regional annotations, and customized learning content. In conclusion, the outcomes underscore the educational value of the OPANEX, reflecting students' positive attitudes towards 3D environments in anatomy education.

Effective communication in healthcare can benefit from clear and engaging visual aids. Grounded in Cognitive Load Theory, Dual Coding Theory, and Visual Literacy Theory, our study investigates the impact of an instructional video designed to enhance physicians' visual communication skills through improved clinical sketches. By collaboration of medical and fine arts disciplines, a rubric was developed for evaluating clinical sketches based on artistic principles of layout, visual clarity, style, sequence and directionality, hierarchy and colour. An instructional video was created highlighting these principles along with clinical examples (Publicly available at: https://mymedia.bu.edu/media/t/1_wgpgpl84). Four physicians created clinical sketches before and after viewing the video. The study includes pre- and post-surveys and evaluations of the sketches by artists. Survey results demonstrated a statistically significant increase in aesthetic quality across multiple categories- layout, visual clarity, style, sequence and directionality - after physicians viewed the instructional video. Physicians reported increased motivation to incorporate clinical illustrations into their practice however outlined time constraints as a barrier. Our findings highlight the efficacy of the instructional video in enhancing physicians' ability to create informative clinical sketches. Future research should focus on integrating visual communication tools into clinics and medical education curricula to pursue patient-centred care.

Four versions of the novel Moletest on-device signal-processing analysis software, delivered on a single-application iPadPro11, were evaluated in pigmented skin lesions of patients sent for biopsy comparing its results with the lesion histology. The primary objective was to demonstrate that the nomela^® test provided at least 95 ± 2% sensitivity for not-melanoma. Proprietary software recognised the lesion perimeter, rejecting images with uncertain border, and performed analysis using non-scalar metrics of the image within the perimeter. From five algorithms any one reading outside the predefined melanoma range assigned the lesion to 'no evidence of melanoma' or otherwise to 'melanoma not excluded'. 1365 participants provided 1573 lesions. 1389 valid cases had a valid signal-processing test result and a valid histology report defined as 'not-melanoma' (n = 1205) or 'melanoma' (n = 184). Statistical analysis for the four versions were: sensitivity (ability of the signal-processing analysis to assign 'No evidence of melanoma' to a lesion with 'not-melanoma' histology) 8.6/48.4/76.9/52.1%; specificity (ability to assign 'Melanoma not excluded' to a lesion with 'melanoma' histology) 100/79.6/75.0/65.2%. The performance of the Moletest signal-processing analysis as a diagnostic support for rule-out of melanoma showed limited value in all four versions.