Simplified Easy-Accessible Smartphone-Based Photogrammetry for 3-Dimensional Anatomy Presentation Exemplified With a Photorealistic Cadaver-Based Model of the Intracranial and Extracranial Course of the Facial Nerve

Smartphone applications for facial scanning: A technical and scoping review

INTRODUCTION

Facial scanning through smartphone scanning applications (SSA) is increasingly being used for medical applications as cost-effective, chairside method. However, clinical validation is lacking. This review aims to address: (1) Which SSA could perform facial scanning? (2) Which SSA can be clinically used? (3) Which SSA have been reported and scientifically validated for medical applications?

METHODS

Technical search for SSA designed for face or object scanning was conducted on Google, Apple App Store, and Google Play Store from August 2022 to December 2023. Literature search was performed on PubMed, Cochrane, EMBASE, MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, Clinicaltrials.gov, ICTRP (WHO) and preprints up to 2023. Eligibility criteria included English-written scientific articles incorporating at least one SSA for clinical purposes. SSA selection and data extraction were executed by one reviewer, validated by second, with third reviewer being consulted for discordances.

RESULTS

Sixty-three applications designed for three-dimensional object scanning were retrieved, with 52 currently offering facial scanning capabilities. Fifty-six scientific articles, comprising two case reports, 16 proof-of-concepts and 38 experimental studies were analysed. Thirteen applications (123D Catch, 3D Creator, Bellus 3D Dental Pro, Bellus 3D Face app, Bellus 3D Face Maker, Capture, Heges, Metascan, Polycam, Scandy Pro, Scaniverse, Tap tap tap and Trnio) were reported in literature for digital workflow integration, comparison or proof-of-concept studies.

CONCLUSION

Fifty-two SSA can perform facial scanning currently and can be used clinically, offering cost-effectiveness, portability and user-friendliness. Although clinical validation is crucial, only 13 SSA were scientifically validated, underlying awareness of potential pitfalls and limitations.

Technologies for Studying and Teaching Human Anatomy: Implications in Academic Education

The teaching of human anatomy (HA) constitutes one of the fundamental pillars of the curriculum in biological and healthcare-related programs. Therefore, it is imperative that the methodology and didactics employed in this discipline equip students in the best possible way. The traditional method of teaching HA involves lectures and practical classes with previously dissected cadaveric specimens and dissection activities. Concurrently, the present era is witnessing the emergence and popularization of new digital technologies connected to the internet, among which we can highlight smartphones, quick response codes, and virtual reality devices, along with the dissemination of complementary imaging methods, such as radiography, ultrasonography, magnetic resonance imaging, and computerized tomography. From this perspective, the objective of this review is to analyze how each of these new tools integrates into the academic context, in order to diversify the teaching of HA and contribute to better understanding of the HA content during academic training, as well as the clinical applications.

Neuroanatomical photogrammetric models using smartphones: a comparison of apps

OBJECTIVES

A deep knowledge of the surgical anatomy of the target area is mandatory for a successful operative procedure. For this purpose, over the years, many teaching and learning methods have been described, from the most ancient cadaveric dissection to the most recent virtual reality, each with their respective pros and cons. Photogrammetry, an emergent technique, allows for the creation of three-dimensional (3D) models and reconstructions. Thanks to the spreading of photogrammetry nowadays it is possible to generate these models using professional software or even smartphone apps. This study aims to compare the neuroanatomical photogrammetric models generated by the two most utilized smartphone applications in this domain, Metascan and 3D-Scanner, through quantitative analysis.

METHODS

Two human head specimens (four sides) were examined. Anatomical dissection was segmented into five stages to systematically expose well-defined structures. After each stage, a photogrammetric model was generated using two prominent smartphone applications. These models were then subjected to both quantitative and qualitative analysis, with a specific focus on comparing the mesh density as a measure of model resolution and accuracy. Appropriate consent was obtained for the publication of the cadaver's image.

RESULTS

The quantitative analysis revealed that the models generated by Metascan app consistently demonstrated superior mesh density compared to those from 3D-Scanner, indicating a higher level of detail and potential for precise anatomical representation.

CONCLUSION

Enabling depth perception, capturing high-quality images, offering flexibility in viewpoints: photogrammetry provides researchers with unprecedented opportunities to explore and understand the intricate and magnificent structure of the brain. However, it is of paramount importance to develop and apply rigorous quality control systems to ensure data integrity and reliability of findings in neurological research. This study has demonstrated the superiority of Metascan in processing photogrammetric models for neuroanatomical studies.

The Evaluation of Virtual Reality Neuroanatomical Training Utilizing Photorealistic 3D Models in Limited Body Donation Program Settings

Background Neuroanatomy is one of the most complex areas of anatomy to teach to medical students. Traditional study methods such as atlases and textbooks are mandatory but require significant effort to conceptualize the three-dimensional (3D) aspects of the neuroanatomical regions of interest. Objectives To test the feasibility of human anatomy teaching medical students in a virtual reality (VR) immersive environment using photorealistic three-dimensional models (PR3DM) of human anatomy, in a limited anatomical body donation program. Methods We used surface scanning technology (photogrammetry) to create PR3DM of brain dissections. The 3D models were uploaded to VR headsets and used in immersive environment classes to teach second-year medical students. Twenty-eight medical students (mean age 20.11, SD 1.42), among which 19 females (n=28/67.9%) and nine males (n=28/32.1%), participated in the study. The students had either none or minimal experience with the use of VR devices. The duration of the study was three months. After completing the curriculum, a survey was done to examine the results. Results The average rating of the students for their overall experience with the method is 4.57/5 (SD=0.63). The "Possibility to study models from many points of view" and "Good Visualization of the models" were the most agreed upon advantages, with 24 students (n=28, 85.7%), and 95% confidence intervals (CI) [0.6643, 0.9532]. The limited availability of the VR headsets was the major disadvantage as perceived by the students, with 11 students (n=28, 39.3%), 95% CI [0.2213, 0.5927] having voted for the option. The majority of the students (25) (n=28, 89.2%, SD=0.31) agreed with the statement that the use of VR facilitated their neuroanatomy education. Conclusion This study shows the future potential of this model of training in limited cadaver dissection options to provide students with modern technological methods of training. Our first results indicate a prominent level of student satisfaction from VR training with minimum negative reactions to the nature of headsets. The proof of concept for the application of photorealistic models in VR neuroanatomy training combined with the initial results of appreciation among the students predisposes the application of the method on a larger scale, adding a nuance to the traditional anatomy training methods. The low number of headsets used in the study limits the generalization of the results but offers possibilities for future perspectives of research.

Photogrammetry Applied to Neurosurgery: A Literature Review

Photogrammetry refers to the process of creating 3D models and taking measurements through the use of photographs. Photogrammetry has many applications in neurosurgery, such as creating 3D anatomical models and diagnosing and evaluating head shape and posture deformities. This review aims to summarize the uses of the technique in the neurosurgical practice and showcase the systems and software required for its implementation. A literature review was done in the online database PubMed. Papers were searched using the keywords "photogrammetry", "neurosurgery", "neuroanatomy", "craniosynostosis" and "scoliosis". The identified articles were later put through primary (abstracts and titles) and secondary (full text) screening for eligibility for inclusion. In total, 86 articles were included in the review from 315 papers identified. The review showed that the main uses of photogrammetry in the field of neurosurgery are related to the creation of 3D models of complex neuroanatomical structures and surgical approaches, accompanied by the uses for diagnosis and evaluation of patients with structural deformities of the head and trunk, such as craniosynostosis and scoliosis. Additionally, three instances of photogrammetry applied for more specific aims, namely, cervical spine surgery, skull-base surgery, and radiosurgery, were identified. Information was extracted on the software and systems used to execute the method. With the development of the photogrammetric method, it has become possible to create accurate 3D models of physical objects and analyze images with dedicated software. In the neurosurgical setting, this has translated into the creation of anatomical teaching models and surgical 3D models as well as the evaluation of head and spine deformities. Through those applications, the method has the potential to facilitate the education of residents and medical students and the diagnosis of patient pathologies.