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Morphological Validation of a Novel Bi-material 3D-printed Model of Temporal Bone for Middle Ear Surgery Education

Overview
Journal Ann Transl Med
Date 2020 May 2
PMID 32355748
Citations 4
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Abstract

Background: A new model of 3D-printed temporal bone with an innovative distinction between soft and hard tissues is described and presented in the present study. An original method is reported to quantify the model's ability to reproduce the complex anatomy of this region.

Methods: A CT-scan of temporal bone was segmented and prepared to obtain 3D files adapted to multi-material printing technique. A final product was obtained with two different resins differentiating hard from soft tissues. The reliability of the anatomy was evaluated by comparing the original CT-scan and the pre-processed files sent to the printer in a first step, and by quantifying the printing technique in a second step. Firstly, we evaluated the segmentation and mesh correction steps by segmenting each anatomical region in the CT-scan by two different other operators without mesh corrections, and by computing distances between the obtained geometries and the pre-processed ones. Secondly, we evaluated the printing technique by comparing the printed geometry imaged using µCT with the pre-processed one.

Results: The evaluation of the segmentation and mesh correction steps revealed that the distance between both geometries was globally less that one millimeter for each anatomical region and close to zero for regions such as temporal bone, semicircular canals or facial nerve. The evaluation of the printing technique revealed mismatches of 0.045±0.424 mm for soft and -0.093±0.240 mm for hard tissues between the initial prepared geometry and the actual printed model.

Conclusions: While other reported models for temporal bone are simpler and have only been validated subjectively, we objectively demonstrated in the present study that our novel artificial bi-material temporal bone is consistent with the anatomy and thus could be considered into ENT surgical education programs. The methodology used in this study is quantitative, inspired by engineer sciences, making it the first of its kind. The validity of the manufacturing process has also been verified and could, therefore, be extended to other specialties, emphasizing the importance of cross-disciplinary collaborations concerning new technologies.

Citing Articles

Developing a production workflow for 3D-printed temporal bone surgical simulators.

Ang A, Chee S, Tang J, Chan C, Tan V, Lee J 3D Print Med. 2024; 10(1):16.

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Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: neurosurgical and otolaryngologic conditions.

Ali A, Morris J, Decker S, Huang Y, Wake N, Rybicki F 3D Print Med. 2023; 9(1):33.

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Preoperative simulation using three-dimensional printer in four temporal bone surgeries.

Fukumoto I, Mita Y, Shimmi R, Sonobe Y, Iinuma T, Yamasaki K Clin Case Rep. 2023; 11(5):e7135.

PMID: 37192847 PMC: 10182005. DOI: 10.1002/ccr3.7135.


Deep learning-based approach for the automatic segmentation of adult and pediatric temporal bone computed tomography images.

Ke J, Lv Y, Ma F, Du Y, Xiong S, Wang J Quant Imaging Med Surg. 2023; 13(3):1577-1591.

PMID: 36915310 PMC: 10006112. DOI: 10.21037/qims-22-658.

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