BACKGROUND: Computer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models.
METHODS: Six cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy.
RESULTS: Two-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well.
CONCLUSIONS: This study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.

The aim of this study was to evaluate the usefulness of a personalized 3D-printed thyroid model that characterizes a patient\'s individual thyroid lesion. The randomized controlled prospective clinical trial (KCT0005069) was designed. Fifty-three of these patients undergoing thyroid surgery were randomly assigned to two groups: with or without a 3D-printed model of their thyroid lesion when obtaining informed consent. We used a U-Net-based deep learning architecture and a mesh-type 3D modeling technique to fabricate the personalized 3D model. The mean 3D printing time was 258.9 min, and the mean price for production was USD 4.23 for each patient. The size, location, and anatomical relationship of the tumor and thyroid gland could be effectively presented using the mesh-type 3D modeling technique. The group provided with personalized 3D-printed models showed significant improvement in all four categories (general knowledge, benefits and risks of surgery, and satisfaction; all p < 0.05). All patients received a personalized 3D model after surgery and found it helpful to understand the disease, operation, and possible complications and their overall satisfaction (all p < 0.05). In conclusion, the personalized 3D-printed thyroid model may be an effective tool for improving a patient\'s understanding and satisfaction during the informed consent process.

Three-dimensional (3D) printing has revolutionized individualized medicine for patient-specific anatomical modeling and surgical planning. The surge of investigations in model creation for preoperative assessments and patient education has demonstrated improvements in both operative factors and patient satisfaction. In addition, recent technologic advances in 3D printing techniques have provided a resource to create visually pleasing models with chromatic cues for segmentation of adjacent structures. Despite these advances, an important consideration that has yet to be addressed is the quality of representation of the not only the form of structures created, but also the functional relationships of each structure. Jean François Fernel (1497-1558 AD) recognized a similar trend in anatomic innovation over 500 years ago, and sparked a series of texts that challenged the superficial anthropocentric views of the time and led to the foundation of physiologic principles that shaped modern medical philosophy. Accurately generating anatomical structures are directly related to discerning true physiologic function, and a comprehensive understanding of both is essential to hold accountability in fidelity for individualized 3D printing.

BACKGROUND: The techniques and applications of 3-dimensional (3D) printing have progressed at a fast pace. In the last 10 years, there has been significant progress in applying this technology to medical applications. We present a case of osteogenesis imperfecta in which treatment was aided by prospectively using patient-specific, anatomically accurate 3D prints of the calvaria. The patient-specific, anatomically accurate 3D prints were used in the clinic and in the operating room to augment patient education, improve surgical decision making, and enhance preoperative planning.
METHODS: A 41-year-old woman with osteogenesis imperfecta and an extensive neurosurgical history presented for cranioplasty revision. Computed tomography (CT) data obtained as part of routine preoperative imaging were processed into a 3D model. The 3D patient-specific models were used in the clinic for patient education and in the operating room for preoperative visualization, planning, and intraoperative evaluation of anatomy. The patient reported the 3D models improved her understanding and comfort with the planned surgery when compared with discussing the procedure with the neurosurgeon or viewing the CT images with a neuroradiologist. The neurosurgeon reported an improved understanding of the patient\'s anatomy and potential cause of patient symptoms as well as improved preoperative planning compared with viewing the CT imaging alone. The neurosurgeon also reported an improvement in the planned surgical approach with a better intraoperative visualization and confirmation of the regions of planned calvarial resection.
CONCLUSIONS: The use of patient-specific, anatomically accurate 3D prints may improve patient education, surgeon understanding and visualization, preoperative decision making, and intraoperative management.

BACKGROUND: Educational simulators provide a means for students and experts to learn and refine surgical skills. Educators can leverage the strengths of medical simulators to effectively teach complex and high-risk surgical procedures, such as placement of an external ventricular drain.
OBJECTIVE: Our objective was to develop a cost-effective, patient-derived medical simulacrum for cerebral lateral ventriculostomy.
METHODS: A cost-effective, patient-derived medical simulacrum was developed for placement of an external lateral ventriculostomy. Elastomeric and gel casting techniques were used to achieve realistic brain geometry and material properties. 3D printing technology was leveraged to develop accurate cranial properties and dimensions. An economical, gravity-driven pump was developed to provide normal and abnormal ventricular pressures. A small pilot study was performed to gauge simulation efficacy using a technology acceptance model.
RESULTS: An accurate geometric representation of the brain was developed with independent lateral cerebral ventricular chambers. A gravity-driven pump pressurized the ventricular cavities to physiologic values. A qualitative study illustrated that the simulation has potential as an educational tool to train medical professionals in the ventriculostomy procedure.
CONCLUSIONS: The ventricular simulacrum can improve learning in a medical education environment. Rapid prototyping and multi-material casting techniques can produce patient-derived models for cost-effective and realistic surgical training scenarios.