Building Three-Dimensional Intracranial Aneurysm Models from 3D-TOF MRA: a Validation Study.

To create realistic three-dimensional (3D) vascular models from 3D time-of-flight magnetic resonance angiography (3D-TOF MRA) of an intracranial aneurysm (IA). Thirty-two IAs in 31 patients were printed using 3D-TOF MRA source images from polylactic acid (PLA) raw material. Two observers measured the maximum IA diameter at the longest width twice separately. A total mean of four measurements as well as each observer's individual average MRA lengths were calculated. After printing, 3D-printed anatomic models (PAM) underwent computed tomography (CT) acquisition and each observer measured them using the same algorithm as applied to MRA. Inter- and intra-observer consistency for the MRA and CT measurements were analyzed using the intraclass correlation coefficient (ICC) and a Bland-Altman plot. The mean maximum aneurysm diameter obtained from four MRA evaluations was 8.49 mm, whereas it was 8.83 mm according to the CT 3D PAM measurement. The Wilcoxon test revealed slightly larger mean CT 3D PAM diameters than the MRA measurements. The Spearman's correlation test yielded a positive correlation between MRA and CT lengths of 3D PAMs. Inter and intra-observer consistency were high in consecutive MRA and CT measurements. According to Bland-Altman analyses, the aneurysmal dimensions obtained from CT were higher for observer 1 and observer 2 (a mean of 0.32 mm and 0.35 mm, respectively) compared to the MRA measurements. CT dimensions were slightly overestimated compared to MRA measurements of the created models. We believe the discrepancy may be related to the Laplacian algorithm applied for surface smoothing and the high slice thickness selection that was used. However, ICC provided high consistency and reproducibility in our cohort. Therefore, it is technically possible to produce 3D intracranial aneurysm models from 3D-TOF MRA images.

3D Brain Imaging in Vascular Segmentation of Cerebral Venous Sinuses.

The three-dimensional (3D) visualization of dural venous sinuses (DVS) networks is desired by surgical trainers to create a clear mental picture of the neuroanatomical orientation of the complex cerebral anatomy. Our purpose is to document those identified during routine 3D venography created through 3D models using two-dimensional axial images for teaching and learning neuroanatomy. Anatomical data were segmented and extracted from imaging of the DVS of healthy people. The digital data of the extracted anatomical surfaces was then edited and smoothed, resulting in a set of digital 3D models of the superior sagittal, inferior sagittal, transverse, and sigmoid, rectus sinuses, and internal jugular veins. A combination of 3D printing technology and casting processes led to the creation of realistic neuroanatomical models that include high-fidelity reproductions of the neuroanatomical features of DVS. The life-size DVS training models were provided good detail and representation of the spatial distances. Geometrical details between the neighboring of DVS could be easily manipulated and explored from different angles. A graspable, patient-specific, 3D-printed model of DVS geometry could provide an improved understanding of the complex brain anatomy. These models have various benefits such as the ability to adjust properties, to convert two-dimension images of the patient into three-dimension images, to have different color options, and to be economical. Neuroanatomy experts can model such as the reliability and validity of the designed models, enhance patient satisfaction with improved clinical examination, and demonstrate clinical interventions by simulation; thus, they teach neuroanatomy training with effective teaching styles.

Creation of 3-Dimensional Life Size: Patient-Specific C1 Fracture Models for Screw Fixation.

BACKGROUND: Transarticular screw fixation has fatal complications such as vertebral artery (VA), carotid artery, and spinal cord injuries. The landmarks for deciding the entry point for C1 lateral mass screws were clarified by using life-size 3-dimensional (3D) patient-specific spine models. METHODS: This study included a total of 10 patients with C1 fractures. Dual-energy computed tomography (CT) scan data from C1 pre- and postscrewing were modified into 3D patient-specific life-size cervical spine models. The detailed information, such as bony and vascular elements, of 13 separate parameters of C1 was used as an intraoperative reference. RESULTS: 3D patient-specific models were created preoperatively with the fracture and postoperatively with the screwed vertebrae. After CT scans of the models were measured, the life-size patient-specific models were proven to be individualized. 3D models assisted in determining the fracture locations, pedicle sizes, and positions of the VA. The range of the measurements for ideal point of entry reveals the need for patient-specific intervention was required. CONCLUSIONS: 3D models were used in surgical planning maximizing the possibility of ideal screw position and providing individualized information concerning cervical spinal anatomy. The individualized 3D printing screw insertion template was user-friendly, of moderate cost, and it enabled a radiation-free cervical screw insertion.

Development of Life-Size Patient-Specific 3D-Printed Dural Venous Models for Preoperative Planning.

BACKGROUND: Despite significant improvement in clinical care, operative strategies, and technology, neurosurgery is still risky, and optimal preoperative planning and anatomical assessment are necessary to minimize the risks of serious complications. Our purpose was to document the dural venous sinuses (DVS) and their variations identified during routine 3-dimensional (3D) venography created through 3D models for the teaching of complex cerebral anatomy. METHODS: 3D models of the DVS networks were printed. Compared with the controls, cases with cortical venous thrombosis have altered venous anatomy, which has not been previously compared. RESULTS: Geometrical changes between the neighboring DVS could be easily manipulated and explored from different angles. Modeling helped to conduct the examination in detail with reference to geometrical features of DVS, degree of asymmetry, its extension, location, and presence of hypoplasia/atresia channels. Challenging DVS anatomy was exposed with models of adverse anatomical variations of the DVS network, including highly angulated, asymmetrical view, narrowed lumens, and hypoplasia and atresia structures. It assisted us in comprehending spatial anatomy configuration of life-like models. CONCLUSIONS: Patient-specific models of DVS geometry could provide an improved understanding of the complex brain anatomy and better navigation in difficult areas and allow surgeons to anticipate anatomical issues that might arise during the operation. Such models offer opportunities to accelerate the development of expertise with respect to new and novel procedures as well as new surgical approaches and innovations, thus allowing novice neurosurgeons to gain valuable experience in surgical techniques without exposing patients to risk of harm.