ABSTRACT
Knowledge of the minimal detectable bone fracture gap is essential in three-dimensional (3D) models, particularly in pre-operative planning of osteosynthesis to avoid overlooking gaps. In this study, defined incisions and bony displacements ranging from 100 to 400 µm were created in diaphyseal radii in 20 paired forearm specimens and verified with light microscopy. The specimens were scanned utilizing different computed tomography (CT) technologies/scanners, specimen positionings, scan protocols, image segmentations, and processing protocols. Inter- and intra-operator variabilities were reported as coefficient kappa. In CT images, fracture gaps of 100 µm and bone lamellae of 300 µm and 400 µm width were identified at a rate of 80 to 100%, respectively, independent of the investigated settings. In contrast, only 400µm incisions and bony displacements were visible in digital 3D models, with detection rates dependent on CT technology, image segmentation, and post-processing algorithm. 3D bone models based on state-of-the-art CT imaging can reliably visualize clinically relevant bone fracture gap sizes. However, verification of fractures to be surgically addressed should be verified with the original CT image series.
ABSTRACT
The introduction of three-dimensional (3D) printed anatomical models has garnered interest in pre-operative planning, especially in orthopedic and trauma surgery. Identifying potential error sources and quantifying their effect on the model dimensional accuracy are crucial for the applicability and reliability of such models. In this study, twenty radii were extracted from anatomic forearm specimens and subjected to osteotomy to simulate a defined fracture of the distal radius (Colles' fracture). Various factors, including two different computed tomography (CT) technologies (energy-integrating detector (EID) and photon-counting detector (PCD)), four different CT scanners, two scan protocols (i.e., routine and high dosage), two different scan orientations, as well as two segmentation algorithms were considered to determine their effect on 3D model accuracy. Ground truth was established using 3D reconstructions of surface scans of the physical specimens. Results indicated that all investigated variables significantly impacted the 3D model accuracy (p < 0.001). However, the mean absolute deviation fell within the range of 0.03 ± 0.20 to 0.32 ± 0.23 mm, well below the 0.5 mm threshold necessary for pre-operative planning. Intra- and inter-operator variability demonstrated fair to excellent agreement for 3D model accuracy, with an intra-class correlation (ICC) of 0.43 to 0.92. This systematic investigation displayed dimensional deviations in the magnitude of sub-voxel imaging resolution for all variables. Major pitfalls included missed or overestimated bone regions during the segmentation process, necessitating additional manual editing of 3D models. In conclusion, this study demonstrates that 3D bone fracture models can be obtained with clinical routine scanners and scan protocols, utilizing a simple global segmentation threshold, thereby providing an accurate and reliable tool for pre-operative planning.
ABSTRACT
OBJECTIVES: A 3-dimensionally (3D) engineered model for simulation of aortic valve and proximal aortic procedures is a reliable tool both for training young surgeons and for simulating complex cases. To achieve a realistic simulation, the artificial model should reproduce the angles and orientations of the cardiac structures based on the patient's anatomical condition, reproduce tissue mechanical characteristics and be easy to obtain and easy to use. The goal of the study was the production and validation of realistic training models, based on the patient's actual anatomical characteristics, to provide training for aortic valve procedures. METHODS: An anatomical model was manufactured using 3D printing and silicone casting. The digital anatomical model was obtained by segmenting computed tomography imaging. The segmented geometrical images were processed and a casting mould was designed. The mould was manufactured on a 3D printer. Silicone was cast into the mould; after curing, the finished model was ready. The realistic reproduction was evaluated by mechanical hardness tests and a survey by cardiac surgeons. RESULTS: Six 3D silicone models were produced that represented the patient's anatomy including aortic valve leaflets, aortic root with coronary ostia, ascending aorta and proximal arch. Aortic valve replacement was performed, and 100% of the participants evaluated the model in a survey as perfectly reproducing anatomy and surgical handling. CONCLUSIONS: We produced a realistic, cost-effective simulator for training purposes and for simulation of complex surgical cases. The model reproduced the real angulation and orientation of the aortic structures inside the mediastinum, permitting a real-life simulation of the desired procedure. This model offers opportunities to simulate various surgical procedures.
