Utility and reproducibility of 3-dimensional printed models in pre-operative planning of complex thoracic tumors

Abstract

Background and objectives: 3D-printed models are increasingly used for surgical planning. We assessed the utility, accuracy, and reproducibility of 3D printing to assist visualization of complex thoracic tumors for surgical planning.

Methods: Models were created from pre-operative images for three patients using a standard radiology 3D workstation. Operating surgeons assessed model utility using the Gillespie scale (1 = inferior to 4 = superior), and accuracy compared to intraoperative findings. Model variability was assessed for one patient for whom two models were created independently. The models were compared subjectively by surgeons and quantitatively based on overlap of depicted tissues, and differences in tumor volume and proximity to tissues.

Results: Models were superior to imaging and 3D visualization for surgical planning (mean score = 3.4), particularly for determining surgical approach (score = 4) and resectability (score = 3.7). Model accuracy was good to excellent. In the two models created for one patient, tissue volumes overlapped by >86.5%, and tumor volume and area of tissues ≤1 mm to the tumor differed by <15% and <1.8 cm² , respectively. Surgeons considered these differences to have negligible effect on surgical planning.

Conclusion: 3D printing assists surgical planning for complex thoracic tumors. Models can be created by radiologists using routine practice tools with sufficient accuracy and clinically negligible variability.

Keywords: 3D printing; chest wall invasion; mediastinal invasion; superior sulcus tumor; thoracic oncology; thoracic surgery.

Figure 1

Workflow of generation of 3D-printed models. Segmentation of aorta and supra-aortic vessels in contrast-enhanced CT is used to create an STL surface that encloses the (segmented) arterial blood pool. The STL surface is typically post-processed, including smoothing and trimming to the region of interest, hollowing to reduce printing material and time (blue arrow), and addition of connectors (black arrows) to adjacent structures, followed by 3D printing.

Figure 2

(A) Standard 3D visualization, (B) overlay of tumor and systemic vessel STL models on source contrast-enhanced CT acquisition, and overlay of bone segmentation on source non-contrast CT acquisition, and (C) post-processed STL model; tumor (black), systemic arteries (red), systemic veins (turquoise), pulmonary vasculature (deep green) and bones (white). Final 3D-printed model (D) demonstrates adherence of tumor to the subclavian artery and vertebral body, and separation from the subclavian vein.

Figure 3

3D-Printed model of Pancoast tumor (black), bone (white), systemic arteries (gray), systemic vein (translucent) and pulmonary vasculature (also white), and correlation with excised tissue in the operating room.

Figure 4

Contrast enhanced MRI (A) and CT (B) demonstrate two of the three focal areas of tumor recurrence in the patient with synovial sarcoma. 3D model (C) demonstrates the relationship of the tumor (black, arrow) with the bones (white), adjacent part of the diaphragm (translucent, thick arrow), prior Gortex mesh (green, dashed arrow), systemic arteries (grey), and systemic veins (translucent).

Figure 5

Model of the aorta and branch vessels generated by two independent radiology software operators. Vessel surface color reflects the distance of the vessel to the tumor, with green closest, and red >1 mm away. Slight difference in delineation of the branches of the subclavian artery by the two operators results in a quantitative difference in the area of the branches in close proximity to the tumor.