Application of a rapid and accurate safe-margin volume generation method in computer-assisted bone tumor resection surgery.
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INTRODUCTION: In computer-assisted bone tumor resection, surgeons manually plan cut planes with a safe margin before surgery and follow them using navigation during osteotomy. However, manual planning is prone to error and often fails to ensure adequate margins. To address this, we propose an efficient method to rapidly and accurately generate a 3D safe-margin volume that uniformly extends the tumor by a safe margin. METHODS: The study was conducted on 20 patients (9 males, 11 females) between May 2018 and October 2023. The average age was 41.75 ± 14.72 years (14-66) and the tumor types were chondrosarcoma in 5 cases, giant cell tumor in 5 cases, osteosarcoma in 2 cases, chordoma in 2 cases, Ewing sarcoma in 2 cases, spindle cell sarcoma in 1 case, osteochondroma in 1 case, chondromyxoid fibroma in 1 case and peripheral nerve sheath tumor in 1 case. The quality of the generated safe-margin volumes were assessed by visual comparison outcomes, geometric errors and maximum absolute geometric errors, time costs and clinical outcomes. RESULTS: All 20 patients were successfully followed up, with a mean follow-up duration of 42.30 ± 18.75 months (range: 3-86 months). The generated 3D safe-margin volumes were visually closer to the ground truth compared to those from the 3D morphological dilation and anisotropic distance transform methods. The method achieved a mean geometric error of approximately 0.10 mm, significantly lower than the dilation method (up to 10.00 mm) and the anisotropic method (about 1.00 mm). The average maximum absolute geometric error was 0.1818 mm, and statistical tests confirmed significant improvements (P-value < 0.01). The method also exhibited favorable computational efficiency, with an average runtime of 26.82 s, substantially faster than our previous point-based method (6.29 min) and acceptable for preoperative planning. CONCLUSION: In this study, we developed a fast and accurate safe-margin volume generation method by combining 3D image resampling with anisotropic distance transform. This method shows strong potential in clinical practice.