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A novel method of light projection and modular jigs to improve accuracy in bone sarcoma resection.

Guangyu HeAmos Z DaiVamiq M MustahsanAadit T ShahLiming LiJafar A KhanMichael R BielskiDavid E KomatsuImin KaoFazel A Khan
Published in: Journal of orthopaedic research : official publication of the Orthopaedic Research Society (2022)
We developed a novel method using a combined light-registration/light-projection system along with an off-the-shelf, instant-assembly modular jig construct that could help surgeons improve bone resection accuracy during sarcoma surgery without many of the associated drawbacks of 3D printed custom jigs or computer navigation. In the novel method, the surgeon uses a light projection system to precisely align the assembled modular jig construct on the bone. In a distal femur resection model, 36 sawbones were evenly divided into 3 groups: manual-resection (MR), conventional 3D-printed custom jig resection (3DCJ), and the novel projector/modular jig (PMJ) resection. In addition to sawbones, a single cadaver experiment was also conducted to confirm feasibility of the PMJ method in a realistic operative setting. The PMJ method improved resection accuracy when compared to MR and 3DCJ, respectively: 0.98 mm versus 7.48 mm (p < 0.001) and 3.72 mm (p < 0.001) in mean corner position error; 1.66 mm versus 9.70 mm (p < 0.001) and 4.32 mm (p = 0.060) in mean maximum deviation error; 0.79°-4.78° (p < 0.001) and 1.26° (p > 0.999) in mean depth angle error. The PMJ method reduced the mean front angle error from 1.72° to 1.07° (p = 0.507) when compared to MR but was slightly worse compared to 0.61° (p = 0.013) in 3DCJ. The PMJ method never showed an error greater than 3 mm, while the maximum error of other two control groups were almost 14 mm. Similar accuracy was found with the PMJ method on the cadaver. A novel method using a light projector with modular jigs can achieve high levels of bone resection accuracy, but without many of the associated drawbacks of 3D printed jigs or computer navigation technology.
Keyphrases
  • bone mineral density
  • minimally invasive
  • machine learning
  • computed tomography
  • acute coronary syndrome
  • atrial fibrillation
  • finite element