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논문 기본 정보

자료유형
학위논문
저자정보

조환성 (서울대학교, 서울대학교 대학원)

발행연도
2015
저작권
서울대학교 논문은 저작권에 의해 보호받습니다.

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이 논문의 연구 히스토리 (2)

초록· 키워드

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Introduction: AR is defined as a real-time direct or indirect view of a physical real-world environment that has been enhanced/augmented by adding virtual computer-generated information to it. AR applications to orthopaedic surgery are not yet clinically available, but may include bone tumor resection. We developed an AR-based navigation system which simply requires tablet PC instead of huge and complex navigation system. We evaluated the accuracy of AR-based navigation assistance in resection of the bone tumor through a simulation of bone tumor in the pig femora.

Methods: One hundred and twenty-three pig femora were employed in simulation of bone tumor. A cortical window was made on the diaphysis and bone cement was inserted. CT scan was used to measure the length of bones and extent of cement inserted in all 123 femora. Tumor resection was simulated into 3 manners. One was AR-assisted resection by an expert orthopedic oncologist, another was AR-assisted resection by a junior orthopedic resident and the other was resection by conventional method. Bone tumor resection was simulated with 10-millimeter safety margin proximally and distally to bone cement. The distance from the edge of cement to the resection margin was evaluated by another orthopedic surgeon. Two hundred and forty-six surgical margins of 123 femora were evaluated. Oneway ANOVA test was used for statistical comparison of the error between groups.

Results: A statistically significant difference was observed between AR-assisted and conventional resections (p<0.05). The mean error of 164 resections in 82 femora in the AR group was 1.71 mm (range, 0?6 mm: 1.76 mm in the expert resections and 1.65 mm in the resident resections). The mean error of 82 resections in 41 femora in the conventional group was 2.64 mm (range, 0?11 mm). The probabilities of a surgeon obtaining a 10-mm surgical margin with a 3-mm tolerance were 87.8% in AR-assisted resections by an expert, 92.7% in AR-assisted resections by a resident, and 72.0% in conventional resections by an expert.

Conclusions: We developed an AR-based navigation system which can run on tablet PC. We suggest that AR based navigation system is useful for safe resection of bone malignancy.

목차

1. Introduction ---------------------------------------------------------------- 1
2. Materials and Methods -------------------------------------------------- 3
3. Results --------------------------------------------------------------------- 13
4. Conclusions --------------------------------------------------------------- 17
5. References ----------------------------------------------------------------- 21
List of figures
Figure 2.1 ------------------------------------------------------------------- 4
Figure 2.2 ------------------------------------------------------------------- 5
Figure 2.3 ------------------------------------------------------------------- 6
Figure 2.4 ------------------------------------------------------------------- 7
Figure 2.5 ------------------------------------------------------------------- 8
Figure 2.6 ------------------------------------------------------------------ 10
Figure 2.7 ------------------------------------------------------------------ 11
Figure 3.1 ------------------------------------------------------------------ 13
Figure 3.2 ------------------------------------------------------------------ 15
Figure 3.3 ------------------------------------------------------------------ 15
Figure 3.4 ------------------------------------------------------------------ 16

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