Augmented reality in bone tumour resection: An experimental study

H. S. Cho, Y. K. Park, S. Gupta, C. Yoon, I. Han, H. S. Kim, H. Choi, J. Hong

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Objectives: We evaluated the accuracy of augmented reality (AR)-based navigation assistance through simulation of bone tumours in a pig femur model. Methods: We developed an AR-based navigation system for bone tumour resection, which could be used on a tablet pc. To simulate a bone tumour in the pig femur, a cortical window was made in the diaphysis and bone cement was inserted. A total of 133 pig femurs were used and tumour resection was simulated with AR-assisted resection (164 resection in 82 femurs, half by an orthropaedic oncology expert and half by an orthopaedic resident) and resection with the conventional method (82 resection in 41 femurs). In the conventional group, resection was performed after measuring the distance from the edge of the condyle to the expected resection margin with a ruler as per routine clinical practice. Results: The mean error of 164 resections in 82 femurs in the AR group was 1.71 mm (0 to 6). The mean error of 82 resections in 41 femurs in the conventional resection group was 2.64 mm (0 to 11) (p < 0.05, one-way analysis of variance). The probabilities of a surgeon obtaining a 10 mm surgical margin with a 3 mm tolerance were 90.2% in AR-assisted resections, and 70.7% in conventional resections. Conclusion We demonstrated that the accuracy of tumour resection was satisfactory with the help of the AR navigation system, with the tumour shown as a virtual template. In addition, this concept made the navigation system simple and available without additional cost or time.

Original languageEnglish
Pages (from-to)137-143
Number of pages7
JournalBone and Joint Research
Volume6
Issue number3
DOIs
StatePublished - Mar 2017

Fingerprint

Femur
Bone and Bones
Neoplasms
Swine
Diaphyses
Bone Cements
Tablets
Orthopedics
Analysis of Variance
Costs and Cost Analysis

Keywords

  • Augmented reality
  • Bone tumour
  • Navigation

Cite this

Cho, H. S. ; Park, Y. K. ; Gupta, S. ; Yoon, C. ; Han, I. ; Kim, H. S. ; Choi, H. ; Hong, J. / Augmented reality in bone tumour resection : An experimental study. In: Bone and Joint Research. 2017 ; Vol. 6, No. 3. pp. 137-143.
@article{fa3a3c43bb8245fe896b4b9644a21223,
title = "Augmented reality in bone tumour resection: An experimental study",
abstract = "Objectives: We evaluated the accuracy of augmented reality (AR)-based navigation assistance through simulation of bone tumours in a pig femur model. Methods: We developed an AR-based navigation system for bone tumour resection, which could be used on a tablet pc. To simulate a bone tumour in the pig femur, a cortical window was made in the diaphysis and bone cement was inserted. A total of 133 pig femurs were used and tumour resection was simulated with AR-assisted resection (164 resection in 82 femurs, half by an orthropaedic oncology expert and half by an orthopaedic resident) and resection with the conventional method (82 resection in 41 femurs). In the conventional group, resection was performed after measuring the distance from the edge of the condyle to the expected resection margin with a ruler as per routine clinical practice. Results: The mean error of 164 resections in 82 femurs in the AR group was 1.71 mm (0 to 6). The mean error of 82 resections in 41 femurs in the conventional resection group was 2.64 mm (0 to 11) (p < 0.05, one-way analysis of variance). The probabilities of a surgeon obtaining a 10 mm surgical margin with a 3 mm tolerance were 90.2{\%} in AR-assisted resections, and 70.7{\%} in conventional resections. Conclusion We demonstrated that the accuracy of tumour resection was satisfactory with the help of the AR navigation system, with the tumour shown as a virtual template. In addition, this concept made the navigation system simple and available without additional cost or time.",
keywords = "Augmented reality, Bone tumour, Navigation",
author = "Cho, {H. S.} and Park, {Y. K.} and S. Gupta and C. Yoon and I. Han and Kim, {H. S.} and H. Choi and J. Hong",
year = "2017",
month = "3",
doi = "10.1302/2046-3758.63.BJR-2016-0289.R1",
language = "English",
volume = "6",
pages = "137--143",
journal = "Bone and Joint Research",
issn = "2046-3758",
publisher = "British Editorial Society of Bone and Joint Surgery",
number = "3",

}

Augmented reality in bone tumour resection : An experimental study. / Cho, H. S.; Park, Y. K.; Gupta, S.; Yoon, C.; Han, I.; Kim, H. S.; Choi, H.; Hong, J.

In: Bone and Joint Research, Vol. 6, No. 3, 03.2017, p. 137-143.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Augmented reality in bone tumour resection

T2 - An experimental study

AU - Cho, H. S.

AU - Park, Y. K.

AU - Gupta, S.

AU - Yoon, C.

AU - Han, I.

AU - Kim, H. S.

AU - Choi, H.

AU - Hong, J.

PY - 2017/3

Y1 - 2017/3

N2 - Objectives: We evaluated the accuracy of augmented reality (AR)-based navigation assistance through simulation of bone tumours in a pig femur model. Methods: We developed an AR-based navigation system for bone tumour resection, which could be used on a tablet pc. To simulate a bone tumour in the pig femur, a cortical window was made in the diaphysis and bone cement was inserted. A total of 133 pig femurs were used and tumour resection was simulated with AR-assisted resection (164 resection in 82 femurs, half by an orthropaedic oncology expert and half by an orthopaedic resident) and resection with the conventional method (82 resection in 41 femurs). In the conventional group, resection was performed after measuring the distance from the edge of the condyle to the expected resection margin with a ruler as per routine clinical practice. Results: The mean error of 164 resections in 82 femurs in the AR group was 1.71 mm (0 to 6). The mean error of 82 resections in 41 femurs in the conventional resection group was 2.64 mm (0 to 11) (p < 0.05, one-way analysis of variance). The probabilities of a surgeon obtaining a 10 mm surgical margin with a 3 mm tolerance were 90.2% in AR-assisted resections, and 70.7% in conventional resections. Conclusion We demonstrated that the accuracy of tumour resection was satisfactory with the help of the AR navigation system, with the tumour shown as a virtual template. In addition, this concept made the navigation system simple and available without additional cost or time.

AB - Objectives: We evaluated the accuracy of augmented reality (AR)-based navigation assistance through simulation of bone tumours in a pig femur model. Methods: We developed an AR-based navigation system for bone tumour resection, which could be used on a tablet pc. To simulate a bone tumour in the pig femur, a cortical window was made in the diaphysis and bone cement was inserted. A total of 133 pig femurs were used and tumour resection was simulated with AR-assisted resection (164 resection in 82 femurs, half by an orthropaedic oncology expert and half by an orthopaedic resident) and resection with the conventional method (82 resection in 41 femurs). In the conventional group, resection was performed after measuring the distance from the edge of the condyle to the expected resection margin with a ruler as per routine clinical practice. Results: The mean error of 164 resections in 82 femurs in the AR group was 1.71 mm (0 to 6). The mean error of 82 resections in 41 femurs in the conventional resection group was 2.64 mm (0 to 11) (p < 0.05, one-way analysis of variance). The probabilities of a surgeon obtaining a 10 mm surgical margin with a 3 mm tolerance were 90.2% in AR-assisted resections, and 70.7% in conventional resections. Conclusion We demonstrated that the accuracy of tumour resection was satisfactory with the help of the AR navigation system, with the tumour shown as a virtual template. In addition, this concept made the navigation system simple and available without additional cost or time.

KW - Augmented reality

KW - Bone tumour

KW - Navigation

UR - http://www.scopus.com/inward/record.url?scp=85018669253&partnerID=8YFLogxK

U2 - 10.1302/2046-3758.63.BJR-2016-0289.R1

DO - 10.1302/2046-3758.63.BJR-2016-0289.R1

M3 - Article

AN - SCOPUS:85018669253

VL - 6

SP - 137

EP - 143

JO - Bone and Joint Research

JF - Bone and Joint Research

SN - 2046-3758

IS - 3

ER -