limitation was not testing small structures with 5
mm or less such as nerves and vessels for
1)
microsurgery. Continued research is needed to
ensure measurement accuracy in actual clinical
use. Another limitation was VR sickness caused
by wearing the HMD. In this study, no VR
2)
sickness symptoms were observed in all raters.
However, VR sickness is an issue that requires
verification for the safe and effective use of VR
technology.
Declarations
3)
The institutional research ethics committee
was exempted from reviewing this study because
it employed anonymized CT image data included
in the OsiriX DICOM image library from a
website authorized to be used for research and
4)
educational purposes. Informed consent was
obtained from all individual participants after we
fully explained the purpose of this study and the
experiment methods.
5)
Conclusion
A prototype of the length measure system
calledsynchro-caliperhas developed, which
enables directly measuring and assessing the VR
6)
Thompson JR, Leonard AC, Doarn CR, Roesch
MJ and Broderick TJ : Limited value of haptics
in virtual reality laparoscopic cholecystectomy
training. Surg Endosc. 25 : 1107-1114, 2011.
Goderstad JM, Sandvik L, Fosse E and Lieng M :
Development and validation of a general and
easy assessable scoring system for laparoscopic
skills using a virtual reality simulator. European
Journal of Obstetrics & Gynecology and Reproductive Biology : X. 4 : 100092. doi : 10.1016/j.
eurox. 2019. 100092, 2019.
Watkinson W, Raison R, Abe T, Harrison P,
Khan S, Van der Poel H, Dasgupta P and Ahmed
K : Establishing objective benchmarks in robotic
virtual reality simulation at the level of a
competent surgeon using the RobotiX Mentor
simulator. Postgraduate Medical Journal. 94 :
270-277, 2018.
Badash I, Burtt K, Solorzano CA and Carey JN :
Innovations in surgery simulation : a review of
past, current and future techniques. Annals of
Translational Medicine. 4 : 453. doi : 10.21037/
atm. 2016. 12. 24, 2016.
Shirk JD, Kwan L and Saigal C : The Use of
3-Dimensional, Virtual Reality Models for
Surgical Planning of Robotic Partial Nephrectomy. Urology. 125 : 92-97, 2019.
Kockro RA, Killeen T, Ayyad A, Glaser M,
Stadie A, Reisch R, Giese A and Schwandt E :
Aneurysm Surgery with Preoperative
70
7)
8)
9)
10)
11)
12)
13)
14)
15)
16)
R. Katayama et al.
Three-Dimensional Planning in a Virtual Reality Environment : Technique and Outcome
Analysis. World Neurosurgery. 96 : 489-499,
2019.
Boedecker C, Huettl F, Saalfeld P, Paschold M,
Kneist W, Baumgart J, Preim B, Hansen C, Lang
H and Huber T : Using virtual 3D-models in
surgical planning : workflow of an immersive
virtual reality application in liver surgery.
Langenbeckʼs Archives of Surgery. 406 : 911915, 2021.
Reitinger B, Bornik A, Beichel D and Schmalstieg D : Liver Surgery Planning Using Virtual
Reality. IEEE Computer Graphics and Applications. 26 : 36-47, 2006.
Zhao L, Patel PK and Cohen M : Application of
Virtual Surgical Planning with Computer
Assisted Design and Manufacturing Technology to Cranio-Maxillofacial Surgery. Archives of
Plastic Surgery 39 : 309-316, 2012.
Chen Y, Li H, Wu D, Bi K and Liu C : Surgical
planning and manual image fusion based on 3D
model facilitate laparoscopic partial nephrectomy for intrarenal tumors. World Journal of
Urology. 32 : 1493-1499, 2013.
Adolphs N, Liu W, Keeve E and Hoffmeister B :
Craniomaxillofacial surgery planning based on
3D models derived from Cone-Beam CT data.
Computer Aided Surgery. 18 : 101-108, 2013.
Shirakawa T, Koyama Y, Mizoguchi H and
Yoshitatsu M : Morphological analysis and
preoperative simulation of a double-chambered
right ventricle using 3-dimensional printing
technology. Interactive CardioVascular and
Thoracic Surgery. 22 : 688-691, 2016.
Wake N, Rude T, Kang SK, Stifelman MD, Borin
JF, Sodickson DK, Huang WC and Chandarana
H : 3D printed renal cancer models derived from
MRI data : application in pre-surgical planning.
Abdominal Radiology. 42 : 1501-1509, 2017.
Clark AD, Barone DG, Candy N, Guilfoyle M,
Budohoski K, Hofmann R, Santarius T, Kirollos
R and Trivedi RA : The Effect of 3-Dimensional
Simulation on Neurosurgical Skill Acquisition
and Surgical Performance : A Review of the
Literature. Journal of Surgical Education. 74 :
828-836, 2017.
Preim B, Tietjen C, Spindler W and Peitgen HO :
Integration of Measurement Tools in Medical 3d
Visualizations. Proceedings of the conference on
Visualization ʼ02 : 21-28, 2002.
Timonen T, Dietz A, Linder P, Lehtimäki A,
Löppönen H, Elomaa AP and Mustajärvi M :
17)
18)
19)
20)
21)
22)
23)
24)
25)
26)
27)
28)
The effect of virtual reality on temporal bone
anatomy evaluation and performance. European
Archives of Oto-Rhino-Laryngology. 279 :
4303-4312, 2021.
Anik AA, Xavier BA, Hansmann J, Ansong E,
Chen J, Zhao L and Michals E : Accuracy and
Reproducibility of Linear and Angular Measurements in Virtual Reality : a Validation Study.
Journal of Digital Imaging. 33 : 111-120, 2020.
Zhuoshu Li, Zixin Li, Cheng Peng, Mingyi Zhao
and Qingnan He : A Bibliometric Analysis of
Virtual Reality in Anatomy Teaching Between
1999 and 2022. Frontiers in Education. 7 :
874406. doi : 10.3389/feduc. 2022. 874406, 2022.
Autodesk FBX Software Developer Kit. Retrieved August 18, 2022 from https: //www.
autodesk.com/developer-network/platform-tec
hnologies/fbx-converter-archives
3D SYSTEMS What Is An STL File?. Retrieved
August 18, 2022 from https://www.3dsystems.
com/quickparts/learning-center/what-is-stl-fi
le
Marro A, Bandukwala T and Mak W : ThreeDimensional Printing and Medical Imaging : A
Review of the Methods and Applications.
Current Problems in Diagnostic Radiology. 45 :
2-9, 2016.
Jarque CM and Bera AK : A Test for Normality
of Observations and Regression Residuals.
International Statistical Review. 55 : 163-172,
1987.
Weir JP : Quantifying test-retest reliability
using the intraclass correlation coefficient and
the SEM. J Strength Cond Res. 19 : 231-241,
2005.
Dunn OJ : Multiple Comparisons among Means.
J Am Stat Assoc. 56 : 52-64. 1961.
Wheeler G, Deng S, Pushparajah K, Schnabel JA,
Simpson JM and Gomez : Virtual linear
measurement system for accurate quantification of medical images. Healthc Technol Lett. 6 :
220-225, 2019.
Laval PB : Mathematics for Computer Graphics-Barycentric Coordinates. Kennesaw State
University, Tech. Rep : 1-9, 2003.
Lecerf G, Fessy MH, Philippot R, Massin P,
Giraud F, Flecher X, Girard J, Mertl P,
Marchetti E and Stindel E : Femoral offset :
Anatomical concept, definition, assessment,
implications for preoperative templating and hip
arthroplasty. Orthop Traumatol-Sur. 95 : 210219, 2009.
Wang Y and MacKenzie CL : The Role of
VR measurement system for medical education and training
29)
30)
31)
32)
33)
Contextual Haptic and Visual Constraints on
Object Manipulation in Virtual Environments.
Proceedings of the SIGCHI conference on
Human Factors in Computing Systems. 2 : 532539, 2000.
Jang S, Vitale JM, Jyung RW and Black JB :
Direct manipulation is better than passive
viewing for learning anatomy in a three-dimensional virtual reality environment. Computers &
Education. 106 : 150-165, 2017.
Duarte ML, Santos LR, Guimarães Júnior JB and
Peccin MS : Learning anatomy by virtual reality
and augmented reality. A scope review :
Apprentissage de lʼanatomie par la réalité
virtuelle et la réalité augmentée. Morphologie.
104 : 254-266, 2020.
Nakai K, Terada S, Takahara A, Hage D, Tubbs
RS and Iwanaga J : Anatomy education for
medical students in a virtual reality workspace :
A pilot study. Clin Anat. 35 : 40-44, 2022.
Pringle Z and Rea PM : Do Digital Technologies
Enhance Anatomical Education?. Practice and
Evidence of Scholarship of Teaching and
Learning in Higher Education. 13 : 2-27, 2018.
Chen S, Zhu J, Cheng C, Pan Z, Liu L, Du J, Shen
X, Shen Z, Zhu H, Liu J, Yang H, Ma C and Pan
H : Can virtual reality improve traditional ana-
71
tomy education programmers? A mixed
methods study on the use of a 3D skull model.
BMC Medical Educ. 20 : 395, 2020.
34) Meyer ER and Cui D : Anatomy Visualizations
Using Stereopsis : Assessment and Implication
of Stereoscopic Virtual Models in Anatomical
Education. Biomedical Visualisation. 6 : 117-130,
2020.
35) Naidoo N, Al-Sharif GA, Khan R, Azar A and
Omer A : In death there is life : perceptions of
the university community regarding body
donation for educational purposes in the United
Arab Emirates. Heliyon. 7 : e07650, 2021.
36) Karbasi Z and Kalhori SRN : Application and
evaluation of virtual technologies for anatomy
education to medical students : A review. Med J
Islamic Repub Iran. 34 : 163, 2020.
37) Smith CF, Tollemache N, Covill D and Johnston
M : Take Away Body Parts! An Investigation
into the Use of 3D-Printed Anatomical Models
in Undergraduate Anatomy Education. Anat Sci
Educ. 11 : 44-53, 2018.
38) Lau I and Sun Z : Three-dimensional printing in
congenital heart disease : A systematic review. J
Med Radiat Sci. 65 : 226-236, 2018.
(Received for publication November 16, 2022)
72
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(和文抄録)
医学教育のための仮想現実空間に表現した物体長計測システムの開発
片 山 礼 司1)2),杜 下 淳 次3),藪 内 英 剛3)
1)
九州大学大学院 医学系学府 保健学専攻 博士後期課程
2)
久留米大学 医学部 医学教育研究センター
3)
九州大学大学院 医学研究院 保健学部門 医用量子線科学分野
【目的】本研究は,head-mounted display(HMD)装着下でバーチャルリアリティ(VR)空間に表現
した VR 解剖モデルの直接的な計測評価が可能なデジタルノギスを利用した長さ計測システムのプロ
トタイプを開発し,計測の正確さと再現性を評価することで,医学・医療分野での活用の可能性と意
義を考察することを目的とした.
【方法】実物体と仮想物体の位置・動きを同期するセンサで,現実空間のデジタルノギスの jaw と VR
空間の仮想 jaw とを紐付け,VR 空間で使用できる長さの計測システムを開発した.この計測システ
ムの評価は,一辺が 5,10,25,50,100 mm の仮想キューブと,VR で表現した三つの VR 解剖モデ
ル(血管,骨格,臓器)に対して行った.キューブは 1 名の被験者による計測,VR 解剖モデルは 2 名
の被験者による計測を行い,結果は,キューブと VR 解剖モデルに対する計測誤差とその統計的分析
により評価した.また,被験者内の計測の信頼性と被験者間の計測の信頼性を,級内相関係数(intraclass correlation coefficients:ICC)を求め評価した.
【結果】開発した計測システムは,現実空間のデジタルノギスの jaw と VR 空間の仮想 jaw が連動し,
HMD 装着下で VR 空間上に表現した物体の長さを計測できた.キューブの計測誤差は,すべての
キューブサイズで 0.5 mm 以内であった.また,各キューブサイズの計測誤差間には統計的有意差を
認めなかった.VR 解剖モデルの計測誤差は,すべての解剖部位で 0.3 mm 以内で,各 VR 解剖モデ
ルの計測誤差の間にも統計的有意差を認めなかった.被験者内および被験者間の計測の信頼性(ICC)
はともに 0.99 と十分に高い値を示した.
【結論】HMD 装着下で VR 解剖モデルの直接的な計測評価が可能な長さ計測システムのプロトタイプ
を開発でき,医学・医療分野での活用の可能性がある.
キーワード:仮想現実,医学教育,手術トレーニング,解剖モデル,物体長計測システム
...