Literature DB >> 23315670

The utilization of cranial models created using rapid prototyping techniques in the development of models for navigation training.

V Waran1, Devaraj Pancharatnam1, Hari Chandran Thambinayagam1, Rajagopal Raman2, Alwin Kumar Rathinam3, Yuwaraj Kumar Balakrishnan3, Tan Su Tung3, Z A Rahman3.   

Abstract

INTRODUCTION: Navigation in neurosurgery has expanded rapidly; however, suitable models to train end users to use the myriad software and hardware that come with these systems are lacking. Utilizing three-dimensional (3D) industrial rapid prototyping processes, we have been able to create models using actual computed tomography (CT) data from patients with pathology and use these models to simulate a variety of commonly performed neurosurgical procedures with navigation systems. AIM: To assess the possibility of utilizing models created from CT scan dataset obtained from patients with cranial pathology to simulate common neurosurgical procedures using navigation systems.
METHODOLOGY: Three patients with pathology were selected (hydrocephalus, right frontal cortical lesion, and midline clival meningioma). CT scan data following an image-guidance surgery protocol in DIACOM format and a Rapid Prototyping Machine were taken to create the necessary printed model with the corresponding pathology embedded. The ability in registration, planning, and navigation of two navigation systems using a variety of software and hardware provided by these platforms was assessed.
RESULTS: We were able to register all models accurately using both navigation systems and perform the necessary simulations as planned.
CONCLUSION: Models with pathology utilizing 3D rapid prototyping techniques accurately reflect data of actual patients and can be used in the simulation of neurosurgical operations using navigation systems. Georg Thieme Verlag KG Stuttgart · New York.

Entities:  

Mesh:

Year:  2013        PMID: 23315670     DOI: 10.1055/s-0032-1330960

Source DB:  PubMed          Journal:  J Neurol Surg A Cent Eur Neurosurg        ISSN: 2193-6315            Impact factor:   1.268


  9 in total

Review 1.  Medical 3D Printing for the Radiologist.

Authors:  Dimitris Mitsouras; Peter Liacouras; Amir Imanzadeh; Andreas A Giannopoulos; Tianrun Cai; Kanako K Kumamaru; Elizabeth George; Nicole Wake; Edward J Caterson; Bohdan Pomahac; Vincent B Ho; Gerald T Grant; Frank J Rybicki
Journal:  Radiographics       Date:  2015 Nov-Dec       Impact factor: 5.333

2.  Crisis Management Simulation: Review of Current Experience.

Authors:  Coulter Small; Divine Nwafor; Devan Patel; Fakhry Dawoud; Abeer Dagra; Jeremy Ciporen; Brandon Lucke-Wold
Journal:  SunText Rev Neurosci Psychol       Date:  2021-03-27

3.  3D-Printed Disease Models for Neurosurgical Planning, Simulation, and Training.

Authors:  Chul-Kee Park
Journal:  J Korean Neurosurg Soc       Date:  2022-06-28

4.  Patient-specific 3D printed model of biliary ducts with congenital cyst.

Authors:  Amee Allan; Catherine Kealley; Andrew Squelch; Yin How Wong; Chai Hong Yeong; Zhonghua Sun
Journal:  Quant Imaging Med Surg       Date:  2019-01

5.  Interactive navigation-guided ophthalmic plastic surgery: assessment of optical versus electromagnetic modes and role of dynamic reference frame location using navigation-enabled human skulls.

Authors:  Mohammad Javed Ali; Milind N Naik; Chetan Mallikarjuniah Girish; Mohammad Hasnat Ali; Swathi Kaliki; Tarjani Vivek Dave; Gautam Dendukuri
Journal:  Clin Ophthalmol       Date:  2016-11-25

Review 6.  3D printing in neurosurgery: A systematic review.

Authors:  Michael Randazzo; Jared M Pisapia; Nickpreet Singh; Jayesh P Thawani
Journal:  Surg Neurol Int       Date:  2016-11-14

7.  Current Applications and Future Perspectives of the Use of 3D Printing in Anatomical Training and Neurosurgery.

Authors:  Vivek Baskaran; Goran Štrkalj; Mirjana Štrkalj; Antonio Di Ieva
Journal:  Front Neuroanat       Date:  2016-06-24       Impact factor: 3.856

8.  The residual STL volume as a metric to evaluate accuracy and reproducibility of anatomic models for 3D printing: application in the validation of 3D-printable models of maxillofacial bone from reduced radiation dose CT images.

Authors:  Tianrun Cai; Frank J Rybicki; Andreas A Giannopoulos; Kurt Schultz; Kanako K Kumamaru; Peter Liacouras; Shadpour Demehri; Kirstin M Shu Small; Dimitris Mitsouras
Journal:  3D Print Med       Date:  2015-11-27

9.  Printing the Future-Updates in 3D Printing for Surgical Applications.

Authors:  Dekel Shilo; Omri Emodi; Ori Blanc; Dani Noy; Adi Rachmiel
Journal:  Rambam Maimonides Med J       Date:  2018-07-30
  9 in total

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