APPLICATIONS OF MODERN IMAGING TECHNOLOGY IN ORTHOPAEDIC TRAUMA SURGERY
Przemysław KRAKOWSKI
Orthopedic Department, Łęczna Hospital, Krasnystawska 52, 21-010 Łęczna (Poland)
Robert KARPIŃSKI
r.karpinski@pollub.plDepartment of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin (Poland)
Marcin MACIEJEWSKI
* Institute of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, (Poland)
Abstract
Orthopaedic trauma surgery is a complex surgical speciality in which anatomy, physiology and physics are mixed. Proper diagnosing and based on that planning and performing surgery is of crucial matter. This article briefly summarizes available radiological modalities used for diagnostics and for surgical planning. It focuses on utility of rapid prototyping process in trauma surgery. Moreover, a case study in which this technique was used is described. Rapid prototyping proved its usefulness and in future it may become a modality of choice for planning complex trauma procedures.
Keywords:
medical imaging, 3D reconstructions, orthopaedic trauma surgeryReferences
The ATLS Subcommittee, American College of Surgeons’ Committee on Trauma, and the International ATLS working group.(2013). Advanced trauma life support(ATLS): the ninth edition. Journal of Trauma and Acute Care Surgery, 74(5), 1363-1366. https://doi.org/10.1097/TA.0b013e31828b82f5
Google Scholar
Bargar, W. L., Bauer, A., & Börner, M. (1998). Primary and revision total hip replacement using the Robodoc system. Clinical Orthopaedics and Related Research, 354, 82–91.
Google Scholar
Bégué, T. (2014). Articular fractures of the distal humerus. Orthopaedics & Traumatology: Surgery & Research, 100(suppl_1), S55–S63. https://doi.org/10.1016/j.otsr.2013.11.002
Google Scholar
Berrington de González, A., Mahesh, M., Kim, K. P., Bhargavan, M., Lewis, R., Mettler, F., & Land, C. (2009). Projected Cancer Risks From Computed Tomographic Scans Performed in the United States in 2007. Archives of Internal Medicine, 169(22), 2071–2077. https://doi.org/10.1001/archinternmed.2009.440
Google Scholar
Bächler, R., Bunke, H., & Nolte, L. P. (2001). Restricted surface matching? Numerical optimization and technical evaluation. Computer Aided Surgery, 6(3), 143–152. https://doi.org/10.1002/igs.1017
Google Scholar
Crawford, R., Walley, G., Bridgman, S., & Maffulli, N. (2007). Magnetic resonance imaging versus arthroscopy in the diagnosis of knee pathology, concentrating on meniscal lesions and ACL tears: a systematic review. British Medical Bulletin, 84(1), 5–23. https://doi.org/10.1093/bmb/ldm022
Google Scholar
Cunningham, B., Jackson, K., & Ortega, G. (2014). Intraoperative CT in the Assessment of Posterior Wall Acetabular Fracture Stability. Orthopedics, 37(4), e328–e331. https://doi.org/10.3928/01477447-20140401-51
Google Scholar
Dale, J. D., Ha, A. S., & Chew, F. S. (2013). Update on Talar Fracture Patterns: A Large Level I Trauma Center Study. American Journal of Roentgenology, 201(5), 1087–1092. https://doi.org/10.2214/AJR.12.9918
Google Scholar
Falchi, M., & Rollandi, G. A. (2004). CT of pelvic fractures. European Journal of Radiology, 50(1), 96–105. https://doi.org/10.1016/j.ejrad.2003.11.019
Google Scholar
Honl, M., Dierk, O., Gauck, C., Carrero, V., Lampe, F., Dries, S., Quante, M., Schwieger, K., Hille, E., & Morlock, M. M. (2003). Comparison of robotic-assisted and manual implantation of a primary total hip replacement. A prospective study. The Journal of Bone and Joint Surgery. American Volume, 85-A(8), 1470–1478.
Google Scholar
Jacob, A. L., Messmer, P., Kaim, A., Suhm, N., Regazzoni, P., & Baumann, B. (2000). A wholebody registration-free navigation system for image-guided surgery and interventional radiology. Investigative Radiology, 35(5), 279–288. https://doi.org/10.1097/00004424-200005000-00001
Google Scholar
Jenkins, P. J., Slade, K., Huntley, J. S., & Robinson, C. M. (2008). A comparative analysis of the accuracy, diagnostic uncertainty and cost of imaging modalities in suspected scaphoid fractures. Injury, 39(7), 768–774. https://doi.org/10.1016/j.injury.2008.01.003
Google Scholar
Kemppainen, J., Pennock, A. T., Roocroft, J. H., Bastrom, T. P., & Mubarak, S. J. (2014). The Use of a Portable CT Scanner for the Intraoperative Assessment of Talocalcaneal Coalition Resections: Journal of Pediatric Orthopaedics, 34(5), 559–564. https://doi.org/10.1097/BPO.0000000000000176
Google Scholar
Lauterbur, P. C. (1973). Image Formation by Induced Local Interactions: Examples Employing Nuclear Magnetic Resonance. Nature, 242(5394), 190–191. https://doi.org/10.1038/242190a0
Google Scholar
MacDessi, S. J., Jang, B., Harris, I. A., Wheatley, E., Bryant, C., & Chen, D. B. (2014). A comparison of alignment using patient specific guides, computer navigation and conventional instrumentation in total knee arthroplasty. The Knee, 21(2), 406–409. https://doi.org/10.1016/j.knee.2013.11.004
Google Scholar
Meskers, C. G. M., Fraterman, H., van der Helm, F. C. T., Vermeulen, H. M., & Rozing, P. M. (1999). Calibration of the “Flock of Birds” electromagnetic tracking device and its application in shoulder motion studies. Journal of Biomechanics, 32(6), 629–633. https://doi.org/10.1016/S0021-9290(99)00011-1
Google Scholar
Mulford, J. S., Babazadeh, S., & Mackay, N. (2016). Three-dimensional printing in orthopaedic surgery: review of current and future applications: Three-dimensional printing in orthopaedic surgery. ANZ Journal of Surgery, 86(9), 648–653. https://doi.org/10.1111/ans.13533
Google Scholar
Ohashi, K., Sanghvi, T., El-Khoury, G. Y., Ahn, J. M., Bennett, D. L., Geijer, M., Inaoka, T., Berbaum, K. (2015). Diagnostic accuracy of 3D color volume-rendered CT images for peroneal tendon dislocation in patients with acute calcaneal fractures. Acta Radiologica, 56(2), 190–195. https://doi.org/10.1177/0284185114522224
Google Scholar
Röntgen, W. C. (1896). On a New Kind of Rays. Nature, 53, 274–276. https://doi.org/10.1038/053274b0
Google Scholar
Oszwald, M., Citak, M., Kendoff, D., Kowal, J., Amstutz, C., Kirchhoff, T., Nolte, L. P., Krettek, C., & Hüfner, T. (2008). Accuracy of navigated surgery of the pelvis after surface matching with an a-mode ultrasound probe. Journal of Orthopaedic Research, 26(6), 860–864. https://doi.org/10.1002/jor.20551
Google Scholar
Oszwald, M., Westphal, R., Bredow, J., Calafi, A., Hufner, T., Wahl, F., Krettek, Ch., & Gosling, T. (2010). Robot-assisted fracture reduction using three-dimensional intraoperative fracture visualization: An experimental study on human cadaver femora. Journal of Orthopaedic Research, 28(9), 1240–1244. https://doi.org/10.1002/jor.21118
Google Scholar
Puig, S., Kuruvilla, Y. C. K., Ebner, L., & Endel, G. (2015). Magnetic resonance tomography of the knee joint. Skeletal Radiology, 44(10), 1427–1434. https://doi.org/10.1007/s00256-015-2178-5
Google Scholar
Rahmathulla, G., Nottmeier, E. W., Pirris, S. M., Deen, H. G., & Pichelmann, M. A. (2014). Intraoperative image-guided spinal navigation: technical pitfalls and their avoidance. Neurosurgical Focus, 36(3), E3. https://doi.org/10.3171/2014.1.FOCUS13516
Google Scholar
Rajasekaran, S., Karthik, K., Ravi Chandra, V., Rajkumar, N., & Dheenadhayalan, J. (2010). Role of intraoperative 3D C-arm-based navigation in percutaneous excision of osteoid osteoma of long bones in children: Journal of Pediatric Orthopaedics B, 19(2), 195–200. https://doi.org/10.1097/BPB.0b013e328333997a
Google Scholar
Richmond, C. (2004). Sir Godfrey Hounsfield. BMJ, 329, 687. https://doi.org/10.1136/bmj.329.7467.687
Google Scholar
Rosas, H. G. (2014). Magnetic Resonance Imaging of the Meniscus. Magnetic Resonance Imaging Clinics of North America, 22(4), 493–516. https://doi.org/10.1016/j.mric.2014.07.002
Google Scholar
Segal, L. S., & Shrader, M. W. (2013). Missed fractures in paediatric trauma patients. Acta Orthopaedica Belgica, 79(6), 608–615.
Google Scholar
Shin, A. Y., Morin, W. D., Germany, J. D., Jones, S. B., & Lapinsky, A. S. (1996). The Superiority of Magnetic Resonance Imaging in Differentiating the Cause of Hip Pain in Endurance Athletes. The American Journal of Sports Medicine, 24(2), 168–176. https://doi.org/10.1177/036354659602400209
Google Scholar
Shindle, M. K., Foo, L. F., Kelly, B. T., Khanna, A. J., Domb, B. G., Farber, A., Wanich, T., & Potter, H. G. (2006). Magnetic Resonance Imaging of Cartilage in the Athlete: Current Techniques and Spectrum of Disease. The Journal of Bone and Joint Surgery (American), 88(suppl_4), 27-46. https://doi.org/10.2106/JBJS.F.00614
Google Scholar
Silva Jr., J. R., Hayashi, D., Yonenaga, T., Fukuda, K., Genant, H. K., Lin, C., Rahmouni, A., & Guermazi, A. (2013). MRI of bone marrow abnormalities in hematological malignancies. Diagnostic and Interventional Radiology, 19, 393-399. https://doi.org/10.5152/dir.2013.067
Google Scholar
Taylor, R. H., Joskowicz, L., Williamson, B., Guéziec, A., Kalvin, A., Kazanzides, P., Van Vorhis, R., Yao, J., Kumar, R., Bzostek, A., Sahay, A., Börner, M., & Lahmer, A. (1999). Computer-integrated revision total hip replacement surgery: concept and preliminary results. Medical Image Analysis, 3(3), 301–319.
Google Scholar
Wong, K. P. L., Han, A. X., Wong, J. L. Y., & Lee, D. Y. H. (2017). Reliability of magnetic resonance imaging in evaluating meniscal and cartilage injuries in anterior cruciate ligament-deficient knees. Knee Surgery, Sports Traumatology, Arthroscopy, 25(2), 411–417. https://doi.org/10.1007/s00167-016-4211-1
Google Scholar
Zheng, G., Kowal, J., González Ballester, M. A., Caversaccio, M., & Nolte, L.-P. (2007). Registration techniques for computer navigation. Current Orthopaedics, 21(3), 170–179. https://doi.org/10.1016/j.cuor.2007.03.002
Google Scholar
Zheng, G., & Nolte, L. P. (2015). Computer-Assisted Orthopedic Surgery: Current State and Future Perspective. Frontiers in Surgery, 2, 66. https://doi.org/10.3389/fsurg.2015.00066
Google Scholar
Authors
Przemysław KRAKOWSKIOrthopedic Department, Łęczna Hospital, Krasnystawska 52, 21-010 Łęczna Poland
Authors
Robert KARPIŃSKIr.karpinski@pollub.pl
Department of Machine Design and Mechatronics, Faculty of Mechanical Engineering, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin Poland
Authors
Marcin MACIEJEWSKI* Institute of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, Poland
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