April 2017 Nugget

Page 12


Patient Specific

Modeling and Clinical Applications By David C. Hatcher, DDS , MSc, MRCDŠ One of the goals of digital technology, SDDS Member besides improved diagnostics, has been to create and interact with the virtual dynamic Dr. Hatcher received his D.D.S. degree from patient-specific model that can be used for the University of Washington. Subsequently a variety of therapeutic endeavors. This he completed two years active duty in the U.S. anticipated process begins with imaging the Public Health Service and a one year general practice residency program at the University of Vermont Medical Center. Dr. Hatcher entered the graduate program in radiology at the Uni- The last several years have versity of Toronto and was granted a specialty witnessed widespread degree in Oral and Maxillofacial Radiology in digitization of life. 1982 and a M.Sc. in 1983. His thesis topic dealt with radiology of tempormandibular disorders. Presently Dr. Hatcher is in private practice in Sacramento, California and has faculty appointments as Clinical Professor at the Uni- patient with the appropriate devices required versity of California San Francisco, University to meet the diagnostic challenge and then of California Los Angeles, University of Califor- producing a patient specific model that can nia Davis, University of the Pacific and Rose- be segmented into anatomic structures. man University of Health Sciences. Using a multi-object viewer the clinician can interact with the segmented model. In addition to diagnostics, the model can be used to simulate treatment options and aid in the design of custom therapeutic devices or navigation to fulfill the treatment objectives. This process has applications in nearly all disciplines of dentistry including orthodontics, implantology, endodontics, oral and maxillofacial surgery and prosthodontics.

By Shikha Rathi, BDS, MS SDDS Member

Dr. Rathi is a Board Certified Oral and Maxillofacial Radiologist practicing in Roseville. She is an adjunct associate professor in the department of Orthodontics at UOP.

In oral and maxillofacial surgery, virtual patient modeling has a profound impact on the diagnosis and management of patients with traumatic facial injuries, craniofacial deformities and growth disorders (see Dr. Jackson’s article). As an example, fractures and fractured segments can be identified on the 3D scan of an acutely injured patient and the fractured segments can then be modeled as objects. When the fractures are

12 | The Nugget • Sacramento District Dental Society

unilateral, the normal side can be mirrored over the involved side to serve as a guide for virtual placement of the fractured segment. The computer software monitors final virtual position of the fractured segments and can ultimately provide 3D coordinates to guide or navigate the segments into place at time of surgery. Surgical access for navigation type surgery may be more conservative than the traditional open access surgery. Patients with craniofacial deformities that are congenital, developmental, or acquired from traumatic, iatrogenic, or post-surgical resection origins also can greatly benefit from the modeling process. Consider the case of removing or preserving a condyle/ coronoid complex during a hemi-mandibular resection: The biomechanical consequences of a total or partial resection of a hemi-mandible can be tested using a patient specific virtual model. The results of such a simulation would demonstrate the proportional degradation in mandibular function corresponding with loss of the muscle attachment framework.1,2 Anatomy supplied by multiple imaging modalities can be combined into a common 3-D matrix and manipulated using optimized software platforms to create interactive multidimensional patient specific anatomic models (Figures 1A & 1B). For example, disparate maging devices could independently produce surface and subsurface images of the TMJ, muscles, teeth, oral cavity, skin, airway, and skeleton that can be combined (fused or registered) onto a common coordinate system for downstream visualization and analysis. Fusion of multiple image sets into a single file results in a patient specific model, with each of the anatomic areas of interest having the desired anatomic accuracy. Such models