Learning-Based Approach for Personalized Craniomaxillofacial Surgical Planning

NIH RePORTER · NIH · R01 · $574,725 · view on reporter.nih.gov ↗

Abstract

Abstract: Our main clinical objective for this project is to provide personalized precision care to patients with craniomaxillofacial (CMF) deformities by significantly improving the surgical planning method. CMF deformities involve congenital and acquired deformities of the jaws and face. A large number of patients in the US and around the world suffer from CMF deformities. The basic principles of CMF surgery involve the restoration of deformed CMF structures back to normal anatomy and functions with osteotomy, autologous, bone grafts, or vascularized free flaps. The success of CMF surgery depends on not only the technical aspects of the operation, but also, to a large extent, the precise formulation of a surgical plan. However, CMF surgical planning is extremely challenging due to the complex nature of CMF anatomy and deformity. During a routine CMF surgical planning, a surgeon first acquires a three-dimensional (3D) model of the patient's skull. He then performs 3D cephalometric analysis to quantify the deformity. Finally, the surgery is simulated by virtually cutting the 3D model into multiple bony segments. The surgeon then tries his best to move and rotate each segment individually to a desired position within the normal range of cephalometric values (the current standard of care). This is problematic as “normal” cephalometric values are the averageness of normal population, in which each value has a mean and a standard deviation. Due to the variation within the normal values, the surgeon must often guess what the exact value the patient's cephalometric measurement should be corrected to. In addition, cephalometry is a group of only linear and angular measurements, which certainly cannot represent the complex nature of human CMF structures. Therefore, surgical outcomes are often subjective and heavily dependent on the surgeons' experience and artistic talent. Because each human face is different, the average “normal values” cannot represent the complex morphology of each individual face. To this end, we hypothesize that if a surgeon can foresee what the normal CMF shape of the patient should be, the surgical plan will be objective and personalized. Therefore, in this project, we propose developing and validating a new surgical planning method of using patient-specific and anatomically-correct reference models. The feasibility of our approach has already been proven by our preliminary studies. The results of this project will significantly improve the quality of patient care by developing personalized and precise surgical plans for CMF surgery objectively. The results will be especially beneficial to patients with jaw deformities, syndromic and non-syndromic craniofacial deformities, trauma, and CMF cancer. In the future, our approach can also be used to design and print 3D patient-specific resorbable bone implants with tissue engineering capability for bone regeneration.

Key facts

NIH application ID
9950849
Project number
5R01DE027251-04
Recipient
METHODIST HOSPITAL RESEARCH INSTITUTE
Principal Investigator
James J Xia
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$574,725
Award type
5
Project period
2017-07-01 → 2022-06-30