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Computer-assisted maxillofacial reconstruction


Introduction

A comprehensive maxillofacial computer-assisted surgical workflow can be divided into three areas: 1) presurgical planning, 2) surgical execution, and 3) anatomic verification. Historically, presurgical planning has been a function of the surgeon’s spatial cognition abilities, surgical execution was heavily dependent on surgeon experience, and intraoperative verification tools to confirm the surgical reconstruction were nonexistent. Advances in computer-assisted surgery (CAS) have resulted in a paradigm shift in each of these areas. A PubMed literature search starting in 1982 reveals fewer than 10 CAS publications per year, with an exponential growth curve starting in 2006 ( Fig. 4.1 ). Since 2017 there has been an average of 131 publications per year looking at CAS applications. Computer-assisted planning software uses computed tomography (CT) or magnetic resonance imaging (MRI) data to generate representative three-dimensional (3D) objects that can be used for presurgical planning. , Virtual environments (augmented, virtual, and mixed reality) can be used to better visualize, understand, and communicate a computer-assisted surgical plan. Additive manufacturing is commonly used to fabricate surgical models, guides and implants, which can guide an accurate surgical repair even with limited visualization. Finally, intraoperative navigation and intraoperative imaging can be used to confirm the accuracy of the repair prior to leaving the operating room. , The authors will describe their current CAS workflow for maxillofacial reconstruction ( Fig. 4.2 ).

Fig. 4.1, Publications found in PubMed search from query for “Computer-aided surgery”, available by year from 1982 to 2021 with an exponential growth curve starting in 2006.

Fig. 4.2, CAS workflow divided into three phases: virtual planning, surgical execution, and anatomic verification. Each phase of the workflow can incorporate multiple technologies. CAS, Computer-assisted surgery

Presurgical planning

Computer-assisted surgical planning can be an extremely valuable tool for both young and experienced surgeons. It allows the surgeon to plan a surgical procedure, in a virtual environment, prior to surgical execution. Computer-assisted planning software imports digital imaging and communications in medicine (DICOM) data (from CT and MRI scanners). The software can be proprietary or open source. Proprietary software applications are highly varied; some offer broad bone and soft tissue planning capabilities, while others are limited to one anatomic region (e.g., facial skeleton) or procedure type (e.g., dental implants). The cost of proprietary software is highly variable, but most vendors use a subscription model necessitating an ongoing funding stream. Open source software can be downloaded for free. These applications are often less refined, rarely automated, less stable, have no technical support, and lack US Food and Drug Administration (FDA) approval. Consequently, open-source, computer-assisted planning software packages are more commonly used for research applications as opposed to clinical applications.

Computer-assisted planning software functionality

Common computer-assisted planning software functions include segmentation, analysis, mirroring, and image fusion.

  • Segmentation: Segmentation procedures are used to separate virtual objects. Some examples might include separating the skin envelope from the facial skeleton ( Fig. 4.3 ), or the right and left halves of the skull ( Fig. 4.4 ). “Manual segmentation” requires selection of individual CT slices, which are then added to generate a volume. This is extremely time consuming and clinically impractical. Therefore, software manufacturers have developed “auto-segmentation” atlases that rapidly segment selected anatomy to facilitate presurgical planning in a timely fashion.

    Fig. 4.3, Bone and soft tissue segmentation.

    Fig. 4.4, Segmentation of the left and right side of the facial skeleton.

  • Analysis: Once segmentation is complete, properties of individual objects can be assessed. For example, preinjury orbital volumes ( Fig. 4.5 ) and measurement of anatomic distances ( Fig. 4.6 ).

    Fig. 4.5, Orbital volume assessment using computer-assisted surgical planning.

    Fig. 4.6, Illustration of virtual anatomic distance measurements being used to evaluate zygoma fracture displacement.

  • Mirroring: Unilateral asymmetries lend themselves to segmentation and mirroring of normal anatomy to replace injured anatomy ( Fig. 4.7 ).

    Fig. 4.7, Example of mirroring process in computer-assisted surgical planning. The patient has a unilateral zygomaticomaxillary fracture (A). The normal side is segmented (B), mirrored to the contralateral side (C), and fused to generate a surgical plan (D).

  • Object fusion: Object fusion is useful (particularly after mirroring) to generate a final surgical plan ( Fig. 4.7 ).

  • Data set fusion: Fusion of two data sets (CT, MRI, or one of each) can assist with presurgical, intraoperative, and postoperative analysis ( Fig. 4.8 ).

    Fig. 4.8, Data fusion of presurgical plan (green) superimposed on intraoperative CT scan to evaluate the accuracy of the orbital floor implant position relative to the presurgical plan.

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