Three dimensional study to quantify the relationship between facial hard and soft tissue movement as a result of orthognathic surgery

Introduction Prediction of soft tissue changes following orthognathic surgery has been frequently attempted in the past decades. It has gradually progressed from the classic “cut and paste” of photographs to the computer assisted 2D surgical prediction planning; and finally, comprehensive 3D surgical planning was introduced to help surgeons and patients to decide on the magnitude and direction of surgical movements as well as the type of surgery to be considered for the correction of facial dysmorphology. A wealth of experience was gained and numerous published literature is available which has augmented the knowledge of facial soft tissue behaviour and helped to improve the ability to closely simulate facial changes following orthognathic surgery. This was particularly noticed following the introduction of the three dimensional imaging into the medical research and clinical applications. Several approaches have been considered to mathematically predict soft tissue changes in three dimensions, following orthognathic surgery. The most common are the Finite element model and Mass tensor Model. These were developed into software packages which are currently used in clinical practice. In general, these methods produce an acceptable level of prediction accuracy of soft tissue changes following orthognathic surgery. Studies, however, have shown a limited prediction accuracy at specific regions of the face, in particular the areas around the lips. Aims The aim of this project is to conduct a comprehensive assessment of hard and soft tissue changes following orthognathic surgery and introduce a new method for prediction of facial soft tissue changes.   Methodology The study was carried out on the pre- and post-operative CBCT images of 100 patients who received their orthognathic surgery treatment at Glasgow dental hospital and school, Glasgow, UK. Three groups of patients were included in the analysis; patients who underwent Le Fort I maxillary advancement surgery; bilateral sagittal split mandibular advancement surgery or bimaxillary advancement surgery. A generic facial mesh was used to standardise the information obtained from individual patient’s facial image and Principal component analysis (PCA) was applied to interpolate the correlations between the skeletal surgical displacement and the resultant soft tissue changes. The identified relationship between hard tissue and soft tissue was then applied on a new set of preoperative 3D facial images and the predicted results were compared to the actual surgical changes measured from their post-operative 3D facial images. A set of validation studies was conducted. To include: • Comparison between voxel based registration and surface registration to analyse changes following orthognathic surgery. The results showed there was no statistically significant difference between the two methods. Voxel based registration, however, showed more reliability as it preserved the link between the soft tissue and skeletal structures of the face during the image registration process. Accordingly, voxel based registration was the method of choice for superimposition of the pre- and post-operative images. The result of this study was published in a refereed journal. • Direct DICOM slice landmarking; a novel technique to quantify the direction and magnitude of skeletal surgical movements. This method represents a new approach to quantify maxillary and mandibular surgical displacement in three dimensions. The technique includes measuring the distance of corresponding landmarks digitized directly on DICOM image slices in relation to three dimensional reference planes. The accuracy of the measurements was assessed against a set of “gold standard” measurements extracted from simulated model surgery. The results confirmed the accuracy of the method within 0.34mm. Therefore, the method was applied in this study. The results of this validation were published in a peer refereed journal. • The use of a generic mesh to assess soft tissue changes using stereophotogrammetry. The generic facial mesh played a major role in the soft tissue dense correspondence analysis. The conformed generic mesh represented the geometrical information of the individual’s facial mesh on which it was conformed (elastically deformed). Therefore, the accuracy of generic mesh conformation is essential to guarantee an accurate replica of the individual facial characteristics. The results showed an acceptable overall mean error of the conformation of generic mesh 1 mm. The results of this study were accepted for publication in peer refereed scientific journal. Skeletal tissue analysis was performed using the validated “Direct DICOM slices landmarking method” while soft tissue analysis was performed using Dense correspondence analysis. The analysis of soft tissue was novel and produced a comprehensive description of facial changes in response to orthognathic surgery. The results were accepted for publication in a refereed scientific Journal. The main soft tissue changes associated with Le Fort I were advancement at the midface region combined with widening of the paranasal, upper lip and nostrils. Minor changes were noticed at the tip of the nose and oral commissures. The main soft tissue changes associated with mandibular advancement surgery were advancement and downward displacement of the chin and lower lip regions, limited widening of the lower lip and slight reversion of the lower lip vermilion combined with minimal backward displacement of the upper lip were recorded. Minimal changes were observed on the oral commissures. The main soft tissue changes associated with bimaxillary advancement surgery were generalized advancement of the middle and lower thirds of the face combined with widening of the paranasal, upper lip and nostrils regions. In Le Fort I cases, the correlation between the changes of the facial soft tissue and the skeletal surgical movements was assessed using PCA. A statistical method known as ’Leave one out cross validation’ was applied on the 30 cases which had Le Fort I osteotomy surgical procedure to effectively utilize the data for the prediction algorithm. The prediction accuracy of soft tissue changes showed a mean error ranging between (0.0006mm±0.582) at the nose region to (-0.0316mm±2.1996) at the various facial regions.

Quantification of variable palmar ligaments around the triquetrum-hamate joint determined by lunate type

The ligaments of the wrist are highly variable and poorly described, which is more obvious on the ulnar side of the wrist. Previous studies highlighted the potential differences within the ligaments of the wrist but no consensus has been reached. Poor tissue description and inconsistent use of terminology hindered the reproducibility of the results. Improved understanding of the morphological variations between carpal bones may facilitate improved understanding of the ligamentous structure within the wrist. This study aims to identify the potential variations between carpal bones that could be used to separate palmar ligamentous patterns around the triquetrum-hamate joint into subgroups within the sample population. Investigations were performed following a detailed nomenclature and a clear definition of ligamentous structures to facilitate detailed description and reproducible results. Quantitative analyses were conducted using 3D modelling technique. Histological sections were then analysed to identify the structure of each ligamentous attachment. Variable patterns of ligamentous attachments were identified. Differences were not only obvious between samples but also between the right and left hands of the same person. These identifications suggested that the palmar ligamentous patterns around the triquetrum-hamate joint are best described as a spectrum with a higher affinity of the triquetrum-hamate-capitate ligament and the lunate-triquetrum ligament to be associated with type I lunate wrists on one extreme and type II lunate wrists with the palmar triquetrum-hamate ligament, triquetrum-hamate-capitate ligament and palmar radius-lunate-triquetrum ligament attachments at the other extreme. Histological analyses confirmed pervious established work regarding the mechanical role of ligaments in wrist joint biomechanics. Also, there were no significant differences between the quantitative data obtained from the Genelyn-embalmed and unembalmed specimens (p>0.05). The current study demonstrated variable ligamentous patterns that suggest different bone restraints and two different patterns of motion. These findings support previous suggestions regarding separating the midcarpal joint into two distinct functional types. Type I wrists were identified with ligamentous attachments that are suggestive of rotating/translating hamate whilst type II wrists identified with ligamentous attachments that are suggestive of flexing/extending hamate motion based upon the patterns of the ligamentous attachments in relation to the morphological features of the underlying lunate type of the wrist. This opens the horizon for particular consideration and/or modification of surgical procedures, which may enhance the clinical management of wrist dysfunction.