Hylke van der Wel’s research while affiliated with University of Groningen and other places

Background Asymmetric joint load is the main cause of development of ankle osteoarthritis (OA). Realignment surgery aims to transfer ankle joint load from the degenerative area toward the uninvolved area. Determination of the optimal shift is still challenging. When the degenerative area is correlated to the ankle joint mechanical axis establishing an optimal target angle for corrective surgery may become more feasible. The primary aim of our study was to investigate if the area of ankle joint activation on single-photon emission computed tomography and conventional computed tomography (SPECT/CT) imaging correlates with the mechanical ankle joint axis point (MAJAP). Methods In this cross-sectional study, patients 18 years or older with symptomatic asymmetric ankle OA and a hip-to-calcaneus long leg view with SPECT/CT of the affected ankle were eligible for inclusion. Primary outcome was MAJAP divided into 3 alignment categories (medial shift, neutral, lateral shift). SPECT/CT activation was determined in 8 different areas of the ankle joint. A Spearman rho correlation coefficient was calculated to investigate the relationship between the alignment categories and SPECT/CT activation in the 8 areas. Results Forty-nine patients (mean age 58.8 [SD 10.0] years) with 52 ankles with moderate to severe asymmetric OA were included. A significantly (Spearman rho −0.379 [ P = .006] and Spearman rho −0.279 [ P = .045]) higher proportion of ankles with radioisotope uptake in the anteromedial ankle joint areas (zones 1 and 5) was seen in the medial shift category. A significantly (Spearman rho .312 ( P = .025)) higher proportion of ankles with radioisotope uptake in the anterolateral ankle joint area (zone 8) was seen in the lateral shift category. Conclusion We found in this patient group that the area of SPECT/CT uptake in asymmetric ankle OA was associated to MAJAP measured on hip-to-calcaneus weightbearing views, although the strength of the correlation is weak to moderate. Consequently, nonweightbearing metabolic SPECT/CT radiotracer uptake has the potential to help determine the area to unload in ankle joint-preserving alignment surgery.

The face is the initial feature used to judge gender in public spaces; it is also a source of significant gender dysphoria. Surgical techniques are available for non-cisgender male patients who desire a more masculine face by augmenting certain features to change the bony framework of the skull. Augmentation using virtually designed patient-specific polyetheretherketone implants has now become a more widely applied method in maxillofacial surgery. When designing implants for augmentation, a three-dimensional (3D) reference or template is very useful. Hence, a 3D statistical shape model was developed of a male skull shape from information from a population of 40 male patients containing the mean shape and principal components of shape variation. By overlaying the template and the patient’s 3D skull model, this method identified the regions of gender dimorphism in this case to be the orbital ridge, zygomatic regions, and frontal bossing area. Based on the 3D template overlay, polyetheretherketone augmentation implants were virtually designed in close consultation with a patient to augment the aforementioned regions. The virtual statistical shape modeling template offered an objective reference, and the possibility to fully involve the patient in the treatment planning.

Knowledge about anatomical shape variations in the pelvis is mandatory for selection, fitting, positioning, and fixation in pelvic surgery. The current knowledge on pelvic shape variation mostly relies on point-to-point measurements on 2D X-ray images and computed tomography (CT) slices. Three-dimensional region-specific assessments of pelvic morphology are scarce. Our aim was to develop a statistical shape model of the hemipelvis to assess anatomical shape variations in the hemipelvis. CT scans of 200 patients (100 male and 100 female) were used to obtain segmentations. An iterative closest point algorithm was performed to register these 3D segmentations, so a principal component analysis (PCA) could be performed, and a statistical shape model (SSM) of the hemipelvis was developed. The first 15 principal components (PCs) described 90% of the total shape variation, and the reconstruction ability of this SSM resulted in a root mean square error of 1.58 (95% CI: 1.53–1.63) mm. In summary, an SSM of the hemipelvis was developed, which describes the shape variations in a Caucasian population and is able to reconstruct an aberrant hemipelvis. Principal component analyses demonstrated that, in a general population, anatomical shape variations were mostly related to differences in the size of the pelvis (e.g., PC1 describes 68% of the total shape variation, which is attributed to size). Differences between the male and female pelvis were most pronounced in the iliac wing and pubic rami regions. These regions are often subject to injuries. Future clinical applications of our newly developed SSM may be relevant for SSM-based semi-automatic virtual reconstruction of a fractured hemipelvis as part of preoperative planning. Lastly, for companies, using our SSM might be interesting in order to assess which sizes of pelvic implants should be produced to provide proper-fitting implants for most of the population.

The aim of this study was to investigate the value of 3D Statistical Shape Modelling for orthognathic surgery planning. The goal was to objectify shape variations in the orthognathic population and differences between male and female patients by means of a statistical shape modelling method. Pre-operative CBCT scans of patients for whom 3D Virtual Surgical Plans (3D VSP) were developed at the University Medical Center Groningen between 2019 and 2020 were included. Automatic segmentation algorithms were used to create 3D models of the mandibles, and the statistical shape model was built through principal component analysis. Unpaired t-tests were performed to compare the principal components of the male and female models. A total of 194 patients (130 females and 64 males) were included. The mandibular shape could be visually described by the first five principal components: (1) The height of the mandibular ramus and condyles, (2) the variation in the gonial angle of the mandible, (3) the width of the ramus and the anterior/posterior projection of the chin, (4) the lateral projection of the mandible’s angle, and (5) the lateral slope of the ramus and the inter-condylar distance. The statistical test showed significant differences between male and female mandibular shapes in 10 principal components. This study demonstrates the feasibility of using statistical shape modelling to inform physicians about mandible shape variations and relevant differences between male and female mandibles. The information obtained from this study could be used to quantify masculine and feminine mandibular shape aspects and to improve surgical planning for mandibular shape manipulations.

The purpose of this study was to assess the 1-year skeletal stability of the osteotomized maxilla after Le Fort I surgery, comparing conventional osteosynthesis with patient-specific osteosynthesis. Patients were assigned to a conventional or patient-specific osteosynthesis group using prospective randomization. The primary outcome was the three-dimensional change in postoperative skeletal position of the maxilla between the 2-week and 1-year follow-up cone beam computed tomography scans. Fifty-eight patients completed the protocol for the 2-week postoperative analysis, and 27 patients completed the 1-year follow-up study protocol. Of the 27 patients completing the entire protocol, 13 were in the conventional group and 14 in the patient-specific osteosynthesis group. The three-dimensional translation analysis showed that the use of the patient-specific osteosynthesis resulted in a skeletally stable result, comparable to that of conventional miniplate fixation. For both the patient-specific osteosynthesis and conventional miniplate fixation groups, median translations of less than 1 mm and median rotations of less than 1° were observed, indicating that both methods of fixation resulted in a stable result for the 27 patients examined. For the Le Fort I osteotomy, the choice between patient-specific osteosynthesis and conventional osteosynthesis did not affect the postoperative skeletal stability after 1 year of follow-up.

Background Success of valgus-type supramalleolar osteotomy (SMOT) depends on adequate correction of malalignment, which can be hard to achieve with current 2-dimensional (2D) planning and operative techniques. A personalized digital 3-dimensional (3D) workflow to virtually plan and perform a 2-step 3D-guided medial opening (MO) SMOT has the potential to improve precision of correction. Methods Computed tomography (CT)–based Proplan medical 3D models were made to virtually plan the desired MO SMOT, and exported to 3-Matic medical to develop patient-specific 2-step cutting and wedge guides. Workflow accuracy was tested in this limited clinical pilot study (3 patients) by comparing the virtual planned position of the osteotomized distal tibial fragment with the 1-year post-MO SMOT configuration. Two millimeters or less translation deviation in every plane was defined as accurate. Results Primary outcome analysis of the osteotomized distal tibial fragment deviation showed a median translation in all planes of 0.7 (range 0-8.2) mm (interquartile range 1.55) with an excellent interrater reliability of the measurements (intraclass correlation coefficient 0.998). There was a strong reduction in ankle pain as reflected by an increase of the AOFAS-AH score and decrease of NRS pain score with an unrestricted hindfoot motion 1 year after surgery. Conclusion 3D virtually planned bone cutting and wedge guides is a promising approach associated with minimal postoperative deviation from the desired correction in medial opening supramalleolar osteotomy.

Medical imaging techniques, such as (cone beam) computed tomography and magnetic resonance imaging, have proven to be a valuable component for oral and maxillofacial surgery (OMFS). Accurate segmentation of the mandible from head and neck (H&N) scans is an important step in order to build a personalized 3D digital mandible model for 3D printing and treatment planning of OMFS. Segmented mandible structures are used to effectively visualize the mandible volumes and to evaluate particular mandible properties quantitatively. However, mandible segmentation is always challenging for both clinicians and researchers, due to complex structures and higher attenuation materials, such as teeth (filling) or metal implants that easily lead to high noise and strong artifacts during scanning. Moreover, the size and shape of the mandible vary to a large extent between individuals. Therefore, mandible segmentation is a tedious and time-consuming task and requires adequate training to be performed properly. With the advancement of computer vision approaches, researchers have developed several algorithms to automatically segment the mandible during the last two decades. The objective of this review was to present the available fully (semi)automatic segmentation methods of the mandible published in different scientific articles. This review provides a vivid description of the scientific advancements to clinicians and researchers in this field to help develop novel automatic methods for clinical applications.

Accurate segmentation of the mandible from cone-beam computed tomography (CBCT) scans is an important step for building a personalized 3D digital mandible model for maxillofacial surgery and orthodontic treatment planning because of the low radiation dose and short scanning duration. CBCT images, however, exhibit lower contrast and higher levels of noise and artifacts due to extremely low radiation in comparison with the conventional computed tomography (CT), which makes automatic mandible segmentation from CBCT data challenging. In this work, we propose a novel coarse-to-fine segmentation framework based on 3D convolutional neural network and recurrent SegUnet for mandible segmentation in CBCT scans. Specifically, the mandible segmentation is decomposed into two stages: localization of the mandible-like region by rough segmentation and further accurate segmentation of the mandible details. The method was evaluated using a dental CBCT dataset. In addition, we evaluated the proposed method and compared it with state-of-the-art methods in two CT datasets. The experiments indicate that the proposed algorithm can provide more accurate and robust segmentation results for different imaging techniques in comparison with the state-of-the-art models with respect to these three datasets.

Accurate mandible segmentation is significant in the field of maxillofacial surgery to guide clinical diagnosis and treatment and develop appropriate surgical plans. In particular, cone-beam computed tomography (CBCT) images with metal parts, such as those used in oral and maxillofacial surgery (OMFS), often have susceptibilities when metal artifacts are present such as weak and blurred boundaries caused by a high-attenuation material and a low radiation dose in image acquisition. To overcome this problem, this paper proposes a novel deep learning-based approach (SASeg) for automated mandible segmentation that perceives overall mandible anatomical knowledge. SASeg utilizes a prior shape feature extractor (PSFE) module based on a mean mandible shape, and recurrent connections maintain the continuity structure of the mandible. The effectiveness of the proposed network is substantiated on a dental CBCT dataset from orthodontic treatment containing 59 patients. The experiments show that the proposed SASeg can be easily used to improve the prediction accuracy in a dental CBCT dataset corrupted by metal artifacts. In addition, the experimental results on the PDDCA dataset demonstrate that, compared with the state-of-the-art mandible segmentation models, our proposed SASeg can achieve better segmentation performance.