Methods for three-dimensional characterization of the acetabulum prior to pelvic reorientation osteotomy: a scoping review.

Periacetabular osteotomy is the gold standard treatment for acetabular dysplasia. The great variability of acetabular dysplasia requires a personalized preoperative planning improved by 3D reconstruction and computer-assisted surgery. To plan the displacement of the acetabular fragment by a pelvic osteotomy, it is necessary to define a reference plane and a method to characterize 3D acetabular orientation. A scoping review was performed on PubMed to search for articles with a method to characterize the acetabulum of native hips in a 3D reference frame. Ninety-eight articles out of 3815 reports were included. Three reproducible reference planes were identified: the anterior pelvic plane, the Standardization and Terminology Committee plane used in gait analysis, and the sacral base plane. The different methods for 3D analysis of the acetabulum were divided in four groups: global orientation, triplanar measurements, segmentation, and surface coverage of the femoral head. Two methods were found appropriate for reorientation osteotomies: the global orientation by a vector method and the triplanar method. The global orientation method relies on the creation of a vector from the acetabular rim, from the acetabular surface or from successive planes. Normalization of the global acetabular vector would correct acetabular dysplasia by a single alignment maneuver on an ideal vector. The triplanar method, based on angle measurements at the center of the femoral head, would involve correction of anomalies by considering axial, frontal, and sagittal planes. Although not directly fit for reorientation, the two others would help to candidate patients and verify both planning and postoperative result.

DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation.

OBJECTIVES: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evaluate a novel open source tool called DentalSegmentator for fully automatic segmentation of five anatomical structures on DMF CT and CBCT scans: maxilla/upper skull, mandible, upper teeth, lower teeth, and the mandibular canal. METHODS: A retrospective sample of 470 CT and CBCT scans was used as a training/validation set. The performance and generalizability of the tool was evaluated by comparing segmentations provided by experts and automatic segmentations in two hold-out test datasets: an internal dataset of 133 CT and CBCT scans acquired before orthognathic surgery and an external dataset of 123 CBCT scans randomly sampled from routine examinations in 5 institutions. RESULTS: The mean overall results in the internal test dataset (n = 133) were a Dice similarity coefficient (DSC) of 92.2 ± 6.3 % and a normalised surface distance (NSD) of 98.2 ± 2.2 %. The mean overall results on the external test dataset (n = 123) were a DSC of 94.2 ± 7.4 % and a NSD of 98.4 ± 3.6 %. CONCLUSIONS: The results obtained from this highly diverse dataset demonstrate that this tool can provide fully automatic and robust multiclass segmentation for DMF CT and CBCT scans. To encourage the clinical deployment of DentalSegmentator, the pre-trained nnU-Net model has been made publicly available along with an extension for the 3D Slicer software. CLINICAL SIGNIFICANCE: DentalSegmentator open source 3D Slicer extension provides a free, robust, and easy-to-use approach to obtaining patient-specific three-dimensional models from CT and CBCT scans. These models serve various purposes in a digital dentistry workflow, such as visualization, treatment planning, intervention, and follow-up.

Spinal axial torque assessment after surgical correction in adolescent idiopathic scoliosis: a new approach to 3D barycentremetry and mass distribution based on biplanar radiographs.

PURPOSE: Barycentremetry in adolescent idiopathic scoliosis (AIS) allows the distribution of masses and their loading of the spine to be studied. In particular, the axial torque on the spine has been studied in AIS, but not after surgical correction. Spinal axial torque was studied in AIS before and after surgery. METHODS: All AIS (Lenke 1 and 3) who underwent posterior spinal fusion surgery at our center in 2019 were included retrospectively. AIS underwent frontal and sagittal biplanar radiographs in the free-standing position before surgery, 4 months after surgery, and at the last follow-up. Their spine and external envelope were reconstructed with validated methods. Spinal axial torque at the apex and the upper and lower end vertebra was calculated. Finally, the preoperative and postoperative values were compared to a previously published reference corridor for asymptomatic subjects. RESULTS: Twenty-nine patients were included (54 ± 11° Cobb angle, 15 ± 2 years old at surgery). The surgical procedure decreased the Cobb angle by 36° ± 11° and decreased the spinal axial torque at the upper end vertebra by 2.5 N/m (95% CI = [1.9; 3]; p < 0.001), at the apex by 0.6 N/m (95% CI = [0.4; 1]; p = 0.004), at the lower end vertebra by 2 N/m (95% CI = [1.5; 2.8]; p < 0.001). Compared to 95th percentile of torque, which was previously evaluated in asymptomatic subjects, more than 90% of patients had higher values at the upper and lower end vertebrae before surgery. Postoperatively, 62% of patients still had higher torque at the upper end vertebra than asymptomatic subjects, while only 38% patients showed abnormal values at the lower junction. CONCLUSION: Results of this study confirm that AIS patients show abnormally high spinal axial torque, especially at the end vertebrae, and that this parameter is normalized postoperatively for only a small number of patients.

An analysis on the determinants of head to pelvic balance in a Chinese adult population.

Background: Balanced global spinopelvic balance is important in the maintenance of the physiological alignment of all body segments above the pelvis with minimum energy expenditure. The key determinants affecting the 3D index-odontoid-hip axis (OD-HA) angle, and in particular its alterations, have not been clearly defined. The aim of this study is to identify the determinants of the 3D OD-HA angle in maintaining global spinopelvic balance in a large Chinese adult cohort of different gender and age groups. Methods: A total of 516 asymptomatic adults were enrolled in this study. Biplanar radiographies were performed to reconstruct the subject's inter-acetabular axis and C2 odontoid process. The 3D angle formed by the vertical and the line between odontoid and mid-interacetabular axis (OD-HA angle) was computed and projected in the subject's sagittal and coronal planes. Thoracic kyphosis (TK), lumbar lordosis (LL), T1 pelvic angle (TPA) and sagittal vertical axis (SVA) were measured. Results: The mean values of sagittal and coronal OD-HA were -0.2°±2.5° and 0.2°±1.1°, respectively. Both sagittal and coronal OD-HA had significant correlation with age (r=0.265 and r=-0.143, P<0.01, respectively), sagittal OD-HA showed increment from 20s to 80s (-1.3° to 0.8° for female, -0.3° to 1.5° for male) and a significant difference between male and female from 20 to 69 years old. Further analysis showed that sex, weight, TK, PT, SVA, TPA and ODI were determinants of OD-HA. Conclusions: 3D OD-HA angle showed physiological stability with little variability from young to elderly adults, with SD of 2.45° and 1.06° in sagittal and coronal planes, respectively. OD-HA angle confirms the hypothesis that the head tends to remain above the pelvis in a small cone of stability. This study provides an analysis of the determinants of OD-HA and the reference range of the head-pelvis balance in each decade and gender based on a large-scale asymptomatic population.

Fully automatic segmentation of craniomaxillofacial CT scans for computer-assisted orthognathic surgery planning using the nnU-Net framework.

OBJECTIVES: To evaluate the performance of the nnU-Net open-source deep learning framework for automatic multi-task segmentation of craniomaxillofacial (CMF) structures in CT scans obtained for computer-assisted orthognathic surgery. METHODS: Four hundred and fifty-three consecutive patients having undergone high-resolution CT scans before orthognathic surgery were randomly distributed among a training/validation cohort (n = 300) and a testing cohort (n = 153). The ground truth segmentations were generated by 2 operators following an industry-certified procedure for use in computer-assisted surgical planning and personalized implant manufacturing. Model performance was assessed by comparing model predictions with ground truth segmentations. Examination of 45 CT scans by an industry expert provided additional evaluation. The model's generalizability was tested on a publicly available dataset of 10 CT scans with ground truth segmentation of the mandible. RESULTS: In the test cohort, mean volumetric Dice similarity coefficient (vDSC) and surface Dice similarity coefficient at 1 mm (sDSC) were 0.96 and 0.97 for the upper skull, 0.94 and 0.98 for the mandible, 0.95 and 0.99 for the upper teeth, 0.94 and 0.99 for the lower teeth, and 0.82 and 0.98 for the mandibular canal. Industry expert segmentation approval rates were 93% for the mandible, 89% for the mandibular canal, 82% for the upper skull, 69% for the upper teeth, and 58% for the lower teeth. CONCLUSION: While additional efforts are required for the segmentation of dental apices, our results demonstrated the model's reliability in terms of fully automatic segmentation of preoperative orthognathic CT scans. KEY POINTS: • The nnU-Net deep learning framework can be trained out-of-the-box to provide robust fully automatic multi-task segmentation of CT scans performed for computer-assisted orthognathic surgery planning. • The clinical viability of the trained nnU-Net model is shown on a challenging test dataset of 153 CT scans randomly selected from clinical practice, showing metallic artifacts and diverse anatomical deformities. • Commonly used biomedical segmentation evaluation metrics (volumetric and surface Dice similarity coefficient) do not always match industry expert evaluation in the case of more demanding clinical applications.

Three-Dimensional Cephalometric Landmarking and Frankfort Horizontal Plane Construction: Reproducibility of Conventional and Novel Landmarks.

In some dentofacial deformity patients, especially patients undergoing surgical orthodontic treatments, Computed Tomography (CT) scans are useful to assess complex asymmetry or to plan orthognathic surgery. This assessment would be made easier for orthodontists and surgeons with a three-dimensional (3D) cephalometric analysis, which would require the localization of landmarks and the construction of reference planes. The objectives of this study were to assess manual landmarking repeatability and reproducibility (R&R) of a set of 3D landmarks and to evaluate R&R of vertical cephalometric measurements using two Frankfort Horizontal (FH) planes as references for horizontal 3D imaging reorientation. Thirty-three landmarks, divided into "conventional", "foraminal" and "dental", were manually located twice by three experienced operators on 20 randomly-selected CT scans of orthognathic surgery patients. R&R confidence intervals (CI) of each landmark in the -x, -y and -z directions were computed according to the ISO 5725 standard. These landmarks were then used to construct 2 FH planes: a conventional FH plane (orbitale left, porion right and left) and a newly proposed FH plane (midinternal acoustic foramen, orbitale right and left). R&R of vertical cephalometric measurements were computed using these 2 FH planes as horizontal references for CT reorientation. Landmarks showing a 95% CI of repeatability and/or reproducibility > 2 mm were found exclusively in the "conventional" landmarks group. Vertical measurements showed excellent R&R (95% CI < 1 mm) with either FH plane as horizontal reference. However, the 2 FH planes were not found to be parallel (absolute angular difference of 2.41°, SD 1.27°). Overall, "dental" and "foraminal" landmarks were more reliable than the "conventional" landmarks. Despite the poor reliability of the landmarks orbitale and porion, the construction of the conventional FH plane provided a reliable horizontal reference for 3D craniofacial CT scan reorientation.

Comparison of 3D and 2D characterization of spinal geometry from biplanar X-rays: a large cohort study.

BACKGROUND: Biplanar X-ray system providing anteroposterior and sagittal plane with an ultra-low radiation dose and in weight-bearing position is increasingly used for spine imaging. The original three-dimensional (3D) reconstruction method from biplanar X-rays has been widely used for clinical parameters, however, the main issue is that manual adjustments of the 3D model was quite time-consuming and limited to thoracolumbar spine. A quasi-automated 3D reconstruction method of the spine from cervical vertebra to pelvis was proposed, which proved fast and accurate in 57 patients with adolescent idiopathic scoliosis. The aim of this study was to compare the newly developed technique of quasi-automatic 3D measurement with classical 2D measurements in a large cohort. METHODS: A total of 494 adults with biplanar EOS X-ray scanning were included in this study and divided into health and deformity group according to the presence of spinal deformity. The proposed method of quasi-automatic 3D measurement was applied to all these subjects. The radiographic parameters included: thoracic kyphosis (TK), lumbar lordosis (LL), pelvic incidence (PI), pelvic tilt (PT), sagittal vertical axis (SVA), T1 pelvic angle (TPA) in sagittal plane, and cobb angle in coronal plane. Comparison was made between quasi-automatic and manual measurement. RESULTS: The mean age was 53.7±19.9 years old. In the whole population, the mean differences between the two methods were 3.9° for TK (30.5°±9.9° vs. 26.5°±9.3°, P<0.001), -5.2° for LL (-47.5°±11.2° vs. -42.4°±11.0°, P<0.001), 3.6° for PI (46.9°±10.3° vs. 43.9°±10.3°, P<0.001), -0.2° for PT (11.9°±7.7° vs. 12.0°±8.2°, P=0.328), -2.1 mm for SVA (15.7±26.2 vs. 17.8±26.3 mm, P=0.221) and -1.1° for TPA (9.0°±7.6° vs. 10.1°±7.8°, P=0.051). The deformity group had similar mean differences with the asymptomatic group with the values ranged from -4.1° to 3.8° for sagittal parameters. The mean differences of Cobb angle were 1.9° for patients with Cobb angle <30° and 2.3° for patients with Cobb angle >30°, respectively. Correlation analysis showed r2 for all clinical parameters ranged from 0.667 to 0.923. On average, the new method takes 5 minutes to compute all the parameters for one case. CONCLUSIONS: In conclusion, this ergonomic and efficient quasi-automatic method for full spine proved fast and accurate measurement in a large population, which showed great potential in extensive clinical application.

A convolutional neural network to detect scoliosis treatment in radiographs.

PURPOSE: The aim of this work is to propose a classification algorithm to automatically detect treatment for scoliosis (brace, implant or no treatment) in postero-anterior radiographs. Such automatic labelling of radiographs could represent a step towards global automatic radiological analysis. METHODS: Seven hundred and ninety-six frontal radiographies of adolescents were collected (84 patients wearing a brace, 325 with a spinal implant and 387 reference images with no treatment). The dataset was augmented to a total of 2096 images. A classification model was built, composed by a forward convolutional neural network (CNN) followed by a discriminant analysis; the output was a probability for a given image to contain a brace, a spinal implant or none. The model was validated with a stratified tenfold cross-validation procedure. Performance was estimated by calculating the average accuracy. RESULTS: 98.3% of the radiographs were correctly classified as either reference, brace or implant, excluding 2.0% unclassified images. 99.7% of brace radiographs were correctly detected, while most of the errors occurred in the reference group (i.e. 2.1% of reference images were wrongly classified). CONCLUSION: The proposed classification model, the originality of which is the coupling of a CNN with discriminant analysis, can be used to automatically label radiographs for the presence of scoliosis treatment. This information is usually missing from DICOM metadata, so such method could facilitate the use of large databases. Furthermore, the same model architecture could potentially be applied for other radiograph classifications, such as sex and presence of scoliotic deformity.

Quasi-automatic early detection of progressive idiopathic scoliosis from biplanar radiography: a preliminary validation.

PURPOSE: To validate the predictive power and reliability of a novel quasi-automatic method to calculate the severity index of adolescent idiopathic scoliosis (AIS). METHODS: Fifty-five AIS patients were prospectively included (age 10-15, Cobb 16° ± 4°). Patients underwent low-dose biplanar X-rays, and a novel fast method for 3D reconstruction of the spine was performed. They were followed until skeletal maturity (stable patients) or brace prescription (progressive patients). The severity index was calculated at the first examination, based on 3D parameters of the scoliotic curve, and it was compared with the patient's final outcome (progressive or stable). Three operators have repeated the 3D reconstruction twice for a subset of 30 patients to assess reproducibility (through Cohen's kappa and intra-class correlation coefficient). RESULTS: Eighty-five percentage of the patients were correctly classified as stable or progressive by the severity index, with a sensitivity of 92% and specificity of 74%. Substantial intra-operator agreement and good inter-operator agreement were observed, with 80% of the progressive patients correctly detected at the first examination. The novel severity index assessment took less than 4 min of operator time. CONCLUSIONS: The fast and semiautomatic method for 3D reconstruction developed in this work allowed for a fast and reliable calculation of the severity index. The method is fast and user friendly. Once extensively validated, this severity index could allow very early initiation of conservative treatment for progressive patients, thus increasing treatment efficacy and therefore reducing the need for corrective surgery. These slides can be retrieved under Electronic Supplementary Material.