Photograph - Woman Standing by a Large Tree Trunk

A woman wearing a hat and holding a small purse. She is standing next to a large tree trunk and there are benches behind her.

Four railway ticket stubs for the Grand Trunk Railway System from St. Catharines, Ontario to Buffalo, New York

Four railway ticket stubs for the Grand Trunk Railway System from St. Catharines, Ontario to Buffalo, New York, Feb 8, 1919.

Printed blank from Grand Trunk Railway for shipping to St. Catharines from Buffalo for table

Printed blank from Grand Trunk Railway for shipping to St. Catharines from Buffalo for table, 1888.

Letter to the Honourable William Dickson at Wood Lawn, Youngstown, New York from W. Bushby

Letter to the Honourable William Dickson at Wood Lawn, Youngstown, New York from W. Bushby. He says that Mary is probably going to marry Mr. Lyon and he asks if there is any chance that Mr. Dickson could come for the wedding. He says he heard about the death of George Hamilton from John Hamilton (3 ½ pages, handwritten), Sept. 29, 1836.

Receipt from Thomas Handford, trunk maker, London, England

Receipt from Thomas Handford, trunk maker, London, England for new cover to writing case with engraving, Aug. 27, 1847.

Inventory of goods and chattels belonging to Samuel Wood and delivered to the Honourable William Dickson

Inventory of goods and chattels belonging to Samuel Wood and delivered to the Honourable William Dickson (double-sided, handwritten page), Dec. 10, 1828.

Scoliosis curve type classification from 3D trunk image

Adolescent idiopathic scoliosis (AIS) is a deformity of the spine manifested by asymmetry and deformities of the external surface of the trunk. Classification of scoliosis deformities according to curve type is used to plan management of scoliosis patients. Currently, scoliosis curve type is determined based on X-ray exam. However, cumulative exposure to X-rays radiation significantly increases the risk for certain cancer. In this paper, we propose a robust system that can classify the scoliosis curve type from non invasive acquisition of 3D trunk surface of the patients. The 3D image of the trunk is divided into patches and local geometric descriptors characterizing the surface of the back are computed from each patch and forming the features. We perform the reduction of the dimensionality by using Principal Component Analysis and 53 components were retained. In this work a multi-class classifier is built with Least-squares support vector machine (LS-SVM) which is a kernel classifier. For this study, a new kernel was designed in order to achieve a robust classifier in comparison with polynomial and Gaussian kernel. The proposed system was validated using data of 103 patients with different scoliosis curve types diagnosed and classified by an orthopedic surgeon from the X-ray images. The average rate of successful classification was 93.3% with a better rate of prediction for the major thoracic and lumbar/thoracolumbar types.

Scoliosis Follow-Up Using Noninvasive Trunk Surface Acquisition

Adolescent idiopathic scoliosis (AIS) is a musculoskeletal pathology. It is a complex spinal curvature in a 3-D space that also affects the appearance of the trunk. The clinical follow-up of AIS is decisive for its management. Currently, the Cobb angle, which is measured from full spine radiography, is the most common indicator of the scoliosis progression. However, cumulative exposure to X-rays radiation increases the risk for certain cancers. Thus, a noninvasive method for the identification of the scoliosis progression from trunk shape analysis would be helpful. In this study, a statistical model is built from a set of healthy subjects using independent component analysis and genetic algorithm. Based on this model, a representation of each scoliotic trunk from a set of AIS patients is computed and the difference between two successive acquisitions is used to determine if the scoliosis has progressed or not. This study was conducted on 58 subjects comprising 28 healthy subjects and 30 AIS patients who had trunk surface acquisitions in upright standing posture. The model detects 93% of the progressive cases and 80% of the nonprogressive cases. Thus, the rate of false negatives, representing the proportion of undetected progressions, is very low, only 7%. This study shows that it is possible to perform a scoliotic patient's follow-up using 3-D trunk image analysis, which is based on a noninvasive acquisition technique.

Analysis of scoliosis trunk deformities using ICA

This paper describes a method for analyzing scoliosis trunk deformities using Independent Component Analysis (ICA). Our hypothesis is that ICA can capture the scoliosis deformities visible on the trunk. Unlike Principal Component Analysis (PCA), ICA gives local shape variation and assumes that the data distribution is not normal. 3D torso images of 56 subjects including 28 patients with adolescent idiopathic scoliosis and 28 healthy subjects are analyzed using ICA. First, we remark that the independent components capture the local scoliosis deformities as the shoulder variation, the scapula asymmetry and the waist deformation. Second, we note that the different scoliosis curve types are characterized by different combinations of specific independent components.

A physically based trunk soft tissue modeling for scoliosis surgery planning systems

One of the major concerns of scoliotic patients undergoing spinal correction surgery is the trunk's external appearance after the surgery. This paper presents a novel incremental approach for simulating postoperative trunk shape in scoliosis surgery. Preoperative and postoperative trunk shapes data were obtained using three-dimensional medical imaging techniques for seven patients with adolescent idiopathic scoliosis. Results of qualitative and quantitative evaluations, based on the comparison of the simulated and actual postoperative trunk surfaces, showed an adequate accuracy of the method. Our approach provides a candidate simulation tool to be used in a clinical environment for the surgery planning process.

Evaluation of Reducibility of Trunk Asymmetry in Lateral Bending

The value of the lateral bending test is important in the assessment of spinal curve mobility and prediction of surgical outcome in the treatment of adolescent idiopathic scoliosis (AIS). However, radiographic bending tests are unable to assess the reducibility of trunk asymmetry. This study aims to exploit surface topography measurement in order to evaluate the changes in shape of the trunk (a) between bending and neutral standing positions, and (b) between standing pre- and post-operative visits, in a cohort of adolescents with AIS having undergone surgical correction; and to correlate the differences measured in cases (a) and (b). Our cohort includes 13 patients with right thoracic AIS. Each patient had their 3D trunk surface digitized with a multi-head InSpeck system in standing posture (at the pre-op and post-op visits) and in maximum voluntary right and left bending (at the pre-op visit). We developed a novel trunk shape analysis method which produces a set of inclined trunk cross-sections allowing comparison between different postures. Two asymmetry indices, trunk rotation (TR) and back surface rotation (BSR), were computed in all cases and a statistical analysis was performed. Our correlation study (Pearson test) showed fair correlations in most cases between the changes in side-bending and those post-surgery, with the strongest relationship (p-value < 0.01) when combining the TR measurements from both bendings. These results provide evidence that the bending test can be used to assess trunk asymmetry reducibility. The proposed approach could provide a non-invasive trunk asymmetry reducibility test for routine clinical use in AIS surgery planning.

Simulation of the postoperative trunk appearance in scoliosis surgery

Persistence of external trunk asymmetry after scoliosis surgical treatment is frequent and difficult to predict by clinicians. This is a significant problem considering that correction of the apparent deformity is a major factor of satisfaction for the patients. A simulation of the correction on the external appearance would allow the clinician to illustrate to the patient the potential result of the surgery and would help in deciding on a surgical strategy that could most improve his/her appearance. We describe a method to predict the scoliotic trunk shape after a spine surgical intervention. The capability of our method was evaluated using real data of scoliotic patients. Results of the qualitative evaluation were very promising and a quantitative evaluation based on the comparison of the simulated and the actual postoperative trunk surface showed an adequate accuracy for clinical assessment. The required short simulation time also makes our approach an eligible candidate for a clinical environment demanding interactive simulations.

Validity of a Quantitative Clinical Measurement Tool of Trunk Posture in Idiopathic Scoliosis

STUDY DESIGN: Concurrent validity between postural indices obtained from digital photographs (two-dimensional [2D]), surface topography imaging (three-dimensional [3D]), and radiographs. OBJECTIVE: To assess the validity of a quantitative clinical postural assessment tool of the trunk based on photographs (2D) as compared to a surface topography system (3D) as well as indices calculated from radiographs. SUMMARY OF BACKGROUND DATA: To monitor progression of scoliosis or change in posture over time in young persons with idiopathic scoliosis (IS), noninvasive and nonionizing methods are recommended. In a clinical setting, posture can be quite easily assessed by calculating key postural indices from photographs. METHODS: Quantitative postural indices of 70 subjects aged 10 to 20 years old with IS (Cobb angle, 15 degrees -60 degrees) were measured from photographs and from 3D trunk surface images taken in the standing position. Shoulder, scapula, trunk list, pelvis, scoliosis, and waist angles indices were calculated with specially designed software. Frontal and sagittal Cobb angles and trunk list were also calculated on radiographs. The Pearson correlation coefficients (r) was used to estimate concurrent validity of the 2D clinical postural tool of the trunk with indices extracted from the 3D system and with those obtained from radiographs. RESULTS: The correlation between 2D and 3D indices was good to excellent for shoulder, pelvis, trunk list, and thoracic scoliosis (0.81>r<0.97; P<0.01) but fair to moderate for thoracic kyphosis, lumbar lordosis, and thoracolumbar or lumbar scoliosis (0.30>r<0.56; P<0.05). The correlation between 2D and radiograph spinal indices was fair to good (-0.33 to -0.80 with Cobb angles and 0.76 for trunk list; P<0.05). CONCLUSION: This tool will facilitate clinical practice by monitoring trunk posture among persons with IS. Further, it may contribute to a reduction in the use of radiographs to monitor scoliosis progression.

Personalized 3D reconstruction of the rib cage for clinical assessment of trunk deformities

Scoliosis is a 3D deformity of the spine and rib cage. Extensive validation of 3D reconstruction methods of the spine from biplanar radiography has already been published. In this article, we propose a novel method to reconstruct the rib cage, using the same biplanar views as for the 3D reconstruction of the spine, to allow clinical assessment of whole trunk deformities. This technique uses a semi-automatic segmentation of the ribs in the postero-anterior X-ray view and an interactive segmentation of partial rib edges in the lateral view. The rib midlines are automatically extracted in 2D and reconstructed in 3D using the epipolar geometry. For the ribs not visible in the lateral view, the method predicts their 3D shape. The accuracy of the proposed method has been assessed using data obtained from a synthetic bone model as a gold standard and has also been evaluated using data of real patients with scoliotic deformities. Results show that the reconstructed ribs enable a reliable evaluation of the rib axial rotation, which will allow a 3D clinical assessment of the spine and rib cage deformities.

Multilevel Analysis of Trunk Surface Measurements for Noninvasive Assessment of Scoliosis Deformities.

Study Design. Reliability study. Objectives. To assess between-acquisition reliability of new multilevel trunk cross sections measurements, in order to define what is a real change when comparing 2 trunk surface acquisitions of a same patient, before and after surgery or throughout the clinical monitoring. Summary of Background Data. Several cross-sectional surface measurements have been proposed in the literature for noninvasive assessment of trunk deformity in patients with adolescent idiopathic scoliosis (AIS). However, only the maximum values along the trunk are evaluated and used for monitoring progression and assessing treatment outcome. Methods. Back surface rotation (BSR), trunk rotation (TR), and coronal and sagittal trunk deviation are computed on 300 cross sections of the trunk. Each set of 300 measures is represented as a single functional data, using a set of basis functions. To evaluate between-acquisition variability at all trunk levels, a test-retest reliability study is conducted on 35 patients with AIS. A functional correlation analysis is also carried out to evaluate any redundancy between the measurements. Results. Each set of 300 measures was successfully described using only 10 basis functions. The test-retest reliability of the functional measurements is good to very good all over the trunk, except above the shoulders level. The typical errors of measurement are between 1.20° and 2.2° for the rotational measures and between 2 and 6 mm for deviation measures. There is a very strong correlation between BSR and TR all over the trunk, a moderate correlation between coronal trunk deviation and both BSR and TR, and no correlation between sagittal trunk deviation and any other measurement. Conclusion. This novel representation of trunk surface measurements allows for a global assessment of trunk surface deformity. Multilevel trunk measurements provide a broader perspective of the trunk deformity and allow a reliable multilevel monitoring during clinical follow-up of patients with AIS and a reliable assessment of the esthetic outcome after surgery.