Rahman, Munsur;Cil, Akin;Johnson, Michael;Lu, Yunkai;Guess, Trent M.
Advances in biomechanics and applications
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v.1
no.3
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pp.169-185
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2014
Computational multibody models of the elbow can provide a versatile tool to study joint mechanics, cartilage loading, ligament function and the effects of joint trauma and orthopaedic repair. An efficiently developed computational model can assist surgeons and other investigators in the design and evaluation of treatments for elbow injuries, and contribute to improvements in patient care. The purpose of this study was to develop an anatomically correct elbow joint model and validate the model against experimental data. The elbow model was constrained by multiple bundles of non-linear ligaments, three-dimensional deformable contacts between articulating geometries, and applied external loads. The developed anatomical computational models of the joint can then be incorporated into neuro-musculoskeletal models within a multibody framework. In the approach presented here, volume images of two cadaver elbows were generated by computed tomography (CT) and one elbow by magnetic resonance imaging (MRI) to construct the three-dimensional bone geometries for the model. The ligaments and triceps tendon were represented with non-linear spring-damper elements as a function of stiffness, ligament length and ligament zero-load length. Articular cartilage was represented as uniform thickness solids that allowed prediction of compliant contact forces. As a final step, the subject specific model was validated by comparing predicted kinematics and triceps tendon forces to experimentally obtained data of the identically loaded cadaver elbow. The maximum root mean square (RMS) error between the predicted and measured kinematics during the complete testing cycle was 4.9 mm medial-lateral translational of the radius relative to the humerus (for Specimen 2 in this study) and 5.30 internal-external rotation of the radius relative to the humerus (for Specimen 3 in this study). The maximum RMS error for triceps tendon force was 7.6 N (for Specimen 3).
Journal of information and communication convergence engineering
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v.17
no.2
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pp.91-96
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2019
In this study, a system to increase the expressiveness of existing standard terminology using three-dimensional (3D) data is designed. We analyze the existing medical terminology system by searching the reference literature and perform an expert group focus survey. A human body image is generated using a 3D modeling tool. Then, the anatomical position of the human body is mapped to the 3D coordinates' identification (ID) and metadata. We define the term to represent the 3D human body position in a total of 12 categories, including semantic terminology entity and semantic disorder. The Blender and 3ds Max programs are used to create the 3D model from medical imaging data. The generated 3D human body model is expressed by the ID of the coordinate type (x, y, and z axes) based on the anatomical position and mapped to the semantic entity including the meaning. We propose a system of standard terminology enabling integration and utilization of the 3D human body model, coordinates (ID), and metadata. In the future, through cooperation with the Electronic Health Record system, we will contribute to clinical research to generate higher-quality big data.
Objective : The aim of this study was to evaluate the utility of volume-rendered helical computerized tomography (CT) angiography focusing tracheostomy tube and innominate artery for prevention of tracheoinnominate artery fistula. Methods : The authors retrospectively analyzed 22 patients with tracheostomy who had checked CT angiography. To evaluate the relationship between tracheostomy tube and innominate artery, we divided into three categories. First proximal tube position based on cervical vertebra, named "tracheostomy tube departure level (TTDL)". Second, distal tube position and course of innominate artery, named "tracheostomy tube-innominate artery configuration (TTIC)". Third, the gap between the tube and innominate artery, named "tracheostomy tube to innominate artery gap (TTIG)". The TTDL/TTIC and TTIG are based on 3-dimensional (3D) reconstruction around tracheostomy and enhanced axial slices of upper chest, respectively. Results : First, mean TTDL was $6.8{\pm}0.6$. Five cases (23%) were lower than C7 vertebra. Second, TTIC were remote to innominate artery (2 cases; 9.1 %), matched with it (14 cases; 63.6%) or crossed it (6 cases; 27.3%). Only 9% of cases were definitely free from innominate artery injury. Third, average TTIG was $4.3{\pm}4.6$ mm. Surprisingly, in 6 cases (27.3%), innominate artery, trachea wall and tracheostomy tube were tightly attached all together, thus have much higher probability of erosion. Conclusion : If low TTDL, match or crossing type TTIC with reverse-L shaped innominate artery, small trachea and thin TTIG are accompanied all together, we may seriously consider early plugging and tube removal.
Cervical foraminal stenosis is a disease in which the nerves that pass from the spinal canal to the limbs are narrowed and the nerves are compressed or damaged. Due to the lack of an imaging method that provides quantitatively stenosis, this study attempted to evaluate the area of the cervical vertebrae by reconstructing a three-dimensional computed tomography image, and to determine the area of the neural foramen in normal adults to calculate the stenosis rate. Using a three-dimensional image processing program, the surrounding bones including the posterior spinous process, lateral process, and lamellar bones of the cervical vertebra were removed so that the neural foramen could be observed well. A region of interest including the neural foraminal area of the three-dimensional image was set using ImageJ, and the number of pixels in the neural foraminal area was measured. The neural foraminal area was calculated by multiplying the number of measured pixels by the pixel size. To measure the largest neural foraminal area, it was measured between 40~50 degrees in the opposite direction and 15~20 degrees toward the head. The average area of the right C2-3 foramen was 44.32 mm2, C3-4 area was 34.69 mm2, C4-5 area was 36.41 mm2, C5-6 area was 35.22 mm2, C6-7 area was 36.03 mm2. The average area of the left C2-3 foramen was 42.71 mm2, C3-4 area was 32.23 mm2, C5-6 area was 34.56 mm2, and C6-7 area was 31.89 mm2. By creating a reference table based on the neural foramen area of normal adults, the stenosis rate of patients with neural foraminal stenosis could be quantitatively calculated. It is expected that this method can be used as basic data for the diagnosis of cervical vertebral foraminal stenosis.
Objective: The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC. Materials and Methods: Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance. Results: The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set. Conclusion: The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.
Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.
The recent 3D printing technology is used in various medical, manufacturing, and education fields and is more efficient in terms of production process, time, and cost than existing production. Especially in fracture surgery, interest and research have been focused on improving accuracy, shortening of operation time and recovery time, and reducing reoperation. However, because of the financial and technical problems of the 3D printer and the file conversion program, the 3D printing is made directly at the hospital, and it is not generally used for diagnosis of fracture and surgical research. In this study, to solve those problems, clavicle CT imaging was switched into Osirix Open Source DICOM Viewer, Stereolithography file conversion programs and commercial Terarecon 3D DICOM Viewer, file conversion programs, and then clavicle fracture model was directly made through 3D printer of fused filament fabrication wire additive processing method, and then the accuracy of the shape was compared and analyzed. Clavicle fracture models printed in two methods were blind-tested on clinicians of general hospitals' orthopedics and radiologic technicians with over 10 years of experiences, and then their analysis opinions of resolution reviews were analyzed. The result showed no difference. The 3D printing model with open source DICOM STL file conversion program used was applicable to clinical, so it is considered useful in precision diagnosis of fracture and operation plans.
Background: The concept of the ideal morphology for the alveolar bone form is an important element to reconstruct or restore the in maximizing esthetic profile and functional alveolar bone restoration. The purpose of this preliminary study is to evaluate the normal alveolar bone structure to provide the standard reference and guide template for use in diagnosing for implant placement, determining the correct amount of bone augmentation in actual clinical practice and producing prostheses based on three-dimensional imaging assessment of alveolar bone. Methods: This study was included 11 men and 11 women (average age, 22.6 and 24.5 years, respectively) selected from among 127 patients. The horizontal widths of alveolar bone of maxilla and mandible were measured at the crestal, mid-root, and root apex level on MDCT (multi-detector computed tomography) images reconstructed by medical imaging software. In addition, tooth dimensions of the central incisors, canines, second premolars, and first molars of maxilla and mandible, including the horizontal width of the interdental alveolar bone crest, were also measured and statistically analyzed. Results: The horizontal alveolar bone width of the palatal side of maxilla showed a distinct increment from the alveolar bone crest to the apical region in both anterior and posterior areas. The average widths of the maxillary alveolar ridge were as follows: central incisor, 7.43 mm; canine, 8.91 mm; second premolar, 9.57 mm; and first molar, 12.38 mm. The average widths of the mandibular alveolar ridge were as follows: central incisor, 6.21 mm; canine, 8.55 mm; second premolar, 8.45 mm; and first molar, 10.02 mm. In the buccal side, the alveolar bone width was not increased from the crest to the apical region. The horizontal alveolar bone width of an apical and mandibular border region was thinner than at the mid-root level. Conclusions: The results of the preliminary study are useful as a clinical guideline when determining dental implant diameter and position. And also, these measurements can also be useful during the production of prefabricated membranes and customized alveolar bone scaffolds.
The accurate measurement of the femoral anteversion is important for the derotational osteotomy. To estimate femoral anteversion, following three major parameters are required; the neck axis, the long axis, and the knee axis. Conventional methods on the basis of 2D images are ambiguous to determine these major axes. As the femur has a complex 3 dimensional structure, the 3 dimensional model should be applied for accurate and reliable measurement of femoral anteversion. In this thesis, we model femur and define three parameters. The neck axis is defined from the femoral head and neck model. The long axis is determined from the cylindrical model of the femoral shaft. The knee axis is also determined from the model of femoral condyles. According to the definition of the femoral anteversion, the femoral anteversion is efficiently estimated from these models. 20 specimens were tested by the conventional 2D imaging method and 3D imaging method witch was developed by authors and the new 3D modeling method. The study provides accurate, fast and human factor free measurement for femoral anteversion.
KIPS Transactions on Software and Data Engineering
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v.3
no.8
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pp.329-334
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2014
In this study, a new method that automatically segments trabecular bone for its morphological analysis using micro-computed tomography imaging was proposed. In the proposed method, the bone region was extracted using a threshold value, and the outer boundary of the bone was detected. The sphere of maximum size with the corresponding voxel as the center was obtained by applying the sphere-fitting method to each voxel of the bone region. If this sphere includes the outer boundary of the bone, the voxels included in the sphere are classified as cortical bone; otherwise, they are classified as trabecular bone. The proposed method was applied to images of the distal femurs of 15 mice, and comparative experiments, with results manually divided by a person, were performed. Four morphological parameters-BV/TV, Tb.Th, Tb.Sp, and Tb.N-for the segmented trabecular bone were measured. The results were compared by regression analysis and the Bland-Altman method; BV/TV, Tb.Th, Tb.Sp, and Tb.N were all in the credible range. In addition, not only can the sphere-fitting method be simply implemented, but trabecular bone can also be divided precisely by using the three-dimensional information.
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