Thoracolumbar spine fractures in patients who have sustained severe trauma: depiction with multi-detector row CT

PURPOSE: To determine if multi–detector row computed tomography (CT) can replace conventional radiography and be performed alone in severe trauma patients for the depiction of thoracolumbar spine fractures. MATERIALS AND METHODS: One hundred consecutive severe trauma patients who underwent conventional radiography of the thoracolumbar spine as well as thoracoabdominal multi–detector row CT were prospectively identified. Conventional radiographs were reviewed independently by three radiologists and two orthopedic surgeons; CT images were reviewed by three radiologists. Reviewers were blinded both to one another’s reviews and to the results of initial evaluation. Presence, location, and stability of fractures, as well as quality of reviewed images, were assessed. Statistical analysis was performed to determine sensitivity and interobserver agreement for each procedure, with results of clinical and radiologic follow-up as the standard of reference. The time to perform each examination and the radiation dose involved were evaluated. A resource cost analysis was performed. RESULTS: Sixty-seven fractured vertebrae were diagnosed in 26 patients. Twelve patients had unstable spine fractures. Mean sensitivity and interobserver agreement, respectively, for detection of unstable fractures were 97.2% and 0.951 for multi–detector row CT and 33.3% and 0.368 for conventional radiography. The median times to perform a conventional radiographic and a multi–detector row CT examination, respectively, were 33 and 40 minutes. Effective radiation doses at conventional radiography of the spine and thoracoabdominal multi–detector row CT, respectively, were 6.36 mSv and 19.42 mSv. Multi–detector row CT enabled identification of 146 associated traumatic lesions. The costs of conventional radiography and multi–detector row CT, respectively, were $145 and $880 per patient. CONCLUSION: Multi–detector row CT is a better examination for depicting spine fractures than conventional radiography. It can replace conventional radiography and be performed alone in patients who have sustained severe trauma.

Evaluation of texture features in hepatic tissue characterization from non-enhanced CT images

Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers

The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Algorithms For Automatic And Robust Registration Of 3D Head Scans

wo methods for registering laser-scans of human heads and transforming them to a new semantically consistent topology defined by a user-provided template mesh are described. Both algorithms are stated within the Iterative Closest Point framework. The first method is based on finding landmark correspondences by iteratively registering the vicinity of a landmark with a re-weighted error function. Thin-plate spline interpolation is then used to deform the template mesh and finally the scan is resampled in the topology of the deformed template. The second algorithm employs a morphable shape model, which can be computed from a database of laser-scans using the first algorithm. It directly optimizes pose and shape of the morphable model. The use of the algorithm with PCA mixture models, where the shape is split up into regions each described by an individual subspace, is addressed. Mixture models require either blending or regularization strategies, both of which are described in detail. For both algorithms, strategies for filling in missing geometry for incomplete laser-scans are described. While an interpolation-based approach can be used to fill in small or smooth regions, the model-driven algorithm is capable of fitting a plausible complete head mesh to arbitrarily small geometry, which is known as "shape completion". The importance of regularization in the case of extreme shape completion is shown.

Virtual implant planning in the edentulous maxilla: criteria for decision making of prosthesis design

OBJECTIVES To evaluate prosthetic parameters in the edentulous anterior maxilla for decision making between fixed and removable implant prosthesis using virtual planning software. MATERIAL AND METHODS CT- or DVT-scans of 43 patients (mean age 62 ± 8 years) with an edentulous maxilla were analyzed with the NobelGuide software. Implants (≥3.5 mm diameter, ≥10 mm length) were virtually placed in the optimal three-dimensional prosthetic position of all maxillary front teeth. Anatomical and prosthetic landmarks, including the cervical crown point (C-Point), the acrylic flange border (F-Point), and the implant-platform buccal-end (I-Point) were defined in each middle section to determine four measuring parameters: (1) acrylic flange height (FLHeight), (2) mucosal coverage (MucCov), (3) crown-Implant distance (CID) and (4) buccal prosthesis profile (ProsthProfile). Based on these parameters, all patients were assigned to one of three classes: (A) MucCov ≤ 0 mm and ProsthProfile≥45(0) allowing for fixed prosthesis, (B) MucCov = 0-5 mm and/or ProsthProfile = 30(0) -45(0) probably allowing for fixed prosthesis, and (C) MucCov ≥ 5 mm and/or ProsthProfile ≤ 30(0) where removable prosthesis is favorable. Statistical analyses included descriptive methods and non-parametric tests. RESULTS Mean values were for FLHeight 10.0 mm, MucCov 5.6 mm, CID 7.4 mm, and ProsthProfile 39.1(0) . Seventy percent of patients fulfilled class C criteria (removable), 21% class B (probably fixed), and 2% class A (fixed), while in 7% (three patients) bone volume was insufficient for implant planning. CONCLUSIONS The proposed classification and virtual planning procedure simplify the decision-making process regarding type of prosthesis and increase predictability of esthetic treatment outcomes. It was demonstrated that in the majority of cases, the space between the prosthetic crown and implant platform had to be filled with prosthetic materials.

Positional guidelines for orthodontic mini-implant placement in the anterior alveolar region: a systematic review

PURPOSE To investigate the adequacy of potential sites for insertion of orthodontic mini-implants (OMIs) in the anterior alveolar region (delimited by the first premolars) through a systematic review of studies that used computed tomography (CT) or cone beam CT (CBCT) to assess anatomical hard tissue parameters, such as bone thickness, available space, and bone density. MATERIALS AND METHODS MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews were searched to identify all relevant papers published between 1980 and September 2011. An extensive search strategy was performed that included the key words "computerized (computed) tomography" and "mini-implants." Information was extracted from the eligible articles for three anatomical areas: maxillary anterior buccal, maxillary anterior palatal, and mandibular anterior buccal. Quantitative data obtained for each anatomical variable under study were evaluated qualitatively with a scoring system. RESULTS Of the 790 articles identified by the search, 8 were eligible to be included in the study. The most favorable area for OMI insertion in the anterior maxilla (buccally and palatally) and mandible is between the canine and the first premolar. The best alternative area in the maxilla (buccally) and the mandible is between the lateral incisor and the canine, while in the maxillary palatal area it is between the central incisors or between the lateral incisor and the canine. CONCLUSIONS Although there is considerable heterogeneity among studies, there is a good level of agreement regarding the optimal site for OMI placement in the anterior region among investigations of anatomical hard tissue parameters based on CT or CBCT scans. In this context, the area between the lateral incisor and the first premolar is the most favorable. However, interroot distance seems to be a critical factor that should be evaluated carefully.

What is the incidence of intracranial bleeding in patients with mild traumatic brain injury? A retrospective study in 3088 Canadian CT head rule patients

OBJECTIVE Only limited data exists in terms of the incidence of intracranial bleeding (ICB) in patients with mild traumatic brain injury (MTBI). METHODS We retrospectively identified 3088 patients (mean age 41 range (7-99) years) presenting with isolated MTBI and GCS 14-15 at our Emergency Department who had undergone cranial CT (CCT) between 2002 and 2011. Indication for CCT was according to the "Canadian CT head rules." Patients with ICB were either submitted for neurosurgical treatment or kept under surveillance for at least 24 hours. Pearson's correlation coefficient was used to correlate the incidence of ICB with age, gender, or intake of coumarins, platelet aggregation inhibitors, or heparins. RESULTS 149 patients (4.8%) had ICB on CCT. No patient with ICB died or deteriorated neurologically. The incidence of ICB increased with age and intake of anticoagulants without clinically relevant correlation (R = 0.11; P < 0.001; R = -0.06; P < 0.001). CONCLUSION Our data show an incidence of 4.8% for ICB after MTBI. However, neurological deterioration after MTBI seems to be rare, and the need for neurosurgical intervention is only required in selected cases. The general need for CCT in patients after MTBI is therefore questionable, and clinical surveillance may be sufficient when CCT is not available.

Optimal sequence timing of CT angiography and perfusion CT in patients with stroke

OBJECTIVE Standard stroke CT protocols start with non-enhanced CT followed by perfusion-CT (PCT) and end with CTA. We aimed to evaluate the influence of the sequence of PCT and CTA on quantitative perfusion parameters, venous contrast enhancement and examination time to save critical time in the therapeutic window in stroke patients. METHODS AND MATERIALS Stroke CT data sets of 85 patients, 47 patients with CTA before PCT (group A) and 38 with CTA after PCT (group B) were retrospectively analyzed by two experienced neuroradiologists. Parameter maps of cerebral blood flow, cerebral blood volume, time to peak and mean transit time and contrast enhancements (arterial and venous) were compared. RESULTS Both readers rated contrast of brain-supplying arteries to be equal in both groups (p=0.55 (intracranial) and p=0.73 (extracranial)) although the extent of venous superimposition of the ICA was rated higher in group B (p=0.04). Quantitative perfusion parameters did not significantly differ between the groups (all p>0.18), while the extent of venous superimposition of the ICA was rated higher in group B (p=0.04). The time to complete the diagnostic CT examination was significantly shorter for group A (p<0.01). CONCLUSION Performing CTA directly after NECT has no significant effect on PCT parameters and avoids venous preloading in CTA, while examination times were significantly shorter.

Measurement of structural anisotropy in femoral trabecular bone using clinical-resolution CT images

Discrepancies in finite-element model predictions of bone strength may be attributed to the simplified modeling of bone as an isotropic structure due to the resolution limitations of clinical-level Computed Tomography (CT) data. The aim of this study is to calculate the preferential orientations of bone (the principal directions) and the extent to which bone is deposited more in one direction compared to another (degree of anisotropy). Using 100 femoral trabecular samples, the principal directions and degree of anisotropy were calculated with a Gradient Structure Tensor (GST) and a Sobel Structure Tensor (SST) using clinical-level CT. The results were compared against those calculated with the gold standard Mean-Intercept-Length (MIL) fabric tensor using micro-CT. There was no significant difference between the GST and SST in the calculation of the main principal direction (median error=28°), and the error was inversely correlated to the degree of transverse isotropy (r=−0.34, p<0.01). The degree of anisotropy measured using the structure tensors was weakly correlated with the MIL-based measurements (r=0.2, p<0.001). Combining the principal directions with the degree of anisotropy resulted in a significant increase in the correlation of the tensor distributions (r=0.79, p<0.001). Both structure tensors were robust against simulated noise, kernel sizes, and bone volume fraction. We recommend the use of the GST because of its computational efficiency and ease of implementation. This methodology has the promise to predict the structural anisotropy of bone in areas with a high degree of anisotropy, and may improve the in vivo characterization of bone.

Quantification of coronary artery stenosis with high-resolution CT in comparison with histopathology in an ex vivo study

PURPOSE To investigate the ex vivo performance of high-resolution computed tomography (CT) for quantitative assessment of percentage diameter stenosis in coronary arteries compared to histopathology. MATERIALS AND METHODS High-resolution CT was performed in 26 human heart specimens after the injection of iodinated contrast media into the coronary arteries. Coronary artery plaques were visually identified on CT images and the grade of stenosis for each plaque was measured with electronic calipers. All coronary plaques were characterized by histopathology according to the Stary classification, and the percentage of stenosis was measured. RESULTS CT depicted 84% (274/326) of all coronary plaques identified by histology. Missed plaques by CT were of Stary type I (n=31), type II (n=16), and type III (n=5). The stenosis degree significantly correlated between CT and histology (r=0.81, p<0.001). CT systematically overestimated the stenosis of calcified plaques (mean difference - 11.0 ± 9.5%, p<0.01) and systematically underestimated the stenosis of non-calcified plaques (mean difference -6.8 ± 10.4%, p<0.05), while there was no significant difference for mixed-type plaques (mean difference -0.4 ± 11.7%, p=0.85). There was a significant underestimation of stenosis degree as measured by CT for Stary II plaques (mean difference -14 ± 9%, p<0.01) and a significant overestimation for Stary VII plaques (mean difference 9 ± 10%, p<0.05), but there was no significant difference in stenosis degree between both modalities for other plaque types. CONCLUSIONS High-resolution CT reliably depicts advanced stage coronary plaques with an overall good correlation of stenosis degree compared to histology, however, the degree of stenosis is systematically overestimated in calcified and underestimated in non-calcified plaques.