Coronary artery stenoses: detection with calcium scoring, CT angiography, and both methods combined

PURPOSE: To investigate prospectively the relative accuracy of computed tomographic (CT) angiography, calcium scoring (CS), and both methods combined in demonstrating coronary artery stenoses by using conventional angiography as the reference standard. MATERIALS AND METHODS: The study was approved by the institutional review board Human Research Ethics Committee, and all patients completed written informed consent. Fifty patients (40 men, 10 women) aged 62 years ± 11 (± standard deviation) who were suspected of having coronary artery disease underwent both conventional coronary angiography and multisection coronary CT angiography with CS. Sensitivity and specificity of CS, CT angiography, and both methods combined in demonstrating luminal stenosis greater than or equal to 50% were determined for each arterial segment, coronary vessel, and patient. Receiver operating characteristic (ROC) curves were generated for CS prediction of significant stenosis, and the Mann-Whitney U test was used for comparison of CS between groups. RESULTS: When used with segment-specific electrocardiographic phase reconstructions, CT angiography demonstrated stenosed segments with 79% sensitivity and 95% specificity. Mean calcium score was greater in segments, vessels, and patients with stenoses than in segments, vessels, and patients without stenoses (P < .001 for all); nine (16%) of 56 stenosed segments, however, had a calcium score of 0. The patient calcium score correlated strongly with the number of stenosed arteries (Spearman {rho} = 0.75, P < .001). CS was more accurate in demonstrating stenosis in patients than in segments (areas under ROC curve were 0.88 and 0.74, respectively). CT angiography, however, was more accurate than CS in demonstrating stenosis in patients, vessels, and segments. The sensitivity and specificity of CS varied according to the threshold used, but when the calcium score cutoff (ie, >150) matched the specificity of CT angiography (95%), the sensitivity of CS in demonstrating stenosed segments was 29% (compared with 79% for CT angiography). Combining CT angiography with CS (at threshold of 400) improved the sensitivity of CT angiography (from 93% to 100%) in demonstrating significant coronary disease in patients, without a loss of specificity (85%); this finding, however, was not statistically significant. CONCLUSION: CT angiography is more accurate than CS in demonstrating coronary stenoses. A patient calcium score of greater than or equal to 400, however, can be used to potentially identify patients with significant coronary stenoses not detected at CT angiography.

Cost-effectiveness analysis of screening for lung cancer with low dose spiral CT (computed tomography) in the Australian setting

Introduction:
Low dose spiral computed tomography (CT) is a sensitive screening tool for lung cancer that is currently being evaluated in both non-randomised studies and randomised controlled trials.
Methods:
We conducted a quantitative decision analysis using a Markov model to determine whether, in the Australian setting, offering spiral CT screening for lung cancer to high risk individuals would be cost-effective compared with current practice. This exploratory analysis was undertaken predominantly from the perspective of the government as third-party funder. In the base-case analysis, the costs and health outcomes (life-years saved and quality-adjusted life years) were calculated in a hypothetical cohort of 10,000 male current smokers for two alternatives: (1) screen for lung cancer with annual CT for 5 years starting at age 60 year and treat those diagnosed with cancer or (2) no screening and treat only those who present with symptomatic cancer.
Results:
For male smokers aged 60–64 years, with an annual incidence of lung cancer of 552 per 100,000, the incremental cost-effectiveness ratio was $57,325 per life-year saved and $105,090 per QALY saved. For females aged 60–64 years with the same annual incidence of lung cancer, the cost-effectiveness ratio was $51,001 per life-year saved and $88,583 per QALY saved. The model was used to examine the relationship between efficacy in terms of the expected reduction in lung cancer mortality at 7 years and cost-effectiveness. In the base-case analysis lung cancer mortality was reduced by 27% and all cause mortality by 2.1%. Changes in the estimated proportion of stage I cancers detected by screening had the greatest impact on the efficacy of the intervention and the cost-effectiveness. The results were also sensitive to assumptions about the test performance characteristics of CT scanning, the proportion of lung cancer cases overdiagnosed by screening, intervention rates for benign disease, the discount rate, the cost of CT, the quality of life in individuals with early stage screen-detected cancer and disutility associated with false positive diagnoses. Given current knowledge and practice, even under favourable assumptions, reductions in lung cancer mortality of less than 20% are unlikely to be cost-effective, using a value of $50,000 per life-year saved as the threshold to define a “cost-effective” intervention.
Conclusion:
The most feasible scenario under which CT screening for lung cancer could be cost-effective would be if very high-risk individuals are targeted and screening is either highly effective or CT screening costs fall substantially.

Interobserver reliability of radial head fracture classification : two-dimensional compared with three-dimensional CT

Background: The Broberg and Morrey modification of the Mason classification of radial head fractures has substantial interobserver variation. This study used a large web-based collaborative of experienced orthopaedic surgeons to test the hypothesis that three-dimensional reconstructions of computed tomography (CT) scans improve the interobserver reliability of the classification of radial head fractures according to the Broberg and Morrey modification of the Mason classification.

Methods: Eighty-five orthopaedic surgeons evaluated twelve radial head fractures. They were randomly assigned to review either radiographs and two-dimensional CT scans or radiographs and three-dimensional CT images to determine the fracture classification, fracture characteristics, and treatment recommendations. The kappa multirater measure (κ) was calculated to estimate agreement between observers.

Results: Three-dimensional CT had moderate agreement and two-dimensional CT had fair agreement among observers for the Broberg and Morrey modification of the Mason classification, a difference that was significant. Observers assessed seven fracture characteristics, including fracture line, comminution, articular surface involvement, articular step or gap of ≥2 mm, central impaction, recognition of more than three fracture fragments, and fracture fragments too small to repair. There was a significant difference in kappa values between three-dimensional CT and two-dimensional CT for fracture fragments too small to repair, recognition of three fracture fragments, and central impaction. The difference between the other four fracture characteristics was not significant. Among treatment recommendations, there was fair agreement for both three-dimensional CT and two-dimensional CT.

Conclusions: Although three-dimensional CT led to some small but significant decreases in interobserver variation, there is still considerable disagreement regarding classification and characterization of radial head fractures. Three-dimensional CT may be insufficient to optimize interobserver agreement.

Interobserver reliability of classification and characterization of proximal humeral fractures: a comparison of two and three-dimensional CT

Interobserver reliability for the classification of proximal humeral fractures is limited. The aim of this study was to test the null hypothesis that interobserver reliability of the AO classification of proximal humeral fractures, the preferred treatment, and fracture characteristics is the same for two-dimensional (2-D) and three-dimensional (3-D) computed tomography (CT). Members of the Science of Variation Group--fully trained practicing orthopaedic and trauma surgeons from around the world--were randomized to evaluate radiographs and either 2-D CT or 3-D CT images of fifteen proximal humeral fractures via a web-based survey and respond to the following four questions: (1) Is the greater tuberosity displaced? (2) Is the humeral head split? (3) Is the arterial supply compromised? (4) Is the glenohumeral joint dislocated? They also classified the fracture according to the AO system and indicated their preferred treatment of the fracture (operative or nonoperative). Agreement among observers was assessed with use of the multirater kappa (κ) measure. Interobserver reliability of the AO classification, fracture characteristics, and preferred treatment generally ranged from "slight" to "fair." A few small but statistically significant differences were found. Observers randomized to the 2-D CT group had slightly but significantly better agreement on displacement of the greater tuberosity (κ = 0.35 compared with 0.30, p < 0.001) and on the AO classification (κ = 0.18 compared with 0.17, p = 0.018). A subgroup analysis of the AO classification results revealed that shoulder and elbow surgeons, orthopaedic trauma surgeons, and surgeons in the United States had slightly greater reliability on 2-D CT, whereas surgeons in practice for ten years or less and surgeons from other subspecialties had slightly greater reliability on 3-D CT. Proximal humeral fracture classifications may be helpful conceptually, but they have poor interobserver reliability even when 3-D rather than 2-D CT is utilized. This may contribute to the similarly poor interobserver reliability that was observed for selection of the treatment for proximal humeral fractures. The lack of a reliable classification confounds efforts to compare the outcomes of treatment methods among different clinical trials and reports.

Is there a link between motor performance variability and social-communicative impairment in children with ADHD-CT : a kinematic study using an upper limb Fitts’ aiming task

 Objective: This study investigated the relationship between motor performance and social-communicative impairment in children with ADHD-combined type (ADHD-CT). Method: An upper limb Fitts’ aiming task was used as a measure of motor performance and the Social Responsiveness Scale as a measure of social-communicative/autistic impairment in the following groups: ADHD-CT (n = 11) and typically developing (TD) controls (n = 10). Results: Children with ADHD-CT displayed greater variability in their movements, reflected in increased error variance over repeated aiming trials compared with TD controls. Motor performance variability was associated with social-communicative deficits in the ADHD-CT but not in the TD group. Conclusion: Social-communicative impairments further complicate the clinical picture of ADHD-CT; therefore, further research in this area is warranted to ascertain whether a particular pattern of motor disturbance in children with ADHD-CT may be clinically useful in identifying and assessing children with a more complex ADHD presentation. © 2012 SAGE Publications.

LNA aptamer based multi-modal, Fe3O4-saturated lactoferrin (Fe3O4-bLf) nanocarriers for triple positive (EpCAM, CD133, CD44) colon tumor targeting and NIR, MRI and CT imaging

This is the first ever attempt to combine anti-cancer therapeutic effects of emerging anticancer biodrug bovine lactoferrin (bLf), and multimodal imaging efficacy of Fe3O4 nanoparticles (NPs) together, as a saturated Fe3O4-bLf. For cancer stem cell specific uptake of nanocapsules/nanocarriers (NCs), Fe3O4-bLf was encapsulated in alginate enclosed chitosan coated calcium phosphate (AEC-CP) NCs targeted (Tar) with locked nucleic acid (LNA) modified aptamers against epithelial cell adhesion molecule (EpCAM) and nucleolin markers. The nanoformulation was fed orally to mice injected with triple positive (EpCAM, CD133, CD44) sorted colon cancer stem cells in the xenograft cancer stem cell mice model. The complete regression of tumor was observed in 70% of mice fed on non-targeted (NT) NCs, with 30% mice showing tumor recurrence after 30 days, while only 10% mice fed with Tar NCs showed tumor recurrence indicating a significantly higher survival rate. From tumor tissue analyses of 35 apoptotic markers, 55 angiogenesis markers, 40 cytokines, 15 stem cell markers and gene expression studies of important signaling molecules, it was revealed that the anti-cancer mechanism of Fe3O4-bLf was intervened through TRAIL, Fas, Fas-associated protein with death domain (FADD) mediated phosphorylation of p53, to induce activation of second mitochondria-derived activator of caspases (SMAC)/DIABLO (inhibiting survivin) and mitochondrial depolarization leading to release of cytochrome C. Induction of apoptosis was observed by inhibition of the Akt pathway and activation of cytokines released from monocytes/macrophages and dendritic cells (interleukin (IL) 27, keratinocyte chemoattractant (KC)). On the other hand, the recurrence of tumor in AEC-CP-Fe3O4-bLf NCs fed mice mainly occurred due to activation of alternative pathways such as mitogen-activated protein kinases (MAPK)/extracellular signal-regulated kinases (ERK) and Wnt signaling leading to an increase in expression of survivin, survivin splice variant (survivin 2B) and other anti-apoptotic proteins Bad, Bcl-2 and XIAP. Apart from the promising anti-cancer efficacy and the exceptional tumor targeting ability observed by multimodal imaging using near-infrared (NIR) imaging, magnetic resonance imaging (MRI) and computerized tomographic (CT) techniques, these NCs also maintained the immunomodulatory benefits of bLf as they were able to increase the RBC, hemoglobin, iron calcium and zinc levels in mice.

Fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images via a learning-based method

In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively.

A robust approach for automated lung segmentation in thoracic CT

Lung segmentation in thoracic computed tomography (CT) scans is an important preprocessing step for computer-aided diagnosis (CAD) of lung diseases. This paper focuses on the segmentation of the lung field in thoracic CT images. Traditional lung segmentation is based on Gray level thresholding techniques, which often requires setting a threshold and is sensitive to image contrasts. In this paper, we present a fully automated method for robust and accurate lung segmentation, which includes a enhanced thresholding algorithm and a refinement scheme based on a texture-aware active contour model. In our thresholding algorithm, a histogram based image stretch technique is performed in advance to uniformly increase contrasts between areas with low Hounsfield unit (HU) values and areas with high HU in all CT images. This stretch step enables the following threshold-free segmentation, which is the Otsu algorithm with contour analysis. However, as a threshold based segmentation, it has common issues such as holes, noises and inaccurate segmentation boundaries that will cause problems in future CAD for lung disease detection. To solve these problems, a refinement technique is proposed that captures vessel structures and lung boundaries and then smooths variations via texture-aware active contour model. Experiments on 2,342 diagnosis CT images demonstrate the effectiveness of the proposed method. Performance comparison with existing methods shows the advantages of our method.

Progressive computed tomography (CT) appearances preceding malignant spinal cord compression (MSCC) in men with castration-resistant prostate cancer

AIM: To test the hypothesis that computed tomography (CT)-based signs might precede symptomatic malignant spinal cord compression (MSCC) in men with metastatic castration-resistant prostate cancer (mCRPC). MATERIALS AND METHODS: A database was used to identify suitable mCRPC patients. Staging CT images were retrospectively reviewed for signs preceding MSCC. Signs of malignant paravertebral fat infiltration and epidural soft-tissue disease were defined and assessed on serial CT in 34 patients with MSCC and 58 control patients. The presence and evolution of the features were summarized using descriptive statistics. RESULTS: In MSCC patients, CT performed a median of 28 days prior to the diagnostic magnetic resonance imaging (MRI) demonstrated significant epidural soft tissue in 28 (80%) patients. The median time to MSCC from a combination of overt malignant paravertebral and epidural disease was 2.7 (0-14.6) months. Conversely, these signs were uncommon in the control cohort. CONCLUSIONS: Significant malignant paravertebral and/or epidural disease at CT precede MSCC in up to 80% of mCRPC patients and should prompt closer patient follow-up and consideration of early MRI evaluation. These CT-based features require further prospective validation.