The Relationship Between Sociosexuality and Aspects of Body Image in Men and Women: A Structural Equation Modeling Approach

The present study investigated the association between individual differences in sociosexual orientation and four aspects of body image in 156 male and 136 female students. While men were characterized by a less restricted sociosexual orientation, higher self-perceived physical attractiveness, and more pronounced self-rated physical assertiveness, women placed more emphasis on accentuation of body presentation. Structural equation modeling revealed significant positive relationships between sociosexual attitudes and physical attractiveness and accentuation of body presentation as well as between sociosexual behavior and physical attractiveness for the total sample. When introducing sex as a grouping variable, the attitudinal and behavioral components of sociosexuality were reliably related to both physical attractiveness and accentuation of body presentation as two aspects of body image in men, but not in women. Furthermore, our findings suggest that accentuation of body presentation represents a goal-directed behavior in men to increase the likelihood of having uncommitted sex but serves additional functions widely unrelated to unrestrictive sociosexual behavior in women.

Feasible Dose Reduction in Routine Chest Computed Tomography Maintaining Constant Image Quality Using the Last Three Scanner Generations: From Filtered Back Projection to Sinogram-affirmed Iterative Reconstruction and Impact of the Novel Fully Integrated Detector Design Minimizing Electronic Noise

OBJECTIVE The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT) by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP) and an iterative reconstruction (IR) algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany) was investigated. MATERIALS AND METHODS 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP), SOMATOM Definition Flash (IR), and SOMATOM Definition Edge (ICD and IR). Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. RESULTS Dose-length product (DLP) with FBP for the average chest CT was 308 mGy*cm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGy*cm ± 68.8 (P = 0.0001). Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGy*cm ± 54.5 (P = 0.033). The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR) was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048). Overall contrast-to-noise ratio (CNR) improved with declining DLP. CONCLUSION The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Statistical shape modeling of pathological scoliotic vertebrae: A comparative analysis

Statistical shape models (SSMs) have been used widely as a basis for segmenting and interpreting complex anatomical structures. The robustness of these models are sensitive to the registration procedures, i.e., establishment of a dense correspondence across a training data set. In this work, two SSMs based on the same training data set of scoliotic vertebrae, and registration procedures were compared. The first model was constructed based on the original binary masks without applying any image pre- and post-processing, and the second was obtained by means of a feature preserving smoothing method applied to the original training data set, followed by a standard rasterization algorithm. The accuracies of the correspondences were assessed quantitatively by means of the maximum of the mean minimum distance (MMMD) and Hausdorf distance (H(D)). Anatomical validity of the models were quantified by means of three different criteria, i.e., compactness, specificity, and model generalization ability. The objective of this study was to compare quasi-identical models based on standard metrics. Preliminary results suggest that the MMMD distance and eigenvalues are not sensitive metrics for evaluating the performance and robustness of SSMs.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Image quality in low-dose coronary computed tomography angiography with a new high-definition CT scanner

A new generation of high definition computed tomography (HDCT) 64-slice devices complemented by a new iterative image reconstruction algorithm-adaptive statistical iterative reconstruction, offer substantially higher resolution compared to standard definition CT (SDCT) scanners. As high resolution confers higher noise we have compared image quality and radiation dose of coronary computed tomography angiography (CCTA) from HDCT versus SDCT. Consecutive patients (n = 93) underwent HDCT, and were compared to 93 patients who had previously undergone CCTA with SDCT matched for heart rate (HR), HR variability and body mass index (BMI). Tube voltage and current were adapted to the patient's BMI, using identical protocols in both groups. The image quality of all CCTA scans was evaluated by two independent readers in all coronary segments using a 4-point scale (1, excellent image quality; 2, blurring of the vessel wall; 3, image with artefacts but evaluative; 4, non-evaluative). Effective radiation dose was calculated from DLP multiplied by a conversion factor (0.014 mSv/mGy × cm). The mean image quality score from HDCT versus SDCT was comparable (2.02 ± 0.68 vs. 2.00 ± 0.76). Mean effective radiation dose did not significantly differ between HDCT (1.7 ± 0.6 mSv, range 1.0-3.7 mSv) and SDCT (1.9 ± 0.8 mSv, range 0.8-5.5 mSv; P = n.s.). HDCT scanners allow low-dose 64-slice CCTA scanning with higher resolution than SDCT but maintained image quality and equally low radiation dose. Whether this will translate into higher accuracy of HDCT for CAD detection remains to be evaluated.

A survey of MRI-based medical image analysis for brain tumor studies

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

Effect of X-ray tube parameters, iodine concentration, and patient size on image quality in pulmonary computed tomography angiography: a chest-phantom-study

OBJECTIVES: The aim of this phantom study was to evaluate the contrast-to-noise ratio (CNR) in pulmonary computed tomography (CT)-angiography for 300 and 400 mg iodine/mL contrast media using variable x-ray tube parameters and patient sizes. We also analyzed the possible strategies of dose reduction in patients with different sizes. MATERIALS AND METHODS: The segmental pulmonary arteries were simulated by plastic tubes filled with 1:30 diluted solutions of 300 and 400 mg iodine/mL contrast media in a chest phantom mimicking thick, intermediate, and thin patients. Volume scanning was done with a CT scanner at 80, 100, 120, and 140 kVp. Tube current-time products (mAs) varied between 50 and 120% of the optimal value given by the built-in automatic dose optimization protocol. Attenuation values and CNR for both contrast media were evaluated and compared with the volume CT dose index (CTDI(vol)). Figure of merit, calculated as CNR/CTDIvol, was used to quantify image quality improvement per exposure risk to the patient. RESULTS: Attenuation of iodinated contrast media increased both with decreasing tube voltage and patient size. A CTDIvol reduction by 44% was achieved in the thin phantom with the use of 80 instead of 140 kVp without deterioration of CNR. Figure of merit correlated with kVp in the thin phantom (r = -0.897 to -0.999; P < 0.05) but not in the intermediate and thick phantoms (P = 0.09-0.71), reflecting a decreasing benefit of tube voltage reduction on image quality as the thickness of the phantom increased. Compared with the 300 mg iodine/mL concentration, the same CNR for 400 mg iodine/mL contrast medium was achieved at a lower CTDIvol by 18 to 40%, depending on phantom size and applied tube voltage. CONCLUSIONS: Low kVp protocols for pulmonary embolism are potentially advantageous especially in thin and, to a lesser extent, in intermediate patients. Thin patients profit from low voltage protocols preserving a good CNR at a lower exposure. The use of 80 kVp in obese patients may be problematic because of the limitation of the tube current available, reduced CNR, and high skin dose. The high CNR of the 400 mg iodine/mL contrast medium together with lower tube energy and/or current can be used for exposure reduction.

Evaluation of magnetic resonance colonography at 3.0 Tesla regarding diagnostic accuracy and image quality

OBJECTIVES: To assess magnetic resonance (MR)-colonography (MRC) for detection of colorectal lesions using two different T1w three-dimensional (3D)-gradient-recalled echo (GRE)-sequences and integrated parallel data acquisition (iPAT) at a 3.0 Tesla MR-unit. MATERIALS AND METHODS: In this prospective study, 34 symptomatic patients underwent dark lumen MRC at a 3.0 Tesla unit before conventional colonoscopy (CC). After colon distension with tap water, 2 high-resolution T1w 3D-GRE [3-dimensional fast low angle shot (3D-FLASH), iPAT factor 2 and 3D-volumetric interpolated breathhold examination (VIBE), iPAT 3] sequences were acquired without and after bolus injection of gadolinium. Prospective evaluation of MRC was performed. Image quality of the different sequences was assessed qualitatively and quantitatively. The findings of the same day CC served as standard of reference. RESULTS: MRC identified all polyps >5 mm (16 of 16) in size and all carcinomas (4 of 4) correctly. Fifty percent of the small polyps noise ratio (8 +/- 3.3 standard deviation (SD) in lesions without contrast enhancement (CE); 24.3 +/- 7.8 SD after CE). For the 3D-VIBE sequence, signal-to-noise ratio doubled in the detected lesions (147 +/- 54 SD without and 292 +/- 168 SD after CE). Although image quality was ranked lower in the VIBE, the image quality score of both sequences showed no statistical significant difference (chi > 0.6). CONCLUSIONS: MRC using 3D-GRE-sequences and iPAT is feasible at 3.0 T-systems. The high-resolution 3D-FLASH was slightly preferred over the 3D-VIBE because of better image quality, although both used sequences showed no statistical significant difference.

Patient exposure and image quality of low-dose pulmonary computed tomography angiography: comparison of 100- and 80-kVp protocols

OBJECTIVE: Measures to reduce radiation exposure and injected iodine mass are becoming more important with the widespread and often repetitive use of pulmonary CT angiography (CTA) in patients with suspected pulmonary embolism. In this retrospective study, we analyzed the capability of 2 low-kilovoltage CTA-protocols to achieve these goals. MATERIALS AND METHODS: Ninety patients weighing less than 100 kg were examined by a pulmonary CTA protocol using either 100 kVp (group A) or 80 kVp (group B). Volume and flow rate of contrast medium were reduced in group B (75 mL at 3 mL/s) compared with group A (100 mL at 4 mL/s). Attenuation was measured in the central and peripheral pulmonary arteries, and the contrast-to-noise ratios (CNR) were calculated. Entrance skin dose was estimated by measuring the surface dose in an ovoid-cylindrical polymethyl methacrylate chest phantom with 2 various dimensions corresponding to the range of chest diameters in our patients. Quantitative image parameters, estimated effective dose, and skin dose in both groups were compared by the t test. Arterial enhancement, noise, and overall quality were independently assessed by 3 radiologists, and results were compared between the groups using nonparametric tests. RESULTS: Mean attenuation in the pulmonary arteries in group B (427.6 +/- 116 HU) was significantly higher than in group A (342.1 +/- 87.7 HU; P < 0.001), whereas CNR showed no difference (group A, 20.6 +/- 7.3 and group B, 22.2 +/- 7.1; P = 0.302). Effective dose was lower by more than 40% with 80 kVp (1.68 +/- 0.23 mSv) compared with 100 kVp (2.87 +/- 0.88 mSv) (P < 0.001). Surface dose was significantly lower at 80 kVp compared with 100 kVp at both phantom dimensions (2.75 vs. 3.22 mGy; P = 0.027 and 2.22 vs. 2.73 mGy; P = 0.005, respectively). Image quality did not differ significantly between the groups (P = 0.151). CONCLUSIONS: Using 80 kVp in pulmonary CTA permits reduced patient exposure by 40% and CM volume by 25% compared with 100 kVp without deterioration of image quality in patients weighing less than 100 kg.

Is body weight the most appropriate criterion to select patients eligible for low-dose pulmonary CT angiography? Analysis of objective and subjective image quality at 80 kVp in 100 patients

The objective of this retrospective study was to assess image quality with pulmonary CT angiography (CTA) using 80 kVp and to find anthropomorphic parameters other than body weight (BW) to serve as selection criteria for low-dose CTA. Attenuation in the pulmonary arteries, anteroposterior and lateral diameters, cross-sectional area and soft-tissue thickness of the chest were measured in 100 consecutive patients weighing less than 100 kg with 80 kVp pulmonary CTA. Body surface area (BSA) and contrast-to-noise ratios (CNR) were calculated. Three radiologists analyzed arterial enhancement, noise, and image quality. Image parameters between patients grouped by BW (group 1: 0-50 kg; groups 2-6: 51-100 kg, decadally increasing) were compared. CNR was higher in patients weighing less than 60 kg than in the BW groups 71-99 kg (P between 0.025 and <0.001). Subjective ranking of enhancement (P = 0.165-0.605), noise (P = 0.063), and image quality (P = 0.079) did not differ significantly across all patient groups. CNR correlated moderately strongly with weight (R = -0.585), BSA (R = -0.582), cross-sectional area (R = -0.544), and anteroposterior diameter of the chest (R = -0.457; P < 0.001 all parameters). We conclude that 80 kVp pulmonary CTA permits diagnostic image quality in patients weighing up to 100 kg. Body weight is a suitable criterion to select patients for low-dose pulmonary CTA.

Weber fractions and time-order errors for long and short durations: Implications for modeling

Using a weighted up-down procedure, in each of eight conditions 28 participants compared durations of auditory (noise bursts) or visual (LED flashes) intervals; filled or unfilled with 3-ms markers; with or without feedback. Standards (Sts) were 100 and 1000 ms, and the ISI 900 ms. Intermixedly, presentation orders were St-Comparison (Co) and Co-St. TOEs were positive for St=100-ms and negative for St=1000 ms. Weber fractions (WFs, JND/St) were lowered by feedback. For visual-filled and visual-empty, WFs were highest for St=100 ms. For auditory-filled and visual-empty, St interacted with Order: lowest WFs occurred for St-Co with St=1000 ms, but for Co-St with St=100 ms. Lowest average WFs occurred with St-Co for visual-filled, but with Co-St for visual-empty. The results refute the generalization of better discrimination with St-Co than with Co-St (”type-B effect”), and support the notion of sensation weighting: flexibly differential impact weights of the compared durations in generating the response.

Modeling microblogging adoption in the enterprise

Despite a broad range of collaboration tools already available, enterprises continue to look for ways to improve internal and external communication. Microblogging is such a new communication channel with some considerable potential to improve intra-firm transparency and knowledge sharing. However, the adoption of such social software presents certain challenges to enterprises. Based on the results of four focus group sessions, we identified several new constructs to play an important role in the microblogging adoption decision. Examples include privacy concerns, communication benefits, perceptions regarding signal-to-noise ratio, as well codification effort. Integrating these findings with common views on technology acceptance, we formulate a model to predict the adoption of a microblogging system in the workspace. Our findings serve as an important guideline for managers seeking to realize the potential of microblogging in their company.

CT dose and image quality in the last three scanner generations.

AIM To compare the computed tomography (CT) dose and image quality with the filtered back projection against the iterative reconstruction and CT with a minimal electronic noise detector. METHODS A lung phantom (Chest Phantom N1 by Kyoto Kagaku) was scanned with 3 different CT scanners: the Somatom Sensation, the Definition Flash and the Definition Edge (all from Siemens, Erlangen, Germany). The scan parameters were identical to the Siemens presetting for THORAX ROUTINE (scan length 35 cm and FOV 33 cm). Nine different exposition levels were examined (reference mAs/peek voltage): 100/120, 100/100, 100/80, 50/120, 50/100, 50/80, 25/120, 25/100 and 25 mAs/80 kVp. Images from the SOMATOM Sensation were reconstructed using classic filtered back projection. Iterative reconstruction (SAFIRE, level 3) was performed for the two other scanners. A Stellar detector was used with the Somatom Definition Edge. The CT doses were represented by the dose length products (DLPs) (mGycm) provided by the scanners. Signal, contrast, noise and subjective image quality were recorded by two different radiologists with 10 and 3 years of experience in chest CT radiology. To determine the average dose reduction between two scanners, the integral of the dose difference was calculated from the lowest to the highest noise level. RESULTS When using iterative reconstruction (IR) instead of filtered back projection (FBP), the average dose reduction was 30%, 52% and 80% for bone, soft tissue and air, respectively, for the same image quality (P < 0.0001). The recently introduced Stellar detector (Sd) lowered the radiation dose by an additional 27%, 54% and 70% for bone, soft tissue and air, respectively (P < 0.0001). The benefit of dose reduction was larger at lower dose levels. With the same radiation dose, an average of 34% (22%-37%) and 25% (13%-46%) more contrast to noise was achieved by changing from FBP to IR and from IR to Sd, respectively. For the same contrast to noise level, an average of 59% (46%-71%) and 51% (38%-68%) dose reduction was produced for IR and Sd, respectively. For the same subjective image quality, the dose could be reduced by 25% (2%-42%) and 44% (33%-54%) using IR and Sd, respectively. CONCLUSION This study showed an average dose reduction between 27% and 70% for the new Stellar detector, which is equivalent to using IR instead of FBP.

Image Space Adaptive Rendering

In this thesis, we develop an adaptive framework for Monte Carlo rendering, and more specifically for Monte Carlo Path Tracing (MCPT) and its derivatives. MCPT is attractive because it can handle a wide variety of light transport effects, such as depth of field, motion blur, indirect illumination, participating media, and others, in an elegant and unified framework. However, MCPT is a sampling-based approach, and is only guaranteed to converge in the limit, as the sampling rate grows to infinity. At finite sampling rates, MCPT renderings are often plagued by noise artifacts that can be visually distracting. The adaptive framework developed in this thesis leverages two core strategies to address noise artifacts in renderings: adaptive sampling and adaptive reconstruction. Adaptive sampling consists in increasing the sampling rate on a per pixel basis, to ensure that each pixel value is below a predefined error threshold. Adaptive reconstruction leverages the available samples on a per pixel basis, in an attempt to have an optimal trade-off between minimizing the residual noise artifacts and preserving the edges in the image. In our framework, we greedily minimize the relative Mean Squared Error (rMSE) of the rendering by iterating over sampling and reconstruction steps. Given an initial set of samples, the reconstruction step aims at producing the rendering with the lowest rMSE on a per pixel basis, and the next sampling step then further reduces the rMSE by distributing additional samples according to the magnitude of the residual rMSE of the reconstruction. This iterative approach tightly couples the adaptive sampling and adaptive reconstruction strategies, by ensuring that we only sample densely regions of the image where adaptive reconstruction cannot properly resolve the noise. In a first implementation of our framework, we demonstrate the usefulness of our greedy error minimization using a simple reconstruction scheme leveraging a filterbank of isotropic Gaussian filters. In a second implementation, we integrate a powerful edge aware filter that can adapt to the anisotropy of the image. Finally, in a third implementation, we leverage auxiliary feature buffers that encode scene information (such as surface normals, position, or texture), to improve the robustness of the reconstruction in the presence of strong noise.