The purpose of this study is to investigate how the imposition of personalized, non-invasively measured blood flow rates as boundary conditions (BCs) influences image-based computational hemodynamic studies in the human aorta. We extracted from 4D phase-contrast MRI acquisitions of a healthy human (1) the geometry of the thoracic aorta with supra-aortic arteries and (2) flow rate waveforms at all boundaries. Flow simulations were carried out, and the implications that the imposition of different BC schemes based on the measured flow rates have on wall shear stress (WSS)-based indicators of abnormal flow were analyzed. Our results show that both the flow rate repartition among the multiple outlets of the aorta and the distribution and magnitude of the WSS-based indicators are strongly influenced by the adopted BC strategy. Keeping as reference hemodynamic model the one where the applied BC scheme allowed to obtain a satisfactory agreement between the computed and the measured flow rate waveforms, differences in WSS-based indicators up to 49% were observed when the other BC strategies were applied. In conclusion, we demonstrate that in subject-specific computational hemodynamics models of the human aorta the imposition of BC settings based on non-invasively measured flow rate waveforms influences indicators of abnormal flow to a large extent. Hence, a BCs set-up assuring realistic, subject-specific instantaneous flow rate distribution must be applied when BCs such as flow rates are prescribed.

Starting from these differences in the structural descriptors, our study sustains the presence of a compensatory mechanism in osteoarthritis to preserve the mechanical competence of bone structure, despite the loss of trabecular bone, underlying lower fracture risk.

The structure of skeletal muscle (SM) can be characterized by quantitative (size) and qualitative (composition) attributes, which are disparately reported to be influenced by body adiposity. This study tests the hypothesis that body adiposity exerts a systematic influence on these muscle characteristics and evaluates the possible functional implications for movements. Lower limb SM volume (VSM) and attenuation (ATTSM), an inverse measure of lipid infiltration in muscle, were determined with computed tomography in 21 men (BMI = 21-36 kg m(-2) ; age = 31-71 years.) and 18 women (BMI = 19-35 kg m(-2) ; age = 32-76 years.). After adjusting for age, a multivariate regression analysis revealed that body adiposity positively correlated (P<0·05-0·001) with absolute VSM and cross-sectional area (CSA) in both genders, while VSM per unit body mass (VSM/BM) decreased with adiposity (P<0·001) in women and was constant in men. ATTSM was higher in men (P<0·05) and decreased (P<0·05) with adiposity in both genders. The product of ATTSM by average muscle CSA (predictor of maximal strength) and by VSM/BM (predictor of maximal dynamic performance) was lower in women (P<0·001) and was reduced by age in both genders (P<0·05-0·01), while obesity had a negative effect (P<0·001) only on the predictor of performance. In conclusion, body adiposity significantly increases SM size and reduces ATTSM. Structural indicators accounting for both quantitative and qualitative characteristics of SM may be useful predictors of the effects of obesity on motor function at different ages. With rising body adiposity and advancing age, women appear mostly affected by the decline of SM features relevant for motor performance.

Our method was found effective on PCMRI data to provide a 3D geometric model of the TA, to support morphometric and hemodynamic characterization of the aorta.

This paper presents the evaluation of the accuracy of an elastic registration algorithm, based on the particle filter and an optical flow process. The algorithm is applied in brain CT and MRI simulated image datasets, and MRI images from a real clinical radiotherapy case. To validate registration accuracy, standard indices for registration accuracy assessment were calculated: the dice similarity coefficient (DICE), the average symmetric distance (ASD) and the maximal distance between pixels (Dmax). The results showed that this registration process has good accuracy, both qualitatively and quantitatively, suggesting that this method may be considered as a good new option for radiotherapy applications like patient's follow up treatment.

We developed an automatic method for regional analysis of femoral neck images acquired by peripheral quantitative computed tomography (pQCT), based on automatic spatial re-alignment and segmentation; the segmentation method, based on a morphological approach, explicitly accounts for the presence of three different bone compartments: cortical region, trabecular region, and transition zone between cortical and trabecular compartments. The proposed method was applied on 13 femoral neck sections derived from female donors who were undergoing hip replacement surgery for primary degenerative arthritis or fracture, and a typical densitometric and structural analysis was performed both globally and regionally. The proposed segmentation method was quantitatively evaluated by comparing automatic contour and the corresponding manual contours delineated by three operators using metrics based on surface distance (average symmetric distance, ASD) and volumetric overlapping (dice similarity coefficient, DSC). The same approach was used to validate the automatic spatial orientation, considering as metric the difference between manual and automatic angle orientation. Results confirm a satisfactory agreement between automatic and manual performances (ASD < 0.41 mm, DSC > 0.91, orientation difference = 3.61°) and show that globally our algorithm performs very well. Concerning regional analysis application, from our results we can observe that significant differences are present among the four bone quadrants.

The anisotropic diffusion filter approach can be considered effective in improving the visualization and analysis of the thoracic aorta hemodynamics from phase-contrast MRI sensitivity encoding images.

Peripheral Quantitative Computerized Tomography (pQCT) allows the acquisition of bone specimens with a spatial resolution adequate to visualize the 3D structure of the bone cortex and the trabecular network. At present, pQCT scanners are equipped with image processing software that limits the bone analysis in two dimensions and requires strong user interaction. In this work, a method is proposed to automatically segment, in 3D, cortical and trabecular components of bone specimens acquired by pQCT, in order to facilitate and enhance the quantitative evaluation of densitometric properties of the bone.