[Estimation of lung recruitment characteristics using the static pressure-volume curve of lungs].

Mechanical ventilation is an importmant life-sustaining treatment for patients with acute respiratory distress syndrome. Its clinical outcomes depend on patients' characteristics of lung recruitment. Estimation of lung recruitment characteristics is valuable for the determination of ventilatory maneurvers and ventilator parameters. There is no easily-used, bedside method to assess lung recruitment characteristics. The present paper proposed a method to estimate lung recruitment characteristics from the static pressure-volume curve of lungs. The method was evaluated by comparing with published experimental data. Results of lung recruitment derived from the presented method were in high agreement with the published data, suggesting that the proposed method is capable to estimate lung recruitment characteristics. Since some advanced ventilators are capable to measure the static pressure-volume curve automatedly, the presented method is potential to be used at bedside, and it is helpful for clinicians to individualize ventilatory manuevers and the correpsonding ventilator parameters.

[Simulation of spontaneous breathing for healthy adults using a nonlinear airway-segmented model of respiratory mechanics].

One-compartment lumped-parameter models of respiratory mechanics, representing the airflow resistance of the tracheobronchial tree with a linear or nonlinear resistor, are not able to describe the mechanical property of airways in different generations. Therefore, based on the anatomic structure of tracheobronchial tree and the mechanical property of airways in each generation, this study classified the human airways into three segments: the upper airway segment, the collapsible airway segment, and the small airway segment. Finally, a nonlinear, multi-compartment lumped-parameter model of respiratory mechanics with three airway segments was established. With the respiratory muscle effort as driving pressure, the model was used to simulate the tidal breathing of healthy adults. The results were consistent with the physiological data and the previously published results, suggesting that this model could be used for pathophysiological research of respiratory system.

Influence of the quality of intraoperative fluoroscopic images on the spatial positioning accuracy of a CAOS system.

BACKGROUND: Spatial positioning accuracy is a key issue in a computer-assisted orthopaedic surgery (CAOS) system. Since intraoperative fluoroscopic images are one of the most important input data to the CAOS system, the quality of these images should have a significant influence on the accuracy of the CAOS system. But the regularities and mechanism of the influence of the quality of intraoperative images on the accuracy of a CAOS system have yet to be studied. METHODS: Two typical spatial positioning methods - a C-arm calibration-based method and a bi-planar positioning method - are used to study the influence of different image quality parameters, such as resolution, distortion, contrast and signal-to-noise ratio, on positioning accuracy. The error propagation rules of image error in different spatial positioning methods are analyzed by the Monte Carlo method. RESULTS: Correlation analysis showed that resolution and distortion had a significant influence on spatial positioning accuracy. In addition the C-arm calibration-based method was more sensitive to image distortion, while the bi-planar positioning method was more susceptible to image resolution. The image contrast and signal-to-noise ratio have no significant influence on the spatial positioning accuracy. The result of Monte Carlo analysis proved that generally the bi-planar positioning method was more sensitive to image quality than the C-arm calibration-based method. CONCLUSIONS: The quality of intraoperative fluoroscopic images is a key issue in the spatial positioning accuracy of a CAOS system. Although the 2 typical positioning methods have very similar mathematical principles, they showed different sensitivities to different image quality parameters. The result of this research may help to create a realistic standard for intraoperative fluoroscopic images for CAOS systems.

Mechanical and physiological effect of partial pressure suit: Experiment and numerical study.

BACKGROUND: During high-altitude flight, the protection of the pilot is vital. A partial pressure suit may affect human physiology, especially circulatory physiology. OBJECTIVE: The purpose of this study was to investigate how a partial pressure suit works. METHOD: Ten subjects took part in the flight simulation experiments. Counter pressure at the chest, abdomen, thigh and shank were detected, together with physiological parameters such as heart rate (HR), mean arterial pressure (MAP), stroke volume (SV), cardiac output (CO) and total peripheral resistance (TPR). A numerical model was also established to simulate hemo-physiological effects of the partial pressure suit. RESULTS: The experiment's results show the non-uniform counter pressure distribution in different parts of the body. There is a linear, proportional relation between TPR and the pressurizing level. HR and MAP increase along with that of the pressure level. SV and CO decrease with the increase of the pressure level. The numerical model simulated the physiological effect of a partial pressure suit. The results were verified by experiment data. The simulation estimated the change of blood flow with the pressure level. CONCLUSIONS: The numerical model provides a potential way to improve the protection of pilots.

The development and error analysis of a kinematic parameters based spatial positioning method for an orthopedic navigation robot system.

BACKGROUND: Spatial positioning is the key function of a surgical navigation robot system, and accuracy is the most important performance index of such a system. METHODS: The kinematic parameters of a six degrees of freedom (DOF) robot arm were used to form the transformation from intraoperative fluoroscopy images to a robot's coordinate system without C-arm calibration and to solve the redundant DOF problem. The influences of three typical error sources and their combination on the final navigation error were investigated through Monte Carlo simulation. RESULTS: The navigation error of the proposed method is less than 0.6 mm, and the feasibility was verified through cadaver experiments. Error analysis suggests that the robot kinematic error has a linear relationship with final navigation error, while the image error and gauge error have nonlinear influences. CONCLUSIONS: This kinematic parameters based method can provide accurate and convenient navigation for orthopedic surgeries. The result of error analysis will help error design and assignment for surgical robots.

Noncontact full-angle fluorescence molecular tomography system based on rotary mirrors.

We propose a novel noncontact fluorescence molecular tomography system that achieves full-angle capacity with the use of a new rotary-mirrors-based imaging head. In the imaging head, four plane mirrors are mounted on a rotating gantry to enable illumination and detection over 360°. In comparison with existing full-angle systems, our system does not require rotation of the specimen animal, a large and heavy light source (with scanning head), or a bulky camera (with filters and lens). The system design and implementation are described in detail. Both physical phantom and in vivo experiments are performed to verify the performance of the proposed system.

[Morphological typing of the middle cerebral artery M1 segment by magnetic resonance angiography].

OBJECTIVE: To study the morphology of middle cerebral artery (MCA) M1 segment. METHODS: We selected the MRA data of 794 MCA (400 of the left side and 394 of the right side) from January 1, 2011 to June 30, 2011 consecutively and analyzed the morphology of the MCA M1 segment in axial, anteroposterior and lateral view, measured the length of the M1 segment, and analyzed the similarity of the left and right side M1 segment morphology. RESULTS: In axial, anteroposterior and lateral view, the MCA M1 segment showed C-shape > L-shape > S-shape. In axial view, it was about 373 (47%) M1 segment performance for the C-shape, of which 340 (42.8%) M1 segments showed bowing to the dorsal side, only 33 (4.2%) M1 segments showed bowing to the ventral side. In anteroposterior view, it was about 322 (40.6%) M1 segments of the performance of the C-shape, of which 262(33.0%) M1 segments showed a bowing to the superior, 60 (7.6%) showed bowing to the inferior. The similarity of the left and right MCA M1 segments was 27.2% (114/419) in axial view and 42.7% (179/419) in anteroposterior view. It was more similar in anteroposterior view than in axial view. Along with the increase of age, in the axial view, L-shape converted to C-shape very obviously, but only mildly elevated in S-shape. In anteroposterior view, the L-shape converted to the C-shape or S-shape along with the increase of age. CONCLUSION: The different morphology of MCA M1 segment in axial and anteroposterior view may be involved in the development of intracranial atherosclerosis.

The effect of tumor size on the imaging diagnosis: a study based on simulation.

Positron emission tomography (PET) has been widely used in early diagnosis of tumors. Though standardized uptake value (SUV) is a common diagnosis index for PET, it will be affected by the size of the tumor. To explore how the tumor size affects imaging diagnosis index, dynamic PET images were simulated to study the relationship between tumor size and the imaging diagnosis index. It was found that the SUV of the region of the tumor varied with scan time, and the SUV was always lower than the true value of tumor. Even more deviations were found in SUV with a reduced tumor size. The diagnosis index SUV(max) was more reliable than SUV, for it declined only when the volume of tumor was less than 3 mm(3). Therefore, the effect of tumor size on the SUV and SUV(max) that are used as diagnosis indices in the early diagnosis of tumors should not be neglected.

The three-dimensional shape analysis of the M1 segment of the middle cerebral artery using MRA at 3T.

INTRODUCTION: The M1 segment of the middle cerebral artery (MCA) is of great importance to neurosurgery and interventional radiology. The purpose of this study was to describe the M1 segment in three dimensions based on shape projection using magnetic resonance angiography (MRA). METHODS: A three-view method was established and used in the retrospective analysis of 717 M1 segments derived from 3D-TOF MRA images. In this method, the M1 segment was first projected on three orthogonal planes (axial, coronary, and sagittal plane); the courses of the projected vessels were classified as line-shape, C-shape, or S-shape on each orthogonal plane; and then the actual parameters, including internal diameter and so on, were measured on the projected images. The shape classifications and the measured parameters were efficient methods of describing the M1 segment. Twelve geometric models of the vessels were reconstructed and were compared with those from an actual validation method. RESULTS: The 3D shape of the M1 segment in the 3D orthogonal views was not uniform. Only 17.3 % M1 segments were straight, 43.5 % followed plane curves, and nearly 40 % were tortuous in 3D space. The probability distributions of shape classifications changed with age. The proportion of the tortuous vessels increased with age. We also showed that the three-view method is effective with a volume relative error of less than 13 %. CONCLUSION: The three-view method is convenient for describing the 3D morphology, including the shape information, of the M1 segment. It is a potential method for planning and predicting risk in neurosurgery/neurointervention.

High-performance fluorescence molecular tomography through shape-based reconstruction using spherical harmonics parameterization.

Fluorescence molecular tomography in the near-infrared region is becoming a powerful modality for mapping the three-dimensional quantitative distributions of fluorochromes in live small animals. However, wider application of fluorescence molecular tomography still requires more accurate and stable reconstruction tools. We propose a shape-based reconstruction method that uses spherical harmonics parameterization, where fluorophores are assumed to be distributed as piecewise constants inside disjointed subdomains and the remaining background. The inverse problem is then formulated as a constrained nonlinear least-squares problem with respect to shape parameters, which decreases ill-posedness because of the significantly reduced number of unknowns. Since different shape parameters contribute differently to the boundary measurements, a two-step and modified block coordinate descent optimization algorithm is introduced to stabilize the reconstruction. We first evaluated our method using numerical simulations under various conditions for the noise level and fluorescent background; it showed significant superiority over conventional voxel-based methods in terms of the spatial resolution, reconstruction accuracy with regard to the morphology and intensity, and robustness against the initial estimated distribution. In our phantom experiment, our method again showed better spatial resolution and more accurate intensity reconstruction. Finally, the results of an in vivo experiment demonstrated its applicability to the imaging of mice.

A study of the metabolism of transplanted tumor in the lung by micro PET/CT in mice.

The difference of tumor metabolism from that of normal tissue is an important factor for diagnosis through functional imaging such as positron emission tomography (PET). A quantitative description of the metabolic process will help to improve the diagnosis methods. In this study, the metabolism of tumor in lung was quantitatively described in mice. The melanoma was transplanted into the lung of mice, and the metabolism of the transplanted tumor was detected by micro PET/CT with [(18)F]fluoro-2-deoxy-D-glucose (FDG). Nine mice were transplanted with B16 melanoma cells through their tail vein. Lung tumor was detected by pathological method. The lesions smaller than 1mm could hardly be directly detected directly by micro PET/CT, while the tumor with a 1-4mm diameter could be detected by micro PET/CT. A metabolic model with three compartments was separately established for lung tumors and normal lung tissues. In this model, the lung cancer had a significantly higher metabolic rate constant as compared to that of the normal lung tissue (p=0.01). The outputs of the model fit well with the original curve from the dynamic images. It is also found that difference of tissue activity between tumors and normal lung tissues varied along scan time. Through this comparison, it was suggested that the difference in metabolism between the lung tissue and the tumor might contribute to the tumor diagnosis.

Fluorescence molecular tomography using a two-step three-dimensional shape-based reconstruction with graphics processing unit acceleration.

In fluorescence molecular tomography, the accurate and stable reconstruction of fluorescence-labeled targets remains a challenge for wide application of this imaging modality. Here we propose a two-step three-dimensional shape-based reconstruction method using graphics processing unit (GPU) acceleration. In this method, the fluorophore distribution is assumed as the sum of ellipsoids with piecewise-constant fluorescence intensities. The inverse problem is formulated as a constrained nonlinear least-squares problem with respect to shape parameters, leading to much less ill-posedness as the number of unknowns is greatly reduced. Considering that various shape parameters contribute differently to the boundary measurements, we use a two-step optimization algorithm to handle them in a distinctive way and also stabilize the reconstruction. Additionally, the GPU acceleration is employed for finite-element-method-based calculation of the objective function value and the Jacobian matrix, which reduces the total optimization time from around 10 min to less than 1 min. The numerical simulations show that our method can accurately reconstruct multiple targets of various shapes while the conventional voxel-based reconstruction cannot separate the nearby targets. Moreover, the two-step optimization can tolerate different initial values in the existence of noises, even when the number of targets is not known a priori. A physical phantom experiment further demonstrates the method's potential in practical applications.

Preparation and characterization of NiW-nHA composite catalyst for hydrocracking.

The synthesis, characterization and catalytic capability of the NiW-nano-hydroxyapatite (NiW-nHA) composite were investigated in this paper. The NiW-nHA catalyst was prepared by a co-precipitation method. Then Fourier transform infrared (FT-IR) spectroscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD) and energy dispersive spectroscopy (EDX) were used to analyze this material. In addition, the catalytic capacity of the NiW-nHA composite was also examined by FT-IR and gas chromatography (GC). The results of FT-IR analysis indicated that Ni, W and nHA combined closely. TEM observation revealed that this catalyst was needle shaped and the crystal retained a nanometer size. XRD data also suggested that a new phase of CaWO(4) appeared and the lattice parameters of nHA changed in this system. nHA was the carrier of metals. The rates of Ni/W-loading were 73.24% and 65.99% according to the EDX data, respectively. Furthermore, the conversion of 91.88% Jatropha oil was achieved at 360 °C and 3 MPa h(-1) over NiW-nHA catalyst. The straight chain alkanes ranging from C(15) to C(18) were the main components in the production. The yield of C(15)-C(18) alkanes was up to 83.56 wt%. The reaction pathway involved hydrocracking of the C═C bonds of these triglycerides from Jatropha oil. This paper developed a novel non-sulfided catalyst to obtain a "green biofuel" from vegetable oil.

Modeling the excretion of FDG in human kidneys using dynamic PET.

In order to understand the excretion function of kidneys, dynamic scan was performed using the positron emission tomography (PET), the process of FDG's (2-[(18)F]fluoro-2-deoxy-D-glucose) excretion was detected, and the kidney model was established. The model in this study consisted of two parts: the fore part of the model described the transportation of FDG from plasma and the accumulation of FDG in kidney, and the latter part of the model described the transportation of FDG from kidney to ureter and then to bladder. Since there was a time delay between the fore part and the later part, which occurred when FDG was filtered into urine and accumulated in pelvis temporarily, a new parameter, delay constant t(0), was introduced in the model. Twelve healthy adult volunteers took part in the dynamic FDG-PET experiment. Ten subjects received dynamic scan on kidneys, and the data extracted from the PET scans were used for parameter estimation and model analysis. The other two subjects received dynamic scan on bladder in order to confirm the time delay constant. The output of the model fit well with the original curve, and the model built in this study could not only describe the excretion process of FDG, but also be used to quantitatively estimate urinary excretion of FDG and plasma clearance. Moreover, the model kept good accordance with physiological characteristics.

Kidney modelling for FDG excretion with PET.

The purpose of this study was to detect the physiological process of FDG's filtration from blood to urine and to establish a mathematical model to describe the process. Dynamic positron emission tomography scan for FDG was performed on seven normal volunteers. The filtration process in kidney can be seen in the sequential images of each study. Variational distribution of FDG in kidney can be detected in dynamic data. According to the structure and function, kidney is divided into parenchyma and pelvis. A unidirectional three-compartment model is proposed to describe the renal function in FDG excretion. The time-activity curves that were picked up from the parenchyma, pelvis, and abdominal aorta were used to estimate the parameter of the model. The output of the model has fitted well with the original curve from dynamic data.