[Advances in the application of dynamic virtual patients in prosthodontics]

With the development and application of technologies such as facial scanning, intraoral scanning, virtual facebow and mandibular movement tracking in prosthodontics, dynamic virtual patients are gradually applied to preoperative analysis, esthetic diagnosis, treatment planning, and restorative implementation, becoming a research hotspot in recent years. This review focuses on data acquisition, construction of dynamic virtual patients and their application advantages, aiming to provide a reference for the clinical application of related digital technologies.

Contrast-Enhanced Spectral Mammography-Based Prediction of Non-Sentinel Lymph Node Metastasis and Axillary Tumor Burden in Patients With Breast Cancer

Purpose

To establish and evaluate non-invasive models for estimating the risk of non-sentinel lymph node (NSLN) metastasis and axillary tumor burden among breast cancer patients with 1–2 positive sentinel lymph nodes (SLNs).

Materials and Methods

Breast cancer patients with 1–2 positive SLNs who underwent axillary lymph node dissection (ALND) and contrast-enhanced spectral mammography (CESM) examination were enrolled between 2018 and 2021. CESM-based radiomics and deep learning features of tumors were extracted. The correlation analysis, least absolute shrinkage and selection operator (LASSO), and analysis of variance (ANOVA) were used for further feature selection. Models based on the selected features and clinical risk factors were constructed with multivariate logistic regression. Finally, two radiomics nomograms were proposed for predicting NSLN metastasis and the probability of high axillary tumor burden.

Results

A total of 182 patients [53.13 years ± 10.03 (standard deviation)] were included. For predicting the NSLN metastasis status, the radiomics nomogram built by 5 selected radiomics features and 3 clinical risk factors including the number of positive SLNs, ratio of positive SLNs, and lymphovascular invasion (LVI), achieved the area under the receiver operating characteristic curve (AUC) of 0.85 [95% confidence interval (CI): 0.71–0.99] in the testing set and 0.82 (95% CI: 0.67–0.97) in the temporal validation cohort. For predicting the high axillary tumor burden, the AUC values of the developed radiomics nomogram are 0.82 (95% CI: 0.66–0.97) in the testing set and 0.77 (95% CI: 0.62–0.93) in the temporal validation cohort.

Discussion

CESM images contain useful information for predicting NSLN metastasis and axillary tumor burden of breast cancer patients. Radiomics can inspire the potential of CESM images to identify lymph node metastasis and improve predictive performance.

Research Progress of Gliomas in Machine Learning

In the field of gliomas research, the broad availability of genetic and image information originated by computer technologies and the booming of biomedical publications has led to the advent of the big-data era. Machine learning methods were applied as possible approaches to speed up the data mining processes. In this article, we reviewed the present situation and future orientations of machine learning application in gliomas within the context of workflows to integrate analysis for precision cancer care. Publicly available tools or algorithms for key machine learning technologies in the literature mining for glioma clinical research were reviewed and compared. Further, the existing solutions of machine learning methods and their limitations in glioma prediction and diagnostics, such as overfitting and class imbalanced, were critically analyzed.

Identification of WHO II/III gliomas by 16 prognostic-related gene signatures using machine learning methods

BACKGROUND

It is found that the prognosis of gliomas of the same grade has large differences among World Health Organization(WHO) grade II and III in clinical observation. Therefore, a better understanding of the genetics and molecular mechanisms underlying WHO grade II and III gliomas is required, with the aim of developing a classification scheme at the molecular level rather than the conventional pathological morphology level.

METHOD

We performed survival analysis combined with machine learning methods of Least Absolute Shrinkage and Selection Operator using expression datasets downloaded from the Chinese Glioma Genome Atlas as well as The Cancer Genome Atlas. Risk scores were calculated by the product of expression level of overall survival-related genes and their multivariate Cox proportional hazards regression coefficients. WHO grade II and III gliomas were categorized into the low-risk subgroup, medium-risk subgroup, and high-risk subgroup. We used the 16 prognostic-related genes as input features to build a classification model based on prognosis using a fully connected neural network. Gene function annotations were also performed.

RESULTS

The 16 genes (AKNAD1, C7orf13, CDK20, CHRFAM7A, CHRNA1, EFNB1, GAS1, HIST2H2BE, KCNK3, KLHL4, LRRK2, NXPH3, PIGZ, SAMD5, ERINC2, and SIX6) related to the glioma prognosis were screened. The 16 selected genes were associated with the development of gliomas and carcinogenesis. The accuracy of an external validation data set of the fully connected neural network model from the two cohorts reached 95.5%. Our method has good potential capability in classifying WHO grade II and III gliomas into low-risk, medium-risk, and high-risk subgroups. The subgroups showed significant (P<0.01) differences in overall survival.

CONCLUSION

This resulted in the identification of 16 genes that were related to the prognosis of gliomas. Here we developed a computational method to discriminate WHO grade II and III gliomas into three subgroups with distinct prognoses. The gene expression-based method provides a reliable alternative to determine the prognosis of gliomas.

A potential field segmentation based method for tumor segmentation on multi-parametric MRI of glioma cancer patients

Background

Accurate segmentation of brain tumors is vital for the gross tumor volume (GTV) definition in radiotherapy. Functional MR images like apparent diffusion constant (ADC) and fractional anisotropy (FA) images can provide more comprehensive information for sensitive detection of the GTV. We synthesize anatomical and functional MRI for accurate and semi-automatic segmentation of GTVs and improvement of clinical efficiency.

Methods

Four MR image sets including T1-weighted contrast-enhanced (T1C), T2-weighted (T2), apparent diffusion constant (ADC) and fractional anisotropy (FA) images of 5 glioma patients were acquired and registered. A new potential field segmentation (PFS) method was proposed based on the concept of potential field in physics. For T1C, T2 and ADC images, global potential field segmentation (global-PFS) was used on user defined region of interest (ROI) for rough segmentation and then morphologically processed for accurate delineation of the GTV. For FA images, white matter (WM) was removed using local potential field segmentation (local-PFS), and then tumor extent was delineated with region growing and morphological methods. The individual segmentations of multi-parametric images were ensembled into a fused segmentation, considered as final GTV. GTVs were compared with manually delineated ground truth and evaluated with segmentation quality measure (Q), Dice’s similarity coefficient (DSC) and Sensitivity and Specificity.

Results

Experimental study with the five patients’ data and new method showed that, the mean values of Q, DSC, Sensitivity and Specificity were 0.80 (±0.07), 0.88 (±0.04), 0.92 (±0.01) and 0.88 (±0.05) respectively. The global-PFS used on ROIs of T1C, T2 and ADC images can avoid interferences from skull and other non-tumor areas. Similarity to local-PFS on FA images, it can also reduce the time complexity as compared with the global-PFS on whole image sets.

Conclusions

Efficient and semi-automatic segmentation of the GTV can be achieved with the new method. Combination of anatomical and functional MR images has the potential to provide new methods and ideas for target definition in radiotherapy.

Hydrogen Peroxide Might Bleach Natural Dentin by Oxidizing Phosphoprotein

Recent studies suggested that bleaching agents may whiten teeth by oxidizing the fluorescent materials, which are the proteins located in the organic-inorganic interface. Therefore, we postulated that fluorescence of dentin came from dentin phosphoprotein (DPP) and that bleaching agents might bleach dentin by oxidizing DPP. Fifty-six specimens were randomly divided into 4 groups and exposed to distilled water, hydrogen peroxide (HP), ethylenediamine tetraacetic acid disodium salt (EDTA), and acetic acid for 24 h. After measuring the organic and inorganic components, fluorescence, and color characteristics of dentin before and after exposure, we found that when DPP was removed from dentin by EDTA, fluorescent intensity declined proportionally with the reduction in Raman relative intensity, and dentin was whitened considerably, with an Δ E value 6 times higher than that of the distilled water group. On the contrary, due to the incapability of acetic acid to dissolve DPP during decalcification, fluorescent intensity values and tooth color remained nearly unchanged after exposure to acetic acid. Dentin exposed to neutral HP showed no obvious morphologic and organic/inorganic component changes except for the destruction of DPP. Similarly, dramatically decreased fluorescent intensity and lightened color were found in the HP group. Moreover, DPP solution of the HP group exhibited decreased ultraviolet absorbance, especially between 250 and 300 nm, which arose from aromatic amino acids. The results indicated that DPP was responsible for the fluorescent properties of dentin and that HP might bleach dentin by the oxidization of aromatic amino acids in DPP. These findings are of great significance in promoting our further understanding of the mechanism of tooth bleaching and the fluorescent property of normal dentin.

New Insights into Effects of Aromatic Amino Acids on Hydroxyapatite

Biomimetics inspired by superstructures and extraordinary properties of teeth have resulted in tooth repair and the generation of novel materials. However, little attention has been paid to tooth color, whose origin remains unknown. Based on recent studies, fluorophores-mainly aromatic amino acids (AAAs) in proteins-might be responsible for tooth color. We synthesized carbonated hydroxyapatite (HA; the mineral phase of teeth) in the presence of different amino acids (AAs; the basic units of protein matrix of teeth) as a simplified model of teeth to explore the color source at the AA level. After measuring the fluorescence and color characteristics of HA-AAs before and after bleaching treatment, we found that only HA, synthesized in the presence of AAAs, exhibited remarkable fluorescence and color property. Furthermore, linearly increased fluorescence intensity and deeper color were observed with an increase in AAA content in HA-AAAs. Similarly, significantly decreased absorbance of HA-AAAs between 250 and 300 nm in ultraviolet spectra, declined fluorescence intensity, and decolored performance of HA-AAAs were observed after bleaching treatment. The results showed that AAAs contributed to the fluorescence and color properties of HA and that hydrogen peroxide might whiten HA-AAAs by oxidizing the benzene ring in AAAs. These findings are of great significance in promoting the synthesis of advanced tooth-colored materials and furthering our understanding of the possible mechanisms of hydrogen peroxide. Moreover, our study shed light on the importance of AAAs and might provide new ideas for investigations of biomineralization and biomimetics.

A novel automatic quantification method for high-content screening analysis of DNA double strand-break response

High-content screening is commonly used in studies of the DNA damage response. The double-strand break (DSB) is one of the most harmful types of DNA damage lesions. The conventional method used to quantify DSBs is γH2AX foci counting, which requires manual adjustment and preset parameters and is usually regarded as imprecise, time-consuming, poorly reproducible, and inaccurate. Therefore, a robust automatic alternative method is highly desired. In this manuscript, we present a new method for quantifying DSBs which involves automatic image cropping, automatic foci-segmentation and fluorescent intensity measurement. Furthermore, an additional function was added for standardizing the measurement of DSB response inhibition based on co-localization analysis. We tested the method with a well-known inhibitor of DSB response. The new method requires only one preset parameter, which effectively minimizes operator-dependent variations. Compared with conventional methods, the new method detected a higher percentage difference of foci formation between different cells, which can improve measurement accuracy. The effects of the inhibitor on DSB response were successfully quantified with the new method (p = 0.000). The advantages of this method in terms of reliability, automation and simplicity show its potential in quantitative fluorescence imaging studies and high-content screening for compounds and factors involved in DSB response.

Comparison of contourlet transform and gray level co-occurrence matrix for analyzing cell-scattered patterns

Distribution of scattered image patterns hinges on morphological and optical characteristics of cells. This paper applied a numerical method to simulate scattered images of real cell morphologies, which were reconstructed from confocal image stacks dyed by fluorescent stains. Two approaches, contourlet transform (CT) and gray level co-occurrence matrix (GLCM), were then used to analyze the simulated scattered images. The results showed that features extracted using GLCM contained more information than those extracted using CT. Higher classification accuracy could be achieved with a single GLCM parameter than CT and GLCM could achieve higher accuracy with fewer parameters than CT when using multiple parameters. Meanwhile, GLCM requires less computational cost. Thus, GLCM is more suitable and efficient than CT for the analysis of cell-scattered images.

Comparison study of distinguishing cancerous and normal prostate epithelial cells by confocal and polarization diffraction imaging

Accurate classification of malignant cells from benign ones can significantly enhance cancer diagnosis and prognosis by detection of circulating tumor cells (CTCs). We have investigated two approaches of quantitative morphology and polarization diffraction imaging on two prostate cell types to evaluate their feasibility as single-cell assay methods toward CTC detection after cell enrichment. The two cell types have been measured by a confocal imaging method to obtain their three-dimensional morphology parameters and by a polarization diffraction imaging flow cytometry (p-DIFC) method to obtain image texture parameters. The support vector machine algorithm was applied to examine the accuracy of cell classification with the morphology and diffraction image parameters. Despite larger mean values of cell and nuclear sizes of the cancerous prostate cells than the normal ones, it has been shown that the morphologic parameters cannot serve as effective classifiers. In contrast, accurate classification of the two prostate cell types can be achieved with high classification accuracies on measured data acquired separately in three measurements. These results provide strong evidence that the p-DIFC method has the potential to yield morphology-related “fingerprints” for accurate and label-free classification of the two prostate cell types.

Original Research: Label-free detection for radiation-induced apoptosis in glioblastoma cells

Current flow cytometry (FCM) requires fluorescent dyes labeling cells which make the procedure costly and time consuming. This manuscript reports a feasibility study of detecting the cell apoptosis with a label-free method in glioblastoma cells. A human glioma cell line M059K was exposed to 8 Gy dose of radiation, which enables the cells to undergo radiation-induced apoptosis. The rates of apoptosis were studied at different time points post-irradiation with two different methods: FCM in combination with Annexin V-FITC/PI staining and a newly developed technique named polarization diffraction imaging flow cytometry. Totally 1000 diffraction images were acquired for each sample and the gray level co-occurrence matrix (GLCM) algorithm was used in morphological characterization of the apoptotic cells. Among the feature parameters extracted from each image pair, we found that the two GLCM parameters of angular second moment (ASM) and sum entropy (SumEnt) exhibit high sensitivities and consistencies as the apoptotic rates (Pa) measured with FCM method. In addition, no significant difference exists between Pa and ASM_S, Pa and SumEnt_S, respectively (P > 0.05). These results demonstrated that the new label-free method can detect cell apoptosis effectively. Cells can be directly used in the subsequent biochemical experiments as the structure and function of cells and biomolecules are well-preserved with this new method.

Spectrophotometric determination of turbid optical parameters without using an integrating sphere

Spectrophotometric quantification of turbidity by multiple optical parameters has wide-ranging applications in material analysis and life sciences. A robust system design needs to combine hardware for precise measurement of light signals with software to accurately model measurement configuration and rapidly solve a sequence of challenging inverse problems. We have developed and validated a design approach and performed system validation based on radiative transfer theory for determination of absorption coefficient, scattering coefficient, and anisotropy factor without using an integrating sphere. Accurate and rapid determination of parameters and spectra is achieved for microsphere suspension samples by combining photodiode-based measurement of four signals with the Monte Carlo simulation and perturbation-based inverse calculations. The three parameters of microsphere suspension samples have been determined from the measured signals as functions of wavelength from 400 to 800 nm and agree with calculated results based on the Mie theory. It has been shown that the inverse problems in the cases of microsphere suspension samples are well posed with convex cost functions to yield unique solutions, and it takes about 1 min to obtain the three parameters per wavelength.

A new assessment model for tumor heterogeneity analysis with [18]F-FDG PET images

It has been shown that the intratumor heterogeneity can be characterized with quantitative analysis of the [18]F-FDG PET image data. The existing models employ multiple parameters for feature extraction which makes it difficult to implement in clinical settings for the quantitative characterization. This article reports an easy-to-use and differential SUV based model for quantitative assessment of the intratumor heterogeneity from 3D [18]F-FDG PET image data. An H index is defined to assess tumor heterogeneity by summing voxel-wise distribution of differential SUV from the [18]F-FDG PET image data. The summation is weighted by the distance of SUV difference among neighboring voxels from the center of the tumor and can thus yield increased values for tumors with peripheral sub-regions of high SUV that often serves as an indicator of augmented malignancy. Furthermore, the sign of H index is used to differentiate the rate of change for volume averaged SUV from its center to periphery. The new model with the H index has been compared with a widely-used model of gray level co-occurrence matrix (GLCM) for image texture characterization with phantoms of different configurations and the [18]F-FDG PET image data of 6 lung cancer patients to evaluate its effectiveness and feasibility for clinical uses. The comparison of the H index and GLCM parameters with the phantoms demonstrate that the H index can characterize the SUV heterogeneity in all of 6 2D phantoms while only 1 GLCM parameter can do for 1 and fail to differentiate for other 2D phantoms. For the 8 3D phantoms, the H index can clearly differentiate all of them while the 4 GLCM parameters provide complicated patterns in the characterization. Feasibility study with the PET image data from 6 lung cancer patients show that the H index provides an effective single-parameter metric to characterize tumor heterogeneity in terms of the local SUV variation, and it has higher correlation with tumor volume change after radiotherapy (R(2) = 0.83) than the 4 GLCM parameters (R(2) = 0.63, 0.73, 0.59 and 0.75 for Energy, Contrast, Local Homogeneity and Entropy respectively). The new model of the H index has the capacity to characterize the intratumor heterogeneity feature from 3D [18]F-FDG PET image data. As a single parameter with an intuitive definition, the H index offers potential for clinical applications.

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus

Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging.

Acquisition of cross-polarized diffraction images and study of blurring effect by one time-delay-integration camera

Blurred diffraction images acquired from flowing particles affect the measurement of fringe patterns and subsequent analysis. An imaging unit with one time-delay-integration (TDI) camera has been developed to acquire two cross-polarized diffraction images. It was shown that selected elements of Mueller matrix of single scatters can be imaged with pixel matching precision in this configuration. With the TDI camera, the effect of blurring on imaging of scattered light propagating along the side directions was found to be much more significant for biological cells than microspheres. Despite blurring, classification of MCF-7 and K562 cells is feasible since the effect has similar influence on extracted image parameters. Furthermore, image blurring can be useful for analysis of the correlations among texture parameters for characterization of diffraction images from single cells. The results demonstrate that with one TDI camera the polarization diffraction imaging flow cytometry can be significantly improved and angular distribution of selected Mueller matrix elements can be accurately measured for rapid and morphology-based assay of particles and cells without fluorescent labeling.

Analysis of diffraction imaging in non-conjugate configurations

Diffraction imaging of scattered light allows extraction of information on scatterer's morphology. We present a method for accurate simulation of diffraction imaging of single particles by combining rigorous light scattering model with ray-tracing software. The new method has been validated by comparison to measured images of single microspheres. Dependence of fringe patterns on translation of an objective based imager to off-focus positions has been analyzed to clearly understand diffraction imaging with multiple optical elements. The calculated and measured results establish unambiguously that diffraction imaging should be pursued in non-conjugate configurations to ensure accurate sampling of coherent light distribution from the scatterer.

A quantitative method for measurement of HL-60 cell apoptosis based on diffraction imaging flow cytometry technique

A quantitative method for measurement of apoptosis in HL-60 cells based on polarization diffraction imaging flow cytometry technique is presented in this paper. Through comparative study with existing methods and the analysis of diffraction images by a gray level co-occurrence matrix algorithm (GLCM), we found 4 GLCM parameters of contrast (CON), cluster shade (CLS), correlation (COR) and dissimilarity (DIS) exhibit high sensitivities as the apoptotic rates. It was further demonstrated that the CLS parameter correlates significantly (R(2) = 0.899) with the degree of nuclear fragmentation and other three parameters showed a very good correlations (R(2) ranges from 0.69 to 0.90). These results demonstrated that the new method has the capability for rapid and accurate extraction of morphological features to quantify cellular apoptosis without the need for cell staining.

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Automatic quantitative analysis of morphology of apoptotic HL-60 cells

Morphological identification is a widespread procedure to assess the presence of apoptosis by visual inspection of the morphological characteristics or the fluorescence images. The procedure is lengthy and results are observer dependent. A quantitative automatic analysis is objective and would greatly help the routine work. We developed an image processing and segmentation method which combined the Otsu thresholding and morphological operators for apoptosis study. An automatic determination method of apoptotic stages of HL-60 cells with fluorescence images was developed. Comparison was made between normal cells, early apoptotic cells and late apoptotic cells about their geometric parameters which were defined to describe the features of cell morphology. The results demonstrated that the parameters we chose are very representative of the morphological characteristics of apoptotic cells. Significant differences exist between the cells in different stages, and automatic quantification of the differences can be achieved.

Analysis of cellular objects through diffraction images acquired by flow cytometry

It was found that the diffraction images acquired along the side scattering directions with objects in a cell sample contain pattern variations at both the global and local scales. We show here that the global pattern variation is associated with the categorical size and morphological heterogeneity of the imaged objects. An automated image processing method has been developed to separate the acquired diffraction images into three types of global patterns. Combined with previously developed method for quantifying local texture pattern variations, the new method allows fully automated analysis of diffraction images for rapid and label-free classification of cells according to their 3D morphology.

Minimally invasive treatment for esthetic management of severe dental fluorosis: a case report

Dental fluorosis is a developmental disturbance of enamel caused by excessive fluoride on ameloblasts during enamel formation. Patients often present to the dentist with a main goal of improving their esthetic appearance. This case report describes a minimally invasive technique for treating a severe case of enamel fluorosis with brown surface aspect and small defects. A selective mega-abrasion and microabrasion were used to recreate macro- and micro- surface morphology, followed by power bleaching, home bleaching, and resin infiltration to improve the esthetic appearance.

Effects of two in-office bleaching agents with different pH on the structure of human enamel: an in situ and in vitro study

This study evaluated the effects of two in-office bleaching agents (Beyond and Opalescence Boost) with different pH on the structure and mechanical properties of human enamel in vitro and in situ. One hundred and eight enamel slabs were obtained from freshly extracted premolars. The specimens were randomly distributed into nine groups (n=12), and the human saliva (HS) in the volunteers' oral cavities was used to simulate the in situ condition: Beyond + HS, Opalescence Boost (O-Boost) + HS, Control + HS, Beyond + artificial saliva (AS), O-Boost + AS, Control + AS, Beyond + distilled water (DW), O-Boost + DW, and Control + DW. The bleaching treatments were performed on the first and eighth day, and the total bleaching time was 90 minutes. Baseline and final surface roughness (RMS), surface morphology, microhardness, and fracture toughness (FT) were measured before the treatment and on the fifteenth day, respectively. Compared with control groups, surface alterations on enamel were found in the Beyond + AS and Beyond + DW groups under atomic force microscopy evaluation. Two-way analysis of variance and Tukey test revealed that the RMS showed significant intergroup differences for both storage condition and bleaching agent, whereas microhardness and FT revealed no significant alteration. The results indicated that in-office bleaching agents with low pH values could induce enamel morphology alterations under in vitro conditions. The presence of natural HS could eliminate the demineralization effect caused by low pH.

WE-C-217BCD-05: A Novel Interpolation Method for the 3D Reconstruction of Cell Structures

PURPOSE

To develop a new interpolation method for accurate 3D reconstruction of cell morphology from laser scanning confocal microscope (LSCM) image data.

METHODS

Current techniques are based on the assumption that pixel intensity or contour shapes of images change linearly in the interpolation direction. Gray-value and position of the pixel in interpolated image slice are obtained through weighted average calculation with gray-values and distances of corresponding pixels in two adjacent original image slices, only information from adjacent image slices is considered, often fail to meet the need of 3D reconstruction for cells because of the complex cell morphology. The new method interpolates cellular organelle contours in polar coordinate system. Coordinate system origin is chosen to be the mass center weighted by pixel intensity instead of conventional geometric center, contour points of the organelle is sampled by their angles first and fitted with uniform cubic B-spline to perform interpolation. For complex organelle structures such as branched nuclei, a special method combining morphological information and corner detection technique based on curvature scale space has been developed to solve the contour division and related problems. New method was applied to confocal images of 130 different cells acquired with an LSCM system (LSM510, Zeiss), sampling step was set as 0.5 μm in longitudinal direction, pixel size in horizontal plane was 0.07 μm and the resolution was 512×512. Marching cubes algorithm was used for 3D reconstruction.

RESULTS

Experiments showed that reconstructed 3D images with new method have much smoother and more valid organelle surfaces for both cytoplasm and nucleus than those from conventional methods.

CONCLUSIONS

The new interpolation method can significantly improve the quality of 3D reconstruction and serve as a valid and effective tool for quantitative study of 3D cell morphology in radiation biology and other areas of life science.*support by NSFC- 81171342. Supported by the National Science Foundation of China (NSFC- 81171342).

[Enhanced continent mechanism of the tapered ileum in continent urinary reservoir]

OBJECTIVE

To construct a reliable continent tube that is easy to catheterize and is surgically simple.

METHODS

From October 1999 through March 2001, 20 patients underwent a procedure in which ileal segment was tapered as an efferent tube and the partial efferent tube was placed between the back surface of the rectus muscle and the wall of the ileal pouch. The internal orifice of the tapered ileum was anastomosed to the ileal pouch and its external orifice of the tapered ileum was anastomosed to the umbilicus. Urodynamic study of the efferent tubes and pouch was done 1.5 to 3 months and 6 to 17 months after operation.

RESULTS

The stoma was easily catheterized with a 16 F catheter in all patients. One patient died of heart disease 55 days after the operation, while 18 of the remaining 19 were completely continent day and night. At 1.5 to 3 months, the urodynamic study of the efferent tubes showed the maximum close pressure with a full pouch of 46-124 cmH2O(91.53 +/- 17.21), and when the pouch was empty it was 34-84 cmH2O(66.68 +/- 11.60). The difference in the mean maximum closure pressure in full and empty pouches was statistically significant (t = 10.59, P < 0.01). At 6 to 17 months, urodynamic study was performed in 12 patients, the maximum closure pressure in the efferent tube was 77 to 154 cmH2O (100.92 +/- 20.88) when the pouch was filled with saline. When the pouch was empty, it was 56 to 115 cmH2O (74.08 +/- 14.59). The difference in the mean maximum closure pressure in full and empty pouches was statistically significant (t = 8.54, P < 0.01). Reservoir capacity was 360 to 750 ml (455 +/- 110.74). When it was filled to the maximum, the reservoir pressure was 16 to 35 cmH2O (23.17 +/- 5.82). There was no contractive wave in filling in any patient.

CONCLUSIONS

This study indicates that the continent mechanism of the tapered ileum can be greatly enhanced by fixing it between the abdominal and pouch walls. This maneuver also provides easy catheterization and surgical simplicity.