bluuebunny/crossref_metadata_2025_split huggingface dataset:
Little enhancement of meal‐induced glucagon‐like peptide 1 secretion in Japanese: Comparison of type 2 diabetes patients and healthy controls
Authors: Yabe Daisuke , Kuroe Akira , Lee Soushou , Watanabe Koin , Hyo Takanori , Hishizawa Masahiro , Kurose Takeshi , Deacon Carolyn F , Holst Jens J , Hirano Tsutomu , Inagaki Nobuya , Seino Yutaka 
Published: March 2010

AbstractAlthough glucose‐dependent insulinotropic polypeptide (GIP) levels have been characterized previously, GLP‐1 levels in Asians remain unclear. Here, we investigate total and intact levels of GLP‐1, as well as GIP during oral glucose and meal tolerance tests (OGTT and MTT) in Japanese patients with or without type 2 diabetes (T2DM). Seventeen Japanese healthy controls and 18 age‐matched and untreated patients with T2DM of short duration participated in the present study. Fasting levels of total GPL‐1 were similar between the two groups (approximately 15 pM), and intact GLP‐1 levels were considerably low in both groups (less than 1 pM). In both groups, total GLP‐1 reached a peak 30 min after glucose ingestion (30–40 pM), whereas intact GLP‐1 levels remained low with no significant peak. In MTT, total and intact GLP‐1 showed no obvious peak. The current data indicate that intact GLP‐1 levels are considerably low in the Japanese and that meal‐induced enhancement of GLP‐1 secretion is negligible in the Japanese. (J Diabetes Invest, doi: 10.1111/j.2040‐1124.2010.00010.x, 2010)
The Dynamics of Embedded-Charge Microenergy Harvesting
Authors: Lutzer Carl V. , Ross David S. 
Published: March 2010

AbstractThe microelectronic devices that are ubiquitous these days are limited by the need for batteries. Various methods of harvesting ambient mechanical energy have been proposed and are being developed. Recently, Potter has developed a method for embedding charge, at high density, stably at the interfaces of dissimilar insulators. In this paper, we present and analyze dynamical system models that Potter and co-workers have used to optimize microenergy harvesters based on this novel technology.
Reconstruction of 3D lung models from 2D planning data sets for Hodgkin's lymphoma patients using combined deformable image registration and navigator channels
Authors: Ng Angela , Nguyen Thao‐Nguyen , Moseley Joanne L. , Hodgson David C. , Sharpe Michael B. , Brock Kristy K. 
Published: March 2010

Purpose:Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose‐risk models could potentially be used to estimate radiotherapy‐related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects.Methods:Three‐dimensional planning CT images of 52 current HL patients were acquired. 12 image sets were used to construct a male and a female population lung model. 23 “Reference” images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient‐specific lung geometry using a biomechanical‐based DIR algorithm, MORFEUS. 17 “Test” patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges. Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference‐adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient.Results:The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be and , respectively. Paired ‐tests demonstrated that the volumetric reconstruction method made a statistically significant improvement to the population lung model shape . The error in the results were also comparable to the volume overlap difference observed between inhale and exhale lung volumes during free‐breathing respiratory motion , which implies that the accuracies of the reconstruction method are within breathing constraints and would not be the confining factor in estimating normal tissue dose exposure.Conclusions:The result findings show that the DIR‐NC technique can achieve a high degree of reconstruction accuracy, and could be useful in approximating 3D dosimetric representations of historical 2D treatment. In turn, this could provide a better understanding of the biophysical relationship between dose‐volume exposure and late term radiotherapy effects.
The quantitative potential for breast tomosynthesis imaging
Authors: Shafer Christina M. , Samei Ehsan , Lo Joseph Y. 
Published: March 2010

Purpose:Due to its limited angular scan range, breast tomosynthesis has lower resolution in the depth direction, which may limit its accuracy in quantifying tissue density. This study assesses the quantitative potential of breast tomosynthesis using relatively simple reconstruction and image processing algorithms. This quantitation could allow improved characterization of lesions as well as image processing to present tomosynthesis images with the familiar appearance of mammography by preserving more low‐frequency information.Methods:All studies were based on a Siemens prototype MAMMOMAT Novation TOMO breast tomo system with a 45° total angular span. This investigation was performed using both simulations and empirical measurements. Monte Carlo simulations were conducted using the breast tomosynthesis geometry and tissue‐equivalent, uniform, voxelized phantoms with cuboid lesions of varying density embedded within. Empirical studies were then performed using tissue‐equivalent plastic phantoms which were imaged on the actual prototype system. The material surrounding the lesions was set to either fat‐equivalent or glandular‐equivalent plastic. From the simulation experiments, the effects of scatter, lesion depth, and background material density were studied. The empirical experiments studied the effects of lesion depth, background material density, x‐ray tube energy, and exposure level. Additionally, the proposed analysis methods were independently evaluated using a commercially available QA breast phantom (CIRS Model 11A). All image reconstruction was performed with a filtered backprojection algorithm. Reconstructed voxel values within each slice were corrected to reduce background nonuniformities.Results:The resulting lesion voxel values varied linearly with known glandular fraction (correlation coefficient ) under all simulated and empirical conditions, including for the independent tests with the QA phantom. Analysis of variance performed on the fit line parameters revealed statistically significant differences between the two different background materials and between 28 kVp and the remaining energies (26, 30, and 32 kVp) for the dense experimental phantom. However, no significant differences arose between different energies for the fatty phantom, nor for any of the many other combinations of parameters.Conclusions:These strong linear relationships suggest that breast tomosynthesis image voxel values, after being corrected by our outlined methods, are highly positively correlated with true tissue density. This consistent linearity implies that breast tomosynthesis imaging indeed has potential to be quantitative.
Backprojection‐filtration reconstruction without invoking a spatially varying weighting factor
Authors: Xia Dan , Cho Seungryong , Pan Xiaochuan 
Published: March 2010

Purpose:To develop a backprojection‐filtration (BPF) algorithm with improved noise properties over the existing BPF algorithm through utilizing (approximate) redundant information in circular cone‐beam or fan‐beam scans.Methods:The backprojection steps in the existing filtered‐backprojection (FBP) and BPF algorithms for fan‐beam and cone‐beam projections invoke spatially varying weighting factors, which may not only increase the computational load in image reconstruction but also, more importantly, result in reconstruction artifacts. Redundant information in fan‐beam projections has been exploited for eliminating the weighting factor in the existing FBP algorithm. However, the new FBP algorithm cannot be applied to image reconstruction in a region of interest from transversely truncated data. In this work, the authors identify approximate data redundancy in circular cone‐beam projections and propose a new BPF algorithm in which the approximate data redundancy is exploited for eliminating the spatially varying weighting factor in the existing BPF algorithm.Results:The authors have implemented and evaluated the proposed BPF algorithm in numerical studies of reconstructing 3D images from both the nontruncated and truncated projection data in a circular cone‐beam scan. The results of numerical studies demonstrate that the proposed BPF algorithm retains the resolution property of the existing BPF algorithm, and that it can also reconstruct accurately ROI images from truncated data. More importantly, the results also indicate that the proposed BPF algorithm not only is computationally more efficient but also yields generally lower image variances than the existing BPF algorithm.Conclusions:A BPF algorithm was proposed that not only retains the desirable properties of the existing BPF algorithm but also possesses improved computational and noise properties over the latter.
Mathematical formulation and analysis of the nonlinear system reconstruction of the online image‐guided adaptive control of hyperthermia
Authors: Cheng Kung‐Shan , Dewhirst Mark W. , Stauffer Paul F. , Das Shiva 
Published: March 2010

Purpose:A nonlinear system reconstruction can theoretically provide timely system reconstruction when designing a real‐time image‐guided adaptive control for multisource heating for hyperthermia. This clinical need motivates an analysis of the essential mathematical characteristics and constraints of such an approach.Methods:The implicit function theorem (IFT), the Karush–Kuhn–Tucker (KKT) necessary condition of optimality, and the Tikhonov–Phillips regularization (TPR) were used to analyze and determine the requirements of the optimal system reconstruction. Two mutually exclusive generic approaches were analyzed to reconstruct the physical system: The traditional full reconstruction and the recently suggested partial reconstruction. Rigorous mathematical analysis based on IFT, KKT, and TPR was provided for all four possible nonlinear reconstructions: (1) Nonlinear noiseless full reconstruction, (2) nonlinear noisy full reconstruction, (3) nonlinear noiseless partial reconstruction, and (4) nonlinear noisy partial reconstruction, when a class of nonlinear formulations of system reconstruction is employed.Results:Effective numerical algorithms for solving each of the aforementioned four nonlinear reconstructions were introduced and formal derivations and analyses were provided. The analyses revealed the necessity of adding regularization when partial reconstruction is used. Regularization provides the theoretical support for one to uniquely reconstruct the optimal system. It also helps alleviate the negative influences of unavoidable measurement noise. Both theoretical analysis and numerical examples showed the importance of having a good initial guess for accomplishing nonlinear system reconstruction.Conclusions:Regularization is mandatory for partial reconstruction to make it well posed. The Tikhonov–Phillips regularized Gauss–Newton algorithm has nice theoretical performance for partial reconstruction of systems with and without noise. The Levenberg–Marquardt algorithm is a more robust algorithmic option compared to the Gauss–Newton algorithm for nonlinear full reconstruction. A severe limitation of nonlinear reconstruction is the time consuming calculations required for the derivatives of temperatures to unknowns. Developing a method of model reduction or implementing a parallel algorithm can resolve this. The results provided herein are applicable to hyperthermia with blood perfusion nonlinearly depending on temperature and in the presence of thermally significant blood vessels.
Variations in tumor size and position due to irregular breathing in 4D‐CT: A simulation study
Authors: Sarker Joyatee , Chu Alan , Mui Kit , Wolfgang John A. , Hirsch Ariel E. , Chen George T. Y. , Sharp Gregory C. 
Published: March 2010

Purpose:To estimate the position and volume errors in 4D‐CT caused by irregular breathing.Methods:A virtual 4D‐CT scanner was designed to reproduce axial mode scans with retrospective resorting. This virtual scanner creates an artificial spherical tumor based on the specifications of the user, and recreates images that might be produced by a 4D‐CT scanner using a patient breathing waveform. 155 respiratory waveforms of patients were used to test the variability of 4D‐CT scans. Each breathing waveform was normalized and scaled to 1, 2, and 3 cm peak‐to‐peak motion, and artificial tumors with 2 and 4 cm radius were simulated for each scaled waveform. The center of mass and volume of resorted 4D‐CT images were calculated and compared to the expected values of center of mass and volume for the artificial tumor. Intrasubject variability was investigated by running the virtual scanner over different subintervals of each patient's breathing waveform.Results:The average error in the center of mass location of an artificial tumor was less than 2 mm standard deviation for 2 cm motion. The corresponding average error in volume was less than 4%. In the worst‐case scenarios, a center of mass error of 1.0 cm standard deviation and volume errors of 30%–60% at inhale were found. Systematic errors were observed in a subset of patients due to irregular breathing, and these errors were more pronounced when the tumor volume is smaller.Conclusions: Irregular breathing during 4D‐CT simulation causes systematic errors in volume and center of mass measurements. These errors are small but depend on the tumor size, motion amplitude, and degree of breathing irregularity.
Advanced statistical techniques applied to comprehensive FTIR spectra on human colonic tissues
Authors: Zwielly A. , Mordechai S. , Sinielnikov I. , Salman A. , Bogomolny E. , Argov S. 
Published: March 2010

Purpose:Colon cancer is a major public health problem due to its high disease rate and death toll worldwide. The use of FTIR microscopy in the field of cancer diagnosis has become attractive over the past 20 years. In the present study, the authors investigated the potential of FTIR microscopy to define spectral changes among normal, polyp, and cancer human colonic biopsied tissues.Methods:A large database of FTIR microscopic spectra was compiled from 230 human colonic biopsies. The database was divided into five subgroups: Normal, cancerous tissues, and three stages of benign colonic polyps, namely, mild, moderate, and severe polyps, which are precursors of carcinoma. All biopsied tissue sections were classified concurrently by an expert pathologist. The authors applied the principal components analysis (PCA) model to reduce the dimension of the original data size to 13 principal components.Results:While PCA analysis shows only partial success in distinguishing among cancer, polyp, and the normal tissues, multivariate analysis (e.g., LDA) shows a promising distinction even within the polyp subgroups.Conclusions:Good classification accuracy among normal, polyp, and cancer groups was achieved with a success rate of approximately 85%. These results strongly support the potential of developing FTIR microscopy as a simple, reagent‐free tool for early detection of colon cancer and, in particular, for discriminating among the benign premalignant colonic polyps having increasing degrees of dysplasia severity (mild, moderate, and severe).
Individualized computer‐aided education in mammography based on user modeling: Concept and preliminary experiments
Authors: Mazurowski Maciej A. , Baker Jay A. , Barnhart Huiman X. , Tourassi Georgia D. 
Published: March 2010

Purpose:The authors propose the framework for an individualized adaptive computer‐aided educational system in mammography that is based on user modeling. The underlying hypothesis is that user models can be developed to capture the individual error making patterns of radiologists‐in‐training. In this pilot study, the authors test the above hypothesis for the task of breast cancer diagnosis in mammograms.Methods:The concept of a user model was formalized as the function that relates image features to the likelihood/extent of the diagnostic error made by a radiologist‐in‐training and therefore to the level of difficulty that a case will pose to the radiologist‐in‐training (or “user”). Then, machine learning algorithms were implemented to build such user models. Specifically, the authors explored‐nearest neighbor, artificial neural networks, and multiple regression for the task of building the model using observer data collected from ten Radiology residents at Duke University Medical Center for the problem of breast mass diagnosis in mammograms. For each resident, a user‐specific model was constructed that predicts the user's expected level of difficulty for each presented case based on two BI‐RADS image features. In the experiments, leave‐one‐out data handling scheme was applied to assign each case to a low‐predicted‐difficulty or a high‐predicted‐difficulty group for each resident based on each of the three user models. To evaluate whether the user model is useful in predicting difficulty, the authors performed statistical tests using the generalized estimating equations approach to determine whether the mean actual error is the same or not between the low‐predicted‐difficulty group and the high‐predicted‐difficulty group.Results:When the results for all observers were pulled together, the actual errors made by residents were statistically significantly higher for cases in the high‐predicted‐difficulty group than for cases in the low‐predicted‐difficulty group for all modeling algorithms (for all methods). This indicates that the user models were able to accurately predict difficulty level of the analyzed cases. Furthermore, the authors determined that among the two BI‐RADS features that were used in this study, mass margin was the most useful in predicting individual user errors.Conclusions:The pilot study shows promise for developing individual user models that can accurately predict the level of difficulty that each case will pose to the radiologist‐in‐training. These models could allow for constructing adaptive computer‐aided educational systems in mammography.
A pseudoinverse deformation vector field generator and its applications
Authors: Yan C. , Zhong H. , Murphy M. , Weiss E. , Siebers J. V. 
Published: March 2010

Purpose:To present, implement, and test aself‐consistent pseudoinverse displacement vector field (PIDVF) generator, which preserves the location of information mapped back‐and‐forth between image sets.Methods:The algorithm is an iterative scheme based on nearest neighbor interpolation and a subsequent iterative search. Performance of the algorithm is benchmarked using a lung 4DCT data set with six CT images from different breathing phases and eight CT images for a single prostrate patient acquired on different days. A diffeomorphic deformable image registration is used to validate our PIDVFs. Additionally, the PIDVF is used to measure the self‐consistency of two nondiffeomorphic algorithms which do not use a self‐consistency constraint: The ITK Demons algorithm for the lung patient images and an in‐house B‐Spline algorithm for the prostate patient images. Both Demons and B‐Spline have been QAed through contour comparison. Self‐consistency is determined by using a DIR to generate a displacement vector field (DVF) between reference image and study image . The same DIR is used to generate . Additionally, our PIDVF generator is used to create . Back‐and‐forth mapping of a set of points (used as surrogates of contours) using and is compared to back‐and‐forth mapping performed with and . The Euclidean distances between the original unmapped points and the mapped points are used as a self‐consistency measure.Results:Test results demonstrate that the consistency error observed in back‐and‐forth mappings can be reduced two to nine times in point mapping and 1.5 to three times in dose mapping when the PIDVF is used in place of the B‐Spline algorithm. These self‐consistency improvements are not affected by the exchanging of and . It is also demonstrated that differences between and can be used as a criteria to check the quality of the DVF.Conclusions:Use of DVF and its PIDVF will improve the self‐consistency of points, contour, and dose mappings in image guided adaptive therapy.
A volumetric model‐based 2D to 3D registration method for measuring kinematics of natural knees with single‐plane fluoroscopy
Authors: Tsai Tsung‐Yuan , Lu Tung‐Wu , Chen Chung‐Ming , Kuo Mei‐Ying , Hsu Horng‐Chaung 
Published: March 2010

Purpose:Accurate measurement of the three‐dimensional (3D) rigid body and surface kinematics of the natural human knee is essential for many clinical applications. Existing techniques are limited either in their accuracy or lack more realistic experimental evaluation of the measurement errors. The purposes of the study were to develop a volumetric model‐based 2D to 3D registration method, called the weighted edge‐matching score (WEMS) method, for measuring natural knee kinematics with single‐plane fluoroscopy to determine experimentally the measurement errors and to compare its performance with that of pattern intensity (PI) and gradient difference (GD) methods.Methods:The WEMS method gives higher priority to matching of longer edges of the digitally reconstructed radiograph and fluoroscopic images. The measurement errors of the methods were evaluated based on a human cadaveric knee at 11 flexion positions.Results:The accuracy of the WEMS method was determined experimentally to be less than 0.77 mm for the in‐plane translations, 3.06 mm for out‐of‐plane translation, and 1.13° for all rotations, which is better than that of the PI and GD methods.Conclusions:A new volumetric model‐based 2D to 3D registration method has been developed for measuring 3Din vivo kinematics of natural knee joints with single‐plane fluoroscopy. With the equipment used in the current study, the accuracy of the WEMS method is considered acceptable for the measurement of the 3D kinematics of the natural knee in clinical applications.