Assessment and Visualization of Ki67 Heterogeneity in Breast Cancers through Digital Image Analysis

The Ki67 index (KI) is a standard clinical marker for tumor proliferation;however, its application is hindered by intratumoral heterogeneity. In this study, we used digital image analysis to comprehensively analyze Ki67 heterogeneity and distribution patterns in breast carcinoma. Using Smart Pathology software, we digitized and analyzed 42 excised breast carcinoma Ki67 slides. Boxplots, histograms, and heat maps were generated to illustrate the KI distribution. We found that 30% of cases (13/42) exhibited discrepancies between global and hotspot KI when using a 14% KI threshold for classification. Patients with higher global or hotspot KI values displayed greater heterogenicity. Ki67 distribution patterns were categorized as randomly distributed (52%, 22/42), peripheral (43%, 18/42), and centered (5%, 2/42). Our sampling simulator indicated analyzing more than 10 high-power fields was typically required to accurately estimate global KI, with sampling size being correlated with heterogeneity. In conclusion, using digital image analysis in whole-slide images allows for comprehensive Ki67 profile assessment, shedding light on heterogeneity and distribution patterns. This spatial information can facilitate KI surveys of breast cancer and other malignancies.

Collagen proportionate area of liver tissue determined by digital image analysis in patients with HBV-related decompensated cirrhosis

BACKGROUND: The accurate assessment of the degree of hepatic fibrosis plays a critical role in guiding the diagnosis, treatment and prognostic assessment of chronic liver diseases. Liver biopsy is currently the most reliable method to evaluate the severity of hepatic fibrosis. However, liver biopsy is an invasive procedure associated with morbidity and mortality, and has several limitations in patients with decompensated cirrhosis. There is no report on the collagen proportionate area (CPA) of liver tissue in the decompensated stage of cirrhosis. This study aimed to determine the CPA of resected liver tissue samples from patients with HBV-related decompensated cirrhosis using digital image analysis, and to analyze the relationship between the CPA and liver functional reserve. METHODS: Fifty-three resected liver tissue samples from liver transplant patients with chronic hepatitis B-induced decompensated cirrhosis were stained with Masson’s trichrome, and the CPA in these samples was quantitatively determined using digital image analysis. The values of relevant liver function just before liver transplantation, the CPA in liver tissue, and their correlation were analyzed. RESULTS: The mean CPA at the decompensated stage of cirrhosis was 35.93±14.42% (11.24%-63.41%). The correlation coefficients of the CPA with a model for end-stage liver disease score, serum total bilirubin and international standard ratio of prothrombin B were 0.553, 0.519 and 0.533, respectively (P<0.001). With increasing CPA values, the three indices reflecting liver functional reserve also changed significantly.CONCLUSIONS: The degree of fibrosis may be correlated with the functional reserve. With the advancement of fibrosis, the liver functional reserve is attenuated accordingly.

DIGITAL IMAGE ANALYSIS OF PHASE STRUCTURE IN THE BLEND OF POLY(BUTYLENE TEREPHTHALATE-COCAPROLACTONE) WITH POLYCARBONATE

The digital image processing technique was used for the extraction of physical information from the temporal image of phase structure in the process of phase separation in the blend of poly (butylene terephthalate-co-caprolactone )with polycarbonate. The power spectrum images of the two-dimensional Fourier transformation (2DFT) of the temporal image of phase structure reflect the change of the phase size with time.

Bubble dynamics properties of B-particles in a quasi-2D gas-solid fluidized bed:Computational particle fluid dynamics numerical simulation and post-processed by digital image analysis technique

Bubble dynamics properties play a crucial and significant role in the design and optimization of gas-solid fluidized beds.In this study,the bubble dynamics properties of four B-particles were investigated in a quasi-two-dimensional(quasi-2D)fluidized bed,including bubble equivalent diameter,bubble size distribution,average bubble density,bubble aspect ratio,bubble hold-up,bed expansion ratio,bubble radial position,and bubble velocity.The studies were performed by computational particle fluid dynamics(CPFD)numerical simulation and post-processed with digital image analysis(DIA)technique,at superficial gas velocities ranging from 2u_(mf) to 7u_(mf).The simulated results shown that the CPFD simulation combining with DIA technique post-processing could be used as a reliable method for simulating bubble dynamics properties in quasi-2D gas-solid fluidized beds.However,it seemed not desirable for the simulation of bubble motion near the air distributor at higher superficial gas velocity from the simulated average bubble density distribution.The superficial gas velocity significantly affected the bubble equivalent diameter and evolution,while it had little influence on bubble size distribution and bubble aspect ratio distribution for the same particles.Both time-averaged bubble hold-up and bed expansion ratio increased with the increase of superficial gas velocity.Two core-annular flow structures could be found in the fluidized bed for all cases.The average bubble rising velocity increased with the increasing bubble equivalent diameter.For bubble lateral movement,the smaller bubbles might be more susceptible,and superficial gas velocity had a little influence on the absolute lateral velocity of bubbles.The simulated results presented a valuable and novel approach for studying bubble dynamics properties.The comprehensive understanding of bubble dynamics behaviors in quasi-2D gas-solid fluidized beds would provide support in the design,operation,and optimization of gas-solid fluidized bed reactors.

An Object-based Approach for Two-level Gully Feature Mapping Using High-resolution DEM and Imagery： A Case Study on Hilly Loess Plateau Region, China

Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.

Assessment of liver fibrosis by a noninvasive method of transient elastography and biochemical markers

AIM： To assess the correlation between the fibrotic area （FA） as calculated by a digital image analysis （DIA）, and to compare the diagnostic accuracy of FibroScan to the other existing Liver fibrosis （LF） markers using the receiver operating curve analysis.METHODS： We recruited 30 patients who underwent a liver resection for three different etiologies including normal liver, hepatitis B, and hepatitis C. Liver stiffness was measured by using a FibroScan. The FA was then calculated by DIA to evaluate LF in order to avoid any sampling bias. RESULTS： The FA negatively correlated with Prothrombin time （PT）, platelet count, lecithin-cholesterol acyltransferase （LCAT）, and pre-albumin （ALB）. On the other hand, the findings of FibroScan correlated with similar markers. The FA positively correlated with FibroScan, serum hyaluronate level, and type Ⅳ collagen level, and aspartate transaminase to platelet ratio index （APRI）. The area under the receiver operating curve for FibroScan was higher than that for the other markers, even though the statistical significance was minimal. CONCLUSION： Our findings suggest that FibroScan can initially be used to assess LF as an alternative to a liver biopsy （LB） and serum diagnosis, because it is a safe method with comparable diagnostic accuracy regarding the existing LF markers.

Endoscopic ultrasound for the diagnosis of chronic pancreatitis

Endoscopic ultrasound(EUS) has become a well accepted test for the diagnosis of chronic pancreatitis.Advantages include its ability to detect subtle and severe changes of the pancreatic duct and parenchyma,and its relative safety compared with endoscopic retrograde cholangiopancreatography.Limitations include inter-and intraobserver variability,operator dependence,and an incomplete understanding of its true accuracy.The Rosemont classif ication has recently been proposed as a weighted,standardized method that may improve EUS chronic pancreatitis scoring.This paper reviews the published evidence regarding the accuracy of EUS in chronic pancreatitis diagnosis,and enumerates the emerging technologies that have been recently studied which may ultimately improve endosonographic imaging of the pancreas.

Quantitative characterization of β-solidifying γ-TiAl alloy with duplex structure

For precise plastic deformation,microstructure control is essential especially for β-solidifying γ-TiAl alloy with duplex structure.Based on stereology,the microstructure of isothermally compressed γ-TiAl alloy was divided into β_(0) grains,remnant α_(2)/γ lamellar colonies,α_(2) and γ grains.The results show that the volume fraction of β_(0) grains slightly increases in the isothermally compressed γ-TiAl alloy with the increase of height reduction.Meanwhile,the volume fractions of remnant α_(2)/γ lamellar colonies and α_(2) grains decrease.However,the volume fraction of γ grains increases from 64.39% to 78.47%.According to the quantitative results,the α→γ phase transformation was investigated in-depth,and it is found that isothermal compression accelerates the α→γ phase transformation.The first α→γ phase transformation is similar to ledge-controlled transformation,through which remnant α_(2)/γ lamellar colonies finally convert intoγgrains in isothermal compression.The second is achieved by α/γ phase interface immigration.

Nuclear morphometry, nucleomics and prostate cancer progression

Prostate cancer （PCa） results from a multistep process. This process includes initiation, which occurs through various aging events and multiple insults （such as chronic infection, inflammation and genetic instability through reactive oxygen species causing DNA double-strand breaks）, followed by a multistep process of progression. These steps include several genetic and epigenetic alterations, as well as alterations to the chromatin structure, which occur in response to the carcinogenic stress-related events that sustain proliferative signaling. Events such as evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis are readily observed. In addition, in conjunction with these critical drivers of carcinogenesis, other factors related to the etiopathogenesis of PCa, involving energy metabolism and evasion of the immune surveillance system, appear to be involved. In addition, when cancer spread and metastasis occur, the ＇tumor microenvironment＇ in the bone of PCa patients may provide a way to sustain dormancy or senescence and eventually establish a ＇seed and soil＇ site where PCa proliferation and growth may occur over time. When PCa is initiated and progression ensues, significant alterations in nuclear size, shape and heterochromatin （DNA transcription） organization are found, and key nuclear transcriptional and structural proteins, as well as multiple nuclear bodies can lead to precancerous and malignant changes. These series of cellular and tissue-related malignancy-associated events can be quantified to assess disease progression and management.

浸渍硅胶薄层色谱板分离钴和镍及数字图像分析法定量(英文)

Thin layer chromatography(TLC) of cobalt and nickel has been performed on silica gel layers induced with alkali mediated cellulose extract.A novel combination of 10% aqueous solutions of Tween-20 and potassium thiocyanate in 1∶1(v/v) was identified as the best mobile phase for the selective separation of Co2+from Ni2+on the impregnated Silica Gel G layers.The chromatographic characteristics of the cations were studied and the limits of detection as well as the limits of quantification for Co2+and Ni2+were determined.The quantitative estimation of the cations was achieved from the digital image analysis of respective chromatograms.The proposed quantitative method was successfully applied with 0-0.50% error for the determination of Co2+from Ni2+in spiked samples of bauxite,soil and rock containing common cations such as Al3+,Fe2+,Ti4+,Zn2+,Mn2+,Cu2+,Cr6+,Mg2+,etc.under the optimized chromatographic conditions.

Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathology

Tremendous advances in artificial intelligence(AI)in medical image analysis have been achieved in recent years.The integration of AI is expected to cause a revolution in various areas of medicine,including gastrointestinal(GI)pathology.Currently,deep learning algorithms have shown promising benefits in areas of diagnostic histopathology,such as tumor identification,classification,prognosis prediction,and biomarker/genetic alteration prediction.While AI cannot substitute pathologists,carefully constructed AI applications may increase workforce productivity and diagnostic accuracy in pathology practice.Regardless of these promising advances,unlike the areas of radiology or cardiology imaging,no histopathology-based AI application has been approved by a regulatory authority or for public reimbursement.Thus,implying that there are still some obstacles to be overcome before AI applications can be safely and effectively implemented in real-life pathology practice.The challenges have been identified at different stages of the development process,such as needs identification,data curation,model development,validation,regulation,modification of daily workflow,and cost-effectiveness balance.The aim of this review is to present challenges in the process of AI development,validation,and regulation that should be overcome for its implementation in real-life GI pathology practice.

A LINEAR APPROACH TO METRIC CIRCUMFERENCE COMPUTATIO FOR DIGITIZED CONVEX SHAPES

Metric measurement of digitized shapes is commonly applied in optical measuring systems.In this letter,three shape-related factors defined by the authors are used in the construction of amultiple linear regression model which is utilized to compute the circumference of the convex shapes inmillimeter unit.The model is first built upon the relationship hypothesis and then its adequacy ismathematically validated.The results of applying the developed model to the given number of convexshapes in a finite circumferential length range suggest that,in terms of percent error,the model pre-cision is to satisfaction by being within±4%.The test also shows the model’s robustness against theshape’s orientation anisotropy.

Modern diagnostic approaches to cholangiocarcinoma

BACKGROUND:Cholangiocarcinoma is a very aggressive tumor with poor survival.Therefore,early diagnosis and surgical resection are of paramount importance.Its diagnosis is difficult because access to the tumor is not easy.Biopsy is possible only for intrahepatic cholangiocarcinoma,which accounts for 10% of cases.Routine brush cytology from endoscopic retrograde cholangiopancreatography(ERCP) has a high specificity of 100% but unfortunately a low sensitivity of 30%.In this review we briefly describe new diagnostic techniques applicable to ERCP brush cytology specimens and targeting the genetic background of the disease,in particular fluorescence in situ hybridization(FISH) and digital image analysis(DIA).DATE SOURCES:The PubMed database up to 2011 was used for the retrieval of relevant articles.The search terms FISH,fluorescence in situ hybridization,DIA,digital image analysis and cholangiocarcinoma were used.Both original and review articles were used.RESULTS:FISH identifies cells with chromosomal abnormalities,mainly numerical aberrations,using a mixture of fluorescencelabeled probes.FISH offers a higher sensitivity than routine cytology,retaining a high level of specificity.The DIA criterion for malignancy is demonstration of aneuploidy.This technique increases the sensitivity to 40%,but the specificity remains low.Preliminary data from application to other tumors suggest that combination of FISH and DIA may be of further benefit.CONCLUSIONS:The new techniques offer a significantly enhanced diagnostic efficacy in the evaluation of ERCP brush specimens.Apart from contributing to a more timely diagnosis,their wider application to cholangiocarcinoma may also facilitate the genetic study of the disease and add to our understanding of oncogenesis at the molecular level,with the prospect of identifying targets for novel therapeutic interventions.

Artificial intelligence in pathological evaluation of gastrointestinal cancers

The integration of artificial intelligence(AI)has shown promising benefits in many fields of diagnostic histopathology,including for gastrointestinal cancers(GCs),such as tumor identification,classification,and prognosis prediction.In parallel,recent evidence suggests that AI may help reduce the workload in gastrointestinal pathology by automatically detecting tumor tissues and evaluating prognostic parameters.In addition,AI seems to be an attractive tool for biomarker/genetic alteration prediction in GC,as it can contain a massive amount of information from visual data that is complex and partially understandable by pathologists.From this point of view,it is suggested that advances in AI could lead to revolutionary changes in many fields of pathology.Unfortunately,these findings do not exclude the possibility that there are still many hurdles to overcome before AI applications can be safely and effectively applied in actual pathology practice.These include a broad spectrum of challenges from needs identification to cost-effectiveness.Therefore,unlike other disciplines of medicine,no histopathology-based AI application,including in GC,has ever been approved either by a regulatory authority or approved for public reimbursement.The purpose of this review is to present data related to the applications of AI in pathology practice in GC and present the challenges that need to be overcome for their implementation.

Bubble behaviors of geldart B particle in a pseudo two-dimensional pressurized fluidized bed

Pressurized fluidized beds have been developed in quite a few industrial applications because of intensified heat and mass transfer and chemical reaction.The bubble behaviors under elevated pressure,strongly influencing the fluidization and reaction conversion of the whole system,are of great research significance.In this work,the bubble behaviors of Geldart B particle in a pseudo two-dimensional(2D)pressurized fluidized bed were experimentally studied based on digital image analysis technique.The effects of pressure and fluidization gas velocity on the general bubble behaviors(i.e.,size,shape and spatial distribution)and the dynamic characteristics,such as the time-evolution of voidage distribution and local flow regimes,were comprehensively investigated.Results show that increasing pressure re-duces the stability of bubbles and facilitates gas passing through the emulsion phase,resulting in the"smoother"fluidization state with smaller bubbles and declined bubble fraction and standard deviation.The equivalent bubble diameter and bubble aspect ratio increase with the increasing gas velocity while decrease as pressure rises.The elevated pressure reduces bubbles extension in the vertical direction,prohibits the"short pass"of fluidization gas in large oblong bubbles/slugs and benefits the gas-solid interaction.The flow regimes variation with gas velocity is affected by the elevated pressure,and demonstrates different features in different local positions of the bed.

AN IMPROVED ALGORITHM FOR DPIV CORRELATION ANALYSIS

In a Digital Particle Image Velocimetry （DPW） system, the correlation of digital images is normally used to acquire the displacement information of particles and give estimates of the flow field. The accuracy and robustness of the correlation algorithm directly affect the validity of the analysis result. In this article, an improved algorithm for the correlation analysis was proposed which could be used to optimize the selection/determination of the correlation window, analysis area and search path. This algorithm not only reduces largely the amount of calculation, but also improves effectively the accuracy and reliability of the correlation analysis. The algorithm was demonstrated to be accurate and efficient in the measurement of the velocity field in a flocculation pool.

Quantification of coarse aggregate shape in concrete

The objective of this study is to choose indices for the characterization of aggregate form and angularity for large scale application. For this purpose, several parameters for aggregate form and angularity featured in previous research are presented. Then, based on these established parameters, 200 coarse quartzite aggregates are analyzed herein by using image processing technology. This paper also analyzes the statistical distributions of parameters for aggregate form and angularity as well as the correlation between form and angularity parameters. It was determined that the parameters for form or angularity of coarse aggregates could be fitted by either normal distribution or log-normal distribution at a 95% confidence level, Some of the form parameters were influenced by changes in angularity characteristics, while aspect ratio and angularity using outline slope, area ratio and radius angularity index, and aspect ratio and angularity index were independent of each other, respectively; and consequently, the independent parameters could be used to quantify the aggregate form and angularity for the purpose to study the influence of aggregate shape on the mechanical behavior of concrete. Furthermore, results from this study＇s in-depth investigations showed that the aspect ratio and the angularity index can further understanding of the effects of coarse aggregates form and angularity on concrete mechanical properties, respectively. Finally, coarse aggregates with the same content, type and surfaces texture, but different aspect ratios and angularity indices were used to study the influence of coarse aggregate form and angularity on the behavior of concrete. It was revealed that the splitting tensile strength of concrete increased with increases in the aspect ratio or angularity index of coarse aggregates.

Optimization of residence time distribution in RCDG and an assessment of its applicability in continuous manufacturing

Knowledge of residence time is a critical aspect in developing control and material diversion strategies for continuous manufacturing processes in pharmaceutical manufacturing.Dry granulation is a promising continuous granulation technique as it is fast and economical.In this study,a step-change method to determine residence time in roll compaction/dry granulation is introduced.The factors roll speed and rotational speed of the impeller in the powder inlet unit of the compactor were evaluated using a central composite circumscribed statistical design of experiments in order to optimize the residence time.The fill volume in the compactor was varied exemplarily.It was found that high roll speed,low rotational speed of the impeller and low fill volume in the compactor are beneficial to generate fast transition through the compactor.The impact of roll speed increase was estimated.It can be concluded that despite fast residence time in the process,high roll speed and its subsequent high material throughput can generate a large amount of material that has to be discarded if material diversion is required.

Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data

Information on Earth’s land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors.In this study,we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion imagery.For this purpose,the spectral angle mapper(SAM),the object-based and the non-linear spectral unmixing based on artificial neural networks(ANNs)techniques were applied.A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification,namely of the pixel purity index(PPI)and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training sites.Objectbased classification outperformed the other techniques with an overall accuracy of 83%.Sub-pixel classification based on the ANN showed an overall accuracy of 52%,very close to that of SAM(48%).SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%.Yet,all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery,which affected the spectral separation among the land use/cover classes.