Importance of Features Selection,Attributes Selection,Challenges and Future Directions for Medical Imaging Data:A Review

In the area of pattern recognition and machine learning,features play a key role in prediction.The famous applications of features are medical imaging,image classification,and name a few more.With the exponential growth of information investments in medical data repositories and health service provision,medical institutions are collecting large volumes of data.These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality.On the other hand,this growth also made it difficult to comprehend and utilize data for various purposes.The results of imaging data can become biased because of extraneous features present in larger datasets.Feature selection gives a chance to decrease the number of components in such large datasets.Through selection techniques,ousting the unimportant features and selecting a subset of components that produces prevalent characterization precision.The correct decision to find a good attribute produces a precise grouping model,which enhances learning pace and forecast control.This paper presents a review of feature selection techniques and attributes selection measures for medical imaging.This review is meant to describe feature selection techniques in a medical domainwith their pros and cons and to signify its application in imaging data and data mining algorithms.The review reveals the shortcomings of the existing feature and attributes selection techniques to multi-sourced data.Moreover,this review provides the importance of feature selection for correct classification of medical infections.In the end,critical analysis and future directions are provided.

Contrast-enhanced ultrasound Liver Imaging Reporting and Data System:Lights and shadows in hepatocellular carcinoma and cholangiocellular carcinoma diagnosis

BACKGROUND Contrast-enhanced ultrasound(CEUS)is considered a secondary examination compared to computed tomography(CT)and magnetic resonance imaging(MRI)in the diagnosis of hepatocellular carcinoma(HCC),due to the risk of misdiagnosing intrahepatic cholangiocarcinoma(ICC).The introduction of CEUS Liver Imaging Reporting and Data System(CEUS LI-RADS)might overcome this limitation.Even though data from the literature seems promising,its reliability in real-life context has not been well-established yet.AIM To test the accuracy of CEUS LI-RADS for correctly diagnosing HCC and ICC in cirrhosis.METHODS CEUS LI-RADS class was retrospectively assigned to 511 nodules identified in 269 patients suffering from liver cirrhosis.The diagnostic standard for all nodules was either biopsy(102 nodules)or CT/MRI(409 nodules).Common diagnostic accuracy indexes such as sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NPV)were assessed for the following associations:CEUS LR-5 and HCC;CEUS LR-4 and 5 merged class and HCC;CEUS LR-M and ICC;and CEUS LR-3 and malignancy.The frequency of malignant lesions in CEUS LR-3 subgroups with different CEUS patterns was also determined.Inter-rater agreement for CEUS LI-RADS class assignment and for major CEUS pattern identification was evaluated.RESULTS CEUS LR-5 predicted HCC with a 67.6%sensitivity,97.7%specificity,and 99.3%PPV(P<0.001).The merging of LR-4 and 5 offered an improved 93.9%sensitivity in HCC diagnosis with a 94.3%specificity and 98.8%PPV(P<0.001).CEUS LR-M predicted ICC with a 91.3%sensitivity,96.7%specificity,and 99.6%NPV(P<0.001).CEUS LR-3 predominantly included benign lesions(only 28.8%of malignancies).In this class,the hypo-hypo pattern showed a much higher rate of malignant lesions(73.3%)than the iso-iso pattern(2.6%).Inter-rater agreement between internal raters for CEUS-LR class assignment was almost perfect(n=511,k=0.94,P<0.001),while the agreement among raters from separate centres was substantial(n=50,k=0.67,P<0.001).Agreement was stronger for arterial phase hyperenhancement(internal k=0.86,P<2.7×10-214;external k=0.8,P<0.001)than washout(internal k=0.79,P<1.6×10-202;external k=0.71,P<0.001).CONCLUSION CEUS LI-RADS is effective but can be improved by merging LR-4 and 5 to diagnose HCC and by splitting LR-3 into two subgroups to differentiate iso-iso nodules from other patterns.

Interobserver agreement for contrast-enhanced ultrasound of liver imaging reporting and data system:A systematic review and metaanalysis

BACKGROUND Hepatocellular carcinoma is the most common primary liver malignancy.From the results of previous studies,Liver Imaging Reporting and Data System(LIRADS)on contrast-enhanced ultrasound(CEUS)has shown satisfactory diagnostic value.However,a unified conclusion on the interobserver stability of this innovative ultrasound imaging has not been determined.The present metaanalysis examined the interobserver agreement of CEUS LI-RADS to provide some reference for subsequent related research.AIM To evaluate the interobserver agreement of LI-RADS on CEUS and analyze the sources of heterogeneity between studies.METHODS Relevant papers on the subject of interobserver agreement on CEUS LI-RADS published before March 1,2020 in China and other countries were analyzed.The studies were filtered,and the diagnostic criteria were evaluated.The selected references were analyzed using the“meta”and“metafor”packages of R software version 3.6.2.RESULTS Eight studies were ultimately included in the present analysis.Meta-analysis results revealed that the summary Kappa value of included studies was 0.76[95%confidence interval,0.67-0.83],which shows substantial agreement.Higgins I2 statistics also confirmed the substantial heterogeneity(I2=91.30%,95%confidence interval,85.3%-94.9%,P<0.01).Meta-regression identified the variables,including the method of patient enrollment,method of consistency testing,and patient race,which explained the substantial study heterogeneity.CONCLUSION CEUS LI-RADS demonstrated overall substantial interobserver agreement,but heterogeneous results between studies were also obvious.Further clinical investigations should consider a modified recommendation about the experimental design.

Hepatocellular carcinoma Liver Imaging Reporting and Data Systems treatment response assessment: Lessons learned and future directions

Hepatocellular carcinoma(HCC)is a leading cause of morbidity and mortality worldwide,with rising clinical and economic burden as incidence increases.There are a multitude of evolving treatment options,including locoregional therapies which can be used alone,in combination with each other,or in combination with systemic therapy.These treatment options have shown to be effective in achieving remission,controlling tumor progression,improving disease free and overall survival in patients who cannot undergo resection and providing a bridge to transplant by debulking tumor burden to downstage patients.Following locoregional therapy(LRT),it is crucial to provide treatment response assessment to guide management and liver transplant candidacy.Therefore,Liver Imaging Reporting and Data Systems(LI-RADS)Treatment Response Algorithm(TRA)was created to provide a standardized assessment of HCC following LRT.LIRADS TRA provides a step by step approach to evaluate each lesion independently for accurate tumor assessment.In this review,we provide an overview of different locoregional therapies for HCC,describe the expected post treatment imaging appearance following treatment,and review the LI-RADS TRA with guidance for its application in clinical practice.Unique to other publications,we will also review emerging literature supporting the use of LI-RADS for assessment of HCC treatment response after LRT.

Liver Imaging Reporting and Data System criteria for the diagnosis of hepatocellular carcinoma in clinical practice: A pictorial minireview

Hepatocellular carcinoma(HCC)is the sixth most common cancer.The main risk factors associated with HCC development include hepatitis B virus,hepatitis C virus,alcohol consumption,aflatoxin B1,and nonalcoholic fatty liver disease.However,hepatocarcinogenesis is a complex multistep process.Various factors lead to hepatocyte malignant transformation and HCC development.Diagnosis and surveillance of HCC can be made with the use of liver ultrasound(US)every 6 mo.However,the sensitivity of this imaging method to detect HCC in a cirrhotic liver is limited,due to the abnormal liver parenchyma.Computed tomography(CT)and magnetic resonance imaging(MRI)are considered to be most useful tools for at-risk patients or patients with inadequate US.Liver biopsy is still used for diagnosis and prognosis of HCC in specific nodules that cannot be definitely characterized as HCC by imaging.Recently the American College of Radiology designed the Liver Imaging Reporting and Data System(LI-RADS),which is a comprehensive system for standardized interpretation of CT and MRI liver examinations that was first proposed in 2011.In 2018,it was integrated into the American Association for the Study of Liver Diseases guidance statement for HCC.LI-RADS is designed to ensure high sensitivity,precise categorization,and high positive predictive value for the diagnosis of HCC and is applied to“highrisk populations”according to specific criteria.Most importantly LI-RADS criteria achieved international collaboration and consensus among liver experts around the world on the best practices for caring for patients with or at risk for HCC.

Validation of Vesical Imaging Reporting and Data System score for the diagnosis of muscle-invasive bladder cancer: A prospective cross-sectional study

Objective:Vesical Imaging Reporting and Data System(VIRADS)score was developed to standardize the reporting and staging of bladder tumors on pre-operative multiparametric magnetic resonance imaging.It helps in avoiding unnecessary repeat transurethral resection of bladder tumor in high-risk non-muscle-invasive bladder cancer patients.This study was done to determine the validity of VIRADS score prospectively for the diagnosis of muscleinvasive bladder cancer.Methods:This study was conducted from March 2019 to March 2020 at Sawai Man Singh Medical College and Hospital,Jaipur,Rajasthan,India.Patients admitted with the provisional diagnosis of bladder tumor were included as participants.All these patients underwent a 3 Tesla mpMRI to obtain a VIRADS score before they underwent transurethral resection of bladder tumor and these data were analyzed to evaluate the correlation of pre-operative VIRADS score with mus-cle invasiveness of the tumor in final biopsy report.Results:A cut-off of VIRADS≥4 for prediction of detrusor muscle invasion yielded a sensitivity of 79.4%,specificity of 94.2%,positive predictive value of 90.0%,negative predictive value of 87.5%,and diagnostic accuracy of 86.4%.A cut off of VIRADS≥3 for prediction of detrusor muscle invasion yielded a sensitivity of 91.2%,specificity of 78.8%,positive predictive value of 73.8%,negative predictive value of 93.2%,and accuracy of 83.7%.The receiver operating curve showed the area under the curve to be 0.922(95%confidence interval:0.862e0.983).Conclusion:VIRADS score appears to be an excellent and effective pre-operative radiological tool for the prediction of detrusor muscle invasion in bladder cancer.

Effect of training on resident inter-reader agreement with American College of Radiology Thyroid Imaging Reporting and Data System

BACKGROUND The American College of Radiology Thyroid Imaging Reporting and Data System(ACR TI-RADS)was introduced to standardize the ultrasound characterization of thyroid nodules.Studies have shown that ACR-TIRADS reduces unnecessary biopsies and improves consistency of imaging recommendations.Despite its widespread adoption,there are few studies to date assessing the inter-reader agreement amongst radiology trainees with limited ultrasound experience.We hypothesize that in PGY-4 radiology residents with no prior exposure to ACR TIRADS,a statistically significant improvement in inter-reader reliability can be achieved with a one hour training session.AIM To evaluate the inter-reader agreement of radiology residents in using ACR TIRADS before and after training.METHODS A single center retrospective cohort study evaluating 50 thyroid nodules in 40 patients of varying TI-RADS levels was performed.Reference standard TI-RADS scores were established through a consensus panel of three fellowship-trained staff radiologists with between 1 and 14 years of clinical experience each.Three PGY-4 radiology residents(trainees)were selected as blinded readers for this study.Each trainee had between 4 to 5 mo of designated ultrasound training.No trainee had received specialized TI-RADS training prior to this study.Each of the readers independently reviewed the 50 testing cases and assigned a TI-RADS score to each case before and after TI-RADS training performed 6 wk apart.Fleiss kappa was used to measure the pooled inter-reader agreement.The relative diagnostic performance of readers,pre-and post-training,when compared against the reference standard.RESULTS There were 33 females and 7 males with a mean age of 56.6±13.6 years.The mean nodule size was 19±14 mm(range from 5 to 63 mm).A statistically significant superior inter-reader agreement was found on the post-training assessment compared to the pre-training assessment for the following variables:1.“Shape”(k of 0.09[slight]pre-training vs 0.67[substantial]post-training,P<0.001),2.“Echogenic foci”(k of 0.28[fair]pre-training vs 0.45[moderate]post-training,P=0.004),3.‘TI-RADS level’(k of 0.14[slight]pre-training vs 0.36[fair]post-training,P<0.001)and 4.‘Recommendations’(k of 0.36[fair]pre-training vs 0.50[moderate]post-training,P=0.02).No significant differences between the preand post-training assessments were found for the variables'composition','echogenicity'and'margins'.There was a general trend towards improved pooled sensitivity with TI-RADS levels 1 to 4 for the post-training assessment while the pooled specificity was relatively high(76.6%-96.8%)for all TI-RADS level.CONCLUSION Statistically significant improvement in inter-reader agreement in the assigning TI-RADS level and recommendations after training is observed.Our study supports the use of dedicated ACR TI-RADS training in radiology residents.

Analysis of the Design and Implementation of a GIS System Incorporating Intelligent Recognition Models

The rapid economic growth,urbanization,and industrialization have led to a scarcity of land resources in coastal areas,exacerbating the conflict between humans and the environment.In order to promote economic development,attention has turned to the sea,and various coastal engineering projects have been undertaken,sparking a wave of land reclamation.However,while these efforts bring economic and social benefits,they also have implications for ecological relationships.To respond to and plan for changes in the coastline and land cover in a timely manner,this paper proposes and constructs a GIS system that integrates remote sensing image recognition models.The system combines geographic information system development technology with image recognition technology,streamlining the processing and identification of image data.This approach is particularly advantageous for marine management departments in their long-term monitoring and dynamic management of coastal lines,ensuring a more effective and efficient response.

Stroke Based Painterly Rendering with Mass Data through Auto Warping Generation

Painting is done according to the artist’s style.The most representative of the style is the texture and shape of the brush stroke.Computer simulations allow the artist’s painting to be produced by taking this stroke and pasting it onto the image.This is called stroke-based rendering.The quality of the result depends on the number or quality of this stroke,since the stroke is taken to create the image.It is not easy to render using a large amount of information,as there is a limit to having a stroke scanned.In this work,we intend to produce rendering results using mass data that produces large amounts of strokes by expanding existing strokes through warping.Through this,we have produced results that have higher quality than conventional studies.Finally,we also compare the correlation between the amount of data and the results.

Data Hiding in AMBTC Images Using Selective XOR Hiding Scheme

Nowadays since the Internet is ubiquitous,the frequency of data transfer through the public network is increasing.Hiding secure data in these transmitted data has emerged broad security issue,such as authentication and copyright protection.On the other hand,considering the transmission efficiency issue,image transmission usually involves image compression in Internet-based applications.To address both issues,this paper presents a data hiding scheme for the image compression method called absolute moment block truncation coding(AMBTC).First,an image is divided into nonoverlapping blocks through AMBTC compression,the blocks are classified four types,namely smooth,semi-smooth,semi-complex,and complex.The secret data are embedded into the smooth blocks by using a simple replacement strategy.The proposed method respectively embeds nine bits(and five bits)of secret data into the bitmap of the semi-smooth blocks(and semicomplex blocks)through the exclusive-or(XOR)operation.The secret data are embedded into the complex blocks by using a hidden function.After the embedding phase,the direct binary search(DBS)method is performed to improve the image qualitywithout damaging the secret data.The experimental results demonstrate that the proposed method yields higher quality and hiding capacity than other reference methods.

Reversible Data Embedding Scheme Using Relationships between Pixel-Values and Their Neighbors

Reversible data embedding is becoming a very important issue in securing images transmitted over the Internet, especially in dealing with sensitive images such as those created for military data and medical data. Based on the relationships between pixels and their neighbors, we propose a reversible data embedding scheme to embed hidden messages into an original image. In our proposed scheme, a two-layer data embedding approach is used for our proposed data embedding phase. Layer-1 embedding is used to hide secret data. Layer-2 embedding, which is an embedding variant of the proposed layer-1 embedding, is used to hide side information, such as the parameters required to restore the marked image. In our layer-1 embedding, the value of an embedded pixel is determined according to a predetermined threshold and the relationship between the pixel and its neighbors. In our layer-2 embedding, the similar data embedding concept is expanded to the block-based. Experimental results provide supportive data to show that the proposed scheme can provide greater hiding capacity while preserving the image quality of a marked image in comparison with previous work.

Satellite Data Reduction Using Entropy-preserved Image Compression Technique

In this paper, three techniques, line run coding, quadtree DF (Depth-First) representation and H coding for compressing classified satellite cloud images with no distortion are presented. In these three codings, the first two were invented by other persons and the third one, by ourselves. As a result, the comparison among their compression rates is. given at the end of this paper. Further application of these image compression technique to satellite data and other meteorological data looks promising.

The Co-alignment of Winged HαData Observed by the New Vacuum Solar Telescope

The New Vacuum Solar Telescope(NVST)has been releasing its novel winged Hαdata(WHD)since 2021 April,namely the Hαimaging spectroscopic data.Compared with the prior released version,the new data are further coaligned among the off-band images and packaged into a standard solar physics community format.In this study,we illustrate the alignment algorithm used by the novel WHD,which is mainly based on the optical flow method to obtain the translation offset between the winged images.To quantitatively evaluate the alignment results of two images with different similarities,we calculate the alignment accuracies between the images of different off-band and line center,respectively.The result shows that our alignment algorithm could reach up to the accuracy of about 0.″1 when the off-band of winged image is lower than 0.6?.In addition,we introduce the final product of the WHD in detail,which can provide convenience for the solar physicists to use high-resolution Hαimaging spectroscopic data of NVST.

Mapping and compositional analysis of mare basalts in the Aristarchus region of the Moon using Clementine data

The process of accurately defining and outlining mare basalt units is nec- essary for constraining the stratigraphy and ages of basalt units, which are used to determine the duration and the flux of lunar volcanism. We use a combination of Clementine＇s five-band ultraviolet/visible data and Ti02 and FeO abundance distri- bution maps to define homogenous mare basalt units and characterize their composi- tional variations （with maturity） in the Aristarchus region. With 20 groups of distinct mare basaltic soils identified using the method in this paper, six additional spectrally defined areas and five basaltic units are constructed, and their mineralogic quanfiza- tion values provide new constraints on their temporal and spatial evolution. Our results indicate that the Aristarchus region has diverse basalt units and a complex history of volcanic evolution. We also demonstrate that the techniques, from which spectrally distinct mare basalts can be mapped, performed well in this study and can be confi- dently expanded to other mare regions of the Moon.

Prostate Cancer Detection with Multiparametric Magnetic Resonance Imaging： Prostate Imaging Reporting and Data System Version 1 versus Version 2

Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American College of Radiology revised the PI-RADS to address the limitations of version 1 in December 2014.This study aimed to determine whether the PI-RADS version 2 （PI-RADS v2） scoring system improves the diagnostic accuracy of mp-MRI of the prostate compared with PI-RADS v1.Methods：This retrospective study was approved by the institutional review board.A total of 401 consecutive patients,with clinically suspicious Pca undergoing 3.0 T mp-MRI （T2-weighted imaging ＋ diffusion-weighted imaging ＋ DCE） before transrectal ultrasound-guided biopsy between June 2013 and July 2015,were included in the study.All patients were scored using the 5-point PI-RADS scoring system based on either PI-RADS v1 or v2.Receiver operating characteristics were calculated for statistical analysis.Sensitivity,specificity,and diagnostic accuracy were compared using McNemar＇s test.Results：Pca was present in 150 of 401 （37.41%） patients.When we pooled data from both peripheral zone （PZ） and transition zone （TZ）,the areas under the curve were 0.889 for PI-RADS v1 and 0.942 for v2 （P =0.0001）.Maximal accuracy was achieved with a score threshold of 4.At this threshold,in the PZ,similar sensitivity,specificity,and accuracy were achieved with v 1 and v2 （all P 〉 0.05）.In the TZ,sensitivity was higher for v2 than for v1 （96.36% vs.76.36%,P =0.003）,specificity was similar for v2 and v1 （90.24% vs.84.15%,P =0.227）,and accuracy was higher for v2 than for v1 （92.70% vs.81.02%,P =0.002）.Conclusions：Both v1 and v2 showed good diagnostic performance for the detection of Pca.However,in the TZ,the performance was better with v2 than with v1.

Evaluation of the Prostate Imaging Reporting and Data System for Magnetic Resonance Imaging Diagnosis of Prostate Cancer in Patients with Prostate-specific Antigen 〈20 ng/ml

Background： The European Society of Urogenital Radiology has built the Prostate Imaging Reporting and Data System （PI-RADS） for standardizing the diagnosis of prostate cancer （PCa）. This study evaluated the PI-RADS diagnosis method in patients with prostate-specific antigen （PSA） 〈20 ng/ml. Methods： A total of 133 patients with PSA 〈20 ng/ml were prospectively recruited. T2-weighted （T2WI） and diffusion-weighted （DWI） magnetic resonance images of the prostate were acquired before a 12-core transrectal prostate biopsy. Each patient＇s peripheral zone was divided into six regions on the images; each region corresponded to two of the 12 biopsy cores. T2WI, DWI, and T2W1 ＋ DWI scores were computed according to PI-RADS. The diagnostic accuracy of the PI-RADS score was evaluated using histopathology of prostate biopsies as the reference standard. Results： PCa was histologically diagnosed in 169 （21.2%） regions. Increased PI-RADS score correlated positively with increased cancer detection rate. The cancer detection rate for scores 1 to 5 was 2.8%, 15.0%, 34.6%, 52.6%, and 88.9%, respectively, using T2W1 and 12.0%, 20.2%, 48.0%, 85.7%, and 93.3%, respectively, using DWI. For T2WI ＋ DWI, the cancer detection rate was 1.5% （score 2）, 13.5% （scores 3-4）, 41.3% （scores 5-6）, 75.9% （scores 7-8）, and 92.3% （scores 9-10）. The area under the curve for cancer detection was 0.700 （T2WI）, 0.735 （DWI） and 0.749 （T2WI ＋ DWI）. The sensitivity and specificity were 53.8% and 89.2%, respectively, when The summed score ofT2Wl ＋ DWI

Contrast-enhanced ultrasound in association with serum biomarkers for differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma

BACKGROUND Combined hepatocellular-cholangiocarcinoma(CHC)is a rare type of primary liver cancer.Due to its complex histopathological characteristics,the imaging features of CHC can overlap with those of hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(ICC).AIM To investigate the possibility and efficacy of differentiating CHC from HCC and ICC by using contrast-enhanced ultrasound(CEUS)Liver Imaging Reporting and Data System(LI-RADS)and tumor biomarkers.METHODS Between January 2016 and December 2019,patients with histologically confirmed CHC,ICC and HCC with chronic liver disease were enrolled.The diagnostic formula for CHC was as follows:(1)LR-5 or LR-M with elevated alphafetoprotein(AFP)and carbohydrate antigen 19-9(CA19-9);(2)LR-M with elevated AFP and normal CA19-9;or(3)LR-5 with elevated CA19-9 and normal AFP.The sensitivity,specificity,accuracy and area under the receiver operating characteristic curve were calculated to determine the diagnostic value of the criteria.RESULTS After propensity score matching,134 patients(mean age of 51.4±9.4 years,108 men)were enrolled,including 35 CHC,29 ICC and 70 HCC patients.Based on CEUS LI-RADS classification,74.3%(26/35)and 25.7%(9/35)of CHC lesions were assessed as LR-M and LR-5,respectively.The rates of elevated AFP and CA19-9 in CHC patients were 51.4%and 11.4%,respectively,and simultaneous elevations of AFP and CA19-9 were found in 8.6%(3/35)of CHC patients.The sensitivity,specificity,positive predictive value,negative predictive value,accuracy and area under the receiver operating characteristic curve of the aforementioned diagnostic criteria for discriminating CHC from HCC and ICC were 40.0%,89.9%,58.3%,80.9%,76.9%and 0.649,respectively.When considering the reported prevalence of CHC(0.4%-14.2%),the positive predictive value and NPV were revised to 1.6%-39.6%and 90.1%-99.7%,respectively.CONCLUSION CHCs are more likely to be classified as LR-M than LR-5 by CEUS LI-RADS.The combination of the CEUS LI-RADS classification with serum tumor markers shows high specificity but low sensitivity for the diagnosis of CHC.Moreover,CHC could be confidently excluded with high NPV.

Using the Prostate Imaging Reporting and Data System version 2 （PI-RIDS v2） to detect prostate cancer can prevent unnecessary biopsies and invasive treatment

Prostate cancer （PCa） is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） to classify men with PCa, clinically significant PCa （CSPCa）, or no PCa, especially among those with serum total prostate-specific antigen （tPSA） levels in the ＂gray zone＂ （4-10 ng ml-1）. A total of 308 patients （355 lesions） were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density （PSAD） were independent predictors of PCa and CSPCa. A PI-RADS v2 score L≥4 provided high negative predictive values （91.39% for PCa and 95.69% for CSPCa）. A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group （PI-RADS score = 5 and PSAD L≥0 15 ng ml-1 cm-3, with tPSA in the gray zone, or PI-RADS score L≥4 with high tPSA level） with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.

Can contrast enhanced ultrasound differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma?

BACKGROUND Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(ICC)differ in treatment and prognosis,warranting an effective differential diagnosis between them.The LR-M category in the contrast-enhanced ultrasound(CEUS)liver imaging reporting and data system(LI-RADS)was set up for lesions that are malignant but not specific to HCC.However,a substantial number of HCC cases in this category elevated the diagnostic challenge.AIM To investigate the possibility and efficacy of differentiating ICC from HCC classified in the LR-M category according to the CEUS LI-RADS.METHODS Patients with complete CEUS records together with pathologically confirmed ICC and LR-M HCC(HCC classified in the CEUS LI-RADS LR-M category)between January 2015 and October 2018 were included in this retrospective study.Each ICC was assigned a category as per the CEUS LI-RADS.The enhancement pattern,washout timing,and washout degree between the ICC and LR-M HCC were compared using theχ2 test.Logistic regression analysis was used for prediction of ICC.Receiver operating characteristic(ROC)curve analysis was used to investigate the possibility of LR-M criteria and serum tumor markers in differentiating ICC from LR-M HCC.RESULTS A total of 228 nodules(99 ICCs and 129 LR-M HCCs)in 228 patients were included.The mean sizes of ICC and LR-M HCC were 6.3±2.8 cm and 5.5±3.5 cm,respectively(P=0.03).Peripheral rim-like arterial phase hyperenhancement(APHE)was detected in 50.5%(50/99)of ICCs vs 16.3%(21/129)of LR-M HCCs(P<0.001).Early washout was found in 93.4%(93/99)of ICCs vs 96.1%(124/129)of LR-M HCCs(P>0.05).Marked washout was observed in 23.2%(23/99)of ICCs and 7.8%(10/129)of LR-M HCCs(P=0.002),while this feature did not show up alone either in ICC or LR-M HCC.Homogeneous hyperenhancement was detected in 15.2%(15/99)of ICCs and 37.2%(48/129)of LR-M HCCs(P<0.001).The logistic regression showed that rim APHE,carbohydrate antigen 19-9(CA 19-9),and alpha fetoprotein(AFP)had significant correlations with ICC(r=1.251,3.074,and-2.767,respectively;P<0.01).Rim APHE presented the best enhancement pattern for diagnosing ICC,with an area under the ROC curve(AUC)of 0.70,sensitivity of 70.4%,and specificity of 68.8%.When rim hyperenhancement was coupled with elevated CA 19-9 and normal AFP,the AUC and sensitivity improved to 0.82 and 100%,respectively,with specificity decreasing to 63.9%.CONCLUSION Rim APHE is a key predictor for differentiating ICC from LR-M HCC.Rim APHE plus elevated CA 19-9 and normal AFP is a strong predictor of ICC rather than LR-M HCC.Early washout and marked washout have limited value for the differentiation between the two entities.

Novel model combining contrast-enhanced ultrasound with serology predicts hepatocellular carcinoma recurrence after hepatectomy

BACKGROUND Surgery is the primary curative option in patients with hepatocellular carcinoma(HCC).However,recurrence within 2 years is observed in 30%–50%of patients,being a major cause of mortality.AIM To construct and verify a non-invasive prediction model combining contrastenhanced ultrasound(CEUS)with serology biomarkers to predict the early recurrence of HCC.METHODS Records of 744 consecutive patients undergoing first-line curative surgery for HCC in one institution from 2016–2018 were reviewed,and 292 local patients were selected for analysis.General characteristics including gender and age,CEUS liver imaging reporting and data system(LIRADS)parameters including wash-in time,wash-in type,wash-out time,and wash-out type,and serology biomarkers including alanine aminotransferase,aspartate aminotransferase,platelets,and alpha-fetoprotein(AFP)were collected.Univariate analysis and multivariate Cox proportional hazards regression model were used to evaluate the independent prognostic factors for tumor recurrence.Then a nomogram called CEUS model was constructed.The CEUS model was then used to predict recurrence at 6 mo,12 mo,and 24 mo,the cut-off value was calculate by X-tile,and each C-index was calculated.Then Kaplan-Meier curve was compared by logrank test.The calibration curves of each time were depicted.RESULTS A nomogram predicting early recurrence(ER),named CEUS model,was formulated based on the results of the multivariate Cox regression analysis.This nomogram incorporated tumor diameter,preoperative AFP level,and LIRADS,and the hazard ratio was 1.123(95%confidence interval[CI]:1.041-1.211),1.547(95%CI:1.245-1.922),and 1.428(95%CI:1.059-1.925),respectively.The cut-off value at 6 mo,12 mo,and 24 mo was 100,80,and 50,and the C-index was 0.748(95%CI:0.683-0.813),0.762(95%CI:0.704-0.820),and 0.762(95%CI:0.706-0.819),respectively.The model showed satisfactory results,and the calibration at 6 mo was desirable;however,the calibration at 12 and 24 mo should be improved.CONCLUSION The CEUS model enables the well-calibrated individualized prediction of ER before surgery and may represent a novel tool for biomarker research and individual counseling.