Two-Dimensional Perovskite Single Crystals for High-Performance X-ray Imaging and Exploring MeV X-ray Detection

Scintillation semiconductors play increasingly important medical diagnosis and industrial inspection roles.Recently,two-dimensional(2D)perovskites have been shown to be promising materials for medical X-ray imaging,but they are mostly used in low-energy(≤130 keV)regions.Direct detection of MeV X-rays,which ensure thorough penetration of the thick shell walls of containers,trucks,and aircraft,is also highly desired in practical industrial applications.Unfortunately,scintillation semiconductors for high-energy X-ray detection are currently scarce.Here,This paper reports a 2D(C_(4)H_(9)NH_(3))_(2)PbBr_(4)single crystal with outstanding sensitivity and stability toward X-ray radiation that provides an ultra-wide detectable X-ray range of between 8.20 nGy_(air)s^(-1)(50 keV)and 15.24 mGy_(air)s^(-1)(9 MeV).The(C_(4)H_(9)NH_(3))_(2)PbBr_(4)single-crystal detector with a vertical structure is used for high-performance X-ray imaging,delivering a good spatial resolution of 4.3 Ip mm^(-1)in a plane-scan imaging system.Low ionic migration in the 2D perovskite enables the vertical device to be operated with hundreds of keV to MeV X-ray radiation at high bias voltages,leading to a sensitivity of 46.90μC Gy_(air)-1 cm^(-2)(-1.16 Vμm^(-1))with 9 MeV X-ray radiation,demonstrating that 2D perovskites have enormous potential for high-energy industrial applications.

A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effectivetreatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breastcancer fromultrasound images. The primary challenge is accurately distinguishing between malignant and benigntumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentationand classification. The main objective of the research paper is to develop an advanced methodology for breastultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, andmachine learning-based classification. A unique approach is introduced that combines Enhanced Speckle ReducedAnisotropic Diffusion (SRAD) filters for speckle noise reduction, U-NET-based segmentation, Genetic Algorithm(GA)-based feature selection, and Random Forest and Bagging Tree classifiers, resulting in a novel and efficientmodel. To test and validate the hybrid model, rigorous experimentations were performed and results state thatthe proposed hybrid model achieved accuracy rate of 99.9%, outperforming other existing techniques, and alsosignificantly reducing computational time. This enhanced accuracy, along with improved sensitivity and specificity,makes the proposed hybrid model a valuable addition to CAD systems in breast cancer diagnosis, ultimatelyenhancing diagnostic accuracy in clinical applications.

Structured magnetic resonance imaging and endoanal ultrasound anal fistulas reporting template(SMART):An interdisciplinary Delphi consensus

BACKGROUND There is still considerable heterogeneity regarding which features of cryptoglandular anal fistula on magnetic resonance imaging(MRI)and endoanal ultrasound(EAUS)are relevant to surgical decision-making.As a con-sequence,the quality and completeness of the report are highly dependent on the training and experience of the examiners.AIM To develop a structured MRI and EAUS template(SMART)reporting the minimum dataset of information for the treatment of anal fistulas.METHODS This modified Delphi survey based on the RAND-UCLA appropriateness for consensus-building was conducted between May and August 2023.One hundred and fifty-one articles selected from a systematic review of the lite-rature formed the database to generate the evidence-based statements for the Delphi study.Fourteen questions were anonymously voted by an interdisciplinary multidisciplinary group for a maximum of three iterative rounds.The degree of agreement was scored on a numeric 0–10 scale.Group consensus was defined as a score≥8 for≥80%of the panelists.RESULTS Eleven scientific societies(3 radiological and 8 surgical)endorsed the study.After three rounds of voting,the experts(69 colorectal surgeons,23 radiologists,2 anatomists,and 1 gastroenterologist)achieved consensus for 12 of 14 statements(85.7%).Based on the results of the Delphi process,the six following features of anal fistulas were included in the SMART:Primary tract,secondary extension,internal opening,presence of collection,coexisting le-sions,and sphincters morphology.CONCLUSION A structured template,SMART,was developed to standardize imaging reporting of fistula-in-ano in a simple,systematic,time-efficient way,providing the minimum dataset of information and visual diagram useful to refer-ring physicians.

The Application Value of Ultrasound Imaging in the Differential Diagnosis of Benign and Malignant Breast Nodules of BI-RADS 3 and Above

Objective:To explore the diagnostic value of ultrasound imaging for breast nodules of breast imaging-reporting and data system(BI-RADS)category 3 and above.Methods:From June 2021 to July 2022,163 patients with breast nodules of BI-RADS 3 or above were selected as the research subjects.After pathological diagnosis,24 cases were malignant breast nodules of BI-RADS 3 or above,while 139 cases were benign breast nodules of BI-RADS 3 or above.The diagnosis rate of malignant and benign breast nodules of BI-RADS 3 or above,including 95%CI,was observed and analyzed.Results:The malignant and benign detection rates of conventional ultrasound were 88.63%and 75.00%,respectively,and the malignant and benign detection rates of ultrasound imaging were 93.18%and 87.50%,respectively,with 95%CIs greater than 0.7.Conclusion:Ultrasound imaging can help improve the diagnostic accuracy of benign and malignant breast nodules of BI-RADS 3 and above and reduce the misdiagnosis rate.

Data augmentation of ultrasound imaging for non-invasive white blood cell in vitro peritoneal dialysis

The limited amount of data in the healthcare domain and the necessity of training samples for increased performance of deep learning models is a recurrent challenge,especially in medical imaging.Newborn Solutions aims to enhance its non-invasive white blood cell counting device,Neosonics,by creating synthetic in vitro ultrasound images to facilitate a more efficient image generation process.This study addresses the data scarcity issue by designing and evaluating a continuous scalar conditional Generative Adversarial Network(GAN)to augment in vitro peritoneal dialysis ultrasound images,increasing both the volume and variability of training samples.The developed GAN architecture incorporates novel design features:varying kernel sizes in the generator’s transposed convolutional layers and a latent intermediate space,projecting noise and condition values for enhanced image resolution and specificity.The experimental results show that the GAN successfully generated diverse images of high visual quality,closely resembling real ultrasound samples.While visual results were promising,the use of GAN-based data augmentation did not consistently improve the performance of an image regressor in distinguishing features specific to varied white blood cell concentrations.Ultimately,while this continuous scalar conditional GAN model made strides in generating realistic images,further work is needed to achieve consistent gains in regression tasks,aiming for robust model generalization.

Prenatal Diagnosis of Sirenomelia by Two-Dimensional and Three-Dimensional Skeletal Imaging Ultrasound

Summary： This study sought to evaluate the contribution of two-dimensional ultrasound （2D-US） and three-dimensional skeletal imaging ultrasound （3D-SUIS） in the prenatal diagnosis of sirenomelia. Be- tween September 2010 and April 2014, a prospective study was conducted in a single referral center using 3D-SU1S performed after 2D-US in 10 cases of sirenomelia. Diagnostic accuracy and detailed findings were compared with postnatal three-dimensional helical computed tomography （3D-HCT）, radiological findings and autopsy. Pregnancy was terminated in all 10 sirenomelia cases, including 9 singletons and I conjoined twin pregnancy, for a total of 5 males and 5 females. These cases of sirenomelia were deter- mined by autopsy and/or chromosomal examination. Initial 2D-US showed that there were 10 cases of oligohydranmios, bilateral renal agenesis, bladder agenesis, single umbilical artery, fusion of the lower limbs and spinal abnormalities; 8 cases of dipus or monopus; 2 cases of apus; and 8 cases of cardiac abnormalities. Subsequent 3D-SUIS showed that there were 9 cases of scoliosis, l0 cases of sacrococ- cygeal vertebra dysplasia, 3 cases of hemivertebra, 1 case of vertebral fusion, 3 cases of spina bifida, and 5 cases of rib abnormalities. 3D-SUIS identified significantly more skeletal abnormalities than did 2D-US, and its accuracy was 79.5% （70/88） compared with 3D-HCT and radiography. 3D-SUIS seems to be a useful complementary method to 2D-US and may improve the accuracy of identifying prenatal skeletal abnormalities related to sirenomelia.

Imaging and endoscopic tools in pediatric inflammatory bowel disease: What’s new?

Pediatric inflammatory bowel disease(IBD)is a chronic inflammatory disorder,with increasing incidence and prevalence worldwide.There have been recent advances in imaging and endoscopic technology for disease diagnosis,treatment,and monitoring.Intestinal ultrasound,including transabdominal,transperineal,and endoscopic,has been emerging for the assessment of transmural bowel inflammation and disease complications(e.g.,fistula,abscess).Aside from surgery,IBD-related intestinal strictures now have endoscopic treatment options including through-the-scope balloon dilatation,injection,and needle knife stricturotomy and new evaluation tools such as endoscopic functional lumen imaging probe.Unsedated transnasal endoscopy may have a role in patients with upper gastrointestinal Crohn’s disease or those with IBD with new upper gastrointestinal symptoms.Improvements to dysplasia screening in pediatric patients with longstanding colonic disease or primary sclerosing cholangitis hold promise with the addition of virtual chromoendoscopy and ongoing research in the field of artificial intelligence-assisted endoscopic detection.Artificial intelligence and machine learning is a rapidly evolving field,with goals of further personalizing IBD diagnosis and treatment selection as well as prognostication.This review summarized these advancements,focusing on pediatric patients with IBD.

A Modified CycleGAN for Multi-Organ Ultrasound Image Enhancement via Unpaired Pre-Training

Handheld ultrasound devices are known for their portability and affordability,making them widely utilized in underdeveloped areas and community healthcare for rapid diagnosis and early screening.However,the image quality of handheld ultrasound devices is not always satisfactory due to the limited equipment size,which hinders accurate diagnoses by doctors.At the same time,paired ultrasound images are difficult to obtain from the clinic because imaging process is complicated.Therefore,we propose a modified cycle generative adversarial network(cycleGAN) for ultrasound image enhancement from multiple organs via unpaired pre-training.We introduce an ultrasound image pre-training method that does not require paired images,alleviating the requirement for large-scale paired datasets.We also propose an enhanced block with different structures in the pre-training and fine-tuning phases,which can help achieve the goals of different training phases.To improve the robustness of the model,we add Gaussian noise to the training images as data augmentation.Our approach is effective in obtaining the best quantitative evaluation results using a small number of parameters and less training costs to improve the quality of handheld ultrasound devices.

Automatic Fetal Segmentation Designed on Computer-Aided Detection with Ultrasound Images

In the present research,we describe a computer-aided detection(CAD)method aimed at automatic fetal head circumference(HC)measurement in 2D ultrasonography pictures during all trimesters of pregnancy.The HC might be utilized toward determining gestational age and tracking fetal development.This automated approach is particularly valuable in low-resource settings where access to trained sonographers is limited.The CAD system is divided into two steps:to begin,Haar-like characteristics were extracted from ultrasound pictures in order to train a classifier using random forests to find the fetal skull.We identified the HC using dynamic programming,an elliptical fit,and a Hough transform.The computer-aided detection(CAD)program was well-trained on 999 pictures(HC18 challenge data source),and then verified on 335 photos from all trimesters in an independent test set.A skilled sonographer and an expert in medicine personally marked the test set.We used the crown-rump length(CRL)measurement to calculate the reference gestational age(GA).In the first,second,and third trimesters,the median difference between the standard GA and the GA calculated by the skilled sonographer stayed at 0.7±2.7,0.0±4.5,and 2.0±12.0 days,respectively.The regular duration variance between the baseline GA and the health investigator’s GA remained 1.5±3.0,1.9±5.0,and 4.0±14 a couple of days.The mean variance between the standard GA and the CAD system’s GA remained between 0.5 and 5.0,with an additional variation of 2.9 to 12.5 days.The outcomes reveal that the computer-aided detection(CAD)program outperforms an expert sonographer.When paired with the classifications reported in the literature,the provided system achieves results that are comparable or even better.We have assessed and scheduled this computerized approach for HC evaluation,which includes information from all trimesters of gestation.

The Application Progress of Skin Imaging Technology in Psoriasis

Skin imaging technologies such as dermoscopy, high-frequency ultrasound, reflective confocal microscopy and optical coherence tomography are developing rapidly in clinical application. Skin imaging technology can improve clinical diagnosis rate, and its non-invasiveness and repeatability make it occupy an irreplaceable position in clinical diagnosis. With the “booming development” of medical technology, skin imaging technology can improve clinical diagnosis rate. Researchers have made significant advances in assisting clinical diagnosis, prediction, and treatment of disease. This article reviews the application and progress of skin imaging in the diagnosis of psoriasis.

Recent Research Advances in Imaging of Prostate Cancer

Imaging study plays a crucial role in the diagnosis of prostate cancer. As early screening and management of prostate cancer has evolved over the past decade, research is now focusing on how to detect clinically significant prostate cancer and avoid overdiagnosis accurately. This article provides an overview of recent advances in imaging in prostate cancer diagnosis, including new ultrasound imaging techniques, positron emission computed tomography, multiparametric magnetic resonance imaging, and emerging areas such as imaging histology, by systematically reviewing and summarizing the existing literature.

Quantitative ultrasound brain imaging with multiscale deconvolutional waveform inversion

High-resolution images of human brain are critical for monitoring the neurological conditions in a portable and safe manner.Sound speed mapping of brain tissues provides unique information for such a purpose.In addition,it is particularly important for building digital human acoustic models,which form a reference for future ultrasound research.Conventional ultrasound modalities can hardly image the human brain at high spatial resolution inside the skull due to the strong impedance contrast between hard tissue and soft tissue.We carry out numerical experiments to demonstrate that the time-domain waveform inversion technique,originating from the geophysics community,is promising to deliver quantitative images of human brains within the skull at a sub-millimeter level by using ultra-sound signals.The successful implementation of such an approach to brain imaging requires the following items:signals of sub-megahertz frequencies transmitting across the inside of skull,an accurate numerical wave equation solver simulating the wave propagation,and well-designed inversion schemes to reconstruct the physical parameters of targeted model based on the optimization theory.Here we propose an innovative modality of multiscale deconvolutional waveform inversion that improves ultrasound imaging resolution,by evaluating the similarity between synthetic data and observed data through using limited length Wiener filter.We implement the proposed approach to iteratively update the parametric models of the human brain.The quantitative imaging method paves the way for building the accurate acoustic brain model to diagnose associated diseases,in a potentially more portable,more dynamic and safer way than magnetic resonance imaging and x-ray computed tomography.

Value of ultrasound and magnetic resonance imaging combined with tumor markers in the diagnosis of ovarian tumors

BACKGROUND Compare the diagnostic performance of ultrasound(US),magnetic resonance imaging(MRI),and serum tumor markers alone or in combination for detecting ovarian tumors.AIM To investigate the diagnostic value of US,MRI combined with tumor markers in ovarian tumors.METHODS The data of 110 patients with ovarian tumors,confirmed by surgery and pathology,were collected in our hospital from February 2018 to May 2023.The dataset included 60 cases of benign tumors and 50 cases of malignant tumors.Prior to surgery,all patients underwent preoperative US and MRI examinations,as well as serum tumor marker tests[carbohydrate antigen 125(CA125),human epididymis protein 4(HE4)].The aim of the study was to compare the diagnostic performance of these three methods individually and in combination for ovarian tumors.RESULTS This study found statistically significant differences in the ultrasonic imaging characteristics between benign and malignant tumors.These differences include echo characteristics,presence or absence of a capsule,blood flow resistance index,clear tumor shape,and blood flow signal display rate(P<0.05).The apparent diffusion coefficient values of the solid and cystic parts in benign tumors were found to be higher compared to malignant tumors(P<0.05).Additionally,the time-intensity curve image features of benign and malignant tumors showed significant statistical differences(P<0.05).The levels of serum CA125 and HE4 in benign tumors were lower than those in malignant tumors(P<0.05).The combined use of US,MRI,and tumor markers in the diagnosis of ovarian tumors demonstrates higher accuracy,sensitivity,and specificity compared to using each method individually(P<0.05).CONCLUSION US,MRI,and tumor markers each have their own advantages and disadvantages when it comes to diagnosing ovarian tumors.However,by combining these three methods,we can significantly enhance the accuracy of ovarian tumor diagnosis,enabling early detection and identification of the tumor’s nature,and providing valuable guidance for clinical treatment.

Early prediction of myocardial viability after acute myocardial infarction by two-dimensional speckle tracking imaging

Background Identifying the transmural extent of myocardial necrosis and the degree of myocardial viability in acute myocardial infarction （AMI） is important clinically. The aim of this study was to assess myocardial viability using two-dimensional speckle tracking imaging （2D-STI） in patients with AMI. Methods 2D-STI was performed at initial presentation, three days, and six months after primary percutaneous coronary intervention （PCI） in 30 patients with AMI, who had a left anterior descending coronary artery （LAD） culprit lesion. In addition, 20 patients who had minimal stenotic lesions （〈 30% stenosis） on coronary angiography were also included in the control group. At six months dobutamine echocardiography was performed for viability assessment in seven segments of the LAD territory. According to the recovery of wall motion abnormality, segments were classified as viable or non-viable. Results A total of 131 segments were viable, and 44 were nonviable. Multivariate analysis revealed significant differences between the viable and nonviable segments in the peak systolic strain, the peak systolic strain rate at initial presentation, and peak systolic strain rate three days after primary PCI. Among these, the initial peak systolic strain rate had the highest predictive value for myocardial viability （hazard ratio： 31.22, P 〈 0.01）. Conclusions 2D-STI is feasible for assessing myocardial viability, and the peak systolic strain rate might be the most reliable predictor of myocardial viability in patients with AMI.

Visibility enhancement in two-dimensional lensless ghost imaging with true thermal light

We report an experimental demonstration of two-dimensional（2D） lensless ghost imaging with true thermal light. An electrodeless discharge lamp with a higher light intensity than the hollow cathode lamp used before is employed as a light source. The main problem encountered by the 2D lensless ghost imaging with true thermal light is that its coherence time is much shorter than the resolution time of the detection system. To overcome this difficulty we derive a method based on the relationship between the true and measured values of the second-order optical intensity correlation, by which means the visibility of the ghost image can be dramatically enhanced. This method would also be suitable for ghost imaging with natural sunlight.

Value of two-dimensional speckle tracking imaging in quantitative assessment of left ventricular function in patients with OSAS

Objective: To research the clinical application of two-dimensional speckle tracking imaging (2D-STI) in quantitative assessment of left ventricular function in patients with obstructive sleep apnea-hypopnea syndrome (OSAS). Method: From July 2016 to December 2018, 86 patients with OSAS were selected as OSAS group. According to sleep apnea hypopnea index (AHI), they were divided into mild OSAS group (24 cases), moderate OSAS group (29 cases) and severe OSAS group (33 cases). Another 50 healthy volunteers who underwent physical examination in our hospital during the same period were selected as the control group. The left ventricular function of all patients was quantitatively assessed by 2D-STI. The left ventricular function of all patients was quantitatively assessed by 2D-STI. The results of routine echocardiography and left ventricular global strain parameters of the OSAS group, the control group and the OSAS patients with different severity were compared and analyzed. Result: There were no significant differences in the levels of left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDd), left ventricular end systolic diameter (LVESd) between the two groups and OSAS patients with different severity (P>0.05). The levels of IVST, LVPW and LVMI in the OSAS group were significantly higher than those in the control group, the levels of end-diastolic interventricular septal thickness (IVS), left ventricular posterior wall thickness (LVPW), left ventricular mass index (LVMI) in the severe OSAS group were significantly higher than those in the mild and moderate OSAS group, and the levels of IVST, LVPW and LVMI in the moderate OSAS group were significantly higher than those in the mild OSAS group, there were significant differences between groups (P<0.05). The levels of GLS, GRS and GCS in the OSAS group were significantly lower than those in the control group (P<0.05). GLS, GRS and GCS levels in the severe OSAS group were significantly lower than those in the mild OSAS group and the moderate OSAS group, while the levels of global longitudinal strain (GLS), global radial strain (GRS) and global circumferential strain (GCS) in the moderate OSAS group were significantly lower than those in the mild OSAS group (P<0.05). Conclusion: The left ventricular systolic function of OSAS patients is obviously impaired. Left ventricular function in OSAS patients can be assessed timely and accurately by two-dimensional speckle tracking imaging.

Non-invasive evaluation of liver steatosis with imaging modalities:New techniques and applications

In the world,nonalcoholic fatty liver disease(NAFLD)accounts for majority of diffuse hepatic diseases.Notably,substantial liver fat accumulation can trigger and accelerate hepatic fibrosis,thus contributing to disease progression.Moreover,the presence of NAFLD not only puts adverse influences for liver but is also associated with an increased risk of type 2 diabetes and cardiovascular diseases.Therefore,early detection and quantified measurement of hepatic fat content are of great importance.Liver biopsy is currently the most accurate method for the evaluation of hepatic steatosis.However,liver biopsy has several limitations,namely,its invasiveness,sampling error,high cost and moderate intraobserver and interobserver reproducibility.Recently,various quantitative imaging techniques have been developed for the diagnosis and quantified measurement of hepatic fat content,including ultrasound-or magnetic resonancebased methods.These quantitative imaging techniques can provide objective continuous metrics associated with liver fat content and be recorded for comparison when patients receive check-ups to evaluate changes in liver fat content,which is useful for longitudinal follow-up.In this review,we introduce several imaging techniques and describe their diagnostic performance for the diagnosis and quantified measurement of hepatic fat content.

Basic physical, acoustic properties, and in vitro ultrasound imaging enhancement of the lipid-coated microbubbles

Aim To research on a stable microbubble with good acoustic properties and excellent imaging enhancing effect, and to make it to be a promising agent for the enhancement of ultrasound imaging in the ultrasound diagnosis of cardiovascular system diseases. Methods The morphology, size and zeta potential of lipid-coated microbubbles （LCM）, the acoustic properties of backscatter, and the second harmonic scatter of LCM were determined. Furthermore, the relationship between the concentrations and the amplitude values of the second harmonic was investigated by testing the intensities of the second harmonic at different concentrations. The imaging effect of LCM was also studied in vitro. Results The mean diameter of LCM was 3.38 μm with 95% of the bubbles under 5 μm. The scatter signal generated by microbubbles was observed under different concentrations in the bistatic modes while the position of transmitting transducer and receiving transducer was orthogonal. The intensity of the second harmonic scatter fell with the decrease of microbubble concentration. The increase rate of the second harmonic amplitude values generated by the microbubbles versus that by physiological saline was linear with the natural logarithm of bubble concentrations. The LCM could enhance the ultrasound image of thrombus. Conclusion The LCM exhibited good physical state and acoustic properties, which could increase the imaging quality.

Vault predicting after implantable collamer lens implantation using random forest network based on different features in ultrasound biomicroscopy images

AIM:To analyze ultrasound biomicroscopy(UBM)images using random forest network to find new features to make predictions about vault after implantable collamer lens(ICL)implantation.METHODS:A total of 450 UBM images were collected from the Lixiang Eye Hospital to provide the patient’s preoperative parameters as well as the vault of the ICL after implantation.The vault was set as the prediction target,and the input elements were mainly ciliary sulcus shape parameters,which included 6 angular parameters,2 area parameters,and 2 parameters,distance between ciliary sulci,and anterior chamber height.A random forest regression model was applied to predict the vault,with the number of base estimators(n_estimators)of 2000,the maximum tree depth(max_depth)of 17,the number of tree features(max_features)of Auto,and the random state(random_state)of 40.0.RESULTS:Among the parameters selected in this study,the distance between ciliary sulci had a greater importance proportion,reaching 52%before parameter optimization is performed,and other features had less influence,with an importance proportion of about 5%.The importance of the distance between the ciliary sulci increased to 53% after parameter optimization,and the importance of angle 3 and area 1 increased to 5% and 8%respectively,while the importance of the other parameters remained unchanged,and the distance between the ciliary sulci was considered the most important feature.Other features,although they accounted for a relatively small proportion,also had an impact on the vault prediction.After parameter optimization,the best prediction results were obtained,with a predicted mean value of 763.688μm and an actual mean value of 776.9304μm.The R²was 0.4456 and the root mean square error was 201.5166.CONCLUSION:A study based on UBM images using random forest network can be performed for prediction of the vault after ICL implantation and can provide some reference for ICL size selection.

Contrast-enhanced ultrasound improved performance of breast imaging reporting and data system evaluation of critical breast lesions

AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesions classified as BI-RADS 4 on conventional ultrasound were evaluated. CEUS was performed within one week before core needle biopsy or surgical resection and a revised BI-RADS classification was assigned based on 10 CEUS imaging characteristics. Receiver operating characteristic curve analysis was then conducted to evaluate the diagnostic performance of CEUS-based BI-RADS assignment with pathological examination as reference criteria. RESULTS: The CEUS-based BI-RADS evaluation classified 116/235(49.36%) lesions into category 3, 20(8.51%), 13(5.53%) and 12(5.11%) lesions into categories 4A, 4B and 4C, respectively, and 74(31.49%) into category 5. Selecting CEUS-based BI-RADS category 4A as an appropriate cut-off gave sensitivity and specificity values of 85.4% and 87.8%, respectively, for the diagnosisof malignant disease. The cancer-to-biopsy yield was 73.11% with CEUS-based BI-RADS 4A selected as the biopsy threshold compared with 40.85% otherwise, while the biopsy rate was only 42.13% compared with 100% otherwise. Overall, only 4.68% of invasive cancers were misdiagnosed.CONCLUSION: This pilot study suggests that evaluation of BI-RADS 4 breast lesions with CEUS results in reduced biopsy rates and increased cancer-to-biopsy yields.