Laser spectroscopy imaging technique coupled withnanomaterials for cancer diagnosis: A review

Laser spectroscopic imaging techniques have received tremendous attention in the-eld of cancer diagnosis due to their high sensitivity,high temporal resolution,and short acquisition time.However,the limited tissue penetration of the laser is still a challenge for the in vivo diagnosis of deep-seated lesions.Nanomaterials have been universally integrated with spectroscopic imaging techniques for deeper cancer diagnosis in vivo.The components,morphology,and sizes of nanomaterials are delicately designed,which could realize cancer diagnosis in vivo or in situ.Considering the enhanced signal emitting from the nanomaterials,we emphasized their combination with spectroscopic imaging techniques for cancer diagnosis,like the surface-enhanced Raman scattering(SERS),photoacoustic,fluorescence,and laser-induced breakdown spectroscopy(LIBS).Applications ofthe above spectroscopic techniques offer new prospectsfor cancer diagnosis.

Activatable fluorescent probes for imaging and diagnosis of rheumatoid arthritis

Rheumatoid arthritis(RA)is a systemic autoimmune disease that is primarily manifested as synovitis and polyarticular opacity and typically leads to serious joint damage and irreversible disability,thus adversely affecting locomotion ability and life quality.Consequently,good prognosis heavily relies on the early diagnosis and effective therapeutic monitoring of RA.Activatable fluorescent probes play vital roles in the detection and imaging of biomarkers for disease diagnosis and in vivo imaging.Herein,we review the fluorescent probes developed for the detection and imaging of RA biomarkers,namely reactive oxygen/nitrogen species(hypochlorous acid,peroxynitrite,hydroxyl radical,nitroxyl),pH,and cysteine,and address the related challenges and prospects to inspire the design of novel fluorescent probes and the improvement of their performance in RA studies.

Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging

BACKGROUND The liver imaging reporting and data system(LI-RADS)diagnostic table has 15 cells and is too complex.The diagnostic performance of LI-RADS for hepatocellular carcinoma(HCC)is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging(EOB-MRI).AIM To evaluate the ability of the simplified LI-RADS(sLI-RADS)to diagnose HCC on EOB-MRI.METHODS A total of 331 patients with 356 hepatic observations were retrospectively analysed.The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLIRADS.The algorithms of sLI-RADS A-D are as follows:The single threshold for sLI-RADS A and B was 10 mm,that is,classified observations≥10mm using an algorithm of 10-19 mm observations(sLI-RADS A)and≥20 mm observations(sLI-RADS B)in the diagnosis table of LI-RADS v2018,respectively,while the classification algorithm remained unchanged for observations<10 mm;the single threshold for sLI-RADS C and D was 20 mm,that is,for<20 mm observations,the algorithms for<10 mm observations(sLI-RADS C)and 10-19 mm observations(sLI-RADS D)were used,respectively,while the algorithm remained unchanged for observations≥20 mm.With hepatobiliary phase(HBP)hypointensity as a major feature(MF),the final sLI-RADS(F-sLI-RADS)was formed according to the optimal sLI-RADS,and its diagnostic performance was evaluated.The times needed to classify the observations according to F-sLIRADS and LI-RADS v2018 were compared.RESULTS The optimal sLI-RADS was sLI-RADS D(with a single threshold of 20 mm),because its sensitivity was greater than that of LI-RADS v2018(89.8%vs 87.0%,P=0.031),and its specificity was not lower(89.4%vs 90.1%,P>0.999).With HBP hypointensity as an MF,the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018(93.0%vs 87.0%,P<0.001)and sLI-RADS D(93.0%vs 89.8%,P=0.016),without a lower specificity(86.5%vs 90.1%,P=0.062;86.5%vs 89.4%,P=0.125).Compared with that of LI-RADS v2018,the time to classify lesions according to FsLI-RADS was shorter(51±21 s vs 73±24 s,P<0.001).CONCLUSION The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.

High-resolution magnetic resonance imaging in the diagnosis and management of vertebral artery dissection:A case report

BACKGROUND Vertebral artery dissection(VAD)is a rare but life-threatening condition characterized by tearing of the intimal layer of the vertebral artery,leading to stenosis,occlusion or rupture.The clinical presentation of VAD can be heterogeneous,with common symptoms including headache,dizziness and balance problems.Timely diagnosis and treatment are crucial for favorable outcomes;however,VAD is often missed due to its variable clinical presentation and lack of robust diagnostic guidelines.High-resolution magnetic resonance imaging(HRMRI)has emerged as a reliable diagnostic tool for VAD,providing detailed visualization of vessel wall abnormalities.CASE SUMMARY A young male patient presented with an acute onset of severe headache,vomiting,and seizures,followed by altered consciousness.Imaging studies revealed bilateral VAD,basilar artery thrombosis,multiple brainstem and cerebellar infarcts,and subarachnoid hemorrhage.Digital subtraction angiography(DSA)revealed vertebral artery stenosis but failed to detect the dissection,potentially because intramural thrombosis obscured the VAD.In contrast,HRMRI confirmed the diagnosis by revealing specific signs of dissection.The patient was managed conservatively with antiplatelet therapy and other supportive measures,such as blood pressure control and pain management.After 5 mo of rehabilitation,the patient showed significant improvement in swallowing and limb strength.CONCLUSION HR-MRI can provide precise evidence for the identification of VAD.

Analysis of The Value of Multi-Slice Spiral CT and Magnetic Resonance Imaging in The Diagnosis of Carpal Joint Injury

Objective:To analyze the value of multi-slice spiral computed tomography(CT)and magnetic resonance imaging(MRI)in the diagnosis of carpal joint injury.Methods:A total of 130 patients with suspected wrist injuries admitted to the Department of Orthopedics of our hospital from January 2023 to January 2024 were selected and randomly divided into a single group(n=65)and a joint group(n=65).The single group was diagnosed using multi-slice spiral CT,and the joint group was diagnosed using multi-slice spiral CT and magnetic resonance imaging,with pathological diagnosis as the gold standard.The diagnostic results of both groups were compared to the gold standard,and the diagnostic energy efficiency of both groups was compared.Results:The diagnostic results of the single group compared with the gold standard were significant(P<0.05).The diagnostic results of the joint group compared with the gold standard were not significant(P>0.05).The sensitivity and accuracy of diagnosis in the joint group were significantly higher than that in the single group(P<0.05).The specificity of diagnosis in the joint group was higher as compared to that in the single group(P>0.05).Conclusion:The combination of multi-slice spiral CT and MRI was highly accurate in diagnosing wrist injuries,and the misdiagnosis rate and leakage rate were relatively low.Hence,this diagnostic program is recommended to be popularized.

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.

Imaging of the Extra-axial Tumors and Tumor-like Lesions Involving both Middle and Posterior Cranial Fossae: Classification and Diagnosis

Objective: To study the imaging features of extra-axial tumors and tumor-likelesions involving both middle and posterior cranial fossae and to make a classification. Methods:Sixty cases of pathologically confirmed extra-axil tumors and tumor-like lesions involving bothmiddle and posterior cranial fossae were analyzed. They were divided into central and lateral types,the latter of which were subdivided into three types: middle cranial fossae type, posterior cranialfossae type and the over-riding type. The constitution and imaging features of each type wereanalyzed. Results: There were 12 cases of central type, including chordoma (n=5), pituitary adenoma(n=3), nasopharyngeal carcinoma (n=2), craniopharyn-gioma (n=1) and meningioma (n=l). 48 cases oflateral type including trigeminal nerve tumors (n=14), meningioma (n=12), epidermoid cyst (n=11),dural cavernous hemangioma (n=4), dermoid cyst (n=2), metastasis (n=2), hemangiopericytoma (n=1),paraganglioma of glonius jugular (n=1) and nasopharyngeal carcinoma (n=1). Each type of the lesionshad its own shape features, some of which were characteristic for some specific tumors. Most of thetumors and tumor-like lesions could be qualitatively diagnosed according to their imagingcharacteristics and the extent of the lesions could be defined definitely. Conclusion: It is helpfulto categorize extra-axial tumors and tumor-like lesions involving both middle and posterior cranialfossae according to their location for qualitative diagnosis and description of the extent of theselesions. It is of great clinical value in providing more precise and thorough imaging informationfor planning therapeutic methods and route of operation.

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.

Advancements in non-invasive diagnosis of gastric cancer

Gastric cancer(GC),a multifaceted and highly aggressive malignancy,represents challenging healthcare burdens globally,with a high incidence and mortality rate.Although endoscopy,combined with histological examination,is the gold stan-dard for GC diagnosis,its high cost,invasiveness,and specialized requirements hinder widespread use for screening.With the emergence of innovative techno-logies such as advanced imaging,liquid biopsy,and breath tests,the landscape of GC diagnosis is poised for radical transformation,becoming more accessible,less invasive,and more efficient.As the non-invasive diagnostic techniques continue to advance and undergo rigorous clinical validation,they hold the promise of sig-nificantly impacting patient outcomes,ultimately leading to better treatment results and improved quality of life for patients with GC.

Histopathological diagnosis of microvascular invasion in hepatocellular carcinoma:Is it reliable?

BACKGROUND Microvascular invasion(MVI)is a critical prognostic factor for postoperative hepatocellular carcinoma recurrence,but the reliability of its current pathological diagnosis remains uncertain.AIM To evaluate the accuracy of current 7-point sampling methods and propose an optimal pathological protocol using whole-mount slide imaging(WSI)for better MVI detection.METHODS We utilized 40 New Zealand white rabbits to establish VX2 liver tumor models.The entire tumor-containing liver lobe was subsequently obtained,following which five different sampling protocols(A-E)were employed to evaluate the detection rate,accuracy,quantity,and distribution of MVI,with the aim of identifying the optimal sampling method.RESULTS VX2 liver tumor models were successfully established in 37 rabbits,with an incidence of MVI of 81.1%(30/37).The detection rates[27%(10/37),43%(16/37),62%(23/37),68%(25/37),and 93%(14/15)]and quantity(15,36,107,125,and 395)of MVI increased significantly from protocols A to E.The distribution of MVI showed fewer MVIs farther away from the tumor,but the percentage of MVI detected quantity gradually increased from 6.7%to 48.3%in the distant nonneoplastic liver tissue from protocols A to E.Protocol C was identified as the optimal sampling method by comparing them in sequence.The sampling protocol of three consecutive interval WSIs at the tumor center(WSI3)was further screened to determine the optimal number of WSIs.Protocol A(7-point sampling method)exhibited only 46%accuracy and a high false-negative rate of 67%.Notably,the WSI3 protocol improved the accuracy to 78%and decreased the false-negative rate to 27%.CONCLUSION The current 7-point sampling method has a high false-negative rate in MVI detection.In contrast,the WSI3 protocol provides a practical and effective approach to improve MVI diagnostic accuracy,which is crucial for hepatocellular carcinoma diagnosis and treatment planning.

Small bowel obstruction due to intra-abdominal hernia:New thoughts on diagnosis and treatment

Internal herniation(IH)refers to the movement of intra-abdominal organs or tissues out of their original position through normal or abnormal orifices and fissures in the peritoneum or mesentery and into an anatomic space within the abdominal cavity.Although the incidence of small bowel obstruction(SBO)caused by IH is very low(approximately 0.2%to 0.9%),its incidence may be increased in certain specific populations or in postoperative patients.Recently Kaw et al shared their 13-year experience of managing IHs in a tertiary care hospital in India.This retrospective study analyzed and determined the clinico-demographic profiles,radiological and operative findings and postoperative course of patients with IH and the association with SBO.The results provide valuable insights into early diagnosis and establishment of a timely treatment regimen for this condition and emphasize the importance of combining rapid imaging evaluation with the traditional therapeutic approach of laparoscopic surgery,thus providing a novel perspective on the diagnosis and treatment of SBO caused by IH.

Value of Magnetic Resonance Imaging Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors

Objective To investigate the difference in texture features on diffusion weighted imaging(DWI) images between breast benign and malignant tumors.Methods Patients including 56 with mass-like breast cancer, 16 with breast fibroadenoma, and 4 with intraductal papilloma of breast treated in the Hainan Hospital of Chinese PLA General Hospital were retrospectively enrolled in this study, and allocated to the benign group(20 patients) and the malignant group(56 patients) according to the post-surgically pathological results. Texture analysis was performed on axial DWI images, and five characteristic parameters including Angular Second Moment(ASM), Contrast, Correlation, Inverse Difference Moment(IDM), and Entropy were calculated. Independent sample t-test and Mann-Whitney U test were performed for intergroup comparison. Regression model was established by using Binary Logistic regression analysis, and receiver operating characteristic curve(ROC) analysis was carried out to evaluate the diagnostic efficiency. Results The texture features ASM, Contrast, Correlation and Entropy showed significant differences between the benign and malignant breast tumor groups(PASM= 0.014, Pcontrast= 0.019, Pcorrelation= 0.010, Pentropy= 0.007). The area under the ROC curve was 0.685, 0.681, 0.754, and 0.683 respectively for the positive texture variables mentioned above, and that for the combined variables(ASM, Contrast, and Entropy) was 0.802 in the model of Logistic regression. Binary Logistic regression analysis demonstrated that ASM, Contrast and Entropy were considered as thespecific imaging variables for the differential diagnosis of breast benign and malignant tumors.Conclusion The texture analysis of DWI may be a simple and effective tool in the differential diagnosis between breast benign and malignant tumors.

Insights into the hydrogen evolution reaction in vanadium redox flow batteries:A synchrotron radiation based X-ray imaging study

The parasitic hydrogen evolution reaction(HER)in the negative half-cell of vanadium redox flow batteries(VRFBs)causes severe efficiency losses.Thus,a deeper understanding of this process and the accompanying bubble formation is crucial.This benchmarking study locally analyzes the bubble distribution in thick,porous electrodes for the first time using deep learning-based image segmentation of synchrotron X-ray micro-tomograms.Each large three-dimensional data set was processed precisely in less than one minute while minimizing human errors and pointing out areas of increased HER activity in VRFBs.The study systematically varies the electrode potential and material,concluding that more negative electrode potentials of-200 m V vs.reversible hydrogen electrode(RHE)and lower cause more substantial bubble formation,resulting in bubble fractions of around 15%–20%in carbon felt electrodes.Contrarily,the bubble fractions stay only around 2%in an electrode combining carbon felt and carbon paper.The detected areas with high HER activity,such as the border subregion with more than 30%bubble fraction in carbon felt electrodes,the cutting edges,and preferential spots in the electrode bulk,are potential-independent and suggest that larger electrodes with a higher bulk-to-border ratio might reduce HER-related performance losses.The described combination of electrochemical measurements,local X-ray microtomography,AI-based segmentation,and 3D morphometric analysis is a powerful and novel approach for local bubble analysis in three-dimensional porous electrodes,providing an essential toolkit for a broad community working on bubble-generating electrochemical systems.

Fault diagnosis method of AC motor rolling bearing based on heterogeneous data fusion of current and infrared image

In order to improve the accuracy of rolling bearing fault diagnosis when the motor is running under non-stationary conditions,an AC motor rolling bearing fault diagnosis method was proposed based on heterogeneous data fusion of current and infrared images.Firstly,VMD was used to decompose the motor current signal and extract the low-frequency component of the bearing fault signal.On this basis,the current signal was transformed into a two-dimensional graph suitable for convolutional neural network,and the data set was classified by convolutional neural network and softmax classifier.Secondly,the infrared image was segmented and the fault features were extracted,so as to calculate the similarity with the infrared image of the fault bearing in the library,and further the sigmod classifier was used to classify the data.Finally,a decision-level fusion method was introduced to fuse the current signal with the infrared image signal diagnosis result according to the weight,and the motor bearing fault diagnosis result was obtained.Through experimental verification,the proposed fault diagnosis method could be used for the fault diagnosis of motor bearing outer ring under the condition of load variation,and the accuracy of fault diagnosis can reach 98.85%.

Anisotropy of Trabecular Bone from Ultra-Distal Radius Digital X-Ray Imaging: Effects on Bone Mineral Density and Age

Background: When applied to trabecular bone X-ray images, the anisotropic properties of trabeculae located at ultra-distal radius were investigated by using the trabecular bone scores (TBS) calculated along directions parallel and perpendicular to the forearm. Methodology: Data from more than two hundred subjects were studied retrospectively. A DXA (GE Lunar Prodigy) scan of the forearm was performed on each subject to measure the bone mineral density (BMD) value at the location of ultra-distal radius, and an X-ray digital image of the same forearm was taken on the same day. The values of trabecular bone score along the direction perpendicular to the forearm, TBSx, and along the direction parallel to the forearm, TBSy, were calculated respectively. The statistics of TBSx and TBSy were calculated, and the anisotropy of the trabecular bone, which was defined as the ratio of TBSy to TBSx and changed with subjects’ BMD and age, was reported and analyzed. Results: The results show that the correlation coefficient between TBSx and TBSy was 0.72 (p BMD and age was reported. The results showed that decreased trabecular bone anisotropy was associated with deceased BMD and increased age in the subject group. Conclusions: This study shows that decreased trabecular bone anisotropy was associated with decreased BMD and increased age.

Magnifying narrow-band imaging endoscopy is superior in diagnosis of early gastric cancer

AIM:To evaluate the diagnostic effectiveness of white light endoscopy,magnifying endoscopy(ME),and magnifying narrow-band imaging endoscopy(ME-NBI) in detecting early gastric cancer(EGC).METHODS:From March 2010 to June 2012,a total of 3616 patients received screening for gastric cancer by magnifying endoscopy. There were 3675 focal gastric lesions detected using conventional high definition white light endoscopy(HD-WLE) in four different referentialhospitals that were recruited for further investigation using ME and ME-NBI. The images obtained from HD-WLE,ME,and ME-NBI were reviewed by four experienced endoscopists to evaluate their diagnostic effectiveness for EGC. The diagnosis of cancerous and non-cancerous lesions was conducted by evaluating the microvascular and microsurface patterns using the VS classification system. The final endoscopic diagnosis of each lesion was determined by consultation when a disagreement occurred. We used histopathological results as the gold standard for the diagnosis of EGC.RESULTS:Among the 3675 lesions found,1508 were validated by pathological findings as chronic gastritis,1279 as chronic gastritis with intestinal metaplasia,631 as low-grade neoplasia,and 257 as EGC. The sensitivity,specificity,positive predictive value,negative predictive value,and accuracy of HD-WLE for the diagnosis of EGC were 71.2%,99.1%,85.5%,97.9% and 97.1%,respectively. The results of ME for diagnosing EGC were 81.3%,98.8%,83.3%,98.6% and 97.6%,respectively. The results of ME-NBI for the diagnosis of EGC were 87.2%,98.6%,82.1%,99.0% and 97.8%,respectively. The diagnostic sensitivity and accuracy of paired ME and ME-NBI were significantly better than those of HD-WLE(P < 0.05).CONCLUSION:HD-WLE has a relatively high accuracy for diagnosing EGC and is an effective screening tool. Further investigations of ME and ME-NBI are required to achieve superior accuracy.

Noninvasive imaging of hepatocellular carcinoma: From diagnosis to prognosis

Hepatocellular carcinoma(HCC) is the most common primary liver cancer and a major public health problem worldwide. Hepatocarcinogenesis is a complex multistep process at molecular, cellular, and histologic levels with key alterations that can be revealed by noninvasive imaging modalities. Therefore, imaging techniques play pivotal roles in the detection, characterization, staging, surveillance, and prognosis evaluation of HCC. Currently, ultrasound is the first-line imaging modality for screening and surveillance purposes. While based on conclusive enhancement patterns comprising arterial phase hyperenhancement and portal venous and/or delayed phase wash-out, contrast enhanced dynamic computed tomography and magnetic resonance imaging(MRI) are the diagnostic tools for HCC without requirements for histopathologic confirmation. Functional MRI techniques, including diffusion-weighted imaging, MRI with hepatobiliary contrast agents, perfusion imaging, and magnetic resonance elastography, show promise in providing further important information regarding tumor biological behaviors. In addition, evaluation of tumor imaging characteristics, including nodule size, margin, number, vascular invasion, and growth patterns, allows preoperative prediction of tumor microvascular invasion and patient prognosis. Therefore, the aim of this article is to review the current state-of-the-art and recent advances in the comprehensive noninvasive imaging evaluation of HCC. We also provide the basic key concepts of HCC development and an overview of the current practice guidelines.

Differential diagnosis of pancreatic cancer by single-shot echo-planar imaging diffusion-weighted imaging

AIM: To investigate the diagnostic ability of single-shot echo-planar imaging(EPI) diffusion-weighted imaging (DWI) to differentiate between malignant and benign pancreatic lesions. METHODS: A computerized search was performed on Pub Med, MEDLINE and EMBASE up to August 2014. Nine studies(10 sets of data) with a total of 304 malignant pancreatic lesions and 188 benign pancreatic lesions were included. The characteristics of each study included the study name, year of publication, magnetic resonance modalities used, patient population, strength of field, pulse time, repetition time, echo time(TE), maximum b factor, mean age, mean body weight, fat suppression, number of benign and malignant lesions, and true positive, true negative, false positive and false negative results. All analyses were performed using Meta-Di Sc and Stata 11.0.RESULTS: The pooled sensitivity and specificity of singleshot EPI DWI were 0.83(95%CI: 0.79-0.87) and 0.77(95%CI: 0.70-0.83), respectively. The positive likelihood ratio and negative likelihood ratio were 5.09(95%CI: 2.19-11.84) and 0.23(95%CI: 0.15-0.36), respectively. The P value for the χ2 heterogeneity for all pooled estimates was < 0.05. From the fitted summary receiver operating characteristic curve, the area under the curve and Q* index were 0.89 and 0.82, respectively. Publication bias was not present(t = 0.58, P = 0.58). Meta-regression analysis indicated that fat suppression, mean age, TE, and maximum b factor were not sources of heterogeneity(all P > 0.05). CONCLUSION: Single-shot EPI DWI is useful to differentiate between malignant and benign pancreatic lesions. Lesion size ≥ 2 cm is the limit for the diagnosis of early lesions.

Use of various CT imaging methods for diagnosis of acute ischemic cerebrovascular disease

Thirty-four patients with cerebral infarction and 18 patients with transient ischemic attack were examined by multi-slice spiral CT scan, CT perfusion imaging, and CT angiography within 6 hours after onset. By CT perfusion imaging, 29 cases in the cerebral infarction group and 10 cases in the transient ischemic attack group presented with abnormal blood flow perfusion, which corresponded to the clinical symptoms. By CT angiography, various degrees of vascular stenosis could be detected in 41 patients, including 33 in the cerebral infarction group and eight in the transient ischemic attack group. The incidence of intracranial artery stenosis was higher than that of extracranial artery stenosis. The intracranial artery stenosis was located predominantly in the middle cerebral artery and carotid artery siphon, while the extracranial artery stenosis occurred mainly in the bifurcation of the common carotid artery and the opening of the vertebral artery. There were 34 cases （83%） with convict vascular stenosis and perfusion abnormalities, and five cases （45%） with perfusion abnormalities but without convict vascular stenosis. The incidence of cerebral infarction in patients with National Institutes of Health Stroke Scale scores 〉 5 points during onset was significantly higher than that in patients with National Institutes of Health Stroke Scale scores 〈 5 points. These experimental findings indicate that the combined application of various CT imaging methods allows early diagnosis of acute ischemic cerebrovascular disease, which can comprehensively analyze the pathogenesis and severity of acute ischemic cerebrovascular disease at the morphological and functional levels.

A Comprehensive Investigation of Machine Learning Feature Extraction and ClassificationMethods for Automated Diagnosis of COVID-19 Based on X-ray Images

The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease.In this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 vs.Normal(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection cases.Based on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 model.In comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.