Clinical Application Value of Combined Detection of CG and TBA in Differential Diagnosis of Hepatobiliary System Diseases

Objective: To understand the clinical value of combined detection of cholyglycine CG and TBA in differential diagnosis of hepatobiliary diseases. Methods: Serum samples from 50 healthy people were collected as healthy control group. According to the latest disease diagnosis and treatment plan, 58 cases of HBV asymptomatic carrier group, 17 cases of viral hepatitis group, 49 cases of cirrhosis group, 50 cases of primary liver cancer group and 50 cases of other hepatobiliary diseases groups were collected respectively. The concentration levels of cholyglycine and total bile acid in each group were detected, and the differences among each group were compared. Results: By statistical analysis, serum CG concentration in viral hepatitis group, cirrhosis group, primary liver cancer group and other hepatobiliary diseases group was significantly higher than that in asymptomatic HEPATITIS B carriers and healthy control group, the differences were statistically significant (p 0.05). There was no significant difference in CG concentration among viral hepatitis group, liver cirrhosis group, primary liver cancer group and other hepatobiliary diseases group (p > 0.05). The serum TBA levels of asymptomatic carriers, viral hepatitis group, cirrhosis group, primary liver cancer group and other hepatobiliary system diseases group were significantly higher than those of healthy control group, the difference was statistically significant, p 0.05. Conclusion: Serum CG expression can not only detect liver lesions, but also distinguish different liver lesions. The positive rate of CG combined with TBA detection in patients with hepatobiliary diseases is significantly higher than that of single CG index detection. CG combined with TBA detection can significantly improve the sensitivity and accuracy of the diagnosis of hepatobiliary diseases, which is worthy of popularization and application.

Can TCM Treatment be Performed on the Basis of Differential Diagnosis of the Diseases Instead of the Syndromes?

Great advances have been achieved in the integration of western and traditional Chinese medicine (TCM).More and more TCM physicians in their practice accept the term 'differential diagnosis of the diseases' instead of the syndromes since western medicine has been introduced into the TCM circle.

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.

Quantitative differential diagnosis of breasttumors using shear wave velocity and differentprobe orientations

Objective The aim of this study was to evaluate the additional benefit of the difference of maximum and minimum shear wave velocity(SWV) values obtained at different probe orientations(D-value) for the differential diagnosis of breast tumors.Methods SWV(m/s) was measured in 123 breast tumors(92 benign,31 malignant) in 76 female patients with the probe placed on the transverse,longitudinal,and 45° planes.The areas under the receiver operating characteristic(AUROC) curves were compared with respect to the maximum SWV,minimum SWV,D-value,maximum SWV combined with the D-value,and minimum SWV combined with the D-value.Results There was a significant difference among the values of the maximum SWV,minimum SWV,and D-value for the 3 planes(P < 0.001).The AUROC curves for the maximum SWV,minimum SWV,and D-values of the 3 planes were 0.751(P = 0.379),0.486(P = 0.863),and 0.603(P = 0.204),respectively.The cutoff value for the maximum SWV for differentiating benign tumors from malignant tumors was 2.51 m/s(sensitivity 67%,specificity 50%).The cutoff value for the minimum SWV was 1.61 m/s(sensitivity 53%,specificity 50%).Adding the D-value increased the AUROC curve for the maximum SWV from 0.571 to 0.733 and the minimum SWV from 0.486 to 0.504(P = 0.964),respectively.Conclusion SWV differs in different planes of breast tumors.The D-value can provide a reference for the differential diagnosis of breast tumors.

Six cases report of differential diagnosis of periapical diseases

The distinction of some particular forms of periapical area, involving diseases from regular periapical disease, is a matter of considerable importance when choosing a correct treatment. The aim of this study is to describe the differential diagnosis of F,eriapical diseases from six rare cases in clinical practice. The six rare cases are examples of situations where it is difficult to make a differential diagnosis in clinical practice. By retrospective surveys on the clinical examination, radiographs and pathological results, six patients referred to endodontic treatment in our department were analyzed for the accuracy of diagnosis and therapy. The pathoses of the six cases included two atypical radical cysts, periapical cemental dysplasia, cemento-ossifying fibroma, thymus cancer metastasis in the periapical site and tuberculosis. This report indicates that endodontists should be cognizant of a few particular circumstances when clinically treating periapical diseases.

Modified Differential Box Counting in Breast Masses for Bioinformatics Applications

Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer.The present research work is useful in image processing for characterizing shape and gray-scale complexity.The proposed Modified Differential Box Counting(MDBC)extract Fractal features such as Fractal Dimension(FD),Lacunarity,and Succolarity for shape characterization.In traditional DBC method,the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels.The problem is overcome by the proposedMDBCmethod that uses box over counting and under counting that covers the whole image with required scale.In MDBC method,the suitable box size selection and Under Counting Shifting rule computation handles over counting problem.An advantage of the model is that the proposed MDBC work with recently developed methods showed that our method outperforms automatic detection and classification.The extracted features are fed to K-Nearest Neighbour(KNN)and Support Vector Machine(SVM)categorizes the mammograms into normal,benign,and malignant.The method is tested on mini MIAS datasets yields good results with improved accuracy of 93%,whereas the existing FD,GLCM,Texture and Shape feature method has 91%accuracy.

Application of support vector machine algorithm for early differential diagnosis of prostate cancer

Prostate cancer(PCa)symptoms are commonly confused with benign prostate hyperplasia(BPH),particularly in the early stages due to similarities between symptoms,and in some instances,underdiagnoses.Clinical methods have been utilized to diagnose PCa;however,at the full-blown stage,clinical methods usually present high risks of complicated side effects.Therefore,we proposed the use of support vector machine for early differential diagnosis of PCa(SVM-PCa-EDD).SVM was used to classify persons with and without PCa.We used the PCa dataset from the Kaggle Healthcare repository to develop and validate SVM model for classification.The PCa dataset consisted of 250 features and one class of features.Attributes considered in this study were age,body mass index(BMI),race,family history,obesity,trouble urinating,urine stream force,blood in semen,bone pain,and erectile dysfunction.The SVM-PCa-EDD was used for preprocessing the PCa dataset,specifically dealing with class imbalance,and for dimensionality reduction.After eliminating class imbalance,the area under the receiver operating characteristic(ROC)curve(AUC)of the logistic regression(LR)model trained with the downsampled dataset was 58.4%,whereas that of the AUC-ROC of LR trained with the class imbalance dataset was 54.3%.The SVM-PCa-EDD achieved 90%accuracy,80%sensitivity,and 80%specificity.The validation of SVM-PCa-EDD using random forest and LR showed that SVM-PCa-EDD performed better in early differential diagnosis of PCa.The proposed model can assist medical experts in early diagnosis of PCa,particularly in resource-constrained healthcare settings and making further recommendations for PCa testing and treatment.

Gingival enlargements: Differential diagnosis and review of literature

Gingival enlargement is one of the frequent features of gingival diseases. However due to their varied presentations, the diagnosis of these entities becomes challenging for the clinician. They can be categorized based on their etiopathogenesis, location, size, extent, etc. Based on the existing knowledge and clinical experience, a differential diagnosis can be formulated. Subsequently, after detailed investigation, clinician makes a final diagnosis or diagnosis of exclusion. A perfect diagnosis is critically important, since the management of these lesions and prevention of their recurrence is completely dependent on it. Furthermore, in some cases where gingival enlargement could be the primary sign of potentially lethal systemic diseases, a correct diagnosis of these enlargements could prove life saving for the patient or at least initiate early treatment and improve the quality of life. The purpose of this review article is to highlight significant findings of different types of gingival enlargement which would help clinician to differentiate between them. A detailed decision tree is also designed for the practitioners, which will help them arrive at a diagnosis in a systematic manner. There still could be some lesions which may present in an unusual manner and make the diagnosis challenging. By knowing the existence of common and rare presentations of gingival enlargement, one can keep a broad view when formulating a differential diagnosis of localized(isolated, discrete, regional) or generalized gingival enlargement.

Potential model for differential diagnosis between Crohn's disease and primary intestinal lymphoma

AIM To evaluate the usefulness of different parameters to differentiate Crohn's disease(CD) from primary intestinal lymphoma(PIL).METHODS The medical records of 85 patients with CD and 56 patients with PIL were reviewed retrospectively. Demographic, clinical, laboratory, endoscopic, and computed tomographic enterography(CTE) parameters were collected. The univariate value of each parameter was analyzed. A differentiation model was established by pooling all the valuable parameters. Diagnostic efficacy was analyzed, and a receiver operating characteristic(ROC) curve was plotted.RESULTS The demographic and clinical parameters that showed significant values for differentiating CD from PIL included age of onset, symptom duration, presence of diarrhea, abdominal mass, and perianal lesions(P < 0.05). Elevated lactate dehydrogenase and serum β2-microglobulin levels suggested a PIL diagnosis(P < 0.05). The endoscopic parameters that showed significant values for differentiating CD from PIL included multiple-site lesions, longitudinal ulcer, irregular ulcer,and intraluminal proliferative mass(P < 0.05). The CTE parameters that were useful in the identification of the two conditions included involvement of ≤ 3 segments, circular thickening of the bowel wall, wall thickness > 8 mm, aneurysmal dilation, stricture with proximal dilation, "comb sign", mass showing the "sandwich sign", and intussusceptions(P < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the differentiation model were 91.8%, 96.4%, 93.6%, 97.5%, and 88.5%, respectively. The cutoff value was 0.5. The area under the ROC curve was 0.989.CONCLUSION The differentiation model that integrated the various parameters together may yield a high diagnostic efficacy in the differential diagnosis between CD and PIL.

Diagnostic performance of texture analysis in the differential diagnosis of perianal fistulising Crohn’s disease and glandular anal fistula

BACKGROUND Perianal fistulising Crohn's disease(PFCD)and glandular anal fistula have many similarities on conventional magnetic resonance imaging.However,many patients with PFCD show concomitant active proctitis,but only few patients with glandular anal fistula have active proctitis.AIM To explore the value of differential diagnosis of PFCD and glandular anal fistula by comparing the textural feature parameters of the rectum and anal canal in fat suppression T2-weighted imaging(FS-T2WI).METHODS Patients with rectal water sac implantation were screened from the first part of this study(48 patients with PFCD and 22 patients with glandular anal fistula).Open-source software ITK-SNAP(Version 3.6.0,http://www.itksnap.org/)was used to delineate the region of interest(ROI)of the entire rectum and anal canal wall on every axial section,and then the ROIs were input in the Analysis Kit software(version V3.0.0.R,GE Healthcare)to calculate the textural feature parameters.Textural feature parameter differences of the rectum and anal canal wall between the PFCD group vs the glandular anal fistula group were analyzed using Mann-Whitney U test.The redundant textural parameters were screened by bivariate Spearman correlation analysis,and binary logistic regression analysis was used to establish the model of textural feature parameters.Finally,diagnostic accuracy was assessed by receiver operating characteristic-area under the curve(AUC)analysis.RESULTS In all,385 textural parameters were obtained,including 37 parameters with statistically significant differences between the PFCD and glandular anal fistula groups.Then,16 texture feature parameters remained after bivariate Spearman correlation analysis,including one histogram parameter(Histogram energy);four grey level co-occurrence matrix(GLCM)parameters(GLCM energy_all direction_offset1_SD,GLCM entropy_all direction_offset4_SD,GLCM entropy_all direction_offset7_SD,and Haralick correlation_all direction_offset7_SD);four texture parameters(Correlation_all direction_offset1_SD,cluster prominence_angle 90_offset4,Inertia_all direction_offset7_SD,and cluster shade_angle 45_offset7);five grey level run-length matrix parameters(grey level nonuniformity_angle 90_offset1,grey level nonuniformity_all direction_offset4_SD,long run high grey level emphasis_all direction_offset1_SD,long run emphasis_all direction_offset4_SD,and long run high grey level emphasis_all direction_offset4_SD);and two form factor parameters(surface area and maximum 3D diameter).The AUC,sensitivity,and specificity of the model of textural feature parameters were 0.917,85.42%,and 86.36%,respectively.CONCLUSION The model of textural feature parameters showed good diagnostic performance for PFCD.The texture feature parameters of the rectum and anal canal in FS-T2WI are helpful to distinguish PFCD from glandular anal fistula.

TCM DIFFERENTIAL TREATMENT OF CHILD HOOD PERSISTING PNEUMONIA -A Report of 52 Cases

According to TCM differentiation of the symptoms and signs, 52 children with presisting pneumonia were divided into the following four types: 1) deficiency of body fluid due to accumulation of heat in the lung, 2) earth failing to generate metal, 3) deficiency of the Ying and Wei systems, and 4) excessiveness of pathogens due to qi deficiency. After treatment for 2-3 weeks, 40 cases were cured, 8 improved, and 4 ineffective.

Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

BACKGROUND Crohn’s disease(CD)is often misdiagnosed as intestinal tuberculosis(ITB).However,the treatment and prognosis of these two diseases are dramatically different.Therefore,it is important to develop a method to identify CD and ITB with high accuracy,specificity,and speed.AIM To develop a method to identify CD and ITB with high accuracy,specificity,and speed.METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB.Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm^(-1) and 1234 cm^(-1) bands,and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy,specificity,and sensitivity of 91.84%,92.59%,and 90.90%,respectively,for the differential diagnosis of CD and ITB.CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level,and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

Monoexponential, biexponential and stretched-exponential models based diffusion weighted imaging: a comparative study in the differential diagnosis of benign and malignant breast lesions

Objective To investgate the value of various parameters obtained from monoexponential,biexponential,and stretched exponential diffusion-weighted imaging models in the differential diagnosis of breast lesions.Methods A retrospective study was performed in 54 patients with pathologically confirmed malignant tumors(n=30),benign lesions(n=34)and normal fibroglandular

Journey to diagnosis:An unfinished exploration of IgG4-related sclerosing cholangitis

IgG4-related sclerosing cholangitis(IgG4-SC)is an inflammatory disease that leads to bile duct stricture,characterized by the infiltration of IgG4-positive plasma cells into the bile duct wall,thickening of the bile duct wall,and narrowing of the lumen.The differential diagnosis of IgG4-SC mainly includes primary sclerosing cholangitis,cholangiocarcinoma,and pancreatic cancer.IgG4-SC is often associated with autoimmune pancreatitis and can be accurately diagnosed based on clinical diagnostic criteria.However,isolated IgG4-SC is difficult to distinguish from biliary tumors.Given the significant differences in biological behavior,treatment,and prognosis between these diseases,accurately identifying isolated IgG4-SC has very important clinical significance.

基于MRI的瘤周水肿特征对浸润性乳腺癌淋巴结转移负荷的预测价值

目的分析基于MRI的瘤周水肿特征对乳腺癌淋巴结转移负荷的预测价值。资料与方法回顾性收集四川省肿瘤医院2017年9月—2019年2月有完整术前MRI资料和术后病理资料的213例浸润性乳腺癌。根据术后病理诊断的淋巴结转移数量,将病例分为高负荷淋巴结转移组47例(转移淋巴结总数>2枚)和低负荷淋巴结转移组166例(转移淋巴结总数≤2枚)。在T2WI序列上,分析每例的乳腺癌瘤周水肿(包括瘤周水肿类型和水肿程度)特征。在DCE-MRI序列上,根据乳腺影像报告和数据系统分类术语分析乳腺癌的MRI特征。通过单因素分析瘤周水肿等T2WI特征和乳腺癌MRI特征对淋巴结转移负荷的诊断价值,将有显著意义的特征进行多因素Logistic回归分析,并建立诊断模型。采用受试者工作特征曲线评价模型对乳腺癌淋巴结转移负荷的诊断效能,根据约登指数计算模型的诊断效能指标。结果本研究的高负荷转移淋巴结占22.1%(47/213)。单因素分析结果显示,瘤周水肿程度(OR=18.70,P<0.001)、瘤周水肿类型(OR=16.00,P<0.001)、肿瘤最长径(OR=1.40,P=0.025)和肿瘤最短径(OR=2.01,P=0.003)对高负荷淋巴结转移有预测价值;多因素Logistic回归分析结果显示,最终对浸润性乳腺癌高负荷淋巴结转移有价值的特征是瘤周水肿水肿特征,包括瘤周水肿程度(OR=8.02,P<0.001)和瘤周水肿类型(OR=5.53,P=0.001),最终诊断模型预测浸润性乳腺癌高负荷淋巴结转移的曲线下面积为0.842,敏感度为0.766,特异度为0.861,阳性预测值为0.610,阴性预测值为0.929。结论术前MRI的瘤周水肿特征对浸润性乳腺癌淋巴结转移负荷有很好的预测价值,尤其是对低负荷淋巴结转移状态预测价值更高。

增强T2^(*)加权血管成像在T2WI低信号肾脏病变良恶性鉴别诊断中的价值

目的探讨增强T2^(*)加权血管成像(enhanced T2 star-weighted angiography,ESWAN)序列中R2^(*)值、相位值、幅度值在T2WI低信号肾脏病变良恶性鉴别诊断中的可行性。材料与方法回顾性收集行ESWAN检查、经病理组织学证实的145例T2WI低信号肾脏病变患者(共145个病灶,恶性病变112个,良性病变33个)的术前MRI图像。在肿瘤最大面积的层面上绘制肿瘤T2WI低信号的感兴趣区。通过Kruskal-Wallis检验、卡方检验对参数进行比较,将有统计学意义的参数进行联合,通过多变量logistic回归建立模型,分析差异有统计学意义的参数,并且绘制其鉴别T2WI低信号肾脏病变良恶性的受试者工作特征(receiver operating characteristic,ROC)曲线,采用DeLong检验评价其诊断效能。结果R2^(*)值和幅度值鉴别T2WI低信号肾脏病变良恶性差异具有统计学意义(P=0.001)。R2^(*)值的ROC曲线下面积(area under the curve,AUC)为0.891[95%置信区间(confidence interval,CI):0.829~0.937,P<0.001],敏感度、特异度分别为97.3%、72.7%;幅度值的AUC为0.869(95%CI:0.803~0.920,P<0.001),敏感度、特异度分别为86.6%、81.8%;相位值的AUC为0.563(95%CI:0.478~0.645,P=0.249),敏感度、特异度分别为67.9%、54.6%;R2^(*)值联合幅度值的AUC为0.886(95%CI:0.823~0.933,P<0.001),敏感度、特异度分别为97.3%、72.7%;R2^(*)值联合病变长径的AUC为0.894(95%CI:0.832~0.939,P<0.001),敏感度、特异度分别为92.0%、81.8%;幅度值联合病变长径的AUC为0.858(95%CI:0.790~0.910,P<0.001),敏感度、特异度分别为75.9%、90.9%。结论R2^(*)值、R2^(*)值联合病变长径、R2^(*)值联合幅度值是鉴别T2WI低信号肾脏病变良恶性的有效方法,R2^(*)值联合病变长径具有更好的诊断性能。

Automated Deep Learning Empowered Breast Cancer Diagnosis UsingBiomedical Mammogram Images

Biomedical image processing is a hot research topic which helps to majorly assist the disease diagnostic process.At the same time,breast cancer becomes the deadliest disease among women and can be detected by the use of different imaging techniques.Digital mammograms can be used for the earlier identification and diagnostic of breast cancer to minimize the death rate.But the proper identification of breast cancer has mainly relied on the mammography findings and results to increased false positives.For resolving the issues of false positives of breast cancer diagnosis,this paper presents an automated deep learning based breast cancer diagnosis(ADL-BCD)model using digital mammograms.The goal of the ADL-BCD technique is to properly detect the existence of breast lesions using digital mammograms.The proposed model involves Gaussian filter based pre-processing and Tsallis entropy based image segmentation.In addition,Deep Convolutional Neural Network based Residual Network(ResNet 34)is applied for feature extraction purposes.Specifically,a hyper parameter tuning process using chimp optimization algorithm(COA)is applied to tune the parameters involved in ResNet 34 model.The wavelet neural network(WNN)is used for the classification of digital mammograms for the detection of breast cancer.The ADL-BCD method is evaluated using a benchmark dataset and the results are analyzed under several performance measures.The simulation outcome indicated that the ADL-BCD model outperforms the state of art methods in terms of different measures.

Treating Principles and Methods of Traditional Chinese Medicine in Treatment of Peripheral Vascular Diseases

Peripheral vascular disease embraces a variety of conditions such as thromboangiitis obliterans, Raynaud's disease, thrombophlebitis, aorto-arteritis, obliterate atherosclerosis, varix or phlebothrombosis of the lower limb. Although the affected blood vessel may be arterial or venous one and caused either by inflammation or degenerate changes, they share common symptoms and signs, such as blood stasis, ischemia, thrombosis, ecchymosis, swelling, constriction or obliteration of blood vessels due to circulatory impairment. Since they share common characteristics, the treating principles and methods will be discussed as follows.

基于瘤体及瘤周多参数MRI对乳腺病变良恶性诊断列线图预测模型的构建与评价

目的:建立基于瘤体及瘤周多参数MRI的乳腺病变良恶性鉴别诊断的列线图模型,并验证其预测效能。方法:纳入经病理学检查明确乳腺病变性质的100例患者作为研究对象,所有患者均行核磁共振(MRI)检查和病理检查,根据病理检查结果分为乳腺良性病变组(n=62)和乳腺恶性病变组(n=38)。收集患者临床资料、瘤体各参数、瘤周各参数以及乳腺病变良恶性情况。多因素Logistic回归分析筛选乳腺恶性病变的危险因素并构建列线图预测模型,采用受试者工作特征(ROC)曲线和Hosmer-Lemeshow拟合优度检验验证模型的预测效能及拟合优度;内部验证采用Bootstrap。结果:乳腺恶性病变组病灶直径、平均扩散峰度(MK)、MDp/t、瘤周与瘤体MKp/n高于乳腺良性病变组(均P<0.05);乳腺恶性病变组表观扩散系数(ADC)值、平均扩散率(MD)、非对称磁化转移率(MTRasym)、MKp/t、MDp/n低于乳腺良性病变组(均P<0.05)。多因素分析结果显示,病灶直径、MK、MDp/t、MKp/n升高,ADC值、MD、MTRasym、MKp/t、MDp/n降低是乳腺恶性病变的独立影响因素(均P<0.05)。基于上述独立影响因素构建乳腺恶性病变的列线图预测模型,曲线下面积(AUC)为0.827。Hosmer-Lemeshow拟合优度检验显示P值为0.004。采用Bootstrap法,生成的校准曲线拟合良好。结论:瘤体及瘤周多参数MRI对乳腺病变良恶性鉴别诊断具有重要预测价值,基于乳腺恶性病变的独立影响因素构建的列线图预测效果良好,能直观预测乳腺发生恶性病变的概率。

血清miR-155、miR-23b在特发性肉芽肿乳腺炎和乳腺癌中的差异性表达及意义

目的 探讨miR-155、miR-23b在特发性肉芽肿乳腺炎(IGM)和乳腺癌(BC)鉴别诊断中的作用。方法 选取2018年10月至2021年11月我院收治的32例IGM患者(ICM组)和40例BC患者(BC组),所有患者均经活检确诊。另外纳入33例健康女性作为对照组。比较患者的临床资料。采用实时荧光定量PCR检测血清miRNAs表达水平。采用受试者工作特征(ROC)曲线评估血清miR-155、miR-23b对IGM和BC的诊断价值。采用Pearson相关系数法评估相关性。结果 3组CRP、WBC、Hb、Hct、CA19-9、CA15-3、CA125水平比较,差异有统计学意义(P<0.05)。IGM组患者血清miR-155、miR-16-5p、miR-21-5p、miR-210-3p、miR-222-3p、miR-29c-3p表达水平较对照组升高(P<0.001),血清miR-23b表达水平低于对照组(P<0.001);BC组患者血清中以上miRNAs表达水平均高于对照组(P<0.001)。BC组患者血清miR-155表达水平低于IGM组(P<0.001),血清miR-23b表达水平高于IGM组(P<0.001)。血清miR-155和miR-23b水平鉴别诊断IGM和BC的ROC曲线下面积(AUC)分别为0.722(95%CI:0.601~0.843)、0.765(95%CI:0.657~0.874),敏感度分别为81.00%、77.50%,特异度分别为65.00%、59.40%;二者联合鉴别诊断的AUC为0.869(95%CI:0.786~0.951),敏感度和特异度分别为84.10%和92.50%。IGM组血清miR-155与WBC、CRP水平均呈正相关(P<0.05),而血清miR-23b与WBC、CRP水平均呈负相关(P<0.05)。结论 血清miR-155和miR-23b有助于区分IGM和BC,可成为IGM和BC早期鉴别诊断的靶标。