Objective To conclude the CT manifestations and pathological features of low-grade appendiceal mucinous neoplasms. Methods We reviewed the clinical and CT findings of 24 patients with low-grade appendiceal mucinous neoplasms, who were confirmed by pathology within 1 month after CT examination in SichuanProvincial People’s Hospital from January 2018 to December 2020. The distribution, morphological characteristics, cyst wall and internal characteristics, CT value and enhancement characteristics of tumors were be detected in detail. Results ① Distribution: of the 24 patients, 22 patients located in the appendix area of the right lower quadrant, 2 patients located in the right middle abdomen, and 2 patients located in the pelvic cavity. ② Morphological characteristics: of the 24 patients, 15 patients manifested as tubular, 3 patients manifested as ellipsoidal, 5 patients manifested as saccular, and 1 patient manifested as irregular shape. The average length of tumors was about 6.4 cm (4.2–12.0 cm), and the average short diameter of tumors was about 2.2 cm (0.8–5.0 cm). The short diameter of 17 patients were more than 1.5 cm. ③ The cyst wall and internal characteristics: all the 24 patients demonstrated as cystic mass, 6 patients had evenly thin and smooth cyst wall, and other 18 patients had uneven cyst wall. Of all the patients,8 patients had arc-shaped, punctate or eggshell-like calcification. ④ The CT value and enhancement characteristics: 24 patients examined by plain CT scan, 22 patients showed uniform low density (the CT value were 7–25 HU), 2 patients contained some slightly high density, 16 patients examined by enhanced CT, the cyst wall, separation, or mural nodules of 8 patients were slightly or moderately enhanced. ⑤ Pathological results: of all the gross specimens, 15 patients showed tubular dilation, 9 patients showed partial or complete dilation as cystic mass. All the 24 patients had gelatinous or mucinous contents. Microscopically, all the patients showed low-grade mucinous epithelial hyperplasia, submucosa, and mucosal muscle atrophy, accompanied by fibrosis or calcification. Conclusion Low-grade appendiceal mucinous neoplasms show some specific CT manifestations, recognize these features can improve the accuracy of preoperative CT.
Objective To explore the value of three-dimensional contrast-enhanced ultrasound angiography in the differential diagnosis of breast masses. Methods A total of 120 patients with breast masses who were treated in our hospital from July 2013 to February 2016 were selected as the research objects retrospectively, including 70 patients of benign tumor (benign group) and 50 patients of malignant tumor (malignant group) that confirmed by surgery and pathology. All patients were given conventional two-dimensional ultrasound and three-dimensional contrast-enhanced ultrasound angiography during the diagnosis. Compared the imaging features of benign group and malignant group, and compared the diagnostic value of two-dimensional ultrasound and three-dimensional contrast-enhanced ultrasound angiography for breast masses. Results Compared with benign group, the rates of irregular masses, unclear boundary, inhomogeneous echo, lateral shadowing, echo attenuation, and micro calcification in the malignant group were all higher (P<0.05). The three-dimensional contrast-enhanced ultrasound angiography scores in malignant group and benign group were significantly different with each other (P<0.05), the score of the malignant group was higher than that of benign group. The 2- and 3-score was common in benign group, but 4- and 5-score was common in malignant group. The diagnostic sensitivity of two-dimensional ultrasound and three-dimensional contrast-enhanced ultrasound angiography for breast masses were 97.1% (68/70) and 98.6% (69/70) respectively, and the specificity were 80.0% (40/50) and 96.0% (48/50) respectively, the specificity of three-dimensional contrast-enhanced ultrasound angiography was significantly higher than that of two-dimensional ultrasound (P<0.05). Conclusion Two-dimensional ultrasound and three-dimensional contrast-enhanced ultrasound angiography both have a certain diagnostic value in the differential diagnosis of breast masses, but the three dimensional contrast-enhanced ultrasound angiography can get more information through assessment of richness of the microvascular in tumor tissue, so as to improve the diagnostic specificity and is worthy of popularization and application.
Objective To determine feasibility of texture analysis of CT images for the discrimination of hepatic epithelioid hemangioendothelioma (HEHE) and liver metastases of colon cancer. Methods CT images of 9 patients with 19 pathologically proved HEHEs and 18 patients with 38 liver metastases of colon cancer who received treatment in West China Hospital of Sichuan University from July 2012 to August 2016 were retrospectively analyzed. Results Thirty best texture parameters were automatically selected by the combination of Fisher coefficient (Fisher)+classification error probability combined with average correlation coefficients (PA)+mutual information (MI). The 30 texture parameters of arterial phase (AP) CT images were distributed in co-occurrence matrix (22 parameters), run-length matrix (1 parameter), histogram (4 parameters), gradient (1 parameter), and autoregressive model (2 parameters). The distribution of parameters in portal venous phase (PVP) were co-occurrence matrix (18 parameters), run-length matrix (2 parameters), histogram (7 parameters), gradient (2 parameters), and autoregressive model (1 parameter). In AP, the misclassification rates of raw data analysis (RDA)/K nearest neighbor classification (KNN), principal component analysis (PCA)/KNN, linear discriminant analysis (LDA)/KNN, and nonlinear discriminant analysis, and nonlinear discriminant analysis (NDA)/artificial neural network (ANN) was 38.60% (22/57), 42.11% (24/57), 8.77% (5/57), and 7.02% (4/57), respectively. In PVP, the misclassification rates of RDA/KNN, PCA/KNN, LDA/KNN, and NDA/ANN was 26.32% (15/57), 28.07% (16/57), 15.79% (9/57), and 10.53% (6/57), respectively. The misclassification rates of AP and PVP images had no statistical significance on the misclassification rates of RDA/KNN, PCA/KNN, LDA/KNN, and NDA/ANN between AP and PVP (P>0.05). Conclusion The texture analysis of CT images is feasible to identify HEHE and liver metastases of colon cancer.
摘要:目的:研究胸腺瘤與前縱隔(血管前間隙)淋巴瘤的MSCT表現,提高對二者的診斷與鑒別診斷能力。方法:回顧性分析經手術病理證實的30例胸腺瘤與18例血管前間隙淋巴瘤MSCT表現,著重觀察腫瘤的密度、形態及其與周圍結構的關系。結果:30例胸腺瘤中,24例良性胸腺瘤與鄰近大血管分界清晰,腫塊表現 “D”字或反“D”字狀,平掃CT值16~59 Hu,增強CT值20~110 Hu;6例侵襲性胸腺瘤邊界不清,呈分葉狀、不規則形,密度不均,平掃CT值23~42 Hu,增強CT值23~60 Hu。18例淋巴瘤中,單發于前上縱隔者6例,其余12例呈多結節、腫塊狀,侵入血管間隙生長,致大血管受壓,增強掃描呈輕度強化,常伴有其它部位淋巴結增大。結論:MSCT能清晰顯示胸腺瘤與前縱隔淋巴瘤的影像學表現特征,并能有效提高對二者的鑒別診斷。Abstract: Objective: To diagnosis and differentiate thymoma and malignant lymphoma in the anterior mediastinum on the basis of multislice CT (MSCT) imaging features. Methods:We retrospectively reviewed 30 cases with thymoma and 18 cases with malignant lymphoma proven by surgery and pathology.More attention was put on the density, morphology and relation with the surrounding structures of the tumors. Results: The CT manifestations of 30 cases of thymoma were shown as: For 24 cases of benign thymoma, the boundaries were clear, the shapes were “D” signs or contra“D” signs, CT attenuation value were 1659Hu and 20110Hu on unenhanced and contrastenhanced scanning. For 6 cases of malignant thymoma, the boundaries were unclear, the shapes were lobulated or irregular, the density was heterogeneous, CT attenuation value were 2342Hu and 2360Hu on unenhanced and contrastenhanced scanning. For 18 cases of malignant lymphoma, 6 cases were located at anterior mediastinum, 12 cases were nodes or multiple mass, enveloped the neighboring vessel structures, mildly enhanced on contrastenhanced scanning, and associated with enlargement of lymph nodes in other place. Conclusion: MSCT can display the imaging features of thymoma and anterior mediastinal lymphoma, and effectively differentiate thymoma and mediastinal lymphoma.
Tumor chemotherapy is a treatment method that employs chemotherapeutic drugs to eradicate cancer cells. These drugs are cytotoxic, meaning they can affect both tumor cells and normal cells. In recent years, there has been a gradual increase in chemotherapy-induced liver injury. Chemotherapy-induced parenchymal liver injury often manifests as diffuse lesions, although focal lesions can occasionally be observed. There is a diversity in the pathogenesis and pathological changes of chemotherapy-induced focal liver disease. Radiologically, there is often challenging in differentiating chemotherapy-induced focal liver disease from hepatic metastases. Therefore, early and accurate diagnosis of this condition poses a certain challenge in clinical practice. This article presents the radiological findings of a case of chemotherapy-induced focal liver disease induced by chemotherapy for gastric cancer, and summarizes the radiological features and differential diagnostic points of chemotherapy-induced focal liver disease, aiming to enhance the understanding of this type of lesion among radiologists and clinicians and reduce related missed diagnoses and misdiagnoses.
Objective To explore the efficacy of a novel detection technique of circulating tumor cells (CTCs) to identify benign and malignant lung nodules. Methods Nanomagnetic CTC detection based on polypeptide with epithelial cell adhesion molecule (EpCAM)-specific recognition was performed on enrolled patients with pulmonary nodules. There were 73 patients including 48 patients with malignant lesions as a malignant group and 25 patients with benign lesion as a benign group. There were 13 males and 35 females at age of 57.0±11.9 years in the malignant group and 11 males and 14 females at age of 53.1±13.2 years in the benign group. e calculated the differential diagnostic efficacy of CTC count, and conducted subgroup analysis according to the consolidation-tumor ratio, while compared with PET/CT on the efficacy. Results CTC count of the malignant group was significantly higher than that of the benign group (0.50/ml vs. 0.00/ml, P<0.05). Subgroup analysis according to consolidation tumor ratio (CTR) revealed that the difference was statistically significant in pure ground glass (pGGO) nodules 1.00/mlvs. 0.00/ml, P<0.05), but not in part-solid or pure solid nodules. For pGGO nodules, the area under the receiver operating characteristic (ROC) curve of CTC count was 0.833, which was significantly higher than that of maximum of standardized uptake value (SUVmax) (P<0.001). Its sensitivity and specificity was 80.0% and 83.3%, respectively. Conclusion The peptide-based nanomagnetic CTC detection system can differentiate malignant tumor and benign lesions in pulmonary nodules presented as pGGO. It is of great clinical potential as a noninvasive, nonradiating method to identify malignancies in pulmonary nodules.
Objective To construct the differential diagnosis model of viral pneumonia and bacterial pneumonia based on lung ultrasonography (LUS) characteristics. Methods A total of 248 patients with pneumonia who completed LUS in our hospital from January 2021 to March 2024 were retrospectively included, and were divided into a viral group (140 cases) and a bacterial group (108 cases) according to the final etiological diagnosis. Predictors in differential diagnosis between viral pneumonia and bacterial pneumonia were analyzed by univariate and multivariate methods. The differential diagnosis model of viral pneumonia and bacterial pneumonia and the prediction efficiency were evaluated. Results Univariate and multivariate logistic analysis showed that the presence or absence of lung consolidation, pleural effusion, B-line range of both lungs and pulmonary ultrasound score were independent predictors of the differential diagnosis of viral pneumonia and bacterial pneumonia (P<0.05). Using the logistic regression model of lung consolidation, pleural effusion, bilateral B-line range, and pulmonary ultrasound score, including the P-values of three variables (lung consolidation, pleural effusion, and bilateral B-line range), and the P-values of four variables (lung consolidation, pleural effusion, bilateral B-line range, and pulmonary ultrasound score), the receiver operating characteristic curve was used to predict the diagnosis of patient. The areas under the curve were 0.863, 0.612, 0.669, 0.684, 0.904, and 0.920, respectively. Conclusion Lung consolidation, pleural effusion, B-line range of both lungs and pulmonary ultrasound score detected by LUS have good diagnostic efficacy in the differential diagnosis of viral pneumonia and bacterial pneumonia, suggesting that LUS technology may be used in the differential diagnosis of viral pneumonia and bacterial pneumonia.
ObjectiveTo investigate the research progress of etiology, pathogenesis, diagnosis, differential diagnosis, and treatment of granulomatous lobular mastitis (GLM). MethodA comprehensive analysis was conducted by reviewing the domestic and foreign literatures on GLM and combining with clinical experience. ResultsGLM was a relatively rare chronic inflammatory disease of the breast, and the number of patients had been increasing in recent years. It mainly occured in multiparous women of childbearing age. Clinically, it was characterized by a hard breast mass with or without redness and pain, and severe cases might be accompanied by nodular erythema and arthritis. Bacterial infection, especially Corynebacterium kroppenstedtii and autoimmunity were considered to be the main causes of GLM. The diagnosis of GLM needed to combine with medical history, clinical manifestations, histopathological findings, imaging findings, and laboratory tests. A multidisciplinary team for diagnosis and treatment of GLM should be established to improve the diagnostic accuracy and reduce misdiagnosis. At present, the treatment methods for GLM were mainly conservative treatment and surgical treatment, including follow-up observation, antibiotic treatment, glucocorticoid treatment, immunosuppressive therapy, surgical treatment, traditional Chinese medicine treatment, and combined treatment. ConclusionsAt present, the incidence of GLM is on the rise, but its etiology and pathogenesis are still unclear. The diagnosis needs to combine with many aspects, and it is recommended that the multidisciplinary team could improve the accuracy of diagnosis. There is still no unified standard for the selection and timing of treatment. Clinicians’ experience and patients’ wishes should be taken into account when choosing treatment options in clinical practice. Prospective and high-quality multicenter clinical trials and evidence-based medicine practice are still needed to further improve diagnosis and treatment of GLM.
Objective To develop and validate a composite model (PAH score) based on dual-center data, integrating logistic regression and machine learning approaches, to improve the preoperative differential diagnostic efficacy for appendiceal mucinous neoplasms (AMNs). MethodsA dual-center retrospective case-control design was adopted. The study included 108 AMNs patients and 230 healthy controls from The 900th Hospital of Joint Logistics Support Force (January 2014 to November 2024) and Sanming First Hospital Affiliated to Fujian Medical University (December 2018 to December 2023) for feature screening and model construction. Additionally, 258 patients with pathologically confirmed chronic appendicitis (CA) from the same period were included as the differential validation group. Predictors were screened using leastabsolute shrinkage and selection operator combined with traditional logistic regression, and four machine learning algorithms—random forest, support vector machine, gradient boosting, and decision tree—were applied to rank feature importance. Core variables consistently identified by both approaches were integrated to construct a logistic regression model. Based on the model results, the PAH score was formulated, and its performance in distinguishing AMNs from CA was validated. An online visualization platform for AMNs risk prediction was subsequently developed. ResultsBaseline characteristics were balanced between the AMNs group and healthy control group, as well as between the AMNs group and CA group (P>0.05). Multivariate logistic regression identified prognostic nutritional index (PNI, OR=0.81), albumin-to-globulin ratio (AGR, OR=0.37), and hemoglobin to red blood cell distribution width ratio (HRR, OR=0.36) as independent predictors of AMNs (all P<0.001). All four machine learning algorithms consistently ranked PNI, AGR, and HRR as the top three important features. Based on these findings, a PAH model was constructed, and the PAH score was calculated using the standardized regression coefficient weighting method as follows: PAH score=20.8–0.21×PNI–0.99×AGR–1.01×HRR. The model demonstrated excellent discriminative ability for AMNs, with an area under the curve (AUC) of 0.918. The Hosmer-Lemeshow test indicated good calibration between predicted and observed probabilities (P=0.925). Decision curve analysis (DCA) showed significant net clinical benefit within the risk threshold range of 0.05–0.95. Bootstrap internal validation confirmed robust model performance (AUC=0.911). The median PAH score was significantly higher in the AMNs group than that of the CA group (MD=1.78, P<0.001). For distinguishing AMNs from CA, the PAH score achieved an AUC of 0.758. At the optimal cutoff value (–1.00), sensitivity was 70%, specificity was 76%, and accuracy rate was 74%. The Hosmer-Lemeshow test again confirmed good calibration (P=0.106), and Bootstrap validation indicated stable performance (AUC=0.783). DCA further demonstrated considerable net benefit within the threshold range of 0.20–0.95. ConclusionsThe PAH score developed in this study effectively predicts the risk of AMNs and accurately differentiates AMNs from CA, showing promising clinical application potential. However, as an exploratory study, further validation through multicenter, large-sample, prospective studies with diverse control groups is needed to enhance the generalizability and stability of the scoring system.
Hepatic angiomyolipoma (HAML) is a rare benign mesenchymal tumor of the liver, which has highly variable imaging appearances, often leads to missed diagnosis and misdiagnosis. The images of 2 patients with HAML confirmed by pathology were presented in this study, and the typical imaging features of the HAML, the underlying pathophysiological mechanism, and the differential diagnosis were briefly summarized so as to deepen the understanding of HAML and to improve the diagnosis and differential diagnosis abilities of HAML, then reduce the rates of missed diagnosis and misdiagnosis of the HAML.