1.Follicular thyroid imaging reporting and data system for differentiating benign and malignant follicular thyroid lesions
Yuchen LI ; Lishan XIAO ; Mengmeng YAN ; Meixia DU ; Cheng ZHAO ; Chunping NING
Chinese Journal of Medical Imaging Technology 2025;41(2):250-253
Objective To observe the value of follicular thyroid imaging reporting and data system(F-TIRADS)for differentiating benign and malignant follicular thyroid lesions.Methods Totally 502 patients with follicular thyroid lesions were retrospectively enrolled,including 104 patients with single malignant lesion(malignant group,containing 77 follicular thyroid carcinomas[FTC]and 27 follicular variant of papillary thyroid carcinomas[FVPTC])and 398 patients with 416 benign lesions(benign group,containing 197 follicular thyroid adenomas[FTA]and 219 thyroid adenomatous hyperplasia).Ultrasonic features of lesions were recorded,and F-TIRADS scores were assigned by 1 junior and 1 senior ultrasound physicians.Taken histopathology results as gold standard,receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy for differentiating benign and malignant follicular thyroid lesions using F-TIRADS.Results Significant differences of composition,internal echo,boundary,calcification and trabecular structure of lesions were found between groups(all P<0.001).Taken F-TIRADS score≥ 7 as the optimal cut-off value,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value for differentiating benign and malignant follicular thyroid lesions by the junior physician was 76.92%,77.40%,77.31%,93.06%and 45.98%,while by the senior physician was 78.84%,81.25%,80.76%,93.89%and 51.25%,respectively.The efficacy of the latter was higher than of the former(AUC was 0.827 and 0.859,respectively,P<0.05).Conclusion F-TIRADS could effectively identifying benign and malignant follicular thyroid lesions.
2.Improved ResNet18 lightweight deep learning models for automatically detecting gouty arthritis lesions based on ultrasonogram of the first metatarsophalangeal joint
Lishan XIAO ; Yizhe ZHAO ; Yuchen LI ; Mengmeng YAN ; Meixia DU ; Cheng ZHAO ; Manhua LIU ; Chunping NING
Chinese Journal of Medical Imaging Technology 2025;41(5):783-787
Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P>0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P<0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.
3.Follicular thyroid imaging reporting and data system for differentiating benign and malignant follicular thyroid lesions
Yuchen LI ; Lishan XIAO ; Mengmeng YAN ; Meixia DU ; Cheng ZHAO ; Chunping NING
Chinese Journal of Medical Imaging Technology 2025;41(2):250-253
Objective To observe the value of follicular thyroid imaging reporting and data system(F-TIRADS)for differentiating benign and malignant follicular thyroid lesions.Methods Totally 502 patients with follicular thyroid lesions were retrospectively enrolled,including 104 patients with single malignant lesion(malignant group,containing 77 follicular thyroid carcinomas[FTC]and 27 follicular variant of papillary thyroid carcinomas[FVPTC])and 398 patients with 416 benign lesions(benign group,containing 197 follicular thyroid adenomas[FTA]and 219 thyroid adenomatous hyperplasia).Ultrasonic features of lesions were recorded,and F-TIRADS scores were assigned by 1 junior and 1 senior ultrasound physicians.Taken histopathology results as gold standard,receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy for differentiating benign and malignant follicular thyroid lesions using F-TIRADS.Results Significant differences of composition,internal echo,boundary,calcification and trabecular structure of lesions were found between groups(all P<0.001).Taken F-TIRADS score≥ 7 as the optimal cut-off value,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value for differentiating benign and malignant follicular thyroid lesions by the junior physician was 76.92%,77.40%,77.31%,93.06%and 45.98%,while by the senior physician was 78.84%,81.25%,80.76%,93.89%and 51.25%,respectively.The efficacy of the latter was higher than of the former(AUC was 0.827 and 0.859,respectively,P<0.05).Conclusion F-TIRADS could effectively identifying benign and malignant follicular thyroid lesions.
4.Improved ResNet18 lightweight deep learning models for automatically detecting gouty arthritis lesions based on ultrasonogram of the first metatarsophalangeal joint
Lishan XIAO ; Yizhe ZHAO ; Yuchen LI ; Mengmeng YAN ; Meixia DU ; Cheng ZHAO ; Manhua LIU ; Chunping NING
Chinese Journal of Medical Imaging Technology 2025;41(5):783-787
Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P>0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P<0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.
5.Consistency and difference analysis of ultrasound and dual-energy computed tomography in assessing gouty knee arthritis
Mengmeng YAN ; Meixia DU ; Lishan XIAO ; Yuchen LI ; Xiaoli LI ; Cheng ZHAO ; Chunping NING
Chinese Journal of Ultrasonography 2024;33(7):597-602
Objective:To assess the consistency of ultrasound and dual-energy computed tomography (DECT) in the diagnosis of gouty arthritis(GA), reasons of the differences were further analyzed.Methods:The ultrasound and DECT images of 150 knee joints from 147 patients diagnosed with gout at the Gout Specialty Clinic of Qingdao University Affiliated Hospital from February 2022 to October 2023 were retrospectively analyzed. According to anatomy, the knee joint was anatomically segmented into five regions: intra-articular, anterior, posterior, medial, and lateral.Location of monosodium urate (MSU) deposition was meticulously recorded. The Kappa consistency test was employed to assess the consistency of the two examination results in different regions of the knee joint. The McNemar chi-square test was utilized to conduct a differential analysis between DECT and ultrasound results.Results:Double contour sign(DCS) (81.2%, 92/112) was the most common intra-articular ultrasound sign in knee joints with GA. In the extra-articular region, MSU was commonly deposited in and around the popliteal tendon (ultrasound: 51.6%, 66/128; DECT: 54.7%, 70/128). Corresponding MSU deposits on DECT were found in 9 of 92 joints with DCS and in 9 of 49 joints with aggregates detected on ultrasound.In the assessment of MSU deposits, ultrasound showed an overall higher positive rate than DECT (87.3% vs. 72.3%, P=0.001), with poor consistency between the two examinations (Kappa=0.153). In distinct anatomical regions, ultrasound and DECT showed high consistency in the medial (Kappa=0.697) and lateral (Kappa=0.718) sides and the difference was not statistically significant ( P>0.05). Intra-articular (Kappa=0.289) and anterior (Kappa=0.303) regions exhibited only fair consistency, with statistically significant diagnostic differences ( P<0.05). When exclusively assessing cases with tophus, ultrasound and DECT demonstrated high consistency in the medial and lateral aspects(Kappa=0.685, 0.748) without statistical difference ( P>0.05). In the anterior region, the consistency between the two examinations was moderate (Kappa=0.256), while in the intra-articular region, the consistency of the two methods was lower (Kappa=0.147), and the differences was statistically significant ( P<0.001). Conclusions:Both ultrasound and DECT exhibit good diagnostic capabilities for gouty knee arthritis.However, the consistency between the two techniques varies in different anatomical locations. Clinical assessment should be tailored based on the specific anatomical position. DECT has an advantage in evaluating intra-articular MSU deposits, while ultrasound is more sensitive to detect early and scattered MSU deposits.
6.Clinical value of the Thyroid Follicular Tumor Ultrasound Risk Stratification System in differentiating thyroid follicular carcinoma and follicular adenoma
Lishan XIAO ; Yuchen LI ; Mengmeng YAN ; Meixia DU ; Cheng ZHAO ; Chunping NING
Chinese Journal of Ultrasonography 2024;33(9):791-799
Objective:To assess the discriminatory value of the Thyroid Follicular Tumor Ultrasound Risk Stratification System (F-TIRADS) in differentiating follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA), and to compare its performance with other risk stratification systems(RSS).Methods:A retrospective analysis was conducted on 325 patients (327 thyroid nodules) diagnosed postoperatively as FTC or FTA at Affiliated Hospital of Qingdao University from January 2016 to December 2023. The cases were divided into FTC group (81 nodules) and FTA group (246 nodules). The nodules were classified based on F-TIRADS, the 2020 Chinese Thyroid Imaging Reporting and Data System (C-TIRADS), the 2015 American Thyroid Association guidelines (ATA guidelines), and the 2017 European Thyroid Association Thyroid Imaging Reporting and Data System (EU-TIRADS) by two ultrasound physicians. Multivariate Logistic regression analysis was used to identify independent predictors associated with FTC. Diagnostic performance of the 4 RSS was compared using postoperative pathological results as the gold standard.Results:Multivariate Logistic regression analysis showed maximum diameter, solid composition, hypoechogenicity, unclear or angular margins, marginal or ring calcifications, trabecular structure, and central blood flow were independent predictors of FTC( OR=1.914, 3.427, 9.926, 9.163, 45.918, 3.191, 8.936, respectively; all P<0.05). Within each RSS, the actual malignancy rate increased with higher risk categories, aligning closely with the recommended malignancy rates (except for ATA guidelines). The optimal cut-off values for distinguishing FTC from FTA were FTC risk 50%-90% in F-TIRADS, C-TIRADS 4B, moderately suspicious nodules in ATA guidelines, and EU-TIRADS 4, with areas under the curve of 0.916, 0.808, 0.827, and 0.836, respectively. F-TIRADS demonstrated the best overall performance (sensitivity: 82.72%, specificity: 82.93%), with significant differences compared with C-TIRADS, ATA guidelines, and EU-TIRADS (all P<0.05). Conclusions:F-TIRADS is highly effective in distinguishing FTA from FTC, outperforming C-TIRADS, ATA Guidelines, and EU-TIRADS. Clinicians should pay close attention to solid hypoechoic nodules with unclear or angular margins, marginal or ring calcifications, central blood flow, or a trabecular structure.
7.Evidence summary of surgical site infection prevention in adult inpatients based on guidelines and clini-cal decision making
Qingmei LEI ; Lishan OU ; Donglan LING ; Qiuchen CHENG ; Shizhen ZHANG ; Zhaotao WANG ; Hongbo YAN
Modern Hospital 2024;24(2):222-226
Objective To provide evidence-based references for the prevention of surgical site infection(SSI)by sum-marizing the best evidence for the prevention of SSI in adult inpatients.Methods The'6S'evidence resource pyramid model was used to systematically search the related evidence in domestic and foreign databases,guideline websites,and academic socie-ty websites from the inception of the database to September 30,2023.Four researchers evaluated the quality of the included guidelines,and two researchers independently evaluated the quality of other types of literature and rated the level of evidence.Results A total of 12 articles were included,including 6 clinical decision making and 6 clinical guidelines.Thirty best items of the evidence were summarized from 7 aspects:diagnosis,clinical symptoms,influencing factors,patient prevention strategies,preventive strategies for medical staff,intraoperative and postoperative treatment,and consultation and education.Conclusion Clinical staff should develop a standardized management plan for infection prevention based on corresponding evidence to reduce the incidence of SSI instead of taking a single measurement.Moreover,they need to formulate a standardized work process for preventing SSI based on the clinical practice and patients'preference.
10.Mechanism of "Sanyang" combined therapy of traditional Chinese medicine in alleviating colonic injury in mice induced by influenza virus based on transcriptome sequencing technique
Yanan ZHANG ; Jun YAN ; Liqiong SONG ; Yuanming HUANG ; Chang LIU ; Guoxing LIU ; Jintong LI ; Yue ZHANG ; Mingzhe WANG ; Zhiguang ZHAI ; Chengxiang WANG ; Lishan ZHANG ; Chengjun BAN ; Wenbo XU ; Miao CHENG
Chinese Journal of Experimental and Clinical Virology 2023;37(2):159-167
Objective:To explore the mechanism of Ma-Xing Shi-Gan decoction combined with Xiao-Chai-Hu decoction (hereinafter referred to as " Sanyang combined treatment" ) in alleviating colon injury in mice infected with influenza virus by transcriptome sequencing technique.Methods:The mouse model of colonic injury caused by influenza virus was induced by intranasal drip of influenza A virus H1N1 suspension. The mice were divided into Control group, Model group, and Sanyang combined treatment (SCT) group. Model group and SCT group were fed with PBS and Ma-Xing Shi-Gan decoction combined with Xiao-Chai-Hu decoction respectively. Seven days later, the colon tissues of each group were taken, the colon length and pathological damage were observed, and the transcriptome was sequenced to screen the significantly different genes between the SCT group and model group for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis(GSEA).Results:After the therapy with SCT, the length of the colon of mice was significantly improved and the pathological injury of the colon was reduced. There are 92 differentially expressed genes between the SCT group and the model group. GO analysis indicated that the differential genes were enriched in biological processes such as regulation of cytokine and chemokine production, inflammatory response, defense response, immune response, regulation of NF-κB inducing kinase(NIK)/Nuclear factor-κB(NF-κB) signal and Mitogen-activated protein kinase(MAPK) cascade, as well as cell components related to intestinal barrier such as brush border membrane, brush border and microvilli. KEGG analysis indicated that the differential genes were enriched in Toll-like receptor signaling pathway, intestinal immune network for IgA production, complement and coagulation cascade, and Peroxisome proliferator-activated receptor(PPAR) signaling pathway. GSEA indicated that the intestinal immune network for IgA production, PPAR signaling pathway, propionic acid metabolism and butyrate metabolism were significantly up-regulated after the intervention with SCT, while apoptosis and MAPK signaling pathway were significantly down-regulated.Conclusions:Sanyang combined therapy can protect the intestinal tract of mice infected with influenza virus mainly through immunity, inflammation and metabolism pathways.

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