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BACKGROUND: The prognostic significance of lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remains controversial. Notably, there is evidence suggesting an association between tissue stiffness and the aggressiveness of the disease. We therefore aimed to explore the effect of tissue stiffness on LNM-related invasiveness in PTC patients. METHOD: A total of 2492 PTC patients from 3 hospitals were divided into an LNM group and a non-LNM group based on their pathological results. The effects of interior lesion stiffness (E) and peri-cancerous tissue stiffness (Eshell) on the LNM-related recurrence rate and mortality in each patient with PTC subgroup were analyzed. The activation of cancer-associated fibroblasts (CAFs) and extracellular matrix component type 1 collagen (COL-I) in the lesion were compared and analyzed across different subgroups. The underlying biological basis of differences in each subgroup was identified using RNA sequencing (RNA-seq) data. RESULTS: The Eshell value and Eshell/E in the LNM group were significantly higher than those in the non-LNM group of patients with PTC (Eshell: 72.72â ±â 5.63 vs 66.05â ±â 4.46; Eshell/E: 1.20â ±â 1.72 vs 1.09â ±â 1.10, Pâ <â .001). When Eshell/Eâ >â 1.412 and LNM were both present, the recurrence rate and mortality were significantly increased compared to those of group of patients with LNM (91.67% and 7.29%, respectively). The CAF activation and COL-I content in the Eshell/E+ group were significantly higher than those in the Eshell/E- group (all Pâ <â .001), and the RNA-seq results revealed significant extracellular matrix (ECM) remodeling in the LNM-Eshell/E+ group. CONCLUSIONS: Stiff peri-cancerous tissue induced CAF activation, COL-I deposition, and ECM remodeling, resulting in a poor prognosis for PTC patients with LNM.
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BACKGROUND: There is some evidence to suggest that there may be a link between body mass index (BMI) and the development of kidney stones, it remains unclear whether weight change was associated with the presence of kidney stone. AIMS: The objective of this study was to investigate the potential association between changes patterns in weight during adulthood and the incidence of kidney stone. METHODS: This study included 14472 participants aged 30-75 years, whose BMI was recorded at both baseline and 10 years prior to the survey. We categorized individuals into five weight change patterns: stable healthy, non-obesity to obesity, obesity to non-obesity, stable obesity, and maximum overweight. Odds ratios (OR) and 95% confidence intervals (CI) relating weight change to incident kidney stone were calculated using logistic regression models adjusting for covariates. The non-linear association between absolute weight change was investigated using the restricted cubic spline (RCS) regression. The supposed population attributable fraction (PAF) for the weight change patterns was calculated. RESULTS: After adjusting for all confounders, participants changing from non-obesity to obesity, obesity to non-obesity, and stable obesity had significantly higher risks of kidney stone than those with healthy weight during adulthood (OR = 1.59, 95% CI:1.18-2.13; OR = 1.78, 95% CI: 1.47-2.16; OR = 1.80, 95% CI: 1.48-2.19, respectively). A U-shaped association was observed, and the risk of kidney stone was lowest in participants with stable healthy BMI. If the population had maintained a healthy BMI, a 28.7% (95% CI: 18.6%-37.5%) lower incidence of kidney stones was observed. CONCLUSIONS: This study found that changes in weight during adulthood are linked to the risk of developing kidney stones. Maintaining healthy weight during adulthood is important for reducing the risk of developing kidney stones.
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Cálculos Renais , Obesidade , Humanos , Adulto , Incidência , Fatores de Risco , Obesidade/complicações , Obesidade/epidemiologia , Sobrepeso/epidemiologia , Índice de Massa Corporal , Cálculos Renais/epidemiologia , Cálculos Renais/etiologiaRESUMO
BACKGROUND: Patients with alpha-fetoprotein (AFP)-positive hepatocellular carcinoma (HCC) have aggressive biological behavior and poor prognosis. Therefore, survival time is one of the greatest concerns for patients with AFP-positive HCC. This study aimed to demonstrate the utilization of six machine learning (ML)-based prognostic models to predict overall survival of patients with AFP-positive HCC. METHODS: Data on patients with AFP-positive HCC were extracted from the Surveillance, Epidemiology, and End Results database. Six ML algorithms (extreme gradient boosting [XGBoost], logistic regression [LR], support vector machine [SVM], random forest [RF], K-nearest neighbor [KNN], and decision tree [ID3]) were used to develop the prognostic models of patients with AFP-positive HCC at one year, three years, and five years. Area under the receiver operating characteristic curve (AUC), confusion matrix, calibration curves, and decision curve analysis (DCA) were used to evaluate the model. RESULTS: A total of 2,038 patients with AFP-positive HCC were included for analysis. The 1-, 3-, and 5-year overall survival rates were 60.7%, 28.9%, and 14.3%, respectively. Seventeen features regarding demographics and clinicopathology were included in six ML algorithms to generate a prognostic model. The XGBoost model showed the best performance in predicting survival at 1-year (train set: AUC = 0.771; test set: AUC = 0.782), 3-year (train set: AUC = 0.763; test set: AUC = 0.749) and 5-year (train set: AUC = 0.807; test set: AUC = 0.740). Furthermore, for 1-, 3-, and 5-year survival prediction, the accuracy in the training and test sets was 0.709 and 0.726, 0.721 and 0.726, and 0.778 and 0.784 for the XGBoost model, respectively. Calibration curves and DCA exhibited good predictive performance as well. CONCLUSIONS: The XGBoost model exhibited good predictive performance, which may provide physicians with an effective tool for early medical intervention and improve the survival of patients.
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Carcinoma Hepatocelular , Neoplasias Hepáticas , Aprendizado de Máquina , alfa-Fetoproteínas , Feminino , Humanos , Masculino , Algoritmos , alfa-Fetoproteínas/metabolismo , Área Sob a Curva , Calibragem , Carcinoma Hepatocelular/sangue , Carcinoma Hepatocelular/diagnóstico , Carcinoma Hepatocelular/patologia , Carcinoma Hepatocelular/mortalidade , Neoplasias Hepáticas/sangue , Neoplasias Hepáticas/diagnóstico , Neoplasias Hepáticas/patologia , Neoplasias Hepáticas/mortalidade , Prognóstico , Curva ROCRESUMO
BACKGROUND: Ovarian damage and follicle loss are major side effects of chemotherapy in young female patients with cancer. However, effective strategies to prevent these injuries are still lacking. The purpose of this study was to verify low-intensity pulsed ultrasound (LIPUS) can reduce ovarian injury caused by chemotherapy and to explore its underlying mechanisms in mice model. METHODS: The mice were randomly divided into the Control group, Cisplatin group, and Cisplatin + LIPUS group. The Cisplatin group and Cisplatin + LIPUS group were intraperitoneally injected with cisplatin every other day for a total of 10 injections, and the Control group was injected with saline. On the second day of each injection, the Cisplatin + LIPUS group received irradiation, whereas the other two groups received sham irradiation. We used a variety of biotechnologies to detect the differences in follicle count, granulosa cell apoptosis, fibrosis, transcriptome level, oxidative damage, and inflammation in differently treated mice. RESULT: LIPUS was able to reduce primordial follicle pool depletion induced by cisplatin and inhibit the apoptosis of granulosa cells. Transcriptomic results confirmed that LIPUS can reduce ovarian tissue injury. We demonstrated that LIPUS can relieve ovarian fibrosis by inhibiting TGF-ß1/Smads pathway. Meanwhile, it can reduce the oxidative damage and reduced the mRNA levels of proinflammatory cytokines caused by chemotherapy. CONCLUSION: LIPUS can reduce the toxic effects of chemotherapy drugs on ovaries, inhibit ovarian fibrosis, reduce the inflammatory response, and redcue the oxidative damage, reduce follicle depletion and to maintain the number of follicle pools.
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Antineoplásicos , Cisplatino , Ovário , Ondas Ultrassônicas , Animais , Feminino , Camundongos , Cisplatino/efeitos adversos , Ovário/efeitos dos fármacos , Ovário/efeitos da radiação , Ovário/patologia , Antineoplásicos/efeitos adversos , Antineoplásicos/toxicidade , Apoptose/efeitos dos fármacos , Apoptose/efeitos da radiação , Folículo Ovariano/efeitos dos fármacos , Folículo Ovariano/efeitos da radiação , Terapia por Ultrassom/métodosRESUMO
OBJECTIVE: Through machine learning (ML) analysis of the radiomics features of ultrasound extracted from patients with lupus nephritis (LN), this attempt was made to non-invasively predict the chronicity index (CI)of LN. METHODS: A retrospective collection of 136 patients with LN who had renal biopsy was retrospectively collected, and the patients were randomly divided into training set and validation set according to 7:3. Radiomics features are extracted from ultrasound images, independent factors are obtained by using LASSO dimensionality reduction, and then seven ML models were used to establish predictive models. At the same time, a clinical model and an US model were established. The diagnostic efficacy of the model is evaluated by analysis of the receiver operating characteristics (ROC) curve, accuracy, specificity, and sensitivity. The performance of the seven machine learning models was compared with each other and with clinical and US models. RESULTS: A total of 1314 radiomics features are extracted from ultrasound images, and 5 features are finally screened out by LASSO for model construction, and the average ROC of the seven ML is 0.683, among which the Xgboost model performed the best, and the AUC in the test set is 0.826 (95% CI: 0.681-0.936). For the same test set, the AUC of clinical model constructed based on eGFR is 0.560 (95% CI: 0.357-0.761), and the AUC of US model constructed based on Ultrasound parameters is 0.679 (95% CI: 0.489-0.853). The Xgboost model is significantly more efficient than the clinical and US models. CONCLUSION: ML model based on ultrasound radiomics features can accurately predict the chronic degree of LN, which can provide a valuable reference for clinicians in the treatment strategy of LN patients.
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Lúpus Eritematoso Sistêmico , Nefrite Lúpica , Humanos , Radiômica , Estudos Retrospectivos , UltrassonografiaRESUMO
BACKGROUND: Orofacial clefts are one of the most common congenital malformations of the fetal face and ultrasound is mainly responsible for its diagnosis. It is difficult to view the fetal palate, so there is currently no unified standard for fetal palate screening, and the diagnosis of cleft palate is not included in the relevant prenatal ultrasound screening guidelines. Many prenatal diagnoses for cleft palate are missed due to the lack of effective screening methods. Therefore, it is imperative to increase the display rate of the fetal palate, which would improve the detection rate and diagnostic accuracy for cleft palate. We aim to introduce a fetal palate screening software based on the "sequential sector scan though the oral fissure", an effective method for fetal palate screening which was verified by our follow up results and three-dimensional ultrasound and to evaluate its feasibility and clinical practicability. METHODS: A software was designed and programmed based on "sequential sector scan through the oral fissure" and three-dimensional ultrasound. The three-dimensional ultrasound volume data of the fetal face were imported into the software. Then, the median sagittal plane was taken as the reference interface, the anterior upper margin of the mandibular alveolar bone was selected as the fulcrum, the interval angles, and the number of layers of the sector scan were set, after which the automatic scan was performed. Thus, the sector scan sequential planes of the mandibular alveolar bone, pharynx, soft palate, hard palate, and maxillary alveolar bone were obtained in sequence to display and evaluate the palate. In addition, the feasibility and accuracy of the software in fetal palate displaying and screening was evaluated by actual clinical cases. RESULTS: Full views of the normal fetal palates and the defective parts of the cleft palates were displayed, and relatively clear sequential tomographic images and continuous dynamic videos were formed after the three-dimensional volume data of 10 normal fetal palates and 10 cleft palates were imported into the software. CONCLUSIONS: The software can display fetal palates more directly which might allow for a new method of fetal palate screening and cleft palate diagnosis.
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Fissura Palatina , Imageamento Tridimensional , Software , Ultrassonografia Pré-Natal , Humanos , Ultrassonografia Pré-Natal/métodos , Fissura Palatina/diagnóstico por imagem , Fissura Palatina/embriologia , Imageamento Tridimensional/métodos , Gravidez , Feminino , Palato/diagnóstico por imagem , Palato/embriologia , Adulto , Estudos de ViabilidadeRESUMO
BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predicting the diagnosis of Non-Alcoholic Steatohepatitis. METHOD: An SD rat model of hepatic steatosis was established through a high-fat diet and subcutaneous injection of CCl4. Liver ultrasound images and elastography were acquired, along with serum data and histopathological results of rat livers.The Pyradiomics software was used to extract radiomic features from 2D ultrasound images of rat livers. The rats were then randomly divided into a training set and a validation set, and feature selection was performed through dimensionality reduction. Various machine learning (ML) algorithms were employed to build clinical diagnostic models, radiomic models, and combined diagnostic models. The efficiency of each diagnostic model for diagnosing NASH was evaluated using Receiver Operating Characteristic (ROC) curves, Clinical Decision Curve Analysis (DCA), and calibration curves. RESULTS: In the machine learning radiomic model for predicting the diagnosis of NASH, the Area Under the Curve (AUC) of ROC curve for the clinical radiomic model in the training set and validation set were 0.989 and 0.885, respectively. The Decision Curve Analysis revealed that the clinical radiomic model had the highest net benefit within the probability threshold range of > 65%. The calibration curve in the validation set demonstrated that the clinical combined radiomic model is the optimal method for diagnosing Non-Alcoholic Steatohepatitis. CONCLUSION: The combined diagnostic model constructed using machine learning algorithms based on ultrasound image radiomics has a high clinical predictive performance in diagnosing Non-Alcoholic Steatohepatitis.
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Aprendizado de Máquina , Hepatopatia Gordurosa não Alcoólica , Radiômica , Ultrassonografia , Animais , Masculino , Ratos , Algoritmos , Modelos Animais de Doenças , Técnicas de Imagem por Elasticidade/métodos , Hepatopatia Gordurosa não Alcoólica/diagnóstico por imagem , Ratos Sprague-Dawley , Curva ROC , Ultrassonografia/métodosRESUMO
OBJECTIVES: The present study aims to explore the role of shear wave elastography (SWE) in the diagnosis of Peyronie disease (PD). METHODS: A total of 59 PD patients and 59 age-matched healthy adult men were included in this study. The B-mode ultrasound (US) and SWE were performed for all subjects, and the Young modulus (YM) values of the corresponding regions of the penis in the PD and control groups were recorded and compared. RESULTS: The mean age of the included PD patients and age-matched controls was 53.81 years (SD 9.52, range 32-73). On B-mode US evaluation, 41 (69.5%) of 59 included PD patients were found to have penile plaques, and the remaining 18 (30.5%) patients had no evidence of penile plaque. After evaluation using SWE, the YM values in the penile plaque region of these 41 patients with penile dysplasia were found to be significantly higher (60.29 kPa ± 19.95) than those outside the plaque (in the same patient) (21.05 kPa ± 4.58) and in the same penile region of the control group (20.59 kPa ± 4.65) (P < .001). In the remaining 18 PD patients, the results showed that the YM value of the abnormal penile region in the PD patients (56.67 kPa ± 13.52) was significantly higher than the YM value outside the abnormal penile region in the same patients (22.79 kPa ± 4.31) and in the same penile region in the control group (19.87 kPa ± 3.48) (P < .001; P < .001). CONCLUSIONS: In conclusion, this study showed that SWE as a non-invasive technique is useful in identifying and differentiating penile plaques in PD patients and is a simple, rapid and complementary method to B-mode US.
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Técnicas de Imagem por Elasticidade , Induração Peniana , Placa Aterosclerótica , Masculino , Adulto , Humanos , Pessoa de Meia-Idade , Técnicas de Imagem por Elasticidade/métodos , Induração Peniana/diagnóstico por imagem , Ultrassonografia , Módulo de Elasticidade , Interpretação de Imagem Assistida por Computador/métodosRESUMO
OBJECTIVES: To investigate the application value of shear wave dispersion (SWD) in healthy adults with the lumbar multifidus muscle (LMM), to determine the range of normal reference values, and to analyze the influences of factors on the parameter. METHODS: Ninety-five healthy volunteers participated in the study, from whom 2-dimensional, shear wave elastography (SWE), and SWD images of the bilateral LMM were acquired in three positions (prone, standing, and anterior flexion). Subcutaneous fat thickness (SFH), SWE velocity, and SWD slope were measured accordingly for analyses. RESULTS: The mean SWD slope of the bilateral LMM in the prone position was as follows: left: 14.8 ± 3.1 (m/second)/kHz (female) and 13.0 ± 2.5 (m/second)/kHz (male); right: 14.8 ± 3.7 (m/second)/kHz (female) and 14.2 ± 3.4 (m/second)/kHz (male). In the prone position, there was a weak negative correlation between the bilateral LMM SWD slope of activity level 2 and level 1 (ß = -1.5 (2 versus 1, left), -1.9 (2 versus 1, right), all P < .05), and between the left SWD slope of activity level 3 and level 1 (ß = -2.3 [3 versus 1, left], P < .05). The correlation between SWE velocity and SWD slope value changed with the position: there was a weak positive correlation in the prone position (r = 0.3 [left], 0.37 [right], both P < .05), and a moderate positive correlation in the standing and anterior flexed positions (r = 0.49-0.74, both P < .001). SFH was moderately negatively correlated with bilateral SWD slope values in the anterior flexion (left: r = -0.4, P = .01; right: r = -0.7, P < .01). CONCLUSIONS: SWD imaging can be used as an adjunct tool to aid in the assessment of viscosity in LMM. Further, activity level, and position are influencing factors that should be considered in clinical practice.
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Técnicas de Imagem por Elasticidade , Músculos Paraespinais , Adulto , Humanos , Masculino , Feminino , Músculos Paraespinais/diagnóstico por imagem , Técnicas de Imagem por Elasticidade/métodos , Região Lombossacral/diagnóstico por imagem , Voluntários Saudáveis , ViscosidadeRESUMO
BACKGROUND: Prenatal diagnosis of cleft palate is still challenging. To describe a practical and efficient method, sequential sector-scan through oral fissure (SSTOF), to evaluate palate. METHODS: According to the characteristics of the fetal oral anatomy and ultrasonic directivity, we designed a practical method, sequential sector-scan through oral fissure, to evaluate the fetal palate, and the approach was verified efficiently by following up results of those fetuses with orofacial cleft who were induced because of their accompanied lethal malformations. Then, the 7098 fetuses were evaluated using sequential sector-scan through oral fissure. Fetuses were followed up after birth or induction to validate and analyze prenatal diagnosis. RESULT: According to the scanning design, sequential sector-scan through oral fissure was performed successfully from the soft palate to the upper alveolar ridge in induced labor fetuses, and the structures were displayed clearly. Among 7098 fetuses, satisfactory images were obtained for 6885 fetuses and the remaining 213 fetuses' images were unsatisfactory because of fetuses' positions and pregnant women with high BMI. Among 6885 fetuses, 31cases were diagnosed CLP or CP, which were confirmed after delivery or termination. There were no missing cases. CONCLUSIONS: SSTOF is a practical and efficient method to diagnose cleft palate, which might be applied to evaluate the fetal palate in prenatal diagnosis.
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Fenda Labial , Fissura Palatina , Gravidez , Humanos , Feminino , Fissura Palatina/diagnóstico por imagem , Ultrassonografia Pré-Natal/métodos , Diagnóstico Pré-Natal/métodosRESUMO
BACKGROUND: In terms of embryonic origin, vascular ring is a congenital anomaly in which the aortic arch and its branches completely or incompletely encircle and compress the trachea or esophagus. Early and accurate diagnosis of a vascular ring is the key to treatment. Prenatal diagnosis mainly relies on fetal echocardiography, but the rate of missed diagnosis and misdiagnosis is still very high, and the prognosis has not been evaluated. The aim of this study was to investigate the accuracy of prenatal diagnosis and to evaluate the prognosis semi-quantitatively according to the shape of the ring and the distance between the vessel and the trachea. METHODS: From 2019 to 2021, 37,875 fetuses underwent prenatal ultrasound examination in our center. All fetal cardiac examinations were performed using the fetal echocardiography method proposed by the American Institute of Ultrasound in Medicine (AIUM) combined with dynamic sequential cross-sectional observation (SCS). For SCS, the standard abdominal section was taken as the initial section, and the probe was moved cephalically along the long axis of the body until the superior mediastinum had disappeared. If a vascular ring was found, the shape of the ring and the distance of the branch to the airway were observed. The distance relationship with the airway was divided into three grades: I-III; the closer the distance, the lower the grade. The vascular rings were monitored every 4 weeks before birth. All were monitored before surgery or 1 year after birth. RESULTS: A total of 418 cases of vascular rings were detected. There was no missed diagnoses or misdiagnoses by SCS. The vessels formed different shaped rings according to their origin and route. Grade I, "" and "O" rings have a poor prognosis and are associated with the highest risk of respiratory symptoms. CONCLUSIONS: SCS can accurately diagnose vascular rings before delivery, evaluate the shape and size of the rings to conduct prenatal monitoring of children until birth, which plays a guiding role in airway compression after birth.
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Anel Vascular , Feminino , Humanos , Gravidez , Estudos Transversais , Diagnóstico Pré-Natal/métodos , Prognóstico , Ultrassonografia Pré-Natal/métodosRESUMO
OBJECTIVES: This study constructed a nomogram based on grayscale ultrasound features and real-time shear wave elastography (SWE) parameters to predict thyroid cancer. METHODS: Clinical data of 217 thyroid nodules of 201 patients who underwent grayscale ultrasound, real-time SWE, and thyroid function laboratory examination in Ma'anshan People's Hospital from January 2019 to December 2020 were retrospectively analyzed. The subjects were divided into a benign nodule group (106 nodules) and a malignant nodule group (111 nodules). The differences in grayscale ultrasound features, quantitative parameters of real-time SWE, and laboratory results of thyroid function between benign and malignant thyroid nodules were analyzed. We used a chi-square test for categorical variables and a t-test for continuous variables. Then, the independent risk factors for thyroid cancer were analyzed using multivariate logistic regression. Based on the independent risk factors, a nomogram for predicting thyroid cancer risk was constructed using the RMS package of the R software. RESULTS: Multivariate logistic regression showed that the grayscale ultrasound features of thyroid nodules were the shape, margin, echogenicity, and echogenic foci of the nodules,the maximum Young's modulus (SWE-max) of thyroid nodules, and the ratio of thyroid nodule and peripheral gland (SWE-ratio) measured by real-time SWE were independent risk factors for thyroid cancer (all p < 0.05), and the other variables had no statistical difference (p > 0.05). Based on the shape (OR = 5.160, 95% CI: 2.252-11.825), the margin (OR = 9.647, 95% CI: 2.048-45.443), the echogenicity (OR = 6.512, 95% CI: 1.729-24.524), the echogenic foci (OR = 2.049, 95% CI: 1.118-3.756), and the maximum Young's modulus (SWE-max) (OR = 1.296, 95% CI: 1.140-1.473), the SWE-ratio (OR = 2.001, 95% CI: 1.403-2.854) of the thyroid nodule to peripheral gland was used to establish the related nomogram prediction model. The bootstrap self-sampling method was used to verify the model. The consistency index (C-index) was 0.979, ROC curve was used to analyze the nomogram scores of all patients, and the AUC of nomogram prediction of thyroid cancer was 0.976, indicating that the nomogram model had high accuracy in the risk prediction of thyroid cancer. CONCLUSIONS: The nomogram model of grayscale ultrasound features combined with SWE parameters can accurately predict thyroid cancer.
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Técnicas de Imagem por Elasticidade , Neoplasias da Glândula Tireoide , Nódulo da Glândula Tireoide , Humanos , Nódulo da Glândula Tireoide/diagnóstico por imagem , Nomogramas , Estudos Retrospectivos , Ultrassonografia , Neoplasias da Glândula Tireoide/diagnóstico por imagemRESUMO
OBJECTIVE: We herein compared the diagnostic accuracy of the BI-RADS, ABVS, SWE, and combined techniques for the classification of breast lesions. METHODS: Breast lesions were appraised using the BI-RADS classification system as well as the combinations of BI-RADS plus ABVS (BI-RADS + ABVS) and BI-RADS plus SWE (BI-RADS + SWE), and both methods (BI-RADS + ABVS + SWE) by two specialties Medical Ultrasound physician. The Fisher's exact and χ2 tests were performed to compare the degree of malignancy for the various methods with a pathology ground truth. Receiver operating characteristic curves (ROC) were generated and the corresponding area under the curve (AUC) values were determined to test the diagnostic efficacy of the various methods and identify the optimal SWE cut-off indicative of malignancy. RESULTS: The incidence of the retraction phenomenon on ABVS images of the malignant group was significantly higher (P < .001) than that of the benign group. The specificity, sensitivity, and positive and negative predictive values of the BI-RADS classification were 88.72, 79.38, 83.70, and 85.50%, respectively. BI-RADS plus SWE-Max exhibited enhanced specificity, sensitivity, and positive and negative predictive values of 88.72, 92.78, 85.70, and 94.40%, respectively. Similarly, when BI-RADS + ABVS was utilized, the sensitivity and negative predictive value increased to 95.88 and 96.40%, respectively. BI-RADS + ABVS + SWE possessed the highest overall sensitivity (96.91%), specificity (94.74%), and positive (93.10%) and negative (97.70%) predictive values from all four indices. CONCLUSION: ABVS and SWE can reduce the subjectivity of BI-RADS. As a result, BI-RADS + ABVS + SWE resulted in the best diagnostic accuracy.
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Neoplasias da Mama , Técnicas de Imagem por Elasticidade , Feminino , Humanos , Ultrassonografia Mamária/métodos , Técnicas de Imagem por Elasticidade/métodos , Sensibilidade e Especificidade , Mama/diagnóstico por imagem , Mama/patologia , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/patologiaRESUMO
OBJECTIVES: To introduce an ultrasound training program for fetal palate screening by using a sequential sector scan through the oral fissure to train less experienced doctors and to investigate its effectiveness. METHODS: Twenty doctors and several women at approximately 20-28 weeks of gestation with singleton pregnancies who provided informed consent were enrolled. The training program consisted of theory and practice training, several tests, and two surveys. Trainees were tested before training and immediately after training; for the latter, each item with a score that was less than 60% of the full score was again used for training with a reconstructed plan. Finally, a post-training test was completed. RESULTS: The median theory scores, median practice scores, median language competence scores, and median self-assessment scores all increased significantly from the pre-training to post-training tests (P < .01). The median completion time for fetal palate scans decreased significantly from the pre-training to post-training tests (P < .01). The median questionnaire scores were 5.00 for pragmatism, 4.00 for content, 4.00 for scientific nature, and 5.00 for effectiveness. CONCLUSIONS: The training program for fetal palate screening can effectively standardize and improve doctors' scans for fetal palates. In addition, the program feasibly allows for the incorporation of the scan sequence into fetal palate screening.
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Fissura Palatina , Ultrassonografia Pré-Natal , Gravidez , Humanos , Feminino , Diagnóstico Pré-Natal , Ultrassonografia , Fissura Palatina/diagnóstico por imagemRESUMO
BACKGROUND: The purpose of this study was to investigate the preoperative prediction of large-number central lymph node metastasis (CLNM) in single thyroid papillary carcinoma (PTC) with negative clinical lymph nodes. METHODS: A total of 634 patients with clinically lymph node-negative single PTC who underwent thyroidectomy and central lymph node dissection at the First Affiliated Hospital of Anhui Medical University and the Nanchong Central Hospital between September 2018 and September 2021 were analyzed retrospectively. According to the CLNM status, the patients were divided into two groups: small-number (≤5 metastatic lymph nodes) and large-number (>5 metastatic lymph nodes). Univariate and multivariate analyses were used to determine the independent predictors of large-number CLNM. Simultaneously, a nomogram based on risk factors was established to predict large-number CLNM. RESULTS: The incidence of large-number CLNM was 7.7%. Univariate and multivariate analyses showed that age, tumor size, and calcification were independent risk factors for predicting large-number CLNM. The combination of the three independent predictors achieved an AUC of 0.806. Based on the identified risk factors that can predict large-number CLNM, a nomogram was developed. The analysis of the calibration map showed that the nomogram had good performance and clinical application. CONCLUSION: In patients with single PTC with negative clinical lymph nodes large-number CLNM is related to age, size, and calcification in patients with a single PTC with negative clinical lymph nodes. Surgeons and radiologists should pay more attention to patients with these risk factors. A nomogram can help guide the surgical decision for PTC.
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Carcinoma Papilar , Neoplasias da Glândula Tireoide , Humanos , Câncer Papilífero da Tireoide , Neoplasias da Glândula Tireoide/diagnóstico por imagem , Neoplasias da Glândula Tireoide/cirurgia , Neoplasias da Glândula Tireoide/patologia , Estudos Retrospectivos , Metástase Linfática/diagnóstico por imagem , Metástase Linfática/patologia , Ultrassom , Carcinoma Papilar/diagnóstico por imagem , Carcinoma Papilar/cirurgia , Carcinoma Papilar/patologia , Linfonodos/diagnóstico por imagem , Linfonodos/patologia , Linfonodos/cirurgia , Fatores de RiscoRESUMO
This study aimed to develop and validate a combined nomogram model based on superb microvascular imaging (SMI)-based deep learning (DL), radiomics characteristics, and clinical factors for noninvasive differentiation between immunoglobulin A nephropathy (IgAN) and non-IgAN.We prospectively enrolled patients with chronic kidney disease who underwent renal biopsy from May 2022 to December 2022 and performed an ultrasound and SMI the day before renal biopsy. The selected patients were randomly divided into training and testing cohorts in a 7:3 ratio. We extracted DL and radiometric features from the two-dimensional ultrasound and SMI images. A combined nomograph model was developed by combining the predictive probability of DL with clinical factors using multivariate logistic regression analysis. The proposed model's utility was evaluated using receiver operating characteristics, calibration, and decision curve analysis. In this study, 120 patients with primary glomerular disease were included, including 84 in the training and 36 in the test cohorts. In the testing cohort, the ROC of the radiomics model was 0.816 (95% CI:0.663-0.968), and the ROC of the DL model was 0.844 (95% CI:0.717-0.971). The nomogram model combined with independent clinical risk factors (IgA and hematuria) showed strong discrimination, with an ROC of 0.884 (95% CI:0.773-0.996) in the testing cohort. Decision curve analysis verified the clinical practicability of the combined nomogram. The combined nomogram model based on SMI can accurately and noninvasively distinguish IgAN from non-IgAN and help physicians make clearer patient treatment plans.
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Aprendizado Profundo , Glomerulonefrite por IGA , Microvasos , Nomogramas , Humanos , Glomerulonefrite por IGA/complicações , Glomerulonefrite por IGA/diagnóstico por imagem , Hematúria , Glomérulos Renais , Estudos Retrospectivos , Microvasos/diagnóstico por imagem , Insuficiência Renal Crônica/diagnóstico por imagem , Insuficiência Renal Crônica/etiologia , Insuficiência Renal Crônica/patologia , BiópsiaRESUMO
PURPOSE: To explore the optimal peri-tumoral regions on ultrasound (US) images and investigate the performance of multimodal radiomics for predicting axillary lymph node metastasis (ALNM). METHODS: This retrospective study included 326 patients (training cohort: n = 162, internal validation cohort: n = 74, external validation cohort: n = 90). Intra-tumoral region of interests (ROIs) were delineated on US and digital mammography (DM) images. Peri-tumoral ROI (PTR) on US images were gained by dilating actual 0.5, 1.0, 1.5, 2.0, 2.5, 3.0 and 3.5 mm radius surrounding the tumor. Support vector machine (SVM) method was used to calculate the importance of radiomics features and to pick the 10 most important. Recursive feature elimination-SVM was used to evaluate the efficacy of models with different feature numbers used. RESULTS: The PTR0.5mm yielded a maximum AUC of 0.802 (95% confidence interval (CI): 0.676-0.901) within the validation cohort using SVM classifier. The multimodal radiomics (intra-tumoral US and DM and US-based PTR0.5mm radiomics model) achieved the highest predictive ability (AUC = 0.888/0.844/0.835 and 95% CI = 0.829-0.936/0.741-0.929/0.752-0.896 for training/internal validation/external validation cohort, respectively). CONCLUSION: The PTR0.5mm could be the optimal area for predicting ALNM. A favorable predictive accuracy for predicting ALNM was achieved using multimodal radiomics and its based nomogram.
Assuntos
Neoplasias da Mama , Linfoma , Humanos , Feminino , Nomogramas , Metástase Linfática/diagnóstico por imagem , Metástase Linfática/patologia , Estudos Retrospectivos , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/patologia , Mama , Linfoma/patologia , Linfonodos/diagnóstico por imagem , Linfonodos/patologiaRESUMO
PURPOSE: To construct a nomogram based on sonogram features and radiomics features to differentiate granulomatous lobular mastitis (GLM) from invasive breast cancer (IBC). MATERIALS AND METHODS: A retrospective collection of 213 GLMs and 472 IBCs from three centers was divided into a training set, an internal validation set, and an external validation set. A radiomics model was built based on radiomics features, and the RAD score of the lesion was calculated. The sonogram radiomics model was constructed using ultrasound features and RAD scores. Finally, the diagnostic efficacy of the three sonographers with different levels of experience before and after combining the RAD score was assessed in the external validation set. RESULTS: The RAD score, lesion diameter, orientation, echogenicity, and tubular extension showed significant differences in GLM and IBC (p < 0.05). The sonogram radiomics model based on these factors achieved optimal performance, and its area under the curve (AUC) was 0.907, 0.872, and 0.888 in the training, internal, and external validation sets, respectively. The AUCs before and after combining the RAD scores were 0.714, 0.750, and 0.830 and 0.834, 0.853, and 0.878, respectively, for sonographers with different levels of experience. The diagnostic efficacy was comparable for all sonographers when combined with the RAD score (p > 0.05). CONCLUSION: Radiomics features effectively enhance the ability of sonographers to discriminate between GLM and IBC and reduce interobserver variation. The nomogram combining ultrasound features and radiomics features show promising diagnostic efficacy and can be used to identify GLM and IBC in a noninvasive approach.
Assuntos
Neoplasias da Mama , Mastite , Feminino , Humanos , Neoplasias da Mama/diagnóstico por imagem , Estudos Retrospectivos , Área Sob a Curva , UltrassonografiaRESUMO
OBJECTIVE: This paper aims to investigate clinical value of intrahepatic and intra-stent hemodynamic changes after transjugular intrahepatic portosystemic shunt (TIPS), by using color Doppler ultrasound during the diagnosis of hepatic encephalopathy (HE) in the patients with hepatitis B cirrhosis. METHODS: A retrospective analysis of the patients with hepatitis B cirrhotic portal hypertension, who underwent TIPS in The First Affiliated Hospital of Anhui Medical University from January 2018 to January 2021, was conducted. 22 patients who developed HE within 3 months after TIPS comprised the observation group (HE group), and 51 patients who did not develop HE were randomly selected as the control group (non-HE group). The porto systemic gradient (PSG), as well as intrahepatic and intra-stent hemodynamic changes of patients in both the HE group and the non-HE group after TIPS were investigated. RESULTS: The intra-stent blood flow, PSG difference, and PSG decrease percentage in the HE group were higher than those in the non-HE group, and the intra-stent flow had a weak positive correlation with PSG difference and with the PSG decrease percentage (r = 0.420, 0.258, respectively). The areas under the ROC curves of HE based on the PSG difference, the PSG decrease percentage, and the intra-stent flow were 0.762, 0.753, and 0.693, respectively. CONCLUSION: The more obvious decrease in PSG, the larger the intra-stent blood flow, and the larger the possibility of HE occurrence were observed. Routine ultrasound measurement of hemodynamic changes has certain clinical significance for predicting HE occurrence.
RESUMO
BACKGROUND: Ectodermal Dysplasia is a diverse group of inherited disorders characterized by a congenital defect in two or more ectodermal structures. Due to a fairly low incidence, to the best of our knowledge there are few clues that can assist in making an effective prenatal ultrasound diagnosis. Currently, the prenatal diagnosis of ectodermal dysplasia depends on a fetal genetic test combined with the family history. In this case report, we present a fetal case of ectodermal dysplasia with a remarkable prenatal ultrasound image, genetic testing, family history, and relevant exams of the stillbirth. CASE PRESENTATION: A multipara with a 22-week singleton male pregnancy undergoing a fetal ultrasound examination. The image showed a hypoplastic maxilla and mandible. Subsequently, the ectodermal dysplasia was defined using a family history and genetic testing. The skin pathology from the aborted fetus demonstrated a hypohidrotic type. The computed tomography (CT) reconstruction after induced labor confirmed the prenatal ultrasound findings of the maxilla and mandible. CONCLUSIONS: This case suggested that prenatal ultrasound may provide a valuable clue of ectodermal dysplasia. The diagnosis can be established using further prenatal genetic testing and a family history.