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Resumen La mamografía contrastada (CEDM, contrast-enhanced digital mammography) es una herramienta nueva que ha ido implementándose de forma creciente. Aparece como alternativa a la resonancia magnética (RM), y al igual que esta, tiene como principio el uso de contraste endovenoso para explorar la angiogénesis tumoral. Combina la imagen de mamografía convencional (Mx) con la técnica de sustracción con energía dual poscontraste, lo que resulta en un incremento en la detección de cáncer de mama, en un tiempo corto de estudio y a un bajo costo. Es un método prometedor en casos seleccionados y de fácil lectura, siendo útil principalmente en pacientes con diagnóstico de cáncer de mama para detectar lesiones adicionales y determinar el tamaño tumoral, ayudando en la planificación quirúrgica, así como también en la evaluación de la respuesta a la neoadyuvancia. También en el seguimiento de pacientes operadas, para caracterizar lesiones dudosas en Mx y ecografía, o como alternativa ante contraindicación de la RM. El objetivo de este trabajo es valorar la utilidad de la mamografía contrastada en la práctica diaria y determinar sus principales indicaciones. Repasamos con casos propios las utilidades y características del método.
Abstract Contrast-enhanced digital mammography (CEDM) is an emerging tool that has been increasingly implemented. It appears as an alternative to magnetic resonance imaging (MRI), using intravenous contrast to explore tumor angiogenesis. It combines conventional mammography (Mx) with post-contrast dual energy subtraction technique, resulting in increased detection of breast cancer, in a short study time and at a low cost. It is a promising method in selected cases and easy to read, being useful mainly in patients with breast cancer to detect additional lesions and determine the tumor size, that helps surgical planning, as well as in the evaluation of post-neoadjuvant chemotherapy response in the follow-up of patients treated with surgery, to address inconclusive findings in screening mammogram, or as an alternative when MRI is contraindicated. The purpose of this article is to assess the usefulness of contrasted mammography in daily practice and to determine its main indications. We review with our own cases the applications and characteristics of this method.
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Intraoperative ultrasound assisted localization is routinely used in the surgical treatment of completely endogenous renal cell tumor, however the localization and guidance ability of conventional ultrasound will decline to a certain extent for isoechoic renal tumor. A 62 years old female patient with right renal tumor was reported. The tumor diameter was about 2.3 cm× 1.7 cm, equivalent to the isoechoic of kidney. Laparoscopic partial nephrectomy was performed under the real-time guidance of contrast-enhanced ultrasound. The tumor was found to be lack of blood supply during the operation, and the tumor contour was clearly developed by contrast agent.The operation was successfully completed, and the pathological diagnosis was polycystic renal tumor with low malignant potential.The incisional margin was negative.The patient recovered well after operation without complications.No recurrence or metastasis was found after 6 months of follow-up.The renal function was good.
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Objective:To synthesize non-contrast-enhanced CT images from enhanced CT images using deep learning method based on convolutional neural network, and to evaluate the similarity between synthesized non-contrast-enhanced CT images by deep learning(DL-SNCT) and plain CT images considered as gold standard subjectively and objectively, as well as to explore their potential clinical value.Methods:Thirty-four patients who underwent conventional plain scan and enhanced CT scan at the same time were enrolled. Using deep learning model, DL-SNCT images were generated from the enhanced CT images for each patient. With plain CT images as gold standard, the image quality of DL-SNCT images was evaluated subjectively. The evaluation indices included anatomical structure clarity, artifacts, noise level, image structure integrity and image deformation using a 4-point system). Paired t-test was used to compare the difference in CT values of different anatomical parts with different hemodynamics (aorta, kidney, liver parenchyma, gluteus maximus) and different liver diseases with distinct enhancement patterns (liver cancer, liver hemangioma, liver metastasis and liver cyst) between DL-SNCT images and plain CT images. Results:In subjective evaluation, the average scores of DL-SNCT images in artifact, noise, image structure integrity and image distortion were all 4 points, which were consistent with those of plain CT images ( P>0.05). However, the average score of anatomical clarity was slightly lower than that of plain CT images (3.59±0.70 vs. 4) with significant difference ( Z = -2.89, P<0.05). For different anatomical parts, the CT values of aorta and kidney in DL-SNCT images were significantly higher than those in plain CT images ( t=-12.89, -9.58, P<0.05). There was no statistical difference in the CT values of liver parenchyma and gluteus maximus between DL-SNCT images and plain CT images ( P>0.05). For liver lesions with different enhancement patterns, the CT values of liver cancer, liver hemangioma and liver metastasis in DL-SNCT images were significantly higher than those in plain CT images( t=-10.84, -3.42, -3.98, P<0.05). There was no statistical difference in the CT values of liver cysts between DL-SNCT iamges and plain CT images ( P>0.05). Conclusions:The DL-SNCT image quality as well as the CT values of some anatomical structures with simple enhancement patterns is comparable to those of plain CT images considered as gold-standard. For those anatomical structures with variable enhancement and those liver lesions with complex enhancement patterns, there is still vast space for DL-SNCT images to be improved before it can be readily used in clinical practice.
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Objective:To explore the value of multiparametric ultrasonography consisting of gray-scale ultrasound(US), color Doppler flow imaging (CDFI), real-time strain elastography(RTE), and contrast-enhanced ultrasound(CEUS) in the differential diagnosis of testicular lesions.Methods:Forty patients (40 lesions) detected by ultrasonography examination at the Ultrasound Medical Center of Lanzhou University Second Hospital from June 2020 to June 2022 were retrospectively analyzed, and further the CDFI, CEUS and RTE were performed. The presence of vascularization in the lesion was determined by CDFI and CEUS, avascular lesions were defined as benign, vascularization lesions were defined as malignant. The lesion tissue elasticity was assessed by real-time strain elastography, tissue stiffness was encoded as red(soft), green(intermediate), and blue(hard), and the hard lesions were defined as malignant, soft lesions were defined as benign. All lesions were subjected to pathological histologic examination after surgical resection or puncture biopsy as a reference standard. The correct classification rate, sensitivity, specificity and likelihood ratio of the multiparametric ultrasonography imaging for the diagnosis of benign and malignant testicular lesions were analyzed by ROC.Results:Of 40 testicular lesions, 24 (60.0%) were benign and 16 (40.0%) were malignant. The sensitivity of CDFI, CEUS and RTE in the diagnosis of testicular lesions was 0.875, 1.000 and 1.000, and the specificity was 0.833, 0.750 and 0.708, respectively. The correct classification rate was 85.0%, 85.0% and 82.5%, and the positive likelihood ratio was 5.24, 4.00 and 4.42, respectively. AUC was 0.781, 0.802, 0.771, respectively. By combining RTE and CDFI, a sensitivity of 1.000 and specificity of 0.875 and correct classification rate of 92.8% and positive likelihood ratio of 8.00 and AUC of 0.915 ( P<0.001) were achieved in differentiating testicular lesions. And combining RTE and CEUS, achieved sensitivity of 1.000 and specificity of 0.917 and correct classification rate of 95.0% and positive likelihood ratio of 12.0 and AUC of 0.958( P<0.001). Conclusions:Multiparametric US is of great value in the differential diagnosis of benign and malignant testicular lesions.
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Objective:To investigate the value of qualitative characteristics of contrast-enhanced ultrasound (CEUS) and VueBox quantitative parameters in the evaluation of pathological molecular typing of breast cancer.Methods:A retrospective analysis was performed on 133 patients with pathologically confirmed breast cancer who underwent CEUS examination in the People′s Hospital of Guangxi Zhuang Autonomous Region from January 2020 to July 2022. The patients were divided into Luminal A type, Luminal B type, human epidermal growth factor receptor-2(HER-2) type and triple negative type according to the results of immunohistochemistry. The differences of qualitative characteristics and quantitative parameters of CEUS in different molecular subtypes of breast cancer were analyzed. The ROC curve was used to evaluate the diagnostic efficacy of CEUS in the differentiation of molecular subtypes of breast cancer.Results:There were significant differences in enhancement intensity, post-enhancement boundary, filling defect and peripheral radial convergence among different molecular subtypes of breast cancer(all P<0.05), while there was no significant difference in enhancement uniformity ( P>0.05). Peak enhancement (PE), wash-in and wash-out areas under the curve (WiWoAUC), and wash-in ratio (WiR) of HER-2 type and triple-negative type breast cancer were higher than Luminal A type and Luminal B type (all P<0.05). ROC curve analysis showed that PE and radial convergence had reasonable diagnostic efficiency in Luminal A type, and the areas under the curve were 0.849 and 0.780, sensitivity was 0.711 and 0.889, specificity was 0.909 and 0.671, accuracy was 0.842 and 0.744, respectively. The areas under the curve of PE in diagnosing Luminal B type was 0.852, the sensitivity, specificity, and accuracy were 0.825, 0.763 and 0.782, respectively. The area under the curve of WiWoAUC and filling defect in diagnosing HER-2 type were 0.912 and 0.898, the sensitivity was 0.903 and 0.903, the specificity was 0.853 and 0.892, and the accuracy was 0.865 and 0.895, respectively. The area under the curve of clear boundary after enhancement in diagnosing triple negative type was 0.919, and the sensitivity, specificity and accuracy were 0.941, 0.897 and 0.902, respectively. Conclusions:There are differences in the qualitative characteristics and quantitative parameters of contrast-enhanced ultrasound in different molecular types of breast cancer. CEUS is suggested as a noninvasive modality for preoperative prediction of molecular subtypes of breast cancer.
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Objective:To assess the value of S-Detect and contrast-enhanced ultrasound (CEUS) in the differential diagnosis of Breast Imaging Reporting and Data System(BI-RADS) 4 breast lesions.Methods:A total of 104 breast lesions in 100 patients diagnosed as BI-RADS category 4 by conventional ultrasound were prospectively enrolled, and all of them were received S-Detect and CEUS examination at the same time. Taking pathology as the gold standard, ROC curve was constructed to compare the diagnostic efficacy of conventional ultrasound, S-Detect, CEUS and their combination.Results:Among the 104 BI-RADS category 4 breast lesions, 63 were benign and 41 were malignant. The sensitivities of conventional ultrasound, S-Detect, CEUS and S-Detect combined with CEUS were 73.17%, 87.80%, 87.80%, 90.24%; the specificities were 57.14%, 60.32%, 68.25%, 77.78%; the positive predictive values were 52.63%, 59.02%, 64.29% and 72.55%; the negative predictive values were 76.60%, 88.37%, 89.59% and 92.45%; the accuracies were 63.46%, 71.15%, 75.96% and 82.69%; and the areas under the ROC curve (AUC) were 0.652, 0.741, 0.780 and 0.840. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of S-Detect and CEUS diagnosis were improved compared with conventional ultrasound. The AUC of combined diagnosis was higher than that of S-Detect, CEUS alone, and the differences were statistically significant(all P<0.05). The AUC of CEUS was higher than that of conventional ultrasound, and the difference was statistically significant ( P<0.05). There were no significant differences in AUC between any two of other groups (all P>0.05). Conclusions:The combined application of S-Detect and CEUS could achieve complementary advantages, which is of great significance for the differential diagnosis of benign and malignant in BI-RADS 4 breast lesions.
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Objective:To investigate the correlation of hepatocellular carcinoma (HCC) classified by contrast-enhanced ultrasound (CEUS) Liver Imaging Data and Report System (LI-RADS) with differentiation degree and Ki-67 index.Methods:A multicenter, retrospective study was conducted.The clinical and CEUS imaging data of 208 patients with 208 HCC lesions from December 2017 to December 2020 in China CEUS database were included and analyzed. According to the CEUS LI-RADS version 2017 proposed by the American College of Radiology, the HCC was classified. The diagnosis and pathological information of all lesions were confirmed by pathology. The differentiation degree of HCC and the distribution of Ki-67 index in different LI-RADS categories were evaluated, and their correlation was analyzed.Results:The degree of differentiation and Ki-67 index among HCC of different CEUS LI-RADS were statistically significant ( P<0.001, P=0.009). LI-RADS M HCC was more likely to be poorly differentiated and showed a higher Ki-67 index. The category of LI-RADS was positively correlated with the degree of tumor differentiation (tau-b=-0.250, P<0.001) and the Ki-67 index (tau-b=0.178, P=0.002), that is, the higher the category of LI-RADS, the lower differentiation degree and the higher the Ki-67. Conclusions:The CEUS LI-RADS classification of HCC is correlating with the degree of differentiation and Ki-67 index.
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Objective:To evaluate the value of Sonazoid contrast enhanced ultrasound (CEUS) in preoperative prediction of proliferating cell nuclear antigen 67 (Ki-67) level of hepatocellular carcinoma (HCC) by establishing predictive model based on radiomics features of Kupffer phase.Methods:From October 2020 to August 2021, patients with histologically confirmed HCC lesion and who underwent Sonazoid CEUS examination 1 week before surgery were prospectively enrolled. The radiomics signatures were extracted from the whole tumor region on gray scale images and Kupffer phase images. Two predictive radiomics models were constructed using radiomic method. The predictive performance of 2 models was compared.Results:A total of 50 patients with histologically confirmed single HCC lesions were prospectively enrolled in this study. Among them, histological results revealed 24 HCC lesions with high level representation of Ki-67 (>20%) and 26 HCC lesions with low level representation of Ki-67 (≤20%). Two radiomics predictive models were established based on gray scale images and Kupffer phase images respectively. While compared with model based on B-mode ultrasound images, model based on Kupffer phase images showed significantly higher area under receiver operating characteristic curve (0.753 vs 0.535, P=0.017), accuracy (0.720 vs 0.580, P=0.023) and sensitivity (0.458 vs 0.250, P=0.043). Calibration plot indicated that Kupffer phase model showed better consistency with the actual Ki-67 level than gray scale model. Conclusions:The radiomics model based on Kupffer phase features of Sonazoid CEUS is a preoperative and noninvasive prediction the presentation level of Ki-67 in HCC lesions.
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Objective:To construct a nomogram for predicting the occurrence of renal allograft rejection based on the combination of multimodal ultrasound features and clinical data.Methods:The ultrasound findings and clinical characteristics of 102 patients with transplanted kidneys who underwent renal biopsy in the General Hospital of Eastern Theater Command from January 2021 to March 2022 were analyzed retrospectively. Patients were divided into rejection group and nephropathy group according to Banff transplant kidney pathological diagnostic criteria (2017 edition). Multivariate Logistic regression was used to screen independent predictors related to the status of rejection, and nomograms were drawn based on the independent predictors. The internal validation of the nomogram was carried out by Bootstrap method, and the ROC curve and calibration curve were utilized to evaluate the diagnostic efficacy of the nomogram.Results:Blood urea nitrogen concentration, renal aortic resistance index, absolute time to peak and cortical echo were independent predictors of rejection( OR=1.073, 1.078, 0.843, 0.205; all P<0.05). Incorporating blood urea nitrogen concentration, renal aortic resistance index, absolute peak time and cortical echo, the nomogram was constructed. The AUC of the predictive model was 0.814(95% CI=0.722-0.905) and the cutoff value was 0.67(corresponding to a total score of about 157 points). Both internal verification (AUC=0.788) and calibration curve demonstrated the clinical usefulness of the nomogram. Conclusions:The nomogram for predicting the occurrence of rejection in renal allograft patients based on multimodal ultrasound features and clinical data can guide the individualized treatment of patients with renal dysfunction.
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Objective:To evaluate the effectiveness of contrast-enhanced ultrasound in the differential diagnosis of atypical adenomyosis and fibroids using a decision tree model.Methods:The data of cases with difficulty in differentiating atypical adenomyosis from fibroids on conventional ultrasound examination at Shengjing Hospital of China Medical University from April 2021 to April 2022 were selected and analyzed. Ninety-five patients with contrast-enhanced ultrasound examination were finally selected, including 64 patients in the pathologically confirmed adenomyosis group and 31 patients in the fibroids group. The data from the qualitative analysis and the quantitative analysis of the time-intensity curve (TIC) curve were collected separately, including the temporal variability of contrast entry into the lesion, i.e.the difference between the time when the contrast agent started to enter the lesion and the time when the contrast agent finally filled the lesion completely. Indicators were first screened for inclusion in the decision tree model by univariate and multifactorial analyses, and decision tree models based on qualitative analysis indicators, and qualitative and TIC-based analyses were developed to further assess the diagnostic efficacy of both models.Results:Through the univariate analysis, it showed that the qualitative analysis indicators of lesion onset enhancement pattern, enhancement intensity, intra-lesion contrast distribution, and post-contrast lesion border were of statistical significance (all P<0.05) between the two groups. The differences in contrast arrive time (AT), contrast time to peak (TTP), |ΔAT|, and |ΔTTP| in the TIC curve analysis indexes were statistically significant between the two groups (all P<0.05). The difference in lesion temporal phase variability was statistically significant between the two groups ( P<0.05). After further screening by multifactorial analysis, the accuracy and misdiagnosis rates were 87.40% and (17.90±3.90)% in the qualitative analysis-based decision tree model respectively, and 90.50% and (21.10±4.20) % in the qualitative and TIC curve-based analysis decision tree model respectively. The ROC curves were plotted according to the two groups of models, and the areas under the curves were 0.915 and 0.931 respectively. Conclusions:A decision tree model based on ultrasonographic image analysis has diagnostic value for the differential diagnosis of atypical adenomyosis and uterine fibroids.
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Objective:To predict the Ki-67 expression grading in patients with mass breast cancer based on multimodal ultrasound features to aid clinical diagnosis and treatment.Methods:Ninety-three female patients (93 masses in total) with breast cancers confirmed by pathological examination were retrospectively included in the Second Affiliated Hospital of Harbin Medical University from September 2017 to September 2020. According to the immunohistochemical results, the patients were divided into Ki-67 high expression group (55 cases) and Ki-67 low expression group (38 cases). The qualitative and quantitative features from two-dimensional gray-scale ultrasound, color Doppler flow imaging (CDFI), shear wave elastography (SWE) and contrast-enhanced ultrasound (CEUS) images of all breast masses were retrospectively analyzed, differential features were analyzed based on logistic regression algorithm. ROC curves and Kappa test were used for the evaluation of diagnosis.Results:The univariate analysis revealed statistically significant differences between the two groups for conventional ultrasound features (size, shape, margins), SWE features (stiff rim sign, Eratio), and CEUS features (perfusion defect, IMAX) (all P<0.05). In the multiple logistic regression analysis, the margins, stiff rim sign, and perfusion defect were the independent factors for predicting the Ki-67 expression (all P<0.05). The performance of the predictive model was 0.882 (95%confidence interval of 0.798-0.940, P<0.05) with the sensitivity of 0.818 and specificity of 0.790. Conclusions:A preliminary analysis of the relationship between multi-modal ultrasound features and Ki-67 expression grading in mass breast cancers was performed based on logistic regression algorithm to provide more imaging information for clinical treatment and prognosis assessment.
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Objective:To establish a machine learning model for the diagnosis of clinically significant prostate cancer based on transrectal contrast-enhanced ultrasound parameters and clinically relevant data.Methods:A retrospective analysis was performed on 151 patients in Chongqing University Cancer Hospital who underwent transrectal contrast-enhanced ultrasonography and transrectal ultrasound-guided needle biopsy from November 2018 to September 2021. The time intensity curve was drawn using VueBox software and 12 parameters such as rise time, peak time, average transit time, peak intensity, and rising slope were quantitatively analyzed. Age, total prostate-specific antigen, free prostate-specific antigen, free prostate-specific antigen ratio, volume, prostate-specific antigen density, and transrectal contrast-enhanced ultrasonography parameters, a total of 18 characteristic parameters, were analyzed and screened through relevant attribute values and information gain attribute values. The screening features were trained and tested by the machine learning single algorithm and integrated algorithm, and then the model was evaluated by the F1 value and the area under the ROC curve(AUC).Results:Using the related attribute value and the information gain attribute value, 12 variables and 5 variables were screened out respectively to establish a machine learning model. The model established by the ensemble algorithm was better than the single algorithm. For the two variable selection methods, the AUC (0.810 vs 0.789) and F1 values (0.748 vs 0.742) of the Bagging ensemble algorithm model, which basic algorithm was decision tree, were the highest, followed by Logistic regression and support vector machine(SVM) in order of AUC and F1 values.Conclusions:Based on transrectal contrast-enhanced ultrasound parameters and clinical data, the Bagging ensemble model based on decision tree has the best performance in diagnosing clinically significant prostate cancer.
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Objective:To explore the risk factors of microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and to predict MVI preoperatively, non-invasively and accurately.Methods:A total of 150 HCC patients (183 HCC lesions) were retrospectively collected in the First Affiliated Hospital of Xi′an Jiaotong University from January 2016 to June 2022.The clinical data and hematological data, gray-scale ultrasonography (US), contrast-enhanced ultrasonography (CEUS), enhanced magnetic resonance imaging with gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (EOB-MRI) and pathological data of these patients were recorded. According to the pathological diagnosis of MVI, the lesions were divided into MVI (+ ) group and MVI (-) group. The indicators between the two groups were compared. All 183 lesions were put into the training set, and the prediction model with nomogram was constructed according to the risk factors of MVI selected by multivariate Logistic regression. The internal verification was carried out by ten-fold cross-validation method.Results:There were significant statistical differences in the following parameters between MVI (+ ) group ( n=109) and MVI (-) group ( n=74) (all P<0.05). These were cirrhosis, serological parameters (alpha-fetoprotein, albumin, total bilirubin), qualitative indexes of US (size, boundary, internal echo), qualitative indexes of CEUS (hyper/iso/hypovascularity of lesions in arterial phase, portal phase, and delayed phase compared with hepatic parenchyma), and quantitative indexes of EOB-MRI [post enhancement rate (post ratio) and gadolinium disodium rate (EOB ratio)] calculated mainly in terms of lesions and surrounding liver parenchyma in hepatobiliary phase and unenhanced T1 images). Finally, cirrhosis of patients, the size, boundary, internal echo of lesions in US; arterial phase (AP), portal phase (PP), post-vascular phase (PVP) features in CEUS; the EOB rate and post rate of EOB-MRI entered the prediction model of MVI. The training set exhibited good calibration and net gain rate. The areas under the ROC curve for the training set and the validation set were 0.981 and 0.961, respectively, while the diagnostic accuracy were 92.9% and 85.8%, respectively. Conclusions:The model constructed mainly by multimodality imaging methods can achieve favorable predictive performance for MVI, which provides valuable ideas for noninvasively predicting the incidence of MVI and optimizing the MVI-related treatment of MVI in HCC patients.
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With the progression of primary and secondary brain injury, as well as the increase of the intracranial pressure, severe traumatic brain injury (sTBI) patients, if not timely and effective treated, will lead to brain hernia or even central failure. Therefore, sTBI patients often require emergency surgical intervention, including large craniotomy or even decompression. However, postural changes, brain tissue pulling and loss of cerebrospinal fluid can cause "brain drift" in sTBI patients. Meanwhile, improper rapid decompression will result in brain tissue displacement or delayed hematoma, which makes the intracranial condition deviated from the preoperative image data, even leads to deterioration. The application of multimodal intraoperative ultrasound can simply, intuitively visualize the intracranial lesion, blood flow and microperfusion in a real-time manner, guiding the surgeon to preserve the normal brain tissue to the maximum extent and improving the prognosis of the patients with the appropriate operation plan. Over the last few decades, the application of multimodal ultrasound in large craniotomy in patients with sTBI was mainly to identify intracranial lesions while there were few studies on the evaluation of cerebral hemodynamic heterogeneity of sTBI. To this end, the authors reviewed the imaging characteristics of various examination techniques of multimodal ultrasound and the progress of its application in sTBI surgery, hoping to provide evidences for accurate intraoperative evaluation and adjustment of treatment plan.
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Prostate cancer is the most common malignant tumor in the male urogenital system. Transrectal ultrasound has become a commonly used method for the diagnosis and biopsy of prostate cancer due to its simplicity, economy, and non radiation. This article will discuss the current application status and progress of traditional transrectal ultrasound, color doppler ultrasound, ultrasound imaging, elastic ultrasound, micro ultrasound, tissue scanning, and multimodal ultrasound in the diagnosis of prostate cancer.
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Breast cancer is a highly heterogeneous tumor originating from genetic basis, with significant differences in morphology, immunophenotype and therapeutic response, which poses great challenges to the treatment of breast cancer patients. Therefore, it is very important to understand the diversity of different molecular biological states and expressions in tumor cells to obtain good therapeutic effects for breast cancer. Contrast-enhanced ultrasound (CEUS) is widely used as a non-invasive real-time diagnostic technique for breast tumors. At present, many domestic and foreign literatures have reported that there is a certain correlation between molecular biological indicators related to breast cancer and the characteristics of CEUS, which is expected to provide a reference for preoperative treatment through non-invasive and convenient ultrasound examination. The combination of ultrasound contrast agent and ultrasound can mediate the drug therapy of breast cancer, which makes the targeted delivery and targeted regulation of drugs possible, thus improving the efficiency of chemotherapy drugs. In this review, we reviewed the relationship between molecular markers related to breast cancer and CEUS and the application of ultrasound contrast agents in targeted therapy of breast cancer.
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Objective:To investigate the clinical efficacy of qualitative and staging diagnosis of rectal tumors with dual contrast-enhanced ultrasonography and interventional biopsy.Methods:A total of 300 patients with rectal tumors who received treatment in The First People's Hospital of Huzhou from December 2019 to March 2022 were included in this study. All patients underwent dual contrast-enhanced ultrasonography and interventional biopsy followed by focus resection. Taking the postoperative histopathological test results as the gold standard, the efficacy of dual contrast-enhanced ultrasonography and interventional biopsy in the localization, qualitative analysis, and staging of rectal tumors was analyzed.Results:The compliance rate of dual contrast-enhanced ultrasonography and interventional biopsy in the localization of rectal tumors was 100%. The sensitivity, specificity, and accuracy of the dual contrast-enhanced ultrasonography and interventional biopsy for qualitative diagnosis of rectal tumors were 94.8%, 97.8%, and 96.7%, respectively. The Kappa value used for assessing agreement in the qualitative diagnosis of rectal tumors between dual contrast-enhanced ultrasonography and interventional biopsy and postoperative tissue pathological examination results was 0.947. The area under the curve plotted for qualitative diagnosis of rectal tumors was 0.974. The sensitivity, specificity, and sensitivity of dual contrast-enhanced ultrasonography and interventional biopsy for diagnosis of stage I-III rectal cancer were 94.1%-97.8%. The Kappa values used for assessing agreement in staging diagnosis of stage I-III rectal cancer between dual contrast-enhanced ultrasonography and interventional biopsy and postoperative tissue pathological examination results were 0.923, 0.912, and 0.927, respectively. The areas under the curve plotted for staging diagnosis of rectal cancer were 0.961, 0.955, and 0.970, respectively.Conclusion:Dual contrast-enhanced ultrasonography and interventional biopsy have a high efficacy in the localization, qualitative diagnosis, and staging diagnosis of rectal tumors.
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Objective:To study the diagnostic value of ultrasonic elastography (UE) CEUS in differentiated thyroid cancer (DTC) and its correlation with invasive gene and proliferative gene expression in DTC tissue.Methods:100 DTC patients who were treated in the Ultrasound Department of Zhuji People’s Hospital of Zhejiang Province from Jan. 2019 to Jan. 2022 were retrospectively selected and included in the TC group, and 100 thyroid adenoma patients who were treated during the same period were included in the thyroid adenoma group. UE and CEUS tests were performed on all patients, and the expression levels of proliferative and invasive genes in tumor tissues were measured. Time to peak (TTP) , average time of contrast medium passage (MTT) and peak intensity (PI) were recorded. DTC patients were divided into groups according to the blue area ratio, elastic ratio of lesions, optimal ROC truncation value of TTP, MTT and PI, that is, elastic value > 1.66, blue area ratio > 51.21%, PI≤17.11dB, MTT≤36.39s, TTP≤18.90s were group A, and vice president was Group B. SPSS 19.0 was used for data analysis, and P < 0.05 was considered to be statistically significant. Results:The blue area ratio and elastic ratio of lesions in TC group were higher than those in thyroid adenoma group ( P < 0.05) , while TTP, MTT and PI in TC group were lower than those in thyroid adenoma group ( P < 0.05) . There were statistically significant differences in blue area ratio, elastic ratio of lesions, TTP, MTT and PI among TC groups with different clinical stages, capsule invasion and lymph node metastasis ( P<0.05) . ROC curve was drawn. The AUC of DTC combined with blue area ratio, elastic ratio of lesions, TTP, MTT and PI was the highest, the specificity of combined detection was 86.37%, and the detection sensitivity was 80.16%. Compared with thyroid adenoma group, Xklp2 target protein (TPX2) , chemokine receptor 4, CXCR4) and polymetalloproteinase-9 (ADAM9) gene expression levels were higher, but TDCD4 gene expression levels were lower ( P<0.05) . The expression levels of TPX2, CXCR4 and ADAM9 genes in group A were higher than those in group B ( P<0.05) , and the programmed death factor 4 (PDCD4) gene in group A was lower than that in group B ( P<0.05) . According to Pearson linear analysis, the blue area ratio and elastic ratio of lesions were positively correlated with the expression levels of TPX2, ADAM9 and CXCR4 genes in DTC tissues, and inversely correlated with the expression levels of PDCD4 genes in DTC tissues ( P<0.05) . The expression levels of TPX2, ADAM9 and CXCR4 genes in TTP, MTT and PI were inversely proportional to the expression levels of PDCD4 genes in DTC patients ( P<0.05) . Conclusion:The combination of blue area ratio, elastic ratio of lesions, TTP, MTT and PI has good diagnostic value for DTC, and the blue area ratio, elastic ratio of lesions, TTP, MTT and PI are correlated with the expression levels of invasive genes and proliferating genes in tumor tissues.
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OBJECTIVES@#As the use of iodinated contrast media has become more widely with advances in imaging, several guidelines have suggested that anxiety increases the risk of acute adverse reactions associated with iodinated contrast media. This study aims to evaluate the impact of anxiety on the occurrence of acute adverse reactions (AAR) to iodinated contrast media in patients undergoing contrast-enhanced CT examinations.@*METHODS@#Inpatients who underwent contrast-enhanced CT examinations at the Third Xiangya Hospital between February and October 2021 were prospectively recruited. Prior to the imaging examinations, all patients completed the Generalized Anxiety Disorder Scale-7 (GAD-7) assessment before the imaging examinations to determine the severity of anxiety, which was categorized as mild, moderate, or severe. Based on the occurrence of AAR, patients were classified into an AAR group and a non-AAR group. The difference in anxiety was compared between the 2 groups. Multivariate logistic regression analysis was used to identify independent risk factors associated with AAR. To ensure comparability between the 2 groups, propensity score matching (PSM) was utilized to align the clinical characteristics. Subsequently, the difference in anxiety within the matched groups was analyzed.@*RESULTS@#The study comprised 880 patients, with 80 patients in the AAR group and 800 patients in the non-AAR group. There was a significant difference in proportion of patients with mild-severe anxiety between the 2 groups (75% in the AAR group and 36% in the non-AAR group, P<0.001). Additionally, differences were also observed in occupation, income, underlying diseases, and allergy history (all P<0.001). The results of multivariate logistic regression analysis revealed that patients' income, allergy history, and anxiety were independent risk factors for AAR to iodinated contrast media (all P<0.05). Following PSM, each matched group included 66 cases, and no significant differences in clinical characteristics were observed between the 2 groups (all P>0.05). However, the proportion of patients with mild-severe anxiety remained significantly higher in the AAR group compared to the non-AAR group (75% in the AAR group and 31% in the non-AAR group, P<0.001).@*CONCLUSIONS@#Anxiety is associated with an increased risk of AAR to iodinated contrast media in patients undergoing contrast-enhanced CT examinations, suggesting the clinical importance of screening for anxiety before imaging examinations.
Subject(s)
Humans , Contrast Media/adverse effects , Tomography, X-Ray Computed/methods , Risk Factors , Anxiety , Hypersensitivity/etiology , Retrospective StudiesABSTRACT
OBJECTIVE@#To evaluate the diagnostic value of dynamic contrast enhanced (DCE) of multiparametric magnetic resonance imaging (mpMRI) for prostate imaging reporting and data system (PI-RADS) 4 lesion in prostate peripheral zone.@*METHODS@#The clinical data of patients with PI-RADS 4 lesion in prostate peripheral zone who underwent prostate biopsy from January 2018 to September 2021 in Peking University First Hospital were retrospectively included. According to DCE status, the patients were divided into the conventional group (4 points for diffusion-weighted imaging) and the comprehensive group (3 points for diffusion-weighted imaging + 1 point for DCE positive). Pearson's chi-square test or Fisher's exact test for comparison was conducted between prostate cancer and non-cancer patients. Univariate and multivariate Logistic regression were performed to analyze the correlation of positive biopsy with age, total prostate specific antigen (PSA), free PSA/total PSA (f/tPSA), prostate volume (PV), PSA density (PSAD) and DCE status.@*RESULTS@#Among the 267 prostate biopsy patients, 217 cases were diagnosed as prostatic cancer (81.27%) and 50 cases were non-cancer (18.73%). Statistical analysis between the prostatic cancer group and the non-cancer group showed that there were significant differences in age, tPSA, PV and PSAD (all P < 0.05), but no significant differences in f/tPSA between the two groups. About different PI-RADS 4 lesion groups, the conventional group and the comprehensive group showed significant difference in biopsy results (P=0.001), and the conventional group had a higher positive rate. The PV of comprehensive group was larger than that of the conventional group. Among the prostate cancer patients diagnosed by biopsy, statistical analysis between the conventional group and comprehensive group showed that there were not significant differences in International Society of Urological Pathology (ISUP) grade and distinguishing clinically significant prostate cancer (all P > 0.05). Logistic univariate analysis showed that the diagnosis of prostate cancer was related to age, tPSA, f/tPSA, PV and DCE group status (all P < 0.05). Multivariate analysis showed that age, tPSA, PV and DCE group status (all P < 0.05) were independent risk factors for the diagnosis of prostatic cancer.@*CONCLUSION@#tPSA, f/tPSA, PV and PSAD are the indicators to improve the diagnosis of prostatic cancer with PI-RADS 4 lesion in peripheral zone lesions. DCE status is worth considering, so that we can select patients for biopsy more accurately, reduce the rate of missed diagnosis of prostate cancer as well as avoid unnecessary prostate puncture.