Dynamic Enhancement Magnetic Resonance Imaging Research Articles

Progressive Dual Priori Network for Generalized Breast Tumor Segmentation.

To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and irregular shape, we propose a progressive dual priori network (PDPNet) to segment breast tumors from dynamic enhanced magnetic resonance images (DCE-MRI) acquired at different centers. The PDPNet first cropped tumor regions with a coarse-segmentation based localization module, then the breast tumor mask was progressively refined by using the weak semantic priori and cross-scale correlation prior knowledge. To validate the effectiveness of PDPNet, we compared it with several state-of-the-art methods on multi-center datasets. The results showed that, comparing against the suboptimal method, the DSC and HD95 of PDPNet were improved at least by 5.13% and 7.58% respectively on multi-center test sets. In addition, through ablations, we demonstrated that the proposed localization module can decrease the influence of normal tissues and therefore improve the generalization ability of the model. The weak semantic priors allow focusing on tumor regions to avoid missing small tumors and low-contrast tumors. The cross-scale correlation priors are beneficial for promoting the shape-aware ability for irregular tumors. Thus integrating them in a unified framework improved the multi-center breast tumor segmentation performance.

Machine learning models for differential diagnosing HER2-low breast cancer: A radiomics approach.

To develop machine learning models based on preoperative dynamic enhanced magnetic resonance imaging (DCE-MRI) radiomics and to explore their potential prognostic value in the differential diagnosis of human epidermal growth factor receptor 2 (HER2)-low from HER2-positive breast cancer (BC). A total of 233 patients with pathologically confirmed invasive breast cancer admitted to our hospital between January 2018 and December 2022 were included in this retrospective analysis. Of these, 103 cases were diagnosed as HER2-positive and 130 cases were HER2 low-expression BC. The Synthetic Minority Oversampling Technique is employed to address the class imbalance problem. Patients were randomly split into a training set (163 cases) and a validation set (70 cases) in a 7:3 ratio. Radiomics features from DCE-MRI second-phase imaging were extracted. Z-score normalization was used to standardize the radiomics features, and Pearson's correlation coefficient and recursive feature elimination were used to explore the significant features. Prediction models were constructed using 6 machine learning algorithms: logistic regression, random forest, support vector machine, AdaBoost, decision tree, and auto-encoder. Receiver operating characteristic curves were constructed, and predictive models were evaluated according to the area under the curve (AUC), accuracy, sensitivity, and specificity. In the training set, the AUC, accuracy, sensitivity, and specificity of all models were 1.000. However, in the validation set, the auto-encoder model's AUC, accuracy, sensitivity, and specificity were 0.994, 0.976, 0.972, and 0.978, respectively. The remaining models' AUC, accuracy, sensitivity, and specificity were 1.000. The DeLong test showed no statistically significant differences between the machine learning models in the training and validation sets (Z = 0, P = 1). Our study investigated the feasibility of using DCE-MRI-based radiomics features to predict HER2-low BC. Certain radiomics features showed associations with HER2-low BC and may have predictive value. Machine learning prediction models developed using these radiomics features could be beneficial for distinguishing between HER2-low and HER2-positive BC. These noninvasive preoperative models have the potential to assist in clinical decision-making for HER2-low breast cancer, thereby advancing personalized clinical precision.

Comparative analysis of the performance of hepatobiliary agents in depicting MRI features of microvascular infiltration in hepatocellular carcinoma.

To compare the ability to depict MRI features of hepatobiliary agents in microvascular infiltration (MVI) of hepatocellular carcinoma (HCC) during different stages of dynamic enhancement MRI. A retrospective study included 111 HCC lesions scanned with either Gd-EOB-DTPA or Gd-BOPTA. All cases underwent multiphase dynamic contrast-enhanced scanning before surgery, including arterial phase (AP), portal venous phase (PVP), transitional phase (TP), delayed phase (DP), and hepatobiliary phase (HBP). Two abdominal radiologists independently evaluated MRI features of MVI in HCC, such as peritumoral hyperenhancement, incomplete capsule, non-smooth tumor margins, and peritumoral hypointensity. Finally, the results were reviewed by the third senior abdominal radiologist. Chi-square (χ2) Inspection for comparison between groups. P < 0.05 is considered statistically significant. Receiver operating characteristic (ROC) curve was used to evaluate correlation with pathology, and the area under the curve (AUC) and 95% confidence interval (95% CI) were calculated. Among the four MVI evaluation signs, Gd-BOPTA showed significant differences in displaying two signs in the HBP (P < 0.05:0.000, 0.000), while Gd-EOB-DTPA exhibited significant differences in displaying all four signs (P < 0.05:0.005, 0.006, 0.000, 0.002). The results of the evaluations of the two contrast agents in the DP phase with incomplete capsulation showed the highest correlation with pathology (AUC: 0.843, 0.761). By combining the four MRI features, Gd-BOPTA and Gd-EOB-DTPA have correlatedsignificantly with pathology, and Gd-BOPTA is better (AUC: 0.9312vs0.8712). The four features of hepatobiliary agent dynamic enhancement MRI demonstrate a good correlation with histopathological findings in the evaluation of MVI in HCC, and have certain clinical significance.

Correlations between dynamic-enhanced magnetic resonance imaging quantitative parameters and postoperative recurrence or metastasis and clinicopathological features in breast cancer patients-a retrospective cohort study.

BackgroundFew related studies focused on the correlations between the quantitative parameters of dynamic-enhanced magnetic resonance imaging (MRI) and the clinical pathological characteristics of patients with invasive breast cancer have been conducted to date. This study sought to explore the value of quantitative parameters of dynamic-enhanced MRI in predicting postoperative recurrence or metastasis in breast cancer patients and their correlations with clinical pathological features, so as to provide clinicians with understanding of MRI in breast cancer.MethodsFrom January 2016 to June 2017, 214 invasive breast cancer patients admitted to Affiliated Kunshan Hospital of Jiangsu University were retrospectively enrolled in this study. Dynamic-enhanced MRI was performed to analyze the relationship between quantitative parameters of dynamic-enhanced MRI and recurrence or metastasis, and analyze their correlations with clinical pathological features in patients with invasive breast cancer.ResultsThe apparent diffusion coefficient and peak time had certain diagnostic value for postoperative recurrence or metastasis in breast cancer patients, and the areas under the curve were 0.821 [95% confidence interval (CI): 0.732–0.911; P<0.001] and 0.691 (95% CI: 0.609–0.774; P<0.001), respectively. An apparent diffusion coefficient <0.78×10−3 mm2/s, a peak time <167.50 s, tumor staging (T staging) ≥2, vascular tumor thrombus, and positive lymph nodes were risk factors for postoperative recurrence or metastasis in breast cancer patients (odds ratio: 19.768, 95% CI: 2.577–151.619, P=0.004; 5.708, 95% CI: 1.088–29.947, P=0.039; 122.474, 95% CI: 5.334–2,812.360, P=0.003; 28.304, 95% CI: 1.372–583.914, P=0.030; 314.407, 95% CI: 10.617–9,310.547, P=0.001), and high estrogen receptor (ER) expression was a protective factor for postoperative recurrence or metastasis in breast cancer patients (odds ratio: 0.056, 95% CI: 0.004–0.795, P=0.033). The apparent diffusion coefficient was related to the site of onset, T staging, vascular tumor thrombus, and positive lymph nodes in breast cancer patients (P<0.05). Peak time was related to a high nuclear-associated antigen Ki-67 index, high ER expression, and high progesterone receptor (PR) expression in breast cancer patients (P<0.05).ConclusionsThe quantitative parameters of MRI were associated with clinical pathological characteristics and recurrence or metastasis in breast cancer after surgery.

Effect of Neoadjuvant Chemotherapy on Angiogenesis and Cell Proliferation of Breast Cancer Evaluated by Dynamic Enhanced Magnetic Resonance Imaging.

Background Breast cancer is the uncontrolled proliferation of breast epithelial cells under the action of various carcinogenic factors. The evaluation of early efficacy of neoadjuvant chemotherapy for breast cancer is helpful to change the treatment plan in time. On this basis, dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) was used to evaluate the effects of neoadjuvant chemotherapy on angiogenesis and cell proliferation in breast cancer. Objective To evaluate the effect of neoadjuvant chemotherapy on angiogenesis and cell proliferation of breast cancer by dynamic enhanced DCE-MRI. Method 80 breast cancer patients were divided into the routine chemotherapy group (3 cycles) and neoadjuvant chemotherapy groups (3 cycles) of 40 cases each from January 2018 to June 2021. Based on conventional imaging, DCE-MRI was performed with Intera Achieva 3.0 TMR superconducting MR scanner before and after treatment. The quantitative indexes, MRI parameters, cell proliferation expression, and DCE-MRI angiogenesis were compared between the two groups. Result The inhibition rate, Vepost, Ktranspre, ADC, Bax, Alexi, and Aurora in the neoadjuvant chemotherapy group were significantly higher than those in the conventional chemotherapy group (P < 0.05), while Kep, Ktrans, and Nek2 were significantly lower than those in the conventional chemotherapy group (P < 0.05). Vepre (cm3), Ktranspre (ml/min/100 cm3), and Ve had no significant difference (P > 0.05). Conclusion The quantitative parameters, MRI parameters, proliferation, and expression of DCE-MRI in breast cancer patients with different chemotherapy regimens are quite different. They can be applied to the diagnosis of neoadjuvant chemotherapy in breast cancer patients with angiogenesis and cell proliferation.

Quantitative Dynamic-Enhanced MRI and Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Prediction of the Pathological Response to Neoadjuvant Chemotherapy and the Prognosis in Locally Advanced Gastric Cancer.

BackgroundThis study aimed to explore the predictive value of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters for the response to neoadjuvant chemotherapy (NCT) in locally advanced gastric cancer (LAGC) patients, and the relationship between the prediction results and patients’ prognosis, so as to provide a basis for clinical individualized precision treatment.MethodsOne hundred twenty-nine newly diagnosed LAGC patients who underwent IVIM-DWI and DCE-MRI pretreatment were enrolled in this study. Pathological tumor regression grade (TRG) served as the reference standard of NCT response evaluation. The differences in DCE-MRI and IVIM-DWI parameters between pathological responders (pR) and pathological non-responders (pNR) groups were analyzed. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCT response. Prediction models were built with statistically significant quantitative parameters and their combinations. The performance of these quantitative parameters and models was evaluated using receiver operating characteristic (ROC) analysis. Clinicopathological variables, DCE-MRI and IVIM-DWI derived parameters, as well as the prediction model were analyzed in relation to 2-year recurrence-free survival (RFS) by using Cox proportional hazards model. RFS was compared using the Kaplan–Meier method and the log-rank test.ResultsSixty-nine patients were classified as pR and 60 were pNR. Ktrans, kep, and ve values in the pR group were significantly higher, while ADCstandard and D values were significantly lower than those in the pNR group. Multivariate logistic regression analysis demonstrated that Ktrans, kep, ve, and D values were independent predictors for NCT response. The combined predictive model, which consisted of DCE-MRI and IVIM-DWI, showed the best prediction performance with an area under the curve (AUC) of 0.922. Multivariate Cox regression analysis showed that ypStage III and NCT response predicted by the IVIM-DWI model were independent predictors of poor RFS. The IVIM-DWI model could significantly stratify median RFS (52 vs. 15 months) and 2-year RFS rate (72.3% vs. 21.8%) of LAGC.ConclusionPretreatment DCE-MRI quantitative parameters Ktrans, kep, ve, and IVIM-DWI parameter D value were independent predictors of NCT response for LAGC patients. The regression model based on baseline DCE-MRI, IVIM-DWI, and their combination could help RFS stratification of LAGC patients.

Early-phase vascular involvement is associated with acute pancreatitis severity: a magnetic resonance imaging study.

Although a number of studies have reported on the vascular abnormalities detected by magnetic resonance imaging (MRI) in patients with late-phase acute pancreatitis (AP), few have studied those occurring in the early phase of the disease. The aim of this research was to investigate the MRI findings of early vascular abnormalities in AP and to analyze the correlation of the prevalence of vascular involvement with the severity of AP based on the MR severity index (MRSI) and Acute Physiology and Chronic Health Evaluation (APACHE) II scores. A retrospective analysis was conducted of 301 consecutive AP patients who were admitted to our institution between March 2013 and June 2019. All patients underwent initial MRI during the early phase of pancreatitis and one or more repeat MRI scans in the late phase. Peripancreatic vascular conditions and pancreatitis were assessed using T1-/T2-weighted imaging and dynamic-enhanced MRI. The association between the prevalence of vascular involvement and AP severity graded according to the MRSI or APACHE II score was analyzed using Spearman's rank correlation. Among 301 AP patients, 75 (24.9%) had at least one MRI-detected vascular abnormality. Overall, vascular involvement on MRI was higher in necrotizing pancreatitis than in edematous pancreatitis [43.2% (54/125) vs. 11.9% (21/176), χ2=38.2, P<0.001]. In the early phase of AP, the prevalence of splenic vein phlebitis, portal vein phlebitis, and splenic arterial arteritis was 24.9% (75/301), 22.3% (67/301), and 19.9% (60/301), respectively. Splenic vein phlebitis was seen on initial MRI in 55.6% (15/27) of patients who had splenic vein thrombosis on repeat MRI. The MRSI scores showed that the prevalence of splenic vein phlebitis, portal vein phlebitis, and splenic arterial arteritis, respectively, was correlated with the severity of pancreatitis (r=0.532, 0.487, and 0.456; all P<0.01). The APACHE II scores showed that the prevalence of MRI-detected vascular involvement was significantly correlated with AP severity (r=0.335, P<0.05). Vascular abnormalities, including splenic vein phlebitis and splenic arterial arteritis, are commonly seen on MRI in patients with early-phase AP, and they may be supplementary indicators that can reflect the severity of pancreatitis.

Comparative study ofmethylene blue tracer and double tracer containing nuclide in sentinel lymph node biopsy of breast cancer

Objective: To compare the application effect of blue dye single tracer and blue dye combined with nuclide double tracer in sentinel lymph node biopsy (SLNB) of breast cancer surgery. Methods: A total of 92 breast cancer patients in Shandong Cancer Hospital and Institute from November 2017 to October 2019 underwent methyleneblue dye combined with (99)Tc(m) sulfur colloid nuclide double tracer in SLNB, while other 92 cases in Jining First People Hospital underwent blue dye single tracer. The number of SLN detection, detection rate, accuracy rate, sensitivity, and false negative rate of the two groups were compared. The impacts of age, menstruation, tumor location, tumor size, clinical stage, pathological type, and estrogen receptor (ER), progesterone receptor (PR), human epidermal receptor 2 (HER-2), molecular typing, dynamic enhanced magnetic resonance imaging (DCE-MRI)on the detection rate of SLN were analyzed. Results: The number of detection, detection rate, accuracy, sensitivity, and false negative rate of the blue dye single tracer group were 3.20±1.10, 90.22%, 93.48%, 95.24% and 4.76%, respectively; the double tracer group were 3.37±1.02, 92.39%, 95.65%, 95.65% and 4.35%, respectively, without significant difference (all P>0.05). In different age, menstrual condition, tumor location, clinical stage, pathological type, ER, PR, HER-2 expression and molecular typing, the detection rate of single tracer group and double tracer group had no significant difference (all P>0.05). However, in the tumor size of 2-5 cm and without DCE-MRI examination, the detection rate of single tracer group was significantly lower than that of double tracer group. Conclusion: The effect of blue dye single tracer in detecting SLN of breast cancer is equivalent to that of double tracer method, which is worthy of promotion and application in primary hospitals.

The Application Value of Magnetic Resonance Imaging (MRI) in the Clinical Diagnosis in Hospital Management.

Background & Objective:To evaluate the application value of dynamic enhanced magnetic resonance imaging (DCE-MRI) in the clinical diagnosis in hospital based on the fuzzy C-means clustering algorithm and conduct its cost-benefit analysis in practice.Methods:This study was conducted from October 11th 2020 to November 25, 2020. Eighteen patients with lung cancer confirmed by pathology were collected and examined by DCE-MRI one day before and one month after surgery using a fuzzy C-means clustering algorithm. And then, taking Guang’an District People’s Hospital as an example, the present paper conducts the cost-benefit analysis with the utilization of net present value (NPV).Results:After 1-month review, eleven patients with effective treatment, four numerical Ktrans, Kep, Ve, Vp compared with preoperative decreased, which Ktrans, Kep, the change of the Ve was statistically significant (P < 0.05), the Vp of decline has no statistical significance (P > 0.05), the experimental and ineffective group after an operation, compared to four numerical Ktrans and Vp difference was statistically significant (P < 0.05), the corresponding AUC (area under the curve) to 1 and 0.818, the sensitivity of 100% and 85.7%, a specific degree of 100% and 72.7%. The NPV analysis results showed that the hospital could achieve profit and loss balance in the third year after purchasing MRI equipment and then gradually obtain positive cash inflow.Conclusion:The application of MRI in the Clinical Diagnosis helps hospital promote the therapeutic effect, thus having great practical value, and also contributes to increasing benefits in the long run.

Free-breathing radial volumetric interpolated breath-hold examination sequence and dynamic contrast-enhanced MRI combined with diffusion-weighted imaging for assessment of solitary pulmonary nodules

ObjectiveTo test the performance of free-breathing Dynamic Contrast-Enhanced MRI (DCE-MRI) using a radial volumetric interpolated breath-hold examination (VIBE) sequence combined with diffusion-weighted imaging (DWI) for quantitative solitary pulmonary nodule (SPN) assessment. MethodsA total of 67 SPN cases receiving routine MRI routine scans, DWI, and dynamic-enhanced MRI in our hospital from May 2017 to November 2018 were collected. These cases were divided into a malignant group and a benign group according to the characteristics of the SPNs. The quantitative DCE-MRI parameters (Ktrans, Kep, Ve) and apparent diffusion coefficient (ADC) values of the nodules were measured. ResultsThe Ktrans and Kep values in the malignant group were higher than those in the benign group, while the ADC values in the malignant group were lower than those in the benign group. Furthermore, the Ktrans value of adenocarcinoma was higher than that of squamous cell carcinoma and small cell carcinoma (P < 0.05). The Ve value was significantly different between non-small cell carcinoma and small cell carcinoma (P < 0.05). With an ADC value of 0.98 × 10−3 mm2/s as the threshold, the specificity and sensitivity to diagnose benign and malignant nodules was 90.6% and 80%, respectively. ConclusionHigh-temporal-resolution DCE-MRI using the r-VIBE technique in combination with DWI could contribute to pulmonary nodule analysis and possibly serve as a potential alternative to distinguish malignant from benign nodules as well as differentiate different types of malignancies.

Adult pancreatoblastoma: clinical features and Imaging findings

The objective of this study was to illustrate the clinical, CT, MRI, and 18F-FDG PET/CT features of adult pancreatoblastoma, an extremely rare disease. In this study, the clinical and imaging features of seven adult patients with pathologically confirmed pancreatoblastoma were retrospectively analyzed. The following parameters were evaluated: size, location, shape, margination, solid-cystic ratio, CT attenuation values or signal intensity and contrast enhancement pattern. We also analyzed whether abnormal FDG uptake occurred during 18F-FDG PET/CT imaging. All seven patients were male (mean age 45 years; range 22–65 years). Six tumors were irregular in shape, exogenous, and grew outward from the pancreatic parenchyma, similar to branches growing from a tree trunk (85.7%). The tumor margins were clear in five patients (71.4%), and three tumors (42.9%) were encapsulated. Six tumors (71.4%) were solid, with homogeneous enhancement observed on contrast-enhanced CT and MRI. Dynamic-enhanced CT and MRI showed progressive enhancement for all tumors. On 18F-FDG PET/CT, one tumor exhibited abnormal FDG uptake, and two tumors exhibited no abnormal uptake (66.7%). In conclusion, adult pancreatoblastoma most commonly occurs in male patients, and it usually appears as an exophytic, irregular, and hypovascular mass with well-defined margins and progressive enhancement on CT and MRI. This type of tumor always grows out of the parenchyma of the pancreas, similar to branches growing outward from a tree trunk.

Generative adversarial network-based super-resolution of diffusion-weighted imaging: Application to tumour radiomics in breast cancer.

Diffusion-weighted imaging (DWI) is increasingly used to guide the clinical management of patients with breast tumours. However, accurate tumour characterization with DWI and the corresponding apparent diffusion coefficient (ADC) maps are challenging due to their limited resolution. This study aimed to produce super-resolution (SR) ADC images and to assess the clinical utility of these SR images by performing a radiomic analysis for predicting the histologic grade and Ki-67 expression status of breast cancer. To this end, 322 samples of dynamic enhanced magnetic resonance imaging (DCE-MRI) and the corresponding DWI data were collected. A SR generative adversarial (SRGAN) and an enhanced deep SR (EDSR) network along with the bicubic interpolation were utilized to generate SR-ADC images from which radiomic features were extracted. The dataset was randomly separated into a development dataset (n = 222) to establish a deep SR model using DCE-MRI and a validation dataset (n = 100) to improve the resolution of ADC images. This random separation of datasets was performed 10 times, and the results were averaged. The EDSR method was significantly better than the SRGAN and bicubic methods in terms of objective quality criteria. Univariate and multivariate predictive models of radiomic features were established to determine the area under the receiver operating characteristic curve (AUC). Individual features from the tumour SR-ADC images showed a higher performance with the EDSR and SRGAN methods than with the bicubic method and the original images. Multivariate analysis of the collective radiomics showed that the EDSR- and SRGAN-based SR-ADC images performed better than the bicubic method and original images in predicting either Ki-67 expression levels (AUCs of 0.818 and 0.801, respectively) or the tumour grade (AUCs of 0.826 and 0.828, respectively). This work demonstrates that in addition to improving the resolution of ADC images, deep SR networks can also improve tumour image-based diagnosis in breast cancer.

Quantitative analysis of microvascular invasion preoperative prediction in solitary small hepatocellular carcinoma on dynamic enhancement MRI

Quantitative analysis of microvascular invasion preoperative prediction in solitary small hepatocellular carcinoma on dynamic enhancement MRI

Correlation analysis between short-term invasive recurrence and functional MRI after radiofrequency ablation of hepatocellular carcinoma

Objective To explore and clarify the correlation between short-term aggressive intrasegmental recurrence (AIR) and functional magnetic resonance imaging after radiofrequency ablation of hepatocellular carcinoma (HCC). Methods A retrospective analysis of 1 262 patients with HCC who underwent radiofrequency ablation (RFA) in our hospital from January 2012 to June 2018, all patients were confirmed by pathology as HCC, of which 30 patients were found to have AIR during radiographic follow-up within 3 months after surgery, another 35 patients with disease progression who were controlled in a short period of time were randomly selected as the control group. All the enrolled patients underwent dynamic enhanced magnetic resonance imaging (DCE-MRI) and diffusion weighted imaging (DWI) scanning before surgery, and the differences in clinical data, lesion location, and functional magnetic resonance parameters between the two groups were compared, and their correlation with AIR after RFA was analyzed. Chi-square test, t test and Pearson test were used. Results The lesions in the AIR group were significantly more in the Ⅰand Ⅳsegments than that in the control group (P 0.05). There was no significant difference in the lesion morphology between the two groups (P>0.05), and there was a significant difference in the early enhancement pattern of the lesions (P<0.05), and the early arterial enhancement rate and apparent diffusion coefficient (ADC) value of the AIR group were significantly lower than the control group (P<0.05). Further correlation analysis found that early enhancement of the arterial artery, early arterial enhancement rate, ADC value and lesion location were associated with AIR and were positively correlated, r values were 0.455, 0.633, 0.518, 0.375 and 0.287 (P<0.05). Conclusion The short-term AIR and functional imaging parameters (arterial early enhancement, early arterial enhancement rate, ADC value) and the liver segment (Ⅰ and Ⅳ) were highly correlated with radiofrequency ablation. Key words: Liver neoplasms; Radiofrequency ablation; Aggressive intrasegmental recurrence; Magnetic resonance imaging

Value of dynamic MRI in monitoring the microenvironmental changes of anti-vascular therapy in a xenograft model

Objective: To explore the feasibility of dynamic-enhanced magnetic resonance imaging (DCE-MRI) and blood oxygen level-dependent MRI (BOLD-MRI) in assessing the hemodynamics and tumor aggressiveness during treatment. Methods: The colon cancer xenograft model was established in BALB/C nude mice with HCT116 cell line. Sixteen nude mice were randomly divided into treatment and control groups (aged 6 to 8 weeks, weighted 15 to 18 g, Certificate No. 11400700325797), which were treated with bevacizumab and saline by intraperitoneal injection on the 1st, 4th, 7th, 10th and 13th day. DCE-MRI and BOLD-MRI were performed before and on the 3th, 6th, 9th, 12th, and 15th day after treatment. The vascular maturity and microenvironment hypoxia were confirmed by pathology. Results: The tumor volume of treatment group was significantly smaller than that of control group after 15 days ((712±43) vs (1 051±112) mm(3),P<0.01).The measurements of K(trans) were (0.135±0.005),(0.147±0.006),(0.175±0.009),(0.161±0.006), (0.140±0.005),(0.116±0.008)/min (F=81.386, P<0.01); K(ep) were (0.788±0.030),(0.804±0.036),(0.983±0.059), (1.105±0.091),(0.840±0.047),(0.786±0.041)/min(F=45.901,P<0.01);Ve were (0.652±0.006), (0.559±0.026), (0.466±0.016), (0.286±0.027), (0.363±0.020), (0.246±0.033) (F=384.290, P<0.01) and R2* values were (24.813±0.961), (24.675±1.070), (21.425±1.371), (17.850±0.885), (24.613±0.640), (27.013±0.734)/s (F=89.323, P<0.01) showed different trends with time in the treatment group, and the differences were statistically significant. The K(trans) values and tumor vessel maturity index (VMI) were higher than baseline values during 3-12 d after treatment. CD31 positive staining rate and VMI had the strongest correlations with K(trans) values (r=0.854 and 0.795), followed by AUC(180) (r=0.750 and 0.808), Ve (r=0.744 and 0.712) and K(ep) values (r=0.729 and 0.758), all P<0.05. R2* value positively correlated with the positive staining rate of HIF-1α and fibronectin (r=0.810 and 0.816), all P<0.05. Conclusion: DCE-MRI and BOLD-MRI are adequate to observe the tumor perfusion and hypoxia during anti-vascular treatment, and the R2* value can predict the tumor metastatic potential during the process of vascular normalization.

Progresses of Functional Magnetic Resonance Imaging Diagnosis in Breast Cancer

Breast cancer is the most common malignant tumor that threatens women’s health. Breast magnetic resonance imaging (MRI) is a commonly used method recommended for the diagnosis of breast cancer. Diffusion weighted imaging (DWI) and dynamic enhanced magnetic resonance imaging (DCE-MRI) are now widely used. At present, with the continuous advancement of magnetic resonance technology, Magnetic resonance spectroscopy (MRS), Perfusion weighted imaging (PWI), Positron emission tomography-magnetic resonance imaging (PET-MRI) and so on are gradually being used in clinical practice. Mammography imaging and imaging genomics are hot topics. This article will briefly introduce several functional magnetic resonance techniques and their latest applications.

The Specific Magnetic Resonance Imaging Indicators in Predicting Clear-Cell Renal Cell Carcinoma Metastatic to the Sinonasal Region.

The aim of this study was to determine the valuable magnetic resonance imaging (MRI) features of sinonasal metastatic clear-cell renal cell carcinoma (cc-RCC), especially focusing on its dynamic-enhanced characteristics. The conventional and dynamic-enhanced MRI findings of 8 patients with histopathologically confirmed sinonasal metastatic cc-RCC were reviewed by 2 radiologists. The control group of 8 patients with capillary hemangioma underwent the same MRI protocol. Metastatic cc-RCCs arose from the nasoethmoid region, maxillary sinus, posterior ethmoid and sphenoid sinus, and nasal cavity in 2 patients in each. These lesions were well circumscribed and the mean maximum dimension was 42 mm. The signal intensity of these lesions was isointense to brain stem on both MR T1- and T2-weighted images. All metastatic tumors showed vivid enhancement on enhanced T1-weighted image. Multiple flow voids within these metastatic lesions were identified in 6 patients. Peripheral cyst was detected around the metastatic tumor in 4 patients. Metastatic cc-RCCs exhibited a characteristic type 4 time intensity curve (TIC) similar to that of the internal carotid artery, whereas capillary hemangiomas showed a type 3 TIC on dynamic-enhanced MRI. A hypervascular mass with the characteristic type 4 TIC in the sinonasal region is highly suggestive of a metastatic cc-RCC.

Correlation of quantitative parameters of dynamic enhanced magnetic resonance imaging with Dukes stage, lymph node metastasis and tumor differentiation degree of rectal cancer

Objective To explore the correlation between quantitative parameters of dynamic enhanced magnetic resonance imaging (DCE-MRI) and Dukes stage, lymph node metastasis, tumor differentiation degree and molecular biological indicators [Ki67 and human epidermal growth factor receptor 2 (CerbB-2)] of rectal cancer. Methods This study was a prospective study. From October 2014 to October 2017, 168 cases of rectal cancer patients were selected as the research objects. DCE-MRI was performed preoperatively to obtain the quantitative parameter values of region of interest (ROI) [apparent diffusion coefficient (ADC)mean, Ktrans, Ve, and Kep] in tumor site. The expression of Ki67 and CerbB-2 were detected by immunohistochemical. Correlations of DCE-MRI quantitative parameter values and rectal cancer Dukes staging, lymph node metastasis, tumor differentiation degree to Ki67 and CerbB-2 expression level were analysised. Results With the increase of tumor differentiation, ADCmean was increasing, while Ktrans and Ve showed a downward trend, with significant difference (P 0.05). The ADCmean was statistically significant between different groups (P 0.05). The ADCmean of lymph node metastasis group was significantly lower than that of no lymph node metastasis group (P<0.001), while Ktrans, Ve and Kep were significantly higher than that of no lymph node metastasis group (P<0.001). With the increase of Dukes staging in rectal cancer, ADCmean was decreasing and Ktrans was increasing, with statistically significant difference (P<0.001); among which the ADCmean of Dukes A and B was significantly higher than that of Dukes C and D (P<0.05), and Ktrans was significantly lower than that of Dukes C and D (P<0.05). Ktrans and Kep were increased with the increased expression levels of Ki67 and CerbB-2, and the difference between Ktrans and Kep was statistically significant (P<0.05). The ADCmean decreased with the increase of Ki67 and CerbB-2 expression level, and the difference was statistically significant (P<0.05). Conclusions DCE-MRI quantitatively participates can reflect the biological behavior of rectal cancer, and can be used to evaluate the prognosis of tumors and guide the clinical selection of more appropriate treatment options. Key words: Rectal neoplasms; Magnetic resonance imaging; Diagnosis, computer-assisted; Ki-67 antigen; Receptor, erbB-2

The Correlation between Osteoporosis and Blood Circulation Function Based on Magnetic Resonance Imaging.

In order to investigate the relationship between changes in blood circulation and bone mineral density (BMD) loss, the characteristic parameters reflecting the function of tissue oxygen metabolism are obtained by means of blood oxygen level-dependent magnetic resonance imaging (BOLD-MRI), image processing and semi-quantitative analysis. The correlation and variance analysis of the characteristic parameters of different BMD groups are carried out, and the physiological parameters of bone marrow blood perfusion are obtained by dynamic enhanced MRI (DCE-MRI). Multivariate logistic regression analysis is carried out with the physiological parameters of blood oxygen metabolism function and bone marrow blood perfusion as independent variables and BMD as dependent variables. It is found that there are significant differences in oxygen metabolism between individual muscles in different BMD groups and between skeletal muscles of different types of muscle fibers. Age, total volume of bone marrow and oxygen metabolism ability of tibial anterior muscle have significant independent effects on osteoporosis. It shows that the changes of blood circulation in bone marrow and surrounding muscle tissue are indeed one of the causes of osteoporosis.

Grading of hepatocellular carcinoma using 3D SE-DenseNet in dynamic enhanced MR images

BackgroundClinical histological grading of hepatocellular carcinoma (HCC) differentiation is of great significance in clinical diagnoses, treatments, and prognoses. However, it is challenging for radiologists to evaluate HCC gradings from medical images. PurposeIn this study, a novel deep neural network was developed by combining the squeeze-and-excitation networks (SENets) in a three-dimensional (3D) densely connected convolutional network (DenseNet), which is referred to as a 3D SE-DenseNet, for the classification of HCC grading using enhanced clinical magnetic resonance (MR) images obtained from two different clinical centers. MethodIn the proposed architecture, the SENet was added as an additional layer between the dense blocks of the 3D DenseNet, to mitigate the impact of feature redundancy. For the HCC grading task, the 3D SE-DenseNet was trained after data augmentation, and it outperformed the 3D DenseNet based on the clinical dataset. ResultsThe quantitative evaluations of the 3D SE-DenseNet on a two-class HCC grading task were conducted based on the dataset, which included 213 samples of the dynamic enhanced MR images. The proposed 3D SE-DenseNet demonstrated an accuracy of 83%, when compared with the 72% accuracy of the 3D DenseNet. ConclusionOwing to the advantage of useful automatic feature learning by the SE layer, the 3D SE-DenseNet can simultaneously handle useful feature enhancement and superfluous feature suppression. The quantitative experiments confirm the excellent performance of the 3D SE-DenseNet in the evaluation of the HCC grading.