Integrating Tumor and Nodal Radiomics to Predict the Response to Neoadjuvant Chemotherapy and Recurrence Risk for Locally Advanced Gastric Cancer.

AIMS: To develop and evaluate machine learning models using tumor and nodal radiomics features for predicting the response to neoadjuvant chemotherapy (NAC) and recurrence risk in locally advanced gastric cancer (LAGC). BACKGROUND: Early and accurate response prediction is vital to stratify LAGC patients and select proper candidates for NAC. OBJECTIVE: A total of 218 patients with LAGC undergoing NAC followed by gastrectomy were enrolled in our study and were randomly divided into a training cohort (n = 153) and a validation cohort (n = 65). METHODS: We extracted 1316 radiomics features from the volume of interest of the primary lesion and maximal lymph node on venous phase CT images. We built 3 radiomics signatures for distinguishing good responders and poor responders based on tumor radiomics (TR), nodal radiomics (NR), and a combination of the two (TNR), respectively. A nomogram was then developed by integrating the radiomics signature and clinical factors. Kaplan- Meier survival curves were used to evaluate the prognostic value of the nomogram. RESULTS: The TNR signature achieved improved predictive value, with AUCs of 0.755 and 0.744 in the training and validation cohorts. Our proposed nomogram model (TNRN) showed a good performance for GR prediction in the prediction efficacy, calibration ability, and clinical benefit, with AUCs of 0.779 and 0.732 in the training and validation cohorts, superior to the clinical model. Moreover, the TNRN could accurately classify the patients into high-risk and low-risk groups in both training and validation cohorts with regard to postoperative recurrence and metastasis. CONCLUSION: The TNRN performed well in identifying good responders and provided valuable information for predicting progression-free survival time (PFS) in patients with LAGC who underwent NAC.

Improved deep learning for automatic localisation and segmentation of rectal cancer on T2-weighted MRI.

INTRODUCTION: The automatic segmentation approaches of rectal cancer from magnetic resonance imaging (MRI) are very valuable to relieve physicians from heavy workloads and enhance working efficiency. This study aimed to compare the segmentation accuracy of a proposed model with the other three models and the inter-observer consistency. METHODS: A total of 65 patients with rectal cancer who underwent MRI examination were enrolled in our cohort and were randomly divided into a training cohort (n = 45) and a validation cohort (n = 20). Two experienced radiologists independently segmented rectal cancer lesions. A novel segmentation model (AttSEResUNet) was trained on T2WI based on ResUNet and attention mechanisms. The segmentation performance of the AttSEResUNet, U-Net, ResUNet and U-Net with Attention Gate (AttUNet) was compared, using Dice similarity coefficient (DSC), Hausdorff distance (HD), mean distance to agreement (MDA) and Jaccard index. The segmentation variability of automatic segmentation models and inter-observer was also evaluated. RESULTS: The AttSEResUNet with post-processing showed perfect lesion recognition rate (100%) and false recognition rate (0), and its evaluation metrics outperformed other three models for two independent readers (observer 1: DSC = 0.839 ± 0.112, HD = 9.55 ± 6.68, MDA = 0.556 ± 0.722, Jaccard index = 0.736 ± 0.150; observer 2: DSC = 0.856 ± 0.099, HD = 11.0 ± 10.1, MDA = 0.789 ± 1.07, Jaccard index = 0.673 ± 0.130). The segmentation performance of AttSEResUNet was comparable and similar to manual variability (DSC = 0.857 ± 0.115, HD = 10.0 ± 10.0, MDA = 0.704 ± 1.17, Jaccard index = 0.666 ± 0.139). CONCLUSION: Comparing with other three models, the proposed AttSEResUNet model was demonstrated as a more accurate model for contouring the rectal tumours in axial T2WI images, whose variability was similar to that of inter-observer.

Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.

RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary response after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. MATERIALS AND METHODS: We enrolled 327 BC patients with axillary lymph node (ALN) metastases receiving axillary operations after NAC. The deep learning features were extracted by ResNet34, which was pretrained by a large, well-annotated dataset from ImageNet. Then we identified deep learning radiomics on magnetic resonance imaging with dynamic contrast enhancement (DCE-MRI) in predicting axillary response after NAC in BC patients. RESULTS: The extraction of 128 deep learning radiomics (DLR) features relied on the DCE-MRI for each patient. After the least absolute shrinkage and selection operator regression analysis, 13, 8, and 21 features remained from the pre-treatment, post-treatment, and combined DCE-MRI, respectively. The DLR signature established based on the combined DCE-MRI achieved good capacity in ALN response after NAC. The support vector machine achieved the best performance with an 0.99 area under the curve (AUC) of (95% confidence interval (CI), 0.98-1.00) and 0.83 (95% CI, 0.73-0.92) in the training and test sets, respectively. The LR model established with clinical parameters represented the best performance with 0.73 AUC (95% CI, 0.62-0.84), 0.73 sensitivity, 0.73 specificity, 0.63 PPV, and 0.81 NPV in the test set, respectively. Finally, the integration of radiomic signature and clinical signature resulted in establishing a predictive radiomic nomogram, with an AUC of 0.99 (95%CI, 0.99-1.00). CONCLUSION: In conclusion, our current study constructed a predictive nomogram through the deep learning method, demonstrating favorable performance in the training and test cohort. The present prognostic model furnishes a precise and objective foundation for directing the surgical strategy toward ALN management in BC patients receiving NAC.

Pulmonary nodules segmentation based on domain adaptation.

With the development of deep learning, the methods based on transfer learning have promoted the progress of medical image segmentation. However, the domain shift and complex background information of medical images limit the further improvement of the segmentation accuracy. Domain adaptation can compensate for the sample shortage by learning important information from a similar source dataset. Therefore, a segmentation method based on adversarial domain adaptation with background mask (ADAB) is proposed in this paper. Firstly, two ADAB networks are built for the source and target data segmentation, respectively. Next, to extract the foreground features that are the input of the discriminators, the background masks are generated according to the region growth algorithm. Then, to update the parameters in the target network without being affected by the conflict between the distinguishing differences of the discriminator and the domain shift reduction of the adversarial domain adaptation, a gradient reversal layer propagation is embedded in the ADAB model for the target data. Finally, an enhanced boundaries loss is deduced to make the target network sensitive to the edge of the area to be segmented. The performance of the proposed method is evaluated in the segmentation of pulmonary nodules in computed tomography images. Experimental results show that the proposed approach has a potential prospect in medical image processing.

Preoperative Evaluation of Gd-EOB-DTPA-Enhanced MRI Radiomics-Based Nomogram in Small Solitary Hepatocellular Carcinoma (≤3 cm) With Microvascular Invasion: A Two-Center Study.

BACKGROUND: Preoperative evaluation of microvascular invasion (MVI) in small solitary hepatocellular carcinoma (HCC; maximum lesion diameter ≤ 3 cm) is important for treatment decisions. PURPOSE: To apply gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI to develop and validate a nomogram for preoperative evaluation of MVI in small solitary HCC and to compare the effectiveness of radiomics evaluation models based on different volumes of interest (VOIs). STUDY TYPE: Retrospective. POPULATION: A total of 196 patients include 62 MVI-positive and 134 MVI-negative patients were enrolled (training cohort, n = 105; testing cohort, n = 45; external validation cohort, n = 46). FIELD STRENGTH/SEQUENCE: 3.0 T, fat suppressed fast-spin-echo T2-weighted and Gd-EOB-DTPA-enhanced T1-weighted magnetization-prepared rapid gradient-echo sequences. ASSESSMENT: Radiomics features were extracted on T2-weighted, arterial phase (AP), and hepatobiliary phase (HBP) images from different VOIs (VOIintratumor and VOIintratumor+peritumor ) and filtered by the least absolute shrinkage selection operator (LASSO) regression. From VOIintratumor and VOIintratumor+peritumor , eight radiomics models were constructed based on three MRI sequences (T2-weighted, AP, and HBP) and fused sequences (combined of three sequences). Nomograms were constructed of a clinical-radiological (CR) model and a clinical-radiological-radiomics (CRR) model. STATISTICAL TESTS: One-way analysis of variance, independent t-test, Chi-square test or Fisher's exact test, Wilcoxon rank-sum test, LASSO, logistic regression analysis, area under the curve (AUC), nomograms, decision curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI) analyses, and DeLong test. RESULTS: Among eight radiomics models, the fused sequences-based VOIintratumor+peritumor radiomics model showed the best performance. The CRR model containing the best performance radiomics model and CR model with the AUC values were 0.934, 0.889, and 0.875, respectively. NRI and IDI analyses showed that the CRR model improved evaluation efficacy over the CR model for all three cohorts (all P-value <0.05). DATA CONCLUSION: The CRR model nomogram could preoperatively evaluate MVI in small solitary HCC. The radiomics model based on VOIintratumor+peritumor might achieve better evaluation results. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY STAGE: 2.

CT Radiomics Model for Predicting the Ki-67 Index of Lung Cancer： An Exploratory Study.

OBJECTIVE: To establish a radiomics signature and a nomogram model based on enhanced CT images to predict the Ki-67 index of lung cancer. METHODS: From January 2014 to December 2018, 282 patients with lung cancer who had undergone enhanced CT scans and Ki-67 examination within 2 weeks were retrospectively enrolled and analyzed. The clinical data of the patients were collected, such as age, sex, smoking history, maximum tumor diameter and serum tumor markers. Our primary cohort was randomly divided into a training group (n=197) and a validation group (n=85) at a 7:3 ratio. A Ki-67 index ≤ 40% indicated low expression, and a Ki-67 index > 40% indicated high expression. In total, 396 radiomics features were extracted using AK software. Feature reduction and selection were performed using the lasso regression model. Logistic regression analysis was used to establish a multivariate predictive model to identify high and low Ki-67 expression in lung cancer. A nomogram integrating the radiomics score was established based on multiple logistic regression analysis. Area under the curve (AUC) was used to evaluate the prediction efficiency of the radiomics signature and nomogram. RESULTS: The AUC,sensitivity, specificity and accuracy of the radiomics signature in the training and validation groups were 0.88 (95% CI: 0.82~0.93),79.2%,84.3%,81.2% and 0.86 (95% CI: 0.78~0.94),74.6%,88.1%,79.8%, respectively. A nomogram combining radiomics features and clinical risk factors (smoking history and NSE) was developed. The AUC, sensitivity, specificity and accuracy were 0.87 (95% CI: 0.80~0.95), 75.0%, 90.2% and 83.5% in the validation group, respectively. CONCLUSION: The radiomics signature and nomogram based on enhanced CT images provide a way to predict the Ki-67 expression level in lung cancer.

Gastrointestinal-type chemotherapy prolongs survival in an atypical primary ovarian mucinous carcinoma: A case report.

BACKGROUND: Primary ovarian mucinous carcinoma is a rare histologic subtype of epithelial ovarian carcinoma and exhibits considerable morphologic overlap with secondary tumour. It is hard to differentiate primary from metastatic ovarian mucinous carcinoma by morphological and immunohistochemical features. Because of the histologic similarity between primary ovarian mucinous carcinoma and metastatic gastrointestinal carcinoma, it has been hypothesized that ovarian mucinous carcinomas might respond better to non-gynecologic regimens. However, the standard treatment of advanced ovarian mucinous carcinoma has not reached a consensus. CASE SUMMARY: A 56-year-old postmenopausal woman presented with repeated pain attacks in the right lower quadrant abdomen, accompanied by diarrhoea, anorexia, and weight loss for about 3 mo. The patient initially misdiagnosed as having gastrointestinal carcinoma because of similar pathological features. Based on the physical examination, tumour markers, imaging tests, and genetic tests, the patient was clinically diagnosed with ovary mucinous adenocarcinoma. Whether gastrointestinal-type chemotherapy or gynecologic chemotherapy was a favourable choice for patients with advanced ovarian mucinous cancer had not been determined. The patient received a chemotherapy regimen based on the histologic characteristics rather than the tumour origin. The patient received nine cycles of FOLFOX and bevacizumab. This was followed by seven cycles of bevacizumab maintenance therapy for 9 mo. Satisfactory therapeutic efficacy was achieved. CONCLUSION: The genetic analysis might be used in the differential diagnosis of primary ovarian mucinous carcinoma and non-gynecologic mucinous carcinoma. Moreover, primary ovarian mucinous carcinoma patients could benefit from gastrointestinal-type chemotherapy.

CT Texture Analysis for Preoperative Identification of Lymphoma from Other Types of Primary Small Bowel Malignancies.

OBJECTIVES: To explore the application of computed tomography (CT) texture analysis in differentiating lymphomas from other malignancies of the small bowel. METHODS: Arterial and venous CT images of 87 patients with small bowel malignancies were retrospectively analyzed. The subjective radiological features were evaluated by the two radiologists with a consensus agreement. The region of interest (ROI) was manually delineated along the edge of the lesion on the largest slice, and a total of 402 quantified features were extracted automatically from AK software. The inter- and intrareader reproducibility was evaluated to select highly reproductive features. The univariate analysis and minimum redundancy maximum relevance (mRMR) algorithm were applied to select the feature subsets with high correlation and low redundancy. The multivariate logistic regression analysis based on texture features and radiological features was employed to construct predictive models for identification of small bowel lymphoma. The diagnostic performance of multivariate models was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: The clinical data (age, melena, and abdominal pain) and radiological features (location, shape, margin, dilated lumen, intussusception, enhancement level, adjacent peritoneum, and locoregional lymph node) differed significantly between the nonlymphoma group and lymphoma group (p < 0.05). The areas under the ROC curve of the clinical model, arterial texture model, and venous texture model were 0.93, 0.92, and 0.87, respectively. CONCLUSION: The arterial texture model showed a great diagnostic value and fitted performance in preoperatively discriminating lymphoma from nonlymphoma of the small bowel.

Active targeting theranostic iron oxide nanoparticles for MRI and magnetic resonance-guided focused ultrasound ablation of lung cancer.

Despite its great promise in non-invasive treatment of cancers, magnetic resonance-guided focused ultrasound surgery (MRgFUS) is currently limited by the insensitivity of magnetic resonance imaging (MRI) for visualization of small tumors, low efficiency of in vivo ultrasonic energy deposition, and damage to surrounding tissues. We hereby report the development of an active targeting nano-sized theranostic superparamagnetic iron oxide (SPIO) platform for significantly increasing the imaging sensitivity and energy deposition efficiency using a clinical MRgFUS system. The surfaces of these PEGylated SPIO nanoparticles (NPs) were decorated with anti-EGFR (epidermal growth factor receptor) monoclonal antibodies (mAb) for targeted delivery to lung cancer with EGFR overexpression. The potential of these targeted nano-theranostic agents for MRI and MRgFUS ablation was evaluated in vitro and in vivo in a rat xenograft model of human lung cancer (H460). Compared with nontargeting PEGylated SPIO NPs, the anti-EGFR mAb targeted PEGylated SPIO NPs demonstrated better targeting capability to H460 tumor cells and greatly improved the MRI contrast at the tumor site. Meanwhile, this study showed that the targeting NPs, as synergistic agents, could significantly enhance the efficiency for in vivo ultrasonic energy deposition in MRgFUS. Moreover, we demonstrated that a series of MR methods including T2-weighted image (T2WI), T1-weighted image (T1WI), diffusion-weighted imaging (DWI) and contrast-enhanced T1WI imaging, could be utilized to noninvasively and conveniently monitor the therapeutic efficacy in rat models by MRgFUS.

Facile Synthesis of Folic Acid-Modified Iron Oxide Nanoparticles for Targeted MR Imaging in Pulmonary Tumor Xenografts.

PURPOSE: The purpose of this study was to develop folic acid (FA)-modified iron oxide (Fe3O4) nanoparticles (NPs) for targeted magnetic resonance imaging (MRI) of H460 lung carcinoma cells. PROCEDURES: Water-dispersible Fe3O4 NPs synthesized via a mild reduction method were conjugated with FA to generate FA-targeted Fe3O4 NPs. The specificity of FA-targeted Fe3O4 NPs to bind FA receptor was investigated in vitro by cellular uptake and cell MRI and in vivo by MRI of H460 tumors. RESULTS: The formed NPs displayed good biocompatibility and ultrahigh r 2 relaxivity (440.01/mM/s). The targeting effect of the NPs to H460 cells was confirmed by in vitro cellular uptake and cell MRI. H460 tumors showed a significant reduction in T2 signal intensity at 0.85 h, which then recovered and returned to control at 2.35 h. CONCLUSIONS: The results indicate that the prepared FA-targeted Fe3O4 NPs have potential to be used as T2 negative contrast agents in targeted MRI.

Assessment of Lipiodol Deposition and Residual Cancer for Hepatocellular Carcinoma After Transcatheter Arterial Chemoembolization via Iodine-Based Material Decomposition Images with Spectral Computed Tomography Imaging: A Preliminary Study.

BACKGROUND: It is critical to follow up hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) in clinical practice. Computed tomography (CT) is used to assess lipiodol deposition, whereas it is difficult to assess hypovascular residual cancer masked by lipiodol. In contrast, magnetic resonance imaging (MRI) is superior to CT in showing residual cancer, but cannot display lipiodol deposition. OBJECTIVES: The aim of this study was to investigate the value of spectral CT imaging in both lipiodol deposition and residual cancer for HCC patients after TACE. PATIENTS AND METHODS: Ten HCC patients after treated with TACE underwent Discovery CT750 HD and MRI750 3T examination. Receiver operating characteristic (ROC) curves of iodine-based material decomposition images, monochromatic images and conventional CT images were generated. RESULTS: Consequently, 30 residual lesions were detected in MRI of 10 patients. They were found in iodine-based images and monochromatic images versus 29 in conventional CT images. The area under ROC curves for the lesion-to-normal parenchyma ratio (LNR) on arterial phase (AP) in iodine-based material decomposition images, monochromatic images and conventional CT images were 0.933, 0.833 and 0.817, respectively. CONCLUSION: The study data highlighted good value of iodine-based material decomposition images of spectral CT in assessment of both lipiodol deposition and residual cancer for follow-up of HCC patients previously treated with TACE.

The effects of early versus delayed castration targeting androgen on prolonging survival in a mouse model of bladder cancer.

OBJECTIVE: To compare the efficacy of early versus delayed surgical castration on prolonging survival and further to investigate the anticancer effect and potential value of targeting androgen in the therapeutic intervention of bladder cancer. MATERIALS AND METHODS: N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) was used to induce bladder cancer in male mice. Mice were randomly divided into three groups: the early castration group (on which castration was perform at 4 weeks after first time of BBN administration), the delayed castration group (on which castration was perform at 20 weeks after first time of BBN administration), and the sham-castrated group. Mice were monitored daily throughout their lifespan until cancer-related death or the progress of an obviously moribund appearance, at which time the mice were killed. Androgen receptor expression and cell proliferation and apoptosis analysis were also evaluated. RESULTS: The average lifespan in early castration, delayed castration and sham-castrated groups were 315.8 days, 300.1 days and 254.6 days, respectively. Early castration conferred a statistically significant survival advantage when compared with the sham-castrated group (P < 0.05). However, the difference in the lifespan between the delayed castration group and the sham-castrated group was not statistically significant (P = 0.198). Both early and delayed castration significantly increased apoptosis of tumor cells when compared with the sham-castrated group (both P < 0.01), which was also accompanied by a significant decrease in cells proliferation (both P < 0.01). Prolonged survival of mice in early castration group was correlated with a lower G/B value (genitourinary tract weight/body weight) at death than the sham-castrated mice. CONCLUSION: Early castration had an overall survival benefit when compared with the sham-castrated treatment in BBN-induced bladder cancer mice. This finding may enhance the feasibility of androgen ablation treatment in patients with bladder cancer.

MRI for discriminating metastatic ovarian tumors from primary epithelial ovarian cancers.

AIMS: To find specific magnetic resonance imaging (MRI) features to differentiate metastatic ovarian tumors from primary epithelial ovarian cancers. METHODS: Eleven cases with metastatic ovarian tumors and 26 cases with primary malignant epithelial ovarian cancers were retrospectively studied. All features such as patient characteristics, MRI findings and biomarkers were evaluated. The differences including laterality, configuration, uniformity of locules, diffusion weighted imaging (DWI) signal of solid components and enhancement of solid portions between metastatic ovarian tumors and primary epithelial ovarian cancers were compared by Fisher's exact test. Median age of patients, the maximum diameter of lesions and biomarkers were compared by the Mann-Whitney test. RESULTS: Patients with metastatic ovarian tumors were younger than patients with primary epithelial ovarian cancers in the median age (P = 0.015). Patients with bilateral tumors in metastatic ovarian tumors were more than those of primary epithelial ovarian cancers (P = 0.032). The maximum diameter of lesions in metastatic ovarian tumors was smaller than that of primary epithelial ovarian cancers (P = 0.005). The locules in metastatic ovarian tumors were more uniform than those of primary epithelial ovarian cancers (P = 0.024). The enhancement of solid portions in metastatic ovarian tumors showed more moderate than that of primary epithelial ovarian cancers (P = 0.037). There was no statistically significant difference between the two groups in configuration, DWI signal of solid components and ascites. Biomarkers such as CA125 and human epididymis protein 4 (HE4) in metastatic ovarian tumors showed less elevated than that of primary epithelial ovarian cancers. CONCLUSIONS: Significant differences between metastatic ovarian tumors and primary epithelial ovarian cancers were found in the median age of patients, laterality, the maximum diameter of lesions, uniformity of locules, enhancement patterns of solid portions and biomarkers. Metastatic ovarian tumors usually presented in the younger patients, smaller-sized, more bilateral lesions, more uniform of locules, more moderate enhancement of solid portions, and less elevated levels of CA125 and HE4 than those of primary epithelial ovarian cancers.

Assessment and classification of cystic arteries with 64-detector row computed tomography before laparoscopic cholecystectomy.

PURPOSE: Major complications of laparoscopic cholecystectomy are bleeding and bile duct injury, and it is necessary to clearly identify structures endoscopically to keep bleeding and injury from occurring. The aim of this study was to depict the anatomical variation between cystic arteries among patients using 64-detector row spiral computed tomography (CT) prior to laparoscopic cholecystectomy. METHODS: A total of 78 patients (31 men, 47 women) who underwent cholecystectomy were examined preoperatively using 64-detector row spiral CT between April 2012 and June 2013. The origin and number of cystic arteries and their relationship with the Calot triangle was evaluated by two independent observers. CT images were compared with laparoscopic cholecystectomy results. RESULTS: The cystic arteries were delineated by CT in 73 of the 78 patients. The relationship between the cystic arteries and the Calot triangle was identified in 71 of the 78 patients. One cystic artery was found in 53 (73%) of the 73 patients, while two cystic arteries were found in 20 (27%) of the patients. A total of 55 (60%) of the 91 cystic arteries passed through the Calot triangle. The remaining 36 cystic arteries (40%) passed anterior, posterior, or inferior to the cystic duct. The relationship between the cystic arteries and the Calot triangle detected by CT was in agreement with the surgical records for all patients. CONCLUSION: The configuration of the cystic arteries and their relationship with the Calot triangle can be identified using 64-detector row CT before laparoscopic cholecystectomy.

Conjugation of iron oxide nanoparticles with RGD-modified dendrimers for targeted tumor MR imaging.

This article reports a new approach for the synthesis of ultrasmall iron oxide nanoparticles (NPs) conjugated with Arg-Gly-Asp (RGD)-modified dendrimers (G5.NHAc-RGD-Fe3O4 NPs) as a platform for targeted magnetic resonance (MR) imaging of C6 glioma cells. Ultrasmall Fe3O4 NPs synthesized via a solvothermal route were conjugated with RGD peptide-modified generation-5 poly(amidoamine) dendrimers (G5.NH2-RGD). The final G5.NHAc-RGD-Fe3O4 NPs were formed following the acetylation of the remaining dendrimer terminal amines. The as-prepared multifunctional Fe3O4 NPs were characterized using various techniques. The results of a cell viability assay, cell morphological observation, and hemolysis assay indicated that the G5.NHAc-RGD-Fe3O4 NPs exhibit excellent cytocompatibility and hemocompatibility over the studied concentration range. In addition, RGD conjugated onto the Fe3O4 NPs allows for the efficient targeting of the particles to C6 cells that overexpress αvß3 receptors, which was confirmed via in vitro cell MR imaging and cellular uptake. Finally, the G5.NHAc-RGD-Fe3O4 NPs were used in the targeted MR imaging of C6 glioma cells in mice. The results obtained from the current study indicate that the developed G5.NHAc-RGD-Fe3O4 NPs offer significant potential for use as contrast agents in the targeted MR imaging of different types of tumors.

The value of magnetic resonance imaging in the detection of prostate cancer in patients with previous negative biopsies and elevated prostate-specific antigen levels: a meta-analysis.

RATIONALE AND OBJECTIVES: To assess the diagnostic performance of magnetic resonance imaging (MRI) for targeting prostate cancer in patients with previous negative biopsies and elevated prostate-specific antigen (PSA) levels. MATERIALS AND METHODS: Pubmed, Scopus, and Cochrane Library databases were searched to identify suitable studies published from January 2001 to October 2013. Polled estimation and subgroup analysis data were obtained using a random effect model. Summary receiver operating characteristic curves were used to summarize overall test performance. RESULTS: Fourteen studies involving 698 patients met the included criteria. The mean prostate cancer detection rate was 37.5%. Twelve studies had a pooled sensitivity, specificity, and diagnostic odds ratio (DOR) of 88%, 69%, and 16.84 by patient analysis, respectively. In the subgroup analysis, magnetic resonance imaging spectroscopy (MRSI) provided higher pooled sensitivity (91%) and specificity (69%) compared with T2-weighted imaging (T2WI). MRSI combined with MRI had the highest pooled specificity (73%). By site analysis, the pooled sensitivity, specificity, and DOR in nine studies were 57%, 90%, and 14.34, respectively. In the subgroup analysis, MRSI combined with MRI showed higher pooled sensitivity (58%) and specificity (93%) compared with T2WI. Diffusion-weighted MRI (DWI) showed the highest pooled specificity: 95% but the lowest pooled sensitivity: 38%. CONCLUSIONS: A limited number of studies suggest that the value of MRI to target prostate cancer in patients with previous negative biopsies and elevated PSA levels appears significant. MRI combined with MRSI is particularly accurate. Further studies are necessary to confirm the eventual role of DWI in this field.

Early and delayed castrations confer a similar survival advantage in TRAMP mice.

The most appropriate time to introduce androgen deprivation therapy for prostate cancer remains controversial. Our aim was to evaluate the effects of early versus delayed surgical castration on prostate cancer progression and survival in the transgenic adenocarcinoma of the mouse prostate (TRAMP) model. TRAMP mice were randomly divided into three groups: the early castration group (on which castration was performed at the age of 4 weeks), the delayed castration group (on which castration was performed when abdominal tumours could be palpated), and the sham-castrated group. Mice were monitored daily throughout their lives until cancer-related death or the development of an obviously moribund appearance, at which time the individual mouse was killed. Androgen receptor expression in prostate tumours was also evaluated. The results shows that the average lifespan in early castration, delayed castration and sham-castrated groups were 54.1 weeks, 59.9 weeks and 39.1 weeks, respectively. Both early castration and delayed castration conferred a statistically significant survival advantage when compared with the sham-castrated group (P<0.001). However, the difference in lifespan between the early castration group and the delayed castration group was not statistically significant (P=0.85). The increase in lifespan in the TRAMP mice that received either early or delayed castration correlated with lower G/B value (genitourinary tract weight/body weight) at death than the sham-castrated mice. In conclusion, early and delayed castrations in TRAMP mice prolonged survival to a similar extent. This finding may provide a guide for clinical practice in prostate cancer therapy.

[Prostatic abscess: a report of 2 cases and meta-analysis of domestic literature in recent 10 years].

OBJECTIVE: To report 2 cases of prostatic abscess and review the current characteristics of prostatic abscess in China. METHODS: Two cases of prostatic abscess were reported, and a meta-analysis was made of the literature from the Chinese National Knowledge Infrastructure database and Wanfang Data in recent 10 years. RESULTS: Both the cases had a high glucose level, and one of them had received instrumental examination of the lower urinary tract prior to the problem, both with difficult defecation, severe perineal pain and high fever, with normal peripheral white blood cell count and negative urine routine. One case of abscess was confirmed by MRI, ruptured into urethra and cured by antibiotics. The other case was confirmed by transrectal ultrasound and CT and cured by transrectal ultrasound guided needle aspiration. Meta-analysis showed that the predisposed factors were diabetes mellitus, the indwelling catheter and instrumentation of the lower urinary tract. Major pathogens were staphylococci aureus and Escherichia coli. For most patients, the diagnosis was mainly established by ultrasonography and the treatment included needle aspiration or surgery. CONCLUSION: The clinical symptoms of prostatic abscess are not typically presented and the differential diagnosis may be difficult. Imaging investigation is helpful, and transrectal ultrasonography can be used for both diagnosis and treatment.