Identification of triple-negative breast cancer and androgen receptor expression based on histogram and texture analysis of dynamic contrast-enhanced MRI.

BACKGROUND: Triple-negative breast cancer (TNBC) is highly malignant and has a poor prognosis due to the lack of effective therapeutic targets. Androgen receptor (AR) has been investigated as a possible therapeutic target. This study quantitatively assessed intratumor heterogeneity by histogram analysis of pharmacokinetic parameters and texture analysis on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to discriminate TNBC from non-triple-negative breast cancer (non-TNBC) and to identify AR expression in TNBC. METHODS: This retrospective study included 99 patients with histopathologically proven breast cancer (TNBC: 36, non-TNBC: 63) who underwent breast DCE-MRI before surgery. The pharmacokinetic parameters of DCE-MRI (Ktrans, Kep and Ve) and their corresponding texture parameters were calculated. The independent t-test, or Mann-Whitney U-test was used to compare quantitative parameters between TNBC and non-TNBC groups, and AR-positive (AR+) and AR-negative (AR-) TNBC groups. The parameters with significant difference between two groups were further involved in logistic regression analysis to build a prediction model for TNBC. The ROC analysis was conducted on each independent parameter and the TNBC predicting model for evaluating the discrimination performance. The area under the ROC curve (AUC), sensitivity and specificity were derived. RESULTS: The binary logistic regression analysis revealed that Kep_Range (p = 0.032) and Ve_SumVariance (p = 0.005) were significantly higher in TNBC than in non-TNBC. The AUC of the combined model for identifying TNBC was 0.735 (p < 0.001) with a cut-off value of 0.268, and its sensitivity and specificity were 88.89% and 52.38%, respectively. The value of Kep_Compactness2 (p = 0.049), Kep_SphericalDisproportion (p = 0.049), and Ve_GlcmEntropy (p = 0.008) were higher in AR + TNBC group than in AR-TNBC group. CONCLUSION: Histogram and texture analysis of breast lesions on DCE-MRI showed potential to identify TNBC, and the specific features can be possible predictors of AR expression, enhancing the ability to individualize the treatment of patients with TNBC.

Application of computed tomography-based radiomics in differential diagnosis of adenocarcinoma and squamous cell carcinoma at the esophagogastric junction.

BACKGROUND: The biological behavior of carcinoma of the esophagogastric junction (CEGJ) is different from that of gastric or esophageal cancer. Differentiating squamous cell carcinoma of the esophagogastric junction (SCCEG) from adenocarcinoma of the esophagogastric junction (AEG) can indicate Siewert stage and whether the surgical route for patients with CEGJ is transthoracic or transabdominal, as well as aid in determining the extent of lymph node dissection. With the development of neoadjuvant therapy, preoperative determination of pathological type can help in the selection of neoadjuvant radiotherapy and chemotherapy regimens. AIM: To establish and evaluate computed tomography (CT)-based multiscale and multiphase radiomics models to distinguish SCCEG and AEG preoperatively. METHODS: We retrospectively analyzed the preoperative contrasted-enhanced CT imaging data of single-center patients with pathologically confirmed SCCEG (n = 130) and AEG (n = 130). The data were divided into either a training (n = 182) or a test group (n = 78) at a ratio of 7:3. A total of 1409 radiomics features were separately extracted from two dimensional (2D) or three dimensional (3D) regions of interest in arterial and venous phases. Intra-/inter-observer consistency analysis, correlation analysis, univariate analysis, least absolute shrinkage and selection operator regression, and backward stepwise logical regression were applied for feature selection. Totally, six logistic regression models were established based on 2D and 3D multi-phase features. The receiver operating characteristic curve analysis, the continuous net reclassification improvement (NRI), and the integrated discrimination improvement (IDI) were used for assessing model discrimination performance. Calibration and decision curves were used to assess the calibration and clinical usefulness of the model, respectively. RESULTS: The 2D-venous model (5 features, AUC: 0.849) performed better than 2D-arterial (5 features, AUC: 0.808). The 2D-arterial-venous combined model could further enhance the performance (AUC: 0.869). The 3D-venous model (7 features, AUC: 0.877) performed better than 3D-arterial (10 features, AUC: 0.876). And the 3D-arterial-venous combined model (AUC: 0.904) outperformed other single-phase-based models. The venous model showed a positive improvement compared with the arterial model (NRI > 0, IDI > 0), and the 3D-venous and combined models showed a significant positive improvement compared with the 2D-venous and combined models (P < 0.05). Decision curve analysis showed that combined 3D-arterial-venous model and 3D-venous model had a higher net clinical benefit within the same threshold probability range in the test group. CONCLUSION: The combined arterial-venous CT radiomics model based on 3D segmentation can improve the performance in differentiating EGJ squamous cell carcinoma from adenocarcinoma.

Bi-specific T1 positive-contrast-enhanced magnetic resonance imaging molecular probe for hepatocellular carcinoma in an orthotopic mouse model.

BACKGROUND: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality. HCC-targeted magnetic resonance imaging (MRI) is an effective noninvasive diagnostic method that involves targeting clinically-related HCC biomarkers, such as alpha-fetoprotein (AFP) or glypican-3 (GPC3), with iron oxide nanoparticles. However, in vivo studies of HCC-targeted MRI utilize single-target iron oxide nanoprobes as negative (T2) contrast agents, which might weaken their future clinical applications due to tumor heterogeneity and negative MRI contrast. Ultra-small superparamagnetic iron oxide (USPIO) nanoparticles (approximately 5 nm) are potential optimal positive (T1) contrast agents. We previously verified the efficiency of AFP/GPC3-double-antibody-labeled iron oxide MR molecular probe in vitro. AIM: To validate the effectiveness of a bi-specific probe in vivo for enhancing T1-weighted positive contrast to diagnose the early-stage HCC. METHODS: The single- and double-antibody-conjugated 5-nm USPIO probes, including anti-AFP-USPIO (UA), anti-GPC3-USPIO (UG), and anti-AFP-USPIO-anti-GPC3 (UAG), were synthesized. T1- and T2-weighted MRI were performed on day 10 after establishment of the orthotopic HCC mouse model. Following intravenous injection of U, UA, UG, and UAG probes, T1- and T2-weighted images were obtained at 12, 12, and 32 h post-injection. At the end of scanning, mice were euthanized, and a histologic analysis was performed on tumor samples. RESULTS: T1- and T2-weighted MRI showed that absolute tumor-to-background ratios in UAG-treated HCC mice peaked at 24 h post-injection, with the T1- and T2-weighted signals increasing by 46.7% and decreasing by 11.1%, respectively, relative to pre-injection levels. Additionally, T1-weighted contrast in the UAG-treated group at 24 h post-injection was enhanced 1.52-, 2.64-, and 4.38-fold compared to those observed for single-targeted anti-GPC3-USPIO, anti-AFP-USPIO, and non-targeted USPIO probes, respectively. Comparison of U-, UA-, UG-, and UAG-treated tumor sections revealed that UAG-treated mice exhibited increased stained regions compared to those observed in UG- or UA-treated mice. CONCLUSION: The bi-specific T1-positive contrast-enhanced MRI probe (UAG) for HCC demonstrated increased specificity and sensitivity to diagnose early-stage HCC irrespective of tumor size and/or heterogeneity.

The application of apparent diffusion coefficients derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer.

OBJECTIVE: To investigate the diagnostic performance of the apparent diffusion coefficient (ADC) derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer. MATERIALS AND METHODS: One hundred forty-six patients with rectal cancer who underwent preoperative MRI were prospectively enrolled. Two radiologists independently placed free-hand regions of interest (ROIs) in the largest tumor cross section and three small ROIs on the peritumoral zone adjacent to the tumor contour. Maximum values of tumor ADC (ADCtmax), minimum values of tumor ADC (ADCtmin), mean values of tumor ADC (ADCtmean), mean values of peritumor ADC (ADCpmean), and ADCpmean/ADCtmean (ADC ratio) were obtained on ADC maps and correlated with prognostic factors using uni- and multivariate logistic regression, and receiver operating characteristic curve (ROC) analysis. RESULTS: Interobserver agreement was excellent for ADCtmax and ADCtmean (intraclass correlation coefficient [ICC], 0.915-0.958), and were good for ADCtmin, ADCpmean, and ADC ratio (ICC, 0.774-0.878). The ADC ratio was significantly higher in the poor differentiation, T3-4 stage, lymph node metastasis (LNM)-positive, extranodal extension (ENE)-positive, tumor deposit (TD)-positive, and lymphovascular invasion (LVI)-positive groups than that in the well-moderate differentiation, T1-2 stage, LNM-negative, ENE-negative, TD-negative, and LVI-negative groups (p = 0.008, < 0.001, < 0.001, 0.001, < 0.001, and < 0.001, respectively). The area under the ROC curve (AUC) of the ADC ratio was the highest for assessing poor differentiation (0.700), T3-4 stage (0.707), LNM-positive (0.776), TD-positive (0.848), and LVI-positive (0.778). Both the ADC ratio (AUC = 0.677) and ADCpmean (AUC = 0.686) showed higher diagnostic performance for assessing ENE. CONCLUSION: The ADC ratio could provide better predictive performance for assessing preoperative prognostic factors in resectable rectal cancer. KEY POINTS: • Both the peritumor/tumor ADC ratio and ADCpmean are correlated with important prognostic factors of resectable rectal cancer. • Both peritumor ADC and peritumor/tumor ADC ratio had higher diagnostic performance than tumor ADC for assessment of prognostic factors in resectable rectal cancer. • Peritumor/tumor ADC ratio showed the most capability for the assessment of prognostic factors in resectable rectal cancer.

Development and Validation of Noninvasive MRI-Based Signature for Preoperative Prediction of Early Recurrence in Perihilar Cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma is a type of hepatobiliary tumor. For perihilar cholangiocarcinoma (pCCA), patients who experience early recurrence (ER) have a poor prognosis. Preoperative accurate prediction of postoperative ER can avoid unnecessary operation; however, prediction is challenging. PURPOSE: To develop a novel signature based on clinical and/or MRI radiomics features of pCCA to preoperatively predict ER. STUDY TYPE: Retrospective. POPULATION: One hundred eighty-four patients (median age, 61.0 years; interquartile range: 53.0-66.8 years) including 115 men and 69 women. FIELD STRENGTH/SEQUENCE: A 1.5 T; volumetric interpolated breath-hold examination (VIBE) sequence. ASSESSMENT: The models were developed from the training set (128 patients) and validated in a separate testing set (56 patients). The contrast-enhanced arterial and portal vein phase MR images of hepatobiliary system were used for extracting radiomics features. The correlation analysis, least absolute shrinkage and selection operator (LASSO) logistic regression (LR), backward stepwise LR were mainly used for radiomics feature selection and modeling (Modelradiomic ). The univariate and multivariate backward stepwise LR were used for preoperative clinical predictors selection and modeling (Modelclinic ). The radiomics and preoperative clinical predictors were combined by multivariate LR method to construct clinic-radiomics nomogram (Modelcombine ). STATISTICAL TESTS: Chi-squared (χ2 ) test or Fisher's exact test, Mann-Whitney U-test or t-test, Delong test. Two tailed P < 0.05 was considered statistically significant. RESULTS: Based on the comparison of area under the curves (AUC) using Delong test, Modelclinic and Modelcombine had significantly better performance than Modelradiomic and tumor-node-metastasis (TNM) system in training set. In the testing set, both Modelclinic and Modelcombine had significantly better performance than TNM system, whereas only Modelcombine was significantly superior to Modelradiomic . However, the AUC values were not significantly different between Modelclinic and Modelcombine (P = 0.156 for training set and P = 0.439 for testing set). DATA CONCLUSION: A noninvasive model combining the MRI-based radiomics signature and clinical variables is potential to preoperatively predict ER for pCCA. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 4.

Value of intravoxel incoherent motion for assessment of lymph node status and tumor response after chemoradiation therapy in locally advanced rectal cancer.

OBJECTIVE: To assess the role of region of interest (ROI) selection of intravoxel incoherent motion (IVIM) for predicting lymph node metastases (LNM) and tumor response after chemoradiation therapy (CRT) in locally advanced rectal cancer. MATERIALS AND METHODS: Seventy-nine patients with biopsy-proven rectal adenocarcinoma who underwent pre- and post-CRT MRI and surgery were prospectively enrolled. The exclusion criteria included nonresectable and/or metastatic disease and loss of follow-up. Pathological stage was determined using ypTNM stage and tumor regression grade. Slow diffusion coefficient (D), fast diffusion coefficient (D*), perfusion-related diffusion fraction (f), apparent diffusion coefficient (ADC) and their percentage changes (Δ%) were evaluated by two readers using whole-volume, single-slice and small samples ROI methods. Risk factors including carcinoembryonic antigen, post-CRT T-staging, extramural venous invasion and IVIM parameters were evaluated through multivariate analyses. Areas under the receiver operating characteristic curves (AUCs) were calculated to evaluate diagnostic performance. Duration of follow-up was two-year. Recurrence-free survival of patients with LNM and tumor response was estimated using Kaplan-Meier analysis. RESULTS: Interobserver agreement were good for pre- and post-CRT three ROI methods (intraclass correlation coefficient [ICC], 0.581-0.953). Whole-volume ROI-derived Δ%D was an independent risk factor for LNM, non-pathological complete response (non-pCR) and poor response (odds ratio, 0.940, 0.952, 0.805, respectively; all p < 0.001). Whole-volume ROI-derived Δ%D showed best AUC of 0.810, 0.851 and 0.903 for LNM, non-pCR and poor response (cutoff value, 31.8%, 54.5%, 52.8%, respectively). Patients with post-CRT LNM showed reduction in 2-year recurrence-free survival (hazard ratio, 3.253). CONCLUSIONS: Whole-volume ROI-derived Δ%D provided high diagnostic performance for evaluating post-CRT LNM and tumor response. Patients with post-CRT LNM showed earlier recurrence.

Development of CT-Based Imaging Signature for Preoperative Prediction of Invasive Behavior in Pancreatic Solid Pseudopapillary Neoplasm.

PURPOSE: It is challenging for traditional CT signs to predict invasiveness of pancreatic solid pseudopapillary neoplasm (pSPN). We aim to develop and evaluate CT-based radiomics signature to preoperatively predict invasive behavior in pSPN. METHODS: Eighty-five patients who had pathologically confirmed pSPN and preoperative contrasted-enhanced CT imaging in our hospital were retrospectively analyzed (invasive: 24; non-invasive: 61). 1316 radiomics features were separately extracted from delineated 2D or 3D ROIs in arterial and venous phases. 200% (SMOTE) was used to generate balanced dataset (invasive: 72, non-invasive: 96) for each phase, which was for feature selection and modeling. The model was internally validated in the original dataset. Inter-observer consistency analysis, spearman correlation, univariate analysis, LASSO regression and backward stepwise logical regression were mainly applied to screen the features, and 6 logistic regression models were established based on multi-phase features from 2D or 3D segmentations. The ROC analysis and Delong's test were mainly used for model assessment and AUC comparison. RESULTS: It retained 11, 8, 7 and 7 features to construct 3D-arterial, 3D-venous, 2D-arterial and 2D-venous model. Based on 3D ROIs, the arterial model (AUC: 0.914) performed better than venous (AUC: 0.815) and the arterial-venous combined model was slightly improved (AUC: 0.918). Based on 2D ROIs, the arterial model (AUC: 0.814) performed better than venous (AUC:0.768), while the arterial-venous combined model (AUC:0.893) performed better than any single-phase model. In addition, the 3D arterial model performed better than the best combined 2D model. The Delong's test showed that the significant difference of model AUC existed in arterial models in original dataset (p = 0.019) while not in arterial-venous combined model (p=0.49) as comparing 2D and 3D ROIs. CONCLUSION: The arterial radiomics model constructed by 3D-ROI feature is potential to predict the invasiveness of pSPN preoperatively.

External validation study of the 8th edition of the American Joint Committee on Cancer staging system for perihilar cholangiocarcinoma: a single-center experience in China and proposal for simplification.

BACKGROUND: Several changes have been made to the primary tumor (T) and lymph node (N) categories in the new 8th edition of the American Joint Committee on Cancer (AJCC) staging system for perihilar cholangiocarcinoma (pCCA). This study was conducted to validate the 8th edition of the AJCC staging system for pCCA in China. METHODS: A total of 335 patients who underwent curative-intent resection for pCCA between January 2010 and December 2018 were retrospectively enrolled. The overall survival (OS) of groups of patients was calculated using the Kaplan-Meier method. The log-rank test was used to compare OS between groups. The concordance index (C-index), Akaike information criteria (AIC), and time-dependent area under receiver operating characteristic (ROC) curve (AUC) were computed to evaluate the discriminatory power of the 8th and 7th editions of the AJCC staging system. RESULTS: The T category changed in 25 (7.5%) patients, the N category changed in 39 (11.6%) patients, and the tumor-node-metastasis (TNM) stage changed in 157 (46.9%) patients when the 8th and 7th editions were compared. No statistically significant difference in survival was observed between T2aN0M0 and T2bN0M0. The C-index of the 8th edition was 0.609 [95% confidence interval (CI): 0.568-0.650], which was slightly higher than that of the 7th edition (C-index, 0.599, 95% CI: 0.558-0.640). The time-dependent AUC value also corroborated that the 8th edition had a better performance than the 7th edition. CONCLUSIONS: The 8th edition of the AJCC staging system for pCCA showed a better ability than the 7th edition to discriminate patient survival. However, further simplification of the 8th edition is still needed.

Development of unenhanced CT-based imaging signature for BAP1 mutation status prediction in malignant pleural mesothelioma: Consideration of 2D and 3D segmentation.

OBJECTIVES: We aimed to explore the feasibility of 2D and 3D radiomics signature based on the unenhanced computed tomography (CT) images to predict BRCA1-associated protein 1 (BAP1) gene mutation status for malignant pleural mesothelioma (MPM) patients. MATERIALS AND METHODS: 74 patients with MPM were retrospectively enrolled (22 mutant BAP1, 52 wild-type BAP1 demonstrated by Sanger sequencing). The radiomic features were extracted respectively from the 2D and 3D segmentation of unenhanced pre-treatment CT images, and the dataset was randomly divided into training (n = 51) and test (n = 23) sets for radiomics model development and internal validation. The synthetic minority over-sampling technique (SMOTE) was used for data balancing in the training set. 2D or 3D features were sequentially selected by ICC > 0.8, correlation analysis (cut-value 0.7), univariate analysis or univariate logistic regression (LR), which were involved into multivariate LR for LR model construction. Following the comparison of the 2D and 3D models by the ROC analysis and Delong test for AUC, the calibration and clinical utility of 2D and 3D models were evaluated. RESULTS: 3D radiomic features showed better ICCs compared with 2D in both intra- (P < 0.001) and inter-observer (P < 0.001) analysis. 3D radiomic model based on selected features developed from a balanced training dataset presented a favorable predictive performance with AUC of 0.786 and 0.768 in the training and test sets, respectively. The predictive performance of 3D model was superior to 2D model (1 feature) both in the training (AUC 0.786 vs. 0.683, P = 0.036) and the test (AUC 0.768 vs.0.652, P = 0.441) set. The calibration curve and decision curves also indicate a better BAP1 prediction performance and clinical benefit for 3D model than that of 2D model. CONCLUSION: The developed unenhanced CT-based 3D radiomics signature is potential as a noninvasive marker for predicting BAP1 mutation status.

Development and validation of preoperative magnetic resonance imaging-based survival predictive nomograms for patients with perihilar cholangiocarcinoma after radical resection: A pilot study.

PURPOSE: We aim to develop survival predictive tools to inform clinical decision-making in perihilar cholangiocarcinoma (pCCA). MATERIALS AND METHODS: A total of 184 patients who had curative resection and magnetic resonance imaging (MRI) examination for pCCA between January 2010 and December 2018 were enrolled. 110 patients were randomly selected for model development, while the other 74 patients for model testing. Preoperative clinical, laboratory, and imaging data were analyzed. Preoperative clinical predictors were used independently or integrated with radiomics signatures to construct different preoperative models through the multivariable Cox proportional hazards method. The nomograms were constructed to predict overall survival (OS), and the performance of which was evaluated by the discrimination ability, time-dependent receiver operating characteristic curve (ROC), calibration curve, and decision curve. RESULTS: The clinical model (Modelclinic) was constructed based on three independent variables including preoperative CEA, cN stage, and invasion of hepatic artery in images. The model yield the best performance (Modelclinic&AP&PVP) was build using three independent variables, SignatureAP and SignaturePVP. In training and testing cohorts, the concordance indexes (C-indexes) of Modelclinic were 0.846 (95 % CI, 0.735-0.957) and 0.755 (95 % CI, 0.540-969), and Modelclinic&AP&PVP achieved C-indexes of 0.962 (95 % CI, 0.905-1) and 0.814 (95 % CI, 0.569-1). Both Modelclinic and Modelclinic&AP&PVP outperformed the TNM staging system. Good agreement was observed in the calibration curves, and favorable clinical utility was validated using the decision curve analysis for Modelclinic and Modelclinic&AP&PVP. CONCLUSION: Two preoperative nomograms were constructed to predict 1-, 3-, and 5-years survival for individual pCCA patients, demonstrating the potential for clinical application to assist decision-making.

Independent Risk Factors of Early Recurrence After Curative Resection for Perihilar Cholangiocarcinoma: Adjuvant Chemotherapy May Be Beneficial in Early Recurrence Subgroup.

PURPOSE: In current clinical practice, early recurrence (ER) is not commonly discussed in perihilar cholangiocarcinoma (pCCA), and its risk factors for this disease have not been well clarified. We carried out this study to analyze the risk factors contributing to ER and explored the prognostic factors after curative resection for pCCA. PATIENTS AND METHODS: A total of 335 consecutive pCCA patients were retrospectively analyzed. Risk factors contributing to ER were evaluated using univariate and multivariate logistic regression analyses. Prognostic factors of the ER group were determined by univariate and multivariate Cox regression models. The overall survival (OS) rate was calculated using the Kaplan-Meier method. The Log rank test was used for OS comparison. RESULTS: Of the 335 cases, 258 patients (77.0%) developed tumor recurrence, 136 patients (40.6%) developed ER, and 122 patients (36.4%) developed late recurrence (LR) postoperatively. The median OS of the ER and LR groups was 15 months and 36 months, respectively (P<0.001). The multivariate analysis revealed that poor pathological differentiation (P=0.006; moderate vs well, odds ratio [OR]=2.162, 95% confidence interval [CI] 0.753-6.208, P=0.152; poor vs well, OR=4.839, 95% CI 1.544-15.170, P=0.007), perineural invasion (OR=4.797, 95% CI 1.586-14.510, P=0.005), and high levels of preoperative carbohydrate antigen 19-9 (CA19-9) (OR=2.205, 95% CI 1.208-4.026, P=0.010) were independent risk factors of developing ER after resection. Adjuvant chemotherapy (HR=0.383, 95% CI 0.154-0.953, P=0.039) remained as the independent protective factor of OS in patients with ER. CONCLUSION: It is recommended that patients with poorly differentiated tumors, presence of perineural invasion, and high levels of preoperative CA19-9 receive closer follow-up and adjuvant chemotherapy following surgery.

Current and Potential Applications of Artificial Intelligence in Gastrointestinal Stromal Tumor Imaging.

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastrointestinal system. Imaging methods are important and indispensable of GISTs in diagnosis, risk staging, therapy, and follow-up. The recommended imaging method for staging and follow-up is computed tomography (CT) according to current guidelines. Artificial intelligence (AI) applies and elaborates theses, procedures, modes, and utilization systems for simulating, enlarging, and stretching the intellectual capacity of humans. Recently, researchers have done a few studies to explore AI applications in GIST imaging. This article reviews the present AI studies in GISTs imaging, including preoperative diagnosis, risk stratification and prediction of prognosis, gene mutation, and targeted therapy response.

Survival analysis of patients with stage T2a and T2b perihilar cholangiocarcinoma treated with radical resection.

BACKGROUND: Both the 7th and 8th editions of the American Joint Committee on Cancer (AJCC) staging system for perihilar cholangiocarcinoma (pCCA) had the same definition for T2a and T2b. But the value of this classification as prognostic factor remains unclear. METHODS: 178 patients with stage T2a or T2b who underwent curative intent resection for pCCA between Jan 2010 and Dec 2018 were enrolled. Relationships between survival and clinicopathological factors including patient demographics and tumor characteristics were evaluated using univariate and multivariate Cox regression analysis. The overall survival (OS) were calculated by Kaplan-Meier method. RESULTS: There was no significant difference in OS between T2a and T2b groups, and the median OS duration were 37 and 31 months (P = 0.354). Both the 7th and 8th edition of the AJCC TNM staging demonstrated a poor prognostic predictive performance. High level of preoperative AST (≥85.0 IU/L) and CA19-9 (≥1000 U/mL), vascular resection and lower pathological differentiation of the tumor were the independent predictors for poor survival after resection. CONCLUSION: The newly released 8th edition of AJCC staging system demonstrated a poor ability to discriminate the prognosis of patients with stage T2a and T2b pCCA after resection.

Development and in vitro study of a bi-specific magnetic resonance imaging molecular probe for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) ranks second in terms of cancer mortality worldwide. Molecular magnetic resonance imaging (MRI) targeting HCC biomarkers such as alpha-fetoprotein (AFP) or glypican-3 (GPC3) offers new strategies to enhance specificity and help early diagnosis of HCC. However, the existing iron oxide nanoparticle-based MR molecular probes singly target AFP or GPC3, which may hinder their efficiency to detect heterogeneous micro malignant HCC tumors < 1 cm (MHCC). We hypothesized that the strategy of double antibody-conjugated iron oxide nanoparticles which simultaneously target AFP and GPC3 antigens may potentially be used to overcome the tumor heterogeneity and enhance the detection rate for MRI-based MHCC diagnosis. AIM: To synthesize an AFP/GPC3 double antibody-labeled iron oxide MRI molecular probe and to assess its impact on MRI specificity and sensitivity at the cellular level. METHODS: A double antigen-targeted MRI probe for MHCC anti-AFP-USPIO-anti-GPC3 (UAG) was developed by simultaneously conjugating AFP andGPC3 antibodies to a 5 nm ultra-small superparamagnetic iron oxide nanoparticle (USPIO). At the same time, the singly labeled probes of anti-AFP-USPIO (UA) and anti-GPC3-USPIO (UG) and non-targeted USPIO (U) were also prepared for comparison. The physical characterization including morphology (transmission electron microscopy), hydrodynamic size, and zeta potential (dynamic light scattering) was conducted for each of the probes. The antigen targeting and MRI ability for these four kinds of USPIO probes were studied in the GPC3-expressing murine hepatoma cell line Hepa1-6/GPC3. First, AFP and GPC3 antigen expression in Hepa1-6/GPC3 cells was confirmed by flow cytometry and immunocytochemistry. Then, the cellular uptake of USPIO probes was investigated by Prussian blue staining assay and in vitro MRI (T2-weighted and T2-map) with a 3.0 Tesla clinical MR scanner. RESULTS: Our data showed that the double antibody-conjugated probe UAG had the best specificity in targeting Hepa1-6/GPC3 cells expressing AFP and GPC3 antigens compared with single antibody-conjugated and unconjugated USPIO probes. The iron Prussian blue staining and quantitative T2-map MRI analysis showed that, compared with UA, UG, and U, the uptake of double antigen-targeted UAG probe demonstrated a 23.3% (vs UA), 15.4% (vs UG), and 57.3% (vs U) increased Prussian stained cell percentage and a 14.93% (vs UA), 9.38% (vs UG), and 15.3% (vs U) reduction of T2 relaxation time, respectively. Such bi-specific probe might have the potential to overcome tumor heterogeneity. Meanwhile, the coupling of two antibodies did not influence the magnetic performance of USPIO, and the relatively small hydrodynamic size (59.60 ± 1.87 nm) of double antibody-conjugated USPIO probe makes it a viable candidate for use in MHCC MRI in vivo, as they are slowly phagocytosed by macrophages. CONCLUSION: The bi-specific probe presents enhanced targeting efficiency and MRI sensitivity to HCC cells than singly- or non-targeted USPIO, paving the way for in vivo translation to further evaluate its clinical potential.

Association between GNB3 c.825C > T polymorphism and the risk of overweight and obesity: A meta-analysis.

BACKGROUND: The association between G protein ß-polypeptide 3 gene (GNB3) c.825C > T polymorphism (rs5443) and the risk of overweight/obesity has been investigated in many published studies, but the results were conflicting and inconclusive. A meta-analysis was performed to make a more accurate assessment of the relationship. METHODS: The PubMed, ProQuest Health & Medical Complete, Web of Science, Chinese Biomedical Medical databases (CBM), Chinese National Knowledge Infrastructure (CNKI), and Wan Fang databases were searched to identify eligible literatures. Pooled odds ratios (ORs) with the corresponding 95% confidence intervals (CIs) were used to assess the strength of association between GNB3 c.825C > T polymorphism and overweight/obesity. RESULTS: Eleven articles including 15 case-control studies with a total of 10,396 subjects (3171 cases of overweight/obesity and 7225 controls) were enrolled in the meta-analysis. The GNB3 c.825C > T was significantly associated with overweight/obesity under a recessive model (OR = 1.22, 95% CI: 1.04-1.44, P = 0.015). Moreover, the GNB3 825T allele was obviously associated with overweight alone in all inheritable models (P < 0.05) except in a recessive model (P = 0.084). In the stratification analysis by potential confounding variables, a significant association was observed between GNB3 c.825C > T polymorphism and overweight/obesity risk in males under an allelic model (P = 0.008), a homozygous model (P = 0.014), a recessive model (P = 0.005), and a dominant model (P = 0.049). And the results also showed that GNB3 c.825C > T polymorphism was significantly associated with overweight/obesity in subgroups of mean age less than 30 years, consistent with HWE, and high-quality studies (P = 0.027, P = 0.043, P = 0.040, respectively) under a recessive model, but not in other subgroups. Meta-regression also revealed that P value of HWE, publication year, and the quality scores of studies were the sources of heterogeneity in a recessive model and an allelic model. "Leave one out" sensitivity analyses indicated that the association was more significant after excluding some studies. The funnel plot and Egger's linear regression test and Begg's test revealed no apparent publication bias. CONCLUSION: This meta-analysis suggests that the presence of TT homozygote might be one of the genetic factors susceptible to overweight/obesity and that males or aged under 30 years increase the genetic susceptibility.

Controlled self-assembly of organic composite microdisks for efficient output coupling of whispering-gallery-mode lasers.

Flexible microdisk whispering-gallery-mode (WGM) resonators with high quality factors were achieved through the controlled assembly of organic materials with an emulsion-solvent-evaporation method. The high material compatibility of the assembled microdisks enabled us to realize low-threshold WGM lasers by doping with organic dyes as gain media. Furthermore, the emulsion-assisted self-assembly provided a strategy for the one-step fabrication of microwire-waveguide-connected microdisk heterostructures, which can be utilized for the efficient output of the isotropic WGM lasers from the coupled waveguides. We hope that these results will pave an avenue for the construction of new types of flexible WGM-based components for photonic integration.

Giant enhancement of second harmonic generation by engineering double plasmonic resonances at nanoscale.

We have investigated second harmonic generation (SHG) from Ag-coated LiNbO3(LN) core-shell nanocuboids and found that giant SHG can occur via deliberately designed double plasmonic resonances. By controlling the aspect ratio, we can tune fundamental wave (FW) and SHG signal to match the longitudinal and transverse plasmonic modes simultaneously, and achieve giant enhancement of SHG by 3 × 10(5) in comparison to a bare LN nanocuboid and by about one order of magnitude to the case adopting only single plasmonic resonance. The underlying key physics is that the double-resonance nanoparticle enables greatly enhanced trapping and harvesting of incident FW energy, efficient internal transfer of optical energy from FW to the SHG signal, and much improved power to transport the SHG energy from the nanoparticle to the far-field region. The proposed double-resonance nanostructure can serve as an efficient subwavelength coherent light source through SHG and enable flexible engineering of light-matter interaction at nanoscale.

Comparison study of gold nanohexapods, nanorods, and nanocages for photothermal cancer treatment.

Gold nanohexapods represent a novel class of optically tunable nanostructures consisting of an octahedral core and six arms grown on its vertices. By controlling the length of the arms, their localized surface plasmon resonance peaks could be tuned from the visible to the near-infrared region for deep penetration of light into soft tissues. Herein we compare the in vitro and in vivo capabilities of Au nanohexapods as photothermal transducers for theranostic applications by benchmarking against those of Au nanorods and nanocages. While all these Au nanostructures could absorb and convert near-infrared light into heat, Au nanohexapods exhibited the highest cellular uptake and the lowest cytotoxicity in vitro for both the as-prepared and PEGylated nanostructures. In vivo pharmacokinetic studies showed that the PEGylated Au nanohexapods had significant blood circulation and tumor accumulation in a mouse breast cancer model. Following photothermal treatment, substantial heat was produced in situ and the tumor metabolism was greatly reduced for all these Au nanostructures, as determined with (18)F-flourodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT). Combined together, we can conclude that Au nanohexapods are promising candidates for cancer theranostics in terms of both photothermal destruction and contrast-enhanced diagnosis.

Efficient surface plasmon amplification from gain-assisted gold nanorods.

We report on the efficient surface plasmon amplification by stimulated emission of radiation (spaser) from a gold nanorod coated with proper gain media. Numerical simulations show that the threshold of the nanorod-based spaser is nearly 1 order of magnitude lower than that of the core-shell nanosphere, which is verified by analysis with electrostatic theory. Furthermore, it is found that the nanorod-based nanosystem possesses unique optical properties such as wavelength tunability and polarization sensitivity.