Xiao-Ting Li

Application of contrast-enhanced ultrasound in the diagnosis of solid pancreatic lesions—A comparison of conventional ultrasound and contrast-enhanced CT

OBJECTIVE To explore the diagnostic value of contrast-enhanced ultrasound (CEUS) by comparison with conventional ultrasound (US) and contrast-enhanced CT (CECT) in solid pancreatic lesions. METHOD Ninety patients with solid pancreatic focal lesions were enrolled, including 36 cases of pancreatic carcinoma, 28 cases of pancreatitis, 6 cases of pancreatic neuroendocrine tumor, 12 cases of solid pseudopapillary tumor of the pancreas, 6 cases of pancreatic metastases, 1 case of cavernous hemolymphangioma and 1 case of lymphoma. US and CEUS were applied respectively for the diagnosis of a total of 90 cases of solid pancreatic lesions. The diagnostic results were scored on a 5-point scale. Results of CEUS were compared with CECT. RESULTS (1) 3-score cases (undetermined) diagnosed by CEUS were obviously fewer than that of US, while the number of 1-score (definitely benign) and 5-score (definitely malignant) cases diagnosed by CEUS was significantly more than that of US. There was a significant difference in the distribution of final scores using the two methods (p<0.001). The overall diagnostic accuracies of the 90 cases for CEUS and US were 83.33% and 44.44%, respectively, which indicated an obvious advantage for CEUS (p<0.001). (2) The diagnostic consistency among three ultrasound doctors: the kappa values calculated for US were 0.537, 0.444 and 0.525, compared with 0.748, 0.645 and 0.795 for CEUS. The interobserver agreement for CEUS was higher than that for US. (3) The sensitivity, specificity and accuracy of the diagnosis of pancreatic carcinoma with CEUS and CECT were 91.7% and 97.2%, 87.0% and 88.9%, and 88.9% and 92.2%, respectively, while for the diagnosis of pancreatitis, the corresponding indices were 82.1% and 67.9%, 91.9% and 100%, and 88.9% and 90%, respectively, showing no significant differences (p>0.05). CONCLUSION CEUS has obvious superiority over conventional US in the general diagnostic accuracy of solid pancreatic lesions and in the diagnostic consistency among doctors. The performances of CEUS are similar to that of CECT in the diagnosis of pancreatic carcinoma and focal pancreatitis.

Sandwich sign of Borrmann type 4 gastric cancer on diffusion-weighted magnetic resonance imaging

OBJECTIVE To assess the appearance of Borrmann type 4 (BT-4) gastric cancer on diffusion-weighted magnetic resonance imaging (DWI) and to investigate the potential of qualitative and quantitative DW images analysis to differentiate BT-4 gastric cancer from poorly distended normal stomach wall. MATERIALS AND METHODS DWI was performed on 23 patients with BT-4 gastric cancer and 23 healthy volunteers. The signal characteristics and correlated histopathological basis of the cancers on DWI were investigated. The contrast-to-noise ratios (CNR) of cancer were compared between DWI and T1WI/T2WI(.) The thickness and apparent diffusion coefficient (ADC) of cancer and normal stomach wall were compared. RESULTS All of the gastric cancers displayed hyperintensity compared to the nearby normal gastric wall on DWI. A three-layer sandwich sign that demonstrated high signal intensity in the inner and outer layer, and low signal intensity in the intermediate layer was observed in 69.6% of cancers on DWI. The low signal intensity represents the muscularis propria through the comparison with pathology, and it is postulated that scattering distribution of the cancer cells in this layer causes less damage and subsequently less restriction of water movement, which causes the low signal intensity on DWI. The CNR obtained with DWI was higher than that with T1WI and T2WI (P<0.001). The mean ADC value of BT-4 gastric cancer was significantly lower than the poorly distended normal stomach wall (1.12 ± 0.23 × 10(-3)mm(2)/s vs. 1.9 3 ± 0.22 × 10(-3)mm(2)/s, P<0.01). CONCLUSION DWI can highlight the signals of BT-4 gastric cancer which may present a characteristic three-layer sandwich sign, and ADC values are helpful in the discrimination of gastric cancer from poorly distended stomach wall.

Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

Purpose: To develop and validate a radiomics model for evaluating pathologic complete response (pCR) to neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer (LARC). Experimental Design: We enrolled 222 patients (152 in the primary cohort and 70 in the validation cohort) with clinicopathologically confirmed LARC who received chemoradiotherapy before surgery. All patients underwent T2-weighted and diffusion-weighted imaging before and after chemoradiotherapy; 2,252 radiomic features were extracted from each patient before and after treatment imaging. The two-sample t test and the least absolute shrinkage and selection operator regression were used for feature selection, whereupon a radiomics signature was built with support vector machines. Multivariable logistic regression analysis was then used to develop a radiomics model incorporating the radiomics signature and independent clinicopathologic risk factors. The performance of the radiomics model was assessed by its calibration, discrimination, and clinical usefulness with independent validation. Results: The radiomics signature comprised 30 selected features and showed good discrimination performance in both the primary and validation cohorts. The individualized radiomics model, which incorporated the radiomics signature and tumor length, also showed good discrimination, with an area under the receiver operating characteristic curve of 0.9756 (95% confidence interval, 0.9185–0.9711) in the validation cohort, and good calibration. Decision curve analysis confirmed the clinical utility of the radiomics model. Conclusions: Using pre- and posttreatment MRI data, we developed a radiomics model with excellent performance for individualized, noninvasive prediction of pCR. This model may be used to identify LARC patients who can omit surgery after chemoradiotherapy. Clin Cancer Res; 23(23); 7253–62. ©2017 AACR.

YAP1 enhances cell proliferation, migration, and invasion of gastric cancer in vitro and in vivo

Yes-associated protein 1 (YAP1) plays an important role in the development of carcinomas such as breast, colorectal, and gastric (GC) cancers, but the role of YAP1 in GC has not been investigated comprehensively. The present study strongly suggests that YAP1 and P62 were significantly up-regulated in GC specimens, compared with normal gastric mucosa. In addition, the YAP1high P62high expression was independently associated with poor prognosis in GC (hazard ratio: 1.334, 95% confidence interval: 1.045–1.704, P = 0.021). Stable YAP1 silencing inhibited the proliferation, migration, and invasion of BGC-823 GC cells in vitro and inhibited the growth of xenograft tumor and hematogenous metastasis of BGC-823 GC cells in vivo. The mechanism was associated with inhibited extracellular signal-regulated kinases (ERK)1/2 phosphorylation, elevated E-cadherin protein expression and decreased vimentin protein expression, down-regulated β-catenin protein expression and elevated α-catenin protein expression, and down-regulated long non-coding RNA (lncRNA) expressions including HOX transcript antisense RNA (HOTAIR), H19, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), human large tumor suppressor-2 (LATS2)-AS1-001, and LATS2. YAP1 over-expression promoted the proliferation, migration, and invasion of human immortalized normal gastric mucosa GES-1 cells in vitro by reversing the above signal molecules. Subcutaneous inoculation of GES-1 cells and YAP1-over-expressing GES-1 cells into nude mice did not generate tumors. We successfully established the xenograft tumor models using MKN-45 GC cells, but immunochemistry showed that there was no YAP1 expression in MKN-45 cells. These results suggest that YAP1 is not a direct factor affecting tumor formation, but could accelerate tumor growth and metastasis. Collectively, this study highlights an important role for YAP1 as a promoter of GC growth and metastasis, and suggests that YAP1 could possibly be a potential treatment target for GC.

Diffusion-tensor imaging as an adjunct to dynamic contrast-enhanced MRI for improved accuracy of differential diagnosis between breast ductal carcinoma in situ and invasive breast carcinoma

OBJECTIVE To determine the value of diffusion-tensor imaging (DTI) as an adjunct to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for improved accuracy of differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive breast carcinoma (IBC). METHODS The MRI data of 63 patients pathologically confirmed as breast cancer were analyzed. The conventional MRI analysis metrics included enhancement style, initial enhancement characteristic, maximum slope of increase, time to peak, time signal intensity curve (TIC) pattern, and signal intensity on FS-T2WI. The values of apparent diffusion coefficient (ADC), directionally-averaged mean diffusivity (Davg), exponential attenuation (EA), fractional anisotropy (FA), volume ratio (VR) and relative anisotropy (RA) were calculated and compared between DCIS and IBC. Multivariate logistic regression was used to identify independent factors for distinguishing IBC and DCIS. The diagnostic performance of the diagnosis equation was evaluated using the receiver operating characteristic (ROC) curve. The diagnostic efficacies of DCE-MRI, DWI and DTI were compared independently or combined. RESULTS EA value, lesion enhancement style and TIC pattern were identified as independent factor for differential diagnosis of IBC and DCIS. The combination diagnosis showed higher diagnostic efficacy than a single use of DCE-MRI (P=0.02), and the area of the curve was improved from 0.84 (95% CI, 0.67-0.99) to 0.94 (95% CI, 0.85-1.00). CONCLUSIONS Quantitative DTI measurement as an adjunct to DCE-MRI could improve the diagnostic performance of differential diagnosis between DCIS and IBC compared to a single use of DCE-MRI.

Fused monochromatic imaging acquired by single source dual energy CT in hepatocellular carcinoma during arterial phase: an initial experience

OBJECTIVE To explore whether single and fused monochromatic images can improve liver tumor detection and delineation by single source dual energy CT (ssDECT) in patients with hepatocellular carcinoma (HCC) during arterial phase. METHODS Fifty-seven patients with HCC who underwent ssDECT scanning at Beijing Cancer Hospital were enrolled retrospectively. Twenty-one sets of monochromatic images from 40 to 140 keV were reconstructed at 5 keV intervals in arterial phase. The optimal contrast-noise ratio (CNR) monochromatic images of the liver tumor and the lowest-noise monochromatic images were selected for image fusion. We evaluated the image quality of the optimal-CNR monochromatic images, the lowest-noise monochromatic images and the fused monochromatic images, respectively. The evaluation indicators included the spatial resolution of the anatomical structure, the noise level, the contrast and CNR of the tumor. RESULTS In arterial phase, the anatomical structure of the liver can be displayed most clearly in the 65-keV monochromatic images, with the lowest image noise. The optimal-CNR monochromatic images of HCC tumor were 50-keV monochromatic images in which the internal structural features of the liver tumors were displayed most clearly and meticulously. For tumor detection, the fused monochromatic images and the 50-keV monochromatic images had similar performances, and were more sensitive than 65-keV monochromatic images. CONCLUSIONS We achieved good arterial phase images by fusing the optimal-CNR monochromatic images of the HCC tumor and the lowest-noise monochromatic images. The fused images displayed liver tumors and anatomical structures more clearly, which is potentially helpful for identifying more and smaller HCC tumors.

Evaluating rectal tumor staging with magnetic resonance imaging, computed tomography, and endoluminal ultrasound: A meta-analysis.

Background:Magnetic resonance imaging (MRI), endoluminal ultrasound (EUS), and computed tomography (CT) are commonly used imaging tools to evaluate rectal tumor staging, but there was no recent meta-analysis to define the present role of the 3 tools. Here, we proposed to systematically compare the accuracy of the 3 imaging tools for rectal tumor staging. Methods:We systematically searched diagnostic accuracy studies of MRI, CT, or EUS on rectal cancer staging, written in English or Chinese, published between January 1, 2003 and Dec 31, 2015 from database of PubMed, EMBASE, and Cochrane Library. The reference standards should be pathological findings. Hierarchical regression model was used for producing summary receiver operating characteristic (SROC) curves and calculating diagnostic accuracy data including sensitivity, specificity, and diagnostic odds ratio for the 3 imaging tools. Investigation of sample size, quality items and resolution, and magnetic field strength on heterogeneity was detected by using subgroup analysis and SROC regression. Results:This analysis included 89 studies. MRI, CT, and EUS yielded similar diagnostic accuracy. Better performance was observed with high-resolution MRI and 3.0-T MRI (P = 0.01 and 0.04, respectively). EUS showed lower diagnostic accuracy after preoperative therapies (P = 0.03). Conclusion:MRI, CT, and EUS have comparable accuracy for rectal tumor staging. High-resolution MRI and 3.0-T MRI can produce better staging results and were recommended. EUS is not suitable for rectal tumor staging for its significantly decreased accuracy.

Identification of benign and malignant thyroid nodules by in vivo iodine concentration measurement using single-source dual energy CT: A retrospective diagnostic accuracy study.

AbstractThis study proposed to determine whether in vivo iodine concentration measurement by single-source dual energy (SSDE) CT can improve differentiation between benign and malignant thyroid nodules. In total, 53 patients presenting with thyroid nodules underwent SSDE CT scanning. Iodine concentrations were measured for each nodule and normal thyroid tissue using the GSI-viewer image analysis software. A total of 26 thyroid nodules were malignant in 26 patients and confirmed by surgery; 33 nodules from 27 patients were benign, with 10 confirmed by surgery and others after follow-up. Iodine concentrations with plain CT were significantly lower in malignant than benign nodules (0.47 ± 0.20 vs 1.17 ± 0.38 mg/mL, P = 0.00). Receiver operating characteristic (ROC) curve showed an area under the curve (AUC) of 0.93; with a cutoff of 0.67, iodine concentration showed 92.3% sensitivity and 88.5% specificity in diagnosing malignancy. Iodine concentration obtained by enhanced and plain CT were significantly higher in malignant than benign nodules (9.05 ± 3.35 vs 3.46 ± 2.24 mg/mL, P = 0.00). ROC curve analysis showed an AUC of 0.93; with a cutoff value of 3.37, iodine concentration displayed 78% sensitivity, 95% specificity in diagnosing malignancy. Combining unenhanced with enhanced iodine concentrations, the diagnostic equation was: Y = –8.641 × unenhanced iodine concentration + 0.663 × iodine concentration. ROC curve showed an AUC of 0.98 (95% CI, 0.94, 1.00). With Y ≥ –2 considered malignancy, diagnostic sensitivity and specificity were 96%, 96.3%, respectively. This study concluded that SSDE CT can detect the differences in iodine uptake and blood supply between benign and malignant thyroid lesions.

Multivariate Analysis of Pleural Invasion of Peripheral Non-Small Cell Lung Cancer-Based Computed Tomography Features.

Objective The aim of this study was to comprehensively analyze computed tomography features to improve the diagnostic accuracy of visceral pleural invasion of peripheral non–small cell lung cancer. Methods The computed tomography features of 205 non–small cell lung cancer patients were retrospectively studied. The lesions relation to the pleura was classified into 5 grades. A multivariate logistic regression analysis was conducted to identify independent factors predicting pleural invasion. Results The multivariate logistic regression analysis showed that sex (odds ratio [OR], 1.822; P = 0.080), pleural indentation (OR, 4.111; P < 0.001), tumor density (OR, 2.735; P = 0.008), and distance between the lesion and pleura (OR, 1.981; P = 0.048) were independent predictors of pleural invasion. A patient with a score of 10.6 had an 80% risk of pleural invasion, whereas a score lower than 2 was associated with a lower (20%) risk of pleural invasion. Conclusions Comprehensive consideration of these factors of pleural indentation, sex, tumor density, and distance between the lesion and pleura might improve the diagnosis of pleural invasion.

MRI in diagnosis of pathological complete response in breast cancer patients after neoadjuvant chemotherapy

OBJECTIVE To select effective indicators for diagnosis of pathological complete response (pCR) by MRI and to establish an appropriate diagnostic program to maximize the accuracy of pCR detection by MRI. MATERIALS AND METHODS Twenty-one pCR patients and 22 non-pCR randomly selected patients receiving neoadjuvant chemotherapy (NAC) and subsequent surgery were recruited for the study. All patients underwent breast MRIs both before and after chemotherapy. Changes in diameter, area and dynamic variables between the first and final MRI were compared between the two groups. Logistic and ROC analysis were performed to select effective indicators for predicting pCR on MRI. RESULTS Eleven out of 43 patients had no residual enhanced areas on MRI, and the sensitivity and specificity for predicting pCR on MRI under the current criterion was 52.38% and 100%, respectively. Logistic regression analysis revealed that changes in diameter, SIpeak and area were effective in predicting pCR by MRI. The latter two parameters had a greater impact on diagnosis than the diameter change. Two new independent criteria were established to predict pCR on MRI: (1) a reduction of ≥78% in area; and (2) a combination of a reduction of ≥27% in SIpeak and of ≥78% in area on MRI. Both had diagnostic accuracy of 88.37% and criterion 1 had higher sensitivity of 90.48%. However, criterion 2 had perfect specificity of 100%. CONCLUSION MRI is an effective means for detecting pCR from non-pCR patients. Changes in area and SIpeak can be used to establish two new independent criteria which perform better in diagnosing pCR on MRI than the current criterion.