Wenxian Guan

Added value of diffusion-weighted MR imaging to T2-weighted and dynamic contrast-enhanced MR imaging in T staging of gastric cancer☆

OBJECTIVE To assess the utilization of diffusion-weighted (DW) magnetic resonance (MR) imaging in T staging of gastric cancer prospectively. METHODS Fifty-one patients underwent T2-weighted (T2W), contrast-enhanced (CE) and DW MR imaging. Two radiologists independently interpreted the images for T staging of the tumors. RESULTS The overall accuracy of T staging in pT1-4 gastric cancers by T2W+CE+DW (88.2%) was significantly higher than that by T2W+CE and T2W+DW (both 76.5%, P=.031). CONCLUSION DW adds useful information to T2W and CE MR imaging in T staging of gastric cancer.

Preoperative T staging of gastric cancer: comparison of diffusion- and T2-weighted magnetic resonance imaging.

Objective The objective of our study was to assess the clinical feasibility of diffusion-weighted (DW) magnetic resonance (MR) imaging in preoperative T staging of gastric cancer prospectively. Methods Forty-five patients underwent axial T2-weighted (T2W) and DW (b, 0 and 1000 seconds/mm2) MR imaging. Two radiologists interpreted the images for detection and staging of the tumors independently. The McNemar test was used to check differences in diagnostic accuracy with the reference of postoperative histopathological results. Results Diffusion-weighted and T2W images detected 44 and 42 of 45 histologically confirmed lesions, respectively. Furthermore, DW images detected 11 of 12 pT1 lesions compared to 9 of 12 lesions by T2W images. The staging accuracy of advanced gastric cancer (≥pT2) in DW imaging is significantly higher than that in T2W imaging (87.9% and 69.7%, respectively; P < 0.05). Conclusions Diffusion-weighted is superior to T2W imaging in detection of early gastric cancers (pT1) and staging advanced cancers (≥pT2).

Preoperative apparent diffusion coefficient value of gastric cancer by diffusion‐weighted imaging: Correlations with postoperative TNM staging

To determine if the apparent diffusion coefficient (ADC) values of gastric cancers on the preoperative diffusion weighted imaging (DWI) correlate with the postoperative TNMs of the lesions.

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps.

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer.

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

ObjectivesTo explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.MethodsPreoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed.ResultsMean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, −0.231 ~ −0.324, 0.228 ~ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = −0.265, −0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion.ConclusionCT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers.Key Points• CT texture analysis is noninvasive and effective for gastric cancer.• Portal venous CT images correlated significantly with differentiation degree and Lauren classification.• Standard deviation, entropy and minimum attenuation in arterial phase reflect vascular invasion.

Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: Correlations with the histological differentiation and Lauren classification

OBJECTIVE The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). MATERIALS AND METHODS Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000s/mm(2)). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. RESULTS The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p<0.05). Mean and minimum ADC values correlated significantly (all p<0.001) with histological differentiation (r=0.564, 0.578) and Lauren classification (r=-0.493, -0.481). CONCLUSIONS The ADC values may be helpful as a noninvasive tool for evaluating the histological features of gastric cancer, such as histological type, degree of differentiation and Lauren classification.

Whole-volume apparent diffusion coefficient-based entropy parameters for assessment of gastric cancer aggressiveness

To explore the role of whole‐volume apparent diffusion coefficient (ADC)‐based entropy parameters in the preoperative assessment of gastric cancers aggressiveness.

Predicting the nodal status in gastric cancers: The role of apparent diffusion coefficient histogram characteristic analysis

PURPOSE To explore the application of histogram analysis in preoperative T and N staging of gastric cancers, with a focus on characteristic parameters of apparent diffusion coefficient (ADC) maps. MATERIALS AND METHODS Eighty-seven patients with gastric cancers underwent diffusion weighted magnetic resonance imaging (b=0, 1000s/mm2), which generated ADC maps. Whole-volume histogram analysis was performed on ADC maps and 7 characteristic parameters were obtained. All those patients underwent surgery and postoperative pathologic T and N stages were determined. RESULTS Four parameters, including skew, kurtosis, s-sDav and sample number, showed significant differences among gastric cancers at different T and N stages. Most parameters correlated with T and N stages significantly and worked in differentiating gastric cancers at different T or N stages. Especially skew yielded a sensitivity of 0.758, a specificity of 0.810, and an area under the curve (AUC) of 0.802 for differentiating gastric cancers with and without lymph node metastasis (P<0.001). All the parameters, except AUClow, showed good or excellent inter-observer agreement with intra-class correlation coefficients ranging from 0.710 to 0.991. CONCLUSION Characteristic parameters derived from whole-volume ADC histogram analysis could help assessing preoperative T and N stages of gastric cancers.

Texture analysis of CT images in predicting malignancy risk of gastrointestinal stromal tumours.

AIM To explore the role of texture analysis of computed tomography (CT) images in predicting the malignancy risk of gastrointestinal stromal tumours (GISTs). MATERIALS AND METHODS Seventy-eight patients with histopathologically confirmed GISTs underwent preoperative CT. Texture analysis was performed on unenhanced and contrast-enhanced CT images, respectively. Fourteen CT texture parameters were obtained and compared among GISTs at different malignancy risks with one-way analysis of variance or independent-samples Kruskal-Wallis test. Correlations between CT texture parameters and malignancy risk were analysed with Spearmans correlation test. Diagnostic performance of CT texture parameters in differentiating GISTs at low/very low malignancy risk was tested with receiver operating characteristic (ROC) analysis. RESULTS Three parameters on unenhanced images (r=-0.268-0.506), four parameters on arterial phase (r=-0.365-0.508), and six parameters on venous phase (r=-0.343-0.481) imaging correlated significantly with malignancy risk of GISTs, respectively (all p<0.05). For identifying GISTs at low/very low malignancy risk, three parameters on unenhanced images (area under ROC curve [AUC], 0.676-0.802), four parameters on arterial phase (AUC, 0.637-0.811), and six parameters on venous phase (AUC, 0.636-0.791) imaging showed significant diagnostic performance, respectively (all p<0.05), especially maximum frequency on both unenhanced and contrast-enhanced images (AUC, 0.791-0.811). CONCLUSION Texture analysis of CT images holds great potential to predict the malignancy risk of GISTs preoperatively.

Preoperative CT texture analysis of gastric cancer: correlations with postoperative TNM staging

AIM To explore the role of computed tomography (CT) texture analysis in predicting pathologic stage of gastric cancers. MATERIALS AND METHODS Preoperative enhanced CT images of 153 patients (112 men, 41 women) with gastric cancers were reviewed retrospectively. Regions of interest (ROIs) were manually drawn along the margin of the lesion on the section where it appeared largest on the arterial and venous CT images, which yielded texture parameters, including mean, maximum frequency, mode, skewness, kurtosis, and entropy. Correlations between texture parameters and pathological stage were analysed with Spearmans correlation test. The diagnostic performance of CT texture parameters in differentiating different stages was evaluated using receiver operating characteristic (ROC) analysis. RESULTS Maximum frequency in the arterial phase and mean, maximum frequency, mode in the venous phase correlated positively with T stage, N stage, and overall stage (all p<0.05) of gastric cancer. Entropy in the venous phase also correlated positively with N stage (p=0.009) and overall stage (p=0.032). Skewness in the arterial phase had the highest area under the ROC curve (AUC) of 0.822 in identifying early from advanced gastric cancers. Multivariate analysis identified four parameters, including maximum frequency, skewness, entropy in the venous phase, and differentiation degree from biopsy, for predicting lymph node metastasis of gastric cancer. The multivariate model could distinguish gastric cancers with and without lymph node metastasis with an AUC of 0.892. CONCLUSION Multiple CT texture parameters, especially those in the venous phase, correlated well with pathological stage and hold great potential in predicting lymph node metastasis of gastric cancers.