Radiomics study for differentiating gastric cancer from gastric stromal tumor based on contrast-enhanced CT images.

PURPOSE: To test the feasibility of differentiate gastric cancer from gastric stromal tumor using a radiomics study based on contrast-enhanced CT images. MATERIALS AND METHODS: The contrast-enhanced CT image data of 60 patients with gastric cancer and 40 patients with gastric stromal tumor confirmed by postoperative pathology were retrospectively analyzed. First, CT images were read by two senior radiologists to acquire subjective CT signs model, including perigastric fatty infiltration, perigastric enlarged lymph nodes, the enhancement and growth modes of gastric tumors. Second, the manual segmentation of gastric tumors from the CT images was performed by the two radiologists to extract radiomics features via ITK-SNAP software, and to construct radiomics signature model. Finally, a diagnostic model integrated with subjective CT signs and radiomics signatures was constructed. The diagnostic efficacy of three models in differentiating gastric cancer from gastric stromal tumor was compared by using receiver operating characteristic curves (ROC). RESULTS: There are statistically significant differences between the gastric cancer and gastric stromal tumor in the perigastric enlarged lymph nodes, growth mode and radiomics signature (p < 0.05). The area under ROC curve (AUC), sensitivity and accuracy of subjective CT signs model were the lowest among the three models. While the combined model yields the highest AUC value (0.903), specificity (93.33%) and accuracy (86.00%) among the three models (p = 0.03). CONCLUSION: The diagnostic model integrating subjective CT signs and radiomics signature can improve the diagnostic accuracy of gastric tumors.

A pilot study of radiomics technology based on X-ray mammography in patients with triple-negative breast cancer.

PURPOSE: To explore the radiomics features of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC) based on X-ray mammography, and to differentiate the two groups of cases. MATERIALS AND METHODS: Preoperative mammograms of 120 patients with breast ductal carcinoma confirmed by surgical pathology were retrospectively analyzed, which include 30 TNBC and 90 non-TNBC patients. The manual segmentation of breast lesions was performed by ITK-SNAP software and 12 radiomics features were extracted by Omni-Kinetics software. The differences of these radiomics features between TNBC and non-TNBC groups were compared, and the receiver operating characteristic (ROC) curve was used to determine the optimal cutoff value of each radiomics parameter for differentiating TNBC from non-TNBC, and the corresponding area under the curve (AUC), sensitivity and specificity were obtained. RESULTS: There were statistically significant differences for 4 radiomics features between TNBC and non-TNBC datasets (P < 0.05). They were the roundness, concavity, gray average and skewness of breast lesions. Compared with non-TNBC, TNBC cases have following characteristics of (1) more round with the roundness of 0.621 vs. 0.413 (P < 0.001), (2) more regular with the concavity of 0.087 vs. 0.141 (P < 0.01), (3) higher density or gray average (67.261 vs. 56.842, P < 0.05), and (4) lower skewness (- 0.837 vs.- 0.671, P = 0.034). AUCs of ROC curves computed using features of the roundness and concavity were both larger than 0.70. CONCLUSION: Radiomics features based on X-ray mammography may be helpful to distinguish between TNBC and non-TNBC, which were associated with breast tumor histology.

A pilot study of low-dose CT perfusion imaging (LDCTPI) technology in patients with triple-negative breast cancer.

PURPOSE: To investigate associations between the clinicopathologic features and CT perfusion parameters of triple-negative breast cancer (TNBC) and non-TNBC using low-dose computed tomography perfusion imaging (LDCTPI), and to find potential clinical applications in the prognosis assessment of TNBC. MATERIALS AND METHODS: A total of 60 patients with breast cancer confirmed by pathological examination were studied prospectively using LDCTPI on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using a tumor perfusion protocol in the CT perfusion software package to measure 2 parameters namely, blood flow (BF), and permeability surface (PS) area product. Patients were grouped into TNBC (n = 27) and non-TNBC (n = 33) subtypes. Associations between these two subtypes and clinicopathologic characteristics were evaluated by both univariate and multivariate logistic regression. CT perfusion parameters values were compared for clinicopathologic characteristics using independent 2-sample t test. RESULTS: TNBC displayed higher CT perfusion parameters values (BF: 57.56±10.94 vs 52.70±7.79 mL/100 g/min, p = 0.006; PS: 38.98±9.46 vs 33.39±8.07 mL/100 g/min, p = 0.001) than non-TNBC. In addition, breast cancer with poorly histologic grade or positive Ki-67 expression showed higher BF and PS values than those with well and moderately histologic grade or negative Ki-67 expression (p < 0.05). TNBC had poorer histologic grade (P = 0.032) and higher Ki-67 expression (P = 0.013) than non-TNBC. CONCLUSION: LDCTPI is a functional imaging technology from the perspective of hemodynamics with potential of clinical applications. The BF and PS values were higher in TNBC patient group than non-TNBC group. TNBC patients also have poorer clinicopathologic outcome.

A clinical application of dynamic contrast-enhanced CT (DCE-CT) in patients with variously differentiated breast ductal carcinoma.

PURPOSE: To explore the hemodynamic characteristics of variously differentiated breast ductal carcinoma (BDC) using the dynamic contrast-enhanced CT (DCE-CT) based CT perfusion imaging (CTPI), including the specific perfusion parameter values, and to identify potential clinical applications in the cell differentiation degree of BDC. MATERIALS AND METHODS: Forty patients with breast ductal carcinoma confirmed by needle puncture biopsy were studied prospectively using CTPI on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using a tumor perfusion protocol in the CT perfusion software package to measure 4 parameters namely, blood flow (BF), blood volume (BV), mean transit time (MTT), and the permeability surface (PS) area product. The different differentiated BDC with CT perfusion parameters were divided into 3 groups of high, moderate and poor differentiation. The comparison among these groups were then made using statistical data analysis software. RESULTS: The patients were categorized into three groups of 12, 13, and 15 highly, moderately and poorly differentiated ductal carcinoma cases, respectively. Comparing the perfusion parameters values of the three groups, BF, BV, and PS values increased from highly to poorly differentiated BDC cases. Differences between the highly and moderately or poorly differentiated groups were all statistically significant for BF, BV, and PS values (p < 0.05), while MTT value showed no statistical difference among the three groups (p > 0.05). CONCLUSION: CTPI is a functional imaging technology from the perspective of hemodynamics with potential clinical applications. Three parameters of BF, BV and PS values have potential to serve as indicators of the cell differentiation degree of the breast ductal carcinoma.

An application study of low-dose computed tomography perfusion imaging (LDCTPI) in breast cancer and breast fibroadenoma.

PURPOSE: To explore the characteristics of breast cancer and breast fibroadenoma using low-dose computed tomography perfusion imaging (LDCTPI) including specific perfusion parameter values, and seek the potential clinical applications in cancer prognosis assessment. MATERIALS AND METHODS: Fifty patients including 30 diagnosed with breast cancer and 20 with breast fibroadenoma, as well as 15 control subjects with normal breasts were studied prospectively using LDCTPI examinations. The acquired volumetric imaging data were used for calculation, mapping and analysis by using a body tumor perfusion protocol in the CT perfusion software to measure 4 parameters: blood flow (BF), blood volume (BV), mean transit time (MTT), and the permeability surface (PS) area product. Statistical data analysis was then performed to distinguish the difference of the 4 parameter values among normal control, breast cancer and breast fibroadenoma cases. RESULTS: The mean perfusion values of 15 normal controls were as follows: BF, 20.03±4.08 mL/100 g/min; BV, 4.53±0.95 mL/100 g; MTT, 5.90±0.82 s; and PS, 9.25±1.18 mL/100 g/min. The mean perfusion values of 30 cancer patients were as follows: BF, 56.67±6.59 mL/100 g/min; BV, 5.82±0.68 mL/100 g; MTT, 6.01±0.82 s; and PS, 24.95±5.05 mL/100 g/min. The mean perfusion values of 20 patients with breast fibroadenoma were as follows: BF, 46.24±6.65 mL/100 g/min; BV, 5.07±0.73 mL/100 g; MTT, 7.51±0.62 s; and PS, 16.73±6.48 mL/100 g/min. Comparing the 3 groups, differences were all statistically significant for BF, BV, MTT and PS values (p < 0.05, respectively); The BF, BV, PS values were highest in group of cancer patients, while the MTT value was highest in group of patients diagnosed with breast fibroadenoma. CONCLUSION: Breast CT perfusion imaging is a promising functional imaging technology in breast cancer diagnosis, which can provide valuable quantitative imaging markers to assist evaluation of breast tumors.

Can low-dose CT perfusion imaging accurately assess response of advanced gastric cancer with neoadjuvant chemotherapy?

PURPOSE: To explore the value of low-dose CT perfusion imaging (LDCTPI) technology and its perfusion parameters in assessing response of neoadjuvant chemotherapy (NAC) in patients with advanced gastric cancer (AGC). METHODS: Thirty patients with AGC were studied prospectively by LDCTPI to measure two parameters including blood flow (BF) and blood volume (BV) of tumor area before and after chemotherapy, respectively. All of the patients received two courses of NAC and surgical resection of gastric tumor within one week after chemotherapy, and then obtained the result of postoperative pathology response for chemotherapy. The comparisons of BF and BV values of AGC before and after chemotherapy were analyzed by paired-samples t-test, respectively; and the correlations between BF as well as BV decrease rates after NAC and the pathology response grade were analyzed by Spearman statistical test. Thirty patients were divided into effective and ineffective groups according to different pathology response grade. Comparisons of BF as well as BV decrease rates between effective and ineffective groups were analyzed by independent-samples t-test, respectively. Receiver operating characteristic (ROC) curves were used to determine the cutoff values of BF and BV decrease rates as evaluation indicators of AGC after NAC and calculate area under the curve (AUC). RESULTS: There were significant differences in BF and BV values of AGC between before and after NAC (p < 0.001), respectively, and there were obvious correlations between BF as well as BV decrease rates and pathology response grade (r = 0.660, p < 0.001; r = 0.706, p < 0.001), respectively. There were also significant differences in BF and BV decrease rates of AGC between effective and ineffective groups (P = 0.001), respectively. If BF decrease rate of 12.1% (AUC was 0.816, P = 0.005) was used as the cutoff value for chemotherapy effectiveness of AGC, the sensitivity of 82% and specificity of 84% were achieved, and if BV decrease rate of 32.8% (AUC was 0.844, P = 0.002) was used as the cutoff value for chemotherapy effectiveness of AGC, the sensitivity of 82% and specificity of 89% were achieved. CONCLUSIONS: BF and BV decrease rates have potential to be used as effective indicators to assess chemotherapy efficacy of AGC from the hemodynamics.

The feasibility of low-dose CT perfusion imaging in gastric cancer.

PURPOSE: To investigate feasibility of applying low-dose CT perfusion imaging (CTPI) to diagnose gastric cancer. MATERIALS AND METHODS: Twenty patients with gastric cancer confirmed by endoscopic biopsy were undergone routine dose (120 kV, 100 mA) and low-dose (120 kV, 50 mA) CTPI examination, respectively. The original data were processed by body perfusion software, and the perfusion parameters values including blood flow (BF), blood volume (BV) and permeability surface (PS) of gastric cancer were measured. Statistical data analyses including paired-samples t test, Pearson correlation analysis and Bland-Altman consistency test were used to compare the perfusion parameters values between the routine dose and low-dose CTPI examinations. Radiation dosage, which the patients received during two CTPI examinations, was also calculated and compared. RESULTS: There were no statistical differences in the BF, BV and PS values between routine dose group and low-dose group (P > 0.05), and there were significant correlation in the BF, BV and PS values between two groups (P <  0.01). The consistency of BF and BV values between the two groups was preferable to that of PS value. The radiation dosage of the low-dose group was much less than that of routine dose group, and the CTDIvol and DLP values of low-dose CTPI were decreased by 50%, respectively. CONCLUSION: The parameters BF and BV values may play a valuable role in the diagnosis and assessment of gastric cancer in low-dose CTPI examination.

Role of CT perfusion imaging in patients with variously differentiated gastric adenocarcinoma.

PURPOSE: To explore the characteristics of variously differentiated gastric cancers on computed tomography (CT) perfusion imaging, including specific perfusion parameter values, and potential clinical applications in the prognosis assessment of gastric cancer. MATERIALS AND METHODS: Fifty patients with gastric cancer confirmed by gastroscope pathology were studied prospectively using CT perfusion imaging examinations on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using an abdominal tumor perfusion protocol (deconvolution method) in the CT perfusion software package to measure 4 parameters: blood flow (BF), blood volume (BV), mean transit time (MTT), and the permeability surface (PS) area product. The different differentiated Gastric cancers with CT perfusion values were divided into 3 groups: well-differentiated, moderately differentiated and poorly differentiated gastric adenocarcinoma, and compared statistically with one another by statistical software. RESULTS: The mean perfusion values of 10 patients with well-differentiated gastric adenocarcinoma were as follows: BF, 75.28 ± 6.81 mL/100 g/min; BV, 9.01 ± 0.94 mL/100 g; MTT, 9.89 ± 1.65 s; and PS, 10.05 ± 0.71 mL/100 g/min. The mean perfusion values of 24 patients with moderately differentiated gastric adenocarcinoma were as follows: BF, 110.01 ± 31.90 mL/100 g/min; BV, 18.18 ± 5.62 mL/100 g; MTT, 9.81 ± 3.69 s; and PS, 40.08 ± 15.82 mL/100 g/min. The mean perfusion values of 16 patients with poorly differentiated gastric adenocarcinoma were as follows: BF, 138.59 ± 38.09 mL/100 g/min; BV, 21.08 ± 4.11 mL/100 g; MTT, 9.47 ± 1.80 s; and PS, 57.50 ± 13.28 mL/100 g/min. Comparing the 3 groups, differences between the well-differentiated group and the moderate differentiation group were all statistically significant for BF, BV, and PS (p < 0.05, respectively), differences between the well-differentiated group and the poor differentiation group were all statistically significant for BF, BV, and PS (p < 0.05,respectively) as well; While MTT value showed no statistical difference among the 3 groups (p > 0.05). CONCLUSION: Stomach CT perfusion imaging is a functional imaging technology from the perspective of hemodynamics with potential clinical applications. The BF, BV and PS values could serve as indicators of the degree of malignancy and aid in prognostic assessment of gastric cancer.