Author of 3 Presentations
SS 3.10 - Prediction of early recurrence after surgery in patients with pancreatic neuroendocrine tumour using preoperative MRI
Abstract
Purpose
To investigate important MRI features for predicting early recurrence in patients with pancreatic neuroendocrine tumor (PNET) after surgery.
Material and methods
A total of 100 patients (mean age 55.8 years; M:F, 49:51) with PNET who underwent MRI and first-line surgery from 2000 to 2018 were included. Two radiologists independently assessed MRI findings including size, location, margin, T1- and T2-signal intensity, enhancement patterns, CBD and pancreatic duct dilatation, vascular invasion, LN enlargement, DWI, ADC value, retrospectively. Survival and clinicopathologic data including underlying disease, tumor grade, TNM stage, resection margin and postoperative complications were collected. Image findings associated with disease-free survival and overall survival were assessed with Kaplan-Meier survival analysis and multivariate Cox proportional hazard regression analysis.
Results
The mean disease-free survival and overall survival of the patients were 115.3 [96.8-133.9] and 130.0 [119.4-140.7] months, respectively. Among the variables, arterial iso- to hypo-enhancement, portal iso- to hypo-enhancement, ductal dilatation, arterial invasion, venous invasion, lymph node enlargement, larger tumor size and higher histologic grade showed significant early recurrence (p< 0.05) and poor overall survival (p< 0.05) in univariate analysis. In multivariate analysis, portal iso- to hypo-enhancement (HR 23.12 [2.72-196.4] (p=0.004)), ductal dilatation (HR 4.76 [1.13-19.95] (p=0.033)), arterial invasion (HR 72.13 [4.63-1123.31] (p=0.002)), venous invasion (HR 6.35 [1.80-22.43] (p=0.004)) and tumor size (HR 1.03 [1.00-1.07] (p=0.046)) showed significant effect on early recurrence. However, there was no significant variable for overall survival.
Conclusion
MRI features including size, enhancement pattern, vascular invasion and ductal dilatation are useful in predicting early recurrence after surgery in patients with PNET.
Video-on-demand
SS 5.5 - Assessment of malignant potential in intraductal papillary mucinous neoplasms of the pancreas using MR findings and texture analysis
Abstract
Purpose
To investigate the usefulness of MR findings and texture analysis for predicting the malignant potential of pancreatic intraductal papillary neoplasms (IPMNs).
Material and methods
248 patients with surgically confirmed IPMNs (106 high grade (HG; invasive carcinoma and high-grade dysplasia) and 142 low grade (LG; low/intermediate-grade dysplasia)) and who underwent preoperative MRI with MRCP were included. MR findings suggestive of high-risk stigmata or worrisome features based on the international consensus Fukuoka guidelines 2017 were analyzed. Quantitative features were extracted using texture analysis of T2-weighted MRCP. Multivariate analysis was used to identify independent predictors for HG IPMNs. Diagnostic performance was also analyzed using receiver operating curve analysis.
Results
Among MR findings, enhancing mural nodules ≥5mm, main pancreatic ductal (MPD) dilatation ≥10mm, and abrupt change of MPD with upstream parenchymal atrophy were significant predictors for HG IPMNs (all Ps <0.05). Among texture variables, the significant predictors for HG IPMNs were lower sphericity (P=0.004) and lower compactness (P<0.001). At multivariate analysis, enhancing mural nodule ≥5mm (odds ratios (ORs), 7.97; 95% confidence interval (CI), 4.10-15.52; P<0.001), MPD dilatation ≥10mm (OR, 2.59; 95% CI, 1.16-5.79; P=0.021) and lower compactness on texture analysis (OR, 0.81; 95 % CI, 0.67-0.98; P=0.032) were significant factors for predicting HG IPMNs. Addition of texture variable to MR findings showed better diagnostic performance for predicting HG IPMNs than using MR findings only (AUC, 0.83 vs. 0.79, P=0.008).
Conclusion
MRCP-derived texture features are useful for predicting malignant potential of IPMNs and addition of texture analysis to MRI features may improve diagnostic performance for predicting HG IPMNs.
Video-on-demand
SS 5.8 - Texture analysis of preoperative CT images of mass-forming cholangiocarcinoma: 2D and 3D texture analysis with disease-free survival
Abstract
Purpose
To determine whether CT texture analysis (CTTA) has a value in the prediction of disease-free survival (DFS) in patients with mass-forming type intrahepatic cholangiocarcinoma (mICC) undergoing surgical resection.
Material and methods
The late arterial-phase CT scans of 89 patients with mICC who underwent surgical treatment were retrospectively analyzed. CTTA was performed using a software (Radiomics, Syngo.via Frontier, Siemens Healthineers, Forchheim, Germany) that employed a first-order and second-order texture analysis by drawing a region of interest of 1) the largest cross-sectional area of the tumor (2D) and 2) whole tumor volume (3D). Patients were followed up until disease progression. Cox proportional hazard models were used to determine the relationship between texture features and DFS.
Results
Univariate analysis of 2D texture identified that first-order mean (p=.001), energy (p=.037), kurtosis (p=.001), and shape-flatness (p=.006) were significant univariate markers of DFS. Univariate analysis of 3D texture yielded mean (p<.001) as a significant factor. Among clinicopathologic parameters, size (p <.001), extrahepatic involvement (p=.006), multiplicity (p=.016), lymph node involvement (p=.000), and CEA (p=.003) were significant univariate markers. A Cox regression model including all significant univariate markers identified no significant texture factors on 2D analysis but first-order mean (p=.006) on 3D analysis. Size and lymph node (LN) involvement were significant factors on 2D and 3D analyses and CEA was a significant factor in 2D analysis on multivariate analysis.
Conclusion
The mean of the 3D texture parameters is independently associated with poorer DFS in patients with mICC, while other texture parameters did not show correlation with DFS.
Video-on-demand
Author of 3 Presentations
SS 3.10 - Prediction of early recurrence after surgery in patients with pancreatic neuroendocrine tumour using preoperative MRI (ID 432)
Abstract
Purpose
To investigate important MRI features for predicting early recurrence in patients with pancreatic neuroendocrine tumor (PNET) after surgery.
Material and methods
A total of 100 patients (mean age 55.8 years; M:F, 49:51) with PNET who underwent MRI and first-line surgery from 2000 to 2018 were included. Two radiologists independently assessed MRI findings including size, location, margin, T1- and T2-signal intensity, enhancement patterns, CBD and pancreatic duct dilatation, vascular invasion, LN enlargement, DWI, ADC value, retrospectively. Survival and clinicopathologic data including underlying disease, tumor grade, TNM stage, resection margin and postoperative complications were collected. Image findings associated with disease-free survival and overall survival were assessed with Kaplan-Meier survival analysis and multivariate Cox proportional hazard regression analysis.
Results
The mean disease-free survival and overall survival of the patients were 115.3 [96.8-133.9] and 130.0 [119.4-140.7] months, respectively. Among the variables, arterial iso- to hypo-enhancement, portal iso- to hypo-enhancement, ductal dilatation, arterial invasion, venous invasion, lymph node enlargement, larger tumor size and higher histologic grade showed significant early recurrence (p< 0.05) and poor overall survival (p< 0.05) in univariate analysis. In multivariate analysis, portal iso- to hypo-enhancement (HR 23.12 [2.72-196.4] (p=0.004)), ductal dilatation (HR 4.76 [1.13-19.95] (p=0.033)), arterial invasion (HR 72.13 [4.63-1123.31] (p=0.002)), venous invasion (HR 6.35 [1.80-22.43] (p=0.004)) and tumor size (HR 1.03 [1.00-1.07] (p=0.046)) showed significant effect on early recurrence. However, there was no significant variable for overall survival.
Conclusion
MRI features including size, enhancement pattern, vascular invasion and ductal dilatation are useful in predicting early recurrence after surgery in patients with PNET.
Video-on-demand
SS 5.5 - Assessment of malignant potential in intraductal papillary mucinous neoplasms of the pancreas using MR findings and texture analysis (ID 423)
Abstract
Purpose
To investigate the usefulness of MR findings and texture analysis for predicting the malignant potential of pancreatic intraductal papillary neoplasms (IPMNs).
Material and methods
248 patients with surgically confirmed IPMNs (106 high grade (HG; invasive carcinoma and high-grade dysplasia) and 142 low grade (LG; low/intermediate-grade dysplasia)) and who underwent preoperative MRI with MRCP were included. MR findings suggestive of high-risk stigmata or worrisome features based on the international consensus Fukuoka guidelines 2017 were analyzed. Quantitative features were extracted using texture analysis of T2-weighted MRCP. Multivariate analysis was used to identify independent predictors for HG IPMNs. Diagnostic performance was also analyzed using receiver operating curve analysis.
Results
Among MR findings, enhancing mural nodules ≥5mm, main pancreatic ductal (MPD) dilatation ≥10mm, and abrupt change of MPD with upstream parenchymal atrophy were significant predictors for HG IPMNs (all Ps <0.05). Among texture variables, the significant predictors for HG IPMNs were lower sphericity (P=0.004) and lower compactness (P<0.001). At multivariate analysis, enhancing mural nodule ≥5mm (odds ratios (ORs), 7.97; 95% confidence interval (CI), 4.10-15.52; P<0.001), MPD dilatation ≥10mm (OR, 2.59; 95% CI, 1.16-5.79; P=0.021) and lower compactness on texture analysis (OR, 0.81; 95 % CI, 0.67-0.98; P=0.032) were significant factors for predicting HG IPMNs. Addition of texture variable to MR findings showed better diagnostic performance for predicting HG IPMNs than using MR findings only (AUC, 0.83 vs. 0.79, P=0.008).
Conclusion
MRCP-derived texture features are useful for predicting malignant potential of IPMNs and addition of texture analysis to MRI features may improve diagnostic performance for predicting HG IPMNs.
Video-on-demand
SS 5.8 - Texture analysis of preoperative CT images of mass-forming cholangiocarcinoma: 2D and 3D texture analysis with disease-free survival (ID 330)
Abstract
Purpose
To determine whether CT texture analysis (CTTA) has a value in the prediction of disease-free survival (DFS) in patients with mass-forming type intrahepatic cholangiocarcinoma (mICC) undergoing surgical resection.
Material and methods
The late arterial-phase CT scans of 89 patients with mICC who underwent surgical treatment were retrospectively analyzed. CTTA was performed using a software (Radiomics, Syngo.via Frontier, Siemens Healthineers, Forchheim, Germany) that employed a first-order and second-order texture analysis by drawing a region of interest of 1) the largest cross-sectional area of the tumor (2D) and 2) whole tumor volume (3D). Patients were followed up until disease progression. Cox proportional hazard models were used to determine the relationship between texture features and DFS.
Results
Univariate analysis of 2D texture identified that first-order mean (p=.001), energy (p=.037), kurtosis (p=.001), and shape-flatness (p=.006) were significant univariate markers of DFS. Univariate analysis of 3D texture yielded mean (p<.001) as a significant factor. Among clinicopathologic parameters, size (p <.001), extrahepatic involvement (p=.006), multiplicity (p=.016), lymph node involvement (p=.000), and CEA (p=.003) were significant univariate markers. A Cox regression model including all significant univariate markers identified no significant texture factors on 2D analysis but first-order mean (p=.006) on 3D analysis. Size and lymph node (LN) involvement were significant factors on 2D and 3D analyses and CEA was a significant factor in 2D analysis on multivariate analysis.
Conclusion
The mean of the 3D texture parameters is independently associated with poorer DFS in patients with mICC, while other texture parameters did not show correlation with DFS.