Yabin Hu1,2, Shengxiang Rao1, Xiaolin Xu3, Yibo Tang1, Mengsu Zeng4. 1. Department of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, 200030, China. 2. Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China. 3. Department of Anesthesiology, Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong, China. 4. Department of Radiology, Zhongshan Hospital, Fudan University and Shanghai Institute of Medical Imaging, Shanghai, 200030, China. zengmengsu@outlook.com.
Abstract
PURPOSE: To evaluate the value of MR imaging features in stratifying Grade 2 (G2) pancreatic neuroendocrine tumors (PNETs) using the 5% cut-off value of the Ki-67 index as reference standards. MATERIALS AND METHODS: Between January 2010 and October 2016, 41 G2 PNET patients (One patient had 3 tumors) with preoperative MR imaging were included. Tumor grading was based on the revised 2016 World Health Organization classification of PNETs. MR imaging features included size, shape, consistency, T1-w and T2-w signal intensities, enhancement pattern, apparent diffusion coefficient (ADC) ratios (tumor/normal pancreatic parenchyma). RESULTS: 16 Ki-67 index < 5% tumors (SKIT, 37.2%) and 27 Ki-67 index ≥ 5% tumors (LKIT, 62.8%) of G2 were evaluated. The LKIT showed solid consistency (85% vs. 50%, P < 0.05), incomplete envelope-like reinforcement in a delayed phase (74% vs. 62%, P < 0.05), and liver or lymph node metastases (67% vs. 31%, P < 0.05) more frequently than did SKIT. However, ADC ratios of LKIT were smaller than SKIT (0.85 ± 0.23 vs. 1.29 ± 0.39, P = 0.001). Using binary logistic regression analysis, the ADC ratio was an independent significant differentiator of SKIT from LKIT. The AUROC of ADC ratios was 0.816 ± 0.07. The optimal cut-off value for the identification of LKIT was 1.25 × 10-3 (sensitivity 96.3%, specificity 62.5%). CONCLUSION: MRI features may identify the overbroad scope of G2 PNETs and help predict Ki-67 values, as a surrogate for tumor aggressiveness, in G2 PNETs. An optimal cut-off value for predicting Ki-67 status (≥/< 5%) was 1.25 × 10-3 of ADC ratio.
PURPOSE: To evaluate the value of MR imaging features in stratifying Grade 2 (G2) pancreatic neuroendocrine tumors (PNETs) using the 5% cut-off value of the Ki-67 index as reference standards. MATERIALS AND METHODS: Between January 2010 and October 2016, 41 G2 PNET patients (One patient had 3 tumors) with preoperative MR imaging were included. Tumor grading was based on the revised 2016 World Health Organization classification of PNETs. MR imaging features included size, shape, consistency, T1-w and T2-w signal intensities, enhancement pattern, apparent diffusion coefficient (ADC) ratios (tumor/normal pancreatic parenchyma). RESULTS: 16 Ki-67 index < 5% tumors (SKIT, 37.2%) and 27 Ki-67 index ≥ 5% tumors (LKIT, 62.8%) of G2 were evaluated. The LKIT showed solid consistency (85% vs. 50%, P < 0.05), incomplete envelope-like reinforcement in a delayed phase (74% vs. 62%, P < 0.05), and liver or lymph node metastases (67% vs. 31%, P < 0.05) more frequently than did SKIT. However, ADC ratios of LKIT were smaller than SKIT (0.85 ± 0.23 vs. 1.29 ± 0.39, P = 0.001). Using binary logistic regression analysis, the ADC ratio was an independent significant differentiator of SKIT from LKIT. The AUROC of ADC ratios was 0.816 ± 0.07. The optimal cut-off value for the identification of LKIT was 1.25 × 10-3 (sensitivity 96.3%, specificity 62.5%). CONCLUSION: MRI features may identify the overbroad scope of G2 PNETs and help predict Ki-67 values, as a surrogate for tumor aggressiveness, in G2 PNETs. An optimal cut-off value for predicting Ki-67 status (≥/< 5%) was 1.25 × 10-3 of ADC ratio.