Yijing Xie1,2,3,4, Shipeng Zhang5, Xianwang Liu1,2,3,4, Xiaoyu Huang1,2,3,4, Qing Zhou1,2,3,4, Yongjun Luo6,2,3,4, Qian Niu7, Junlin Zhou8,9,10. 1. Department of Radiology, Lanzhou University Second Hospital, Lanzhou, 730000, China. 2. Second Clinical School, Lanzhou University, Lanzhou, 730000, China. 3. Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, 730000, China. 4. Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, 730000, China. 5. Department of Radiology, Gansu Provincial Maternity and Child-Care Hospital, Lanzhou, 730000, China. 6. Department of Nuclear Medicine, Lanzhou University Second Hospital, Lanzhou, 730000, China. 7. Department of Pathology, Lanzhou University Second Hospital, Lanzhou, 730000, China. 8. Department of Radiology, Lanzhou University Second Hospital, Lanzhou, 730000, China. ery_zhoujl@lzu.edu.cn. 9. Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, 730000, China. ery_zhoujl@lzu.edu.cn. 10. Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, 730000, China. ery_zhoujl@lzu.edu.cn.
Abstract
PURPOSE: To investigate the diagnostic performance of the minimal apparent diffusion coefficient (ADCmin) to distinguish between pancreatic neuroendocrine tumors (Pan-NETs) with low and high Ki-67 proliferation index values and to evaluate the relationship between ADCmin and the Ki-67 proliferation index. METHODS: Pre-operative magnetic resonance imaging data and postoperative Ki-67 proliferation index data of 42 patients with primary neuroendocrine tumor of the pancreas from November 2014 to March 2021 were included in this retrospective study. According to the Ki-67 proliferation index value, Pan-NETs were divided into a high-expression group (Ki-67 ≥ 10%, n = 17) and low-expression group (Ki-67 < 10%, n = 25), and mean ADC (ADCmean) and ADCmin values were compared between groups using receiver operating characteristic (ROC) curves to evaluate the performance of ADCmean and ADCmin in judging the expression level of Ki-67 proliferation index. The relationship between ADCmin and the Ki-67 proliferation index was also evaluated. RESULTS: The ADCmin was significantly higher in the low-expression group (Z = - 3.537, p < 0.01). The area under the ROC curve (AUC) for ADCmin was 0.825, which was higher than that for ADCmean (0.781). Using 1.32 × 10-3 mm2/s as the optimal discriminating threshold, the sensitivity, specificity, accuracy, and positive and negative predictive values of the two groups were 80%, 88.2%, 83.3%, 90%, and 75%, respectively. The ADCmin of Pan-NETs showed a significant negative correlation with the Ki-67 proliferation index (rs = - 0.634, p < 0.001). CONCLUSION: The ADCmin is a potential imaging biomarker, which may be helpful for non-invasive preoperative prediction of the Ki-67 proliferation index of Pan-NETs and the subsequent planning of appropriate treatment.
PURPOSE: To investigate the diagnostic performance of the minimal apparent diffusion coefficient (ADCmin) to distinguish between pancreatic neuroendocrine tumors (Pan-NETs) with low and high Ki-67 proliferation index values and to evaluate the relationship between ADCmin and the Ki-67 proliferation index. METHODS: Pre-operative magnetic resonance imaging data and postoperative Ki-67 proliferation index data of 42 patients with primary neuroendocrine tumor of the pancreas from November 2014 to March 2021 were included in this retrospective study. According to the Ki-67 proliferation index value, Pan-NETs were divided into a high-expression group (Ki-67 ≥ 10%, n = 17) and low-expression group (Ki-67 < 10%, n = 25), and mean ADC (ADCmean) and ADCmin values were compared between groups using receiver operating characteristic (ROC) curves to evaluate the performance of ADCmean and ADCmin in judging the expression level of Ki-67 proliferation index. The relationship between ADCmin and the Ki-67 proliferation index was also evaluated. RESULTS: The ADCmin was significantly higher in the low-expression group (Z = - 3.537, p < 0.01). The area under the ROC curve (AUC) for ADCmin was 0.825, which was higher than that for ADCmean (0.781). Using 1.32 × 10-3 mm2/s as the optimal discriminating threshold, the sensitivity, specificity, accuracy, and positive and negative predictive values of the two groups were 80%, 88.2%, 83.3%, 90%, and 75%, respectively. The ADCmin of Pan-NETs showed a significant negative correlation with the Ki-67 proliferation index (rs = - 0.634, p < 0.001). CONCLUSION: The ADCmin is a potential imaging biomarker, which may be helpful for non-invasive preoperative prediction of the Ki-67 proliferation index of Pan-NETs and the subsequent planning of appropriate treatment.
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