Value of diffusion-weighted magnetic resonance imaging in predicting World Health Organization grade in G1/G2 pancreatic neuroendocrine tumors

Guo, Chuangen; Zhuge, Xiaoling; Chen, Xiao; Wang, Zhongqiu; Xiao, Wenbo; Wang, Qidong

doi:10.3892/ol.2017.6029

Cited by 14 publications

(7 citation statements)

References 17 publications

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“…Several reports have discussed the relationship between ADC values and the WHO classification of PanNETs. Similar to our data, DWI was useful in the identification of high-grade tumors [17][18][19][20][21]. In particular, Guo et al reported that ADC values were negatively correlated with the higher Ki-67 index and higher mitotic count [19].…”

Section: Discussionsupporting

confidence: 89%

Diffusion‐Weighted MRI Predicts Lymph Node Metastasis and Tumor Aggressiveness in Resectable Pancreatic Neuroendocrine Tumors

et al. 2020

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Objectives The aim of this study was to identify whether diffusion-weighted magnetic resonance imaging (DW-MRI) can predict the malignant behavior of preoperative well-differentiated pancreatic neuroendocrine tumors (PanNETs). Method Forty patients with PanNETs who underwent pancreatectomy were enrolled in this study. The apparent diffusion coefficient (ADC) values were measured. Clinicopathological factors were compared in patients with high ADC and low ADC values and in patients with and without lymph node metastasis (LNM). Result The low ADC group was significantly associated with higher Ki-67 index, higher mitotic count, larger tumor size, higher rate of LNM, and venous invasion. In patients with low ADC values, the incidence of LNMs was 33.3%. In patients with high ADC values, there were no patients with LNM being 0%. A significant negative correlation was found between the mean ADC values and the Ki-67 index and between the mean ADC values and the mitotic count. In multivariate analysis, neural invasion and mean ADC values B 1458 were independent predictors of LNM. Conclusion ADC values obtained using DW-MRI in the preoperative assessment of patients with PanNETs might be a useful predictor of malignant potential, especially LNM.

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Section: Discussionsupporting

confidence: 89%

Diffusion‐Weighted MRI Predicts Lymph Node Metastasis and Tumor Aggressiveness in Resectable Pancreatic Neuroendocrine Tumors

et al. 2020

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“…In addition to the radiomics parameters associated with dynamic enhancement images, this study also found a correlation between the radiomics parameters associated with ADC maps and GIST mitosis. The ADC value, as a more widely used parameter of DWI functional imaging, can indirectly reflect the density and proliferation rate of tumor cells through the diffusion of water molecules 30 . A previous investigation showed that DWI is not inferior to PET/CT in the diagnostic rate and therapeutic evaluation of GIST 31 .…”

Section: Discussionmentioning

confidence: 99%

MRI Texture‐Based Models for Predicting Mitotic Index and Risk Classification of Gastrointestinal Stromal Tumors

Yang

Zheng

Dong

et al. 2020

Magnetic Resonance Imaging

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Background Treatment regimens and prognoses of gastrointestinal stromal tumors (GIST) are quite different for tumors in different risk categories. Accurate preoperative grading of tumors is important for avoiding under‐ or overtreatment. Purpose To develop and validate an MRI texture‐based model to predict the mitotic index and its risk classification. Study Type Retrospective. Population Ninety‐one patients with histologically‐confirmed GIST; 64 patients in a training cohort, and 27 patients in a test cohort. Field Strength/Sequence T2‐weighted imaging (T2WI), diffusion‐weighted imaging (DWI), and dynamic contrast‐enhanced three‐dimensional volumetric interpolated breath‐hold examination (3D‐VIBE) at 1.5T. Assessment GIST images were manually segmented by two independent radiologists using ITK‐SNAP software and MRI features were extracted using Pyradiomics. Two pathologists reviewed the tissue specimens of the tumors to identify the mitotic index and risk classification in consensus. Statistical Tests The least absolute shrinkage and selection operator (LASSO) regression method was used to select texture features. A logistic regression model was established based on the radiomic score (radscore), tumor location, and maximum diameter to predict tumor classification and develop a nomogram. Receiver operator characteristic (ROC) curves were used to evaluate the ability of the nomogram to distinguish between two tumors with different risk classifications, and a calibration curve was used to evaluate the consistency between the predicted risk and the actual risk. Results The texture signature achieved high efficacy in predicting the mitotic index area under the curve ([AUC], 0.906; 95% confidence interval [CI]: 0.813, 0.961). A nomogram for prediction of the risk classification of GIST, which incorporated this texture signature together with maximum tumor diameter and location, allowed good discrimination in the training cohort (AUC, 0.878; 95% CI: 0.769, 0.960) and the validation cohort (AUC, 0.903; 95% CI: 0.732, 0.922). Data Conclusion The texture‐based model can be used to predict GIST mitotic index and risk classification preoperatively. Level of Evidence 2. Technical Efficacy Stage 3

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“…G2 was favored over G1 panNETs by the presence of marked hyperintensity(p=0.01), the ADC value negative correlated with grade and was lower in G2, with a cut-off value of 0.93×10–3 mm2/sec identifying G2 with a sensitivity of 82% and specificity of 80% [73]…”

Section: Figurementioning

confidence: 99%

Imaging of pancreatic neuroendocrine tumors: recent advances, current status, and controversies

Lee

Ito

Jensen

2018

Expert Review of Anticancer Therapy

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Recently, there have been a number of advances in imaging pancreatic neuroendocrine tumors (panNETs), as well as other neuroendocrine tumors (NETs), which have had a profound effect on the management and treatment of these patients, but in some cases are also associated with controversies. Areas covered: These advances are the result of numerous studies attempting to better define the roles of both cross-sectional imaging, endoscopic ultrasound, with or without fine-needle aspiration, and molecular imaging in both sporadic and inherited panNET syndromes; the increased attempt to develop imaging parameters that correlate with tumor classification or have prognostic value; the rapidly increasing use of molecular imaging in these tumors and the attempt to develop imaging parameters that correlate with treatment/outcome results. Each of these areas and the associated controversies are reviewed. Expert commentary: There have been numerous advances in all aspects of the imaging of panNETs, as well as other NETs, in the last few years. The advances are leading to expanded roles of imaging in the management of these patients and the results being seen in panNETs/GI-NETs with these newer techniques are already being used in more common tumors.

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Value of diffusion-weighted magnetic resonance imaging in predicting World Health Organization grade in G1/G2 pancreatic neuroendocrine tumors

Cited by 14 publications

References 17 publications

Diffusion‐Weighted MRI Predicts Lymph Node Metastasis and Tumor Aggressiveness in Resectable Pancreatic Neuroendocrine Tumors

Diffusion‐Weighted MRI Predicts Lymph Node Metastasis and Tumor Aggressiveness in Resectable Pancreatic Neuroendocrine Tumors

MRI Texture‐Based Models for Predicting Mitotic Index and Risk Classification of Gastrointestinal Stromal Tumors

Imaging of pancreatic neuroendocrine tumors: recent advances, current status, and controversies

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