Prediction of Pancreatic Neuroendocrine Tumor Grade Based on CT Features and Texture Analysis.
Canellas Rodrigo,Burk Kristine S,Parakh Anushri,Sahani Dushyant V
AJR. American journal of roentgenology
OBJECTIVE:The purposes of this study were to assess whether CT texture analysis and CT features are predictive of pancreatic neuroendocrine tumor (PNET) grade based on the World Health Organization (WHO) classification and to identify features related to disease progression after surgery. MATERIALS AND METHODS:Preoperative contrast-enhanced CT images of 101 patients with PNETs were assessed. The images were evaluated for tumor location, tumor size, tumor pattern, predominantly solid or cystic composition, presence of calcification, presence of heterogeneous enhancement on contrast-enhanced images, presence of pancreatic duct dilatation, presence of pancreatic atrophy, presence of vascular involvement by the tumor, and presence of lymphadenopathy. Texture features were also extracted from CT images. Surgically verified tumors were graded according to the WHO classification, and patients underwent CT or MRI follow-up after surgical resection. Data were analyzed with chi-square tests, kappa statistics, logistic regression analysis, and Kaplan-Meier curves. RESULTS:The CT features predictive of a more aggressive tumor (grades 2 and 3) were size larger than 2.0 cm (odds ratio [OR], 3.3; p = 0.014), presence of vascular involvement (OR, 25.2; p = 0.003), presence of pancreatic ductal dilatation (OR, 6.0; p = 0.002), and presence of lymphadenopathy (OR, 6.8; p = 0.002). The texture parameter entropy (OR, 3.7; p = 0.008) was also predictive of more aggressive tumors. Differences in progression-free survival distribution were found for grade 1 versus grades 2 and 3 tumors (χ [df, 1] = 21.6; p < 0.001); for PNETs with vascular involvement (χ [df, 1] = 20.8; p < 0.001); and for tumors with entropy (spatial scale filter 2) values greater than 4.65 (χ (df, 1) = 4.4; p = 0.037). CONCLUSION:CT texture analysis and CT features are predictive of PNET aggressiveness and can be used to identify patients at risk of early disease progression after surgical resection.
10.2214/AJR.17.18417
Tumor Size on Microscopy, CT, and MRI Assessments Versus Pathologic Gross Specimen Analysis of Pancreatic Neuroendocrine Tumors.
Bian Yun,Li Jing,Jiang Hui,Fang Xu,Cao Kai,Ma Chao,Lu Jianping
AJR. American journal of roentgenology
The purpose of the present study was to assess the consistency of measurements of pancreatic neuroendocrine tumor (PNET) tumor size obtained using pre-operative imaging, pathologic gross specimen analysis, and microscopic examination of large pathologic sections; evaluate the impact of differences in pathologic and radiologic measurements of size on T categorization; and investigate the exact relationships among tumor size measurements obtained from microscopic analysis, CT, MRI, and pathologic gross specimen analysis. We enrolled 64 patients with pathologically confirmed PNETs who underwent radiologic examination between December 2016 and September 2019. Tumor sizes were measured by CT, MRI, pathologic gross specimen analysis, and microscopic examination. The relationship between the tumor sizes calculated by MRI and microscopy was analyzed using univariate and multivariate logistic regression models. The measurements of tumor sizes calculated by pathologic and radiologic assessments and CT and MRI assessments showed good concordance, but measurements calculated by microscopic analysis and other methods showed poor concordance. When T categories from pathologic gross specimen analysis were considered the reference, alterations in T category were found in the microscopic assessments of 12 of 64 patients (18.75%), CT assessments of 15 of 64 patients (23.44%), and MRI assessments of 13 of 64 patients (20.31%). In the fully adjusted model, microscopic size (β, 1.05; 95% CI, 0.98-1.12; < .001), CT size (β, 0.90; 95% CI, 0.78-1.02; < .001), and MRI size (β, 0.92; 95% CI, 0.81-1.04; < .001) were significantly correlated with gross tumor size. Tumor sizes measured by microscopy, CT, and MRI were significantly associated with the gross size of PNETs. This finding provides physicians with new tools for rapid identification of gross tumor size.
10.2214/AJR.20.23413
Application of low dose pancreas perfusion CT combined with enhancement scanning in diagnosis of pancreatic neuroendocrine tumors.
Wan Yamin,Hao Hui,Meng Saisai,Li Zhizhen,Yu Fulong,Meng Chi ,Chao Qi,Gao Jianbo
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
PURPOSE:To explore the diagnostic value of pancreatic perfusion CT combined with contrast-enhanced CT in one-time scanning (PCECT) in pancreatic neuroendocrine tumors (PNETs) and to evaluate the difference of perfusion parameters between different grades of PNETs. MATERIALS AND METHODS:From October 2016 to December 2018, forty consecutive patients with histopathological-proven PNETs were identified retrospectively that received PCECT for the preoperative PNETs evaluation. Two board certified radiologists who were blinded to the clinical data evaluated the images independently. The image characters of PNETs vs. tumor-free pancreatic parenchymal and different grades of PNETs were analyzed. RESULTS:One-time PCECT scanning had a detection rate of 89.1% for PNETs, which was higher than the detection accuracy of the perfusion CT only (83.6%). The perfusion parameters of PNETs including blood volume (BV), blood flow (BF), mean slope of increase (MSI), and capillary surface permeability (PS) were significantly increased than those of tumor-free pancreatic parenchyma (p < 0.05, respectively). For differential comparison between grade I (G1) and grade II (G2) tumors, the parameters of BF and impulse residue function (IRF) of tumor tissue were significantly higher in the G2 tumors (p < 0.05, for both). In this study, the total radiation dose of the whole PCECT scan was 16.241 ± 2.289 mSv. CONCLUSION:The one-time PCECT scan may improve the detection of PNETs according to morphological features and perfusion parameters with a relative small radiation dose. The perfusion parameters of BF and IRF may be used to help distinguish G1 and G2 tumors in the preoperative evaluation.
10.1016/j.pan.2020.10.046
Non-functional neuroendocrine tumors of the pancreas: Advances in diagnosis and management.
Cloyd Jordan M,Poultsides George A
World journal of gastroenterology
Nonfunctional neuroendocrine tumors of the pancreas (NF-PNETs) are a heterogeneous group of neoplasms. Although rare, the incidence of NF-PNETs is increasing significantly. The classification of PNETs has evolved over the past decades and is now based on a proliferation grading system. While most NF-PNETs are slow growing, tumors with more aggressive biology may become incurable once they progress to unresectable metastatic disease. Tumors of higher grade can be suspected preoperatively based on the presence of calcifications, hypoenhancement on arterial phase computed tomography, positron emission technology avidity and lack of octreotide scan uptake. Surgery is the only curative treatment and is recommended for most patients for whom complete resection is possible. Liver-directed therapies (thermal ablation, transarterial embolization) can be useful in controlling unresectable hepatic metastatic disease. In the presence of unresectable progressive disease, somatostatin analogues, everolimus and sunitinib can prolong progression-free survival. This article provides a comprehensive review of NF-PNETs with special emphasis on recent advances in diagnosis and management.
10.3748/wjg.v21.i32.9512
Pancreatic neuroendocrine tumors: Nosography, management and treatment.
Orditura Michele,Petrillo Angelica,Ventriglia Jole,Diana Anna,Laterza Maria Maddalena,Fabozzi Alessio,Savastano Beatrice,Franzese Elisena,Conzo Giovanni,Santini Luigi,Ciardiello Fortunato,De Vita Ferdinando
International journal of surgery (London, England)
Pancreatic neuroendocrine tumors (pNETs) represent about 7% of all NETs, 8.7% of gastroenteropancreatic NETs (GEP-NETs) and 1-2% of all pancreatic neoplasms. In the last two decades, the increased diagnosis of pNETs has generated great interest and the development of different classifications, grading and staging systems. Recently, several trials were performed in order to improve the knowledge of biomarkers and imaging and to provide an early diagnosis, but their role is still under debate. Nowadays, surgery represents the only curative approach for pNETs. Approximately 90% of pNETs are silent and non-functional; therefore, most patients are diagnosed in late stage and present metastatic (60%) or locally unresectable advanced disease (21%) with a poor prognosis. Not many therapeutic options are available for pNETs, with different treatments for G1-G2 and G3 tumors, because these diseases are still rare and trials are made up of few series of patients. At present, medical treatments is controversial. On these bases, we believe that a multidisciplinary team composed of surgeons, oncologists, endocrinologists, radiation oncologists, radiologists, pathologists and medicals nuclear is required. This paper presents a review of present state-of-the-art in the field of pNETs.
10.1016/j.ijsu.2015.12.052
Neuroendocrine tumours: the role of imaging for diagnosis and therapy.
van Essen Martijn,Sundin Anders,Krenning Eric P,Kwekkeboom Dik J
Nature reviews. Endocrinology
In patients with neuroendocrine tumours (NETs), a combination of morphological imaging and nuclear medicine techniques is mandatory for primary tumour visualization, staging and evaluation of somatostatin receptor status. CT and MRI are well-suited for discerning small lesions that might escape detection by single photon emission tomography (SPECT) or PET, as well as for assessing the local invasiveness of the tumour or the response to therapy. Somatostatin receptor imaging, by (111)In-pentetreotide scintigraphy or PET with (68)Ga-labelled somatostatin analogues, frequently identifies additional lesions that are not visible on CT or MRI scans. Currently, somatostatin receptor scintigraphy with (111)In-pentetreotide is the more frequently available of the two techniques to determine somatostatin receptor expression and is needed to select patients for peptide receptor radionuclide therapy. In the future, because of its higher sensitivity, PET with (68)Ga-labelled somatostatin analogues is expected to replace somatostatin receptor scintigraphy. Whereas (18)F-FDG-PET is only used in high-grade neuroendocrine cancers, PET-CT with (18)F-dihydroxy-L-phenylalanine or (11)C-5-hydroxy-L-tryptophan is a useful problem-solving tool and could be considered for the evaluation of therapy response in the future. This article reviews the role of imaging for the diagnosis and management of intestinal and pancreatic NETs. Response evaluation and controversies in NET imaging will also be discussed.
10.1038/nrendo.2013.246
The Role of PET/CT in the Imaging of Pancreatic Neoplasms.
Duan Heying,Baratto Lucia,Iagaru Andrei
Seminars in ultrasound, CT, and MR
Pancreas cancer is a complex disease and its prognosis is related to the origin of the tumor cell as well as the stage of disease at the time of diagnosis. Pancreatic adenocarcinomas derive from the exocrine pancreas and are the fourth leading cause of cancer-related deaths in the United States, while well-differentiated pancreatic neuroendocrine tumors (pNETs) derived from the endocrine part of the pancreas are rare and characterized by a slow growth and good life expectancy. Surgery is the only curative treatment approach, and an accurate assessment of resectability is of paramount importance in order to avoid futile procedures. The role of molecular imaging with positron emission tomography and computed tomography ranges from indispensable for pNETs to controversial for certain scenarios in pancreatic adenocarcinomas. This review article aims to overview molecular pancreatic imaging.
10.1053/j.sult.2019.04.006
Diagnostic imaging of pancreatic neuroendocrine neoplasms (pNEN): tumor detection, staging, prognosis, and response to treatment.
Baur Alexander D J,Pavel Marianne,Prasad Vikas,Denecke Timm
Acta radiologica (Stockholm, Sweden : 1987)
Pancreatic neuroendocrine neoplasms (pNEN) are rare malignancies arising from neuroendocrine cells of the pancreas. Functional tumors can present with specific clinical syndromes due to hormonal secretion. These tumors can present as incidental findings on imaging performed for unrelated purposes or they are diagnosed when workup is initiated in patients with specific syndromes or metastases. This article presents an overview of available imaging techniques focusing on computed tomography and magnetic resonance imaging. Recommendations regarding examination protocols are given. Typical imaging features of pNEN and metastases are described. Their potential value for the evaluation of prognosis as well as tumor response under treatment is discussed.
10.1177/0284185115579932
Pancreatic neuroendocrine tumors: MR imaging features preoperatively predict lymph node metastasis.
Sun Haitao,Zhou Jianjun,Liu Kai,Shen Tingting,Wang Xingxing,Wang Xiaolin
Abdominal radiology (New York)
PURPOSES:Predictive factors of lymph node metastasis (LNM) in pancreatic neuroendocrine tumors (pNETs) are not well established. We sought to identify the value of MR imaging features in preoperatively predicting the lymph node metastasis of pNETs. MATERIALS AND METHODS:In this study, we enrolled 108 consecutive patients with pNETs between January 2009 and June 2018. MR morphologic features and quantitative data were evaluated. Predictors of LNM were evaluated using univariate and multivariate logistic regression models. RESULTS:A total of 108 patients with pNETs were finally enrolled, including 82 LNM-negative and 26 LNM-positive patients. Features significantly related to the LNM of pNETs at univariate analysis were tumor size > 2 cm (P = 0.003), Ki-67 > 5% (P = 0.002), non-enhancement pattern (P < 0.001), apparent diffusion coefficient value (P < 0.001), main pancreatic duct dilation (P < 0.001) and pancreatic atrophy (P = 0.032) and extrapancreatic tumor spread (P = 0.001), CNRs during arterial, portal and delay phase (P = 0.005, 0.047, and 0.045, respectively), and histological classification (P = 0.006). At multivariate analysis, non-enhancement pattern (P = 0.019; odds ratio, 6.652; 95% CI 1.369, 32.321) and main pancreatic duct dilation (P = 0.018; odds ratio, 6.745; 95% CI 1.379, 32.991) were independent risk factors for predicting the LNM of pNETs. CONCLUSION:The non-enhancement characteristic and main pancreatic duct dilation appear to be linked with LNM in pNETs. These radiological predictors can be easily obtained preoperatively, and may help to avoid missing pNETs with a high risk of LNM.
10.1007/s00261-018-1863-y
Comparison of imaging-based and pathological dimensions in pancreatic neuroendocrine tumors.
Paiella Salvatore,Impellizzeri Harmony,Zanolin Elisabetta,Marchegiani Giovanni,Miotto Marco,Malpaga Anna,De Robertis Riccardo,D'Onofrio Mirko,Rusev Borislav,Capelli Paola,Cingarlini Sara,Butturini Giovanni,Davì Maria Vittoria,Amodio Antonio,Bassi Claudio,Scarpa Aldo,Salvia Roberto,Landoni Luca
World journal of gastroenterology
AIM:To establish the ability of magnetic resonance (MR) and computer tomography (CT) to predict pathologic dimensions of pancreatic neuroendocrine tumors (PanNET) in a caseload of a tertiary referral center. METHODS:Patients submitted to surgery for PanNET at the Surgical Unit of the Pancreas Institute with at least 1 preoperative imaging examination (MR or CT scan) from January 2005 to December 2015 were included and data retrospectively collected. Exclusion criteria were: multifocal lesions, genetic syndromes, microadenomas or mixed tumors, metastatic disease and neoadjuvant therapy. Bland-Altman (BA) and Mountain-Plot (MP) statistics were used to compare size measured by each modality with the pathology size. Passing-Bablok (PB) regression analysis was used to check the agreement between MR and CT. RESULTS:Our study population consisted of 292 patients. Seventy-nine (27.1%) were functioning PanNET. The mean biases were 0.17 ± 7.99 mm, 1 ± 8.51 mm and 0.23 ± 9 mm, 1.2 ± 9.8 mm for MR and CT, considering the overall population and the subgroup of non-functioning- PanNET, respectively. Limits of agreement (LOA) included the vast majority of observations, indicating a good agreement between imaging and pathology. The MP further confirmed this finding and showed that the two methods are unbiased with respect to each other. Considering ≤ 2 cm non-functioning-PanNET, no statistical significance was found in the size estimation rate of MR and CT ( = 0.433). PBR analysis did not reveal significant differences between MR, CT and pathology. CONCLUSION:MR and CT scan are accurate and interchangeable imaging techniques in predicting pathologic dimensions of PanNET.
10.3748/wjg.v23.i17.3092