672 research outputs found

    Contrast-enhanced harmonic endoscopic ultrasound using time–intensity curve analysis predicts pathological grade of pancreatic neuroendocrine neoplasm

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    PURPOSE: Histological grading is important for the treatment algorithm in pancreatic neuroendocrine neoplasms (PNEN). The present study examined the efficacy of contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) and time-intensity curve (TIC) analysis of PNEN diagnosis and grading. METHODS: TIC analysis was performed in 30 patients using data obtained from CH-EUS, and a histopathological diagnosis was made via EUS-guided fine-needle aspiration or surgical resection. The TIC parameters were analyzed by dividing them into G1/G2 and G3/NEC groups. Then, patients were classified into non-aggressive and aggressive groups and evaluated. RESULTS: Twenty-six patients were classified as G1/G2, and four as G3/NEC. From the TIC analysis, five parameters were obtained (I: echo intensity change, II: time for peak enhancement, III: speed of contrast, IV: decrease rate for enhancement, and V: enhancement ratio for node/pancreatic parenchyma). Three of these parameters (I, IV, and V) showed high diagnostic performance. Using the cutoff value obtained from the receiver-operating characteristic (ROC) analysis, the correct diagnostic rates of parameters I, IV, and V were 96.7%, 100%, and 100%, respectively, between G1/G2 and G3/NEC. A total of 21 patients were classified into the non-aggressive group, and nine into the aggressive group. Using the cutoff value obtained from the ROC analysis, the accurate diagnostic rates of I, IV, and V were 86.7%, 86.7%, and 88.5%, respectively, between the non-aggressive and aggressive groups. CONCLUSION: CH-EUS and TIC analysis showed high diagnostic accuracy for grade diagnosis of PNEN. Quantitative perfusion analysis is useful to predict PNEN grade diagnosis preoperatively

    Mesenteric fibrosis in neuroendocrine tumors:An entangled conundrum

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    Mesenteric fibrosis in neuroendocrine tumors:An entangled conundrum

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    A Tri-Marker Proliferation Index Predicts Biochemical Recurrence after Surgery for Prostate Cancer

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    Prostate cancer exhibits tremendous variability in clinical behavior, ranging from indolent to lethal disease. Better prognostic markers are needed to stratify patients for appropriately aggressive therapy. By expression profiling, we can identify a proliferation signature variably expressed in prostate cancers. Here, we asked whether one or more tissue biomarkers might capture that information, and provide prognostic utility. We assayed three proliferation signature genes: MKI67 (Ki-67; also a classic proliferation biomarker), TOP2A (DNA topoisomerase II, alpha), and E2F1 (E2F transcription factor 1). Immunohistochemical staining was evaluable on 139 radical prostatectomy cases (in tissue microarray format), with a median clinical follow-up of eight years. Each of the three proliferation markers was by itself prognostic. Notably, combining the three markers together as a “proliferation index” (0 or 1, vs. 2 or 3 positive markers) provided superior prognostic performance (hazard ratio = 2.6 (95% CI: 1.4–4.9); P = 0.001). In a multivariate analysis that included preoperative serum prostate specific antigen (PSA) levels, Gleason grade and pathologic tumor stage, the composite proliferation index remained a significant predictor (P = 0.005). Analysis of receiver-operating characteristic (ROC) curves confirmed the improved prognostication afforded by incorporating the proliferation index (compared to the clinicopathologic data alone). Our findings highlight the potential value of a multi-gene signature-based diagnostic, and define a tri-marker proliferation index with possible utility for improved prognostication and treatment stratification in prostate cancer

    Dynamic computed tomography is useful for prediction of pathological grade in pancreatic neuroendocrine neoplasm

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    BACKGROUND AND AIM: Pathological grading is important in defining the therapeutic strategy in pancreatic neuroendocrine neoplasm (PNEN) but is difficult for unresectable cases. Endoscopic ultrasound (EUS)-guided fine needle aspiration (FNA) is useful in the diagnosis of PNEN, but its usefulness for pathological grading is not well established. No studies have examined the diagnostic ability of dynamic computed tomography (CT) for pathological grading of PNEN. We investigated the usefulness of EUS-FNA and dynamic CT in the diagnosis and pathological grading of PNEN. METHODS: In this retrospective study, 39 PNEN patients finally diagnosed via EUS-FNA and/or surgical resection underwent dynamic CT. Pathological samples were diagnosed based on WHO2010; staging was based on the European Neuroendocrine Tumor Society classification. The proportion of the quantification value in the tumor to the pancreatic parenchyma in arterial phase was defined as the CT ratio. Immunohistochemical staining with CD31 was performed to evaluate microvessel density (MVD). We evaluated the relationship between pathological grade, CT ratio, and MVD. RESULTS: By using EUS-FNA, 35 of 39 (90%) cases were diagnosed as PNEN. As for pathological grade, 15 of 35 (43%) cases could be identified correctly. CT ratio could predict pathological Grade 3 disease. The sensitivity, specificity, and diagnostic accuracy were 100%, 94%, and 95%. MVD was significantly correlated with CT ratio (r = 0.83, P < 0.0001) and pathological grade (P = 0.0074). CONCLUSIONS: Computed tomography ratio has a relationship with pathological grade in PNEN, which would help decide therapeutic strategy in unresectable cases and cases in which pathological grading is difficult
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