Neuroendocrine tumor presenting like lymphoma: a case report

INTRODUCTION: Neuroendocrine tumors are a rare but diverse group of malignancies that arise in a wide range of organ systems, including the mediastinum. Differential diagnosis includes other masses arising in the middle mediastinum such as lymphoma, pericardial, bronchogenic and enteric cysts, metastatic tumors, xanthogranuloma, systemic granuloma, diaphragmatic hernia, meningocele and paravertebral abscess. CASE PRESENTATION: We present a case of 42-year-old Caucasian man with a neuroendocrine tumor of the middle-posterior mediastinum and liver metastases, which resembled a lymphoma on magnetic resonance imaging. CONCLUSION: The differential diagnosis in patients with mediastinal masses and liver lesions should include neuroendocrine tumor

Pleomorphic adenoma of the breast.

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Duodenal Duplication Cyst: A Rare Case Report

Gastrointestinal duplication cysts are infrequent congenital abnormalities. 2% to 12% of these abnormalities are localized in correspondence of the duodenum. This disease rarely remains asymptomatic until adulthood. We present a case of A 62-year-old woman with intermittent upper abdominal pain and nausea, describing the diagnostic and therapeutic route

Our Experience in Percutaneous Ablative Treatment of Renal T1a E T1b Lesions: Results from 90 Patients Treated with Microwave Ablation, Radiofrequency Ablation and Cryoablation

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Clinical Efficacy and Economic Impact of an Augmented Reality Navigation System: Experience On 498 Percutaneous Computed Tomogaphy-Guided Pulmonary Biopsies

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Combined Trans-arterial Embolization and Microwave Ablation for the Treatment of >3 cm Liver Metastases

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Combined Antegrade and Retrograde Approach in Iatrogenic Ureteral Injuries: The Rendezvous Technique

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3T MRI-radiomic approach to predict for lymph node status in breast cancer patients

Simple SummaryBreast cancer is the most common cancer in women worldwide. The axillary lymph node status is one of the main prognostic factors. Currently, the methods to define the lymph node status are invasive and not without sequelae (from biopsy to lymphadenectomy). Radiomics is a new tool, and highly varied, but with high potential that has already shown excellent results in numerous fields of application. In our study, we have developed a classifier validated on a relatively large number of patients, which is able to predict lymph node status using a combination of patients clinical features, primary breast cancer histological features and radiomics features based on 3 Tesla post contrast-MR images. This approach can accurately select breast cancer patients who may avoid unnecessary biopsy and lymphadenectomy in a non-invasive way.Background: axillary lymph node (LN) status is one of the main breast cancer prognostic factors and it is currently defined by invasive procedures. The aim of this study is to predict LN metastasis combining MRI radiomics features with primary breast tumor histological features and patients' clinical data. Methods: 99 lesions on pre-treatment contrasted 3T-MRI (DCE). All patients had a histologically proven invasive breast cancer and defined LN status. Patients' clinical data and tumor histological analysis were previously collected. For each tumor lesion, a semi-automatic segmentation was performed, using the second phase of DCE-MRI. Each segmentation was optimized using a convex-hull algorithm. In addition to the 14 semantics features and a feature ROI volume/convex-hull volume, 242 other quantitative features were extracted. A wrapper selection method selected the 15 most prognostic features (14 quantitative, 1 semantic), used to train the final learning model. The classifier used was the Random Forest. Results: the AUC-classifier was 0.856 (label = positive or negative). The contribution of each feature group was lower performance than the full signature. Conclusions: the combination of patient clinical, histological and radiomics features of primary breast cancer can accurately predict LN status in a non-invasive way