0000000000647569

AUTHOR

Mauro Calamia

A Predictive System to Classify Preoperative Grading of Rectal Cancer Using Radiomics Features

Although preoperative biopsy of rectal cancer (RC) is an essential step for confirmation of diagnosis, it currently fails to provide prognostic information to the clinician beyond a rough estimation of tumour grade. In this study we used a risk classification to stratified patient in low-risk and high-risk patients in relation to the disease free survival and the overall survival using histopathological post-operative features. The purpose of this study was to evaluate if low-risk and high-risk RC can be distinguished using a CT-based radiomics model. We retrospectively reviewed the preoperative abdominal contrast-enhanced CT of 40 patients with RC. CT portal-venous phase was used for manua…

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RUOLO DEL COEFFICIENTE DI DIFFUSIONE APPARENTE (ADC) NELLO STUDIO DELLA PROSTATA IN RISONANZA MAGNETICA (RM)

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The cheating liver: imaging of focal steatosis and fatty sparing

ABSTRACT: Focal steatosis and fatty sparing are a frequent finding in liver imaging, and can mimic solid lesions. Liver regional variations in the degree of fat accumulation can be related to vascular anomalies, metabolic disorders, use of certain drugs or coexistence of hepatic masses. CT and MRI are the modalities of choice for the noninvasive diagnosis of hepatic steatosis. Knowledge of CT and MRI appearance of focal steatosis and fatty sparing is crucial for an accurate diagnosis, and to rule-out other pathologic processes. This paper will review the CT and MRI techniques for the diagnosis of hepatic steatosis and the CT and MRI features of common and uncommon causes of focal steatosis …

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Radiomics and Prostate MRI: Current Role and Future Applications

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine …

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TYPICAL AND ATYPICAL HEPATOBILIARY PHASE (HB PHASE) APPEARANCES OF FOCAL NODULAR HYPERPLASIA (FNH)

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Role of apparent diffusion coefficient values in prostate diseases characterization on diffusion-weighted magnetic resonance imaging.

BACKGROUND: To evaluate if normal and pathological prostate tissue can be distinguished by using apparent diffusion coefficient (ADC) values on magnetic resonance imaging (MRI) and to understand if it is possible to differentiate among pathological prostate tissues using ADC values.METHODS:Our population consisted in 81 patients (mean age 65.4 years) in which 84 suspicious areas were identified. Regions of interest were placed over suspicious areas, detected on MRI, and over areas with normal appearance, and ADC values were recorded. Statistical differences between ADC values of suspicious and normal areas were evaluated. Histopathological diagnosis, obtained from targeted biopsy using MRI-…

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Deep Learning Network for Segmentation of the Prostate Gland With Median Lobe Enlargement in T2-weighted MR Images: Comparison With Manual Segmentation Method

Purpose: Aim of this study was to evaluate a fully automated deep learning network named Efficient Neural Network (ENet) for segmentation of prostate gland with median lobe enlargement compared to manual segmentation. Materials and Methods: One-hundred-three patients with median lobe enlargement on prostate MRI were retrospectively included. Ellipsoid formula, manual segmentation and automatic segmentation were used for prostate volume estimation using T2 weighted MRI images. ENet was used for automatic segmentation; it is a deep learning network developed for fast inference and high accuracy in augmented reality and automotive scenarios. Student t-test was performed to compare prostate vol…

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