Search results for " Prostate"
showing 10 items of 177 documents
Stereotactic body radiotherapy in oligoprogressive metastatic castration-resistant prostate cancer during abiraterone or enzalutamide
2022
Introduction: This monocentric, single-arm, retrospective study investigated the role of stereotactic body radiotherapy in patients with metastatic castration resistant prostate cancer who experienced oligoprogression during androgen receptor targeted agents. Methods: We retrospectively enrolled metastatic castration resistant prostate cancer patients treated with androgen receptor targeted agents between December 2016 and January 2022. All patients experienced an oligoprogression (defined as the appearance and/or the progression of ⩽5 bone or nodal or soft tissue metastases) during treatment with androgen receptor targeted agents and received stereotactic body radiotherapy upon oligoprogre…
Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging
2017
Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…
Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging
2021
Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardwar…
Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks
2021
[EN] Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was tra…
Fully automatic multispectral MR image segmentation of prostate gland based on the fuzzy C-means clustering algorithm
2017
Prostate imaging is a very critical issue in the clinical practice, especially for diagnosis, therapy, and staging of prostate cancer. Magnetic Resonance Imaging (MRI) can provide both morphologic and complementary functional information of tumor region. Manual detection and segmentation of prostate gland and carcinoma on multispectral MRI data is not easily practicable in the clinical routine because of the long times required by experienced radiologists to analyze several types of imaging data. In this paper, a fully automatic image segmentation method, exploiting an unsupervised Fuzzy C-Means (FCM) clustering technique for multispectral T1-weighted and T2-weighted MRI data processing, is…
Radiomics: A New Biomedical Workflow to Create a Predictive Model
2020
‘Radiomics’ is utilized to improve the prediction of patient overall survival and/or outcome. Target segmentation, feature extraction, feature selection, and classification model are the fundamental blocks of a radiomics workflow. Nevertheless, these blocks can be affected by several issues, i.e. high inter- and intra-observer variability. To overcome these issues obtaining reproducible results, we propose a novel radiomics workflow to identify a relevant prognostic model concerning a real clinical problem. In the specific, we propose an operator-independent segmentation system with the consequent automatic extraction of radiomics features, and a novel feature selection approach to create a…
Novel σ1 antagonists designed for tumor therapy: Structure – activity relationships of aminoethyl substituted cyclohexanes
2021
Abstract Depending on the substitution pattern and stereochemistry, 1,3-dioxanes 1 with an aminoethyl moiety in 4-position represent potent σ1 receptor antagonists. In order to increase the stability, a cyclohexane ring first replaced the acetalic 1, 3-dioxane ring of 1. A large set of aminoethyl substituted cyclohexane derivatives was prepared in a six-step synthesis. All enantiomers and diastereomers were separated by chiral HPLC at the stage of the primary alcohol 7, and their absolute configuration was determined by CD spectroscopy. Neither the relative nor the absolute configuration had a large impact on the σ1 affinity. The highest σ1 affinity was found for cis-configured benzylamines…
Multiparametric MRI-based Dosimetric Parameters Best Predict Short-term Time Course of PSA After Iodine 125 Permanent Prostate Implantation for Local…
2012
International audience; D90% and V150% of the entire prostate are recognized as the best dosimetric predictors of outcome after 125 I permanent prostate implantation (PPI). The purpose of this study was 2-fold: 1) to determine the relationship between dose-volume parameters of the Dominant Intraprostatic Lesion (DIL) when compared to the prostate and early biochemical outcome after PPI; 2) to define if dose-volume parameters of the central gland (CG), the peripheral zone (PZ) and the DIL could best predict PSA bounce occurrence. The time course of PSA and mechanisms of bounces still remain unclear after PPI. Patients who had a higher dose in the DIL had a worse PSA level at 1 year which is …
USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
2019
Prostate cancer is the most common malignant tumors in men but prostate Magnetic Resonance Imaging (MRI) analysis remains challenging. Besides whole prostate gland segmentation, the capability to differentiate between the blurry boundary of the Central Gland (CG) and Peripheral Zone (PZ) can lead to differential diagnosis, since tumor's frequency and severity differ in these regions. To tackle the prostate zonal segmentation task, we propose a novel Convolutional Neural Network (CNN), called USE-Net, which incorporates Squeeze-and-Excitation (SE) blocks into U-Net. Especially, the SE blocks are added after every Encoder (Enc USE-Net) or Encoder-Decoder block (Enc-Dec USE-Net). This study ev…
Adherence to Guidelines among Italian Urologists on Imaging Preoperative Staging of Low-Risk Prostate Cancer: Results from the MIRROR (Multicenter It…
2011
Objective. A number of evidence-based guidelines for diagnosis and management of prostate cancer have been published. The aim of this study is to evaluate the adherence of Italian urologists to the guidelines concerning the preoperative imaging staging of prostate cancer.Methods. In October 2007 a multicentric observational perspective study called Multicentric Italian Report on Radical prostatectomy Outcome and Research (MIRROR) was started in 135 Italian urology centers. Recruitment was closed in December 2008 and 2,408 cases were collected. In this paper we have taken into consideration all examinations carried out for preoperative imaging staging, evaluating compliance with the recommen…