Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented.

Early Assessment of Colorectal Cancer Patients with Liver Metastases Treated with Antiangiogenic Drugs: The Role of Intravoxel Incoherent Motion in Diffusion-Weighted Imaging.

Purpose: To assess the feasibility and effectiveness of quantitative intravoxel incoherent motion (IVIM) of Diffusion-weighted imaging (DWI) in the assessment of liver metastases treated with targeted chemotherapy agents.

Methods: 12 patients with unresectable liver metastases from colorectal cancer were enrolled and received neoadjuvant FOLFIRI (5-fluorouracil, leucovorin, irinotecan) plus bevacizumab therapy. DWI was performed for 36 metastases at baseline and after 14 days from starting the treatment.

Integration of DCE-MRI and DW-MRI Quantitative Parameters for Breast Lesion Classification.

Objective: The purpose of our study was to evaluate the diagnostic value of an imaging protocol combining dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) in patients with suspicious breast lesions.

Materials And Methods: A total of 31 breast lesions (15 malignant and 16 benign proved by histological examination) in 26 female patients were included in this study. For both DCE-MRI and DW-MRI model free and model based parameters were computed pixel by pixel on manually segmented ROIs.

Risk management in magnetic resonance: failure mode, effects, and criticality analysis.

The aim of the study was to perform a risk management procedure in "Magnetic Resonance Examination" process in order to identify the critical phases and sources of radiological errors and to identify potential improvement projects including procedures, tests, and checks to reduce the error occurrence risk. In this study we used the proactive analysis "Failure Mode Effects Criticality Analysis," a qualitative and quantitative risk management procedure; has calculated Priority Risk Index (PRI) for each activity of the process; have identified, on the PRI basis, the most critical activities and, for them, have defined improvement projects; and have recalculated the PRI after implementation of improvement projects for each activity. Time stop and audits are performed in order to control the new procedures.