Using an elliptical signal model, an analytical solution to the bSSFP banding problem has been found and demonstrated with simulation as well as phantom and in vivo experiments.
Although 7-T MRI has recently received approval for use in clinical patient care, there are distinct safety issues associated with this relatively high magnetic field. Forces on metallic implants and radiofrequency power deposition and heating are safety considerations at 7 T. Patient bioeffects such as vertigo, dizziness, false feelings of motion, nausea, nystagmus, magnetophosphenes, and electrogustatory effects are more common and potentially more pronounced at 7 T than at lower field strengths. Herein the authors review safety issues associated with 7-T MRI. The rationale for safety concerns at this field strength are discussed as well as potential approaches to mitigate risk to patients and health care professionals.
Purpose
Soft tissue sarcomas (STS) represent a heterogeneous group of diseases, and selection of individualized treatments remains a challenge. The goal of this study was to determine whether radiomic features extracted from magnetic resonance (MR) images are independently associated with overall survival (OS) in STS.
Methods and Materials
This study analyzed 2 independent cohorts of adult patients with stage II-III STS treated at center 1 (N = 165) and center 2 (N = 61). Thirty radiomic features were extracted from pretreatment T1-weighted contrast-enhanced MR images. Prognostic models for OS were derived on the center 1 cohort and validated on the center 2 cohort. Clinical-only (C), radiomics-only (R), and clinical and radiomics (C+R) penalized Cox models were constructed. Model performance was assessed using Harrell's concordance index.
Results
In the R model, tumor volume (hazard ratio [HR], 1.5) and 4 texture features (HR, 1.1-1.5) were selected. In the C+R model, both age (HR, 1.4) and grade (HR, 1.7) were selected along with 5 radiomic features. The adjusted c-indices of the 3 models ranged from 0.68 (C) to 0.74 (C+R) in the derivation cohort and 0.68 (R) to 0.78 (C+R) in the validation cohort. The radiomic features were independently associated with OS in the validation cohort after accounting for age and grade (HR, 2.4;
P
= .009).
Conclusions
This study found that radiomic features extracted from MR images are independently associated with OS when accounting for age and tumor grade. The overall predictive performance of 3-year OS using a model based on clinical and radiomic features was replicated in an independent cohort. Optimal models using clinical and radiomic features could improve personalized selection of therapy in patients with STS.
The need for a guidance document on MR safe practices arose from a growing awareness of the MR environment's potential risks and adverse event reports involving patients, equipment, and personnel. Initially published in 2002, the American College of Radiology White Paper on MR Safety established de facto industry standards for safe and responsible practices in clinical and research MR environments. The most recent version addresses new sources of risk of adverse events, increases awareness of dynamic MR environments, and recommends that those responsible for MR medical director safety undergo annual MR safety training. With regular updates to these guidelines, the latest MR safety concerns can be accounted for to ensure a safer MR environment where dangers are minimized.
Level of Evidence: 1
Technical Efficacy Stage: 5
J. Magn. Reson. Imaging 2020;51:331–338.
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