Initial experience with a next-generation low-field MRI scanner: Potential for breast imaging?

PURPOSE: Broader clinical adoption of breast magnetic resonance imaging (MRI) faces challenges such as limited availability and high procedural costs. Low-field technology has shown promise in addressing these challenges. We report our initial experience using a next-generation scanner for low-field breast MRI at 0.55T. METHODS: This initial cases series was part of an institutional review board-approved prospective study using a 0.55T scanner (MAGNETOM Free.Max, Siemens Healthcare, Erlangen/Germany: height < 2 m, weight < 3.2 tons, no quench pipe) equipped with a seven-channel breast coil (Noras, Höchberg/Germany). A multiparametric breast MRI protocol consisting of dynamic T1-weighted, T2-weighted, and diffusion-weighted sequences was optimized for 0.55T. Two radiologists with 12 and 20 years of experience in breast MRI evaluated the examinations. RESULTS: Twelve participants (mean age: 55.3 years, range: 36-78 years) were examined. The image quality was diagnostic in all examinations and not impaired by relevant artifacts. Typical imaging phenotypes were visualized. The scan time for a complete, non-abbreviated breast MRI protocol ranged from 10:30 to 18:40 min. CONCLUSION: This initial case series suggests that low-field breast MRI is feasible at diagnostic image quality within an acceptable examination time.

Motivation and success factors in radiological research in Germany - results of a survey by the Methodology and Research Working Group of the German Radiological Society. / Motivation und Erfolgsfaktoren in der radiologischen Forschung in Deutschland ­ Ergebnisse einer Umfrage der AG Methodik und Forschung.

Investigation of motivation and identification of success factors in radiology research in Germany.Using a German online survey (54 questions, period: 3.5 months), demographic aspects, intrinsic and extrinsic success characteristics, as well as personal and organizational success factors were surveyed based on a career success model. The survey results were reported descriptively. The correlations between success factors and success characteristics were examined using linear, binary-logistic, and multinomial regression models.176 people (164 academically active, 10 not academically active) answered the survey. Most participants (80%, 139/174) worked at a university hospital. 32% had privatdozent or professor as their highest academic title (56/173). The researchers' main motivation was intrinsic interest in research (55%, 89/163), followed by a desire to increase their own career opportunities (25%, 41/163). The following were identified as factors for intrinsic success: i) support from department management (estimate=ß=0.26, p<0.001), ii) good work-life balance (ß=0.37, p<0.001), and iii) the willingness to pursue science even after reaching the career goal (ß=0.16, p<0.016). Relevant factors for extrinsic scientific success were mentoring, protected research time, and activities in professional societies.Researchers in German radiology are mainly intrinsically motivated. Factors known from the literature that determine intrinsic and extrinsic scientific success were confirmed in this study. Knowledge of these factors allows targeted systematic support and could thus increase scientific success in German radiology. · Main motivation for German radiology research is intrinsic interest, followed by career opportunities.. · Factors for intrinsic scientific success are good work-life balance and support by department management.. · Factors for extrinsic scientific success are mentoring, activities in professional societies, and protected research time.. · Wegner F, Heinrichs H, Stahlmann K et al. Motivation and success factors in radiological research in Germany - results of a survey by the Methodology and Research Working Group of the German Radiological Society. Fortschr Röntgenstr 2024; DOI 10.1055/a-2350-0023.

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII.

PURPOSE: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. METHODS: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. RESULT: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. CONCLUSION: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. CRITICAL RELEVANCE STATEMENT: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. KEY POINTS: • A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).