Insights Into Imaging

This prognostic model combining #radiomics and hematologic parameters can predict overall survival in esophageal squamous cell carcinoma patients following definitive chemoradiotherapy (dCRT). (Jinfeng Cui et al.) 🔗 https://buff.ly/3TDqZSJ #InsightsIntoImaging #RadiologyAndBeyond #OutcomePrediction

In this Educational Review, Esra Akçiçek et al. discuss the challenges in differential diagnosis of multiple pulmonary nodules caused by metastasis from those caused by infections, inflammation, or rare benign diseases. Key factors such as size, density, location, and growth rate help in diagnosis, alongside clinical and lab data. #InsightsIntoImaging 🔗 https://buff.ly/3ZjaIFm

A new ultra-high gradient 3.0-T MRI system enables a super-fast, high-quality biparametric MRI (bpMRI) protocol for #prostate imaging. Reducing scan time by 62%, bpMRI shows excellent overall image quality, making it a promising tool for faster, reliable #ProstateCancer detection. (Leon M. Bischoff et al.) #InsightsIntoImaging #PIRADS 🔗 https://buff.ly/49JzZxq

A #DeepLearning (DL)-based prostate segmentation algorithm, with conformal prediction (CP), improves the accuracy and reliability of DL-based prostate volume (PV) calculation in patients at risk of #ProstateCancer. (Marius Gade et al.) #InsightsIntoImaging 🔗 https://buff.ly/49FWaoj

🕯️ The 4th Sunday of #rAdvent has arrived and we're delighted to share this wonderful article from #InsightsIntoImaging with you, courtesy of Social Media Editorial team member Gennaro D'Anna. 🎁 Now let's unpack this box! #Radiomics research has immense potential to revolutionize medical imaging, but its clinical translation is often hindered by methodological issues. To address this, a large international team of experts developed the METhodological RadiomICs Score (METRICS), a comprehensive quality assessment tool tailored for radiomics studies. Key highlights: ❄️ 30 Items Across 9 Categories: #METRICS evaluates essential aspects like study design, imaging data, feature extraction, and open science practices. ❄️ Expert-Weighted Criteria: Each item is weighted based on importance, ensuring a nuanced evaluation. ❄️ Versatility: The tool accommodates both handcrafted radiomics and #DeepLearning-based approaches. ❄️ Accessibility: A user-friendly online platform streamlines scoring and provides community feedback. This initiative, supported by EuSoMII - European Society of Medical Imaging Informatics, aims to standardize and elevate the quality of radiomics research, paving the way for better reproducibility and clinical adoption. 🔗 https://buff.ly/48OrdwQ 🎄 ⛄ 🎅 Thank you for joining us the last four weeks! To check out all four holiday articles, click on #rAdvent! Happy Holidays to you and yours! #ESRJournals #Radiology #Imaging

Contrast-enhanced US (CEUS) Bosniak classification shows substantial intra- and inter-rater reproducibility and good diagnostic performance for predicting malignancy in cystic renal masses. (Dong-dong Jin et al.) #InsightsIntoImaging 🔗 https://buff.ly/4inlLWS

📚✨ Highlights from Session 3: The ESR Journal Family ✨📚 Moderated by Marc Dewey, MD and Ioana-Andreea Gheonea, this session showcased the incredible growth and innovation across the ESR journals: ✅ European Radiology: 4.7 impact factor, 5,650 projected submissions. ✅ Insights into Imaging & European Radiology Experimental: Leading with high-quality research and multidisciplinary initiatives like ESR Bridges and ESR Essentials. 📈 Challenges such as reviewer fatigue and evolving impact factor calculations were addressed with strategic solutions, including AI integration (JuiSci app) and new incentives for reviewers. 👏 Big thanks to Bernd Hamm for outlining the achievements and future plans for radiology publishing! What part of these updates excites you most? Share your thoughts below! 💬 #ESRALM2024

Radiomics, especially peritumoral features, can improve predictive accuracy of overall survival in proximal esophageal cancer and reveal insights into lipid metabolism linked to radioresistance, highlighting its potential regarding personalized treatment strategies. (Linrui Li et al.) #InsightsIntoImaging #Radiomics 🔗 https://buff.ly/3ZLMSUd

In #CervicalCancer, MRI-derived tumor size was the only independent predictor of survival. More specifically, MAXimaging ≥ 4.0 cm was shown to be the optimal cutoff for predicting long-term disease-specific survival in cervical cancer. (Njål Lura et al.) 🔗 https://buff.ly/3ZlrRi1 #InsightsIntoImaging #RadiologyAndBeyond #OutcomePrediction

Hepatic #steatosis impacts liver #stiffness measurement (LSM) values in chronic hepatitis B patients, but doesn't affect the diagnostic efficiency of LSM to stage liver fibrosis. Furthermore, using higher cut-off values can improve LSM's diagnostic accuracy regarding steatosis. (Zhiyuan Chen et al.) #InsightsIntoImaging 🔗 https://buff.ly/3OQwDz6