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#InsightsIntoImaging is a gold open access journal owned by the European Society of Radiology and edited by Editor-in-Chief, Paola Clauser. 🟣 https://www.i3-journal.org/ Social Media Editor: @cannellaroberto.bsky.social
Insights into Imaging





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🫁🔍 A large multicenter study shows that density heterogeneity is a powerful predictor for distinguishing malignant from benign subcentimeter solid pulmonary nodules.
Insights into Imaging
How should neuroradiology reports be written to best support clinical decision-making? 🧠📄 A new survey study at a tertiary neuroscience center highlights a clear communication gap between neuroradiologists and clinicians.
A new study introduces an explainable multimodal fusion model to predict depth of stromal invasion (DSI) in early-stage cervical cancer.
📊 AUC up to 0.928 (validation set) 📐 Optimal heterogeneity cutoff: 57.3 HU 🧠 Heterogeneous density outperformed classic CT signs like lobulation and spiculation link.springer.com/article/10.1... (Wen-tao Zhang et al.)
📊 Best model (T+R+C) AUC: up to 0.912 🧾 Integrates MRI radiomics, clinical variables, and NLP-derived report features 🔍 SHAP analysis highlights key imaging, text, and clinical predictors driving decisions link.springer.com/article/10.1... (Raoying Xie et al.)
📊 89.8% of clinicians value key images in reports 🧾 59.3% prefer standardized classifications and quantitative data 🧠 In stroke scenarios, clinicians strongly favor context-based structured reporting (45.8% vs 9.5% of neuroradiologists) link.springer.com/article/10.1... (Felix Gunzer et al.)
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Insights into Imaging
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link.springer.com
Objectives To determine the significance of density homogeneity in differentiating malignant and benign subcentimeter solid nodules (SNs). Materials and methods Between January 2018 and July 2024,…
link.springer.com
Density homogeneity as a crucial CT indicator for differentiating malignant and benign subcentimeter solid pulmonary nodules: A retrospective multi-center study - Insights into Imaging
Objectives Depth of stromal invasion (DSI) is a key prognostic factor significantly influencing treatment decisions in early-stage cervical cancer (ESCC). This study aims to develop an explainable…
link.springer.com
MRI- and report-based multimodal model with SHAP-based explanation for preoperative prediction of deep stromal invasion in early-stage cervical cancer - Insights into Imaging