Intratumoral and peritumoral CT radiomics combined with clinical and hematologic inflammatory markers for predicting lymph node metastasis in esophageal squamous cell carcinoma: a retrospective single-center study [0.03%]
结合临床及血液炎症标志物的食管鳞癌淋巴结转移预测的肿瘤内和肿瘤周CT影像组学研究：单中心回顾性研究
Xinmiao Yang,Hongfeng Niu,Ziqing Yang et al.
Xinmiao Yang et al.
Objective: To develop and validate a hybrid model integrating intratumoral (TR) and peritumoral (PTR) CT radiomics with clinical and hematologic inflammatory markers for predicting lymph node metastasis (LNM) in esophagea...
Diagnostic performance of abbreviated MRI in surveillance of patients with hepatocellular carcinoma candidates for liver transplantation [0.03%]
肝移植候选人的肝细胞癌监测的简化MRI诊断性能评估
Monica Mattone,Alessandro De Maio,Alessandro Napoli et al.
Monica Mattone et al.
Purpose: To compare the diagnostic performance of three different abbreviated MRI protocols simulated by extraction from a standard liver MRI protocol with hepatobiliary-specific contrast agent obtained for hepatocellular...
Digital infrastructures and data interoperability in radiology for prevention: from digital health to AI-enabled, quantitative imaging workflows [0.03%]
放射学中的数字基础设施和数据互操作性在预防方面的应用：从数字健康到人工智能驱动的定量成像工作流程
Luca Maria Sconfienza
Luca Maria Sconfienza
Radiology is rapidly evolving from a service that produces images into a data-centric clinical platform that supports prevention, early diagnosis, and personalized care. This shift is accelerated by the convergence of digital health, artifi...
Image-quality optimization for late iodine enhancement with photon-counting CT: impact of spectral analysis and reconstruction parameters [0.03%]
光子计数CT晚期碘增强图像优化：谱学分析与重建参数的影响
Elisa Bruno,Anna Palmisano,Francesco Pisu et al.
Elisa Bruno et al.
Purpose: Clinical application of late iodine enhancement (LIE) for myocardial scar identification is limited by low contrast-to-noise ratio (CNR). Photon-counting detector-CT (PCD-CT) can improve image quality providing s...
Request and reporting models for computed tomography in the multidisciplinary management of cancer patients: consensus between the Italian Society of Medical and Interventional Radiology (SIRM) and the Italian Society of Medical Oncology (AIOM) [0.03%]
意大利医学与介入放射学会（SIRM）和意大利肿瘤内科学会（AIOM）关于多学科管理癌症患者的CT申请和报告模型的共识意见
Vincenza Granata,Alessandro Serafini,Roberta Fusco et al.
Vincenza Granata et al.
Background: Multidisciplinary management of oncological patients has improved patient outcomes, responding effectively and efficiently to the patient's health needs. A critical element remains adequate communication, also...
Functional hyperpolarized gas magnetic resonance imaging of idiopathic pulmonary fibrosis: a systematic review [0.03%]
特发性肺纤维化功能过度极化气体磁共振成像的系统评价
David Zaccagnini,Andrea Magnini,Lorenzo Cinci et al.
David Zaccagnini et al.
Objectives: Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease. New non-invasive tools to monitor pulmonary function, disease progression, and therapeutic response are needed. The study was a...
Will AI systems replace radiologists? An "old" radiologist discusses the future of radiology with ChatGPT [0.03%]
AI系统会取代放射科医生吗？一位“老”放射科医生与ChatGPT讨论放射学的未来
Andrea Giovagnoni
Andrea Giovagnoni
LiT-WSAG: high-precision 3D liver tumor segmentation via 2D training and 3D reconstruction [0.03%]
基于二维训练和三维重建的高精度肝脏肿瘤分割方法(LiT-WSAG)
Chen Yi,Yu-Xin Li,Shu-Hang Cao et al.
Chen Yi et al.
Liver cancer remains a major cause of cancer mortality, and precise CT-based liver tumor segmentation is critical for early diagnosis and personalized treatment. In practice, fully 3D‑supervised training is limited by prohibitive annotatio...
Diagnostic performance of bpMRI versus mpMRI and AI-assisted bpMRI in prostate cancer detection: a multi-reader study [0.03%]
基于前列腺影像报告和数据系统诊断的bpMRI、mpMRI及AI辅助bpMRI检测前列腺癌的诊断效能分析：一项多阅片人研究
Luca Russo,Silvia Bottazzi,Luca D&#x;Erme et al.
Luca Russo et al.
Purpose: To compare biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for detecting clinically significant prostate cancer (csPCa), and to assess the impact of artificial intelligence (AI)-assisted bpMRI on diagnos...
A novel deep learning-based grading system for assessing breast arterial calcification on mammograms, as an independent risk factor for predicting adverse cardiovascular events [0.03%]
一种新颖的基于深度学习的乳腺动脉钙化分级系统，用于评估其作为独立风险因素预测不良心血管事件的价值
Mu&#x;ath Ibrahim,Patrick C Brennan,Mo&#x;ayyad E Suleiman et al.
Mu&#x;ath Ibrahim et al.
Purpose: To develop a deep learning-based framework for automated detection and grading of breast arterial calcification (BAC) on mammograms, and to evaluate its association with major adverse cardiovascular events (MACE)...