Università degli studi di Milano, via Festa del Perdono, 7, 20122 Milan, Italy.
Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono, 7, 20122 Milan, Italy.
Crit Rev Oncog. 2024;29(2):77-90. doi: 10.1615/CritRevOncog.2023050470.
The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be challenging but decisive, because it affects the diagnostic and therapeutic process, especially in case of metastases. Several studies have already demonstrated how the integration of AI-based tools in the current clinical workflow could bring benefits to patients and to healthcare workers. AI technologies could help radiologists in early bone metastases detection, increasing the diagnostic accuracy and reducing the overdiagnosis and the number of unnecessary deeper investigations. In addition, radiomics and radiogenomics approaches could go beyond the qualitative features, visible to the human eyes, extrapolating cancer genomic and behavior information from imaging, in order to plan a targeted and personalized treatment. In this article, we want to provide a comprehensive summary of the most promising AI applications in bone metastasis imaging and their role from diagnosis to treatment and prognosis, including the analysis of future challenges and new perspectives.
人工智能（AI）的引入代表了放射学领域的一次真正革命，包括骨病变成像。骨病变在健康患者和肿瘤患者中经常被检测到，鉴别诊断具有挑战性但至关重要，因为它会影响诊断和治疗过程，尤其是在转移的情况下。已有多项研究表明，将基于 AI 的工具集成到当前的临床工作流程中，可以为患者和医疗工作者带来益处。人工智能技术可以帮助放射科医生早期发现骨转移，提高诊断准确性，减少过度诊断和不必要的深入检查数量。此外，放射组学和放射基因组学方法可以超越肉眼可见的定性特征，从影像学中推断出癌症的基因组和行为信息，以便规划有针对性和个性化的治疗。在本文中，我们希望全面总结骨转移成像中最有前途的 AI 应用及其从诊断到治疗和预后的作用，包括分析未来的挑战和新视角。
