对比度(视觉)
肝组织
计算机断层摄影术
病理
生物
医学
放射科
计算机科学
人工智能
内分泌学
作者
Xianfu Meng,Jiahao Gao,Yanhong Sun,Fei Duan,Bixue Chen,Guanglei Lv,Huiyan Li,Xingwu Jiang,Yelin Wu,Jiawen Zhang,Xiangming Fang,Zhenwei Yao,Changjing Zuo,Wenbo Bu
标识
DOI:10.1002/advs.202304668
摘要
Positive computed tomography (CT) contrast nanoagent has significant applications in diagnosing tumors. However, the sensitive differentiation between hepatoma and normal liver tissue remains challenging. This challenge arises primarily because both normal liver and hepatoma tissues capture the nanoagent, resulting in similar positive CT contrasts. Here, a strategy for fusing positive and negative CT contrast nanoagent is proposed to detect hepatoma. A nanoagent Hf-MOF@AB@PVP initially generates a positive CT contrast signal of 120.3 HU in the liver. Subsequently, it can specifically respond to the acidic microenvironment of hepatoma to generate H2 , further achieving a negative contrast of -96.0 HU. More importantly, the relative position between the negative and positive signals area is helpful to determine the location of hepatoma and normal liver tissues. The distinct contrast difference of 216.3 HU and relative orientation between normal liver and tumor tissues are meaningful to sensitively distinguish hepatoma from normal liver tissue utilizing CT imaging.
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