Prediction of the early hepatocellular carcinoma development in patients with chronic hepatitis B virus infection using gadoxetic acid-enhanced magnetic resonance imaging
Mimi Tang, Danyang Xu, Huilin Jin, Chenyu Song, Xiaoqi Zhou, Huasong Cai, Lujie Li, Meicheng Chen, Yuxin Wu, Yanji Luo, Yuying Chen, Shi-Ting Feng · 2024
Read Prediction of the early hepatocellular carcinoma development in patients with chronic hepatitis B virus infection using gadoxetic acid-enhanced magnetic resonance imaging by Mimi Tang, Danyang Xu, Huilin Jin, Chenyu Song, Xiaoqi Zhou, Huasong Cai, Lujie Li, Meicheng Chen, Yuxin Wu, Yanji Luo, Yuying Chen, Shi-Ting Feng (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11575160.txt.
Description
Mimi Tang and co-authors published a 2024 study on predicting liver cancer in people with long-term hepatitis B infection. Some liver nodules that look quiet on scans can turn into fast-growing cancer over time. Knowing which patients are at risk would sharpen follow-up care. The team tested whether a special MRI scan could forecast cancer within two years.
They reviewed eighty-six patients scanned at a hospital in China between 2011 and 2019. Features from the scans, such as scarring and fatty change, were recorded. Computer-extracted patterns from the whole liver were added. Thirteen patients developed cancer within two years. Older age, liver scarring, and the quiet nodules each raised the risk. Models mixing clinical facts, scan features, and computer patterns were built to predict cancer. The study also examined which traits mark the nodules most likely to turn.
Catalog record
| CREATOR | Mimi Tang, Danyang Xu, Huilin Jin, Chenyu Song, Xiaoqi Zhou, Huasong Cai, Lujie Li, Meicheng Chen, Yuxin Wu, Yanji Luo, Yuying Chen, Shi-Ting Feng |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 36 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |