医学
烧蚀
烧蚀区
肝细胞癌
边距(机器学习)
磁共振成像
射频消融
肿瘤进展
射频消融术
核医学
离格
肝硬化
放射科
放射治疗
癌症
内科学
机器学习
计算机科学
作者
Arnaud Hocquelet,Hervé Trillaud,Nora Frulio,Panteleimon Papadopoulos,P. Balageas,C. Salut,Marie Meyer,Jean‐Frédéric Blanc,Michel Montaudon,Baudouin Denis de Senneville
标识
DOI:10.1016/j.jvir.2016.02.031
摘要
To propose a postprocessing technique that measures tumor surface with insufficient ablative margins (≤ 5 mm) on magnetic resonance (MR) imaging to predict local tumor progression (LTP) following radiofrequency (RF) ablation.A diagnostic method is proposed based on measurement of tumor surface with a margin ≤ 5 mm on MR imaging. The postprocessing technique includes fully automatic registration of pre- and post-RF ablation MR imaging, a semiautomatic segmentation of pre-RF ablation tumor and post-RF ablation volume, and a subsequent calculation of the three-dimensional exposed tumor surface area. The ability to use this surface margin ≤ 5 mm to predict local recurrence at 2 years was then tested on 16 patients with cirrhosis who were treated by RF ablation with a margin ≤ 5 mm in 2012: eight with LTP matched according to tumor size and number and α-fetoprotein level versus eight without local recurrence.The error of estimated tumor surface with a margin ≤ 5 mm was less than 12%. Results of a log-rank test showed that patients with a tumor surface area > 425 mm(2) had a 2-year LTP rate of 77.5%, compared with 25% for patients with a tumor surface area ≤ 425 mm(2) (P = .018).This proof-of-concept study proposes an accurate and reliable postprocessing technique to estimate tumor surface with insufficient ablative margins, and underscores the potential usefulness of tumor surface with a margin ≤ 5 mm to stratify patients with HCC treated by RF ablation according to their risk of LTP.
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