4.4 Article

Quantitative and Volumetric European Association for the Study of the Liver and Response Evaluation Criteria in Solid Tumors Measurements: Feasibility of a Semiautomated Software Method to Assess Tumor Response after Transcatheter Arterial Chemoembolization

期刊

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jvir.2012.08.028

关键词

-

资金

  1. Philips
  2. NIH
  3. French Society of Radiology (FSR)
  4. NIH/NCI [R01 CA160771]
  5. Philips Research North America
  6. Briarcliff Manor, New York
  7. French Society of Radiology (SFR)

向作者/读者索取更多资源

Purpose: To show that hepatic tumor volume and enhancement pattern measurements can be obtained in a time-efficient and reproducible manner on a voxel-by-voxel basis to provide a true three-dimensional (3D) volumetric assessment. Materials and Methods: Magnetic resonance (MR) imaging data obtained from 20 patients recruited for a single-institution prospective study were retrospectively evaluated. All patients had a diagnosis of hepatocellular carcinoma (HCC) and underwent drug-eluting beads (DEB) transcatheter arterial chemoembolization for the first time. All patients had undergone contrast-enhanced MR imaging before and after DEB transcatheter arterial chemoembolization; poor image quality excluded 3 patients, resulting in a final count of 17 patients. Volumetric RECIST (vRECIST) and quantitative EASL (qEASL) were measured, and segmentation and processing times were recorded. Results: There were 34 scans analyzed. The time for semiautomatic segmentation was 65 seconds +/- 33 (range, 40-200 seconds). vRECIST and qEASL of each tumor were computed < 1 minute for each. Conclusions: Semiautomatic quantitative tumor enhancement (qEASL) and volume (vRECIST) assessment is feasible in a workflow-efficient time frame. Clinical correlation is necessary, but vRECIST and qEASL could become part of the assessment of intraarterial therapy for interventional radiologists.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据