School of Technology, Brigham Young University, Provo, UT, USA.
Biomed Eng Online. 2010 Jun 22;9:30. doi: 10.1186/1475-925X-9-30.
The success of radiation therapy depends critically on accurately delineating the target volume, which is the region of known or suspected disease in a patient. Methods that can compute a contour set defining a target volume on a set of patient images will contribute greatly to the success of radiation therapy and dramatically reduce the workload of radiation oncologists, who currently draw the target by hand on the images using simple computer drawing tools. The most challenging part of this process is to estimate where there is microscopic spread of disease.
Given a set of reference CT images with "gold standard" lymph node regions drawn by the experts, we are proposing an image registration based method that could automatically contour the cervical lymph code levels for patients receiving radiation therapy. We are also proposing a method that could help us identify the reference models which could potentially produce the best results.
The computer generated lymph node regions are evaluated quantitatively and qualitatively.
Although not conforming to clinical criteria, the results suggest the technique has promise.
放射治疗的成功与否取决于能否精确地勾画靶区,即患者体内已知或疑似疾病的区域。能够在一组患者图像上计算出勾画靶区的轮廓集的方法将极大地促进放射治疗的成功,并显著减少放射肿瘤学家的工作量,因为目前他们是使用简单的计算机绘图工具在图像上手动勾画靶区。这一过程中最具挑战性的部分是估计疾病的微观扩散范围。
我们提出了一种基于图像配准的方法,该方法可利用一组参考 CT 图像和专家勾画的“金标准”淋巴结区域,自动勾画接受放射治疗的患者的颈部淋巴结水平。我们还提出了一种方法,可以帮助我们识别可能产生最佳结果的参考模型。
计算机生成的淋巴结区域进行了定量和定性评估。
尽管该技术不符合临床标准,但结果表明其具有一定的潜力。