Thoracic Surgery, Pizhou Hospital of Traditional Chinese Medicine, Pizhou 221300, Jiangsu, China.
Respiratory Medicine, Pizhou Hospital of Traditional Chinese Medicine, Pizhou 221300, Jiangsu, China.
Contrast Media Mol Imaging. 2021 Nov 8;2021:1368687. doi: 10.1155/2021/1368687. eCollection 2021.
This work was to study the guiding value of magnetic resonance imaging (MRI) based on the target region boundary tracking algorithm in lung cancer surgery. In this study, the traditional boundary tracking algorithm was optimized, and the target neighborhood point boundary tracking method was proposed. The iterative method was used to binarize the lung MRI image, which was applied to the MRI images of 50 lung cancer patients in hospital. The patients were divided into two groups as the progression-free survival (PFS) and overall survival (OS) of surgical treatment group (experimental group, = 25) and nonsurgical treatment group (control group, = 25). The experimental group received surgical resection, while the control group received systemic chemotherapy. The results showed that the traditional boundary tracking algorithm needed to manually rejudge whether the concave and convex parts of the image were missing. The target boundary tracking algorithm can effectively avoid the leakage of concave and convex parts and accurately locate the target image contour, fast operation, without manual intervention. The PFS time of the experimental group (325 days) was significantly higher than that of the control group (186 days) ( < 0.05). The OS time of the experimental group (697 days) was significantly higher than that of the control group (428 days) ( < 0.05). Fisher exact probability method was used to test the total survival time of patients in the two groups, and the tumor classification and treatment group had significant influence on the OS time ( < 0.05). The target boundary tracking algorithm in this study can effectively locate the contour of the target image, and the operation speed was fast. Surgical resection of lung cancer can improve the PFS and OS of patients.
本研究旨在探讨基于目标区域边界跟踪算法的磁共振成像（MRI）在肺癌手术中的指导价值。本研究对传统边界跟踪算法进行了优化，并提出了目标邻域点边界跟踪方法。采用迭代方法对肺部 MRI 图像进行二值化处理，将其应用于医院 50 例肺癌患者的 MRI 图像。将患者分为两组：手术治疗组（实验组，n=25）和非手术治疗组（对照组，n=25）。实验组接受手术切除，对照组接受全身化疗。结果表明，传统边界跟踪算法需要手动重新判断图像的凹凸部分是否缺失。目标边界跟踪算法可以有效地避免凹凸部分的泄漏，准确地定位目标图像轮廓，操作快速，无需人工干预。实验组的无进展生存期（PFS）时间（325 天）明显高于对照组（186 天）（<0.05）。实验组的总生存期（OS）时间（697 天）明显高于对照组（428 天）（<0.05）。Fisher 确切概率法检验两组患者的总生存时间，肿瘤分类和治疗组对 OS 时间有显著影响（<0.05）。本研究中的目标边界跟踪算法能够有效地定位目标图像的轮廓，且操作速度较快。肺癌的手术切除可以提高患者的 PFS 和 OS。
