Departments of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Departments of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Med Phys. 2020 Jan;47(1):64-74. doi: 10.1002/mp.13769. Epub 2019 Nov 19.
Currently, radiologists use tumor-to-normal tissue contrast across multiphase computed tomography (MPCT) for lesion detection. Here, we developed a novel voxel-based enhancement pattern mapping (EPM) technique and investigated its ability to improve contrast-to-noise ratios (CNRs) in a phantom study and in patients with hepatobiliary cancers.
The EPM algorithm is based on the root mean square deviation between each voxel and a normal liver enhancement model using patient-specific (EPM-PA) or population data (EPM-PO). We created a phantom consisting of liver tissue and tumors with distinct enhancement signals under varying tumor sizes, motion, and noise. We also retrospectively evaluated 89 patients with hepatobiliary cancers who underwent active breath-hold MPCT between 2016 and 2017. MPCT phases were registered using a three-dimensional deformable image registration algorithm. For the patient study, CNRs of tumor to adjacent tissue across MPCT phases, EPM-PA and EPM-PO were measured and compared.
EPM resulted in statistically significant CNR improvement (P < 0.05) for tumor sizes down to 3 mm, but the CNR improvement was significantly affected by tumor motion and image noise. Eighty-two of 89 hepatobiliary cases showed CNR improvement with EPM (PA or PO) over grayscale MPCT, by an average factor of 1.4, 1.6, and 1.5 for cholangiocarcinoma, hepatocellular carcinoma, and colorectal liver metastasis, respectively (P < 0.05 for all).
EPM increases CNR compared with grayscale MPCT for primary and secondary hepatobiliary cancers. This new visualization method derived from MPCT datasets may have applications for early cancer detection, radiomic characterization, tumor treatment response, and segmentation.
We developed a voxel-wise enhancement pattern mapping (EPM) technique to improve the contrast-to-noise ratio (CNR) of multiphase CT. The improvement in CNR was observed in datasets of patients with cholangiocarcinoma, hepatocellular carcinoma, and colorectal liver metastasis. EPM has the potential to be clinically useful for cancers with regard to early detection, radiomic characterization, response, and segmentation.
目前，放射科医生使用多期 CT（MPCT）的肿瘤-正常组织对比来检测病变。在这里，我们开发了一种新的体素增强模式映射（EPM）技术，并在体模研究和肝胆癌患者中研究了其提高对比噪声比（CNR）的能力。
EPM 算法基于每个体素与使用患者特定（EPM-PA）或人群数据（EPM-PO）的正常肝脏增强模型的均方根偏差。我们创建了一个包含肝组织和具有不同大小、运动和噪声的肿瘤的增强信号的体模。我们还回顾性评估了 2016 年至 2017 年间接受主动屏气 MPCT 的 89 例肝胆癌患者。使用三维可变形图像配准算法对 MPCT 相位进行配准。对于患者研究，测量并比较了肿瘤与相邻组织在 MPCT 相位、EPM-PA 和 EPM-PO 上的 CNR。
EPM 导致肿瘤大小降至 3 毫米时 CNR 统计学显著提高（P<0.05），但 CNR 提高受肿瘤运动和图像噪声的显著影响。89 例肝胆病例中有 82 例显示 EPM（PA 或 PO）比灰度 MPCT 有 CNR 改善，胆管癌、肝细胞癌和结直肠癌肝转移的平均改善因子分别为 1.4、1.6 和 1.5（均 P<0.05）。
EPM 与原发性和继发性肝胆癌的灰度 MPCT 相比，可提高 CNR。这种源自 MPCT 数据集的新可视化方法可能适用于早期癌症检测、放射组学特征、肿瘤治疗反应和分割。
我们开发了一种基于体素的增强模式映射（EPM）技术，以提高多期 CT 的对比噪声比（CNR）。在胆管癌、肝细胞癌和结直肠癌肝转移的患者数据集中观察到 CNR 的提高。EPM 有可能在早期检测、放射组学特征、反应和分割方面对癌症具有临床应用价值。
