Kipritidis John, Hofman Michael S, Siva Shankar, Callahan Jason, Le Roux Pierre-Yves, Woodruff Henry C, Counter William B, Keall Paul J
Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia.
Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, VIC 3002, Australia.
Med Phys. 2016 Jan;43(1):33. doi: 10.1118/1.4937599.
Computed tomography ventilation imaging (CTVI) aims to visualize air-volume changes in the lung by quantifying respiratory motion in 4DCT using deformable image registration (DIR). A problem is that DIR-based CTVI is sensitive both to 4DCT image artifacts and DIR parameters, hindering clinical validation of the technique. To address this, the authors present a streamlined CTVI approach that estimates blood-gas exchange in terms of time-averaged 4DCT Hounsfield unit (HU) values without relying on DIR. The purpose of this study is to quantify the accuracy of the HU-based CTVI method using high-resolution (68)Ga positron emission tomography ("Galligas PET") scans in lung cancer patients.
The authors analyzed Galligas 4D-PET/CT scans acquired for 25 lung cancer patients at up to three imaging timepoints during lung cancer radiation therapy. For each 4DCT scan, the authors produced three types of CTVIs: (i) the new method (CTV IHU¯), which takes the 4D time-averaged product of regional air and tissue densities at each voxel, and compared this to DIR-based estimates of (ii) breathing-induced density changes (CTV IDIR-HU), and (iii) breathing-induced volume changes (CTV IDIR-Jac) between the exhale/inhale phase images. The authors quantified the accuracy of CTV IHU¯, CTV IDIR-HU and CTV IDIR-Jac versus Galligas PET in terms of voxel-wise Spearman correlation (r) and the separation of mean voxel values between clinically defined defect/nondefect regions.
Averaged over 62 scans, CTV IHU¯ showed better accuracy than CTV IDIR-HU and CTV IDIR-Jac in terms of Spearman correlation with Galligas PET, with (mean ± SD) r values of (0.50 ± 0.17), (0.42 ± 0.20), and (0.19 ± 0.23), respectively. A two-sample Kolmogorov-Smirnov test indicates that CTV IHU¯ shows statistically significant separation of mean ventilation values between clinical defect/nondefect regions. Qualitatively, CTV IHU¯ appears concordant with Galligas PET for emphysema related defects, but differences arise in tumor-obstructed regions (where aeration is overestimated due to motion blur) and for other abnormal morphology (e.g., fluid-filled or peritumoral lung with HU ≳ - 600) where the assumptions of the HU model may break down.
The HU-based CTVI method can improve voxel-wise correlations with Galligas PET compared to DIR-based methods and may be a useful approximation for voxels with HU values in the range (-1000, - 600). With further clinical verification, HU-based CTVI could provide a straightforward and reproducible means to estimate lung ventilation using free-breathing 4DCT.
计算机断层扫描通气成像（CTVI）旨在通过使用可变形图像配准（DIR）对4DCT中的呼吸运动进行量化，以可视化肺内的空气体积变化。一个问题是基于DIR的CTVI对4DCT图像伪影和DIR参数均敏感，这阻碍了该技术的临床验证。为解决此问题，作者提出了一种简化的CTVI方法，该方法根据时间平均的4DCT亨氏单位（HU）值估计血气交换，而无需依赖DIR。本研究的目的是使用高分辨率（68）Ga正电子发射断层扫描（“Galligas PET”）扫描对肺癌患者量化基于HU值的CTVI方法的准确性。
作者分析了25例肺癌患者在肺癌放射治疗期间多达三个成像时间点所采集的Galligas 4D-PET/CT扫描。对于每次4DCT扫描，作者生成了三种类型的CTVI：（i）新方法（CTVIHU¯），该方法获取每个体素处区域空气和组织密度的4D时间平均乘积，并将其与基于DIR的以下两项估计值进行比较：（ii）呼吸引起的密度变化（CTVIDIR-HU），以及（iii）呼气/吸气相图像之间呼吸引起的体积变化（CTVIDIR-Jac）。作者根据体素级别的斯皮尔曼相关性（r）以及临床定义的缺损/非缺损区域之间平均体素值的差异，对CTVIHU¯、CTVIDIR-HU和CTVIDIR-Jac与Galligas PET的准确性进行了量化。
在62次扫描的平均值中，就与Galligas PET的斯皮尔曼相关性而言，CTVIHU¯显示出比CTVIDIR-HU和CTVIDIR-Jac更高的准确性，其（均值±标准差）r值分别为（0.50±0.17）、（0.42±0.20）和（0.19±0.23）。双样本柯尔莫哥洛夫-斯米尔诺夫检验表明，CTVIHU¯在临床缺损/非缺损区域之间的平均通气值显示出统计学上的显著差异。定性地说，CTVIHU¯在肺气肿相关缺损方面似乎与Galligas PET一致，但在肿瘤阻塞区域（由于运动模糊导致通气被高估）以及其他异常形态（例如HU≳ - 600的液性填充或肿瘤周围肺组织）中会出现差异，在这些区域中HU模型的假设可能不成立。
与基于DIR的方法相比，基于HU值的CTVI方法可以改善与Galligas PET的体素级相关性，并且对于HU值在（-1000， - 600）范围内的体素可能是一种有用的近似方法。经过进一步的临床验证，基于HU值的CTVI可以提供一种直接且可重复的方法，用于使用自由呼吸的4DCT估计肺通气。
