由于实时4D动态磁共振成像(dMRI)方法具有足够的空间和时间分辨率用于对儿科胸部成像目前还不可用,目前采用自由呼吸切片采集,然后采用适当的4D构造方法。自选通方法,仅从图像信息中提取呼吸信号,而无需任何外部门控技术,为此目的有很大的潜力,例如用于研究小儿胸部功能不全综合征(TIS)。患有TIS的患者经常患有严重的胸壁畸形,隔膜,和脊柱,导致非常复杂的呼吸,包括深或浅的呼吸周期。现有的4D构造方法在这种情况下不能令人满意地执行,大多数不是全自动的,需要手动交互操作。在本文中,我们提出了一种新颖的全自动4D图像构建方法,基于称为通量的图像派生概念来解决这些挑战。
我们利用了来自25名没有已知胸部异常的儿科受试者的25个dMRI数据集和来自29名TIS患者的58个dMRI数据集,每个患者在手术前后都进行了dMRI扫描。在自由呼吸条件下,在每个矢状位置以〜480ms/切片的速率连续采集80个切片的时间序列,根据胸部大小,每位受试者的胸部有30-40个矢状位置。在我们的方法中,我们首先根据图像时间序列中身体区域的光流矢量场的通量提取每个矢状位置的呼吸信号。这里,对于呼吸阶段的每个时间点,身体区域的净通量可以被认为是进入或离开身体区域的通量,我们称之为光通量(OFx)。OFx提供了胸部的真实呼吸运动的非常鲁棒的表示。OFx允许我们对所有呼吸周期进行全面分析,以稳健的方式仅提取正常周期,并将所有提取的正常周期映射到每个矢状位置的一个余弦呼吸模型。随后,我们从每个位置的呼吸模型中独立地重新采样一个正常周期。与不同矢状位置相关联的正常周期模型最终被合成以形成最终构建的4D图像。
我们采用了几个指标来评估4D构造结果的质量:Eie-定位对应于结束吸气和结束呼气的时间瞬间的误差;Eto-与每个检测到的正常周期中正确的时间顺序的偏差;Ess-空间平滑度的偏差;Esc-与读者评分的空间连续性的偏差。这些指标对于正常受试者和TIS患者的平均值和标准偏差被发现是,分别为:以时间为单位的Eie:0.25±0.05和0.38±0.16(理想值=0);Eto:2.7%±2.3%和1.8%±2%(理想值=0);以像素为单位的Ess:0.5±0.17和0.54±0.25(理想值=0);Esc:4.6±0.48和4.56±0.98(得分范围:最佳=5,最差=1)。结果表明,OFx方法实现了出色的时空连续性,其产量为100%,这意味着它成功地在每个测试的数据集上进行了4D构建。与最近发布的方法相比,OFx是全自动的,从获得的dMRI扫描开始,每个研究需要约5分钟的计算时间。即使在包括许多异常呼吸周期的复杂TIS数据集上,该方法也实现了高的时间和空间连续性。
提出了一种基于光通量概念的新的4DdMRI构造方法,该方法是全自动的,并且在纯粹从动态图像序列中得出呼吸信号时非常鲁棒,即使由于TIS等严重疾病而呈现复杂的呼吸模式。评估表明,其准确性与手动注释中发现的变化相当。该方法的一个重要特征是,它与施工过程中使用的矢状位置的数量无关,这表明它适用于仅在几个矢状位置而不是胸部全宽处获取数据的成像技术。该方法不依赖于任何特定的成像模式,如本文所示,不仅在dMRI上,而且在动态计算机断层扫描(CT)上。
Since real-time 4D dynamic magnetic resonance imaging (dMRI) methods with adequate spatial and temporal resolution for imaging the pediatric thorax are currently not available, free-breathing slice acquisitions followed by appropriate 4D construction methods are currently employed. Self-gating methods, which extract breathing signals only from image information without any external gating technology, have much potential for this purpose, such as for use in studying pediatric thoracic insufficiency syndrome (TIS). Patients with TIS frequently suffer from extreme malformations of the chest wall, diaphragm, and spine, leading to breathing that is very complex, including deep or shallow respiratory cycles. Existing 4D construction methods cannot perform satisfactorily in this scenario, and most are not fully automatic, requiring manual interactive operations. In this paper, we propose a novel fully automatic 4D image construction method based on an image-derived concept called flux to address these challenges.
We utilized 25 dMRI data sets from 25 pediatric subjects with no known thoracic anomalies and 58 dMRI data sets from 29 patients with TIS where each patient had a dMRI scan before and after surgery. A time sequence of 80 slices are acquired at each sagittal location continuously at a rate of ~480 ms per slice under free-breathing conditions, with 30-40 sagittal locations across the chest for each subject depending on the thoracic size. In our approach, we first extract the breathing signal for each sagittal location based on the flux of the optical flow vector field of the body region from the image time series. Here, for each time point of respiratory phase, the net flux of the body region can be regarded as the flux going into or out of the body region, which we term Optical Flux (OFx). OFx provides a very robust representation of the real breathing motion of the thorax. OFx allows us to perform a full analysis of all respiratory cycles, extract only normal cycles in a robust manner, and map all extracted normal cycles on to one cosine respiration model for each sagittal location. Subsequently, we re-sample one normal cycle from the respiration model for each location independently. The normal cycle models associated with the different sagittal locations are finally composited to form the final constructed 4D image.
We employ several metrics to evaluate the quality of the 4D construction results: Eie - error in locating time instants corresponding to end inspiration and end expiration; Eto - deviation from correct temporal order in each detected normal cycle; Ess - deviation in spatial smoothness; and Esc - deviation from spatial continuity as scored by a reader. The means and standard deviations of these metrics for normal subjects and TIS patients are found to be, respectively: Eie: 0.25 ± 0.05 and 0.38 ± 0.16 in units of time instance (ideal value = 0); Eto: 2.7% ± 2.3% and 1.8% ± 2% (ideal value = 0%); Ess: 0.5 ± 0.17 and 0.54 ± 0.25 in pixel units (ideal value = 0); Esc: 4.6 ± 0.48 and 4.56 ± 0.98 (score range: best = 5, worst = 1). The results show that the OFx method achieves excellent spatial and temporal continuity and its yield was 100% meaning that it successfully performed 4D construction on every data set tested. Compared to a recently published method, OFx is fully automatic requiring about 5 min of computational time per study starting from acquired dMRI scans. The method achieves high temporal and spatial continuity even on complex TIS data sets that include many abnormal respiratory cycles.
A new 4D dMRI construction method based on the concept of optical flux is presented which is fully automatic and very robust in deriving respiratory signals purely from dynamic image sequences even when presented with complex breathing patterns due to severe disease conditions like TIS. Evaluations show that its accuracy is comparable to the variations found in manual annotations. An important characteristic of the method is that it is independent of the number of sagittal locations used in the construction process, which suggests that it is applicable to imaging techniques where data are acquired at only a few sagittal locations instead of the full width of the thorax. The method is not tied to any specific imaging modality, as demonstrated in this paper on not just dMRI but dynamic computed tomography (CT) as well.