Gerstner Anna-Katharina, Risch Franka, Canalini Luca, Widmann Gerlig, Gizewski Elke R, Bette Stefanie, Hellbrueck Simon, Kroencke Thomas, Decker Josua A
Department of Radiology, Medical University Innsbruck, Anichstrasse 35, Innsbruck, 6020, Austria.
Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany.
BMC Med Imaging. 2025 Aug 4;25(1):311. doi: 10.1186/s12880-025-01849-0.
The aim of this retrospective study is to compare photon-counting detector computed tomography (PCD-CT) derived virtual non-contrast (VNC) images of the liver reconstructed from both arterial and portal venous phase using conventional and liver-specific VNC algorithm to true non-contrast images, in context of the body mass index (BMI).
VNC images reconstructed from multiphase (non-contrast, arterial and portal venous phase) PCD-CT scans performed between April 2021 and February 2023 were analysed retrospectively. For each patient, four VNC series were generated: two series (arterial and portal venous) using a conventional VNC algorithm (VNC; VNC) and two using a liver-specific “Liver VNC” algorithm (VNC; VNC). Regions of interest were placed in the left and right liver lobes and in the spleen, avoiding large vessels and focal lesions. The VNC CT-values were then compared to those of the corresponding true non-contrast images (TNC). The subsequent analysis involved the calculation of both correlation and mean offsets. The median split was utilised to ascertain distinct cohorts of patients with elevated and reduced body mass indices. These cohorts were then subjected to a comparative analysis of attenuation values to discern potential disparities between them. The results were compared by using parametric and non-parametric tests; Pearson’s correlation coefficient was employed. Bland-Altman plots were utilised to visually assess the agreement between results and Passing-Bablok regression, thereby quantifying the observed agreement.
The study population comprised 42 patients (mean age 70.0 ± 10.2 years, 33 males). Mean offsets between TNC and VNC was 0.62 ± 5.23 HU, TNC-VNC 1.24 ± 6.67 HU, TNC-VNC -0.94 ± 5.59 and TNC-VNC -0.35 ± 6.99 with no significant difference. Significant differences were found for VNC, VNC and VNC images regarding spleen attenuation. Bland-Altman plots demonstrated good agreement and the absence of any systematic difference in liver attenuation. As for the TNC-VNC, TNC-VNC, TNC-VNC and TNC-VNC variables, strong correlations were obtained (Pearson’s coefficient: 0.79, 0.69, 0.79 and 0.7, all < 0.001). The investigation revealed no statistically significant disparities between the BMI groups with respect to the mean offset of liver density (:TNC-VNC 0.51; VNC 0.61; VNC 0.68; VNC 0.45). Furthermore, no significant offset between TNC and VNC images was detected within each BMI group. A Passing-Bablok regression analysis revealed no systematic or proportional difference between the two methods.
It is evident that PCD-CT-derived VNC images generally constitute a corresponding alternative to TNC images. However, caution is advised in the interpretation of images, as there are outliers with differences exceeding 15 HU are present. In general, the mean values obtained from the analysis of, VNC images reconstructed from arterial and portal venous phases employing both the liver-specific and general VNC reconstruction algorithm did not demonstrate any clincially significant difference when compared with TNC images. Furthermore, no significant discrepancy was observed in the utilisation of the conventional and the liver-specific algorithm. The findings of this study demonstrated that, within the limitations of the study, the patients’ BMI did not have a significant impact on the VNC images.
The online version contains supplementary material available at 10.1186/s12880-025-01849-0.
本回顾性研究的目的是在体重指数(BMI)背景下,比较使用传统算法和肝脏特异性虚拟平扫(VNC)算法,从动脉期和门静脉期重建的光子计数探测器计算机断层扫描(PCD-CT)获得的肝脏虚拟平扫(VNC)图像与真实平扫图像。
回顾性分析2021年4月至2023年2月期间进行的多期(平扫、动脉期和门静脉期)PCD-CT扫描重建的VNC图像。对每位患者,生成四个VNC系列:两个系列(动脉期和门静脉期)使用传统VNC算法(VNC;VNC),另外两个使用肝脏特异性“肝脏VNC”算法(VNC;VNC)。在左、右肝叶和脾脏中放置感兴趣区域,避开大血管和局灶性病变。然后将VNC CT值与相应的真实平扫图像(TNC)的CT值进行比较。后续分析包括计算相关性和平均偏移量。采用中位数分割来确定体重指数升高和降低的不同患者队列。然后对这些队列进行衰减值的比较分析,以辨别它们之间的潜在差异。使用参数检验和非参数检验比较结果;采用Pearson相关系数。使用Bland-Altman图直观评估结果之间的一致性以及Passing-Bablok回归,从而量化观察到的一致性。
研究人群包括42例患者(平均年龄70.0±10.2岁,男性33例)。TNC与VNC之间的平均偏移量为0.62±5.23 HU,TNC-VNC为1.24±6.67 HU,TNC-VNC为 -0.94±5.59,TNC-VNC为 -0.35±6.99,无显著差异。在脾脏衰减方面,VNC、VNC和VNC图像存在显著差异。Bland-Altman图显示肝脏衰减具有良好的一致性且无任何系统差异。对于TNC-VNC、TNC-VNC、TNC-VNC和TNC-VNC变量,获得了强相关性(Pearson系数:0.79、0.69、0.79和0.7,均<0.001)。研究发现,BMI组之间在肝脏密度的平均偏移方面无统计学显著差异(TNC-VNC为0.51;VNC为0.61;VNC为0.68;VNC为0.45)。此外,在每个BMI组内,未检测到TNC与VNC图像之间的显著偏移。Passing-Bablok回归分析显示两种方法之间无系统或比例差异。
显然,PCD-CT衍生的VNC图像通常可作为TNC图像的相应替代。然而,在图像解读时建议谨慎,因为存在差异超过15 HU的异常值。总体而言,使用肝脏特异性和通用VNC重建算法从动脉期和门静脉期重建的VNC图像分析获得的平均值,与TNC图像相比未显示任何临床显著差异。此外,在传统算法和肝脏特异性算法的使用上未观察到显著差异。本研究结果表明,在研究的局限性内,患者的BMI对VNC图像没有显著影响。
在线版本包含可在10.1186/s12880-025-01849-0获取的补充材料。