Validation of an automated technique for quantification of pulmonary perfusion territories using computed tomography angiography

Figures

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  Figure 1. Minimum-cost path assignment technique. The whole-lung segmentation and the pulmonary arterial tree segmentation were performed on the CTPA image. The vessel tree was cut from the tip of the balloon location. The vessel centerlines were extracted from the vessel segmentation. Using the vessel centerlines as seed points, distance maps through a whole-lung 3D binary mask were generated using the Fast-Marching algorithm. The distance maps were used to determine the minimum-cost path of each tissue voxel to the PE-proximal and PE-distal artery subtrees, yielding MCP assignment territories. 3D, three-dimensional; CTPA, computed tomography pulmonary angiography; MCP, minimum-cost path; PE, pulmonary embolism.

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  Figure 2. Image processing diagram. (A) MCP assignment processing block. The whole-lung segmentation and the pulmonary arterial tree segmentation were performed on the CTPA image. The pulmonary arterial tree was cut based on the location of the tip of the balloon. The vessel centerlines were extracted from the vessel segmentation. Using the vessel centerlines as seed points, distance maps through a whole-lung 3D binary mask were generated using the Fast-Marching algorithm. The distance maps were used to determine the MCP of each tissue voxel to the PE-proximal and PE-distal artery subtrees, yielding MCP assignment territories. (B) Reference standard processing block. Dynamic CT acquisition was performed and a first-pass perfusion technique was used to generate the perfusion distribution map. A region-growing segmentation was performed within the perfusion defect region to generate the reference standard territories. 3D, three-dimensional; CTPA, computed tomography pulmonary angiography; CTP, computed tomography perfusion; MCP, minimum-cost path; PE, pulmonary embolism.

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  Figure 3. Qualitative results of the MCP and reference perfusion techniques. (A) The MIP of the CT angiography (top row), the perfusion distribution map (middle row), and the MCP distance map (bottom row). The red arrows shown in the CT angiography point to the balloon tip. The color bar shown in perfusion map indicates the perfusion in mL/min/g. The red dashed circle in the 3D perfusion map indicates the under-perfused lung tissue. The color bar shown in the MCP distance map indicates the relative distance of each voxel to its nearest distal vessel centerline point. (B) The MCP and reference standard territories are shown in axial, coronal and posterior 3D volumetric views. (C) Slice-by-slice comparison of PE-distal mass and ischemic tissue mass. CT, computed tomography; 3D, three-dimensional; MCP, minimum-cost path; MIP, maximum intensity projection; PE, pulmonary embolism; REF, reference standard.

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  Figure 4. Mass correspondence comparison. (A) Linear regression and (B) Bland-Altman analysis comparing the MCP assigned PE-distal tissue masses (MMCP) and the reference standard perfusion ischemic tissue masses (MREF). (C) Histogram of the PE-distal mass-percent using the MCP and REF techniques on a total of 33 PE cases in this study. MCP, minimum-cost path; PE, pulmonary embolism; REF, reference standard; RMSE, root-mean-square error; RMSD, root-mean-square deviation; SD, standard deviation.

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  Figure 5. Dice’s similarity coefficient and the mean Euclidean distance on the reference standard ischemic mass. REF, reference standard.