RATIONALE AND OBJECTIVES: Serial CT lung studies are difficult to compare due to misregistration between image sets. An optical flow method (OFM) was adapted for use on CT lung images to register images and visualize changes between studies. Three applications were investigated: lung nodule assessment; evaluation of pulmonary enhancement; and functional changes due to air trapping. MATERIALS AND METHODS: From an initial clinical study, a follow-up study was created by digitally manipulating the images to simulate patient positioning errors and nodule growth. Nodule growth was measured from the temporal subtraction of registered images. In application to the assessment of pulmonary enhancement, pre and postcontrast images from a patient with acute pulmonary embolism (PE) were registered. A map of the perfused blood volume was computed from the ratio of aligned lung volumes. Functional changes in the lung were demonstrated using images from a patient with air trapping. End-inspiratory and end-expiratory volumes were aligned and displacement fields estimated using the OFM. Principal strains were computed from the displacement fields. RESULTS: All image volumes were aligned with at least 0.95 correlation. OFM estimates of displacement showed excellent agreement with the prescribed displacements with 0.33 pixel RMS error. Nodule growth was evident in the presence of significant positioning errors. In the PE case, enhancement ratios indicated a hypoperfused area consistent with an occlusive hypodense filling defect. For the air trapping case, a strain map showed functional changes along the interface of the air trap. CONCLUSIONS: The OFM can facilitate the detection and quantification of changes between serial CT lung studies.
RATIONALE AND OBJECTIVES: Serial CT lung studies are difficult to compare due to misregistration between image sets. An optical flow method (OFM) was adapted for use on CT lung images to register images and visualize changes between studies. Three applications were investigated: lung nodule assessment; evaluation of pulmonary enhancement; and functional changes due to air trapping. MATERIALS AND METHODS: From an initial clinical study, a follow-up study was created by digitally manipulating the images to simulate patient positioning errors and nodule growth. Nodule growth was measured from the temporal subtraction of registered images. In application to the assessment of pulmonary enhancement, pre and postcontrast images from a patient with acute pulmonary embolism (PE) were registered. A map of the perfused blood volume was computed from the ratio of aligned lung volumes. Functional changes in the lung were demonstrated using images from a patient with air trapping. End-inspiratory and end-expiratory volumes were aligned and displacement fields estimated using the OFM. Principal strains were computed from the displacement fields. RESULTS: All image volumes were aligned with at least 0.95 correlation. OFM estimates of displacement showed excellent agreement with the prescribed displacements with 0.33 pixel RMS error. Nodule growth was evident in the presence of significant positioning errors. In the PE case, enhancement ratios indicated a hypoperfused area consistent with an occlusive hypodense filling defect. For the air trapping case, a strain map showed functional changes along the interface of the air trap. CONCLUSIONS: The OFM can facilitate the detection and quantification of changes between serial CT lung studies.
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