Use of an optical flow method for the analysis of serial CT lung images.

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.

Improved radiologic staging of lung cancer with 2-[18F]-fluoro-2-deoxy-D-glucose-positron emission tomography and computed tomography registration.

PURPOSE: To determine if volumetric nonlinear registration or registration of thoracic computed tomography (CT) and 2-[18F]-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET) datasets changes the detection of mediastinal and hilar nodal disease in patients undergoing staging for lung cancer and if it has any impact on radiologic lung cancer staging. METHOD: Computer-based image registration was performed on 45 clinical thoracic helical CT and FDG-PET scans of patients with lung cancer who were staged by mediastinoscopy and/or thoracotomy. Thoracic CT, FDG-PET, and registration datasets were each interpreted by 2 readers for the presence of metastatic nodal disease and were staged independently of each other. Results were compared with surgical pathologic findings. RESULTS: One hundred and thirty lymph node stations in the mediastinum and hila were evaluated each on CT, PET, and registration datasets. Sensitivity, specificity, positive predictive value, and negative predictive value, respectively, for detecting metastatic nodal disease for CT were 74%, 78%, 55%, 88%; for PET with CT side by side, 59% to 76%, 77% to 89%, 48% to 68%, and 84% to 91%; and for CT-PET registration, 71% to 76%, 89% to 96%, 70% to 86%, and 90% to 91%. Registration images were significantly more sensitive in detecting nodal disease over PET for 1 reader (P = 0.0156) and were more specific than PET (P = 0.0107 and 0.0017) in identifying the absence of mediastinal disease for both readers. Registration was significantly more accurate for staging when compared with PET for both readers (P = 0.002 and 0.035). CONCLUSION: Registration of CT and FDG-PET datasets significantly improved the specificity of detecting metastatic disease. In addition, registration improved the radiologic staging of lung cancer patients when compared with CT or FDG-PET alone.

Alignment of CT lung volumes with an optical flow method.

RATIONALE AND OBJECTIVES: This study was performed to evaluate an optical flow method for registering serial computed tomographic (CT) images of lung volumes to assist physicians in visualizing and assessing changes between CT scans. MATERIALS AND METHODS: The optical flow method is a coarse-to-fine model-based motion estimation technique for estimating first a global parametric transformation and then local deformations. Five serial pairs of CT images of lung volumes that were misaligned because of patient positioning, respiration, and/or different fields of view were used to test the method. RESULTS: Lung volumes depicted on the serial paired images initially were correlated at only 28%-68% because of misalignment. With use of the optical flow method, the serial images were aligned to at least 95% correlation. CONCLUSION: The optical flow method enables a direct comparison of serial CT images of lung volumes for the assessment of nodules or functional changes in the lung.

Improved image interpretation with registered thoracic CT and positron emission tomography data sets.

OBJECTIVE: The purpose of this study was to determine if nonlinear registration of clinically acquired thoracic CT and FDG positron emission tomography (PET) data sets supports more detailed interpretation of metastatic thoracic disease when compared with interpretations from nonregistered PET studies. CONCLUSION: In 11 of 16 data sets of patients imaged for detection of metastatic disease, interpretations from PET studies were correctly altered with registration information. All changes were either improvements in tumor localization or correct interpretation of less metastatic involvement.