Implementation and evaluation of a new workflow for registration and segmentation of pulmonary MRI data for regional lung perfusion assessment

Recently it has been shown that regional lung perfusion can be assessed using time-resolved contrast-enhanced magnetic resonance (MR) imaging. Quantification of the perfusion images has been attempted, based on definition of small regions of interest (ROIs). Use of complete lung segmentations instead of ROIs could possibly increase quantification accuracy. Due to the low signal-to-noise ratio, automatic segmentation algorithms cannot be applied. On the other hand, manual segmentation of the lung tissue is very time consuming and can become inaccurate, as the borders of the lung to adjacent tissues are not always clearly visible. We propose a new workflow for semi-automatic segmentation of the lung from additionally acquired morphological HASTE MR images. First the lung is delineated semi-automatically in the HASTE image. Next the HASTE image is automatically registered with the perfusion images. Finally, the transformation resulting from the registration is used to align the lung segmentation from the morphological dataset with the perfusion images. We evaluated rigid, affine and locally elastic transformations, suitable optimizers and different implementations of mutual information (MI) metrics to determine the best possible registration algorithm. We located the shortcomings of the registration procedure and under which conditions automatic registration will succeed or fail. Segmentation results were evaluated using overlap and distance measures. Integration of the new workflow reduces the time needed for post-processing of the data, simplifies the perfusion quantification and reduces interobserver variability in the segmentation process. In addition, the matched morphological data set can be used to identify morphologic changes as the source for the perfusion abnormalities.

MRT zum Staging des Lungenkarzinoms

PURPOSE

Overview of magnetic resonance imaging (MRI) in staging of lung cancer.

MATERIAL AND METHODS

Currently available methods of imaging lung cancer, lymph node and distant metastases by MRI are explained. At present, MRI is mainly used in the detection of cerebral metastases and assessment of infiltration of the thoracic wall and of the mediastinum. The capabilities of T2-weighted single-shot TSE (HASTE) and T1-weighted 3D gradient echo techniques (VIBE) are demonstrated.

RESULTS

With the advent of new fast sequences like HASTE and VIBE the spatial resolution comes close to that of computed tomography but with an outstanding soft tissue contrast and without radiation exposure. The introduction of lymph node specific contrast media will improve sensitivity and specificity in N staging. Additionally, whole-body MRI is capable of detecting distant metastases, in particular in the organs at risk, i.e. brain, upper abdomen and musculoskeletal system.

CONCLUSION

MRI is gaining importance as part of a multimodal imaging approach for staging of lung cancer.