Breathing motion is a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Accounting for breathing motion has a profound effect on the size of conformal radiation portals employed in these sites. Breathing motion also causes artifacts and distortions in treatment planning computed tomography (CT) scans acquired during free breathing and also causes a breakdown of the assumption of the superposition of radiation portals in intensity-modulated radiation therapy, possibly leading to significant dose delivery errors. Proposed voluntary and involuntary breath-hold techniques have the potential for reducing or eliminating the effects of breathing motion, however, they are limited in practice, by the fact that many lung cancer patients cannot tolerate holding their breath. We present an alternative solution to accounting for breathing motion in radiotherapy treatment planning, where multislice CT scans are collected simultaneously with digital spirometry over many free breathing cycles to create a four-dimensional (4-D) image set, where tidal lung volume is the additional dimension. An analysis of this 4-D data leads to methods for digital-spirometry, based elimination or accounting of breathing motion artifacts in radiotherapy treatment planning for free breathing patients. The 4-D image set is generated by sorting free-breathing multislice CT scans according to user-defined tidal-volume bins. A multislice CT scanner is operated in the ciné mode, acquiring 15 scans per couch position, while the patient undergoes simultaneous digital-spirometry measurements. The spirometry is used to retrospectively sort the CT scans by their correlated tidal lung volume within the patient's normal breathing cycle. This method has been prototyped using data from three lung cancer patients. The actual tidal lung volumes agreed with the specified bin volumes within standard deviations ranging between 22 and 33 cm3. An analysis of sagittal and coronal images demonstrated relatively small (<1 cm) motion artifacts along the diaphragm, even for tidal volumes where the rate of breathing motion is greatest. While still under development, this technology has the potential for revolutionizing the radiotherapy treatment planning for the thorax and upper abdomen.

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We have developed a four-dimensional computed tomography (4D CT) technique for mapping breathing motion in radiotherapy treatment planning. A multislice CT scanner (1.5 mm slices) operated in ciné mode was used to acquire 12 contiguous slices in each couch position for 15 consecutive scans (0.5 s rotation, 0.25 s between scans) while the patient underwent simultaneous quantitative spirometry measurements to provide a sorting metric. The spirometry-sorted scans were used to reconstruct a 4D data set. A critical factor for 4D CT is quantifying the reconstructed data set quality which we measure by correlating the metric used relative to internal-object motion. For this study, the internal air content within the lung was used as a surrogate for internal motion measurements. Thresholding and image morphological operations were applied to delineate the air-containing tissues (lungs, trachea) from each CT slice. The Hounsfield values were converted to the internal air content (V). The relationship between the air content and spirometer-measured tidal volume (v) was found to be quite linear throughout the lungs and was used to estimate the overall accuracy and precision of tidal volume-sorted 4D CT. Inspection of the CT-scan air content as a function of tidal volume showed excellent correlations (typically r>0.99) throughout the lung volume. Because of the discovered linear relationship, the ratio of internal air content to tidal volume was indicative of the fraction of air change in each couch position. Theoretically, due to air density differences within the lung and in room, the sum of these ratios would equal 1.11. For 12 patients, the mean value was 1.08 +/- 0.06, indicating the high quality of spirometry-based image sorting. The residual of a first-order fit between v and V was used to estimate the process precision. For all patients, the precision was better than 8%, with a mean value of 5.1% +/- 1.9%. This quantitative analysis highlights the value of using spirometry as the metric in sorting CT scans. The 4D reconstruction provides the CT data required to measure the three-dimensional trajectory of tumor and lung tissue during free breathing.

An important consideration in four-dimensional CT scanning is the selection of a breathing metric for sorting the CT data and modeling internal motion. This study compared two noninvasive breathing metrics, spirometry and abdominal height, against internal air content, used as a surrogate for internal motion. Both metrics were shown to be accurate, but the spirometry showed a stronger and more reproducible relationship than the abdominal height in the lung. The abdominal height was known to be affected by sensor placement and patient positioning while the spirometer exhibited signal drift. By combining these two, a normalization of the drift-free metric to tidal volume may be generated and the overall metric precision may be improved.

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