Clinical Research Imaging Facility (CRIF), c/o Clinical Research Centre (CRC), James Arrott Drive, Ninewells Hospital & Medical School, Dundee, DD1 9SY, Scotland, UK
Prof. Dr. Luc Bidaut
Clinical Research Imaging Facility (CRIF), c/o Clinical Research Centre (CRC), James Arrott Drive, Ninewells Hospital & Medical School, Dundee, DD1 9SY, Scotland, UK
Despite exciting progress in the understanding of breast cancer development and progression, and in the development of novel therapeutic strategies, breast cancer remains the second leading cause of cancer-related death in women, with a yearly toll of more than 40,000 deaths in the United States
A novel method for dynamic ventilation imaging of the full respiratory cycle from four-dimensional computed tomography (4D CT) acquired without added contrast is presented. Three cases with 4D CT images obtained with respiratory gated acquisition for radiotherapy treatment planning were selected. Each of the 4D CT data sets was acquired during resting tidal breathing. A deformable image registration algorithm mapped each (voxel) corresponding tissue element across the 4D CT data set. From local average CT values, the change in fraction of air per voxel (i.e. local ventilation) was calculated. A 4D ventilation image set was calculated using pairs formed with the maximum expiration image volume, first the exhalation then the inhalation phases representing a complete breath cycle. A preliminary validation using manually determined lung volumes was performed. The calculated total ventilation was compared to the change in contoured lung volumes between the CT pairs (measured volume). A linear regression resulted in a slope of 1.01 and a correlation coefficient of 0.984 for the ventilation images. The spatial distribution of ventilation was found to be case specific and a 30% difference in mass-specific ventilation between the lower and upper lung halves was found. These images may be useful in radiotherapy planning.
1 August 2012 in Journal of Pain and Symptom Management