Quantification and optimisation of lung ventilation SPECT images

Currently, lung function tests are the gold standard for lung function measurements. Since the outcome of a lung function test is a summation of the status of the whole lung, significant changes in lung function may occur before a deviation from the norm can be identified. A method that can reliably detect lung abnormalities earlier in a disease process would therefore be beneficial. Regional differences in the lung are ideally studied by imaging methods. Heterogeneous ventilation in lungs of allergic individuals, cigarette smokers, asthmatics and chronic obstructive pulmonary disease (COPD) patients has been demonstrated using various imaging techniques such as single photon emission computer tomography, SPECT. The amount of heterogeneous ventilation is correlated to disease advancement. The CVT-method, that measures heterogeneity using the coefficient of variation (CV) caused by lung function reduction in lung SPECT images, was developed and optimised. Lung function in patients and healthy volunteers was evaluated using the CVT-method. Monte Carlo simulated gamma camera projections were generated of activity distributions in two anthropomorphic phantoms. When comparing the two reconstruction algorithms, filtered back projection (FBP) and ordered subset expectation maximisation (OSEM), trade-off plots of spatial resolution, contrast and noise were used. Development and optimisation of the CVT-method was performed using activity distributions mimicking various degrees of COPD. The CVT-method itself was used when the optimal combination of acquisition, reconstruction and analysis parameter values was determined. The radioactive tracer 99mTc-Technegas was used for the ventilation examination on human subjects. OSEM resulted in higher spatial resolution in combination with lower noise level compared to FBP and was therefore chosen. The optimal parameter values found were a total number of counts in the projections of at least 3.6 x 106 and a low energy highresolution collimator. The number of OSEM updates and cut-off frequency of the noise reduction filter depended on if the periphery of the lung was excluded or not. The CVT-method showed to be capable of identifying early COPD in computersimulated images (p<0.001). The CVT-method was also capable of correctly identifying patients with severe COPD (p<0.05). A compensation technique was implemented, making the heterogeneity values from healthy lung volumes of different subjects comparable. This adaptation made it possible to identify subjects who had normal lung function tests but with indications of conditions associated with ventilation disturbances. The results indicate that the present method has the capacity to identify minor lung function abnormalities earlier in a disease process than conventional lung function tests