BackgroundReduced ventilation in lung regions affected by chronic obstructive pulmonary disease (COPD), reflected as inhomogeneities in the single-photon emission computed tomography (SPECT) lung image, is correlated to disease advancement. An analysis method for measuring these inhomogeneities is proposed in this work. The first aim was to develop a quantitative analysis method that could discriminate between Monte Carlo simulated normal and COPD lung SPECT images. A second aim was to evaluate the ability of the present method to discriminate between human subjects with advanced COPD and healthy volunteers.MethodsIn the simulated COPD study, different activity distributions in the lungs were created to mimic the healthy lung (normal) and different levels of COPD. Gamma camera projections were Monte Carlo simulated, representing clinically acquired projections of a patient who had inhaled 125 MBq 99mTc-Technegas followed by a 10-min SPECT examination. Reconstructions were made with iterative ordered subset expectation maximisation. The coefficient of variance (CV) was calculated for small overlapping volumes covering the 3D reconstructed activity distribution. A CV threshold value (CVT) was calculated as the modal value of the CV distribution of the simulated normal. The area under the distribution curve (AUC), for CV values greater than CVT, AUC(CVT), was then calculated. Moreover, five patients with advanced emphysema and five healthy volunteers inhaled approximately 75 MBq 99mTc-Technegas immediately before the 20-min SPECT acquisition. In the human study, CVT was based on the mean CV distribution of the five healthy volunteers.ResultsA significant difference (p < 0.001) was found between the Monte-Carlo simulated normal and COPD lung SPECT examinations. The present method identified a total reduction of ventilation of approximately 5%, not visible to the human eye in the reconstructed image. In humans the same method clearly discriminated between the five healthy volunteers and five patients with advanced COPD (p < 0.05).ConclusionsWhile our results are promising, the potential of the AUC(CVT) method to detect less advanced COPD in patients needs further clinical studies.

BackgroundHeterogeneous ventilation in lungs of individuals with allergies, cigarette smokers, asthmatics and chronic obstructive pulmonary disease (COPD) patients has been demonstrated using imaging modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT). These individuals suffer from narrow and/or closed airways to various extents. By calculating regional heterogeneity in lung ventilation SPECT images as the coefficient of variation (CV) in small elements of the lung, heterogeneity maps and CV-density curves can be generated and used to quantitatively measure heterogeneity. This work explores the potential to use such measurements to detect mild ventilation heterogeneities in lung-healthy subjects.MethodFourteen healthy subjects without documented lung disease or respiratory symptoms, and two patients with documented airway disease, inhaled on average approximately 90 MBq 99mTc-Technegas immediately prior to the 20-min SPECT acquisition. Variation in activity uptake between subjects was compensated for in resulting CV values. The area under the compensated CV density curve (AUC), for CV values greater than a threshold value CVT, AUC(CV > CVT), was used as the measure of ventilation heterogeneity.ResultsPatients with lung function abnormalities, according to lung function tests, generated higher AUC(CV > 20%) values compared to healthy subjects (p = 0.006). Strong linear correlations with the AUC(CV > 20%) values were found for age (p = 0.006) and height (p = 0.001). These demonstrated that ventilation heterogeneities increased with age and that they depend on lung size. Strong linear correlations were found for the lung function value related to indices of airway closure/air trapping, residual volume/total lung capacity (RV/TLC; p = 0.009), and diffusion capacity of the lung for carbon monoxide adjusted for haemoglobin concentration in the blood (DLCOc; p = 0.009), a value partly related to supposed ventilation/perfusion mismatch. These findings support the association between conventional lung function tests and the AUC(CV > 20%) value.ConclusionsAmong the healthy subjects, there is a group with increased AUC(CV > 20%) values, but with normal lung function tests, which implies that it might be possible to differentiate ventilation heterogeneities earlier in a disease process than by lung function tests.Electronic supplementary materialThe online version of this article (doi:10.1186/s13550-014-0039-1) contains supplementary material, which is available to authorized users.

For the configuration studied, the OSEM reconstruction in combination with post-filtering should be used in lung SPECT studies with at least 60 MLEM equivalent iterations. Compared to FBP the spatial resolution was improved by about 1 mm. For a constant level of CV, a four-fold increase in count level resulted in an increased resolution of about 2 mm. Spatial resolution and cut-off frequency depends on what value of noise in the image is acceptable also increased by using a low-energy, high-resolution collimator for CV values above 3%. The choice of noise-reducing filter and cut-off frequency depends on what value of noise in the image is acceptable.

BackgroundThe amount of inhomogeneities in a 99mTc Technegas single-photon emission computed tomography (SPECT) lung image, caused by reduced ventilation in lung regions affected by chronic obstructive pulmonary disease (COPD), is correlated to disease advancement. A quantitative analysis method, the CVT method, measuring these inhomogeneities was proposed in earlier work. To detect mild COPD, which is a difficult task, optimised parameter values are needed.MethodsIn this work, the CVT method was optimised with respect to the parameter values of acquisition, reconstruction and analysis. The ordered subset expectation maximisation (OSEM) algorithm was used for reconstructing the lung SPECT images. As a first step towards clinical application of the CVT method in detecting mild COPD, this study was based on simulated SPECT images of an advanced anthropomorphic lung software phantom including respiratory and cardiac motion, where the mild COPD lung had an overall ventilation reduction of 5%.ResultsThe best separation between healthy and mild COPD lung images as determined using the CVT measure of ventilation inhomogeneity and 125 MBq 99mTc was obtained using a low-energy high-resolution collimator (LEHR) and a power 6 Butterworth post-filter with a cutoff frequency of 0.6 to 0.7 cm−1. Sixty-four reconstruction updates and a small kernel size should be used when the whole lung is analysed, and for the reduced lung a greater number of updates and a larger kernel size are needed.ConclusionsA LEHR collimator and 125 99mTc MBq together with an optimal combination of cutoff frequency, number of updates and kernel size, gave the best result. Suboptimal selections of either cutoff frequency, number of updates and kernel size will reduce the imaging system’s ability to detect mild COPD in the lung phantom.