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Quantitative lung SPECT applied on simulated early COPD and humans with advanced COPD
Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.ORCID iD: 0000-0002-1380-2497
Linköping University, Department of Medical and Health Sciences, Pulmonary Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Respiratory Medicine.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics.ORCID iD: 0000-0003-0209-498X
Sahlgrenska Academy at University of Gothenburg.
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2013 (English)In: EJNMMI Research, ISSN 2191-219X, E-ISSN 2191-219X, Vol. 3, no 28Article in journal (Refereed) Published
Abstract [en]

BACKGROUND:Reduced 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.

METHODS:In 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.

RESULTS:A 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).

CONCLUSIONS:While our results are promising, the potential of the AUC(CVT) method to detect less advanced COPD in patients needs further clinical studies.

Place, publisher, year, edition, pages
Germany: SpringerOpen , 2013. Vol. 3, no 28
Keyword [en]
Quantitative lung SPECT, Ventilation, Iterative reconstruction, Lung disorder, Monte Carlo, COPD
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-96748DOI: 10.1186/2191-219X-3-28PubMedID: 23597059OAI: oai:DiVA.org:liu-96748DiVA: diva2:643190
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2017-12-06
In thesis
1. Quantification and optimisation of lung ventilation SPECT images
Open this publication in new window or tab >>Quantification and optimisation of lung ventilation SPECT images
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2014. 79 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1403
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-106667 (URN)10.3384/diss.diva-106667 (DOI)978-91-7519-359-5 (ISBN)
Public defence
2014-06-05, Eken, ingång 65 (HU) plan 9, Campus US, Linköpings universitet, Linköping, 09:00 (Swedish)
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Available from: 2014-05-19 Created: 2014-05-19 Last updated: 2015-03-20Bibliographically approved

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Norberg, PernillaPersson, Hans LennartAlm Carlsson, GudrunSandborg, MichaelGustafsson, Agnetha

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Norberg, PernillaPersson, Hans LennartAlm Carlsson, GudrunSandborg, MichaelGustafsson, Agnetha
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Radiation PhysicsCenter for Medical Image Science and Visualization (CMIV)Faculty of Health SciencesDepartment of Radiation PhysicsPulmonary MedicineDepartment of Respiratory MedicineDivision of Radiological SciencesDepartment of Clinical Physiology in Linköping
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