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Does quantitative lung SPECT detect lung abnormalities earlier than lung function tests?: Results of a pilot study
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. 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, Division of Cardiovascular 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 Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
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.ORCID iD: 0000-0003-0209-498X
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2014 (English)In: EJNMMI Research, ISSN 2191-219X, E-ISSN 2191-219X, Vol. 4, no 39, 1-12 p.Article in journal (Refereed) Published
Abstract [en]

Background: Heterogeneous ventilation in lungs of allergic individuals, cigarette smokers, asthmatics and chronic obstructive pulmonary disease (COPD) patients has been demonstrated using imaging modalities such as PET, MR and 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-frequency 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.

Method: Fourteen 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 frequency curve (AUC), for CV values greater than a threshold value CVT, AUC(CV> CVT), was used as the measure of ventilation heterogeneity.

Results: Patients 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, RV/TLC (p=0.009), and 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.

Conclusions: Among 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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2014. Vol. 4, no 39, 1-12 p.
Keyword [en]
Quantitative lung SPECT, ventilation heterogeneities, lung function tests
National Category
Clinical Medicine Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:liu:diva-106666DOI: 10.1186/s13550-014-0039-1ISI: 000358049300001PubMedID: 26055938Scopus ID: 2-s2.0-84905881037OAI: oai:DiVA.org:liu-106666DiVA: diva2:717920
Note

On the date of the defence date of the Ph.D. Thesis the status of this article was Manuscript.

Available from: 2014-05-19 Created: 2014-05-19 Last updated: 2017-12-05Bibliographically approved
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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Supervisors
Available from: 2014-05-19 Created: 2014-05-19 Last updated: 2015-03-20Bibliographically approved

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Norberg, PernillaPersson, H LennartSchmekel, BirgittaAlm Carlsson, GudrunWahlin, KarlSandborg, MichaelGustafsson, Agnetha

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Norberg, PernillaPersson, H LennartSchmekel, BirgittaAlm Carlsson, GudrunWahlin, KarlSandborg, MichaelGustafsson, Agnetha
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Center for Medical Image Science and Visualization (CMIV)Division of Radiological SciencesFaculty of Health SciencesDepartment of Radiation PhysicsDivision of Cardiovascular MedicineDepartment of Respiratory MedicineDepartment of Clinical Physiology in LinköpingStatisticsFaculty of Arts and Sciences
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