A quantitative computed tomography approach towards opportunistic osteoporosis screening

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dc.contributor.advisorBoyd, Steven Kyle
dc.contributor.authorMichalski, Andrew Steven
dc.contributor.committeememberEdwards, William Brent
dc.contributor.committeememberPowell, James N.
dc.contributor.committeememberJohnston, James B.
dc.contributor.committeememberSalo, Paul T.
dc.contributor.committeememberManske, Sarah Lynn
dc.date2020-06
dc.date.accessioned2020-03-24T14:59:57Z
dc.date.available2020-03-24T14:59:57Z
dc.date.issued2020-03-20
dc.description.abstractOpportunistic computed tomography (oCT) complements dual X-ray absorptiometry (DXA) by screening for osteoporosis and determining subject-specific fracture risk. Quantitative CT-based bone mineral density (BMD) and finite element (FE) estimated bone strength outcomes are known to improve fracture prediction, as compared to DXA areal BMD. However, there are shortcomings of oCT, which limit its ability to be clinically integrated as a skeletal health assessment tool for the purpose of identifying individuals at high risk of fracture that have not yet had any additional osteoporosis screening, such as a DXA scan. In this dissertation, the oCT limitation of understanding how CT scan acquisition parameters influence the skeletal health assessment is first investigated by identifying differences between CT reconstruction kernels. By using a bone-type kernel, the estimated FE failure load was increased by 18.2%, as compared to a standard-type kernel, suggesting that a standardized reconstruction kernel should be used when performing any oCT analyses. An internal density calibration method was then developed and validated to overcome the limitation of requiring a density calibration phantom within the scan field-of-view to perform oCT skeletal assessment. The developed internal calibration approach uses five reference regions and relates the known Hounsfield Units to equivalent mass attenuation values and then to equivalent bone density values. This approach was validated both in cadavers and an in vivo cohort, and it was shown to have a precision of 7.2% for skeletal health assessment outcomes. Finally, an oCT screening cohort was established using clinically acquired abdominal CT scans and was used to predict low energy fracture at known major osteoporotic fracture sites. Using this cohort, oCT screening resulted in a maximum predictive value of 0.710 for the area under the receiver operator characteristic curve to predict women with low energy fractures. These findings overcome some of the shortcomings currently preventing oCT screening from being clinically integrated. By using the millions of CT scans performed each year, oCT screening can repurpose these scans to assess skeletal health and reduce the costs and burden of fracture to both the healthcare system and society.en_US
dc.identifier.citationMichalski, A. S. (2020). A quantitative computed tomography approach towards opportunistic osteoporosis screening (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/37644
dc.identifier.urihttp://hdl.handle.net/1880/111749
dc.language.isoengen_US
dc.publisher.facultyCumming School of Medicineen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectOpportunistic Screeningen_US
dc.subjectComputed Tomographyen_US
dc.subjectFinite Element Analysisen_US
dc.subjectOsteoporosisen_US
dc.subjectBoneen_US
dc.subject.classificationRadiologyen_US
dc.subject.classificationEngineering--Biomedicalen_US
dc.titleA quantitative computed tomography approach towards opportunistic osteoporosis screeningen_US
dc.typedoctoral thesisen_US
thesis.degree.disciplineEngineering – Biomedicalen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
ucalgary.item.requestcopytrueen_US
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