Bone ageing and osteoporosis: Automated DXA image analysis for population imaging (2025)

Farzi, M. (2018). Bone ageing and osteoporosis: Automated DXA image analysis for population imaging. [Doctoral Thesis, The University of Sheffield].

Farzi, Mohsen. / Bone ageing and osteoporosis : Automated DXA image analysis for population imaging. 2018. 183 p.

@phdthesis{59f3a314c61e4a9287d5863775be7eeb,

title = "Bone ageing and osteoporosis: Automated DXA image analysis for population imaging",

abstract = "Osteoporosis is an age-associated bone disease characterised by low bone mass. The consequent fragility fractures with increased follow-up mortality and morbidity underlie the clinical significance of osteoporosis in public health. However, current diagnostic criteria using bone mineral density (BMD) at the femoral neck at most can identify half of the fragility fractures, and thereby the ability to provide new metrics capturing the bone strength beyond neck BMD remains of interest in osteoporosis research. This study aims to, first, quantify pixel BMD at anatomically corresponding locations in the femur; second, model the evolution of spatial BMD patterns with ageing; and third, characterise how trabecular and cortical bone arrangements change at different stages of osteoporosis progression. To construct the atlas, a novel cross-calibration procedure is proposed to integrate data from different DXA manufacturers into an amalgamated largescale dataset (n > 13000). A new technique, termed region free analysis (RFA), is proposed to eliminate morphological variation between scans by warping each image into a reference template. This image warping establishes a correspondence between pixel coordinates that allows modelling pixel BMD evolution with ageing using smooth quantile curves. Given access to largescale datasets, automatic quality control of DXA scans has been identified as an emerging challenge to the community for which an unsupervised nondistortion-specific, opinion-free framework was proposed. The developed atlas usefully added to our understanding of spatial BMD patterns and their relationship with osteoporosis. The concept of osteoporosis progression is introduced by proposing bone age as the age at which an individual bone map best fits the constructed atlas. Normalising BMD maps for bone age, local fracture-specific patterns were identified. The proposed framework in this thesis constitutes a first step toward modelling osteoporosis progression to identify better bone-based risk factors for prediction of fragility fractures.",

keywords = "Dual-energy X-ray Absorptiometry (DXA), Region Free Analysis (RFA), Osteoporosis, Disease Progression Estimation,, Atlas Development",

author = "Mohsen Farzi",

note = "Includes bibliographical references",

year = "2018",

month = dec,

day = "21",

language = "English",

school = "The University of Sheffield",

}

Farzi, M 2018, 'Bone ageing and osteoporosis: Automated DXA image analysis for population imaging', Doctor of Philosophy, The University of Sheffield. <http://etheses.whiterose.ac.uk/22477/>

Bone ageing and osteoporosis: Automated DXA image analysis for population imaging. / Farzi, Mohsen.
2018. 183 p.

Research output: Thesis › Doctoral Thesis

TY - BOOK

T1 - Bone ageing and osteoporosis

T2 - Automated DXA image analysis for population imaging

AU - Farzi, Mohsen

N1 - Includes bibliographical references

PY - 2018/12/21

Y1 - 2018/12/21

N2 - Osteoporosis is an age-associated bone disease characterised by low bone mass. The consequent fragility fractures with increased follow-up mortality and morbidity underlie the clinical significance of osteoporosis in public health. However, current diagnostic criteria using bone mineral density (BMD) at the femoral neck at most can identify half of the fragility fractures, and thereby the ability to provide new metrics capturing the bone strength beyond neck BMD remains of interest in osteoporosis research. This study aims to, first, quantify pixel BMD at anatomically corresponding locations in the femur; second, model the evolution of spatial BMD patterns with ageing; and third, characterise how trabecular and cortical bone arrangements change at different stages of osteoporosis progression. To construct the atlas, a novel cross-calibration procedure is proposed to integrate data from different DXA manufacturers into an amalgamated largescale dataset (n > 13000). A new technique, termed region free analysis (RFA), is proposed to eliminate morphological variation between scans by warping each image into a reference template. This image warping establishes a correspondence between pixel coordinates that allows modelling pixel BMD evolution with ageing using smooth quantile curves. Given access to largescale datasets, automatic quality control of DXA scans has been identified as an emerging challenge to the community for which an unsupervised nondistortion-specific, opinion-free framework was proposed. The developed atlas usefully added to our understanding of spatial BMD patterns and their relationship with osteoporosis. The concept of osteoporosis progression is introduced by proposing bone age as the age at which an individual bone map best fits the constructed atlas. Normalising BMD maps for bone age, local fracture-specific patterns were identified. The proposed framework in this thesis constitutes a first step toward modelling osteoporosis progression to identify better bone-based risk factors for prediction of fragility fractures.

AB - Osteoporosis is an age-associated bone disease characterised by low bone mass. The consequent fragility fractures with increased follow-up mortality and morbidity underlie the clinical significance of osteoporosis in public health. However, current diagnostic criteria using bone mineral density (BMD) at the femoral neck at most can identify half of the fragility fractures, and thereby the ability to provide new metrics capturing the bone strength beyond neck BMD remains of interest in osteoporosis research. This study aims to, first, quantify pixel BMD at anatomically corresponding locations in the femur; second, model the evolution of spatial BMD patterns with ageing; and third, characterise how trabecular and cortical bone arrangements change at different stages of osteoporosis progression. To construct the atlas, a novel cross-calibration procedure is proposed to integrate data from different DXA manufacturers into an amalgamated largescale dataset (n > 13000). A new technique, termed region free analysis (RFA), is proposed to eliminate morphological variation between scans by warping each image into a reference template. This image warping establishes a correspondence between pixel coordinates that allows modelling pixel BMD evolution with ageing using smooth quantile curves. Given access to largescale datasets, automatic quality control of DXA scans has been identified as an emerging challenge to the community for which an unsupervised nondistortion-specific, opinion-free framework was proposed. The developed atlas usefully added to our understanding of spatial BMD patterns and their relationship with osteoporosis. The concept of osteoporosis progression is introduced by proposing bone age as the age at which an individual bone map best fits the constructed atlas. Normalising BMD maps for bone age, local fracture-specific patterns were identified. The proposed framework in this thesis constitutes a first step toward modelling osteoporosis progression to identify better bone-based risk factors for prediction of fragility fractures.

KW - Dual-energy X-ray Absorptiometry (DXA)

KW - Region Free Analysis (RFA)

KW - Osteoporosis

KW - Disease Progression Estimation,

KW - Atlas Development

M3 - Doctoral Thesis

ER -

Farzi M. Bone ageing and osteoporosis: Automated DXA image analysis for population imaging. 2018. 183 p.