Statistical Properties of a Virtual Cohort for In Silico Trials Generated with a Statistical Anatomy Atlas.


Journal

Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512

Informations de publication

Date de publication:
Jan 2023
Historique:
received: 14 04 2022
accepted: 06 08 2022
pubmed: 7 9 2022
medline: 13 1 2023
entrez: 6 9 2022
Statut: ppublish

Résumé

Osteoporosis-related hip fragility fractures are a catastrophic event for patient lives but are not frequently observed in prospective studies, and therefore phase III clinical trials using fractures as primary clinical endpoint require thousands of patients enrolled for several years to reach statistical significance. A novel answer to the large number of subjects needed to reach the desired evidence level is offered by In Silico Trials, that is, the simulation of a clinical trial on a large cohort of virtual patients, monitoring the biomarkers of interest. In this work we investigated if statistical aliasing from a custom anatomy atlas could be used to expand the patient cohort while retaining the original biomechanical characteristics. We used a pair-matched cohort of 94 post-menopausal women (at the time of the CT scan, 47 fractured and 47 not fractured) to create a statistical anatomy atlas through principal component analysis, and up-sampled the atlas in order to obtain over 1000 synthetic patient models. We applied the biomechanical computed tomography pipeline to the resulting virtual cohort and compared its fracture risk distribution with that of the original physical cohort. While the distribution of femoral strength values in the non-fractured sub-group was nearly identical to that of the original physical cohort, that of the fractured sub-group was lower than in the physical cohort. Nonetheless, by using the classification threshold used for the original population, the synthetic population was still divided into two parts of approximatively equal number.

Identifiants

pubmed: 36066781
doi: 10.1007/s10439-022-03050-8
pii: 10.1007/s10439-022-03050-8
pmc: PMC9832093
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

117-124

Subventions

Organisme : Horizon 2020 Framework Programme
ID : 823712
Organisme : Horizon 2020 Framework Programme
ID : 101016503

Informations de copyright

© 2022. The Author(s).

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Auteurs

Antonino A La Mattina (AA)

Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna (IT), Bologna, Italy. antonino.lamattina@unibo.it.
Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy. antonino.lamattina@unibo.it.

Fabio Baruffaldi (F)

Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy.

Mark Taylor (M)

Medical Device Research Institute, College of Science and Engineering, Flinders University, Adelaide, Australia.

Marco Viceconti (M)

Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna (IT), Bologna, Italy.
Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy.

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