Trabecular bone microstructure parameters as predictors for chronological age: a systematic review.
Arshiya TabassumMansharan Kaur Chainchel SinghNorliza IbrahimVinita SanjeevanMohd Yusmiaidil Putera Mohd YusofPublished in: Forensic science, medicine, and pathology (2024)
Estimating chronological age is crucial in forensic identification. The increased application of medical imaging in age analysis has facilitated the development of new quantitative methods for the macroscopic evaluation of bones. This study aimed to determine the association of age-related changes in the trabecular microstructure with chronological age for age estimation in forensic science through different non-invasive imaging techniques. This systematic review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. An electronic search was performed with PubMed/MEDLINE, Scopus, and Cochrane databases as well as with a Google Scholar search. Qualitative synthesis was performed using the Anatomical Quality Assessment tool. A detailed literature search yielded 3467 articles. A total of 14 articles were ultimately included in the study. A narrative approach was employed to synthesize the data. Microcomputed tomography, high-resolution peripheral quantitative computed tomography, and cone beam computed tomography have been used for the quantitative estimation of age. These imaging techniques aid in identifying the trabecular bone microarchitectural parameters for chronological age estimation. Age-related changes in trabecular bone included a decrease in the bone volume fraction, trabecular number, and connectivity density and an increase in trabecular separation. This study also revealed that morphometric indices vary with age and anatomical site. This study is registered with the International Prospective Register of Systematic Reviews (PROSPERO) with the registration number CDRD42023391873.
Keyphrases
- systematic review
- high resolution
- bone mineral density
- meta analyses
- computed tomography
- postmenopausal women
- randomized controlled trial
- white matter
- machine learning
- emergency department
- public health
- artificial intelligence
- multiple sclerosis
- soft tissue
- functional connectivity
- high speed
- quality improvement
- liquid chromatography
- bone regeneration
- resting state