• Schwarzenberg P, Darwiche S, Yoon RS, Dailey HL. Imaging modalities to assess fracture healing. Curr Osteoporos Rep. 2020;18(3):169–79. https://doi.org/10.1007/s11914-020-00584-5. This paper outlines use of radiographic, CT, DXA, and MRI-based approaches for analyzing fracture union and non-union. It additionally highlights the information that can be derived from finite element modeling of bone calluses and compares novel techniques to the radiographic gold standard.
Otjen J, et al. Foot and ankle musculoskeletal imaging of pediatric patients with cerebral palsy. AJR Am J Roentgenol. 2020;214(6):1389–97. https://doi.org/10.2214/AJR.19.22354.
Berkeley R, Tennant S, Saifuddin A. Multimodality imaging of the paediatric flatfoot. Skeletal Radiol. 2021;50(11):2133–49. https://doi.org/10.1007/s00256-021-03806-8.
Fayad LM, Bluemke DA, Weber KL, Fishman EK. Characterization of pediatric skeletal tumors and tumor-like conditions: specific cross-sectional imaging signs. Skeletal Radiol. 2006;35(5):259–68. https://doi.org/10.1007/s00256-006-0079-3.
Paul AR, Adamo MA. Non-accidental trauma in pediatric patients: a review of epidemiology, pathophysiology, diagnosis and treatment. Transl Pediatr. 2014;3(3):195–207. https://doi.org/10.3978/j.issn.2224-4336.2014.06.01.
Article PubMed PubMed Central Google Scholar
Duffy SO, Squires J, Fromkin JB, Berger RP. Use of skeletal surveys to evaluate for physical abuse: analysis of 703 consecutive skeletal surveys. Pediatrics. 2011;127(1):e47-52. https://doi.org/10.1542/peds.2010-0298.
Article PubMed PubMed Central Google Scholar
Jarrett DY, Ecklund K. EOS imaging of scoliosis, leg length discrepancy and alignment. Semin Roentgenol. 2021;56(3):228–44. https://doi.org/10.1053/j.ro.2021.06.001.
Hecker A, Lerch TD, Egli RJ, Liechti EF, Klenke FM. The EOS 3D imaging system reliably measures posterior tibial slope. J Orthop Surg Res. 2021;16(1):388. https://doi.org/10.1186/s13018-021-02529-9.
Article PubMed PubMed Central Google Scholar
Zember J, Vega P, Rossi I, Rosenberg ZS. Normal development imaging pitfalls and injuries in the pediatric shoulder. Pediatr Radiol. 2019;49(12):1617–28. https://doi.org/10.1007/s00247-019-04512-3.
Cavallo F, Mohn A, Chiarelli F, Giannini C. Evaluation of bone age in children: a mini-review. Front Pediatr. 2021;9:580314. https://doi.org/10.3389/fped.2021.580314.
Article PubMed PubMed Central Google Scholar
De Sanctis V, Di Maio S, Soliman AT, Raiola G, Elalaily R, Millimaggi G. Hand X-ray in pediatric endocrinology: skeletal age assessment and beyond. Indian J Endocrinol Metab. 2014;18(Suppl 1):S63-71. https://doi.org/10.4103/2230-8210.145076.
Article PubMed PubMed Central Google Scholar
Thevenot J, et al. Trabecular homogeneity index derived from plain radiograph to evaluate bone quality. J Bone Miner Res. 2013;28(12):2584–91. https://doi.org/10.1002/jbmr.1987.
Huber MB, et al. Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs. Med Phys. 2009;36(11):5089–98. https://doi.org/10.1118/1.3215535.
Article CAS PubMed Google Scholar
Clavert P, et al. How to determine the bone mineral density of the distal humerus with radiographic tools? Surg Radiol Anat. 2016;38(4):389–93. https://doi.org/10.1007/s00276-015-1569-6.
•• Wang F, Zheng L, Theopold J, Schleifenbaum S, Heyde CE, Osterhoff G. Methods for bone quality assessment in human bone tissue: a systematic review. J Orthop Surg Res. 2022;17(1):174. https://doi.org/10.1186/s13018-022-03041-4. This paper reviews the methods for bone density, microstructrue, and quality assessment using a variety of imaging modalieties including radiographs, DXA, CT, and MRI as well as mechanical testing methods used to test bone quality in a research setting. It summarizes the benefits and pitfalls of each modality and highlights the importance of quantitative bone assessment.
Article PubMed PubMed Central Google Scholar
Kim SB, et al. Reliability of the EOS imaging system for assessment of the spinal and pelvic alignment in the sagittal plane. Clin Orthop Surg. 2018;10(4):500–7. https://doi.org/10.4055/cios.2018.10.4.500.
Article PubMed PubMed Central Google Scholar
Machida M, Rocos B, Zabjek K, Lebel DE. A comparison of the reliability and vulnerability of 3D sterEOS and 2D EOS when measuring the sagittal spinal alignment of patients with adolescent idiopathic scoliosis. Spine Deform. 2022;10(5):1029–34. https://doi.org/10.1007/s43390-022-00499-4.
Sun J, et al. Automatic video analysis framework for exposure region recognition in X-ray imaging automation. IEEE J Biomed Health Inform. 2022;26(9):4359–70. https://doi.org/10.1109/JBHI.2022.3172369.
Reddy PK, Kanakatte A, Gubbi J, Poduval M, Ghose A, Purushothaman B. Anatomical landmark detection using deep appearance-context network. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:3569–72. https://doi.org/10.1109/EMBC46164.2021.9630457.
Sa R, et al. Intervertebral disc detection in X-ray images using faster R-CNN. Annu Int Conf IEEE Eng Med Biol Soc. 2017;2017:564–7. https://doi.org/10.1109/EMBC.2017.8036887.
Kundu R, Das R, Geem ZW, Han GT, Sarkar R. Pneumonia detection in chest X-ray images using an ensemble of deep learning models. PLoS ONE. 2021;16(9):e0256630. https://doi.org/10.1371/journal.pone.0256630.
Article CAS PubMed PubMed Central Google Scholar
Widodo CS, Naba A, Mahasin MM, Yueniwati Y, Putranto TA, Patra PI. UBNet: deep learning-based approach for automatic X-ray image detection of pneumonia and COVID-19 patients. J Xray Sci Technol. 2022;30(1):57–71. https://doi.org/10.3233/XST-211005.
Article CAS PubMed Google Scholar
Reis EP, et al. BRAX, Brazilian labeled chest x-ray dataset. Sci Data. 2022;9(1):487. https://doi.org/10.1038/s41597-022-01608-8.
Article PubMed PubMed Central Google Scholar
Shevroja E, Cafarelli FP, Guglielmi G, Hans D. DXA parameters, trabecular bone score (TBS) and bone mineral density (BMD), in fracture risk prediction in endocrine-mediated secondary osteoporosis. Endocrine. 2021;74(1):20–8. https://doi.org/10.1007/s12020-021-02806-x.
Article CAS PubMed PubMed Central Google Scholar
Martel D, Monga A, Chang G. Osteoporosis imaging. Radiol Clin North Am. 2022;60(4):537–45. https://doi.org/10.1016/j.rcl.2022.02.003.
Havrda JB (2012)Pediatric bone densitometry. Radiol Technol 84(2):155–77
Wasserman H, O’Donnell JM, Gordon CM. Use of dual energy X-ray absorptiometry in pediatric patients. Bone. 2017;104:84–90. https://doi.org/10.1016/j.bone.2016.12.008.
Gordon RJ, Gordon CM. Bone health in pediatric patients with IBD: what is new? Curr Osteoporos Rep. 2021;19(4):429–35. https://doi.org/10.1007/s11914-021-00691-x.
Wasserman H, Gordon CM. Bone mineralization and fracture risk assessment in the pediatric population. J Clin Densitom. 2017;20(3):389–96. https://doi.org/10.1016/j.jocd.2017.06.007.
Borga M, et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. 2018;66(5):1–9. https://doi.org/10.1136/jim-2018-000722.
Article PubMed PubMed Central Google Scholar
Shepherd JA, Ng BK, Sommer MJ, Heymsfield SB. Body composition by DXA. Bone. 2017;104:101–5. https://doi.org/10.1016/j.bone.2017.06.010.
Article PubMed PubMed Central Google Scholar
Di Iorgi N, Maruca K, Patti G, Mora S. Update on bone density measurements and their interpretation in children and adolescents. Best Pract Res Clin Endocrinol Metab. 2018;32(4):477–98. https://doi.org/10.1016/j.beem.2018.06.002.
Bowman L, Loucks AB. In vivo assessment of cortical bone fragility. Curr Osteoporos Rep. 2020;18(1):13–22. https://doi.org/10.1007/s11914-020-00558-7.
Article PubMed PubMed Central Google Scholar
Litrenta J, Masrouha K, Wasterlain A, Castaneda P. Ultrasound evaluation of pediatric orthopaedic patients. J Am Acad Orthop Surg. 2020;28(16):e696–705. https://doi.org/10.5435/JAAOS-D-17-00895.
Piccolo CL, et al. Pediatric musculoskeletal injuries: role of ultrasound and magnetic resonance imaging. Musculoskelet Surg. 2017;101(Suppl 1):85–102. https://doi.org/10.1007/s12306-017-0452-5.
Article CAS PubMed Google Scholar
Karnik AS, Karnik A, Joshi A. Ultrasound examination of pediatric musculoskeletal diseases and neonatal spine. Indian J Pediatr. 2016;83(6):565–77. https://doi.org/10.1007/s12098-015-1957-2.
Riccabona M. Pediatric three-dimensional ultrasound: basics and potential clinical value. Clin Imaging. 200
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