
Journal of Shanghai Jiao Tong University (Medical Science) ›› 2023, Vol. 43 ›› Issue (3): 385-390.doi: 10.3969/j.issn.1674-8115.2023.03.016
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LIU Chenjun(
), YIN Bohao, SUN Hui, ZHANG Wei(
)
Received:2022-08-22
Accepted:2023-02-17
Online:2023-03-28
Published:2023-03-28
Contact:
ZHANG Wei
E-mail:chenjunliuorth@163.com;orthozhang@sjtu.edu.cn
Supported by:CLC Number:
LIU Chenjun, YIN Bohao, SUN Hui, ZHANG Wei. Application of non-invasive methods of radiology to the osteoporosis[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2023, 43(3): 385-390.
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URL: https://xuebao.shsmu.edu.cn/EN/10.3969/j.issn.1674-8115.2023.03.016
| 1 | WRIGHT N C, SAAG K G, DAWSON-HUGHES B, et al. The impact of the new National Bone Health Alliance (NBHA) diagnostic criteria on the prevalence of osteoporosis in the United States: supplementary presentation[J]. Osteoporos Int, 2017, 28(11): 3283-3284. |
| 2 | KIMMEL D B, VENNIN S, DESYATOVA A, et al. Bone architecture, bone material properties, and bone turnover in non-osteoporotic post-menopausal women with fragility fracture[J]. Osteoporos Int, 2022, 33(5): 1125-1136. |
| 3 | ADAMS J E. Advances in bone imaging for osteoporosis[J]. Nat Rev Endocrinol, 2013, 9(1): 28-42. |
| 4 | PADLINA I, GONZALEZ-RODRIGUEZ E, HANS D, et al. The lumbar spine age-related degenerative disease influences the BMD not the TBS: the Osteolaus cohort[J]. Osteoporos Int, 2017, 28(3): 909-915. |
| 5 | AMNUAYWATTAKORN S, SRITARA C, UTAMAKUL C, et al. Simulated increased soft tissue thickness artefactually decreases trabecular bone score: a phantom study[J]. BMC Musculoskelet Disord, 2016, 17(1): 17. |
| 6 | RAJAN R, CHERIAN K E, KAPOOR N, et al. Trabecular bone score-an emerging tool in the management of osteoporosis[J]. Indian J Endocrinol Metab, 2020, 24(3): 237-243. |
| 7 | MESSINA C, RINAUDO L, CESANA B M, et al. Prediction of osteoporotic fragility re-fracture with lumbar spine DXA-based derived bone strain index: a multicenter validation study[J]. Osteoporos Int, 2021, 32(1): 85-91. |
| 8 | HUMBERT L, MARTELLI Y, FONOLLÀ R, et al. 3D-DXA: assessing the femoral shape, the trabecular macrostructure and the cortex in 3D from DXA images[J]. IEEE Trans Med Imaging, 2017, 36(1): 27-39. |
| 9 | CLOTET J, MARTELLI Y, DI GREGORIO S, et al. Structural parameters of the proximal femur by 3-dimensional dual-energy X-ray absorptiometry software: comparison with quantitative computed tomography[J]. J Clin Densitom, 2018, 21(4): 550-562. |
| 10 | HE Q F, SUN H, SHU L Y, et al. Radiographic predictors for bone mineral loss: cortical thickness and index of the distal femur[J]. Bone Joint Res, 2018, 7(7): 468-475. |
| 11 | LIM H K, HA H I, PARK S Y, et al. Comparison of the diagnostic performance of CT Hounsfield unit histogram analysis and dual-energy X-ray absorptiometry in predicting osteoporosis of the femur[J]. Eur Radiol, 2019, 29(4): 1831-1840. |
| 12 | LI Y L, WONG K H, LAW M W M, et al. Opportunistic screening for osteoporosis in abdominal computed tomography for Chinese population[J]. Arch Osteoporos, 2018, 13(1): 76. |
| 13 | POOLE K E, TREECE G M, PEARSON R A, et al. Romosozumab enhances vertebral bone structure in women with low bone density[J]. J Bone Miner Res, 2022, 37(2): 256-264. |
| 14 | SU Y B, WANG L, LIU X Y, et al. Lack of periosteal apposition in the head and neck of femur after menopause in Chinese women with high risk for hip fractures—a cross-sectional study with QCT[J]. Bone, 2020, 139: 115545. |
| 15 | 程晓光, 王亮, 曾强, 等. 中国定量CT骨质疏松症诊断指南(2018)[J]. 中华健康管理学杂志, 2019, 5(3): 195-200. |
| CHEN X G, WANG L, ZENG Q, et al. Chinese guideline for the diagnosis of osteoporosis with quantitative computed tomography(2018)[J]. Chin J Health Manage, 2019, 5(3): 195-200. | |
| 16 | SCHULTE F A, CHRISTEN P, BADILATTI S D, et al. Virtual supersampling as post-processing step preserves the trabecular bone morphometry in human peripheral quantitative computed tomography scans[J]. PLoS One, 2019, 14(2): e0212280. |
| 17 | HANSEN S, SHANBHOGUE V, FOLKESTAD L, et al. Bone microarchitecture and estimated strength in 499 adult Danish women and men: a cross-sectional, population-based high-resolution peripheral quantitative computed tomographic study on peak bone structure[J]. Calcif Tissue Int, 2014, 94(3): 269-281. |
| 18 | SAMELSON E J, BROE K E, XU H F, et al. Cortical and trabecular bone microarchitecture as an independent predictor of incident fracture risk in older women and men in the Bone Microarchitecture International Consortium (BoMIC): a prospective study[J]. Lancet Diabetes Endocrinol, 2019, 7(1): 34-43. |
| 19 | BURT L A, LIANG Z Y, SAJOBI T T, et al. Sex- and site-specific normative data curves for HR-pQCT[J]. J Bone Miner Res, 2016, 31(11): 2041-2047. |
| 20 | ALVARENGA J C, CAPARBO V F, DOMICIANO D S, et al. Age-related reference data of bone microarchitecture, volumetric bone density, and bone strength parameters in a population of healthy Brazilian men: an HR-pQCT study[J]. Osteoporos Int, 2022, 33(6): 1309-1321. |
| 21 | RAMCHAND S K, DAVID N L, LEE H, et al. Effects of combination denosumab and high-dose teriparatide administration on bone microarchitecture and estimated strength: the DATA-HD HR-pQCT study[J]. J Bone Miner Res, 2021, 36(1): 41-51. |
| 22 | NILSSON A G, SUNDH D, JOHANSSON L, et al. Type 2 diabetes mellitus is associated with better bone microarchitecture but lower bone material strength and poorer physical function in elderly women: a population-based study[J]. J Bone Miner Res, 2017, 32(5): 1062-1071. |
| 23 | MANSKE S L, DAVISON E M, BURT L A, et al. The estimation of second-generation HR-pQCT from first-generation HR-pQCT using in vivo cross-calibration[J]. J Bone Miner Res, 2017, 32(7): 1514-1524. |
| 24 | SODICKSON A D, KERALIYA A, CZAKOWSKI B, et al. Dual energy CT in clinical routine: how it works and how it adds value[J]. Emerg Radiol, 2021, 28(1): 103-117. |
| 25 | ZHOU S W, ZHU L, YOU T, et al. In vivo quantification of bone mineral density of lumbar vertebrae using fast kVp switching dual-energy CT: correlation with quantitative computed tomography[J]. Quant Imaging Med Surg, 2021, 11(1): 341-350. |
| 26 | SHEN W, SCHERZER R, GANTZ M, et al. Relationship between MRI-measured bone marrow adipose tissue and hip and spine bone mineral density in African-American and Caucasian participants: the CARDIA study[J]. J Clin Endocrinol Metab, 2012, 97(4): 1337-1346. |
| 27 | LI J, CHEN X, LU L Y, et al. The relationship between bone marrow adipose tissue and bone metabolism in postmenopausal osteoporosis[J]. Cytokine Growth Factor Rev, 2020, 52: 88-98. |
| 28 | LIU Z H, ZHANG Y T, LIU Z, et al. Dual-energy computed tomography virtual noncalcium technique in diagnosing osteoporosis: correlation with quantitative computed tomography[J]. J Comput Assist Tomogr, 2021, 45(3): 452-457. |
| 29 | WICHMANN J L, BOOZ C, WESARG S, et al. Dual-energy CT-based phantomless in vivo three-dimensional bone mineral density assessment of the lumbar spine[J]. Radiology, 2014, 271(3): 778-784. |
| 30 | BOOZ C, HOFMANN P C, SEDLMAIR M, et al. Evaluation of bone mineral density of the lumbar spine using a novel phantomless dual-energy CT post-processing algorithm in comparison with dual-energy X-ray absorptiometry[J]. Eur Radiol Exp, 2017, 1(1): 11. |
| 31 | CHANG G, HONIG S, LIU Y X, et al. 7 Tesla MRI of bone microarchitecture discriminates between women without and with fragility fractures who do not differ by bone mineral density[J]. J Bone Miner Metab, 2015, 33(3): 285-293. |
| 32 | RAJAPAKSE C S, HOTCA A, NEWMAN B T, et al. Patient-specific hip fracture strength assessment with microstructural MR imaging-based finite element modeling[J]. Radiology, 2017, 283(3): 854-861. |
| 33 | RAJAPAKSE C S, FARID A R, KARGILIS D C, et al. MRI-based assessment of proximal femur strength compared to mechanical testing[J]. Bone, 2020, 133: 115227. |
| 34 | ZHANG L Y, WANG L, FU R S, et al. In vivo assessment of age- and loading configuration-related changes in multiscale mechanical behavior of the human proximal femur using MRI-based finite element analysis[J]. J Magn Reson Imaging, 2021, 53(3): 905-912. |
| 35 | JERBAN S, MA Y J, JANG H, et al. Water proton density in human cortical bone obtained from ultrashort echo time (UTE) MRI predicts bone microstructural properties[J]. Magn Reson Imaging, 2020, 67: 85-89. |
| 36 | BAUM T, YAP S P, KARAMPINOS D C, et al. Does vertebral bone marrow fat content correlate with abdominal adipose tissue, lumbar spine bone mineral density, and blood biomarkers in women with type 2 diabetes mellitus?[J]. J Magn Reson Imaging, 2012, 35(1): 117-124. |
| 37 | HE J, FANG H, LI X N. Vertebral bone marrow fat content in normal adults with varying bone densities at 3T magnetic resonance imaging[J]. Acta Radiol, 2019, 60(4): 509-515. |
| 38 | LI X J, SHET K, XU K P, et al. Unsaturation level decreased in bone marrow fat of postmenopausal women with low bone density using high resolution magic angle spinning (HRMAS) 1H NMR spectroscopy[J]. Bone, 2017, 105: 87-92. |
| 39 | WOODS G N, EWING S K, SCHAFER A L, et al. Saturated and unsaturated bone marrow lipids have distinct effects on bone density and fracture risk in older adults[J]. J Bone Miner Res, 2022, 37(4): 700-710. |
| 40 | GUO Y H, CHEN Y J, ZHANG X T, et al. Magnetic susceptibility and fat content in the lumbar spine of postmenopausal women with varying bone mineral density[J]. J Magn Reson Imaging, 2019, 49(4): 1020-1028. |
| 41 | MOMENI M, ASADZADEH M, MOWLA K, et al. Sensitivity and specificity assessment of DWI and ADC for the diagnosis of osteoporosis in postmenopausal patients[J]. Radiol med, 2020, 125(1): 68-74. |
| 42 | RAUM K, GRIMAL Q, VARGA P, et al. Ultrasound to assess bone quality[J]. Curr Osteoporos Rep, 2014, 12(2): 154-162. |
| 43 | MOAYYERI A, ADAMS J E, ADLER R A, et al. Quantitative ultrasound of the heel and fracture risk assessment: an updated meta-analysis[J]. Osteoporos Int, 2012, 23(1): 143-153. |
| 44 | MCCLOSKEY E V, KANIS J A, ODÉN A, et al. Predictive ability of heel quantitative ultrasound for incident fractures: an individual-level meta-analysis[J]. Osteoporos Int, 2015, 26(7): 1979-1987. |
| 45 | LIU Z J, ZHANG C, MA C, et al. Automatic phantom-less QCT system with high precision of BMD measurement for osteoporosis screening: technique optimisation and clinical validation[J]. J Orthop Transl, 2022, 33: 24-30. |
| 46 | LI Y C, CHEN H H, LU H H S, et al. Can a deep-learning model for the automated detection of vertebral fractures approach the performance level of human subspecialists?[J]. Clin Orthop Relat Res, 2021, 479(7): 1598-1612. |
| 47 | FANG Y J, LI W, CHEN X J, et al. Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks[J]. Eur Radiol, 2021, 31(4): 1831-1842. |
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