Chinese expert consensus on the diagnosis of osteoporosis by imaging and bone mineral density.

With an aging society, osteoporosis is one of the most common diseases threatening the health of China's elderly population and is an issue that is raising increasing concern. Osteoporosis is characterized by bone loss and increased susceptibility to fragility fractures. Various imaging modalities such as X-ray, CT, MRI and nuclear medicine along with assessment of bone mineral density (BMD) play an important role in its diagnosis and management, and the treatment requires multidisciplinary teamwork. A lack of consensus in the approach to imaging and BMD measurement is hampering the quality of service and patient care in China. Therefore a panel of Chinese experts from the fields of radiology, orthopedics, endocrinology and nuclear medicine reviewed the international guidelines, consensus and literature with the most recent data from China and, taking account of current clinical practice in China, the panel reached this consensus to help guide the diagnosis of osteoporosis using imaging and BMD. This consensus report provides guidelines and standards for the imaging and BMD assessment of osteoporosis and criteria for the diagnosis of osteoporosis in China.

[1]  Joseph E. Burns,et al.  Artificial Intelligence in Musculoskeletal Imaging: A Paradigm Shift , 2019, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[2]  Qianqian Wang,et al.  The Prevalence of Osteoporosis in China, a Nationwide, Multicenter DXA Survey , 2019, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[3]  J. Shepherd,et al.  Cross-calibration, Least Significant Change and Quality Assurance in Multiple Dual-Energy X-ray Absorptiometry Scanner Environments: 2019 ISCD Official Position , 2019, Journal of Clinical Densitometry.

[4]  Huijiang Song,et al.  Prevalence of osteoporotic vertebral fracture among community-dwelling elderly in Shanghai , 2019, Chinese medical journal.

[5]  Jianhua Yao,et al.  Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment. , 2019, The British journal of radiology.

[6]  Timothy J Ziemlewicz,et al.  Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults. , 2019, Radiology.

[7]  Q. Zeng,et al.  Prevalence of osteoporosis in China: a multicenter, large-scale survey of a health checkup population , 2019 .

[8]  Kai Li,et al.  Discordance in diagnosis of osteoporosis by quantitative computed tomography and dual-energy X-ray absorptiometry in Chinese elderly men , 2018, Journal of orthopaedic translation.

[9]  J. Kanis,et al.  A brief history of FRAX , 2018, Archives of Osteoporosis.

[10]  Cheng Chen,et al.  Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data , 2018, Journal of magnetic resonance imaging : JMRI.

[11]  J. Griffith,et al.  Osteoporotic vertebral deformity with endplate/cortex fracture is associated with higher further vertebral fracture risk: the Ms. OS (Hong Kong) study results , 2018, Osteoporosis International.

[12]  A. Napoli,et al.  Quantitative imaging techniques for the assessment of osteoporosis and sarcopenia. , 2018, Quantitative imaging in medicine and surgery.

[13]  Sandro G. da Silva,et al.  Artificial intelligence on the identification of risk groups for osteoporosis, a general review , 2018, BioMedical Engineering OnLine.

[14]  F. Pfeiffer,et al.  Bone mineral density measurements in vertebral specimens and phantoms using dual-layer spectral computed tomography , 2017, Scientific Reports.

[15]  W. Leslie,et al.  Trabecular bone score (TBS): Method and applications. , 2017, Bone.

[16]  Chih-Hwa Chen,et al.  Bone biomarker for the clinical assessment of osteoporosis: recent developments and future perspectives , 2017, Biomarker Research.

[17]  C. Cooper,et al.  UK clinical guideline for the prevention and treatment of osteoporosis , 2017, Archives of Osteoporosis.

[18]  Ronald M. Summers,et al.  Vertebral Body Compression Fractures and Bone Density: Automated Detection and Classification on CT Images. , 2017, Radiology.

[19]  P. Zysset,et al.  Clinical Use of Quantitative Computed Tomography-Based Advanced Techniques in the Management of Osteoporosis in Adults: the 2015 ISCD Official Positions-Part III. , 2015, Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry.

[20]  C. Cann,et al.  CTXA Hip—An Extension of Classical DXA Measurements Using Quantitative CT , 2014, PloS one.

[21]  Heinrich Resch,et al.  Trabecular Bone Score: A Noninvasive Analytical Method Based Upon the DXA Image , 2014, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[22]  N. Zhang,et al.  An increase in the incidence of hip fractures in Tangshan, China , 2014, Osteoporosis International.

[23]  Thomas M Link,et al.  osteoporosis imaging : State of the Art and Advanced Imaging 1 , 2022 .

[24]  S. Cummings,et al.  Rapidly increasing rates of hip fracture in Beijing, China , 2012, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[25]  Wei Yu,et al.  Cause analysis of missing diagnosis for vertebral fracture on lateral chest radiography , 2010 .

[26]  C. Cooper,et al.  European guidance for the diagnosis and management of osteoporosis in postmenopausal women , 2008, Osteoporosis International.

[27]  C. Cooper,et al.  European guidance for the diagnosis and management of osteoporosis in postmenopausal women , 2008, Osteoporosis International.

[28]  Jian Gong,et al.  Normal reference for bone density in healthy Chinese children. , 2007, Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry.

[29]  M. Nevitt,et al.  Vertebral fracture assessment using a semiquantitative technique , 1993, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[30]  Claus Christiansen,et al.  Diagnosis of Osteoporosis , 1992, Southern medical journal.

[31]  H. Genant,et al.  Quantitative Computed Tomography of Vertebral Spongiosa: A Sensitive Method for Detecting Early Bone Loss After Oophorectomy , 1982, Annals of internal medicine.

[32]  M. Sheridan Chinese Children , 1974 .

[33]  B. Riggs Diagnosis and Treatment of Primary Osteoporosis , 1968 .

[34]  Zhang Zhiha,et al.  Expert consensus on the diagnosis of osteoporosis in Chinese Population , 2014 .

[35]  Yong-bin Su,et al.  Validation of quantitative computed tomography‐derived areal bone mineral density with dual energy X‐ray absorptiometry in an elderly Chinese population , 2014, Chinese medical journal.

[36]  Judith E. Adams,et al.  Advances in bone imaging for osteoporosis , 2012, Nature Reviews Endocrinology.

[37]  Gabriele Armbrecht,et al.  Clinical use of quantitative computed tomography and peripheral quantitative computed tomography in the management of osteoporosis in adults: the 2007 ISCD Official Positions. , 2008, Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry.