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Research progress of routine CT and MRI in opportunistic screening for osteoporosis
LI Qintao  ZHANG Xiaomei  LUO Xi  WU Zichen  LIU Shaoqiang 

DOI:10.12015/issn.1674-8034.2026.02.032.


[Abstract] Osteoporosis (OP) is a prominent public health issue against the backdrop of global aging. Characterized by reduced bone mass and impaired bone microarchitecture, it is prone to causing fragility fractures and poses a serious threat to patients' health. At present, dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT), the gold standards in clinical practice, have limitations such as low popularity, high radiation dose or high cost. In contrast, opportunistic screening based on conventional computed tomography (CT) and magnetic resonance imaging (MRI) has become a research hotspot for the early diagnosis of OP, as it requires no additional costs or radiation exposure. The integration of artificial intelligence (AI) technology has further improved screening efficiency. However, current research progress in this field is relatively fragmented and has not yet formed a systematic integration, so it is necessary to refine core findings through a comprehensive review. This review systematically summarizes recent research advances in opportunistic screening for OP based on conventional CT and MRI, analyzes the application value of AI technology in this field, clarifies the limitations of existing studies including inconsistent diagnostic thresholds, pending optimization of calibration algorithms and insufficient model standardization, and discusses future development directions. This paper aims to provide a reference for the early diagnosis of OP and the optimization of clinical screening strategies, as well as to offer guidance for relevant clinical research.
[Keywords] osteoporosis；magnetic resonance imaging；computed tomography；opportunistic screening；artificial intelligence

LI Qintao1, 2   ZHANG Xiaomei1, 2   LUO Xi1, 2   WU Zichen1   LIU Shaoqiang1, 2*  

1 The First Clinical Medical School of Gannan Medical University, Ganzhou 341000, China

2 Department of Medical Imaging, the First Affiliated Hospital of Gannan Medical University. Ganzhou 341000, China

Corresponding author: LIU S Q, E-mail: Liushaoqiang116@163.com

Conflicts of interest   None.

Received  2025-11-20
Accepted  2026-01-30
DOI: 10.12015/issn.1674-8034.2026.02.032
DOI:10.12015/issn.1674-8034.2026.02.032.

[1]
XIAO P L, CUI A Y, HSU C J, et al. Global, regional prevalence, and risk factors of osteoporosis according to the World Health Organization diagnostic criteria: a systematic review and meta-analysis[J]. Osteoporos Int, 2022, 33(10): 2137-2153. DOI: 10.1007/s00198-022-06454-3.
[2]
LEBOFF M S, GREENSPAN S L, INSOGNA K L, et al. The clinician's guide to prevention and treatment of osteoporosis[J]. Osteoporos Int, 2022, 33(10): 2049-2102. DOI: 10.1007/s00198-021-05900-y.
[3]
O'KELLY J, BARTSCH R, KOSSACK N, et al. Real-world effectiveness of osteoporosis treatments in Germany[J/OL]. Arch Osteoporos, 2022, 17(1): 119 [2025-11-19]. https://pubmed.ncbi.nlm.nih.gov/36044096/. DOI: 10.1007/s11657-022-01156-z.
[4]
GAO L, MOODIE M, WATTS J J, et al. Cost-effectiveness of osteoporosis opportunistic screening using computed tomography in China[J/OL]. Value Health Reg Issues, 2023, 38: 38-44 [2025-11-19]. https://pubmed.ncbi.nlm.nih.gov/37454646/. DOI: 10.1016/j.vhri.2023.06.001.
[5]
LIN W T, HE C Q, XIE F Q, et al. Quantitative CT screening improved lumbar BMD evaluation in older patients compared to dual-energy X-ray absorptiometry[J/OL]. BMC Geriatr, 2023, 23(1): 231 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/37069511/. DOI: 10.1186/s12877-023-03963-6.
[6]
ROUX C. Opportunistic screening for osteoporosis[J/OL]. Jt Bone Spine, 2024, 91(5): 105726 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/38582362/. DOI: 10.1016/j.jbspin.2024.105726.
[7]
ZHANG Y H, GUO H, ZHU X S. Correlation among CT attenuation value of cancellous bone in the lumbar vertebrae, age, and bone mineral density measured by dual-energy X-ray absorptiometry[J]. Chin J Osteoporos, 2016, 22(6): 695-699. DOI: 10.3969/j.issn.1006-7108.2016.06.008.
[8]
PICKHARDT P J, POOLER B D, LAUDER T, et al. Opportunistic screening for osteoporosis using abdominal computed tomography scans obtained for other indications[J]. Ann Intern Med, 2013, 158(8): 588-595. DOI: 10.7326/0003-4819-158-8-201304160-00003.
[9]
COHEN A, FOLDES A J, HILLER N, et al. Opportunistic screening for osteoporosis and osteopenia by routine computed tomography scan: a heterogeneous, multiethnic, middle-eastern population validation study[J/OL]. Eur J Radiol, 2021, 136: 109568 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/33545629/. DOI: 10.1016/j.ejrad.2021.109568.
[10]
ZOU D, LI W S, DENG C, et al. The use of CT Hounsfield unit values to identify the undiagnosed spinal osteoporosis in patients with lumbar degenerative diseases[J]. Eur Spine J, 2019, 28(8): 1758-1766. DOI: 10.1007/s00586-018-5776-9.
[11]
LI Y L, WONG K H, LAW M W, et al. Opportunistic screening for osteoporosis in abdominal computed tomography for Chinese population[J/OL]. Arch Osteoporos, 2018, 13(1): 76 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/29987388/. DOI: 10.1007/s11657-018-0492-y.
[12]
PERRIER-CORNET J, OMOROU A Y, FAUNY M, et al. Opportunistic screening for osteoporosis using thoraco-abdomino-pelvic CT-scan assessing the vertebral density in rheumatoid arthritis patients[J]. Osteoporos Int, 2019, 30(6): 1215-1222. DOI: 10.1007/s00198-019-04931-w.
[13]
WANG P, SHE W, MAO Z Q, et al. Use of routine computed tomography scans for detecting osteoporosis in thoracolumbar vertebral bodies[J]. Skeletal Radiol, 2021, 50(2): 371-379. DOI: 10.1007/s00256-020-03573-y.
[14]
ZOU D, HE X, SHANG Z S, et al. Osteoporosis screening using QCT-based cutoff value of Hounsfield units in patients with degenerative lumbar diseases[J]. Eur Spine J, 2024, 33(12): 4499-4503. DOI: 10.1007/s00586-024-08491-4.
[15]
WANG X W, ZHAO W H, YAN X W, et al. The correlation between CT attenuation value, BMD, and T-score of the lumbar pedicle corresponding to cross section[J]. Chin J Osteoporos, 2022, 28(10): 1465-1471. DOI: 10.3969/j.issn.1006-7108.2022.10.011.
[16]
BUENGER F, SAKR Y, ECKARDT N, et al. Correlation of quantitative computed tomography derived bone density values with Hounsfield units of a contrast medium computed tomography in 98 thoraco-lumbar vertebral bodies[J]. Arch Orthop Trauma Surg, 2022, 142(11): 3335-3340. DOI: 10.1007/s00402-021-04184-5.
[17]
PU M Y, ZHANG B, ZHU Y, et al. Hounsfield unit for evaluating bone mineral density and strength: variations in measurement methods[J/OL]. World Neurosurg, 2023, 180: e56-e68 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/37544597/. DOI: 10.1016/j.wneu.2023.07.146.
[18]
MATHESON B E, BOYD S K. Establishing the effect of computed tomography reconstruction kernels on the measure of bone mineral density in opportunistic osteoporosis screening[J/OL]. Sci Rep, 2025, 15(1): 5449 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/39953113/. DOI: 10.1038/s41598-025-88551-x.
[19]
SHEPHERD J A, SCHOUSBOE J T, BROY S B, et al. Executive summary of the 2015 ISCD position development conference on advanced measures from DXA and QCT: fracture prediction beyond BMD[J]. J Clin Densitom, 2015, 18(3): 274-286. DOI: 10.1016/j.jocd.2015.06.013.
[20]
DU MONT S, BARKMANN R, DAMM T, et al. Long-term reproducibility of BMD-measurements with clinical QCT using simultaneous and asynchronous calibration methods and different measurement and reconstruction protocols[J]. Calcif Tissue Int, 2024, 115(5): 552-561. DOI: 10.1007/s00223-024-01303-3.
[21]
SKORNITZKE S, VATS N, KOPYTOVA T, et al. Asynchronous calibration of quantitative computed tomography bone mineral density assessment for opportunistic osteoporosis screening: phantom-based validation and parameter influence evaluation[J/OL]. Sci Rep, 2022, 12(1): 20729 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/36456574/. DOI: 10.1038/s41598-022-24546-2.
[22]
PRADO M, KHOSLA S, CHAPUT C, et al. Opportunistic application of phantom-less calibration methods for fracture risk prediction using QCT/FEA[J]. Eur Radiol, 2021, 31(12): 9428-9435. DOI: 10.1007/s00330-021-08071-w.
[23]
BARTENSCHLAGER S, DANKERL P, CHAUDRY O, et al. BMD accuracy errors specific to phantomless calibration of CT scans of the lumbar spine[J/OL]. Bone, 2022, 157: 116304 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/34973497/. DOI: 10.1016/j.bone.2021.116304.
[24]
BARTENSCHLAGER S, CAVALLARO A, POGARELL T, et al. Impact of intravenous CT contrast agents on internal calibration techniques to determine trabecular BMD of the lumbar spine[J/OL]. Eur J Radiol, 2025, 183: 111923 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/39823659/. DOI: 10.1016/j.ejrad.2025.111923.
[25]
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/OL]. J Orthop Translat, 2022, 33: 24-30 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/35228994/. DOI: 10.1016/j.jot.2021.11.008.
[26]
LI W, WENG Y Z, ZONG R F, et al. Automatic phantom-less calibration of routine CT scans for the evaluation of osteoporosis and hip fracture risk[J/OL]. Bone, 2025, 194: 117431 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/40015421/. DOI: 10.1016/j.bone.2025.117431.
[27]
ADEJUYIGBE B, KALLINI J, CHIOU D, et al. Osteoporosis: molecular pathology, diagnostics, and therapeutics[J/OL]. Int J Mol Sci, 2023, 24(19): 14583 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/37834025/. DOI: 10.3390/ijms241914583.
[28]
SHAH L M, HANRAHAN C J. MRI of spinal bone marrow: part I, techniques and normal age-related appearances[J]. AJR Am J Roentgenol, 2011, 197(6): 1298-1308. DOI: 10.2214/AJR.11.7005.
[29]
EHRESMAN J, PENNINGTON Z, SCHILLING A, et al. Novel MRI-based score for assessment of bone density in operative spine patients[J]. Spine J, 2020, 20(4): 556-562. DOI: 10.1016/j.spinee.2019.10.018.
[30]
EHRESMAN J, SCHILLING A, YANG X H, et al. Vertebral bone quality score predicts fragility fractures independently of bone mineral density[J]. Spine J, 2021, 21(1): 20-27. DOI: 10.1016/j.spinee.2020.05.540.
[31]
GAUSPER A, GIBBS W N, ELDER B D, et al. Magnetic resonance imaging-based assessment of bone quality using vertebral bone quality (VBQ) scores in spine surgery-a critical assessment and narrative review[J/OL]. J Clin Med, 2025, 14(18): 6477 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/41010680/. DOI: 10.3390/jcm14186477.
[32]
HU F K, LI X P, ZHAO D, et al. The diagnostic value of MRI-based vertebral bone quality score for osteoporosis or osteopenia in patients undergoing lumbar surgery: a meta-analysis[J]. Osteoporos Int, 2024, 35(11): 1881-1895. DOI: 10.1007/s00198-024-07190-6.
[33]
CLYNES M A, GREGSON C L, BRUYÈRE O, et al. Osteosarcopenia: where osteoporosis and sarcopenia collide[J]. Rheumatology, 2021, 60(2): 529-537. DOI: 10.1093/rheumatology/keaa755.
[34]
WANG S, ZHANG X, QU B, et al. A novel MRI-based paravertebral muscle quality (PVMQ) score for evaluating muscle quality and bone quality: a comparative study with the VBQ score[J/OL]. Clin Interv Aging, 2024, 19: 1203-1215 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/38974509/. DOI: 10.2147/CIA.S464187.
[35]
BANDIRALI M, DI LEO G, PAPINI G D E, et al. A new diagnostic score to detect osteoporosis in patients undergoing lumbar spine MRI[J]. Eur Radiol, 2015, 25(10): 2951-2959. DOI: 10.1007/s00330-015-3699-y.
[36]
PU M Y, ZHONG W T, HENG H Q, et al. Vertebral bone quality score provides preoperative bone density assessment for patients undergoing lumbar spine surgery: a retrospective study[J/OL]. J Neurosurg Spine, 2023: 1-10 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/36840730/. DOI: 10.3171/2023.1.SPINE221187.
[37]
MIERKE A, RAMOS O, MACNEILLE R, et al. Intra- and inter-observer reliability of the novel vertebral bone quality score[J]. Eur Spine J, 2022, 31(4): 843-850. DOI: 10.1007/s00586-021-07096-5.
[38]
LIU D, KADRI A, HERNANDO D, et al. MRI-based vertebral bone quality score: relationship with age and reproducibility[J]. Osteoporos Int, 2023, 34(12): 2077-2086. DOI: 10.1007/s00198-023-06893-6.
[39]
HU F K, CHEN B, BIAN H M, et al. The diagnostic cutoff value of vertebral bone quality score for osteoporosis is significantly influenced by the magnetic field in patients undergoing lumbar surgery[J]. Quant Imaging Med Surg, 2025, 15(10): 10249-10261. DOI: 10.21037/qims-2025-173.
[40]
ROCH P J, ÇELIK B, JÄCKLE K, et al. Combination of vertebral bone quality scores from different magnetic resonance imaging sequences improves prognostic value for the estimation of osteoporosis[J]. Spine J, 2023, 23(2): 305-311. DOI: 10.1016/j.spinee.2022.10.013.
[41]
BAI W Q, QIAN W J, JIANG X X, et al. Analysis of the diagnostic efficacy of multi-sequence optimized VBQs and QCT for osteoporosis[J]. Chin J Magn Reson Imaging, 2025, 16(8): 106-115. DOI: 10.12015/issn.1674-8034.2025.08.016.
[42]
KADRI A, BINKLEY N, HERNANDO D, et al. Opportunistic use of lumbar magnetic resonance imaging for osteoporosis screening[J]. Osteoporos Int, 2022, 33(4): 861-869. DOI: 10.1007/s00198-021-06129-5.
[43]
HUANG W B, GONG Z Y, ZHENG C J, et al. Preoperative assessment of bone density using MRI-based vertebral bone quality score modified for patients undergoing cervical spine surgery[J]. Global Spine J, 2024, 14(4): 1238-1247. DOI: 10.1177/21925682221138261.
[44]
HUANG W B, GONG Z Y, WANG H L, et al. Use of MRI-based vertebral bone quality score (VBQ) of S1 body in bone mineral density assessment for patients with lumbar degenerative diseases[J]. Eur Spine J, 2023, 32(5): 1553-1560. DOI: 10.1007/s00586-023-07643-2.
[45]
SEKUBOYINA A, HUSSEINI M E, BAYAT A, et al. VerSe: a Vertebrae labelling and segmentation benchmark for multi-detector CT images[J/OL]. Med Image Anal, 2021, 73: 102166 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/34340104/. DOI: 10.1016/j.media.2021.102166.
[46]
WEI L H, QIU Y H, LIN W H, et al. Combination of artificial intelligence and chest computed tomography to assess bone mineral density[J]. Skeletal Radiol, 2026, 55(3): 671-680. DOI: 10.1007/s00256-025-05067-1.
[47]
GUO M, ZHANG Y, GU X X, et al. A comparative study of bone density in elderly people measured with AI and QCT[J/OL]. Front Artif Intell, 2025, 8: 1582960 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/40771941/. DOI: 10.3389/frai.2025.1582960.
[48]
DU C Y, HE J, CHENG Q Y, et al. Automated opportunistic screening for osteoporosis using deep learning-based automatic segmentation and radiomics on proximal femur images from low-dose abdominal CT[J/OL]. BMC Musculoskelet Disord, 2025, 26(1): 378 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/40241032/. DOI: 10.1186/s12891-025-08631-x.
[49]
SEBRO R, DE LA GARZA-RAMOS C. Machine learning for opportunistic screening for osteoporosis from CT scans of the wrist and forearm[J/OL]. Diagnostics, 2022, 12(3): 691 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/35328244/. DOI: 10.3390/diagnostics12030691.
[50]
SEBRO R, ELMAHDY M. Machine learning for opportunistic screening for osteoporosis and osteopenia using knee CT scans[J]. Can Assoc Radiol J, 2023, 74(4): 676-687. DOI: 10.1177/08465371231164743.
[51]
HE L, LIU Z, LIU C Y, et al. Radiomics based on lumbar spine magnetic resonance imaging to detect osteoporosis[J/OL]. Acad Radiol, 2021, 28(6): e165-e171 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/32386949/. DOI: 10.1016/j.acra.2020.03.046.
[52]
HOU R H, TAN W Y, LIU C Y, et al. Clinical-radiomics nomogram construction from magnetic resonance imaging to diagnose osteoporosis: a preliminary study[J]. Eur Spine J, 2025, 34(9): 3843-3852. DOI: 10.1007/s00586-025-08978-8.
[53]
WANG W B, LI D M, LUO F, et al. Enhanced diagnosis of osteoporosis using vision transformer with lumbar MRI[J/OL]. BMC Med Imag, 2025, 25(1): 424 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/41126064/. DOI: 10.1186/s12880-025-01960-2.
[54]
JAYASURIYA N M, FENG E, NATHANI K R, et al. Automated vertebral bone quality score measurement on lumbar MRI using deep learning: Development and validation of an AI algorithm[J/OL]. Clin Neurol Neurosurg, 2025, 257: 109094 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/40780043/. DOI: 10.1016/j.clineuro.2025.109094.
[55]
ZHEN T, FANG J, HU D C, et al. Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis[J/OL]. BMC Musculoskelet Disord, 2024, 25(1): 185 [2025-11-18]. https://pubmed.ncbi.nlm.nih.gov/38424582/. DOI: 10.1186/s12891-024-07309-0.

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