ReviewIndian journal of orthopaedics2023
DEXA and Imaging in Osteoporosis.
Review in Indian journal of orthopaedics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 35 citations in OpenAlex.
- Radiographic Classification of Low-Energy Distal Radius Fracture Status Using Automated Hand Segmentation.Journal of imaging informatics in medicine · 2026Article
- Radiographic features of bone ingrowth in highly porous cementless total knee arthroplasty with minimum 2-year follow-up.Arthroplasty (London, England) · 2026Article
- Assessing Osteoporosis Risk on Panoramic Radiography through Fractal Dimension Analysis of Mandibular Condyles in Postmenopausal Women.European journal of dentistry · 2026Article
- Cervical Disc Replacement Does Not Increase Revision or Reoperation Risk Compared With Fusion in Osteoporotic Women: A Retrospective Matched Cohort Study.Global spine journal · 2026Article
- C- VBQ versus CT Hounsfield units in predicting cage subsidence following ACDF: a retrospective cohort analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- The Use of Statistical Shape and Appearance Modelling for Predicting Osteoporotic Fracture Risk.Current osteoporosis reports · 2026Review
- Photon-counting detector CT virtual monoenergetic imaging for bone mineral density quantification: Validation with Micro-CT.iScience · 2026Article
- Musculoskeletal Assessment in Patients with Adrenal Incidentalomas: Should We Integrate the Trabecular Bone Score and/or Circulating Irisin?Diagnostics (Basel, Switzerland) · 2026Article
- MRI-Based Vertebral Bone Quality Scoring for Opportunistic Osteoporosis Screening in Postmenopausal Women: A QCT-Referenced Study.Calcified tissue international · 2026Article
- Mandibular CT-Based radiomorphometric and density indices for opportunistic osteoporosis screening.BMC oral health · 2026Article
- Protective effects and mechanism of chrysophanol against age-related osteoporosis in rats.Iranian journal of basic medical sciences · 2026Article
- MicroRNAs in osteoporosis: current evidence and clinical perspectives.Reumatologia · 2026Review
- Prophylactic fixation in elderly fractures: Preventive breakthrough or unnecessary intervention?World journal of orthopedics · 2025Review
- Review
- Multidisciplinary consensus on the management of patients with osteopenia and fracture risk in Spain.BMC musculoskeletal disorders · 2025Article
- Post-stroke Bone Fragility: Early Bone Loss, Risk Factors, and Recovery Considerations.Cureus · 2025Review
- Bone Mineral Density (BMD) Assessment Using Dual-Energy CT with Different Base Material Pairs (BMPs).Journal of imaging · 2025Article
- AI-Powered Identification of Osteoporosis in Dental Panoramic Radiographs: Addressing Methodological Flaws in Current Research.Diagnostics (Basel, Switzerland) · 2024Article
- The influence of proliferative tissue on Hounsfield unit and its correlation with BMD in middle-aged and elderly patients with lumbar degenerative diseases.Journal of orthopaedic surgery and research · 2024Article
- Enhanced Osteoporosis Detection Using Artificial Intelligence: A Deep Learning Approach to Panoramic Radiographs with an Emphasis on the Mental Foramen.Medical sciences (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Reduced bone density and increased fragility are hallmarks of osteoporosis, making the disease a major public health concern. The disease necessitates early diagnosis and appropriate therapy depend on an accurate evaluation of bone health. Essential tools for assessing osteoporosis include dual-energy X-ray absorptiometry (DEXA) and other imaging modalities. Methods: This chapter focuses on dual-energy X-ray absorptiometry (DEXA) and other imaging methods as essential tools for assessment of osteoporosis. The chapter also explores complementary imaging modalities that help overcome limitation of DEXA by providing insights into the microarchitecture and bone quality. Results: T-scores, used to categorise bone health, are determined by DEXA by comparing bone mineral density to age-matched standards. Bone mineral density (BMD) is the most common indicator of bone health; nevertheless, DEXA may misclassify bone health owing to reasons other than BMD. These constraints may be overcome with the use of complementary imaging methods, which provide information on the microarchitecture and quality of bone. The evaluation of bone structure is aided by high-resolution peripheral quantitative computed tomography (HR-pQCT), which produces precise 3D images of the trabecular and cortical bone compartments. Independent of traditional methods of gauging fracture risk, quantitative ultrasonography (QUS) uses an analysis of the characteristics of sound waves to determine bone health. Diagnostic precision is improved by magnetic resonance imaging (MRI) due to its ability to view bone marrow and trabecular structure without the use of ionising radiation. Discussion: New methods, such as the trabecular bone score (TBS), examine bone texture and provide more data on the likelihood of fracture than conventional DEXA. By modelling bone strength using imaging data, finite element analysis (FEA) provides a biomechanical viewpoint on breakage probability. These combined methods boost diagnostic accuracy and pave the way for individualised treatment plans. Imaging helps with therapy monitoring as well as diagnosis. By monitoring bone density and structure over time, therapy effectiveness or course corrections may be quickly identified. The availability of sophisticated imaging techniques and the standardisation of procedures provide obstacles not withstanding their advantages. Ongoing work is being done to solve these issues and standardise and disseminate these methods in a variety of contexts. Conclusion: The evaluation of osteoporosis is significantly aided by DEXA and other imaging methods. While DEXA is still the gold standard for diagnosing osteoporosis, other imaging techniques may shed light on bone health in greater detail. These methods improve fracture risk prediction and treatment assessment by providing information on bone architecture, quality, and strength. Integration of several imaging modalities shows potential for bettering osteoporosis therapy and patient outcomes as the field develops.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.