Journal of Clinical Densitometry最新文献

Purpose: People with spinal cord injury (SCI) experience a considerable loss of bone after the injury. Lumbar spine (LS) bone mineral density (BMD) has been reported to be within the normal range, or even higher when assessed with DXA, in people with SCI; hence, it has been hypothesized that sources of error may spuriously increase LS BMD. The aim of this study was to describe the frequency of potential sources of error that may alter LS BMD measurement in a cohort of individuals with chronic SCI at baseline and over a 2-year period. Methods: We analyzed baseline and 2-year follow up DXA scans (Hologic Discovery QDR 4500, Hologic Inc., MA, USA) previously performed from a cohort of males and females with chronic SCI. Two physicians independently reviewed each scan, commented on whether the scan was appropriate for BMD analysis, should be re-analyzed, or be removed from the dataset, and reported on the presence of potential sources of error in LS BMD measurement. Results: We reviewed 115 lumbar spine DXA scans from 58 participants, and 107 (93.0 %) scans from 52 participants presented at least one potential source of error. At baseline, the average number of potential sources of error per scan was 5.5 ± 1.7 and 5.7 ± 1.5 according to rater 1 and rater 2, respectively. Follow-up scans presented an average of 5.6 ± 1.6 and 5.7 ± 1.4 potential sources of error according to rater 1 and rater 2, respectively. Facet sclerosis, osteophytes and difficulty in detecting bone edges were the most prevalent sources of error. Conclusion: The high frequency of potential sources of error is consistent with current recommendations against the use of LS BMD for fracture risk assessment in people with SCI.

Introduction: Only change in bone mineral density (BMD) on repeat DXA that exceeds the 95% least significant change (LSC) should be considered clinically meaningful. Frequently lumbar spine DXA must be reported after omitting vertebrae with localized structural artifact, which reduces measurement precision. Previous reports have raised concerns of higher least significant change (LSC) when spine BMD is based on non-contiguous rather than contiguous vertebrae. The current study was performed to compare lumbar spine LSC and BMD response to intervening anti-osteoporosis medication use from non-contiguous versus contiguous vertebrae.

Methodology: LSCs for lumbar spine DXA based on L1-L4 and all combinations of non-contiguous and contiguous vertebrae were calculated using 879 scan-pairs from the Manitoba BMD Program. We compared BMD change from these regions, overall and in relation to intervening anti-osteoporosis medication use, in 11,722 patients who had 2 DXA examinations.

Results: LSCs were slightly greater when calculated from combinations of fewer than 4 vertebrae, but there was no meaningful difference between contiguous versus non-contiguous vertebrae. There were consistently high correlations between lumbar spine BMD change from L1-L4 and all combinations of continuous and non-contiguous vertebrae (all Pearson r≥ 0.9, p<0.001). Percentage changes in spine BMD and the fraction with treatment-concordant change exceeding the LSC were similar using contiguous or non-contiguous vertebrae.

Conclusions: Lumbar spine BMD change can be assessed from 2 or 3 non-contiguous vertebrae when clinically necessary, and precision in such cases is similar to using contiguous vertebrae. Non-contiguous vertebrae can detect treatment-concordant changes similar in spine BMD to contiguous vertebrae.

Nephritis and osteoporosis are debilitating medical conditions that significantly impact human health and reduce quality of life. To develop potential therapeutic strategies for these disorders necessitates understanding the genetic and molecular mechanisms. Here, we employed bioinformatics techniques purposed to find key genes and associated pathways responsible for nephritis-osteoporosis comorbidity. Six microarray datasets of systemic lupus erythematosus (SLE) and osteoporosis were retrieved from the Gene Expression Omnibus (GEO) database. Post normalization of data sets LIMMA package was utilized for differential expression analysis, among the datasets 44 differentially expressed genes (DEGs) were identified. The identified 44 genes were further analyzed for gene ontology (GO) where it was found that these genes are involved in defense response, organism interactions, and response to external stimuli. In predicting the molecular function, they were involved in several biological processes including binding to lipopolysaccharides and having peptidase and hydrolase activities. Firstly, the identified genes were primarily associated with certain granules such as specific granules and secretory granules in the aspect of cellular components. Enrichment analysis pointed out the potential pathways linked to the immune system, neutrophil degranulation, innate immunity, and immune response to tuberculosis. To examine interactions among DEGs, a complex protein-protein interaction (PPI) network was built, resulting in the identification of seven hub genes, CXCL8, ELANE, LCN2, MMP8, IFIT1, MX1, and ISG15. The study suggests that these elucidated hub genes might have high potential to be exploited as promising biomarkers and therapeutic targets in nephritis-osteoporosis. Taken together, this study provided deeper insights into the genetic and molecular basis for the comorbidity of nephritis and osteoporosis.

Introduction: Although different dual-energy X-ray absorptiometry (DXA) scanners provide different bone mineral density (BMD) values, there is not a gold standard DXA scanner. T-score is used to facilitate the interpretation of BMD, and osteoporosis (OP) is diagnosed based on T-scores. In this retrospective study, we aimed to evaluate the BMD and T-score differences between Lunar Prodigy and Hologic Horizon DXA scanners.

Methodology: Data were collected for patients with previous BMD measurement on Lunar Prodigy and Hologic Horizon DXA scanners within one year in the same medical center.

Results: In a total of 55 patients, BMD values of femoral neck/total, and lumbar vertebrae were all lower at Hologic than Lunar (all p < 0.01). The mean T-score difference at the lumbar spine was 0.74 ± 0.42 (p < 0.001). Of the 49 patients diagnosed as OP (T-score ≤−2.5) with the Hologic, the diagnoses were changed for 25 individuals (51.0 %) with Lunar (p < 0.001). Herewith, although the diagnoses of OP did not change by the repeat technique in other 24 patients (49 %), 13 of them (26.5 %) were categorized as having “high fracture risk” instead of “very high fracture risk” group (i.e., T-score <−3.0). We observed moderate-to-good reliabilities (with an intraclass correlation coefficient [ICC] of 0.633–0.878 and 0.733–0.842 for BMD and T-scores, respectively) between measurements with the Lunar and Hologic scanners. Except for one measurement in L3, L4, L1–4 vertebrae, the Bland–Altman plot did not reveal any consistent bias between the measurements of the Lunar and Hologic scanners.

Conclusions: The consistency between different DXA scanners (especially for Hologic vs. Lunar) is important for proper management, especially in patients with low T-scores and OP.

Introduction: The aim of this study was to evaluate whether degenerative bone changes in the mandibular condyle on cone beam computed tomography images are associated with the Eichner index.

Methodology: 336 cone beam computed tomography images condyle images of 168 patients were analyzed for degenerative bone changes. These changes were named as condyle flattening, osteophytes, erosions, subchondral sclerosis, generalized sclerosis and subchondral cysts. The edentulous status of the patients was classified as group A-B-C and subtypes according to the Eichner index. Categorical variables were evaluated with chi-square test and p < 0.05 was considered statistically significant.

Results: According to the results of the study, the most common degenerative condyle change was flattening of the condyle. Among the Eichner index groups, the most common group was A and the least common group was C. Condyle changes on the right and left sides were most commonly observed in group A patients. The statistically significant majority of patients with right-sided condyle flattening and erosion were in group C. No significant difference was found between all other condyle changes and Eichner index groups. There was no significant relationship between Eichner index and gender.

Conclusion: Degenerative bone changes (flattening and erosion of the condyle) in the condyle region were more common in group C patients with more tooth loss. There is a significant relationship between condyle changes and posterior toothlessness.

Previous studies have yielded inconsistent results regarding the relationship between obesity and bone mineral density (BMD). The aim of this study was to determine the influence of body composition on BMD and the serum sclerostin level in overweight and obese adults. The study had a cross-sectional design and included 90 men and 118 women with a body mass index ≥25. Fat mass, lean mass, and spinal and pelvic BMD were measured using dual-emission X-ray absorptiometry. Subcutaneous fat, visceral fat, and lean mass were measured between L2 and L3 by 16-slice spiral computed tomography. The serum sclerostin level was determined by enzyme-linked immunosorbent assay. Pearson analysis showed that fat mass and appendicular lean mass were positively correlated with spinal BMD in both sexes. A positive association of both fat mass and lean mass with pelvic BMD, which was stronger in women, was also found. Partial correlation analysis showed the positive association between fat mass and BMD was significantly attenuated but the positive association between lean mass and pelvic BMD remained after adjustment for age and body weight. A negative correlation was observed between visceral fat and spinal and pelvic BMD only in women, and the positive association between lean mass with pelvic BMD was more obvious in women than in men, indicating body composition seemed to have a greater impact on the BMD in women. The serum sclerostin level was positively associated with BMD but not with body composition. These findings suggest that the correlation between body composition and BMD is influenced by sex and skeletal site.

Current tobacco smoking is included in FRAX^TM calculator for fracture risk assessment. It is unknown whether previous smoking increases the risk of fracture. The current analysis was performed to compare incident fracture risk associated with current smoking, smoking cessation and non-smoking. The study population comprised 18,115 individuals aged 40 years and older (mean age 68.8 years, 95.1% female) from a large clinical registry of DXA tests for the Province of Manitoba, Canada, with two consecutive visits (mean interval 4.4 years) where current smoking was recorded. Smokers (N=1620) were defined as those reporting current smoking at visit 2 (index date), non-smokers (N=15,942) as answering no to current smoking at both visits, and ex-smokers (N=553) as answering yes to current smoking at visit 1 but no at visit 2. Incident fractures were identified through healthcare data linkage. Compared with non-smokers, risk for any incident fracture (primary outcome) was significantly greater in current smokers (hazard ratio [HR] 1.41, 95% CI 1.19-1.67 adjusted for age/sex; HR 1.22, 95% CI 1.03-1.44 full adjusted) and ex-smokers (HRs 1.56, 95% CI 1.19-2.024 and 1.42, 95% CI 1.09-1.86, respectively). Similar directions and magnitudes of effect were seen for incident major osteoporotic fractures and hip fractures (secondary outcomes), with point estimates for ex-smokers that were close to current smokers. In summary, recent smoking cessation was associated with ongoing increased short-term fracture risk similar to current smoking. Larger studies are needed to better define the time course of fracture risk after smoking cessation.

The primary aim of this study was to explore the effects of team sports practice on bone health indices in adults engaged in team sports. The secondary aim was to investigate the osteogenic effects of each type of team sport. This systematic literature search was conducted using common electronic databases from inception in June 2023, using key terms (and synonyms searched for by the MeSH database) that were combined using the operators “AND”, “OR”, “NOT”: (``men'' OR ``man'' OR ``women'' OR ``woman'') AND (``bone mineral density'' OR ``BMD'' OR ``bone mineral content'' OR ``BMC'' OR ``peak bone mass'' OR ``mechanical loading'' OR ``osteoporosis'' OR ``bone geometry'' OR ``bone resistance'') AND (``team sport'' OR ``sport'' OR rugby OR basketball OR volleyball OR handball OR soccer OR football OR ``players''). After screening, 16 studies were included in the final analysis (5 continents, 2740 participants). The training duration lasted 1 to 13 years. Team sport training had a moderate impact on whole body bone mineral density (WB BMD) (1.07 SMD; 95 % [0.77, 1.37], p < 0.00) but a more significant impact on whole body bone mineral content (WB BMC) (1.3 SMD; 95 % [0.81, 1.79], p < 0.00). Subgroup analyses indicated that rugby training had a moderate but non-significant impact on WB BMD (1.19 SMD; 95 % [−0.13, 2.52], p = 0.08) but a greater impact on WB BMC (2.12 SMD; 95 % [0.84, 3.39], p < 0.00); basketball training had a moderate but significant impact on WB BMD (1 SMD; 95 % [0.35, 1.64], p < 0.00) and a trivial non-significant impact on WB BMC (0.18 SMD; 95 % [−1.09, 1.46], p = 0.78); volleyball training had a moderate but non-significant impact on WB BMD (0.63 SMD; 95 % [−0.22, 1.49], p = 0.15) and a significant impact on WB BMC (2.39 SMD; 95 % [1.45, 3.33], p < 0.00). Handball training produced a moderate significant impact on WB BMD (1.02 SMD; 95 % [0.33, 1.71], p < 0.00) and WB BMC (0.97 SMD; 95 % [0.47, 1.48], p < 0.00), and soccer training led to moderate but significant effects on WB BMD (1.16 SMD; 95 % [0.88, 1.44], p < 0.00) and a large effect on WB BMC (1.34 SMD; 95 % [0.92, 1.77], p < 0.00). Rugby training was associated with a higher WB BMC compared to basketball training (p = 0.03). Our systematic review and meta-analysis suggests that team sports, such as rugby, basketball, volleyball, handball and soccer have moderate to large effects on WB BMD and WB BMC. Specifically, our findings indicate that handball and soccer enhance WB BMD and WB BMC, whereas rugby only increases WB BMC. There is currently insufficient evidence indicating the superiority of any type of sport training that improves bone health in adults.