intervertebral t-score differences in younger and older women

Journal of Clinical Densitometry: Assessment & Management of Musculoskeletal Health, vol. 16, no. 3, 329e335, 2013� Copyright 2013 by The International Society for Clinical Densitometry1094-6950/16:329e335/$36.00
http://dx.doi.org/10.1016/j.jocd.2012.05.004
Original Article

Intervertebral T-Score Differences in Younger and Older Women

Glen M. Blake,*,1 Edward Noon,1 Tim D. Spector,2 and Ignac Fogelman1

1Osteoporosis Research Unit, King’s College London, King’s Health Partners, Guy’s Hospital, London, UK; and2Department of Twin Research and Genetic Epidemiology, King’s College London, King’s Health Partners, St Thomas’

Hospital, London, UK

Abstract

Re*A

ReseaKing’sE-mai

The T-score discordance among skeletal sites is an important aspect of dual-energy X-ray absorptiometry (DXA)measurements. In the spine, large T-score differences between vertebrae are frequently seen in elderly patients owingto degenerative disease. However, it is unclear how often such differences occur in younger adults with healthyspines.

The T-scores for individual lumbar vertebrae were compared for 2391 female singletons (18e79 yr) recruited tothe Twins UK Adult Twin Register. Women were divided into 6 age bands and 5 bands by body weight, respectively,and the T-score differences between the pairs of vertebrae were examined using correlation coefficients and the stan-dard error of the estimate (SEE) from linear regression analysis.

Correlations between the T-scores for adjacent lumbar vertebrae were r5 0.92 decreasing to r5 0.79 between L1and L4. When plotted as a function of age, r-values were constant for the 5 younger age bands, but decreased in theoldest group. In contrast, the T-score SEE values increased progressively with age from 0.4 to 0.5 for the youngergroups to 0.7 for the oldest. Similar trends were seen when women were divided according to body weight. Bothincreasing age and higher body weight were statistically significantly associated with a higher T-score SEE.

The incidence of large T-score differences between vertebrae varies with age and body weight, but is commoneven among younger women. Clinically significant T-score differences can occur in the absence of osteoarthritis,and visual assessment of spine DXA scans for evidence of degenerative disease is advised before vertebrae are omit-ted from scan analyses.

Key Words: Bone mineral density; lumbar spine; T-score discordance; T-scores.

Introduction

The most important attribute of dual-energy X-ray absorp-tiometry (DXA) measurements of bone mineral density(BMD) is their correlation with the risk of patients havingan osteoporotic fracture (1e3). This provides the rationalefor the clinical application of DXA scans for the diagnosis

ceived 03/30/12; Revised 05/11/12; Accepted 05/17/12.ddress correspondence to: Glen M. Blake, PhD, Osteoporosisrch Unit, 1st Floor, Tower Wing, King’s College London,Health Partners, Guy’s Hospital, London SE1 9RT, UK.

l: [email protected]

329

of osteoporosis using T-scores (4) and the prediction of10-yr risk of fracture using FRAX (5,6).

Arguably the second most significant aspect of DXA mea-surements affecting the outcome of patient examinations isthe discordance in findings among different skeletal sites(7,8). For BMD sites well separated anatomically (e.g. lumbarspine, hip, forearm, and calcaneus), the correlation coefficientsbetween T-scores are typically in the range rz 0.5e0.7 (8), re-sulting in significant discordance in clinical interpretationwhen results from different sites are compared (7).

For spine and hip DXA scans, these differences are ratio-nalized by basing the clinical interpretation on the minimumT-score at the spine, femoral neck, and total hip sites (9). ForDXA scans of the lumbar spine, it is usual to delete vertebrae

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330 Blake et al.

affected by artifacts (e.g., spinal degeneration and hyperosto-sis; vertebral fractures; metal, buttons, and other overlying ar-tifacts) (10,11) subject to the requirement that scaninterpretation is based on at least 2 evaluable vertebrae (9).

It is widely understood that clinically significant T-scoredifferences between vertebrae caused by degenerative diseaseare common in elderly patients (12e17), and that their pres-ence can be identified by careful visual inspection of the im-ages included in manufacturers’ scan reports (10), assisted bysoftware that flags vertebrae with divergent T-scores that mayneed to be omitted from the scan analysis (11). However, fewstudies have examined the incidence of these variations inyounger adults with healthy spines in whom T-score differ-ences might still arise either because of the real differencesbetween vertebrae or BMD measurement errors caused byvariations in soft tissue composition (18,19). It is possiblethat too rigid adherence to manufacturers’ computer-assisteddiagnosis might lead to the overinterpretation of T-score dif-ferences between vertebrae in both younger and older pa-tients, and that the unnecessary deletion of vertebrae fromscan analyses may influence the diagnosis of osteoporosis.

In this study, we examined T-score variations in the lumbarspine in women from the Twins UK adult twin registry, a data-base of adult twins recruited from all over the UK (20). By ex-amining data for over 6 decades of age, we are able to quantifythe onset of T-score differences in the lumbar spine with in-creasing age and compare its incidence in younger and olderwomen. We hypothesize that: (1) based on the onset of spinaldegenerative disease in women older than 50 yr, the incidenceof T-score differences increases significantly with age; (2) thateven in younger women with healthy spines, T-score differ-ences may still arise because of soft tissue composition errors(18,19) and/or real differences between vertebrae.

Subjects and Methods

The Twins UK adult twin registry is a volunteer cohort ofadult twins aged 18e85 yr that currently includes approx10,000 monozygotic and dizygotic twins, recruited by mediacampaigns from all over the UK (20). A database of DXABMD measurements and demographic data from the registrywas used in this study. Dizygotic twins have DNA that is ap-proximately 50% identical to each of their siblings (twin ornot), and monozygotic twins have identical DNA. To ruleout any genetic bias, results from just 1 of each pair of twinshaving BMD measurements were included in the present in-vestigation, leaving data for 2391 singleton Caucasian fe-males. Studies have shown that this population is similar tosingleton populations derived from age-sex registers, suchas the Chingford study (21).

BMD Measurements

Fig. 1. Definition of the standard error of the estimate(SEE) calculated from the scatter plot of T-score values for2 lumbar vertebrae. The SEE is the standard deviation ofthe y-axis values about the best-fit regression line.

Fan-beam measurements of lumbar spine BMD were ob-tained using Hologic QDR-2000 and QDR-4500 densitome-ters (Hologic Inc., Bedford, MA). All scans were performedby trained technologists. Regions of interest analyzed werethe total spine (L1eL4) and the respective individual lumbar

Journal of Clinical Densitometry: Assessment & Management of Muscu

vertebrae. Subjects’ age, height, and weight were also re-corded. Daily quality assurance was performed using theHologic spine phantom and results were within the limits rec-ommended by the manufacturer. The QDR-2000 and QDR-4500 densitometers were cross-calibrated using the samespine phantom.

Data Analysis

The women were divided into 6 age bands: 18e24, 25e34,35e44, 45e54, 55e64, and 65þ yr. T-scores were calculatedby the difference between the subject’s and the young-adultmean BMD, expressed in standard deviation units. RawBMD results for L1eL4 and the L1, L2, L3, and L4 vertebraewere captured electronically and the T-scores were calculatedfrom BMD values using the published summary of the man-ufacturer’s US spine reference range (22).

Pearson correlation coefficients between T-scores wereevaluated for all 6 possible combinations of vertebrae (L1vs L2, L1 vs L3, L1 vs L4, L2 vs L3, L2 vs L4, and L3 vsL4) for the entire group and for the women divided into the6 age bands.

The relationships between the T-scores of individual verte-brae were also investigated using linear regression analysis toevaluate the standard error of the estimate (SEE). When T-scores for 1 particular vertebra (e.g., L2) are plotted on they-axis against the T-scores for a second vertebra (e.g., L1)on the x-axis, the SEE gives the standard deviation of the off-sets of the y-axis values from the best-fitting straight line de-termined by linear regression (Fig. 1) (23). In this alternative

loskeletal Health Volume 16, 2013

Fig. 2. Division of the study population into 4 groups ac-cording to whether the subjects’ age and body weight weregreater or less than the median values of 48 yr and 64 kg.The T-score standard error of the estimate results were calcu-lated for each group for each of the 6 possible combinationsof individual vertebrae (L1 vs L2, L1 vs L3, L1 vs L4, L2 vsL3, L2 vs L4, and L3 vs L4) and differences between groupsexamined using the F-test.

Table 2Pearson Correlation Coefficients Between Vertebrae for

All Subjects

Spine L2 L3 L4

L1 0.918 (6) 0.862 (10) 0.786 (15)L2 d 0.920 (6) 0.826 (13)L3 d d 0.893 (8)

Note: Number in brackets is the error (95% confidence interval)in the last figure of the correlation coefficient.

Intervertebral T-Score Differences 331

to correlation analysis, 2 SEE results are obtained for eachpair of vertebrae because the axes can be inverted by plottingL1 T-scores on the y-axis against L2 T-scores on the x-axis.SEE values were calculated for the women divided into thesame 6 age bands, and also into 5 bands by body weight:!50, 50e59, 60e69, 70e79, and 80þ kg.

To investigate the separate effects of age and body weighton the SEE, the women were divided into 4 groups according

Table 1Demographic Data for the Study Population Broken Down

by Age

Age group NSpine BMD(L1eL4)

Weight(kg)

Height(m)

BMI(kg/m2)

18e24 142 0.996 63.1 1.65 23.125e34 321 1.038 64.8 1.64 24.135e44 500 1.046 65.4 1.63 24.545e54 741 1.012 65.9 1.63 25.055e64 534 0.936 66.7 1.61 25.6�65 153 0.906 64.1 1.59 25.4Tot/Av 2391 0.998 65.5 1.63 24.8

Abbr: BMD, bonemineral density; BMI, bodymass index; N, num-ber in group; Tot/Av, total n, average BMD, weight, height, or BMI.


to their median age (48 yr) and median body weight (64 kg;Fig. 2). For each pair of vertebrae, the statistical significanceof the differences between the SEE values for relevant pairsof groups (Group 1 vs Group 2 and Group 3 vs Group 4 toinvestigate the effect of body weight in the younger and olderage groups, respectively; Group 1 vs Group 3 and Group 2 vsGroup 4 to investigate the effect of age in the lighter andheavier groups, respectively) were evaluated using the F-test.

Finally, spineT-score results in individualwomenwere eval-uated in terms of the largest T-score difference between the4 vertebrae and results plotted as histograms for subjects ineach of the 6 age groups. Individual histograms were evaluatedin terms of their 95th centile (i.e., the T-score difference thatcaptured 95% of subjects) and the percentage of women witha largest T-score difference greater or equal to 1.0, 1.5, and 2.0.

Statistical Analysis

Statistical errors in the Pearson correlation coefficientswere evaluated using Fisher’s z-transformation (23). Statisti-cal errors in the SEE values were evaluated using the chi-square distribution (23). The statistical significance of thesquare of the ratio of SEE values between the groups shownin Fig. 2 was assessed using the F-test (23). Statistical signif-icance was based on a p-value of 0.05 or less.

Results

Demographic data for the 6 age groups, including figuresfor total spine (L1eL4) BMD, weight, height, and bodymass index (BMI) are shown in Table 1.

Pearson correlation coefficients between T-scores weregreatest between adjacent vertebrae (L1 vs L2, L2 vs L3,and L3 vs L4), somewhat poorer between vertebrae 2 apart(L1 vs L3 and L2 vs L4), and worst between L1 and L4(Table 2 and Fig. 3). Correlations that included L4 werepoorer than those between the other 3 vertebrae (Table 2).Figure 4 shows the correlation coefficients for 3 of the 6 com-binations of vertebrae plotted as a function of age with errorbars showing their 95% confidence intervals. Plots for theother 3 pairs of vertebrae were omitted to avoid crowdingthe figure, but were similar to those shown in Fig. 4. Correla-tion coefficients were either constant or increased slightlywith increasing age for the 5 younger age bands, butdecreased for the oldest age group.


Fig. 3. Scatter plots of T-scores for individual vertebrae for the whole study population: (A) L2 vs L1, (B) L3 vs L1, and(C) L4 vs L1.

332 Blake et al.

Figure 5A shows plots of the T-score SEE against agegroup for the 3 combinations of adjacent vertebrae, andFig. 5B shows the same plots for the 3 pairs further apart.For adjacent vertebrae, SEE values were approx 0.4e0.5 forthe younger age groups increasing to 0.7 for the oldest group.For vertebrae further apart, SEE values were approx 0.6 forthe younger age groups increasing to 0.9 for the oldest group.Similar results were obtained when the 2 axes were inverted.

Figure 5C and D show plots of T-score SEE for the 5 bodyweight groups. As with the age plots, there was a trend forSEE to increase with increasing body weight, especially forthe 3 pairs of vertebrae that included L4.

Fig. 4. Plots of the Pearson correlation coefficient with thestudy population divided into 6 age bands (18e24, 25e34,35e44, 45e54, 55e64, and 65þ yr). Plots are for the same3 combinations of vertebrae as shown in Fig. 3. Plots forthe other 3 pairs of vertebrae were omitted to avoid crowdingthe figure, but were similar to those shown here. Error barsshow the 95% confidence intervals estimated using Fisher’sz-transformation.


To assess the independent effects of age and body weighton T-score SEE, the SEE values were compared for the 4groups shown in Fig. 2 using the F-test (Table 3). Therewas a strong trend for both age and body weight to influenceSEE values with 10 of 12 F-tests for the effect of body weightand 11 of 12 for the effect of age showing a statistically sig-nificant relationship (Table 3). Similar results were obtainedwhen the 2 axes were inverted.

Figure 6 shows histograms for the largest T-score differ-ence for the 6 age groups. The 95th centile T-score differ-ences were 1.9, 1.7, 1.8, 2.0, 2.1, and 2.8 for the 6 groupswith increasing age. Table 4 lists the percentage of womenin each age group with their largest T-score difference greateror equal to 1.0, 1.5, and 2.0. When the 3 younger age groups(18e44 yr) were pooled, a total of 31 of 963 women (3.2%)had a largest T-score difference of 2.0 or more. For the 3 old-est age groups, the percentages with increasing age were5.0%, 5.4%, and 17.0%, respectively.

Discussion

The correlation coefficients between BMD T-scores for ad-jacent lumbar vertebraewere rz 0.9, decreasing to rz 0.8 forlumbar vertebrae further apart, comparedwith rz 0.5e0.7 be-tweenmore distant sites, such as the lumbar spine, hip, forearm,and calcaneus (8). When the correlation coefficient was exam-ined for subjects in different age decades, the value was con-stant or increased slightly with age for women in the agegroups 18e64 yr, but decreased for women in the oldest groupas would be predicted from the expected increased incidence ofdegenerative disease in the 65þ yr age group and consequentgreater variation in T-scores (12e17).

In contrast to the correlation coefficient, values of theT-score SEEs increased with age in the 5 younger age groupsas well as the oldest group, indicating a trend for T-score vari-ation in the spine to increase with age even in women youngerthan 65 yr. Of the 2 different analyses, correlation and SEE, the


Fig. 5. (A) Plots of the T-score standard error of the estimate (SEE) with the study population divided into the same 6 agebands as shown in Fig. 4. Plots shown are for L2 vs L1, L3 vs L2, and L4 vs L3. Error bars show the 95% confidence intervalsestimated using Chi-square distribution. (B) Same as (A) except for the combinations L3 vs L1, L4 vs L2, and L4 vs L1.(C) Same as (A) expect for the subjects divided into 5 bands by body weight (!50, 50e59, 60e69, 70e79, and 80þ kg).(D) Same as (B) expect for the subjects divided into 5 bands by body weight (!50, 50e59, 60e69, 70e79, and 80þ kg).


latter gives the truer impression of the effect of age on T-scoredifferences because the variation of the correlation coefficientwith age (Fig. 4) reflects not only the changes in the SEE butalso a trend for the standard deviation of T-score values to in-crease with age as subjects lose BMD at different rates, leadingto an increase in the spread of data points along the regressionline (Fig. 1) that counteracts the effect of an increased SEE onthe value of the correlation coefficient.

To assess the independent effects of age and body weighton SEE, the study population was divided into 4 groups ac-cording to the median values of age and body weight(Fig. 2), and the F-test was used to evaluate the statistical sig-nificance of the square of the SEE ratios between the differentgroups for each of the 6 combinations of lumbar vertebrae

Tablep-Values for Comparison of T-Score SEE Values Bet

Groups Variable L1/L2 L2/L3

1 vs 2 Body weight !0.0001 0.0173 vs 4 0.003 0.00051 vs 3 Age !0.0001 0.00042 vs 4 !0.0001 !0.0001

Note: For definition of groups, see Fig. 2.Abbr: SEE, standard error of the estimate.


(Table 3). Although the trend for the T-score SEE to increasewith age was expected because of the onset of degenerativedisease (12e17), there was an equally strong trend for theSEE to increase with body weight (Fig. 5). The findingswere similar when the SEE data were analyzed in terms ofthe BMI instead of the body weight. In these analyses,body weight and BMI are surrogates for the total tissue thick-ness through the lumbar spine region of interest because these3 variables are highly correlated with each other with correla-tion coefficients rz 0.9 (24).

An unexpected finding of this study was the frequent inci-dence of clinically significant T-score differences in the lumbarspine in younger as well as older women (Fig. 6). Precision er-rors in the BMD measurements are 1 possible source of these

3ween Subject Groups Evaluated Using the F-Test

L3/L4 L1/L3 L2/L4 L1/L4

!0.0001 0.011 !0.0001 !0.00010.098 0.015 0.090 0.012

!0.0001 !0.0001 !0.0001 !0.00010.44 !0.0001 0.027 0.005


Fig. 6. Histograms for the largest T-score difference for subjects divided into 6 age bands (18e24, 25e34, 35e44, 45e54,55e64, and 65þ yr). Arrows mark the 95% centile for each histogram.

334 Blake et al.

differences, especially because errors for individual vertebraeare around twice than those for L1eL4 combined (25). Theselarger precision errors lead to T-score SEEs of 0.14e0.20 inscatter plots for individual vertebrae (25) and hence cannot ex-plain even the smallest SEE values of 0.4e0.6 found for theyounger, lighter women in Group 1. BMD measurements inthe lumbar spine are subject to significant measurement errorscaused by the inhomogeneous distribution of fat and lean tissuein the scan field (18,19), and the most plausible explanation ofthe effect of weight on SEE values is an increase in the soft tis-sue accuracy errors with increasing body thickness at the lum-bar spine in heavier subjects, coupled with vertebra-to-vertebradifferences in these errors (18).

To assist the interpretation of spine BMD scans, manufac-turers provide algorithms for computer-assisted diagnosisbased on differences in T-scores between individual lumbarvertebrae to flag scans that may require manual deletion of af-fected vertebrae (11). An important question is whether clini-cians reporting DXA scans choose to modify scan analyses

Table 4Percentage of Women in Different Age Groups With theLargest T-Score Difference in the Lumbar Spine Greater or

Equal to 1.0, 1.5, and 2.0

Largest T-scoredifference

Age group (yr)

18e24 25e34 35e44 45e54 55e64 65þ�1.0 (%) 38.0 36.4 34.2 43.5 44.9 58.2�1.5 (%) 11.3 11.2 13.4 16.1 17.6 28.8�2.0 (%) 4.2 2.8 3.2 5.0 5.4 17.0


purely on the basis of T-score differences between vertebraeflagged by the automated software, or whether there is an ad-ditional requirement that vertebrae with discrepant T-scoresshould show visual evidence of degenerative disease or otherartifacts on scan images. In the present study, the incidence oflargest T-score differences �1.0, �1.5, and �2.0 was onlyslightly higher in women in the age ranges 45e54 and55e64 yr than in women aged 18e44 yr, suggesting thatmuch of the effect in these younger age groups is owing tothe factors other than degenerative disease. Consequently,some caution is required before vertebrae are omitted fromscan analyses based on large T-score differences alone.

This study has a number of limitations. Owing to the re-placement of the DXA scanners, it was not possible to recoverspine scans from archive to visually review images and scorethem for the presence of degenerative disease. Although thepresent study strongly suggests that BMD measurement errorsarising from the distribution of fat and lean tissue in the abdo-men contribute to T-score variations in the spine, it cannot tellus how much of the SEE in younger subjects may be owing toreal vertebra to vertebra differences.

In conclusion, T-score differences in lumbar spine DXAscans are common even in younger women, and their inci-dence increases with both age and body weight. Althoughthe former is explained by the onset of degenerative disease,the latter is likely to be caused by measurement errors relatedto soft tissue composition. Clinicians should be aware thatsignificant T-score variation in the spine can occur even inthe absence of osteoarthritis, and that the visual assessmentof spine DXA scans for the presence of degenerative diseaseor other artifacts is advised before omitting vertebrae flaggedby the manufacturers’ software.



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intervertebral t-score differences in younger and older women

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