Comparisons of Noninvasive Bone Mineral Measurementsin Assessing Age-Related Loss, Fracture Discrimination,

and Diagnostic Classification*STEPHAN GRAMPP, HARRY K. GENANT, ASHWINI MATHUR, PHILIPP LANG, MICHAEL JERGAS,

MASAHIKO TAKADA, CLAUS-C. GLUER, YING LU, and MONICA CHAVEZ

ABSTRACTThe purpose of this study was to examine the commonly available methods of noninvasively assessing bonemineralstatus across three defined female populations to examine their interrelationships, compare their respectiveabilities to reflect age- and menopause-related bone loss, discriminate osteoporotic fractures, and classify patientsdiagnostically. A total of 47 healthy premenopausal (age 33 6 7 years), 41 healthy postmenopausal (age 64 6 9years), and 36 osteoporotic postmenopausal (age 70 6 6 years) women were examined with the followingtechniques: (1) quantitative computed tomography of the L1–L4 lumbar spine for trabecular (QCT TRAB BMD)and integral (QCT INTG BMD) bone mineral density (BMD); (2) dual X-ray absorptiometry of the L1–L4posterior-anterior (DXA PA BMD) and L2–L4 lateral (DXA LAT BMD) lumbar spine, of the femoral neck (DXANECK BMD) and trochanter (DXA TROC BMD), and of the ultradistal radius (DXA UD BMD) for integralBMD; (3) peripheral QCT of the distal radius for trabecular BMD (pQCT TRAB BMD) and cortical bone mineralcontent (BMC) (pQCT CORT BMC); (4) two radiographic absorptiometric techniques of the metacarpal (RAMETC BMD) and phalanges (RA PHAL BMD) for integral BMD; and (5) two quantitative ultrasound devices(QUS) of the calcaneus for speed of sound (SOS CALC) and broadband ultrasound attenuation (BUA CALC). Ingeneral, correlations ranged from (r 5 0.10–0.93) among different sites and techniques. We found that pQCTTRAB BMD correlated poorly (r 0.46) with all other measurements except DXAUDBMD (r5 0.62, p 0.0001)and RA PHAL BMD (r 5 0.52, p 0.0001). The strongest correlation across techniques was between QCT INTBMD and DXA LAT BMD (r 5 0.87, p 0.0001), and the weakest correlation within a technique was betweenpQCT TRAB BMD and pQCT CORT BMC (r5 0.25, p 0.05). Techniques showing the highest correlations withage in the healthy groups also showed the greatest differences among groups. They also showed the bestdiscrimination (as measured by the odds ratios) for the distinction between healthy postmenopausal and osteo-porotic postmenopausal groups based on age-adjusted logistic regression analysis. For each anatomic site, thetechniques providing the best results were: (1) spine, QCT TRAB BMD (annual loss, 21.2% [healthy premeno-pausal and healthy postmenopausal]); Student’s t-value [not the T score], 5.4 [healthy postmenopausal vs.osteoporotic postmenopausal]; odds ratio, 4.3 [age-adjusted logistic regression for healthy postmenopausal vs.osteoporotic postmenopausal]); (2) hip, DXA TROCBMD (20.46; 3.5; 2.2); (3) radius, DXAUDBMD (20.44; 3.3;1.9) and pQCT, CORT BMC (20.72; 2.9; 1.7); (4) hand, RA PHAL (20.51; 3.6; 2.0); and (5) calcaneus, SOS(20.09; 3.4; 2.1) and BUA (20.52; 2.6; 1.7). Despite these performance trends, the differences among sites andtechniques were statistically insignificant ( p > 0.05) using age-adjusted receiver operating characteristic (ROC)curve analysis. Nevertheless, kappa score analysis (using 22.0 T score as the cut-off value for osteopenia and 22.5 Tscore for osteoporosis) showed that in general the diagnostic agreement among these measurements in classifyingwomen as osteopenic or osteoporotic was poor, with kappa scores averaging about 0.4 (exceptions were QCT TRAB/INTG BMD, DXA LAT BMD, and RA PHAL BMD, with kappa scores ranging from 0.63 to 0.89). Often differentpatients were estimated at risk by using differentmeasurement sites or techniques. (J BoneMinerRes 1997;12:697–711)

Musculoskeletal Section and Osteoporosis Research Group, Department of Radiology, University of California, San Francisco,California, U.S.A.

*Presented in part by H.K.G. at the XIth International Work-shop on Bone Densitometry, Gleneden Beach, Oregon, U.S.A.,September 24–28, 1995.(28)

JOURNAL OF BONE AND MINERAL RESEARCHVolume 12, Number 5, 1997Blackwell Science, Inc.q 1997 American Society for Bone and Mineral Research

697

INTRODUCTION

OSTEOPOROSIS is the most common generalized disease ofthe skeleton, causing reduction of bone mass and

changes in bone structure. The loss of integrity of thetrabecular network and the cortical shell result in a reduc-tion in bone strength and in fragility fractures. Currentmethods for evaluating skeletal status, assessing osteoporo-sis, and determining fracture risk rely mostly on the nonin-vasive measurement of bone mineral content (BMC) andbone mineral density (BMD).(1–5) Of these methods, themost common is dual X-ray absorptiometry (DXA), typi-cally used at the posterior-anterior and lateral lumbarspine, proximal femur, and forearm. Quantitative computedtomography (QCT) overcomes the projectional limitationsof DXA and allows a selective measurement of trabecularbone in the spine. The validity of QCT of the lumbar spine isgenerally accepted and the method is regarded as a sensi-tive tool for noninvasive measurement of the BMD.(6–11)

Recently, peripheral QCT (pQCT) instruments have be-come available leading to renewed interest in measurementsof the radius.(11–16) Similarly, new techniques to measureBMD of the phalanges(17–19) and metacarpals(20–23) usingradiographic absorptiometry (RA) have shown promisingresults. The only established techniques for noninvasiveassessment of bone status that do not require radiation areultrasound-based techniques measuring ultrasound velocity(speed of sound, SOS) and broadband ultrasound attenua-tion (BUA) at the calcaneus and other sites.(24–27)

The purpose of this study(28) was to examine the above-mentioned methods of noninvasively assessing bone min-eral status across three defined female populations (healthypremenopausal, healthy postmenopausal, and osteoporoticpostmenopausal women) to examine their interrelation-ships, compare their respective abilities to reflect age- andmenopause-related bone loss, discriminate women with os-teoporotic vertebral fractures, and classify women diagnos-tically as osteopenic or osteoporotic.

MATERIALS AND METHODS

We studied 47 healthy premenopausal (PRE, age 33 6 7years), 41 healthy postmenopausal (POST, age 64 6 9years), and 36 osteoporotic postmenopausal (OSTEO, age70 6 6 years) women. Exclusion criteria were history ofgeneralized disease of bone, malignant disease, or traumaat the measurement sites, or any drug treatment that couldinfluence bone metabolism. The diagnosis of osteoporosiswas defined as the presence of at least one atraumaticvertebral fracture. A fracture was determined by a semi-quantitative assessment of morphologic changes of the tho-racic and lumbar spine on lateral conventional radio-graphs.(29) This assessment was based on the qualitativeappearance of each vertebra, with a fracture defined byaltered morphology and a decrease in vertebral height ofapproximately 20% or more at the anterior, middle, orposterior aspect of the vertebral body.Nearly all of these women (Table 1) were examined with

each of the following techniques. (1) QCT with a GE 9800

computerized tomography (CT) scanner (General Electric,Milwaukee, WI, U.S.A.). The standard protocol for spinalbone mineral analysis(6,30,31) was used. It uses a 10 mmthick axial slice in the midsection of four vertebral bodiesfrom L1 to L4. Measurements were performed with a singleenergy technique at 80 kVp. Calibration of the CT imagewas achieved by a simultaneous scanning of a calibrationphantom (Image Analysis, Columbia, KY, U.S.A.) contain-ing various inserts of hydroxyapatite-equivalent material.The images were evaluated on an off-line image processingworkstation with an automated quantitative image evalua-tion technique.(30) Two different regions of interest (ROIs)in each vertebra were evaluated for BMD.(30) These werethe elliptical ROIs, (trabecular bone of the vertebral body)and the integral ROIs (a portion of the trabecular andcortical bone of the entire vertebra representing a cross-section through the midvertebra and portions of the poste-rior elements but no transverse processes or vertebral end-plates). BMDwas determined for each ROI (trabecular [QCTTRABBMD] and integral [QCT INTGBMD]) and expressedin hydroxyapatite-equivalent units (mg/cm3).(6,30–33)

(2) DXA with a Hologic QDR-2000 scanner (HologicInc., Waltham, MA, U.S.A.) using pencil beam, 140/70 kVp,2.0 mA and the manufacturer’s recommended standardanalysis procedures for the posterior-anterior lumbar spineat L1–L4 (DXA PA BMD), the lateral lumbar spine atL2–L4 (DXA LAT BMD), the proximal femur at the fem-oral neck (DXA NECK BMD), trochanter (DXA TROCBMD), intertrochanteric region (DXA INTER BMD), andWard’s triangle (DXAWARD BMD), and the distal radiusat the ultradistal (DXA UD BMD), 1/3 (DXA 1/3 BMD),total (DXA TOT BMD), and midradius (DXA MIDBMD). The software allowed anatomic separation of thedifferent ROIs. Spine scans were performed with the pa-tient in the supine position. Lateral scans were performedfollowing a PA scan in which the vertebral levels wereidentified with the subject in supine position. Hip scanswere performed with the subject in supine position. Distalradius scans were performed with the subject’s arm placedpalm down on the scanning table, scanning distal to theradial styloid and covering the ultradistal, the distal thirdradius, and the ulna. The projectional BMD results for allROIs were given in grams per square centimeter.(3) Peripheral QCT measurements of the nondominant

radius were obtained with a Stratec XCT-960 scanner(Stratec GmbH, Pforzheim, Germany), using a single en-ergy technique (47 kVp, 0.3 mA). One axial slice (2.5 mmthickness) was obtained at a region defined to be at 4% ofthe ulnar length proximal to the most proximal site of theradial articular surface. The axial slice was automaticallyevaluated to define trabecular, cortical, and total ROIs. Tocalculate the total ROI, the software used a thresholdingalgorithm to define the outer boundary of the bone. Thetrabecular ROI was generated by reducing the area of thetotal ROI by 55%. This was done by trimming pixels fromthe periphery to define a core area, which consists exclu-sively of trabecular bone. The cortical was defined througha second thresholding algorithm identifying bone with highdensity in the outer rim. Constant threshold levels wereused for all subjects (0.5 mg/cm3 for total bone; 0.7 mg/cm3

698 GRAMPP ET AL.

for cortical bone). Based on this approach, pQCT TOTBMD, pQCT TRAB BMD, pQCT CORT BMD and so onwere calculated. From area, slice thickness, and BMD (mg/cm3), the BMC (g) (for example pQCT CORT BMC) ofeach region was calculated.(4) Two computerized RA techniques were performed

on conventional radiographs of the nondominant hand.Two manufacturer-specific aluminum wedges were used asreference phantoms: for the second metacarpal (ChugaiPharmaceutical Co. Ltd, Tokyo, Japan) and for the middlephalanges (Computed Osteosystems, Yellow Springs, OH,U.S.A.). Lateral radiographs were taken for each subject bydirect exposure. The hands were radiographed twice witheach phantom in accordance with the procedures providedby the manufacturers (50 kVp, 400 mA, 0.8 s, and 60 kVp,300 mA, 0.5 s; the mean of the double measurement wasused in the data analysis). The focus-to-film distance was105 cm. An aluminum alloy reference wedge was placedparallel to the middle phalanx of the index finger (phalanxmeasurement) or parallel to the main axis of the entirehand (metacarpal measurement). Developed films weresent to both manufacturers for analysis. In order to do this,each film was digitized by a high resolution video camera.For the phalanx measurements, ROIs were defined encom-passing the wedge and the middle phalanges; ROIs for themetacarpal measurements were encompassing the wedgeand a 6- to 8-mm-long portion (10% of the length) of thesecond metacarpal. Through a curve fitting process appliedto the wedge image data, a set of parameters was calculateddefining the relationship between absorber density and op-tical density for each individual film. These parameterswere applied to the bone image data to compute bonemineral mass. The integral BMDs (RA CH METC BMDand RA CO PHAL BMD) for the respective bones weredetermined with both techniques and given as aluminum-equivalent units in grams per square centimeter.(5) Two quantitative ultrasound devices made by Walker

Sonix (WS, Hologic Inc.) and the Lunar Achilles (LA,Lunar Corp., Madison, WI, U.S.A.) were used for measure-ments of the calcaneus of the nondominant side. Bothsystems used an emitting and receiving transducer eitherside of the heel, with water (heated to 358C) as the couplingagent. The systems used a transmitting transducer with acentral frequency of 0.5 MHz, which was electronicallyexited to produce a broadband spectra. Ultrasonic waveswith a predominant bipolar appearance were transmittedthrough the heel, detected by receiving transducers, anddigitized for analysis. SOS (m/s) and BUA (dB/MHz) weredetermined (SOS WS CALC, BUA WS CALC, SOS LACALC, and BUS LA CALC) with both machines accordingto the manufacturers’ recommended standard procedures.The means and standard deviations of the measurements

for the three subject groups were calculated. The Student’st-test (t values and p values) and percent decrement wereused for comparing the different measurements for reflect-ing intergroup differences. Annual changes were expressedas percent changes relative to the predicted values at age 30and as fractional standard deviations relative to the stan-dard deviation (SD) of PRE. Correlations with age alongwith p values are also reported. Odds ratios (for 1 SD

decrease in the measured parameter) and 95% confidencelimits based on the age-adjusted logistic regression werecalculated to measure the discriminative ability (for dis-criminating between OSTEO and POST group) and the riskof osteoporotic fracture associated with the measured pa-rameter. The pairwise comparisons of the discriminativeabilities were tested using age-adjusted receiver operatingcharacteristic (ROC) curve analysis.Pairwise comparisons of all techniques were obtained by

pooling all subjects (PRE, POST, OSTEO) and using Pear-son’s correlation coefficients (r), percent standard errors ofthe estimate (CV), and p values for testing significance ofthe correlations.To compare techniques for their diagnostic ability, a

kappa score analysis was done on the postmenopausalwomen (POST and OSTEO) and osteoporotic postmeno-pausal women (OSTEO). This was done by classifying everywomen from the postmenopausal groups as osteopenic ifher T score with respect to the reference group (PRE) wasless than 22.0. Similarly every subject from the osteopo-rotic group was classified as osteoporotic if her T scorecompared with the reference group (PRE) was less than22.5. The T score for an individual woman and a particularmeasurement is defined as the measurement minus themean measurement for the young normals (PRE) dividedby the SD of the measurement in the PRE group. Note thatthe T score is measuring the position of an individualwoman with respect to the PRE group and is different fromthe Student’s t value.

RESULTS

Results showed that all parameters (except pQCT TRABBMD) between the PRE and POST groups had statisticallysignificant differences ( p # 0.05) (Table 1). Except forpQCT TRAB BMD, pQCT CORT BMD, pQCT TRABBMC, SOS WS CALC, and BUA LA CALC, other mea-surements showed statistically significant differences be-tween POST and OSTEO groups ( p # 0.05; Table 1). TheStudent’s t values and percent decrements demonstrate thedifferent levels of significance (Table 1 and Fig. 1).Linear regressions showed that in healthy women (PRE

AND POST) the only parameter not significantly corre-lated with age was pQCT TRAB BMD. All other parame-ters were significantly correlated with age ( p # 0.05;Table 1 and Fig. 2). The highest correlation with age wasfound at the spine with r 5 20.78 for QCT TRAB BMDand QCT INTG BMD and r 5 20.72 for DXA LAT BMD.The highest annual bone loss was measured by QCT TRABBMD (1.18%), DXA WARD BMD (1.0%), and QCTINTG BMD (0.80%). The smallest annual changes wereregistered for both measurements of the ultrasound param-eter SOS (SOS WS CALC 5 20.02; SOS LA CALC 520.09). However, when expressed in terms of SD ratherthan percentages (relative to PRE) the annual changes forultrasound SOS were comparable to most other techniques.Age-adjusted odds ratios for discriminating the OSTEO

from POST group were significant for QCT TRAB BMD(4.3, 95% confidence limits 1.8, 10.0) and QCT INTG BMD

NONINVASIVE BONE MINERAL MEASUREMENTS 699

TABLE 1. COMPARISON OF MEANS, AGE-RELATED LOSSES, AND FRACTURE ASSOCIATIONS BY TECHNIQUE

Methodparameter (n)

Mean SD% decr.t valuep valuePRE vs.POST

% decr.t valuep valuePOSTvs.

OSTEO

Annual loss(%)/SDPRE 1POST

Cor (2) w.age p valuePRE 1POST

Odds ratioLCL/UCLPOST vs.OSTEO

ROCAREA SEPOST vs.OSTEOPRE POST OSTEO

QCT TRAB 178 106 72 40.7 31.5 1.18 0.78 4.3 0.82BMD mg/cm3 33 30 22 10.7 5.4 0.064 0.0001 1.8/10.1 0.05(123) 0.0001 0.000QCT INTG 289 208 176 27.8 15.5 0.80 0.78 3.0 0.80BMD mg/cm3 36 31 29 11.2 4.7 0.064 0.0001 1.5/6.1 0.05(123) 0.0001 0.000DXA PA BMD 1.02 0.90 0.79 11.7 12.0 0.30 0.41 2.4 0.78g/cm2 (124) 0.12 0.12 0.15 4.6 3.6 0.026 0.0001 1.4/4.2 0.05

0.0001 0.001DXA LAT BMD 0.82 0.65 0.58 20.8 11.4 0.58 0.72 2.6 0.79g/cm2 (123) 0.08 0.08 0.07 9.7 4.2 0.058 0.0001 1.4/5.0 0.05

0.0001 0.000DXA FEM 0.82 0.67 0.62 18.0 7.7 0.53 0.56 1.5 0.71NECK BMD 0.12 0.12 0.10 5.8 2.0 0.036 0.0001 0.9/2.5 0.06g/cm2 (124) 0.0001 0.045DXA FEM 0.69 0.58 0.52 15.8 11.5 0.46 0.54 2.2 0.77TROC BMD 0.10 0.08 0.09 5.7 3.5 0.033 0.0001 1.3/3.8 0.05g/cm2 (124) 0.0001 0.001DXA FEM 1.09 0.90 0.84 17.4 6.7 0.47 0.55 1.5 0.71INTER BMD 0.14 0.13 0.15 6.4 2.1 0.030 0.0001 0.9/2.5 0.06g/cm2 (124) 0.0001 0.040DXA FEM 0.76 0.50 0.43 34.2 14.0 1.00 0.70 1.6 0.72WARD BMD 0.15 0.14 0.11 8.1 2.5 0.040 0.0001 0.9/2.9 0.06g/cm2 (124) 0.0001 0.020DXA FEM 0.94 0.77 0.71 18.1 7.8 0.48 0.57 1.6 0.73TOT BMD 0.12 0.11 0.12 6.5 2.4 0.030 0.0001 0.9/2.7 0.06g/cm2 (124) 0.0001 0.020DXA RAD 0.44 0.38 0.34 14.0 10.4 0.44 0.62 1.9 0.74UD BMD 0.05 0.04 0.06 6.1 3.3 0.039 0.0001 1.0/3.5 0.06g/cm2 (122) 0.0001 0.002DXA RAD 0.68 0.60 0.56 11.8 6.7 0.38 0.64 1.6 0.721/3 BMD 0.05 0.07 0.07 6.3 2.9 0.052 0.0000 0.9/2.7 0.06g/cm2 (122) 0.0000 0.006DXA RAD 0.59 0.53 0.48 10.2 9.4 0.35 0.63 2.1 0.73MID BMD 0.05 0.06 0.07 5.8 3.2 0.042 0.0000 1.0/4.6 0.06g/cm2 (122) 0.0000 0.002DXA RAD 0.57 0.50 0.46 12.3 8.0 0.46 0.66 2.2 0.74TOT BMD 0.04 0.05 0.06 6.5 3.3 0.053 0.0000 1.1/4.4 0.06g/cm2 (122) 0.0000 0.001pQCT RAD 192 175 161 9.0 8.1 0.22 0.18 1.4 0.70TRAB BMD 30 53 41 1.8 1.2 0.014 0.1000 0.9/2.4 0.06mg/cm3 (106) 0.0829 0.230pQCT RAD 692 650 618 6.1 4.9 0.19 0.31 1.3 0.71CORT BMD 70 85 69 2.3 1.7 0.019 0.0070 0.7/2.3 0.06mg/cm3 (106) 0.0200 0.090pQCT RAD 361 323 290 10.5 10.2 0.31 0.35 1.5 0.73TOT BMD 49 62 53 2.9 2.4 0.023 0.0020 0.9/2.8 0.06mg/cm3 (106) 0.0050 0.020pQCT RAD 68 59 55 13.2 6.8 0.38 0.30 1.2 0.69TRAB BMC 13 17 16 2.8 1.0 0.019 0.0070 0.7/2.1 0.06mg (106) 0.0070 0.300

700 GRAMPP ET AL.

(3.0, 1.5, 6.1), for DXA PA BMD (2.4, 1.4, 4.2), DXA LATBMD (2.6, 1.4, 5.0), DXA TROC BMD (2.2, 1.3, 3.8), DXAUD BMD (1.9, 1.0, 3.5), DXA MID BMD (2.1, 1.0, 4.6),DXA RAD TOT BMD (2.2, 1.1, 4.4), for RA CO PHALBMD (2.0, 1.1, 3.6), and for BUA WS CALC (1.7, 1.0, 3.0)and SOS LA CALC (2.1, 1.2, 3.9) (Table 1 and Fig. 3). Thearea under the age adjusted ROC curves for the differentmeasurements were not significantly different from eachother ( p . 0.05).For further comparisons between and among techniques,

we selected from each technique those parameters that aremost widely used. We also included the parameters thatshowed the best performance if they were not the mostcommonly used parameters. (See Tables 2 and 3).Correlations, percentage standard error of estimate

(CV), and p values based on all women and on linearregressions for the selected parameters are given in Table 2.Correlations ranged from 0.11 to 0.94 among different sitesand techniques. We found that pQCT TRAB BMD corre-lated poorly, with correlations less than 0.46 with othermeasurements (except DXA UD BMD, r 5 0.62, p #0.0001 and RA CO PHAL BMD, r 5 0.52, p # 0.0001).Comparing all techniques, the strongest correlation acrosstechniques was between QCT INTG BMD and DXA LATBMD (r 5 0.87, p # 0.0001) and the weakest within a

technique was between pQCT TRAB BMD and pQCTCORT BMC (r5 0.25, p# 0.01). The mean correlation andthe associated SD for each technique was calculated(Fig. 4). On the average, the QCT techniques correlatedbest while the pQCT and QUS techniques showed weakercorrelations.By kappa analysis the diagnostic agreement among the

different measurements was generally poor in classifyingpostmenopausal women (POST and OSTEO) as osteopenic(T score , 2.0) or in classifying women with vertebralfractures (OSTEO) as osteoporotic (T score , 2.5) (Table 3and Figs. 5 and 6). Exceptions were the kappa analysiscomparisons among QCT TRAB, QCT INTG, DXA LAT,and RA PHAL, which gave kappa scores between 0.65 and0.89 for the classification as osteopenic and between 0.63and 0.87 for the classification as osteoporotic. Even in thesecases, different patients were sometimes estimated at riskby different measurement approaches (Figs. 5 and 6).

DISCUSSION

Measurements of different bone parameters such asBMD, BMC, SOS, or BUA at various body sites have beenfound useful in assessing skeletal status, assessing osteopo-

TABLE 1. CONTINUED

Methodparameter (n)

Mean SD% decr.t valuep valuePRE vs.POST

% decr.t valuep valuePOSTvs.

OSTEO

Annual loss(%)/SDPRE 1POST

Cor (2) w.age p valuePRE 1POST

Odds ratioLCL/UCLPOST vs.OSTEO

ROCAREA SEPOST vs.OSTEOPRE POST OSTEO

pQCT RAD 145 111 87 23.2 21.9 0.72 0.46 1.7 0.73CORT BMC 40 38 30 3.7 2.9 0.027 0.0001 0.9/3.2 0.06mg (106) 0.0004 0.006pQCT RAD 283 241 221 14.8 8.3 0.44 0.54 1.4 0.69TOT BMC 43 32 35 4.9 2.4 0.029 0.0000 0.8/2.7 0.06mg (106) 0.0000 0.020RA CH 2.48 2.13 1.91 14.2 10.3 0.47 0.63 1.7 0.73METC BMD 0.30 0.28 0.29 4.9 3.3 0.038 0.0001 0.9/3.3 0.06A1 eqival. (103) 0.0001 0.002RA CO 107 88 79 18.6 10.0 0.51 0.71 2.0 0.77PHAL BMD 9 11 10 8.2 3.6 0.062 0.0001 1.1/3.6 0.06A1 eqival. (103) 0.0001 0.001BUA WS 89 74 64 16.5 13.5 0.52 0.45 1.7 0.73CALC 18 16 18 4.1 2.6 0.026 0.0001 1.0/3.0 0.06db/MHz (123) 0.0001 0.010SOS WS 1517 1505 1504 0.8 0.1 0.02 0.57 1.0 0.69CALC 11 8 27 5.6 0.32 0.034 0.0001 0.6/1.5 0.06m/s (121) 0.0001 0.750BUA LA 117 111 106 5.1 5.2 0.18 0.30 1.4 0.70CALC 13 12 15 2.2 1.9 0.016 0.0050 0.8/2.4 0.06db/MHz (115) 0.0310 0.068SOS LA 1580 1532 1510 3.0 1.5 0.09 0.63 2.1 0.78CALC 38 30 26 6.3 3.4 0.039 0.0001 1.2/3.9 0.05m/s (115) 0.0001 0.001

NONINVASIVE BONE MINERAL MEASUREMENTS 701

rosis, and determining osteoporotic fracture risk. QCT ofthe spine has been used to assess the skeletal status anddetect age- and disease-related changes,(6–11,30–33) but ithas been less widely used than DXA due to its cost andcomplexity. More recently, QUS, pQCT, and computerized

RA have been introduced as reliable methods for assessingskeletal status.Most of these techniques have been evaluated and com-

pared in limited combinations in different studies. Since thestudy populations and/or the definition of osteoporosis dif-

FIG. 1. (A) QCT TRAB BMD, (B) DXA LAT BMD, (C) DXA FEM TROC BMD, (D) DXA RAD UD BMD, (E)pQCT CORT RAD BMC, (F) RA CO PHAL BMD, (G) BUA WS CALC, and (H) SOS LA CALC in the discriminationof study groups. Means with standard deviation lines are given.

702 GRAMPP ET AL.

fered, the results of the different studies cannot be easilycompared. In addition, all techniques reported in thismanuscript have not yet been used in one single populationand the results compared. Ensuring that all the patientswere measured by each technique enabled comparability ofthe different techniques.

Detection of age- and menopause-related bone loss

In our study, we found that all the techniques exceptpQCT RAD TRAB BMD readily differentiated betweenhealthy premenopausal and healthy postmenopausal sub-jects and reflected age- and menopause-related bone loss.In differentiating between healthy premenopausal and

healthy postmenopausal women, the best abilities (based onpercentage decrement and Student’s t values) were shownby QCT, followed by DXA LAT BMD of the spine. Similarresults were also obtained by Steiger et al.(31) who found adecrement of 42% in the comparison of healthy premeno-pausal and healthy postmenopausal women for QCT TRABBMD and 28% for QCT INTG BMD. DXA of the spineshowed better abilities in the lateral (DXA LAT BMD)measurements compared with the PA (DXA PA BMD)measurements. This agrees with the results obtained byGuglielmi et al.,(7) who found the highest sensitivity andspecificity for the detection of age- and osteoporosis-relatedchanges for QCT TRAB BMD followed by DXA LATBMD and by DXA PA BMD. The RA CO PHAL BMD

FIG. 2. Linear correlations with age (r values) shown as a bar chart.

FIG. 3. Age-adjusted odds ratios are shown as a bar chart.

NONINVASIVE BONE MINERAL MEASUREMENTS 703

TABLE 2. CORRELATION COEFFICIENTS (R) AND %SEE (CV) FOR ALL WOMEN (PRE, POST AND OSTEO) P VALUE 5 NS,NOT SIGNIFICANT AT 0.05; 21 SIGNIFICANCE AT 0.05; 22 AT 0.01; 23 AT 0.001; 24 AT 0.0001

r CV p

QCTTRABBMD

QCTINTGBMD

DXAPABMD

DXALATBMD

DXAFEMNECKBMD

DXAFEMTROCBMD

DXAUDRADBMD

pQCTTRABRADBMD

pQCTCORTRADBMC

RACHMETCBMD

RACOPHALBMD

BUAWSCALC(db/MHz)

SOSWSCALC(m/s)

BUALACALC(db/MHz)

SOSLACALC(m/s)

QCT 1 0.94 0.72 0.87 0.71 0.77 0.76 0.40 0.64 0.71 0.81 0.64 0.40 0.40 0.79TRAB 8.8 12.1 9.2 14.2 12.1 11.0 23.0 28.7 12.1 9.8 19.9 1.1 11.5 1.7BMD 24 24 24 24 24 24 24 24 24 24 24 24 24 24QCT 0.94 1 0.83 0.88 0.77 0.83 0.76 0.41 0.62 0.72 0.80 0.60 0.37 0.41 0.76INTG 15.1 9.6 8.9 12.8 10.7 11.0 22.8 29.4 11.9 10.1 20.7 1.1 11.4 1.9BMD 24 24 24 24 24 24 24 24 24 24 24 24 24 24DXA 0.72 0.83 1 0.74 0.76 0.76 0.62 0.36 0.48 0.57 0.61 0.50 0.31 0.34 0.58PA 30.2 14.0 12.8 13.1 12.3 13.3 23.2 32.8 14.0 13.5 22.4 1.1 11.8 2.3BMD 24 24 24 24 24 24 24 24 24 24 24 23 23 24DXA 0.87 0.88 0.74 1 0.71 0.81 0.67 0.40 0.55 0.66 0.75 0.61 0.41 0.35 0.74LAT 21.0 11.9 11.7 14.2 11.3 12.5 22.9 31.2 12.8 11.3 20.5 1.1 11.7 1.9BMD 24 24 24 24 24 24 24 24 24 24 24 24 24 24DXA 0.71 0.77 0.76 0.71 1 0.84 0.67 0.40 0.53 0.60 0.62 0.54 0.37 0.34 0.67FEM 30.6 16.1 11.3 13.3 10.4 12.5 22.9 31.8 13.7 13.3 21.8 1.1 11.8 2.1NECK 24 24 24 24 24 24 24 24 24 24 24 24 23 24BMDDXA 0.77 0.83 0.76 0.81 0.84 1 0.65 0.45 0.49 0.60 0.69 0.55 0.34 0.29 0.72FEM 27.5 14.2 11.2 11.2 11.0 12.8 22.2 32.6 13.7 12.3 21.6 1.1 12.0 2.0TROC 24 24 24 24 24 24 24 24 24 24 24 23 22 24BMDDXA 0.76 0.76 0.62 0.67 0.67 0.65 1 0.62 0.69 0.74 0.77 0.56 0.42 0.24 0.66UD 27.9 16.3 13.5 13.8 14.8 14.4 19.7 25.9 11.4 10.8 21.3 1.1 11.1 2.1RAD 24 24 24 24 24 24 24 24 24 24 24 24 21 24BMDpQCT 0.40 0.41 0.36 0.40 0.40 0.45 0.62 1 0.25 0.38 0.52 0.41 0.29 0.11 0.46TRAB 40.3 23.2 16.0 17.2 19.1 17.5 13.3 36.3 15.5 14.5 23.3 1.2 11.8 2.6RAD 24 24 24 24 24 24 24 21 24 24 24 22 NS 24BMDpQCT 0.64 0.62 0.48 0.55 0.53 0.49 0.69 0.25 1 0.62 0.63 0.42 0.27 0.30 0.42CORT 33.8 20.0 15.1 15.6 17.7 17.1 12.1 24.2 13.2 13.2 23.2 1.2 11.3 2.6RAD 24 24 24 24 24 24 24 21 24 24 24 22 22 24BMCRA 0.71 0.72 0.57 0.66 0.60 0.60 0.74 0.38 0.62 1 0.73 0.51 0.28 0.26 0.60CH 32.7 18.5 14.9 14.7 16.5 16.1 12.2 23.5 30.3 11.6 23.7 1.2 12.0 2.4METC 24 24 24 24 24 24 24 24 24 24 24 22 21 24BMDRA 0.81 0.80 0.61 0.75 0.62 0.69 0.77 0.52 0.63 0.73 1 0.62 0.45 0.38 0.75CO 27.1 16.0 14.5 13.1 16.2 14.6 11.6 21.8 29.9 11.8 21.5 1.1 11.4 2.0PHAL 24 24 24 24 24 24 24 24 24 24 24 24 24 24BMDBUA 0.64 0.60 0.50 0.61 0.54 0.55 0.56 0.41 0.42 0.51 0.62 1 0.52 0.41 0.83WS 33.3 20.2 15.0 15.0 16.9 15.9 14.0 22.8 33.9 14.8 13.2 1.0 11.4 1.6CALC 24 24 24 24 24 24 24 24 24 24 24 24 24 24(db/MHz)SOS 0.40 0.37 0.31 0.41 0.37 0.34 0.42 0.29 0.27 0.28 0.45 0.52 1 0.24 0.56WS 39.2 23.3 16.3 17.2 18.6 18.1 15.1 23.9 36.0 16.2 14.9 22.2 12.1 2.4CALC 24 24 22 24 24 23 24 22 22 22 24 24 22 24(m/s)BUA 0.40 0.41 0.34 0.35 0.34 0.29 0.24 0.11 0.30 0.26 0.38 0.41 0.24 1 0.42LA 38.9 23.2 16.3 17.7 19.1 18.5 16.3 25.2 35.1 16.3 15.4 23.8 1.1 2.6CALC 24 24 23 24 23 22 21 NS 22 21 24 24 22 24(db/MHz)SOS 0.79 0.76 0.58 0.74 0.67 0.72 0.66 0.46 0.42 0.60 0.75 0.83 0.56 0.42 1LA 26.1 16.6 14.2 12.7 15.1 13.4 12.6 22.5 33.4 13.6 10.9 14.5 1.0 11.4CALC 24 24 24 24 24 24 24 24 24 24 24 24 24 24(m/s)

TABLE 3. KAPPA SCORES FOR THE CLASSIFICATION OF POSTMENOPAUSAL WOMEN (POST AND OSTEO) AS OSTEOPENIC(T SCORE , 22.0) AND OSTEOPOROTIC POSTMENOPAUSAL (OSTEO) AS OSTEOPOROTIC (T SCORE , 22.5)

kt,22.0t,22.5

QCTTRABBMD

QCTINTGBMD

DXAPABMD

DXALATBMD

DXAFEMNECKBMD

DXAFEMTROCBMD

DXAUDRADBMD

pQCTTRABRADBMD

pQCTCORTRADBMD

RACHMETCBMD

RACOPHALBMD

BUAWSCALC(db/MHz)

SOSWSCALC(m/s)

BUALACALC(db/MHz)

SOSLACALC(m/s)

QCTTRABBMD

1.00 0.89 0.41 0.75 0.34 0.47 0.41 0.25 0.18 0.32 0.68 0.20 0.29 0.04 0.38

1.00 0.87 0.54 0.81 0.16 0.30 0.31 0.17 0.22 0.33 0.75 0.12 0.12 0.03 0.28

QCTINTGBMD

0.89 1.00 0.46 0.75 0.32 0.50 0.43 0.29 0.21 0.32 0.71 0.24 0.33 0.05 0.41

0.87 1.00 0.60 0.86 0.18 0.35 0.43 0.15 0.12 0.28 0.78 0.14 0.14 0.05 0.33

DXAPABMD

0.41 0.46 1.00 0.37 0.43 0.66 0.40 0.16 0.19 0.35 0.31 0.30 0.33 0.06 0.27

0.54 0.60 1.00 0.55 0.15 0.35 0.22 0.07 0.34 0.50 0.44 0.17 0.31 0.04 0.09

DXALATBMD

0.75 0.75 0.37 1.00 0.26 0.44 0.33 0.26 0.21 0.34 0.65 0.27 0.38 0.06 0.47

0.81 0.86 0.55 1.00 0.21 0.40 0.35 0.21 0.08 0.44 0.63 0.16 0.17 0.05 0.34

DXAFEMNECKBMD

0.34 0.32 0.43 0.26 1.00 0.56 0.55 0.21 0.10 0.39 0.19 0.30 0.50 0.13 0.37

0.16 0.18 0.15 0.21 1.00 0.47 0.07 20.04 20.04 20.08 0.06 20.04 0.25 0.17 0.28

DXAFEMTROCBMD

0.47 0.50 0.66 0.44 0.56 1.00 0.33 0.35 0.20 0.33 0.36 0.25 0.36 0.04 0.42

0.30 0.35 0.35 0.40 0.47 1.00 0.38 0.64 0.35 0.53 0.31 0.33 0.33 0.07 0.37

DXAUDRADBMD

0.41 0.43 0.40 0.33 0.55 0.33 1.00 0.44 0.31 0.44 0.36 0.36 0.44 0.07 0.38

0.31 0.43 0.22 0.35 0.07 0.38 1.00 0.58 0.29 0.41 0.44 0.24 20.04 0.07 0.58

pQCTTRABRADBMD

0.25 0.21 0.16 0.26 0.21 0.35 0.44 1.00 0.22 0.33 0.35 0.22 0.16 0.05 0.29

0.17 0.15 0.07 0.21 20.04 0.64 0.58 1.00 0.41 0.57 0.32 0.47 20.04. 20.06 0.40

pQCTCORTRADBMC

0.18 0.21 0.19 0.20 0.10 0.20 0.31 0.22 1.00 0.29 0.17 0.16 0.25 0.13 0.23

0.22 0.12 0.34 20.08 20.04 0.35 0.29 0.41 1.00 0.26 0.19 0.17 0.25 0.24 20.07

RACHMETCBMD

0.32 0.32 0.35 0.34 0.38 0.33 0.44 0.33 0.29 1.00 0.30 0.27 0.23 0.11 0.24

0.33 0.28 0.49 0.44 0.08 0.53 0.41 0.57 0.26 1.00 0.43 0.48 0.33 0.08 0.19

RACOPHALBMD

0.68 0.71 0.30 0.65 0.19 0.36 0.36 0.35 0.17 0.30 1.00 0.33 0.23 0.03 0.50

0.75 0.78 0.44 0.63 0.06 0.31 0.44 0.32 0.19 0.43 1.00 0.23 0.10 0.07 0.35

BUAWSCALC(db/MHz)

0.20 0.24 0.30 0.27 0.30 0.25 0.36 0.22 0.16 0.27 0.33 1.00 0.55 0.18 0.50

0.12 0.14 0.17 0.16 20.04 0.33 0.24 0.47 0.17 0.48 0.23 1.00 0.31 20.05 0.37

SOSWSCALC(m/s)

0.29 0.33 0.33 0.38 0.50 0.36 0.44 0.16 0.25 0.23 0.23 0.55 1.00 0.03 0.63

0.12 0.14 0.31 0.17 0.25 0.33 20.04 20.04 0.25 0.33 0.10 0.31 1.00 20.04 20.04

BUALACALC(db/MHz)

0.04 0.05 0.06 0.63 0.13 0.03 0.07 0.05 0.13 0.11 0.03 0.18 0.03 1.00 0.07

0.03 0.05 0.04 0.05 0.17 0.07 0.07 20.06 0.24 20.08 0.07 20.05 20.04 1.00 0.12

SOSLACALC(m/s)

0.38 0.41 0.27 0.47 0.37 0.43 0.38 0.29 0.23 0.24 0.50 0.50 0.63 0.07 1.00

0.28 0.33 0.09 0.34 0.28 0.37 0.58 0.40 20.08 0.19 0.35 0.37 20.04 0.12 1.00

NONINVASIVE BONE MINERAL MEASUREMENTS 705

technique showed good distinction between healthy pre-menopausal and healthy postmenopausal women and bet-ter sensitivity to age-related changes than pQCT, QUS, andDXA of either femur or radius. A similar trend was re-ported by Matsumoto et al.,(23) who found that RA of themetacarpals provided a sensitivity for discrimination be-tween age groups similar to that of DXA PA BMD. Inaddition, we found that for DXA of the proximal femur, thebest parameter was the DXA FEMWARDBMD; for DXAof the radius, DXA RAD TOT BMD; for pQCT of theradius, pQCT RAD CORT BMC; for RA of the hand, RACO PHAL BMD; and for QUS of the calcaneus, SOS LACALC.Similarly, when investigating age- and menopause-re-

lated changes by linear regression analysis, we found astrong inverse relationship between bone parameters andage for most sites and techniques. Our results, in agreementwith many studies,(7,10,31,34,35) suggest that the sensitivity todetect age-related changes, expressed as percentage annualloss, was higher at the spine measured with QCT TRABBMD than with QCT INTG BMD, DXA LAT BMD, orDXA PA BMD. We found that DXA PA BMD showedcomparatively smaller age-related changes compared withother axial and many appendicular measures except pQCTand QUS. This finding agrees with that of Steiger et al.,(36)

who found smaller changes with age in DXA PA BMD thanin DXA at the femur or at the calcaneus. The authorssuggested that this may be influenced by the fact that DXAPA spine measurements are confounded by degenerativechanges of the vertebrae, a suggestion strongly supportedby Ito et al.(9) and also suggested in our study population.We also found a comparatively high annual change ofaround 21% for DXA FEM WARD. Similar results forDXA of the femur were reported by Greenspan et al.,(37)

who found that in women aged 65 and over, the highestannual BMD changes (20.86%) occurred at the Ward’striangle. However, results given by Steiger et al.(36) for

age-related changes in women aged 65 and over showedlarger changes for DXA FEMNECK BMD and DXA FEMTROC BMD (20.82% and 21.30%, respectively). Thosenumbers differ from ours principally because our measureof annual loss substantially reflects the menopause whileSteiger’s reflect age-related effects among the very elderly.For QUS measurements, we found that BUAWS CALC,

which largely covers a volume of trabecular bone, showed acomparatively high annual loss of 20.52% (the SOS per-cent decrement would generally be low compared withother parameters due to a large denominator). This sup-ports the concept that skeletal sites consisting predomi-nantly of trabecular bone respond faster to metabolic stim-uli than cortical bone.(38,39) This measure, however, was theonly ultrasound parameter in our study which showed sucha substantial annual decrement. Similar results were re-ported by Schott et al.(40) who found annual changes in afemale population of 20.29% by BUA LA CALC and of20.07% by SOS LA CALC. Moris et al.(41) found agecorrelations in women of r 5 20.62 for SOS and r 5 20.59for BUA, similar to our observed correlations.In our study, the measurements at the radius most

strongly influenced by age and menopause were DXA RAD1/3 BMD (20.46%/year) and pQCT RAD COR BMC(20.38%). Age-related changes in cortical BMC at theradius appear to be largely due to endosteal thinning of thecortical bone since both cortical area and cortical BMCdiminish proportionally. The importance of changes in theperipheral cortical bone was recently emphasized in severalstudies at the forearm using DXA(36,42–44) as well aspQCT.(13,15) However, some authors have reported signif-icant losses in radial trabecular BMD of 20.5 to 21.1%/year in women, especially shortly after the meno-pause.(14,45) The differences between our results and thesestudies might be caused by differences between study pop-ulations, especially due to different criteria used in thedefinition of healthy subjects. Moreover, in contrast to

FIG. 4. Mean intersite/technique correlations (average r values by technique) shown as a bar chart.

706 GRAMPP ET AL.

these pQCT studies, which separated cortical bone and softtissue by an iterative contour-finding algorithm(14) or anindividual threshold setting,(45) a constant threshold wasused for all subjects in our study. Although this consistencyof threshold guaranteed a high measurement precision,(15)

it under-represented the total amount of bone in cases oflow overall density or thin cortical rims. Differences in thedata evaluation process were therefore most pronounced inelderly subjects and might be responsible for the inconsis-tency in the trabecular BMD results.With respect to RA techniques, our data showed reason-

able age-related changes at both the phalanges and the

metacarpals. The age-related annual losses were compara-ble to other peripheral measurements used in our study.This result is consistent with the results published for RA atboth sites of the hand. In this context, Fukunaga et al.(21)

demonstrated that RA CH METC BMD showed age-re-lated losses comparable to DXA RAD BMD and betterthen DXA PA BMD of the lumbar spine. Matsumoto etal.(23) reported annual losses in women by RA of the meta-carpals which ranged between 20.8% (in the eighth de-cade) and 21.5% (in the sixth decade). One reason ournumbers differ could be that in calculating annual bone losswe used all the women with ages ranging from 21 to 79,

FIG. 5. Mean (1SD) kappa scores for the classification of postmenopausal women (POST and OSTEO) as osteopenic(T score , 22.0 relative to PRE) shown as a bar chart.

FIG. 6. Mean (1SD) kappa scores for the classification of women with vertebral fractures (OSTEO) as osteoporotic(T score , 2.5 relative to PRE) shown as a bar chart.

NONINVASIVE BONE MINERAL MEASUREMENTS 707

while Matsumoto et al.(23) calculated losses for women ineach decade.

Discrimination of osteoporotic women

Of equal interest to the comparisons of the two healthygroups (reflecting age- and menopause-related changes)are the comparisons of the measurements in their ability todiscriminate between healthy postmenopausal and osteopo-rotic postmenopausal women. We used the Student’s t-test,odds ratios, and area under the ROC curve as statisticalapproaches to quantify the ability of the measurements todiscriminate the osteoporotic postmenopausal group fromthe healthy postmenopausal group. Since most of the mea-surements are influenced by age, we adjusted for age in thelogistic regression and ROC analysis. The results of oddsratios analysis reflected closely the trends shown by theStudent’s t-test. In our study, QCT TRAB BMD and QCTINTG BMD gave the best results based on age-adjustedodds ratios, followed by DXA LAT BMD and DXA PABMD. The same trend, with QCT demonstrating the high-est sensitivity for distinction between normal and osteopo-rotic women, was found in studies by Guglielmi et al.(7) andby Jergas et al.,(35) who compared QCT with DXA LATBMD and DXA PA BMD, by Pacifici et al.,(10) and by VanBerkum et al.,(46) who compared QCT with DXA PA BMD.Some appendicular measurements made in our study alsogave a significant odds ratio but were generally lower com-pared with measurements at the spine. The parametersgiving the highest odds ratio for each of these techniqueswere: for DXA of the femur, FEM TROC BMD; for DXAof radius, RAD TOT BMD; for pQCT of the radius, RADCORT BMC; for RA of the hand, CO PHAL BMD; and forQUS of the calcaneus, SOS LA CALC. The trend of spinemeasurements showing better discrimination for vertebralfractures has been reported in many cross-sectional studiescomparing the abilities of measurements of the spine withthose of peripheral sites.(34,47–50) In contrast, it has beenreported in both cross-sectional and longitudinal studiesthat peripheral measurements may be equal to spinal mea-surements when the latter are obtained by projectionaltechniques such as DXA. Cummings et al.(51) and Davis etal.(52) found that calcaneal DXA measurements were betterthan the DXA PA BMD for assessing hip fracture risk andage-related bone loss. Matsumoto et al.,(23) in a comparisonof RA CH METC BMD and DXA PA BMD, found themethods were equivalent in their abilities to discriminate anosteoporotic group from a healthy group. Grampp et al.,Bjarnson et al., and Overgaard et al. found that DXA of theradius had a discriminative ability comparable to spinalDXA.(15,53,54)

Even with the trends shown in our study, the discrimina-tive abilities of various measurements based on the age-adjusted ROC analysis were not significantly different. Dueto the relatively small sample size of our study, the powerfor detecting small differences is not very great. Therefore,the comparison of odds ratios was only able to depict trendsin our study and could become significant in larger popu-lations. So with the small sample sizes in mind and thetrends shown above, it can be suggested that the ability of

QCT TRAB BMD for the discrimination of osteoporoticsubjects is strongest, followed by QCT INTG BMD. DXAat the spine as well as other measurements at hip, radius,hand, and calcaneus also demonstrate these discriminatoryabilities, similar to each other but weaker than those ofQCT.

Correlations among measurement techniques

Correlations between the different measurementsranged from weak to strong depending on the anatomicsite and technique used. Average correlations amongall the techniques/sites were only modest (Fig. 7) andwere similar to those given in the recent litera-ture.(7,10,11,15,17,19–22,34–36,45,47,55,56) Generally, correlationsbetween measurements at the lumbar spine includingQCT and DXA were modest to strong. Correlations be-tween the various measurement ROIs at the femur usingDXA were modest, and between the various calcaneusmeasurements using QUS weak to moderate. At the radius,measurements performed with pQCT and DXA did notshow strong correlations, and trabecular and cortical boneparameters by pQCT were only weakly correlated.We found modest correlations when comparing axial and

peripheral measurement sites. One remarkable point maybe that in our study the comparison between X-ray basedmethods and ultrasound measurements were only margin-ally lower than those between X-ray based methods alone.This agrees with results given by other authors for measure-ments of BUA(40,41,50,57,58) and SOS.(41,59)

The only study that reported substantially different re-sults from ours for pQCT was from Rico et al.(60) In theirstudy of radial pQCT, correlation coefficients for compar-isons between total BMD and cortical BMD, total BMDand trabecular BMD, and trabecular BMD and corticalBMD were r 5 0.95, 0.62, and 0.43, respectively. This couldbe due to different study populations, a different definitionof osteoporosis, and/or a different algorithm to differentiatecortical bone from soft tissue.

Diagnostic agreement among measurement techniques

The selection of a specific threshold level for t score israther arbitrary, and at any given point the prevalence of“disease” differs substantially by site and technique. In thisexercise we selected a T score of 22 for osteopenia toachieve a reasonable balance between “disease” and “non-disease” in this elderly female population. The selection ofT score of 22.5 for osteoporosis is compatible with WHOproposed criteria and perhaps appropriate for the vertebralfracture group.Considering the relatively modest correlation coefficients

found between the different parameters, techniques, andsites, it is not surprising that by kappa analysis the diagnos-tic agreement among these measures in classifying womenas osteopenic or osteoporotic was generally poor whenusing specific thresholds. The exception to this was theagreement of QCT TRAB/INTG BMD with DXA LATBMD and with RA CO PHAL BMD. Often different pa-tients were estimated at risk by different measurement

708 GRAMPP ET AL.

approaches, (as indicated by the rather low kappa scores).These levels of diagnostic disagreement may result from anumber of factors. All of the techniques have their ownspecific error sources as well as fundamentally differentmethodologies and units of expression that undermine theirrespective abilities to define true biological relationshipswithin or between anatomic sites or between individuals.(1,61)

Beyond technical considerations, genetic and environmen-tal influences and pathophysiologic forces may impact thecortical and trabecular bone envelopes or the appendicularand axial skeleton in a different manner in different indi-viduals,(36,49,52,62) and therefore some of the measured dis-crepancies reflect true anatomic variations that result inunlike diagnostic classifications. These observations havemajor clinical ramifications. The choice of the same T score(22.0 for osteopenia and 22.5 for osteoporosis in thisstudy) for different sites and different techniques may notbe advisable. More importantly, use of a single measure anda specific cut-off to diagnose and treat an individual patientis problematic and perhaps unwise.There are limitations in the interpretation of our study

results. First, due to our small population size, many of thedifferences do not reach statistical significance and someapparent differences may not be real. Second, this study iscross-sectional in design and can provide inferences aboutvertebral fracture discrimination but no information specif-ically about fracture risk prediction or the ability to monitordisease or treatment-induced changes. Third, our resultsmay be influenced by our definition for osteoporosis, re-quiring the presence of a vertebral fracture.(63) This diag-nostic criterion may favor axial measurements over periph-eral measurements, whereas selecting hip fracture or otherlong-bone fracture could provide different ranking of themethods.All of the techniques examined were capable of assessing

age- and menopause-related changes, and of defining theskeletal status in these women. Spinal QCT appeared toprovide the most robust performance overall. The othermeasurements at the axial or appendicular sites were rela-tively similar to each other. The results derived from thevarious techniques were only moderately correlative, whichprecluded the prediction of one parameter from anotherparameter in the individual woman and caused disagree-ment in diagnostic classification in many women.

ACKNOWLEDGMENTS

We thank Cynthia Hayashi-Clark ARRT, Susan SchoenARRT, and Vesta March ARRT for performing the mea-surements and analyses of the patient scans.

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Address correspondence and reprint requests to:Harry K. Genant, M.D.

Professor of Radiology, Medicine, and Orthopedic SurgeryExecutive Director, Osteoporosis Research Group

Department of RadiologyMusculoskeletal Section

University of California–San Francisco505 Parnassus Avenue

Box 0628San Francisco, CA 94143 U.S.A.

Received in original form August 14, 1996; in revised form No-vember 1, 1996; accepted December 5, 1996.

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