Phalangeal osteosonogrammetry study: age-related changes, diagnostic sensitivity, and discrimination power. The Phalangeal Osteosonogrammetry Study Group.
ABSTRACT Phalangeal osteosonogrammetry was introduced as a method for bone tissue investigation in 1992. It is based on the measure of the velocity of ultrasound (amplitude-dependent speed of sound [AD-SoS]) and on the interpretation of the characteristics of the ultrasound signal. In this study we have collected a database of 10,115 subjects to evaluate the performance of AD-SoS and to develop a parameter that is able to quantify the signal characteristics: ultrasound bone profile index (UBPI). The database only includes females of which 4.5% had documented vertebral osteoporotic fractures, 16% lumbar spine dual X-ray absorptiometry (DXA), and 6% hip DXA. The analysis of the ultrasound signal has shown that with aging the UBPI, first wave amplitude (FWA), and signal dynamics (SDy) follow a trend that is different from the one observed for AD-SoS; that is, there is no increase during childhood. In the whole population, the risk of fracture per SD decrease for AD-SOS was odds ratio (OR) 1.71 (CI, 1.58-1.84). The AD-SoS in fractured subjects was significantly lower than in a group of age-matched nonfractured subjects (p < 0.0001). In a small cohort of hip-fractured patients UBPI proved to be lower than in a control age-matched group (p < 0.0001). When the World Health Organization (WHO) working group criteria were applied to this population to identify the T score value for osteoporosis, for AD-SoS we found a T score of -3.2 and for UBPI we found a T score of -3.14. Sixty-six percent of vertebral fractures were below the AD-SoS -3.2 T score and 62% were below UBPI -3.14. We observed the highest incidence of fractures (63.6%) among subjects with AD-SoS who had both DXA T score values below the threshold. We conclude from this study that ultrasound investigation at the hand phalanges is a valid methodology for osteoporosis assessment. It has been possible to quantify signal changes by means of UBPI, a parameter that will improve the possibility of investigating bone structure.
- [Show abstract] [Hide abstract]
ABSTRACT: Osteoporosis is a major cause of fragility fractures and these are responsible of large social burden; nevertheless, osteoporosis often remains an underdiagnosed disease. FRAX is a new and simple validate fracture risk assessment tool helping physicians to select patients at high risk of future fragility fractures. To promote early diagnosis of osteoporosis, we evaluated fracture risk by FRAX and performed phalangeal quantitative ultrasound (QUS) measurements in a population of postmenopausal women referring to our center during the World Osteoporosis Day on 20th October 2011. Eighty post-menopausal women (age 60.8±8.6) were screened and the risk of major osteoporotic and hip fractures over ten years was calculated by considering multiple clinical risk factors (CRFs). The median risk of major osteoporotic fracture (%) was 4.9 (3.5-8.6) in women younger than 55 years, 7.3 (5.4-11) in women aged between 55 and 65 years and 17.5 (11-27) in women older than 65 years; the median risk of hip fracture (%) was 0.6 (0.3-1.3), 1.5 (0.9-2.5) and 7.2 (3.1-14) respectively. QUS measurements, were lower in the older women and when multiple CRFs coexisted, and were found to correlate with fracture risk, especially with hip fracture risk (p<0.05). Within one month from the screening, 75% (44/59) of the women over 55 years came back and received a diagnosis of osteoporosis/osteopenia by dual x-ray absorptiometry (DXA); a positive association between DXA and QUS measurements was observed (p<0.0001). Adequate treatment of these subjects could reduce fracture rates, improve the quality of life, and reduce the social costs of osteoporosis.Clinical Cases in Mineral and Bone Metabolism 01/2013; 10(3):191-194.
- [Show abstract] [Hide abstract]
ABSTRACT: Effective prevention and management of osteoporosis would require suitable methods for population screenings and early diagnosis. Current clinically-available diagnostic methods are mainly based on the use of either X-rays or ultrasound (US). All X-ray based methods provide a measure of bone mineral density (BMD), but it has been demonstrated that other structural aspects of the bone are important in determining fracture risk, such as mechanical features and elastic properties, which cannot be assessed using densitometric techniques. Among the most commonly used techniques, dual X-ray absorptiometry (DXA) is considered the current "gold standard" for osteoporosis diagnosis and fracture risk prediction. Unfortunately, as other X-ray based techniques, DXA has specific limitations (e.g., use of ionizing radiation, large size of the equipment, high costs, limited availability) that hinder its application for population screenings and primary care diagnosis. This has resulted in an increasing interest in developing reliable pre-screening tools for osteoporosis such as quantitative ultrasound (QUS) scanners, which do not involve ionizing radiation exposure and represent a cheaper solution exploiting portable and widely available devices. Furthermore, the usefulness of QUS techniques in fracture risk prediction has been proven and, with the last developments, they are also becoming a more and more reliable approach for assessing bone quality. However, the US assessment of osteoporosis is currently used only as a pre-screening tool, requiring a subsequent diagnosis confirmation by means of a DXA evaluation. Here we illustrate the state of art in the early diagnosis of this "silent disease" and show up recent advances for its prevention and improved management through early diagnosis.World journal of radiology. 11/2013; 5(11):398-410.
- [Show abstract] [Hide abstract]
ABSTRACT: To evaluate bone status in children born from mothers followed for autoimmune diseases and treated during pregnancy with low molecular weight heparin (LMVH) and/or prednisone.Annals of the Rheumatic Diseases 01/2014; 12:47. · 9.11 Impact Factor
Phalangeal Osteosonogrammetry Study: Age-Related
Changes, Diagnostic Sensitivity, and Discrimination Power
C. WU¨STER,1C. ALBANESE,2D. DE ALOYSIO,3F. DUBOEUF,4M. GAMBACCIANI,5S. GONNELLI,6
C.C. GLU¨ER,7D. HANS,8J. JOLY,9J.Y. REGINSTER,10,11F. DE TERLIZZI,12R. CADOSSI,12and
THE PHALANGEAL OSTEOSONOGRAMMETRY STUDY GROUP*
Phalangeal osteosonogrammetry was introduced as a method for bone tissue investigation in 1992. It is based on
of the characteristics of the ultrasound signal. In this study we have collected a database of 10,115 subjects to
evaluate the performance of AD-SoS and to develop a parameter that is able to quantify the signal characteristics:
ultrasound bone profile index (UBPI). The database only includes females of which 4.5% had documented
vertebral osteoporotic fractures, 16% lumbar spine dual X-ray absorptiometry (DXA), and 6% hip DXA. The
analysis of the ultrasound signal has shown that with aging the UBPI, first wave amplitude (FWA), and signal
dynamics (SDy) follow a trend that is different from the one observed for AD-SoS; that is, there is no increase
during childhood. In the whole population, the risk of fracture per SD decrease for AD-SOS was odds ratio (OR)
1.71 (CI, 1.58–1.84). The AD-SoS in fractured subjects was significantly lower than in a group of age-matched
nonfractured subjects (p < 0.0001). In a small cohort of hip-fractured patients UBPI proved to be lower than in
a control age-matched group (p < 0.0001). When the World Health Organization (WHO) working group criteria
and for UBPI we found a T score of ?3.14. Sixty-six percent of vertebral fractures were below the AD-SoS ?3.2
T score and 62% were below UBPI ?3.14. We observed the highest incidence of fractures (63.6%) among subjects
with AD-SoS who had both DXA T score values below the threshold. We conclude from this study that ultrasound
investigation at the hand phalanges is a valid methodology for osteoporosis assessment. It has been possible to
quantify signal changes by means of UBPI, a parameter that will improve the possibility of investigating bone
structure. (J Bone Miner Res 2000;15:1603–1614)
Key words:osteoporosis, ultrasound, signal processing, bone, phalanges
1Department of Internal Medicine I, Endocrinology and Metabolism, University of Heidelberg, Heidelberg, Germany.
2Institute of Radiology, University La Sapienza, Rome, Italy.
3Menopause Clinic, Department of Obstetrics and Gynaecology, University of Bologna, Bologna, Italy.
4Department of Rheumatology, Edouard Herriot Hospital, Lyon, France.
5Department of Obstetrics and Gynaecology “Piero Fioretti,” University of Pisa, Pisa, Italy.
6Institute of Internal Medicine, University of Siena, Siena, Italy.
7Klinik fu ¨r Diagnostische Radiologie, Klinikum der Christian-Albrechts-Universita ¨t zu Kiel, Kiel, Germany.
8Osteoporosis and Arthritis Research Group, Department of Radiology, University of California at San Francisco, San Francisco,
9Arthritis and Metabolic Bone Disease Research Unit, University Hospital, K.U. Leuven, Pellenberg, Belgium.
10World Health Organization Collaborating Centre for Public Health of Osteoarticular Disorders, University of Lie `ge, Lie `ge, Belgium.
11Department of Epidemiology and Public Health, University of Lie `ge, Lie `ge, Belgium.
12IGEA Biophysics Laboratory, Carpi, Modena, Italy.
*Members of the Phalangeal Osteosonogrammetry Study Group
contributing to the study were: R. Barkmann, G.P.I. Baroncelli,
C.M. Boivin, E. Boschitsch, G. Federico, C. Franceschi, C. Gen-
nari, G. Guglielmi, M. Mauloni, G. Pini, J. Nijs, C.F. Njeh, S.
Ortolani, W. Pluskiewicz, J.P. Sabatier, A. Sili Scavalli, R. Theiler.
JOURNAL OF BONE AND MINERAL RESEARCH
Volume 15, Number 8, 2000
© 2000 American Society for Bone and Mineral Research
an aid in the diagnosis of osteoporosis, has been addressed
in multiple studies over the past decade.(1–4)The interest in
this technology is partly based on unresolved issues con-
cerning current diagnostic means in osteoporosis but mostly
based on its undoubted practical advantages, as compared
with conventional X-ray–based methods. It is relatively
inexpensive, free of ionizing radiation, and equipment is
small in size, permitting easy transport and use in places
distant from fully equipped medical centers. Nevertheless,
often it has been claimed that bone ultrasound (US) methods
are “easy to use,” but such statements are overly optimistic
in view of the practical problems encountered in the increas-
ing use of the wide-ranging equipment available today, and
the essential need for adequate training of the operators
should always be stressed.(5)
One of the initial starting points in the research on ultra-
sound and bone tissue was that ultrasound possibly could
provide more and different information on the physical
properties of bone tissue, as compared with dual X-ray
absorptiometry (DXA).(6,7)This goal has not been pursued
in depth, and recently the ultrasound results have been
proposed as “estimated BMD.”(8)Finally, in most instances
ultrasound measurement has been indicated as a method to
identify subjects that require further investigation by DXA,
thereby the possible intrinsic advantage of ultrasound tech-
nology risks being largely neglected.
The interaction of ultrasound energy with living bone
tissue is extremely complex as density, structure, and elas-
ticity affect ultrasound transmission, that is, velocity, ab-
sorption, scattering, and signal characteristics.(9,10)Thus, a
more sophisticated approach, including the analysis of the
pattern of the transmitted US signal,(11,12)could be fruitfully
adopted, as it has been for most of the diagnostic applica-
tions of ultrasound technology, for example, the echogra-
phy. Among the techniques that have focused on signal
pattern analysis the bone ultrasound investigation at the
phalanx plays a central role.
The phalangeal osteosonogrammetry method was intro-
duced in Europe in 1992–1993 and many studies have
suggested its validity in clinical settings. Bone resorption is
associated with significant changes both in ultrasound ve-
locity and in the characteristics of the ultrasound signal once
it has crossed the phalanx.(13–22)
Phalangeal osteosonogrammetry is computer-assisted and
all measurement data are routinely stored in a personal
computer (PC). This feature makes it possible to collect
large amounts of unprocessed raw data. Thus, we have been
able to pool and analyze data collected in over 20 European
centers that are involved in the buildup of normative data,
the discrimination of subjects with osteoporotic fractures,
and the comparison with DXA findings at the spinal and
femoral sites. All the centers are characterized by their
homogeneity in training and patient recruitment criteria. In
this way, a cross-sectional database was created containing
the osteosonogrammetry readings of over 10,000 European
women of all ages.
HE SUITABILITY of ultrasound-based investigations for
the diagnostic assessment of bone tissue, particularly as
This large database would enable the investigation of
ultrasound velocity changes with aging and osteoporosis
and give us enough statistical power to analyze and quantify
the changes occurring to the ultrasound signal in conse-
quence of its interaction with bone tissue. The final aim was
to ascertain the diagnostic relevance of the ultrasound pa-
rameters to be utilized in the clinical practice.
MATERIALS AND METHODS
At all centers the measurements were performed after
approval by the local ethical committee and all patients gave
their consent to undergo ultrasound examination. For chil-
dren the consent was obtained from parents. To pool the
data, each center was interviewed as to the criteria and
procedures for patient recruitment for phalangeal os-
teosonogrammetry. The center was then asked to supply its
original database that also should contain the patient’s age,
menopausal status, and body mass index. Data only refer-
ring to female white subjects of all ages were collected. For
adult females alcohol abuse or smoking were exclusion
criteria adopted by all centers.
Data sets referring to patients with intercurrent diseases
influencing bone tissue homeostasis, such as rheumatoid
arthritis, renal impairment, and hyperparathyroidism, were
excluded. Patients undergoing treatment with corticoste-
roids or drugs that could interfere with bone metabolism
were excluded, as well as subjects having over 6 months of
treatment with osteotrophic drugs.
When possible, we also included spine and hip bone
mineral density (BMD) measurements. We collected data
from eight different DXA devices, six Hologic (Waltham,
MA, U.S.A.) (five quantitative digital radiography [QDR]
and one ODX) and two Lunar (Lunar Corp., Madison, WI,
U.S.A.); a cross calibration program was not foreseen. Nev-
ertheless, we verified that for each center the mean values of
BMD in the adult premenopausal population were not sig-
nificantly different (data not shown). To be able to compare
the results from different devices, we used the American
National Health and Nutrition Educational Survey (NHANES)
tables to obtain the equivalent T score values from the
actual BMD measurements.(23)In one case (ODX), to be
able to compare data we used a different algorithm devel-
oped in that center.(24)
T score values were used for both quantitative ultrasound
(QUS) and DXA measurements; they were defined accord-
ing to the following formula:
T score ? (measured value
? average value in young adult)/SD in young adult.
Subjects were included in a fractured group if the presence
of at least one fracture was documented (25% reduction in
any height of the vertebra) by lateral X-ray of the thoraco-
lumbar spine. Nevertheless, no central review of the X-rays
1604WU¨STER ET AL.
The final database, referring to measurements performed
from 1993 to 1998, included 10,450 females, between the
ages 0 and 109 years. Before any in-depth analysis, the
database was first inspected and subjects were excluded on
the basis of the following criteria:
● Menopausal age greater than chronological age
● Menopause before 30 years of age
● Body mass index extremes (?19 and ?40), only re-
ferring to adult subjects (over 20 years of age)
● Mistakes in ultrasound measurement, that is, missing
data from one or more fingers, and ultrasound speed in
bone lower than in soft tissue
Cases excluded (335) were documented and reviewed in
cooperation with the supplying center (Table 1).
The final validated database was made up of 10,115
subjects. The entire database was then sorted by test date, to
ensure randomization. Then the database was blinded as to
the source of the data and code, and subjects were identified
exclusively by sequential numbering.
The phalangeal osteosonogrammetry method used in this
study (DBM Sonic 1200 IGEA; Carpi, Italy) is based on the
transmission of US through the proximal phalanges (digits
II-V), probes are applied to the lateral surfaces of the finger.
The coupling of the probes with the skin is mediated by gel.
The device calculates the amplitude-dependent speed of
sound (AD-SoS) and it automatically averages the AD-SoS
values of the four fingers.(16)
At each measuring session the reference speed of the
patient’s soft tissue is measured by applying the probes to
the soft tissue area between the base of the thumb and the
index finger. For bone tissue measurement probes are posi-
tioned at the distal metaphysis of the first phalanges in the
proximity of the condyles. For newborn babies and children
below 3 years of age the velocity was measured at the distal
humerus with probes in the proximity of the condyles,
because the diameter (14 mm) of the US probes was too
large to allow the measurement at the fingers. The distal
humerus is the most accessible and easy to measure with the
DBM Sonic 1200.
All osteosonogrammetry data were stored on a PC con-
nected to the device. For most of the patients it was possible
to collect the ultrasound graphic trace, that is, the charac-
teristics of the electrical signal generated by the ultrasound
at the receiving probe after crossing the phalanx (see Fig. 1).
To perform an in depth analysis of the graphic trace we
considered the part of the US signal with a speed higher
than 1570 m/s (speed in soft tissue), because at a lower
velocity the signal processing is not possible because am-
plitude values saturate. Furthermore, analysis was limited to
the data relating to digits II–IV, because the little finger
often fails to yield a sufficient signal for analysis.
Based on previous experiences(18,22,25,26)the following
parameters on each graphic trace (Fig. 1) were considered:
● Fast wave amplitude (FWA; in mV)
● Dynamics of the ultrasound signal (SDy; mV/?s2)
● Time interval between the first received signal and the
speed value of 1700 m/s (time frame [TF]; in ?s)
● Signal energy (EN) normalized (in mV2*?s)
● Maximum signal amplitude (UPA) in the TF (in mV)
Device calibration and operator training
All devices had been calibrated by the manufacturer using
a composite mother phantom. The devices were calibrated
for AD-SoS (m/s) and the amplitude of the first peak (FWA
in mV). In addition, each center was provided with a phan-
tom to control the ultrasound velocity in Plexiglas on a
weekly basis (reference value, 2760 m/s).
All the operators had been trained by the personnel of the
manufacturer and the measurement method and as the de-
vice calibration were verified twice a year. Whenever a
device was returned to IGEA it was always compared with
the “mother phantom” to verify the amplitude calibration.
Five centers supplied data sets, which were collected to
evaluate the reproducibility of the technology, these were
kept separate from the large database. This second database
included a total of 29 young adult subjects measured at least
three times for intraoperator reproducibility. Interoperator
reproducibility involved two operators per center and 14
young adult females. Intraoperator reproducibility studies
foresaw the repositioning of the probes. Operators were
blinded from previous measurements.
The root mean square (RMS)_CV% was obtained by
graphic trace analysis.
Physical parameters that were considered for
1605PHALANGEAL OSTEOSONOGRAMMETRY STUDY
?i ? 1
where xiis the mean value obtained for each patient i, m is
the number of subjects (i ? 1,2,. . . . , m), and SD is
calculated according to the following formula(27):
SD ???j ? 1
Statistical methods included Student’s t-test and analysis
of variance (ANOVA) for the comparison between groups
of data. The random distribution of the measurements was
guaranteed by the final ordering by test date. When com-
paring fractured and nonfractured subjects, we created sub-
groups of the same size and age from the nonfractured
population, which was usually much larger than the frac-
tured one. Thus, we considered for each age range (2 years)
the number of subjects in the fractured and nonfractured
group; these were sorted according to the sequential num-
bering of the whole database. For each age range we cal-
culated the ratio (n) between nonfractured and fractured
subjects. The first subject of each sequence of n subjects
was selected in the nonfractured group for each age range.
The linear regression analysis was used to detect the
associations between variables yielding correlation coeffi-
cients. Multiple logistic regression was used to determine
the relative risk of fracture with a CI of 95%, referred either
to densitometric or ultrasonic variables and to compare the
discriminatory ability of the different methods. Relative risk
of fracture was expressed as the odds ratio (OR) per SD
decrease of each variable.
The logistic regression analysis also was used to test the
diagnostic effectiveness of the investigated US variables
and, from these variables, to find an optimized model able to
discriminate fractured from nonfractured subjects. The as-
sessment of the optimum combination of variables was
made using Wald’s test, by selecting the variables that
jointly contribute in a significant way to the improvement of
the diagnostic effectiveness of the model.(28,29)The vari-
ables in the optimized model should then show a signifi-
cance level of p ? 0.05.
Receiver operating characteristic (ROC) analysis was
done to assess the discrimination ability of different param-
eters between fractured and nonfractured subjects by calcu-
lating the area under the ROC curve (AUC).
Standardized precision errors (SPEs) also were calculated
for QUS parameters using lumbar spine BMD as a reference
technique, according to the criteria proposed by Glu ¨er.(30)
All statistical analyses were done with the software Sta-
tistical Package for Social Sciences (SPSS, Inc., Chicago,
IL, U.S.A.) and the ROC analyses were done with
LABROC software (Dept. Of Radiology, University of Chi-
cago, Chicago, IL, U.S.A.).
The World Health Organization (WHO) Study Group on
Osteoporosis(31,32)has proposed criteria for the definition of
osteoporosis on the basis of a BMD T score threshold level,
to identify subjects at elevated risk of fracture. This defini-
tion is based on the lower 17% of the overall distribution of
postmenopausal (aged over 50 years) readings at one given
skeletal site. The same criteria have been applied in this
study to find out T score values for QUS parameters, which
can identify osteoporotic subjects. Nevertheless, to extend
the WHO Study Group criteria to our population, we had to
take into account the differences in the distribution of sub-
jects in the age ranges considered, as reported by the WHO
Study Group, in which the incidence of osteoporosis was
calculated separately for different age ranges in the post-
Characteristics of the devices
At the start of the investigation, the mean speed of ultra-
sound in the composite mother phantom was 2565 ? 12 m/s
and the mean amplitude of the first peak was 2.17 ? 0.17
mV for 26 devices utilized. With the mother phantom we
were able to verify 24 out of 26 devices after completion of
the ultrasound measurements by the centers and we could
confirm that calibration was within the accepted range, that
is, 2565 ? 13m/s for AD-SoS and 2.14 ? 0.16mV for
amplitude of the first peak. All values were not statistically
different from those recorded at the beginning of the ultra-
Device calibration was checked routinely and recorded at
each center with the Plexiglas phantom. The device calibra-
tion was maintained by means of a resident program
through a guided calibration procedure. For all devices the
average ultrasound speed in the phantom was 2758 ? 8 m/s.
Characteristics of the study group
The overall database was built up with the contributions
of 22 centers, using 26 individual DBM Sonic devices for
the measurement of a total of 10,450 subjects; of these, 335
(3.2%) measurements were subsequently excluded on ac-
count of inconsistencies, as listed in Table 1. The average
number of measurements per center was 421 ? 308, the
smallest group being represented by the 45 newborns.
The demographics of the population in age decades are
shown in Table 2, where the incidence of subjects with
radiological evidence of atraumatic osteoporotic fractures is
Out of the 10,115 subjects for whom the average AD-SoS
value was available, 7693 (76.1%) also had the graphic
trace recorded. In fact, in the early stages (1993–1994) the
signal data were not regularly stored. Within the graphic
trace group 307 females had a documented osteoporotic
Spine BMD and hip BMD measurements were available
for 1675 and 592 subjects, respectively; all subjects having
hip measurement also had spine measurement. DXA results
were supplied by eight centers; the average number of
measurements per center were 221 ? 206 for spine and
137 ? 101 for hip DXA. Nevertheless, both AD-SoS and
1606 WU¨STER ET AL.
graphic trace information was available for 1549 (92%)
lumbar spine and 549 (93%) hip BMD.
Nevertheless, we could verify that for both QUS and
DXA measurements, there were no statistically significant
differences in the values of adult premenopausal women
among different centers.
In the premenopausal adult population the comparison
with ANOVA test of AD-SoS values among the centers
showed no statistically significant differences (data not
shown). Mean speed of sound in soft tissue for the whole
population was 1565 ? 13 m/s.
The peak value for AD-SoS was found in the group aged
25–30 years, 2119 ? 68 m/s; this peak value virtually
overlaps the one of the device reference curve (2124 ? 70
m/s). The lowest AD-SoS reading of 1594 m/s was observed
in a 74-year-old woman having multiple vertebral fractures
and a soft tissue speed of 1570 m/s.
Figure 2 shows the average AD-SoS trend in the nonfrac-
tured population (9665 subjects). AD-SoS correlation with
age was positive from 3 to 30 years of age (r ? ?0.75).
Between 31 and 40 years of age (premenopause), the cor-
relation coefficient was r ? ?0.16. We then evaluated
women after the age of 50 years and in postmenopause
(because after the age of 50 years 95% of the whole popu-
lation was postmenopausal); among these, the correlation
with age was r ? ?0.58. Furthermore, we calculated the
annual AD-SoS loss in early and late postmenopause. In the
first 5 years after menopause the mean annual AD-SoS loss
is 10.4 ? 1.02 m/s, whereas in late menopause (more than
5 years after menopause) the mean annual AD-SoS loss is
significantly lower (3.86 ? 0.80 m/s; p ? 0.0001).
For 7386 nonfractured subjects graphic traces were avail-
able, three for each subject (digits II, III, and IV) adding up
to a total of over 22,000 graphic traces. We evaluated the
trend versus age of the five parameters characterizing the
graphic trace. Three of these, EN, TF, and UPA show a
trend similar to the AD-SoS, growing from birth to adult-
hood, constant over adulthood, declining after menopause.
Figure 3 shows the trend of EN and TF. On the other side,
Fig. 4 shows that SDy and FWA are stable from childhood
to adulthood and then they decline significantly after meno-
pause, this effect being more evident for SDy compared
with FWA. These findings imply that although young and
aged postmenopausal females may have similar AD-SoS
values, they should differ for SDy and FWA values.
The population included 450 subjects with radiological
evidence of osteoporotic fractures: 414 (92%) vertebral
fractures and 36 (8%) hip fractures, average age 68.8 ? 10
and 75.7 ? 17 years, respectively. The mean AD-SoS value
was 1860 ? 101 m/s for the vertebral fractures (?3.8 ? 1.4
T score) and 1843 ? 97 m/s for the hip fractures (?4.0 ?
1.4 T score). Considering the low number of hip fractures
and the lack of BMD data for these patients, we will focus
most of our analysis on vertebral fracture cases.
We then considered only the subjects over 20 years of
age. By multiple logistic regression analysis, we calculated
the risk of vertebral fracture per SD decrease of AD-SoS,
controlled for age; the OR was 1.71 (CI, 1.58–1.84). Within
the subjects for whom the graphic trace was available, we
compared the whole vertebral fracture group (284 subjects,
71 ? 8.7 years) with a nonfractured age-matched group also
made of 284 subjects (70.9 ? 10 years). Their graphic trace
data have been utilized to select a combination of parame-
ters, which can discriminate fractured subjects.
The optimum logistic multivariate model derived from
this analysis allows us the identification, from the five
parameters considered, of the set of three signal parameters
in which mathematical combination best discriminated the
fractured subjects from controls. This optimum combination
was called Ultrasound Bone Profile Index (UBPI), based on
the following mathematical equation:
UBPI ? ?(?0.0018 ? SDy ? 0.0560 ? FWA
? 1.1467 ? TF ? 3.0300)
UBPI thus describes the probability that the tested subject
belongs to the nonfractured group, derived from the vari-
ables inserted in the equation; then UBPI has been normal-
ized and its values range from 0–1, 1 being attributed to the
highest value obtained.(29)The average values of UBPI and
AD-SoS in the nonfractured group (0.48 ?0.0.16 and
1926 ? 29, respectively) were significantly higher than in
the fractured group: UBPI, 0.35 ? 0.15 ( p ? 0.0001); and
AD-SoS, 1864 ? 98 ( p ? 0.0001).
TABLE 1. MEASUREMENTS EXCLUDED
Incomplete US measure
BMI ? 40 and ?19
Age at menopause ? 30
Age at menopause ? age
TABLE 2. DISTRIBUTION ACCORDING TO AGE GROUPS OF
450 10,115 9665
1607 PHALANGEAL OSTEOSONOGRAMMETRY STUDY
The calculation of the UBPI parameter includes the SDy
and the FWA values that we showed do not show the same
trend versus age observed for AD-SoS. Thus, we should
expect that UBPI contains information that is different from
AD-SoS. As a confirmation of this Table 3 shows that
children and aged women with the same AD-SoS can in-
stead be discriminated by UBPI.
When UBPI was tested over the whole population we
found that among the subjects aged 25–30 years the average
UBPI is 0.83 ? 0.14. Figure 5 shows the changes of UBPI
with aging. UBPI correlation with subjects aged 3–30 years
was r ? 0.13. UBPI declined after menopause and its
correlation with age was r ? ?0.57.
We calculated the UBPI CV using the database that
included reproducibility measurements at different centers
and we found 2.85% CV intraoperator and 2.97% CV
interoperator. When the CV was calculated for AD-SoS in
the same data set we found 0.75% intraoperator and 0.87%
SPE was calculated for AD-SoS and UBPI, using lumbar
spine DXA as a reference technique (SPE, 0.90%) with the
following results: SPE (AD-SoS vs. DXA) ? 1.38%; SPE
(UBPI vs. DXA) ? 0.89%.
The correlation between AD-SoS and UBPI for subjects
over 20 years of age was r ? 0.74.
UBPI could be calculated for 307 fractured subjects;
UBPI T score value among 284 vertebral fractures was
?3.43 ? 1.04 and among 23 hip fractures was ?3.28 ?
We then tested the efficiency of UBPI by logistic regres-
sion using the hip-fractured group (76 ? 15.4 years) and a
group of 74 nonfractured females (75.4 ? 14.3 years),
yielding an OR of 2.11 (CI, 1.02–4.57) and an AUC of
0.69 ? 0.05. In the same group the OR calculated for
AD-SoS was 1.93 (CI, 1.09–3.42) and the AUC was 0.71 ?
nonfractured women. For subjects be-
low 3 years of age data were collected
using the humerus as the site of mea-
AD-SoS trend versus age in
(mean ? 1 SD). These trends are AD-SoS–like. No data on
newborns are shown because it was not possible to analyze
Trends of EN and TF versus age in women
1608 WU¨STER ET AL.
Osteosonogrammetry and densitometry
We considered 1549 subjects for whom lumbar spine
BMD, AD-SoS, and UBPI were available. Among these 549
had hip BMD measured too; Table 4 shows the positive
correlation r values among densitometric and osteosono-
grammetry measurements, all being highly significant ( p ?
Table 5 shows the mean values of AD-SoS and UBPI
according to BMD T score levels at the spine and at the hip,
We selected, within the 1433 nonfractured subjects, an
age-matched subgroup made up of 114 subjects; Table 6
shows that both US and BMD values remain significantly
different between fractured and nonfractured subjects. Our
analysis was limited to lumbar spine BMD data because hip
measurements were too few in this subgroup.
We then calculated the ability to discriminate between
fractured subjects of DXA and QUS in the whole popula-
tion, between young premenopausal women and women
with fracture, and finally in age-matched groups; Table 7
reports the AUC values for each group and the methodol-
To find the AD-SoS T score threshold level the WHO
criteria were applied to the 5203 postmenopausal women
over 50 years of age; we found a T score cut-off level for
AD-SoS of ?3.2 corresponding to 1900 m/s. We then
studied the distribution of 414 vertebral and of 36 hip-
fractured subjects around the T score threshold level. Sixty-
six percent of the vertebral fractures and 75% of the hip
fractures fell below ?3.2 SD. Proceeding in a similar way
for UBPI, a T score cut-off level of ?3.14 was found,
corresponding to a value of 0.38. Again, the distribution of
284 vertebral and 23 hip-fractured subjects was studied;
62% of vertebral fractures and 52% of hip fractures fell
below this threshold. These results compare favorably with
DXA measurement (1675 measurements available) be-
cause, out of 116 subjects with vertebral fractures for whom
DXA measurement was available, 63% had a T score value
below ?2.5 SD.
We then considered the whole adult population (6961
females over 20 years of age) for which both AD-SoS and
UBPI were calculated and that included 284 documented
vertebral fractures. We evaluated the distribution of subjects
below the ?3.2 T score level for AD-SoS and ?3.14 for
UBPI and above the ?1 T score level to identify the
frequency of fractured subjects in each group. Out of 804
subjects with AD-SoS values below ?3.2 T score, 180
(22.4%) were fractured. On the other hand, out of 2546 with
AD-SoS T score values ? ?1 SD, only five (0.2%) were
fractured. UBPI had T score values ? ?3.14 SD in 515
subjects; 169 (32.8%) of these were fractured. Among 3431
subjects with normal UBPI (T score ? ?1) seven (0.2%)
were fractured. Both parameters were below the cut-off
values (T score, ?3.2 for AD-SoS and 3.14 for UBPI) in
456 subjects; 157 (34.4%) were fractured. Among the 2073
subjects, with both AD-SoS and UBPI T score ? ?1 SD,
only one (0.05%) was fractured.
To compare these results with DXA performances, we
used the group of 1549 subjects with lumbar spine BMD;
among the 466 subjects with lumbar spine BMD T score ?
?2.5, 82 (17.5%) were fractured; out of 468 subjects with
BMD T score values ? ?1, six (1.3%) were fractured.
Among 108 subjects that cumulate the contemporary
presence of AD-SoS and spine BMD parameters below their
respective threshold level, the percent of fractures increases
up to 35.3% (Fig. 6). Furthermore, when hip BMD was
considered, out of 68 subjects with a T score below ?2.5
SD, 30 (44%) were fractured; nevertheless, out of 22 sub-
jects with AD-SoS and both BMD values below the thresh-
TABLE 3. ULTRASOUND PARAMETERS IN YOUNG AND
1944 ? 47
0.71 ? 0.15
8 ? 1
1944 ? 87
0.51 ? 0.16
67 ? 6
p ? 0.0001
p ? 0.0001
(mean ? 1 SD). These trends are not AD-Sos–like. No data
on newborns are shown because it was not possible to
analyze US signal.
Trends of FWA and SDy versus age in women
1609PHALANGEAL OSTEOSONOGRAMMETRY STUDY
old, 14 (63.6%) were fractured. When AD-SoS, UBPI, hip,
and lumbar spine BMD were below the threshold level,
68.4% of subjects were fractured. Furthermore, we evalu-
ated the 80 fractured women for whom hip and spine DXA
and finger US data were available. Values below the thresh-
olds were found for hip DXA in 30 (38%), for spine DXA
in 60 (75%), and for AD-SoS in 46 (58%) of women with
fractures. In 75 (94%) of these we found that the test results
were below threshold values in at least one of the three
skeletal sites investigated.
In this study 10,115 phalangeal osteosonogrammetry
measurements performed in European women of the white
race of all ages were pooled for cross-sectional analysis.
This was made possible because the selected test centers
were homogeneous with regard to equipment calibration,
measurement procedures, and operator training. Moreover,
study aims in all centers exclusively addressed the issues of
(i) the precision of the method, (ii) the collection of nor-
mality data, (iii) tests of the discrimination ability regarding
subjects with osteoporotic fractures, and (iv) in some 16%
of the adults included in the population, the comparison
with densitometric methods.
The speed of ultrasound through the distal metaphyseal
portions of the first phalanges of digits II–V was measured
over an age range of 3–109 years and for a small group of
newborn babies and children less than 3 years of age by
measuring the distal humerus. It is still to be seen how this
site compares with finger measurement in older groups.
Nevertheless, the AD-SoS showed very large dynamic vari-
ations over a lifetime, in agreement with previous radio-
grammetry data witnessing the largest range of deviation
from peak adult bone mass for the finger phalanges.(33–35)
Soft tissue ultrasound speed was homogeneous and stable
over a lifetime, thus forming the baseline value for bone
ultrasound measurement. Peak adult AD-SoS values were
recorded in the 25- to 30-year age group (2119 m/s), which
virtually overlaps the age reference value of 2124 m/s
supplied with the device. Considering that there should be
no AD-SoS values lower than the soft tissue readings, the
resulting dynamic range of the phalangeal ultrasound mea-
surements thus is given by the difference between soft tissue
baseline speed and the peak adult velocity plus 2 SD (CI,
95%), that is, 695 m/s.
The access to such a large number of measurements and
particularly to over 20,000 graphic traces made it possible to
investigate, besides the speed parameter AD-SoS, also a
series of parameters making up the ultrasound signal trace.
The study of the graphic trace is justified both by the
empirical observation of the changes occurring to the
graphic trace in osteoporotic patients(36)and, most impor-
tant, by the recent experimental findings showing that
graphic trace changes can be extremely specific and infor-
mative (Fig. 7).(22,26)
associated parameters could be combined to develop the
UBPI. UBPI, conceived as a “fracture-predictive value,” has
shown a good sensitivity and specificity in discriminating
hip-fractured from -nonfractured subjects of the same age.
UBPI is calculated on the results of the analysis of the
graphic trace of 3 fingers, whereas AD-SoS is calculated in
4 fingers. Here, we decided to continue calculating AD-SoS
in this way to allow comparison of our AD-SoS results with
UBPI changes with aging.
TABLE 4. LINEAR CORRELATION BETWEEN AD-SoS, UBPI,
BMD L2–L4, BMD HIP IN THE GROUP OF
549 SUBJECTS (p ? 0.0001)
AD-SoSUBPI BMD L2–L4
1610WU¨STER ET AL.
those present in the literature, because all are based on
We have shown that this new parameter discriminates
between young and adult females having the same AD-SoS
values. The increase of AD-SoS with age (r ? 0.75) before
30 years reflects the increase in bone mineralization; in fact
it has been shown that ultrasound velocity is largely depen-
dent on BMD rather than on bone width.(37)On the other
hand, the independence of UBPI from the age before 30
years (r ? 0.13) cannot be explained by phalanx thickness,
bone marrow distribution (in fact, they change significantly
during that period of life(38)), or by the amount of soft tissue
because it does not influence the UBPI calculation.
After the adult age the natural occurring decrease in
mineral content is associated with changes in structural and
elastic properties of the bone. This explains the high corre-
lation between AD-SoS and UBPI (r ? 0.74) and the similar
correlation level of both parameters to lumbar spine BMD.
Before the adult age the correlation between AD-SoS and
UBPI is poor (r ? 0.46) when low BMD values are not
associated to any deficit in structural or elastic properties of
bone. Based on all of the above considerations, we hypoth-
esize that UBPI may be related mostly to bone tissue char-
acteristics like elasticity and structure rather than density.
Nevertheless, it has been shown in an animal model that the
characteristics of the US graphic trace can discriminate
between osteomalacia and castration-induced osteoporosis,
whereas AD-SoS could not.(12)
UBPI values were found to be reproducible, with a cal-
culated intraoperator precision error of 2.85% in the same
population where AD-SoS precision error was calculated as
Among subjects with radiographically documented frac-
tures AD-SoS was found far below young adult reference
values and was able to discriminate between groups who
fractured and those who did not fracture ( p ? 0.0001, Table
6). Furthermore, for each SD decrease from adult age the
calculated OR was 1.7. When UBPI was tested on hip-
fractured patients we calculated an OR of 2.11 per SD
decrease. Our findings confirm the results of radiographic
absorptiometry showing the sensitivity of the phalanx as a
site predictive of fracture risk.(35)
When we analyzed subjects for whom BMD values were
available, we found that ultrasound (AD-SoS and UBPI)
was able to identify subjects with a BMD T score below
?2.5 and those with a BMD T score above the threshold
value. Ultrasound and densitometric results were moder-
ately but positively correlated.
Within the group with BMD measurements, when frac-
tured and nonfractured subjects were compared, it was seen
that there were no statistically significant differences among
the AUC calculated by ROC analyses for any of the diag-
nostic procedures. Actually, our findings for QUS and DXA
yield similar results to those reported by Greenspan when
comparing young adults and fractured subjects whereas in
this study the performance of both DXA and QUS is slightly
better in age-matched groups.(39)
Finally, using the WHO Study Group criteria to identify
osteoporotic subjects, cut-off levels of ?3.2 T score for
AD-SoS and ?3.14 T score for UBPI were obtained. The
AD-SoS T score threshold translates into a speed of 1900
m/s, which is very close to the cut-off values calculated in
several studies done on much smaller populations.(14,15,17)
Among those subjects with AD-SoS T score below ?3.2
SD, 22% had an osteoporotic fracture, this percentage in-
creased to 35.3% when both AD-SoS and spine BMD T
score values were below the calculated thresholds. When
hip BMD was considered also the percent of fractures cases
increases to 63.6%. These results indicate that having more
than one skeletal site with test results (QUS or BMD) below
threshold increases the probability of being fractured. On
the other hand, measuring different skeletal sites allows the
TABLE 5. MEAN VALUES FOR US PARAMETERS GROUPED ACCORDING TO T SCORE VALUES OF SPINE AND HIP
T score BMD HIP (549)
T-score BMD L2:L4
T ? ?2.5
63.5 ? 7.8
1932 ? 51
0.49 ? 0.16
?1.92 ? 0.87
?2.5 ? T ? ?1
57.7 ? 8.4
1992 ? 84
0.62 ? 0.17
?1.39 ? 0.90
?1 ? T
54.0 ? 8.6
2022 ? 79
0.71 ? 0.18
?0.33 ? 1.02
T ? ?2.5
68.3 ? 8.1
1908 ? 91
0.42 ? 0.13
?3.41 ? 1.30
?2.5 ? T ? ?1
60.0 ? 9.0
1961 ? 109
0.55 ? 0.19
?2.32 ? 1.10
?1 ? T
52.7 ? 8.6
2017 ? 98
0.70 ? 0.22
?1.03 ? 1.30
TABLE 6. AVERAGE VALUES OF US MEASUREMENT AND
LUMBAR SPINE BMD IN AGE-MATCHED GROUPS
T score BMD L2–L4 ?2.08 ? 1.38 ?3.17 ? 1.29 ?0.0001
69.1 ? 7.3
1946 ? 74
0.50 ? 0.12
69.4 ? 7.5
1872 ? 101 ?0.0001
0.38 ? 0.13 ?0.0001
1611 PHALANGEAL OSTEOSONOGRAMMETRY STUDY
identification of a higher number of fractured subjects; 75
out of 80 (94%) women with vertebral fractures had test
results below threshold values in at least one of the three
skeletal sites investigated, finger, spine, or hip.
Overall, the results of this large-scale analysis confirm
that QUS investigations are indeed useful for the study of
bone tissue and confirm the positive clinical experience
previously reported in smaller studies. Threshold levels
have been calculated for ultrasound parameters (AD-SoS
and UBPI) using the criteria developed for DXA; they have
been shown to be valuable; nevertheless, their application in
clinical practice should always be integrated with all other
information, both clinical and instrumental.
The main limitations of the study are (i) it only considers
European white women; (ii) vertebral fractures were as-
sessed at each center but no central review was performed
but, nevertheless, all centers are experienced in osteoporosis
investigation; (iii) the limited number of vertebral fractures
representing 4.5% of the population; (iv) the number of hip
fractures is low and limited investigation on peripheral
fracture has been carried out; (v) the number of DXA
measurements is limited to 16% of the population but,
nevertheless, subgroup analysis showed similar results to
the large total group; (vi) no cross-calibration of DXA
devices was performed; (vii) the lack of information about
the actual absence of osteoporotic fractures in the nonfrac-
when AD-SoS, spine, and hip BMD T score
values are below threshold. *Data referred
to a 549 subject population for which hip
BMD data were available.
Percent of fractured subjects
traces of (A) healthy normal child (8
years of age); (B) adult healthy
woman (35 years of age); (C) post-
menopausal nonfractured woman (67
years of age); (D) postmenopausal os-
teoporotic woman with vertebral frac-
tures (69 years of age).
Examples of US graphic
TABLE 7. AUC FOR QUS AND LUMBAR DXA PARAMETERS FOR SUBJECTS WITH AND WITHOUT FRACTURES
Total populationPremenopausal Age-matched
n nonfractured/n fractured
BMD Hip (549)
0.823 ? 0.020
0.867 ? 0.019
0.798 ? 0.022
0.779 ? 0.027
0.954 ? 0.013
0.983 ? 0.007
0.932 ? 0.016
0.721 ? 0.033
0.742 ? 0.032
0.721 ? 0.032
1612 WU¨STER ET AL.
tured group, in fact the fracture rate does not follow the
expected age-related increase. This, especially when age-
matched groups are compared, will have a negative impact
on the performances of both QUS and DXA; nevertheless,
it actually results in a conservative evaluation of the effi-
ciency of US technology.
Our data indicate that the analysis of multiple osteosono-
grammetry parameters, pertaining to the ultrasound signal
modifications, will contribute to the improvement of the
efficacy of QUS procedures in bone assessment, beyond the
established value of speed of sound and ultrasound attenu-
ation. The further study of ultrasound signal features using
a signal processing approach successfully used for many
years in echography may also in the near future provide new
ways of looking at diverse disorders affecting bone tissue
We thank Richard Eastell and Bridget Ingle for their
determinant contribution to the redaction of this paper.
1. Langton CM, Palmer SD, Porter RW 1984 The measurement
of broadband ultrasonic attenuation in cancellous bone. Eng
2. Glu ¨er CC for the International Quantitative Ultrasound Con-
sensus Group 1997 Quantitative ultrasound technique for the
assessment of osteoporosis: Expert agreement on current sta-
tus. J Bone Miner Res 12:1280–1288.
3. Hans D, Dargent-Molina P, Schott AM, Sebert JL, Cormier C,
Kotek PO, Delimas PD, Pouilles JM, Breant G, Meunier PJ
1996 Osteosonographic heel measurements to predict hip frac-
ture in elderly women: The EPIDOS prospective study. Lancet
4. Bauer DC, Glu ¨er CC, Cauley JA, Vogt TM, Ensrud KE,
Genant HK, Black DM 1997 Bone ultrasound predicts frac-
tures strongly and independently of densitometry in older
women: A prospective study. Arch Intern Med 157:629–634.
5. National Osteoporosis Society 1998 The use of quantitative
ultrasound in the management of osteoporosis in primary or
secondary care. Position statement of June 30, 1998.
6. Hans D, Wu C, Njeh CF, Zhao S, Augat P, Newitt D, Link T,
Lu Y, Majumdar S, Genant HK 1999 Ultrasound velocity of
trabecular bones reflects mainly bone density and elasticity.
Calcif Tissue Int 64:18–23.
7. Njeh CF, Kuo CW, Langton CM, Athrah HI, Boivin CM 1997
Prediction of human femoral bone strength using ultrasound
velocity and BMD: An in vitro study. Osteoporos Int 7:471–
8. Tylovsky FA, Frase PF, Williams T, Carbone LD 1998 Adi-
posity and ethnic differences in ultrasound measurement of the
calcaneus. Bone 23(Suppl):5T496 (abstract).
9. Barkmann R, Glu ¨er CC 1998 Continuous amplitude dependent
speed of sound: A new parameter improving the precision of
phalanx ultrasound measurements. Bone 23(Suppl):5T496
10. Katz JL, Meunier A 1987 The elastic anisotropy of bone.
J Biomech 20:1063–1070.
11. Vernazza GL, Serpico SB, Dellepiane SG 1987 A knowledge
based system for biomedical image processing and recogni-
tion. IEEE Trans on Circuits and Systems CAS 34:1399–
12. Luisetto G, Camozzi V, De Terlizzi F, Moschini G, Ballanti P
1999 Use of ultrasonography in the diagnosis of osteomalacia:
preliminary results on experimental osteomalacia in the rat. J
Ultrasound Med 18:225–229.
13. Aguado F, Revilla M, Hernandez ER, Villa LF, Rico H 1997
Ultrasound bone velocity on proximal phalanges in premeno-
pausal, perimenopausal and postmenopausal healthy women.
Invest Radiol 32:66–70.
14. Sili Scavalli A, Marini M, Spadaro A, Messineo D, Cremona
A, Sensi F, Riccieri V, Taccari E 1997 Ultrasound transmis-
sion velocity of the proximal phalanges of the non dominant
hand in the study of osteoporosis. Clin Rheum 16:396–403.
15. Reginster JY, Dethor M, Pirenne H, Dewe W, Albert A 1998
Reproducibility and diagnostic sensitivity of ultrasonometry of
the phalanges to assess osteoporosis. Int J Gynecol Obstet
16. Mele R, Masci G, Ventura V, de Aloysio D, Bicocchi M,
Cadossi R 1997 Three year longitudinal study with quantita-
tive ultrasound at the hand phalanx in a female population.
Osteoporos Int 7:550–557.
17. Ventura V, Mauloni M, Mura M, Paltrinieri F, de Aloysio D
1996 Ultrasound velocity changes at the proximal phalanges of
the hand in pre-, peri-, and postmenopausal women. Osteopo-
ros Int 6:368–375.
18. Alenfeld FE, Wu ¨ster C, Funk C, Pereira-Lima JFS, Fritz T,
Meeder PJ, Ziegler R 1998 Ultrasound measurement at the
proximal phalanges in healthy women and patients with hip
fractures. Osteoporos Int 8:393–398.
19. Soballa T, Wu ¨ster C, Schlegel J, Cadossi R, Isani R, Battista
S, Heilmann P, Ziegler R 1998 Ultrasound transmission speed
and ultrasound bone profile score (UBPS) of the phalanges in
normal women and women with osteoporosis. Horm Metab
20. Blanckaert F, Cortet B, Coquerelle P, Flipo RM, Duquesnoy
B, Delcambre B 1999 Ultrasound velocity through the phalan-
ges in normal and osteoporotic patients. Calcif Tissue Int
21. Wu ¨ster C, Heilmann P, Pereira-Lima J, Schlegel J, Ansta ¨tt K,
Soballa T 1998 Quantitative Ultrasonomatry (QUS) for the
evaluation of osteoporosis risk: Reference data for various
measurement sites, limitations and application possibilities.
Exp Clin Endocrinol Diabetes 106:277–88.
22. Joly J, Westhovens R, Borghs H, Peeters H, Tiny J, Nijs J,
Dequeker J 1999 Reference curve and diagnostic sensitivity
for a new ultrasound device for the phalanges, the DBM Sonic
1200, in Belgian females. Osteoporos Int 9:284–289.
23. Looker AC, Johnston CCjr, Wahmenr HW, Dunn WL, Calvo
MS, Harris TB, Heyse SP, Lindsay RL 1995 Prevalence of low
femoral bone density in older US women from NHANES III.
J Bone Miner Res 10:796–802.
24. Benmalek A, Sabatier J-P 1998 Comparison and cross-
calibration of DXA systems: ODX-240 and Sophos L-XRA
versus Hologic QDR-4500, for spinal bone mineral measure-
ment. Translation of a reference database. Osteoporos Int
25. Cadossi R, Cane ` V 1996 Pathways of transmission of ultra-
sound energy through the distal metaphysis of the second
phalanx of pigs: An in vitro study. Osteoporos Int 6:196–206.
26. Cadossi R, de Terlizzi F, Battista S 1998 Density and elasticity
influence in different ways US propagation: An in vitro study.
Bone 23(Suppl):5F479 (abstract).
27. Glu ¨er C-C, Blake G, Lu Y, Blunt BA, Jergas M, Genant HK
1995 Accurate assessment of precision errors: How to measure
the reproducibility of bone densitometry techniques. Osteopo-
ros Int 5:262–270.
28. Armitage P, Berry G 1994 Statistical methods in medical
research. Blackwell Scientific Publication, Oxford, U.K.
29. Albery A 1982 On the use and computation of likelihood ratios
in clinical chemistry. Clin Chem 5:1113–1119.
1613PHALANGEAL OSTEOSONOGRAMMETRY STUDY
30. Glu ¨er C-C 1999 Monitoring skeletal changes by radiological
techniques. J Bone Miner Res 14:1952–1962.
31. World Health Organization (WHO) 1994 Assessment of frac-
ture risk and its application to screening for postmenopausal
osteoporosis. WHO Technical Report. Series 843, WHO
32. Kanis JA, Melton LJ, Christiansen C, Johnston CC, Khaltaev
N 1994 The diagnosis of osteoporosis. J Bone Miner Res
33. Kleerekoper M, Nelson DA, Flynn MJ, Pawluszka AS, Jacob-
sen G, Peterson EL 1994 Comparison of radiologic absorpti-
ometry with dual energy X-ray absorptiometry and quantita-
tive computed tomography in normal older white and black
women. J Bone Miner Res 9:1745–1750.
34. Wasnich RD 1998 Perspective on fracture risk and phalangeal
bone mineral density. J Clin Densitometry 1:259–268.
35. Mussolino ME, Looker AC, Madans JH, Edelstein D, Walker
RE, Lydick E, Epstein RS, Yates J 1997 Phalangeal bone
density and hip fracture risk. Arch Intern Med 157:433–438.
36. Hans D, Njeh CF, Genant HK, Meunier P-J 1998 Quantitative
ultrasound in bone status assessment. Rev Rhum Engl Ed
37. Sakata S, Barkmann R, Lochmuller E-M, Glu ¨er C-C 1999
Associations between density and quantitative ultrasound pa-
rameters in finger phalanges in vitro. Calcif Tissue Int
64(Suppl 1):P210 (abstract).
38. Poznanski HK 1994 The Hand in Radiologic Diagnosis. W.B.
Saunders Company, Philadelphia, PA, U.S.A.
39. Greenspan SL, Bouxsein ML, Melton ME, Kolodny AH, Clair
JH, Delucca PT, Stek MJr, Faulkner KG, Orwoll ES 1997
Precision and discriminatory ability of calcaneal bone assess-
ment technologies. J Bone Miner Res 12:1303–1311.
Address reprint requests to:
Prof. Dr. med. Christian Wu ¨ster
Received in original form August 11, 1999; in revised form Jan-
uary 31, 2000; accepted March 15, 2000.
1614WU¨STER ET AL.