Phenotype and Genotype of Osteoporosis

Phenotype and Genotype of Osteoporosis Vicente Gilsanz

A top priority in osteoporosis research is the identification of the structural basis and the genetic factors that contribute to variations in the risk for fragility fractures. This review summarizes current knowledge regarding the genetic determination of fragility fractures and bone mass measurements, and the complex phenotypes and genotypes of osteoporosis.

et al. 1962). Most studies have shown a lower incidence of fractures at all skeletal sites in blacks when compared with whites (Cummings et al. 1985). More recent evidence that fractures are determined genetically is based on the association of a polymorphism of the collagen type I a 1 (COLIA1) gene (which encodes the collagen type I peptide chain) with osteoporotic fractures in British and Dutch women (Grant et al. 1996, Uitterlinden et al. 1998). These results have yet to be corroborated by other investigators and in other populations. •

Osteoporosis, a disease characterized by skeletal fractures, is a major cause of morbidity and mortality in the elderly. The fractures associated with osteoporosis can occur without significant trauma, may involve virtually any bone and become exponentially more frequent with increasing age. While these fractures are rare in the young, epidemiological studies have estimated that 50% of women and 25% of men aged 60 years will suffer from at least one fracture during the remainder of their lifetime (Nguyen et al. 1993). As life expectancy increases in years to come, fragility fractures will become even more common unless we can develop strategies that counteract the alarming rise in the prevalence of osteoporosis. Because it is now clear that this disease, which is largely irreversible once it has manifested itself, has its antecedents during childhood (Bonjour et al. 1991), a major goal for the next decade is to design effective early interventions for the prevention of osteoporosis. However, only when the phenotype(s) and/or the gene(s) for this condition are defined clearly will we be in a position to identify those at high risk for osteoporosis before fractures occur.

V. Gilsanz is at the Children’s Hospital Los Angeles, Radiology Department, M.S. 81, 4650 Sunset Boulevard, Los Angeles, CA 90027, USA.

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•

Genetic Determination of Fractures

Genetic factors contribute to the variations in the risk for osteoporotic fractures among the elderly. However, we know little of the degree to which they do so, the specific genes, how they confer susceptibility or resistance to fractures, or the ways in which they interact with environmental factors. Evidence for genetic control of bone mass is based on our knowledge that a family history, female gender, northern European heritage and, more recently, unfavorable polymorphisms of certain genes are major risk factors for fractures (Cummings et al. 1995). According to data from family studies, a history of hip fractures in a woman’s mother, sister or maternal grandmother doubles her risk for osteoporotic fractures (Cummings et al. 1995, Seeley et al. 1996, Torgerson et al. 1996). Regardless of race or country of origin, the majority of studies indicate a higher fracture rate in women than in men. In the USA, Caucasian women have about a twofold higher incidence of hip fractures and a four to eightfold higher incidence of vertebral fractures than Caucasian men (Cummings et al. 1985). Many studies have also compared fracture rates between Americans of European descent with those of African descent, ever since it was noted ~40 years ago that fractures of the hip were seen infrequently in African Americans (Gyepes

Heritability of Bone Mass

For many years, osteoporosis was recognized as the occurrence of fractures owing to low bone mass in the elderly (Nelson and Kleerekoper 1997). In the past few decades, a variety of techniques have been developed that accurately measure bone mass at different skeletal sites. This has enabled the characterization of the disease to change and osteoporosis is now defined as a disease of low bone mass and increased fracture risk (Nelson and Kleerekoper 1997). Currently, the most commonly used quantitative radiological method to assess bone mass is dual energy X-ray absorptiometry (DXA). Heredity is an important determinant of bone mass, as measured with absorptiometric techniques. Convergent data from mother–daughter pairs, sib pairs and twin studies have estimated the heritability of bone mass to account for 60–80% of its variance (Christian et al. 1989, Seeman et al. 1989, Pocock et al. 1991). The magnitude of the genetic effect varies with age and between skeletal sites; it is higher in the young than in the elderly and in the spine than in the extremities (Slemenda et al. 1991). Further support for this genetic influence comes from studies showing reduced bone mass in daughters of osteoporotic women when compared with controls (Seeman et al. 1989), in men and women with first-degree relatives who have osteoporosis (Evans et al. 1988) and in perimenopausal women who have a family history of hip

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fracture (Torgerson et al. 1995). In addition, recent investigations have reported a link between several ‘candidate’ genes and bone mass (Sainz et al. 1997, Uitterlinden et al. 1998). •

Phenotype

Progress in analyzing the genetic factors of osteoporosis has been modest owing to our incomplete knowledge of the phenotype(s) of this disease, and advancement will remain slow until the structural basis for bone fragility can be defined unambiguously. Bone mass measurements using DXA are based on a two-dimensional projection of a three-dimensional structure, and are a function of three skeletal parameters: the size of the bone being examined, the volume of the bone and its mineral density. While these measurements are used commonly to diagnose osteoporosis, to predict fracture risk and to assess response to therapy, they should not be used as the endpoint in the study of the pathophysiology of fragility fractures (Hangartner 1990, Carter et al. 1992). A deeper understanding of the structural parameters that account for bone fragility and the diversity in bone strength among women, sexes and races is needed to identify the phenotype(s) for osteoporosis. The key questions are: (1) why do many women with low bone mass not experience fractures (Gallagher et al. 1985, Melton et al. 1989), (2) which structural variables confer greater resistance to fractures in men, and (3) why are people of European descent more

susceptible to fractures than those of African descent? Recent advances in our knowledge have come from the use of techniques that allow threedimensional comparative studies to identify the structural basis for the skeletal differences between subjects who are susceptible to fractures and those who are not. Studies in Women As bone mass and bone strength decline with age, the skeleton becomes unable to withstand the loads associated with normal daily activities. Consequently, every year in the USA ~500 000 and ~150 000 elderly women are newly diagnosed with vertebral and hip fractures, respectively (Cummings et al. 1985, Melton et al. 1989). Of the two components of bone mass, bone density and bone size, the prevailing view has been that the decline in bone density is the major determinant of fragility fractures. However, many people with low bone density values do not experience fractures and there is substantial overlap in values between those with and without radiographical evidence of fractures (Gallagher et al. 1985, Melton et al. 1989). This inability to predict accurately the risk for fractures based on bone density values alone is true for both three-dimensional and projection techniques. On average, however, the predictive power of computed tomography (CT) measurements of the volumetric density of cancellous bone for vertebral fractures is superior to that of areal spinal density measurements

by DXA (Pacifici et al. 1990, Ross et al. 1993, Guglielmi et al. 1994, LavalJeantet et al. 1995, Yu et al. 1995). In an attempt to understand why some women with low bone density do not have fractures, other properties of bone that contribute to its strength are being considered in the pathogenesis of osteoporotic fractures. Using CT, in vitro studies have indicated that the compressive strength of the vertebra is determined not only by the density of cancellous bone, but also by its crosssectional area (Biggemann et al. 1988, Brinckmann et al. 1989) and more recent in vivo studies have shown that vertebral size is a major determinant of fractures (Gilsanz et al. 1994a and 1995). In a case-control study of matched pairs of elderly women with reduced bone density, whose main difference was absence or presence of vertebral fractures, the cross-sectional areas of the unfractured vertebrae were 8% smaller in the women with fractures (Table 1) (Gilsanz et al. 1995). These findings indicate that, as bone density declines with age and the stress within the spine increases, a small vertebral cross-sectional area imparts an added mechanical disadvantage that escalates the risk for fractures. Thus, the subphenotypes for vertebral fractures in elderly women are both low bone density and small cross-sectional area. Unfortunately, the rate of progress in our understanding of the pathogenesis of hip fractures has been more modest. Our knowledge of the phenotype

Table 1. Measurements of the vertebrae in elderly women with and without fractures Cancellous bone density (mg cm3) Level T12 (n = 12) L1 (n = 16) L2 (n = 26) L3 (n = 23) L4 (n = 27) All (n = 104)

Cross-sectional area (cm2)

Vertebral height (cm)

Fx (–)

Fx (+)

p value

Fx (–)

Fx (+)

p value

Fx (–)

Fx (+)

p value

129 ± 26 109 ± 34 97 ± 41 88 ± 34 85 ± 44 99 ± 39

129 ± 27 119 ± 51 99 ± 49 85 ± 39 82 ± 48 99 ± 46

NS NS NS NS NS NS

2.3 ± 0.1 2.4 ± 0.2 2.5 ± 0.2 2.6 ± 0.2 2.6 ± 0.2 2.5 ± 0.4

2.3 ± 0.2 2.4 ± 0.1 2.5 ± 0.2 2.5 ± 0.2 2.5 ± 0.2 2.4 ± 0.4

NS NS NS NS NS NS

9.2 ± 1.1 9.8 ± 0.9 10.0 ± 1.2 11.0 ± 1.2 11.7 ± 1.1 10.5 ± 1.4

8.4 ± 1.4 8.7 ± 1.1 9.3 ± 1.4 10.4 ± 1.4 10.7 ± 1.2 9.7 ± 1.5

0.08 0.007 0.042 0.17 0.005 0.0001

All, the mean for all vertebrae; Fx, fracture; L1, first lumbar vertebrae; L2, second lumbar vertebrae; L3, third lumbar vertebrae; L4, fourth lumbar vertebrae; T12, twelfth thoracic vertebrae; NS, not significant. Adapted from Gilsanz et al. (1995). Values are means ± SD.

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Vertebral cross-sectional area (cm2)

12 10 8 6 4 2 0

0

2

4

6

8

10 12 14 16 18 20

Age (years)

Figure 1. Cross-sectional area of the lumbar vertebrae in boys (closed circles) and girls (open circles). Values are means ±SD. Adapted from Gilsanz et al. (1988 and 1997).

of these fractures in women is limited to studies using projection techniques showing low bone mass values in the proximal femur, and both a wider femoral neck and a longer hip axis length (the distance from the greater trochanter to the inner pelvic brim) (Faulkner et al. 1993, Boonen et al. 1995). The exact role that these femoral dimensions play in the pathogenesis of hip fractures needs to be confirmed and further investigations using techniques that allow for a three-dimensional analysis of bone are required. Gender Differences Bone mass is greater and the incidence of fractures is lower in men than in women. The difference in bone mass has been documented by means of neutron activation analysis, measurement of the calcium content of selected regions of the skeleton and the techniques of radiogrammetry and absorptiometry (Arnold et al. 1966, Trotter and Peterson 1970, Garn et al. 1972, Specker et al. 1987, DePriester et al. 1991). Challenging the widely held view that gender differences in bone mass were a result of differences in bone density, recent evidence indicates that neither cancellous nor cortical bone density differs between men and women (Mosekilde and Mosekilde 1990, Gilsanz et al. 1994a). While the apparent density of cancellous bone

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increases during puberty and declines with age, the true density of cortical bone remains constant throughout life, and neither is influenced by gender. Instead, gender differences in bone mass are a result of differences in bone size (Gilsanz et al. 1994a and b). Observations using CT indicate that, throughout life, females have a smaller vertebral cross-sectional area when compared with males, even after accounting for differences in body size. On average, the cross-sectional area of the vertebral bodies is 11% smaller in prepubertal girls than in prepubertal boys matched for age, height and weight (Gilsanz et al. 1994b and 1997). This disparity increases with growth and is greatest at skeletal maturity, when the cross-sectional dimensions of the vertebrae are about 25% smaller in women than in men, even after taking into consideration differences in body size (Fig. 1) (Gilsanz et al. 1994a). Thus, the phenotypic basis for the four- to eightfold higher incidence of vertebral fractures in women compared with men (Cummings et al. 1985) might lie in the smaller size of the female vertebra. In contrast, the cross-sectional dimensions of the femur do not differ between males and females matched for age, height and weight (Gilsanz et al. 1997). The cross-sectional and cortical bone areas at the midshaft of the femur are related primarily to body weight, regardless of gender, a notion consistent with analytical models proposing that long bone cross-sectional growth is strongly driven by mechanical loads (van der Meulen et al. 1993, Carter et al. 1996). At present, the reasons for the reported gender differences in the incidence of hip fractures are unknown. Racial Differences Race has a significant and differential effect on the bones in the axial and appendicular skeletons (Gilsanz et al. in press). In the axial skeleton, the density of cancellous bone in the vertebral bodies is greater in black than in white persons, regardless of gender. This difference becomes apparent during the late stages of puberty and persists throughout life. Before puberty, cancellous

bone density is similar in black and white children, and during puberty it increases in all adolescents. The magnitude of the increase from prepubertal to postpubertal values is, however, substantially greater in black than in white subjects (34% vs 11%, respectively) (Fig. 2A) (Gilsanz et al. in press). Histomorphometric data indicate that the higher cancellous bone density in blacks is due to a greater trabecular thickness and that there are no racial differences in the number of trabeculae or their degree of mineralization (Han et al. 1997). In contrast to the findings in vertebral bone density, the crosssectional areas of the vertebral bodies do not differ between black and white subjects (Gilsanz et al. in press). Thus, theoretically, the structural basis for the lower vertebral bone strength and the greater incidence of fractures in the axial skeleton of white subjects lies in their lower cancellous bone density. In the appendicular skeleton, values for cortical bone density are not influenced by race (Fig. 2B) (Gilsanz et al. in press). Measurements of cortical bone density reflecting the true density of bone, are remarkably similar in all populations and remain constant throughout life. In the femur, both the area of cortical bone and the crosssectional area correlate strongly with age and body mass (Gilsanz et al. in press). While race has no effect on the cortical bone area, it has a significant influence on the cross-sectional area of the femur, which, at skeletal maturity, is 7% and 11% greater in black than in white subjects, respectively (Gilsanz et al. in press). As the same amount of cortical bone placed further from the center of the bone results in greater bone strength, the skeletal advantage for blacks in the appendicular skeleton is probably the consequence of the greater cross-sectional size of the bones (van der Meulen et al. 1993). Using projection techniques, some investigators have also suggested that the greater resistance to hip fractures in black subjects might result from a wider and shorter femoral neck (Cummings et al. 1994, Mikhail et al. 1996), while others found no such racial differences (Nelson et al. 1995). TEM Vol. 9, No. 5, 1998

B 400

2500 Cortical bone density (mg cm–3)

Cancellous bone density (mg cm–3)

A

350

300

250

2000 1500 1000 500

0

200 I

II

III

IV

V

Tanner stage

6

8

10

12

14

16

18

20

Age

Figure 2. (A) Vertebral cancellous bone density in black (closed circles) and white (open squares) children at each stage of sexual development. Values are means ±SD. Adapted from Gilsanz et al. (1991 and 1998). The density of cancellous bone is defined as the mean value of the computed tomography (CT) unit of measurement (mg cm –3) at the midportion of the first three lumbar vertebral bodies. Because of the relatively small size of the trabeculae when compared with the pixel, CT values for apparent cancellous bone density reflect not only the amount of mineralized bone and osteoid, but also the amount of marrow per pixel (Genant et al. 1996). These measurements are analogous to in vitro determinations of the volumetric density of trabecular bone, which are obtained by washing the marrow from the pores of a specimen of cancellous bone, weighing it, and dividing the weight by the volume of the specimen, including the pores (Dyson et al. 1970). (B) Femoral cortical bone density in 80 black (closed circles) and 80 white (open circles) children from seven to 20 years of age. The density of cortical bone is defined as the amount of bone per pixel (mg cm–3) at the midshaft of the femur. Because of the thickness and the relative lack of porosity of cortical bone in the femur, CT values reflect the material or true density of the bone (the amount of collagen and mineral in a given volume of bone) (Hangartner and Gilsanz 1996). These measurements are analogous to in vitro determinations of the intrinsic mineral density of bone, which are expressed commonly as the ash weight per unit volume of bone (Gong et al. 1964). Adapted from Gilsanz et al. (1998).

•

Genotype

Two approaches are usually used to determine the genetic contribution to complex diseases: linkage and association studies. Linkage studies search for any genomic region contributing a relatively large variation in quantitative traits by using dense genetic markers covering the whole human genome (Gong et al. 1996, Johnson et al. 1997). These studies are expensive, time consuming and require sophisticated technology. Moreover, our previous limited understanding of the complex phenotype of osteoporosis made linkage studies notoriously difficult to perform. Studies using fractures as the endpoint require a large number of elderly pairs of twins or siblings, while those using DXA bone mass values as the surrogate for the phenotype are prone to error, owing to the large number of structural variables that these measurements reflect. As our knowledge of phenotypes increases and we are able to identify TEM Vol. 9, No. 5, 1998

this disease unambiguously before it becomes clinically manifest, linkage studies searching for the genotypes of osteoporosis will become more feasible. Association studies examine specific genomic regions at or near candidate genes and, in osteoporosis research, are facilitated by our knowledge of the factors that regulate bone turnover and the proteins that make up normal bone matrix (Morrison et al. 1994, Cooper and Umbach 1996, Ralston 1997). Given the wide range of factors involved in bone metabolism, there is a seemingly unlimited supply of candidate genes for osteoporosis, although relatively few have been studied thus far. The first candidate gene to be identified was the vitamin D receptor (VDR) gene (Morrison et al. 1994). Claims that the VDR gene accounted for 80% of the variance in bone mass were exaggerated and re-analysis of the data indicates a much weaker association (Cooper and Umbach 1996,

Nguyen et al. 1996). The debate sparked from these reports makes it evident that progress analyzing the complex genotype of osteoporosis will be more difficult than some had envisaged. Other candidate gene studies have also found significant associations between bone mass and polymorphisms in the estrogen receptor gene, the interleukin-6 gene, the transforming growth factor b gene, and the Sp1 binding site of the COLIA1 gene (Grant et al. 1996, Uitterlinden et al. 1998). Most important has been the association of this last polymorphism with osteoporotic fractures in the spine of women (Grant et al. 1996, Uitterlinden et al. 1998). The obvious application of genetic studies to osteoporosis is the discovery of genetic markers that consistently predict osteoporotic fractures and allow the identification of subjects at risk (Dawson-Hughes et al. 1995, Howard et al. 1995). Understanding the roles played by genetic factors might also facilitate the prediction of the response to treatment. For example, the response of bone mass to dietary supplementation with vitamin D and calcium is partly dependent on VDR polymorphisms (Graafmans et al. 1997), and other genes might aid in establishing who would benefit from treatments, such as hormone replacement therapy, bisphosphonates or even exercise. Whether osteoporosis is determined by a few genes with a strong effect or by multiple genes with small additive effects is unknown. Nevertheless, it is anticipated that future studies will show that this disease results, in part, from inherited variations in genes that are involved in the regulation of the two components of bone mass: bone size and bone density. It is also foreseen that any gene linked to fractures in the elderly will be found to be associated with low bone density and/or small bones in children, as the risk of osteoporosis is greatly determined by peak bone mass. Moreover, this association is likely to be present even in early childhood because bone mass, bone density and bone size measurements can be tracked from childhood to early adulthood, and do not change percentiles during growth (Ferrari et al. 187

A P=0.03

Cancellous bone density (mg cm–3)

P=0.01 250

230

210 aa

Aa

AA bb Genotype

Bb

BB

B Cortical bone density (mg cm–3)

P=0.008

P=0.04

1980

1940

1900 aa

Aa

AA bb Genotype

Bb

BB

Figure 3. (A) Vertebral cancellous bone density and (B) femoral cortical bone density in relation to the VDR gene in 100 prepubertal girls. Values are means ±SE. Adapted from Sainz et al. (1997).

1998; V. Gilsanz, unpublished data). Indeed, recent studies in children indicate that the VDR and COLIA1 genes, which have been associated with low bone mass and/or fractures in the elderly (Morrison et al. 1994, Grant et al. 1996), are also related to bone density in prepubertal girls (Fig. 3) (Sainz et al. 1997, Van Tornout et al. 1997). In addition, it is reasonable to suspect that because sex hormones and growth hormone have decisive effects on bone accumulation, deciphering the cellular mechanisms that underlie this process may provide the instruments for the genetic control of the amount of bone that is gained during growth (Parfitt 1997). Thus, the search for the relevant genes should be approached from the standpoint of the developmental biology of the skeleton. •

Conclusion

The main areas of progress in osteoporosis research during the last five years have been: (1) the general recognition

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that this condition (which is the cause of so much pain in the elderly) has its roots in childhood; (2) the identification of the structural basis accounting for much of the variations in bone strength among humans; and (3) insight into the complex genotypes of this disease. Progress in elucidating the basis of gender and racial differences has been considerably greater for the axial skeleton than for the appendicular skeleton. Vertebral fractures are probably more common in women than in men because women have smaller vertebrae, and they are probably more common in white persons than in black persons because whites have lower cancellous bone density. Although more work is needed, it is tempting to think that the phenotype(s) will soon be completely delineated and that the search for the complex genotype of osteoporosis will be our challenge for the next millenium. Such knowledge will provide a more rational way to diagnose, prevent and treat this disease.

axis length consistent with heterogeneity in the pathogenesis of osteoporotic fractures. J Bone Miner Res 10:1908–1912. Brinckmann P, Biggemann M, Hilweg D: 1989. Prediction of the compressive strength of human lumbar vertebrae. Spine 6:606–610. Carter DR, Bouxsein ML, Marcus R: 1992. New approaches for interpreting projected bone densitometry data. J Bone Miner Res 7:137–145. Carter DR, van der Meulen MCH, Beaupre GS: 1996. Skeletal development: mechanical consequences of growth, aging and disease. In Marcus R, Feldman D, Kelsey J, eds. Osteoporosis. San Diego, Academic Press, pp 333–350. Christian JC, Yu PL, Slemenda CW, Johnston CC: 1989. Heritability of bone mass: a longitudinal study in ageing male twins. Am J Hum Genet 44:429–433. Cooper GS, Umbach DM: 1996. Are vitamin D receptor polymorphisms associated with bone mineral density? A meta-analysis. J Bone Miner Res 11:1841–1849. Cummings SR, Kelsey JL, Nevitt NC, O’Dowd KJ: 1985. Epidemiology of osteoporosis and osteoporotic fractures. Epidemiol Rev 7: 178–208.

• Acknowledgements The author thanks Drs A. Michael Parfitt and Ego Seeman for their insightful criticisms and Ms Cara L. Beck for her technical assistance on this manuscript. The author’s work was supported in part by a grant (R01AR4-1853-01A1) from the National Institute of Arthritis and Musculoskeletal and Skin Diseases and a grant (1RO1 LM06270-01) from the National Library of Medicine.

Cummings SR, Cauley JA, Palermo L, et al.: 1994. Racial differences in hip axis lengths might explain racial differences in rates of hip fracture. Osteoporosis Int 4: 226–229.

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Recent Advances in the Management of Adrenal Incidentalomas Michael L. Adler and Richard J. Robbins

Modern imaging techniques have made adrenal incidentaloma a relatively common diagnostic problem. When an incidental adrenal mass is found, the clinician must try to determine its etiology and functionality, and the likelihood of malignancy. This task is complicated further in patients with a history of extra-adrenal malignancy. In this article, we present a review of the literature and propose a diagnostic algorithm for management of adrenal incidentalomas. Computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound scans are common radiological procedures. Studies show that 0.4–4.4% of abdominal CT scans performed for other indications will incidentally identify an adrenal mass (Kloos et al. 1995). The discovery of adrenal ‘incidentalomas’ is likely to increase as imaging technology is able to resolve smaller masses, as the prevalence of these masses on autopsy is 1.4–8.9% (Kloos et al. 1995).

The adrenal incidentaloma was an uncommon problem before the modern radiological era, as intravenous pyelograms and abdominal radiographs were unable to detect most adrenal masses. With the increasing use of CT, MRI and ultrasound, the clinician is faced with a difficult set of questions when an incidental adrenal mass is detected. Based on the cost-effective use of radiological and endocrine testing, decisions need to be made regarding the likelihood of

M.L. Adler is at the Memorial Sloan-Kettering Cancer Center and The New York HospitalCornell University Medical Center, 1275 York Ave, Box 296, New York, NY 10021, USA; and R.J. Robbins is at Cornell University Medical College, Endocrinology Service, Memorial SloanKettering Cancer Center, 1275 York Ave, Box 296, New York, NY 10021, USA.

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malignancy and/or hormone production by the mass, which will determine its management. A differential diagnosis of adrenal masses based on findings from several studies is shown in Table 1 (Osella et al. 1994, KasperlikZaluska et al. 1997). •

Radiological Evaluation

The initial step in the evaluation of an adrenal incidentaloma is to complete a thorough radiological evaluation. Imaging studies can help differentiate benign processes from malignant ones. Unfortunately, most CT studies are performed with intravenous contrast, preventing useful Houndsfield (density) measurement, which is essential to distinguish most benign processes from malignant ones. This usually requires the patient to have followup imaging at a later time, most commonly with an unenhanced (noncontrast) CT. Features of a benign mass on CT include: lack of suspicious adenopathy, smooth and well-defined borders, a diameter under 5 cm and Houndsfield attenuation (H) of 10 units or less (Korobkin et al. 1996b). Features of a malignant mass on CT include: adenopathy, irregular borders, size greater than 5 cm and Houndsfield attenuation of 30 units or greater (Korobkin et al. 1996b). An attenuation of 10 H or less, with a uniform distribution throughout the mass on unenhanced CT, represents an adrenal adenoma in virtually all cases. A recent review of the literature by Korobkin et al. (1996a) found that a cutoff of 10 H or less provides a sensitivity of 73% and a specificity of 96% for adrenal adenomas. In some cases, a definitive etiology of the mass can be determined by CT characteristics alone. An example is the adrenal myelolipoma, which is a rare tumor composed of fat and marrow elements, with discrete areas of low attenuation (Korobkin et al. 1996b). If the CT findings are inconclusive, repeat imaging should be performed six months later to evaluate change in the size of the mass (Bernadino 1988). A significant change in adrenal mass by six months is suspicious of a malignant process (Bernadino 1988).

© 1998, Elsevier Science Ltd, 1043-2760/98/$19.00. PII: S1043-2760(98)00040-X

TEM Vol. 9, No. 5, 1998