Growth of uterine leiomyomata among
premenopausal black and white women
Shyamal D. Peddadaa, Shannon K. Laughlinb, Kelly Minera,1, Jean-Philippe Guyonc, Karen Hanekec,2,
Heather L. Vahdatc,3, Richard C. Semelkad, Ania Kowalike,4, Diane Armaod, Barbara Davisf,5, and Donna Day Bairdb,6
aBiostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709;bEpidemiology Branch, National Institute of
Environmental Health Sciences, Research Triangle Park, NC 27709;cIntegrated Laboratory Systems, Durham, NC 27713;dDepartment of Radiology, University
of North Carolina, Chapel Hill, NC 27599;eDepartment of Obstetrics/Gynecology, University of North Carolina, Chapel Hill, NC 27599; andfLaboratory of
Women’s Health, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709
Edited by R. Michael Roberts, University of Missouri, Columbia, MO, and approved October 16, 2008 (received for review August 18, 2008)
Uterine leiomyomata (fibroids) are the leading cause of hysterec-
tomy in the United States. Black women have a greater fibroid
burden than whites, yet no study has systematically evaluated the
growth of fibroids in blacks and whites. We prospectively tracked
growth for 262 fibroids (size range: 1–13 cm in diameter) from 72
premenopausal participants (38 blacks and 34 whites). Fibroid
volume was measured by computerized analysis of up to four MRI
scans over 12 months. We used mixed effects models to identify
factors that are associated with growth, and results were con-
verted to percent change per 6 months for clinical relevance. The
median growth rate was 9% (range: ?89% to ?138%). Seven
percent of fibroids regressed (>20% shrinkage). Tumors from the
variation was twice the component among women; both were
significant, P < 0.001). Black and white women less than 35 years
of age had similar fibroid growth rates. However, growth rates
declined with age for whites but not for blacks (P ? 0.05). The odds
of a tumor growing more than 20% in 6 months also decreased
not influenced by tumor size, location, body mass index, or parity.
We conclude that (i) spontaneous regression of fibroids occurs; (ii)
fibroids from the same woman grow at different rates, despite a
uniform hormonal milieu; (iii) fibroid size does not predict growth
rate; and (iv) age-related differences in fibroid growth between
blacks and whites may contribute to the higher symptom burden
for black women.
ethnic ? fibroid ? MRI ? tumor growth ? longitudinal data
uterine artery embolization are also common treatments, but
hysterectomy may be required subsequently (2). Hartmann et al.
(3) estimate a $4,600 excess health care cost during the year
following each US woman’s diagnosis of fibroids. National
medical costs associated with fibroids exceed 2 billion dollars
annually (4). African Americans have a higher fibroid incidence
(5, 6), experience more severe symptoms (7), present with larger
tumors (7), and have a threefold higher risk of hysterectomy (8)
compared with whites. Symptoms increase with the size of
fibroids (7, 9, 10). However, few studies have examined the
growth of fibroids over time (11–13), and no study has system-
atically followed the growth of fibroids in black and white
The Fibroid Growth Study was designed to measure the
growth of fibroids in black and white women with clinically
relevant fibroids using MRI technology. We compare growth
growth in black and white women; and examine associations with
age, parity, body mass index (BMI), and tumor characteristics.
terine leiomyomata (fibroids) are the leading indication for
hysterectomy in the United States (1). Myomectomy and
Study Participants. Characteristics of the 72 participants are
shown in Table 1. Our cohort ranged in age from 24 to 54 years,
and approximately half were African American. Nearly 60%
were overweight or obese. More than half were diagnosed with
fibroids within 2 years of study entry. Most had multiple fibroids,
and approximately a third had more than eight. As expected
from the criteria for entry, participants had enlarged uteri
(range: 110–1,995 cm3, with nearly a fifth greater than 1,000
cm3). Fifteen of the 72 women opted for treatment during the
study year. There were no statistically significant differences
between black and white women with respect to these charac-
teristics, but there was a tendency for blacks to be younger and
to have higher BMIs. Women were recruited irrespective of
symptoms. Although most (88%) reported problems with pelvic
pain or bleeding, only 31% reported that these symptoms limited
Fibroid Characteristics at Enrollment. Fibroid size, type, and loca-
fibroids varied from 1.3 to 1098 cm3(1.4–12.8-cm diameter),
with a median volume of 17.3 cm3(3.2-cm diameter). The 6
submucosal fibroids tended to be small, with a median size of 7.7
Fibroid and Uterine Growth Rates. The 262 tumors varied widely in
their growth rates; they ranged from shrinkage of 89% to growth
of 138% per 6 months (Fig. 1). The median fibroid growth rate
for both black and white women was 9% per 6 months. Eighty-
eight tumors (34%) were rapidly growing (?20% increase in
volume per 6 months), and 19 (7%) were spontaneously regress-
ing (?20% decrease in volume per 6 months).
We next wanted to determine how fibroid growth was related
to overall uterine growth. The median uterine growth rate was
for most women, those who had at least one measured fibroid
that was rapidly growing had significantly increased uterine
growth compared with those without a rapidly growing tumor
(P ? 0.027). Uterine growth rate averaged 14% higher for
women with a measured rapidly growing tumor compared with
Author contributions: S.D.P., K.H., R.S., A.K., D.A., B.D., and D.B. designed research; S.D.P.,
J-P.G., H.V., and D.B. analyzed data; and S.D.P., S.L., B.D., and D.B. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
1Present address: Novartis, Cambridge, MA 02139.
3Present address: Family Health International, Durham, NC 27713.
4Present address: Reproductive Science Center, Lexington, MA 02421.
5Present address: Millennium: The Takeda Oncology Company, Cambridge, MA 02139.
6To whom correspondence should be addressed. E-mail: email@example.com.
This article contains supporting information online at www.pnas.org/cgi/content/full/
© 2008 by The National Academy of Sciences of the USA
December 16, 2008 ?
vol. 105 ?
no. 50 ?
Spontaneously Regressing Tumors. Nineteen tumors from 14
tively, they were found to vary in size and location and to come
from both blacks and whites aged 30–49 years [see supporting
these 19 tumors for lack of gadolinium enhancement, which
would be consistent with loss of arterial blood flow and necrosis
(14). By visual estimate, 7 tumors showed necrosis exceeding
50% of tumor volume and 2 others showed 20% to 40% necrosis.
Tumors with more dramatic shrinkage tended to have greater
Table 1. Characteristics of the participants (n ? 72) and their fibroids (n ? 262), Fibroid Growth Study, enrollment 2001–2004
n ? 72 women,
n ? 38 women,
n ? 34 women,
Time since initial diagnosis of fibroids (yr)
Uterine volume, cm3
Number of fibroids
Initial fibroid volume (diameter†)
?14.0 cm3(?3.0 cm)
14.0–64.9 cm3(3.0–4.9 cm)
?65.0 cm3(?5.0 cm)
*Treated women had growth data censored at treatment (5 women had 4 MRI scans, but 3 were censored after 3 MRI scans, and 7 were censored after 2 MRI
†Diameter calculated from measured volume based on ellipsoid formula.
www.pnas.org?cgi?doi?10.1073?pnas.0808188105 Peddada et al.
necrosis (Spearman correlation ? ?0.56, P ? 0.013; Table S1).
In a comparison sample of 19 tumors randomly selected from the
remaining 243, 1 tumor showed 20% necrosis and none showed
greater than 20% necrosis.
Fibroids from the Same Woman Grow at Different Rates. Growth
rates for each woman’s tumors are shown in Fig. 2, with the 72
women ordered by the median growth rate of their tumors. The
individual tumor growth rates are represented by the hatch
marks on the vertical lines. These demonstrate the wide range of
fibroid growth rates within a given woman. Seven women had
both a rapidly growing and a spontaneously regressing tumor.
Fig. 2 also shows that despite the within-woman variability,
some women tend to have tumors that grow rapidly, whereas
other women tend to have stable or shrinking tumors. When the
total variation in tumor growth rate was partitioned into a
component for within-woman variation and a component for
between-women variation using mixed model regression, both
components were significant (P ? 0.001). The variation of tumor
growth within women was two times the variation between
Factors Related to Rate of Fibroid Growth. Fig. 3 shows the asso-
ciations of fibroid growth with several characteristics, including
ethnicity, age, number of fibroids, and size of the fibroid. The
results are based on analysis of 258 fibroids from 72 women after
excluding statistical outliers (the four most rapidly shrinking
tumors; see SI Text for description of effects of the outliers). The
for whites (12% vs. 10% increase in volume per 6 months,
respectively). However, when we compared tumors within age
years) grew much more slowly than those from older black
women (2% vs. 15% growth rate, respectively; Fig. 3). Adjusted
analyses based on linear mixed effects models supported this
association, demonstrating a significant decline in growth rate
with age for tumors from whites but not from blacks (P ? 0.05;
Table 2). The pair-wise analysis shows a significant decrease in
tumor growth rate for older whites when compared with younger
whites (P ? 0.004), and no such difference was found among
blacks (P ? 0.67). Furthermore, the chance of a tumor growing
rapidly (?20% increase in volume per 6 months) depended on
age for white women but not for black women (P ? 0.004). The
relative odds of rapid growth for younger whites was 17 times
that of the older whites (P ? 0.001). For blacks there was no
significant difference by age (P ? 0.81). These results are
summarized in Table S2.
The only other factor affecting fibroid growth rate was the
number of fibroids in the uterus. Single tumors grew much faster
than fibroids that shared a uterus (Fig. 3, Table 2). Fibroid
growth rates were not significantly associated with BMI or
parity, or with tumor size, type, or location. The reader is
referred to SI Text for sensitivity analyses (including dropping
the six submucosal fibroids and dropping the five women with a
single fibroid) that demonstrated robustness of results.
With the exception of the factors that we found to be
important (age, ethnicity, and number of tumors), other char-
acteristics were associated with ?5% difference in growth rates.
Although such differences would be statistically significant with
extremely large sample sizes, they would likely not be viewed as
premenopausal women, Fibroid Growth Study, enrollment 2001–2004.
Frequency distribution of growth rates for 262 fibroids from 72
for each of 72 participants, ordered by each participant’s median tumor
growth rate. The horizontal hatch marks show the growth rate for each
individual tumor, Fibroid Growth Study, enrollment 2001–2004.
participants, Fibroid Growth Study, enrollment 2001–2004.
Unadjusted mean fibroid growth rates by participant characteristics
Peddada et al.
December 16, 2008 ?
vol. 105 ?
no. 50 ?
clinically important. Using our variance estimates, we found that
our study had 80% power to detect differences in growth rates
This longitudinal study of 262 uterine leiomyomata in 72 pre-
menopausal women provides an in-depth analysis of tumor
growth in black and white women. We demonstrated that
fibroids within the same woman often have different growth
rates despite having a similar hormonal milieu. Indeed, each
tumor appeared to have its own intrinsic growth rate, consistent
with studies showing that fibroids are monoclonal in origin (15,
16) with variable molecular characteristics (17–21). The only
other large study of fibroid growth was conducted in Japan, and
most of the 70 participants had only a single tumor (11); thus,
variation in growth of fibroids from the same woman could not
We observed spontaneous regression in a small percentage of
fibroids, surprising in premenopausal women. Tumor shrinkage
after menopause is assumed to occur; there is a dramatic
reduction in clinical diagnoses after menopause (22), and post-
menopausal fibroids are predominantly small lesions (23). De-
waay et al. (12) identified six small spontaneously resolved
tumors in women approaching menopause; otherwise, however,
spontaneously regressing tumors in premenopausal women have
not been well documented in the literature. The women with
regressing tumors in our study were having regular menses, and
half were in their 30s. Many of the shrinking tumors we observed
showed evidence of necrosis, suggesting that vascular events may
A fundamental question we sought to address is whether
fibroid growth differs in black and white women. There is a
general assumption that fibroids grow faster in black women
compared with white women because black women are diag-
nosed at a younger age and have a higher incidence and more
symptoms (5–8). Molecular markers also may differ between
tumors from blacks and whites (18, 21, 24). We found significant
ethnic differences in fibroid growth when age was considered.
Growth rates were similar between blacks and whites in the
youngest age group (?35 years) but declined in older white
women so that, on average, tumors grew extremely slowly in
white women in the ?45 age group. In contrast, growth rates
showed little decline with increasing age for blacks. Importantly,
the greater fibroid burden observed in black women may be
explained by our observation that fibroid growth rates show little
decline with increasing age in black women and by the previously
reported finding that black women have an earlier onset com-
pared with white women (5, 6, 25).
The decline in tumor growth rate in older white women was
an unexpected finding and could not be attributed to these
women entering menopause. Participants were having regular
periods, and the decline was not seen exclusively in the oldest age
group. Instead, there was a gradual decline across the three age
groups for whites. Even if some were perimenopausal, their
fibroids would have been expected to continue growing based on
the clinical literature (26, 27), which refers to perimenopausal
instability of ovarian function and more frequent periods of
Dysregulation of the extracellular matrix has been suggested as
an important etiologic factor in fibroid growth (28). There may
be age-related changes in angiogenesis or extracellular matrix
production that differ between blacks and whites. Future studies
should consider the age of the woman when looking at fibroid
The finding that fibroid growth was not influenced by tumor
characteristics such as size and location was surprising and is
important for research that characterizes molecular character-
istics of fibroid tissue. Tumor size has been related to variation
in molecular markers (17, 19–21), and it has been assumed that
the molecular differences reflect differences in tumor growth
rates. Our data show that large tumor size cannot be used as an
indicator of a growing tumor.
Our data showed more rapid growth for solitary tumors than
for multiple tumors that share a uterus. However, our sample
size of women with solitary tumors was quite small, and we
required participants to have either at least one large fibroid or
an enlarged uterus for enrollment. It is possible that only rapidly
growing tumors can attain a large size while remaining solitary,
so the finding could be attributable to our sample selection.
Alternatively, solitary tumors may grow faster because of less
competition for uterine blood supply. To evaluate these alter-
natives, small solitary tumors need to be studied.
The study has other limitations. Extremely small tumors
(?1.5-cm diameter) could not be measured accurately, and our
focus on women with at least one already well-developed fibroid
Table 2. Adjusted growth rate differences* associated with
participant and fibroid characteristics, Fibroid Growth Study,
Adjusted differences in
growth rate estimate
(95% confidence interval)
Age by ethnicity, yr
?7.05 (?17.62, 4.87)
?3.38 (?17.31, 12.90)
Number of fibroids
Initial fibroid volume
?14.0 cm3(?3 cm)
14.0–64.9 cm3(3.0–4.9 cm)
?65 cm3(?5.0 cm)
?7.76 (?21.04, 7.74)
5.69 (?2.89, 42.32)
0.72 (?13.73, 43.26)
33.75 (7.58, 61.17)
?4.81 (?13.79, 38.67)
2.40 (?7.30, 41.61)
4.17 (?5.86, 42.41)
?3.53 (?9.43. 37.80)
?3.10 (?9.96, 38.36)
0.55 (?5.12, 39.20)
?3.25 (?9.67, 38.12)
?0.75 (?7.49, 39.17)
n ? 258 fibroids from 72 women. Four statistical outliers (all shrinking
?50% in volume per 6 months) were excluded, leaving 258 fibroids.
*Age by ethnicity differences are adjusted for number of fibroids; number of
fibroid differences are adjusted for age by ethnicity; all other variables are
adjusted for age by ethnicity and number of fibroids.
†P value for the overall importance of each factor for growth.
P ? 0.004.
§Diameter calculated from measured volume based on ellipsoid formula.
¶Intramural group includes six submucosal fibroids.
www.pnas.org?cgi?doi?10.1073?pnas.0808188105Peddada et al.
did not allow us to examine initial tumor development. We also
were unable to examine submucosal fibroids statistically because
there were so few of them. However, we investigated potential
biases, including biased sample selection, variation in menstrual
phase at time of MRI, and other possible confounders and found
little effect on our findings (SI Materials).
Our findings have implications for patient care and for further
research directions. Current clinical practice encourages an
ultrasound or pelvic examination at 6 months to evaluate growth
(29). Our analysis shows that the majority of tumors grow less
than 20% in 6 months, with a median growth rate of 9%. Thus,
it may be possible to extend the follow-up time for clinical
assessment of fibroid growth. In addition, if further research
supports our findings that tumor growth rates decline in white
women as they age, those approaching perimenopause might
choose to delay treatment and wait for menopause when tumors
are likely to shrink. Current medical therapies have focused on
hormonal manipulation of well-developed tumors (30). The
rapid growth of tumors in young women in both ethnic groups
suggests that research is urgently needed to study tumor onset
and identify preventive factors. Treatments that inhibit early
tumor growth could stop development of debilitating symptoms.
Study Design. The National Institute of Environmental Health Sciences Fibroid
Growth Study was a collaborative study with the University of North Carolina
Medical Center that enrolled participants from 2001 to 2004 with approval
from both institutional review boards. Premenopausal women with a known
diagnosis of fibroids, confirmed by ultrasound, were recruited from gynecol-
ogy clinics and announcements in the community (Davis et al., in review). To
ensure clinical relevance, enrollment was limited to women with at least one
pregnancy size (200–250 cm3) (31). Fibroids were measured up to four times
(MRI scans taken at enrollment and then at 3, 6, and 12 months). Of the 116
4 women dropped out, and 1 woman had completed only one MRI scan when
the field study ended). Of the 81 women with two or more MRI scans, 3 were
excluded because their tumors were smaller than the size criteria for this
analysis. We further limited analysis to black and white women. This left 72
women in our analysis sample (38 blacks and 34 whites). Prospective time in
the study averaged approximately 9 months, primarily because of early ter-
mination when the field study ended (see details in SI Text).
Measurement of Tumor and Uterine Volume. Sagittal T2-weighted MRI scans
without contrast were evaluated for type (submucosal, intramural, or subse-
rosal), location, and size of fibroids (see detailed description of MRI protocol
in SI Text). Fibroids were selected for volumetric measurement if they were
seen in at least three consecutive slices and had traceable borders. When a
woman had many fibroids, the technician selected tumors representing dif-
ferent sizes and positions in the uterus. All submucosal fibroids were mea-
sured. The final sample was limited to tumors that had volumes ?5.0 cm3or
woman contributing 1–11 individual tumors).
Fibroid volume was determined using the volume estimation and tracking
over time method developed for this study (32). All analyses used volumetric
measures, but a diameter size was calculated from measured volume for
descriptive purposes. Uterine volume was estimated from each participant’s
first and last MRI scan based on measurement of craniocaudal length (L),
assurance are in SI Text.
tumors were centered in the endometrial lining, intramural in the myome-
trium, and subserosal along the external lining or outside of the uterus. The
in relation to the fundus, corpus, or lower uterine segment (see reference
diagram in SI Text).
Determination of Fibroid and Uterine Growth Rates. The natural logarithm of
fibroid volume was used to make the distribution approximately normal. The
growth rate of each tumor was based on the change in log volume between
each MRI scan divided by the number of days in the interval. For each tumor,
rates across intervals were averaged. For clearer clinical application, the
A 6-month interval was chosen because that is a clinically recommended
follow-up period (29) and it falls within the observation period of this study.
The reader is referred to SI Text for further details of growth rate determi-
by the number of days between the first and last MRI scans, summarized as
percent change in volume per 6 months.
Statistical Analyses. We used mixed effects linear regression models to eval-
uate factors that may influence fibroid growth rates (PROC MIXED, version
9.1; SAS Institute, Cary, NC). This method accounted for any correlation in
model selection are in SI Text. We investigated ethnicity (blacks vs. whites,
based on self-reported ethnicity), age, number of fibroids in the uterus at
study enrollment (1, 2, 3–8, or ?8), participant BMI (kg/m3based on measure-
ments taken at the first MRI scan), participant parity (nulliparous vs. parous
based on self-report), initial fibroid volume, fibroid type (subserosal vs. the
only 6 submucosal fibroids), and location of fibroid (fundus, corpus, or lower
segment) as potential factors associated with tumor growth. Statistical sig-
nificance of pair-wise differences was evaluated only when a factor was
significant at P ? 0.05. We also investigated the factors associated with the
odds of a tumor growing rapidly (20% or more growth in a 6-month period)
using random effects logistic regression analysis (SAS macro GLIMMIX; SAS
Institute, Cary, NC) (see SI Text for details). We conducted analyses with the
same primary and secondary variables as in the growth rate model and used
the same 258 tumors in analysis.
ACKNOWLEDGMENTS. The authors thank study participants; Ms. Edelstein
(National Institute on Environmental and Health Sciences [NIEHS]) for graph-
ics; Ms. Greasby (Graduate Student, Department of Biostatistics, University of
California, Davis) for initial data quality control checks; Ms. Firat (Radiology
Technician, University of North Carolina, Chapel Hill); Mss. Daniel, Davis, and
Pope for managing radiology films and digital images (all at Integrated
Laboratory Systems); and Ms. Ragan and Drs. Kissling, Korach, Weinberg, and
Wilcox (NIEHS) and Dr. Leppert (Duke University) for reviewing an earlier
Program of the NIEHS, National Institutes of Health (Grant Z01ES 101663-05),
with partial funding from the National Center on Minority Health and Health
Disparities Grant MO1RR00046 and NIEHS Contracts N01-ES-95446 and 273-
1. Farquhar CM, Steiner CA (2002) Hysterectomy rates in the United States 1990–1997.
Obstet Gynecol 99:229–234.
2. Edwards RD et al. (2007) Committee of the Randomized Trial of Embolization versus
Surgical Treatment for Fibroids. Uterine-artery embolization versus surgery for symp-
tomatic uterine fibroids. N Engl J Med 356:360–370.
3. Hartmann KE, et al. (2006) Annual costs associated with diagnosis of uterine leiomy-
omata. Obstet Gynecol 108:930–937.
tumors in the United States. Am J Obstet Gynecol 195:955–964.
5. Baird DD, Dunson DB, Hill MC, Cousins D, Schectman JM (2003) High incidence of
uterine leiomyoma in black and white women: Ultrasound evidence. Am J Obstet
6. Marshall LM, et al. (1997) Variation in the incidence of uterine leiomyoma among
premenopausal women by age and race. Obstet Gynecol 90:967–973.
Racial differences in severity, symptoms and age at diagnosis. J Reprod Med 41:483–490.
8. Myers ER, et al. (2001) Management of uterine fibroids (Evidence Report/Technology
omata. Obstet Gynecol 101:431–437.
11. Tsuda H, Kawabata M, Nakamoto O, Yamamoto K (1998) Clinical predictors in the
natural history of uterine leiomyoma: preliminary study. J Ultrasound Med 17:17–
12. DeWaay DJ, Syrop CH, Nygaard IE, Davis WA, Van Voorhis BJ (2002) Natural history of
uterine polyps and leiomyamata. Obstet Gynecol 100:3–7.
13. Ichimura T, et al. (1998) Correlation between the growth of uterine leiomyomata and
estrogen and progesterone receptor content in needle biopsy specimens. Fertil Steril
Peddada et al.
December 16, 2008 ?
vol. 105 ?
no. 50 ?
14. Shimada K, Ohashi I, Kasahara I, Miyasaka N, Shibuya H (2004) Triple-phase dynamic
15. Hashimoto K et al. (1995) Clonal determination of uterine leiomyomas by analyzing
necol Obstet Invest 40:204–208.
a common clonal origin of different tumor nodules in some multiple leiomyomas. Int
J Oncol 31:1379–1389.
17. Lobel MK, Somasundaram P, Morton CC (2006) The genetic heterogeneity of uterine
leiomyomata. Obstet Gynecol Clin North Am 33:13–39.
18. Wei J-J, et al. (2006) Ethnic differences in expression of the dysregulated proteins in
uterine leiomyomata. Hum Reprod 21:57–67.
19. Wei J-J, Chiriboga L, Mittal K (2005) Expression profile of the tumorigenic factors
associated with tumor size and sex steroid hormone status in uterine leiomyomata.
Fertil Steril 84:474–484.
20. Wolanska M, Bankowski E (2007) Transforming growth factor beta and platelet-
derived growth factor in human myometrium and in uterine leiomyomas at various
stages of tumour growth. Eur J Obstet Gynecol Reprod Biol 130:238–244.
21. Wang T, et al. (2007) A micro-RNA signature associated with race, tumor size, and target
gene activity in human uterine leiomyomas. Genes Chromosomes Cancer 46:336–347.
22. Ross RK, et al. (1986) Risk factors for uterine fibroids: reduced risk associated with oral
contraceptives. Br Med J 293:359–362.
23. Cramer SF, Patel A (1990) The frequency of uterine leiomyomas. Am J Clin Pathol
24. Pan Q, Luo X, Chegini N (2007) Genomic and proteomic profiling I: Leiomyomas in
African Americans and Caucasians. Reprod Biol Endocrinol 5:34–48.
25. Wise LA. Palmer JR, Stewart EA, Rosenberg L (2005) Age-specific incidence rates for
26. Ryan GL, Syrop CH, VanVoorhis BJ (2005) Role, epidemiology, and natural history of
benign uterine mass lesions. Clin Obstet Gynecol 48:312–324.
27. Wallach EE, Vlahos NF (2004) Uterine myomas: An overview of development, clinical
features, and management. Obstet Gynecol 104:393–406.
28. Leppert PC, Catherino WH, Segars JH (2006) A new hypothesis about the origin of
uterine fibroids based on gene expression profiling with microarrays. Am J Obstet
29. Katz V, Lentz G (2007) Congenital abnormalities of the female reproductive tract:
Anomalies of the vagina, cervix, uterus, and adnexa. Comprehensive Gynecology, eds
Katz V, Lentz G, Lobo R, Gershenson D (Mosby, St. Louis), 5th Ed.
30. Stewart EA (2001) Uterine fibroids. Lancet 357:293–298.
31. Harb TS, Adam RA (2005) Predicting uterine weight before hysterectomy: Ultrasound
measurements versus clinical assessment. Am J Obstet Gynecol 193:2122–2125.
32. Guyon J-P, et al. (2003) VETOT, volume estimation and tracking over time: Framework
and validation. Lecture Notes Comput Sci 2879(Pt 2):142–149.
www.pnas.org?cgi?doi?10.1073?pnas.0808188105Peddada et al.