Bone marrow consists of both hematopoietic (red) and fatty (yellow) components, the
proportions of which are thought to be related to the remodeling capacity of bone.
There is a well-established, age-related conversion of red to yellow bone marrow
(1), and Neumann was
the first who reported that active hematopoietic (red) bone marrow declined with age
and converted to fatty (yellow) marrow, starting from the periphery and extending
towards the axial skeleton (2). From this point forward, this phenomenon was referred to as
Neumann’s law (3). Both
the causes and consequences of this change are uncertain, as is the role of fat in
the regulation of the bone marrow (4).Recently, magnetic resonance imaging (MRI) has become the non-invasive imaging
modality of choice in diagnosing bone marrow pathology (5). Red and yellow marrow is easily
distinguishable, and marrow composition may be qualitatively assessed from signal
intensity variations on an MRI. Previous articles have demonstrated the age-related
conversion of bone marrow in cranial bones (6), femoral bones (7), bone epiphyses (8), and pelvic bones (9). In particular, Ricci et al. (10) described three
distinct signal intensity age-related patterns in the lumbar spine. In comparison,
relatively few MRI studies have tried to present quantitative measurements of bone
marrow by inferring red and yellow composition from their water and fat signal
contributions. Those studies have tended to focus on a single vertebral body in the
lumbar spine, usually L2 or L3 (11).On the other hand, the reconciliation between skeletal and chronological age is of
big importance in the context of criminal proceedings involving living individuals,
who frequently lack any associated identification documentation and are referred to
the criminal justice system. Many times, a forensic practitioner is requested to
perform an assessment of age in a dead or a living individual in order to provide
information that carries significant evidentiary value in legal decisions.Therefore, the purpose for this study was to use the advent of clinical scanners to
examine the correlation between age and fat content in the lower vertebral bodies
(signal ratio on T1-weighted [T1W] MRI). Furthermore, the influence of field
inhomogeneities, sequence parameters, and signal ratios of a 1.5-T and 3-T scanner
on this correlation was examined.
Material and Methods
The institutional review board (IRB) proposal was waived due to the retrospective
nature of the study and the anonymity of the patients’ exams. A continuous sample of
patients with lumbar spine MRI was retrospectively selected in order to get a
representative sample from our 1.5-T and 3-T MRI unit (Magnetom Avanto® and Magntom
Skyra®, Siemens Healthineers, Erlangen, Germany).
Patients
Inclusion criterion was as follows: a lumbar spine MRI with a T1W image of
diagnostic quality. Exclusion criteria were as follows: postoperative status,
any pathology in the spine interfering with the proper measurement or MRI exam
with severe motion or metal artifacts. During a time period of two years (May
2015 to May 2017), a total of 205 patients were included in the 1.5-T unit (80
men, 125 women; median age = 57 years; age range = 17–96 years) and a total of
319 patients were included in the 3-T unit (151 boys/men, 168 girls/women;
median age = 53 years; age range = 2–94 years). Age distribution is provided in
Fig. 1.
Fig. 1.
Age distribution (per decade) of the 205 and 319 patients examined on the
1.5-T and 3-T units.
Age distribution (per decade) of the 205 and 319 patients examined on the
1.5-T and 3-T units.
MRI exam
In our routine protocol the entire lumbar spine was scanned, along with most of
the adjacent sacral bone and the adjacent lower thoracic vertebral bodies. The
standard sagittal T1W parameters of the 1.5-T and 3-T unit are given in Table 1.
Table 1.
Routine sagittal T1 turbo spin-echo protocol for the 1.5-T unit (Magnetom
Avanto®) and the 3-T unit (Magntom Skyra®).
TR (ms)
TE (ms)
FOV (mm)
Base resolution
Phase oversampling (%)
Stack
Slice thickness (mm)
Voxel (mm)
1.5 T
604
9.6
360
384
50
19
3
0.9 × 0.9
3 T
506
9.8
300
448
100
17
3
0.7 × 0.7
FOV, field of view; TE, echo time; TR, repetition time.
Routine sagittal T1 turbo spin-echo protocol for the 1.5-T unit (Magnetom
Avanto®) and the 3-T unit (Magntom Skyra®).FOV, field of view; TE, echo time; TR, repetition time.
Image analysis
Two radiologists, with 15 and 5 years of experience in musculoskeletal imaging,
respectively, read the MRIs of the patients of the 1.5-T unit (Readers 1 and 2)
and two radiology fellows of musculoskeletal imaging read the images of the 3-T
unit separately (Readers 3 and 4). The readers analyzed the images independently
and were blinded to the ages of the patients. The images were read in a random
order. Two picture archiving and communication system (PACS, Sectra, Linköping,
Sweden and General Electric, Milwaukee, WI, USA) were used. Both groups were
instructed to note the T1 signal intensity within the center of all captured
vertebra (avoiding variants and pathologies). The region of interest (ROI)
should be as large as possible on the sagittal T1W image, without including the
cortical plate of the vertebra. Furthermore, the readers measured the T1 signal
of the subcutaneous tissue on the level of the lumbar vertebra L1 and the sacral
vertebra S1 (Fig. 2).
The ROI should be as large as possible, without including the cutis or the
muscles. After four weeks, all radiologists were asked to reread half of the
patients in another random order.
Fig. 2.
Measurement of the T1 fat signal in the subcutaneous tissue for
standardization (L1 and S1).
Measurement of the T1 fat signal in the subcutaneous tissue for
standardization (L1 and S1).
Analysis of real fat fraction in the spine (ex-vivo experiment)
From the standardized T1 signal, the relative vertebral fat signal and,
consequently, the vertebral age, could be approximated. With a second
experiment, we aimed to determine the actual fat content in the vertebral bodies
with the following ex-vivo experiment: 20-mL syringes filled with different
fat–water mixtures, with administered solvent (having the same signal as water).
Sunflower oil (Florin AG, Muttenz, Switzerland) was mixed with tap water and
solvent (Splendid, Salzburg, Austria) accordingly to reach a fat fraction of 0,
20%, 40%, 60%, 80%, and 100%. These six syringes were scanned with the 1.5-T and
3-T lumbar spine standard protocol to determine the T1 signal intensities and
calculate the relative signal by dividing the signal in a specific syringe by
the signal of the syringe filled with 100% oil. A fitting curve of the graph fat
fraction signal/actual fat fraction would allow for absolute fat fraction
determination in the vertebral bodies.
Statistical analysis
The absolute mean T1 signal intensity measurements were standardized by dividing
their signal value by the signal of the subcutaneous tissue (vertebra-to-fat
ratio). For each vertebral body, bone-to-fat ratios (for both lumbar and sacral
subcutaneous fat) were calculated. After four weeks, all radiologists were asked
to reread half of the MRIs of the patients for an intra-reader concordance, in
addition to the inter-reader concordance. Both were calculated as Pearson
correlation coefficient R values with 95% confidence interval (CI). The
age-signal correlation coefficients (R) were calculated from each spine level
and compared to each other for women and men, both separately and together.
Furthermore, a comparison of R values of 1.5-T versus 3-T images was performed
for each spine level. MedCalc® version 15.0 (MedCalc Software, Ostend, Belgium)
and a significance level of P < 0.05 were utilized. An
age-signal fitting curve was selected for best correlation. The SD of this
fitting curve was calculated using the differences of the calculated age and
real age, to provide a hands-on tool for physicians.
Results
The standardized sagittal T1 signal intensity in the spine correlated significantly
with the age of the patients. The strongest correlation was demonstrated for the
1.5-T unit in the thoracic vertebra T11, followed by lumbar vertebra L1, showing
correlation coefficients (R) of 0.64 (95% CI = 0.53–0.72,
P < 0.0001) and 0.49 (95% CI = 0.38–0.59,
P < 0.0001), respectively. For the 125 women and 80 men at the
1.5-T unit, the R values were similar in T11, with 0.62 (95% CI = 0.49–0.72) and
0.64 (95% CI = 0.44–0.77), respectively. The other R values are listed in Table 2.
Table 2.
R values for best age-signal correlation in the 1.5-T group.
Gender
Fat signal measurement level (standardization)
Age signal correlation coefficient (1.5-T
unit)
T11
T12
L1
L2
L3
L4
L5
All
S1
0.64
0.44
0.49
0.46
0.39
0.34
0.43
Male
S1
0.64
0.50
0.57
0.50
0.43
0.42
0.52
Female
S1
0.62
0.42
0.44
0.43
0.37
0.30
0.39
All
L1
0.35
0.25
0.29
0.25
0.21
0.17
0.24
Confidence intervals of T11 and L1
All
S1
0.53–0.72
0.38–0.59
Male
S1
0.44–0.77
0.41–0.70
Female
S1
0.49–0.72
0.28–0.57
All with P < 0.0001
R values for best age-signal correlation in the 1.5-T group.The R value was significantly higher when the signal in the subcutaneous fat on the
sacral level instead of the lumbar level was used for standardization
(P < 0.02). The vertebral signal correlated significantly
better with age in the 1.5-T unit compared to the 3-T unit on all vertebral levels:
comparing the best R values, the 3-T unit demonstrated an R of 0.20 (95%
CI = 0.09–0.30, P < 0.0001) compared to the 1.5-T unit. On the
3-T images, better R values were obtained by using the lumbar level for
standardizing the fat signal, except for the level of thoracic vertebra T11 (Table 3).
Table 3.
Age-signal correlation in the 3-T group.
Fat signal measurement level (standardization)
Age signal correlation coefficient R (3-T
unit)
T11
T12
L1
L2
L3
L4
L5
R
P value
R
P value
R
P value
R
P value
R
P value
R
P value
R
P value
L1
0.19
0.17
0.18
0.00
0.20
0.00
0.18
0.00
0.15
0.01
0.16
0.00
0.19
0.00
S1
0.20
0.13
0.10
0.08
0.11
0.04
0.11
0.05
0.10
0.07
0.10
0.06
0.10
0.07
Age-signal correlation in the 3-T group.The average standardized T1 signal per decade is shown in Fig. 3 and the age-signal curve is
demonstrated in Fig. 4 (for
both the 1.5-T and 3-T units), with obvious superiority of the 1.5-T unit. The
fitting curve demonstrated the best R value for linear fitting
(R2 = 0.403). Therefore, the formula for age estimation was
y = 101.68x + 11.813, with y representing age and x representing the T1 signal ratio
of vertebra-to-fat (subcutaneous fat on level S1). The SD for the age was ±14.06
years. This meant that there was an average increase of the relative T1 signal in
thoracic vertebra T11 of 0.098 per decade, equaling a 10% increase in absolute T1
signal intensity per decade (Fig.
5). The inferior average relative age-signal curve for thoracic vertebra
T11 on the 3-T MRI unit is shown in Fig. 4.
Fig. 3.
Average standardized T1 signal intensity in thoracic vertebra T11 per decade,
examined on a 1.5T and 3T MRI unit.
Fig. 4.
Age to T1 signal correlation in thoracic vertebra T11 examined on a 1.5-T and
3-T MRI unit. The formula of the linear fit curve, as well as the
R2 value, are indicated.
Fig. 5.
Vertebral T1 fat signal ratios (T1FSR). T1FSR of thoracic vertebra T11 and
subcutaneous tissue on a 1.5-T scanner (top row) and T1FSR of lumbar
vertebra L1 and subcutaneous tissue on a 3-T scanner (bottom row). T1FSR
increased with age: (a/f, b/g, c/h, d/i, e/j) T1W images represent examples
for the 2nd, 4th, 6th, 8th, and 10th decade, respectively, with increasing
vertebral T1 hyperintensity.
Average standardized T1 signal intensity in thoracic vertebra T11 per decade,
examined on a 1.5T and 3T MRI unit.Age to T1 signal correlation in thoracic vertebra T11 examined on a 1.5-T and
3-T MRI unit. The formula of the linear fit curve, as well as the
R2 value, are indicated.Vertebral T1 fat signal ratios (T1FSR). T1FSR of thoracic vertebra T11 and
subcutaneous tissue on a 1.5-T scanner (top row) and T1FSR of lumbar
vertebra L1 and subcutaneous tissue on a 3-T scanner (bottom row). T1FSR
increased with age: (a/f, b/g, c/h, d/i, e/j) T1W images represent examples
for the 2nd, 4th, 6th, 8th, and 10th decade, respectively, with increasing
vertebral T1 hyperintensity.
Inter- and intra-reader concordance
Inter- and intra-reader correlations was significant for all readers, with an
R > 0.82 and > 0.88, respectively (both with
P < 0.0001). Intra-reader correlations of Reader 1, 2, 3,
and 4 were 0.998 (95% CI = 0.998–0.999, P < 0.0001), 0.883
(95% CI = 0.84–0.92, P < 0.0001), 0.961 (95% CI = 0.95–0.97,
P < 0.0001), and 0.930 (95% CI = 0.91–0.95,
P < 0.0001). Inter-reader correlation between Reader 1/2
and Reader 3/4 was 0.827 (95% CI = 0.74–0.89, P < 0.0001)
and 0.883 (95% CI = 0.83–0.92, P < 0.0001).
Calculated absolute vertebral fat fraction
There was a linear relationship between T1 signal intensity and fat content in
the syringes in the ex-vivo experiment (Fig. 6). The relative T1 signal ratio
demonstrated a linear increase parallel to the ex-vivo fat ratio; therefore, the
absolute vertebral fat content could be determined. The fitting curve and
correlation coefficient are indicated on Fig. 6.
Fig. 6.
Ex-vivo experiment with syringes filled with water and oil: 6 syringes
with 0%, 20%, 40%, 60%, 80%, and 100% oil (mL), in a 1.5-T and 3-T MRI
unit (top line demonstrates cross-section through the syringes 1.5-T).
An almost perfect linear correlation was observed between fat content
ratio and T1 signal ratio (R2 > 0.99). For example, a
patient with a standardized T1 signal ratio of 0.5 on a 1.5-T MRI would
have a real fat content of 0.4 in the vertebral body.
Ex-vivo experiment with syringes filled with water and oil: 6 syringes
with 0%, 20%, 40%, 60%, 80%, and 100% oil (mL), in a 1.5-T and 3-T MRI
unit (top line demonstrates cross-section through the syringes 1.5-T).
An almost perfect linear correlation was observed between fat content
ratio and T1 signal ratio (R2 > 0.99). For example, a
patient with a standardized T1 signal ratio of 0.5 on a 1.5-T MRI would
have a real fat content of 0.4 in the vertebral body.
Discussion
An inverse relationship between increasing marrow fat and trabecular bone loss in
osteoporosis has been evident for the past several years (12). It was only recently, through the use
of MR-based techniques, that marrow fat content could be quantified on a large scale
(13) and at different
anatomical parts (14).
Several studies examining the physiological changes in marrow fat content have
proven that the percentage of marrow fat content gradually increases with advancing
years (11,15–17). An easily
remembered approximation is that vertebral body marrow fat content increases from
25% at 25 years of age to 65% at 65 years of age (15). Moreover, along with the increase in
marrow fat content with age, MR-based studies have shown that a distinct sex
difference in marrow fat content exists (11,15). Other studies have suggested that
glucose metabolism and weight loss may influence marrow fat behavior, and marrow fat
may be a determinant of bone metabolism (18), with other studies presenting the
evidence that specific volumes and types of exercise may influence the
age-determined adipose marrow conversion (19). To overcome this sex-, metabolic-, or
habit-related predilection, in our study, we investigated different age groups
consisting of randomized numbers of male and female patients with different medical
status, body mass index, smoking habits, and levels of physical activity. In this
way, we intended to investigate the direct connection between the age and the fat
content of the lumbar vertebrae. There is a linear correlation between the age and
the relative T1 signal of the spine and the real fat fraction in the spine. The
syringe with 0% fat/100% water did not produce zero signal because of the remaining
signal from the pure water in Fig.
6.Several previous studies have tried to evaluate the efficacy of MR spectroscopy (MRS)
on high field imaging systems (3.0 T) for the assessment of normal bone marrow
composition (20); other
studies have tried to quantitatively evaluate vertebral bone marrow fat content with
chemical-shift MRI (21).
Those studies demonstrated an age‐related increase in the fat content of the spine,
with values greater in men compared to women. There was also a trend in vertebral
bodies within the same individuals, with fat content increasing from the L1 vertebra
to the L5 vertebra (20).
In our study, the most reliable vertebra, according to the age-related fat content,
was shown to be thoracic vertebra T11. If the thoracic spine is not included in the
imaging field, the second-best age assessment could be made in the lumbar vertebra
L1. The pathophysiological relevance of this is unknown but may be because of the
“peripheral to axial” conversion from red to yellow marrow with increasing age
(2). Due to this
conversion, the inferior lumbar vertebrae may be prone to show more fatty
infiltration with lower age. This may be in opposition with the fact that the lower
spine is more sensitive to early degenerative changes, which could be one reason
that our results found that vertebrae T11 and L1 were best for age matching. In
these previous studies, the results demonstrated an advantage of higher magnetic
field (3.0 T) because of the increase in both signal‐to‐noise ratio and chemical
shift dispersion, thus leading to improved spatial resolution, which is crucial in
the examination of small vertebral bodies and those vertebral bodies that are
anatomically more difficult to identify as L5 (20). Additionally, an improvement in
spectral quality at 3.0 T was demonstrated compared to 1.5 T in one individual
(20). On the other
hand, it was demonstrated that the vertebral bone marrow fat content, when
calculated with chemical-shift MRI, is not a reliable parameter for predicting bone
mineral density in female patients aged 50–65 years (21). However, chemical-shift-based
water–fat separation enables the quantitation of vertebral marrow adiposity with
excellent reproducibility, which appears to be a useful method in providing
complementary information to osteoporosis-related research fields (22). In our study, we
discovered that, because of the higher magnetic field of a 3.0-T imaging system, the
results had a lower statistical significance compared to a 1.5-T system due to the
regional field inhomogeneity. We avoided the use of chemical shift sequences or
spectroscopy in our investigation because we wanted to examine the direct age
changes in the fat content of the bone marrow by utilizing a daily used,
non-extravagant sagittal T1W imaging system. This type of imaging system is used by
almost every radiology department in the imaging of the spine and is accessible by
almost every forensic department.This study had some limitations. First, we had no histological reference standard. To
overcome this limitation, we retrospectively examined an efficient number of
individuals of different ages and we used a consistent measuring field size. Second,
we had to deal with several artifacts, such as the susceptibility, truncation,
chemical-shift, third arm, and, particularly, pulsation artifacts, along with choice
of slice orientation, for which all options are equally advantageous in all regions
of the lower spine and reduce the image quality. Spine studies in clinical routine
are performed with a posterior coil and the subcutaneous adipose tissue on the back
side may be artificially too T1-hyperintense which may lead to a biased fat
fraction. This problem could be solved with a Dixon sequence because of the inherent
B1 correction. In addition, MRS (single voxel) of the vertebral bone marrow could
overcome this problem. Furthermore, the retrospective nature of the study is not as
powerful as prospectively acquired data: a longitudinal assessment of an
individual’s fat signal over time will demonstrate the real correlation.The T1 signal intensity in spine MRI is not only dependent from fat, several factors
influence the signal intensity. First, the localization of the coil and the distance
from the spine to the coil influences the signal. Second, the saturation pulse used
for suppression of breathing artifacts influences the signal depending on the
location of the saturation band. Third, postprocessing image homogenization due to
b1 inhomogeneity is a vendor specific T1 variable. We tried to overcome these
limitations by including many patients and using relative T1 signal for neutralizing
these variables to come forward with a fast and simple age estimation method that
can be used in daily clinical or forensic routine. Many of these limitations can be
eliminated by measuring the absolute T1 time (T1 mapping) and we are currently
recruiting patients for a prospective T1 mapping of the spine for age estimation. In
addition, we used sunflower oil in the ex-vivo experiment, without knowing if it is
a good “mimic” of the vertebral bone marrow and whether the T1W sequence used really
captured the potential differences in fat spectrum (R2* effects). Until further
confirmation of the results with biopsy or spectroscopy, others would have to apply
the exact same T1W imaging parameters to utilize the described ex-vivo approach.In conclusion, these results demonstrate a vertebral fat signal ratio relationship to
age. The fatty conversion of the bone marrow during life presented a linear increase
of 10% T1 signal ratio per decade with the 1.5-T scanner.
Authors: James F Griffith; David K W Yeung; Heather Ting Ma; Jason Chi Shun Leung; Timothy C Y Kwok; Ping Chung Leung Journal: J Magn Reson Imaging Date: 2012-02-15 Impact factor: 4.813
Authors: Thomas Baum; Samuel P Yap; Michael Dieckmeyer; Stefan Ruschke; Holger Eggers; Hendrik Kooijman; Ernst J Rummeny; Jan S Bauer; Dimitrios C Karampinos Journal: J Magn Reson Imaging Date: 2015-02-02 Impact factor: 4.813
Authors: Tiffany Y Kim; Ann V Schwartz; Xiaojuan Li; Kaipin Xu; Dennis M Black; Dimitry M Petrenko; Lygia Stewart; Stanley J Rogers; Andrew M Posselt; Jonathan T Carter; Dolores M Shoback; Anne L Schafer Journal: J Bone Miner Res Date: 2017-08-09 Impact factor: 6.741
Authors: Gary P Liney; Clare P Bernard; David J Manton; Lindsay W Turnbull; Chris M Langton Journal: J Magn Reson Imaging Date: 2007-09 Impact factor: 4.813
Authors: D Jaramillo; T Laor; F A Hoffer; D J Zaleske; R H Cleveland; B R Buchbinder; T K Egglin Journal: Radiology Date: 1991-09 Impact factor: 11.105