Quantification of fat deposition in bone marrow in the lumbar vertebra by proton MRS and in-phase and out-of-phase MRI for the diagnosis of osteoporosis

Abstract

The goal for this study was to investigate if proton MRS (1H-MRS) and out-of-phase and in-phase MRI can quantify the fat deposition in bone marrow within the lumbar vertebra that can be used to distinguish well between osteoporosis patients and healthy control subjects. Sixty-eight subjects participated in this study. The diagnostic results from dual-energy x-ray absorptiometry served as the gold standard, which was able to separate the subjects into osteoporosis (38 subjects) and non-osteoporosis group (30 subjects). Then the 68 subjects were further scanned by 1H-MRS and in-phase and out-of-phase MRI and the findings from the imaging methods were also compared and analyzed. It was found that the measured signal intensity ratio (SIR), lipid-water ratio (LWR) and fat fraction (FF) in L2 vertebra from the two imaging methods were able to identify the fat deposition in bone marrow, which could be used to diagnose osteoporosis. Diagnostic accuracy for osteoporosis based on identified SIR, LRW and FF was analyzed by using ROC curves. Our findings suggested that statistically significant differences were identified between osteoporosis patients and healthy subjects. The sensitivity and specificity equal to 78.9% and 75.9% for SIR, 79.2% and 66.7% for LRW, 71.4% and 72.4% for FF, can be achieved when fat deposition-related parameters in bone marrow from the lumbar vertebra are used as classifiers. Our results showed that fat deposition-related parameters including fat content in bone marrow and water content in the lumbar vertebra are clearly different between the osteoporosis and non-osteoporosis group, suggesting that both 1H-MRS and in-phase and out-of-phase MRI can be used for diagnosing osteoporosis and monitoring its progression.

Keywords

1H-MRS in-phase and out-of-phase MRI bones osteoporosis dual-energy x-ray absorptiometry

1 Introduction

Osteoporosis is a devastating disease that affects about 10 million Americans in US [1]. The major symptoms of osteoporosis are the low bone density, and structural deterioration of bones such as bone fragility and increased risk of fracture. Besides the reduced bone mineral content, osteoporosis will also lead to trabecular depletion, and fat deposition in bone marrow in the lumbar vertebra that is considered to be negatively correlated with the bone mass density (BMD) [2, 3]. In particular, low back pain caused by osteoporosis is widely recognized as one of the most common metabolic bone diseases. There are no clinical signs and symptoms for this disease until vertebral compression fractures occur. As a result, highly sensitive imaging technologies are essential for the early detection of osteoporosis, which can significantly reduce the medical cost and improve the quality of life.

To identify the fat deposition in bone marrow and bone density alterations in low back influenced by osteoporosis, dual-energy x-ray absorptiometry (DXA), quantitative CT and MRI have been implemented for the diagnosis of osteoporosis [4 –7]. Interestingly, DXA is currently the gold standard for the detection of BMD in osteoporosis and for monitoring its progression [8]. In addition, due to the high imaging resolution, 1H-MRS and in-phase and out-of-phase MRI are emerging as potential tools for noninvasively imaging bone marrow fat in clinical practice [9–10]. In-phase and out-of-phase MRI is a water and fat separation technology that is based on the Larmor frequency difference between water protons and fat protons in living tissues. In in-phase and out-of-phase MRI, two echoes are captured, in which one echo is generated if the fat and the water signals are in opposite phases while additional echo is obtained if they have the same phases. Due to its advantages of separating fat tissues promptly, wide compatibility and high signal-noise ratio, in-phase/ out-of-phase water and fat separation technology has been widely utilized in the detection of fat tissue in bone marrow. In addition, 1H-MRS makes full use of point resolved spectroscopy (PRESS) serial, which is able to identify fat molecules and water molecules based on chemical-shift imaging theory. In a recent study, it has been shown that the vertebral bone marrow fat could be effectively detected [11], suggesting that 1H-MRS and in-phase and out-of-phase MRI do have the capability of detecting osteoporosis. Importantly, 1H-MRS can detect fat content and fat/water ratio in bone marrow precisely, which plays an essential role in the study of osteoporosis pathogenesis [12].

While 1H-MRS is an excellent tool for identifying the bone fat mass, it is technically demanding and needs advanced post-processing (around 2 min). In contrast, in-phase and out-of-phase MRI only requires a much shorter acquisition time and easier post-processing(around 50 s), in which the MRI sequences are generated due to the different chemical shifts from the fat and water that can be used to evaluate the fat accumulation in humans [13]. To make full use of the findings of the two technologies, 1H-MRS and out-of-phase and in-phase MRI were implemented in this study to show if they could reliably detect osteoporosis for low back pain patients. With DXA as the gold standard, the features from the two imaging techniques are also carefully compared to see if a good correlation exists for the findings between them. Interestingly it is observed from the imaging results that both 1H-MRS and in-phase and out-of-phase MRI show their promises for early detection of osteoporosis quantitatively and noninvasively.

2 Methods and materials

2.1 Subjects, clinical examination and DXA measurements

Sixty-eight subjects participated in this study from 05/2013 to 09/2013 : 38 subjects with osteoporosis and 30 cases without osteoporosis. All the 68 subjects (22 females and 16 males, average age for 63.2 years old, the age ranged from 42 to 73 for the osteoporosis group; 14 females and 16 males, average age for 34.3 years old, the age ranged from 20 to 52 for the control group) were required to sign the informed consent documents before the clinical tests. Subjects were recruited by the Department of Spine and Orthopedics with China Southern Medical University in Guangzhou. The clinical investigation was approved by the ethical review committee of the Third Affiliated Hospital of Southern Medical University and the University of Macau.

The patients were examined by the doctors at the Southern Medical University in Guangzhou, China. DXA was used for the diagnosis of osteoporosis, which also served the gold standard for the present work. According to the lumbar DXA results, 38 cases were diagnosed with osteoporosis while 30 cases were with normal bone mass excluding cases of the tumor, fresh fractures, infection and other metabolic diseases.

2.2 MRI, in-phase and out-of-phase MRI and 1H-MRS measurements and image analysis

MRI, 1H-MRS and in-phase and out-of-phase MRI were conducted on the same day for each subject or completed in 5 days when there were unforeseen reasons. Two radiologists independently participated in the 1H-MRS and in-phase and out-of-phase MRI study and they were blinded about the results of DXA.

2.3 Regular MRI examination

For the examination using MRI 1.5T scanner (Philips Achieva; 15ch phased-arrayed spine coil), the scanning sequences included sagittal view T2 weighted image (T2WI), transverse view T2WI and sagittal view T1 weighted image (T1WI). For sagittal view T2WI, the parameters were: TR of 2740 ms, TE of 100 ms, FOV of 160 mm×302 mm, acquisition matrix of 176×238, gap of 0 mm, slice thickness of 4 mm, and NEX(number of exciting) of 2. According to transverse view T2WI, the parameter were listed as follows: TR, 2308 ms; TE, 120 ms; FOV, 160 mm×302 mm; acquisition matrix, 280×210; gap, 0 mm; slice thickness, 4 mm. In terms of sagittal view T1WI, we had TR of 400 ms, TE of 8.0 ms, FOV of 160 mm×302 mm, acquisition matrix of 160×210, gap of 0 mm, slice thickness of 4 mm, flip angle of 90° and NEX of 1.

2.4 Dual echo out-of-phase and in -phase MRI examination

Dual-FFE (fast field echo, FFE) scan was performed using the same 1.5T magnetic resonance imager (Philips Achieva). According to sagittal view T1W1 of dual echo imaging, we utilized TR of 150 ms, TE in-phase of 4.61 ms and out-of-phase of 2.3 ms, FOV of 48 cm×44 cm, flip angle of 90°, acquisition matrix of 256×257, slice thickness of 3.2 mm, gap of 0 mm, slice number of 15, and scanning time of 39.1 s. In terms of the transverse view T1WI for dual echo imaging, we had TR of 110 ms, TE of 2.5 ms, FOV of 480 mm×440 mm, flip angle of 80°, acquisition matrix of 256×217, slice thickness of 10 mm, gap of 2 mm, slice number of 12, and scanning time of 20.2 s.

2.5 1H-MRS examination

1H-MRS was performed using the same 1.5T MRI machine (Philips Achieva). Positioning in the sagittal lumbar spine was first performed, and then shimming over the MRS voxel was conducted without water suppression for the MRS acquisition preparation. The point resolved spectroscopy (PRESS) serial with the following parameters was adopted: TR of 2000 s, TE of 38 ms, point size of 15cm×15cm×15 cm, flip angle of 90°, times of collection of 8, scanning time of 20 s, and NEX of 2.

2.6 Image analysis and data processing

In consideration of the axial T1WI FS image as the anatomical location map, the intensity of out-of-phase and in-phase images generated using the vertebral body signals was obtained for all the subjects. The images were also evaluated by two radiologists who had multiple-year experience in diagnosing spinal diseases and osteoporosis. Here the mid-sagittal view of the vertebral body of L2 was chosen as ROI (region of interest) with an area of 100–105 mm² for further analysis, in which the vertebral body cortex and vascular area should be excluded, as shown in Fig. 1. Then signal intensity ratio (SIR) was considered as a classifier and calculated: SIR = signal intensity measured from the out-of-phase image/signal intensity measured from the in-phase image. The calculated results for SIR were provided in Table 1 for both osteoporosis and healthy groups. The out-of-phase and in-phase MRI of the lumbar vertebra were provided in Figs. 1 and 2 for a representative osteoporosis patient and control subject, respectively.

MRS conducted spectrum correction first by measuring water peak at 4.65 ppm and then lipid peak at 1.3 ppm. Two classifiers, lipid-water ratio LWR (LWR = L/W) and fat fraction FF (FF = LWR/1 + LWR) were generated from our 1H-MRS analysis results, in which L is lipid content and W is water content. The FF and LWR were quantitatively analyzed in the selected ROI of the L2, as shown in Fig. 3(a). The measurements mentioned above were conducted three times for each subject. The mean results were provided in Table 2 for the two groups. The 1H-MRS analysis results for a representative osteoporosis patient and healthy control subject were given in Figs. 3(b) and 3(c), respectively.

2.7 Statistical analysis

The classification problem for detecting fat deposition in bone marrow in the lumbar vertebra was conducted using a ROC curve, which displayed the distribution of the sensitivity vs. specificity under various cut-off points. The accuracy of the diagnosis results would be determined by the areas under the ROC curves (AUC).

3 Results

3.1 Results of in-phase and out-of-phase MRI

Table 1 provided the analysis results using the in-phase and out-of-phase MRI findings from both the osteoporosis group and control group. ROC analysis was performed based on SIR with various cut-off points and the calculated ROC curves were displayed in Fig. 4.

According to the analysis results in Table 1, the mean age for the osteoporosis and control group was 63.2±8.1 and 38.1±9.4 years, respectively. And the averaged SIR values of the osteoporosis and control group was 0.498±0.160 and 0.350±0.097, respectively. Inspecting Table 1, we observed big differences from the imaging results between the osteoporosis group and control group. We found that the SIR is able to distinguish well between osteoporosis and healthy control in the majority of the subjects. In addition, it was revealed from the results in Table 1 that with increased age, subjects are more likely to develop osteoporosis.

Diagnostic accuracy of osteoporosis based on SIR values was analyzed by using ROC curves with different diagnostic thresholds of SIR. It was found from Fig. 4 that SIR values are useful to reliably separate the healthy subjects from osteoporosis patients, in which the sensitivity of 0.789 and specificity of 0.667 could be obtained. Using the SIR value of 0.385 as the ROC cut-off point, the AUC is 0.784.

3.2 Results of 1H-MRS

In terms of the calculated results in Table 2, the mean value of FF for the osteoporosis and the control group was 0.732±0.176 and 3.677±3.093, respectively while the mean value of LWR for the osteoporosis and the control group was 0.573±0.211 and 2.094±1.892, respectively. It was observed from Table 2 that the mean age of osteoporosis subjects were older than that from the healthy control subjects (p < 0.05).

Diagnostic accuracy for osteoporosis with the FF and LWR values were examined by using ROC curves with different diagnostic thresholds of FF and LWR, as plotted in Fig. 5. When the FF value of 0.674 was used as the ROC cut-off point, the area under ROC curve was 0.740 while the diagnostic sensitivity and specificity was 79.2% and 72.4%, respectively. If we adopted the LWR value of 2.063 as the ROC cut-off point, the area under ROC curve was 0.706 while the diagnostic sensitivity and specificity was 75% and 71.4%, respectively.

4 Discussion

It is widely recognized [14, 15] that the amount of fat, water, protein, mineral and other components in bone marrow varies among different ages. Previous findings have validated that the fat content in the yellow bone marrow in the vertebral body increases with increased ages whereas the water content in the red bone marrow in the vertebral body decreases with increased ages [16]. Previous work has also revealed that the fat amount (fat content) and BMD in bone marrow are negatively correlated to each other [17 –19]. The decreased BMD and increased fat amount in the yellow bone marrow with bone marrow fat degeneration in the vertebral body would result in the decreased water content in the red bone marrow, which will further generate higher values of LWR, FF, and SIR [20 –22]. These observations are in good agreement with the identified features in this work. For example, in this study the average age of control group is relatively young (38 year old) and the mean values of LWR, FF and SIR for control group are 2.09, 0.573 and 0.35, respectively while the average age of osteoporosis group is 63 and the mean values of LWR, FF and SIR for this group are 3.68, 0.732 and 0.50, respectively.

From all the reconstructed results presented, we found from Figs. 2–5 and Tables 1 and 2 that the difference in age and the fat content of L2 vertebral body between the osteoporosis patients and healthy controls seem more significant.

It was found from our investigation that there is a close linking between the fat content in bone marrow and osteoporosis disease. And the lumbar is an excellent examining organ in osteoporosis diagnosis because it can reflect the BMD over the whole body [22]. That is why we choose the lumbar as our detection target of 1H-MRS and in-phase and out-of-phase MRI. In particular, we could see from our imaging results that both 1H-MRS and in-phase and out-of-phase MRI are very efficient in the quantification of fat content in L2 bone marrow and in distinguishing osteoporosis patients from control subjects.

In conclusion, the 1H-MRS and in-phase and out-of-phase MRI imaging results revealed the fat deposition was able to be employed for diagnosing and monitoring the progression of osteoporosis, as validated by the ROC curves in Figs. 4 and 5. Further investigations are essential to find if the present imaging techniques can be extended to detect the osteoporosis at an early stage. Right now, we are combining near-infrared spectroscopy, CT and in-phase and out-of-phase MRI for the accurate quantification of fat content [23 –32], which could further improve the sensitivity and specificity for the diagnosis of osteoporosis.

Footnotes

Acknowledgments

The study is supported by SRG2013-00035-FHS Grant, MYRG2014-00093-FHS Grant, MYRG2015-00036-FHS grant from University of Macau in Macau, and FDCT grant 026/2014/A1 and FDCT grant 025/2015/A1 from Macao government.

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