Keywords
diffusion-weighted imaging - chemical shift imaging - fat fraction - Dixon sequence
Introduction
Vertebral lesions in elderly and in patients with known malignancy are quite a common
occurrence. It can be due to various etiologies, such as degenerative changes, infections,
trauma, and malignancy.[1] The spine is the most frequent site of osseous metastasis in the body. Metastasis
from carcinoma breast, kidney, and thyroid is associated with an increased risk of
pathological fractures and compressive myelopathy.[2] It is at times difficult to differentiate from benign osteoporotic fracture as a
result of decreased bone density, especially in elderly females.[3]
Apart from this, trauma, infective spondylodiskitis, and primary vertebral neoplasm
also can present with complications such as vertebral fracture and compressive myelopathy.
Hence, it is essential to distinguish malignant and benign vertebral lesions as it
affects treatment strategy, clinical staging, and prognosis in patients with proven
malignancies.
Although histopathological diagnosis is the gold standard, it is invasive and associated
with its own complications. Also, it is sometimes not feasible, especially if the
lesion is located in the cervical spine. A positron emission tomography (PET) scan
can be useful in some cases; however, it also has its limitations in differentiating
malignant and infective lesions as both may show uptake.
Magnetic resonance imaging (MRI) is an excellent noninvasive method for the assessment
of bone marrow lesions with high spatial resolution. Apart from gross morphological
data, MRI gives information about cellular and chemical levels.[4] Conventional MRI is highly sensitive in detecting abnormality; however, it lacks
specificity. It sometimes can represent a diagnostic conundrum, specifically in case
of the elderly patients and in patients with known cases of cancer. The sensitivity
of T1-weighted (T1W), T2-weighted (T2W) imaging, and short tau inversion recovery
(STIR) sequence is quite high, but the specificity of these sequences to discriminate
between benign and malignant lesions is low. This is due to the fact that signal alterations
seen in bone marrow edema due to benign causes is similar to that observed in bony
metastasis.[4]
MRI techniques reflecting distinct aspects of the chemical environment and pathophysiology
of vertebral marrow lesions have been put forward to distinguish benign vertebral
lesions from malignant vertebral lesions with more accuracy. Diffusion-weighted imaging
(DWI) measures the random Brownian motion of water molecules.[5] Studies have shown significantly lower apparent diffusion coefficient (ADC) value
in malignant lesions compared with benign lesions.[5]
[6] There is a paucity of studies in the literature regarding the correlation of the
vertebral lesion with the vertebral marrow fat fraction (FF). In this study, we evaluated
the role of DWI and vertebral body FF obtained from chemical shift MRI to differentiate
between benign and malignant vertebral lesions.
Material and Methods
This is a cross-sectional hospital-based study performed in a tertiary care teaching
institute after obtaining ethical clearance from the institutional ethics committee.
Patients older than 18 years having vertebral lesions with or without fractures were
included. A sample size of 72 was obtained with a confidence interval of 95%. After
obtaining informed consent, the enrolled patients underwent MRI in a 3-T MRI scanner
(Discovery MR750W, GE Healthcare) using a 32-channel spine coil. The protocol is discussed
in the following section.
Magnetic Resonance Imaging Protocol
The following protocols were used: sagittal T2WI (repetition time [TR]/echo time [TE]:
4,474/85 milliseconds, field of view [FOV]: 28.0 cm, number of excitations [NEX]:
3.00); sagittal T1W (TR/TE: 671/13.5 milliseconds, FOV: 28.0 cm, NEX: 2.00); axial
T2WI (TR/TE: 4,209/85 milliseconds, FOV: 28 cm, NEX: 3.00, slice thickness: 3.0 mm,
interslice distancing: 0.3 mm); sagittal STIR (TR/TE: 4,333/68 milliseconds, FOV:
28 cm, NEX: 2.00, slice thickness of 3 mm, interslice gap of 0.3 mm); sagittal DWI
(TR/TE: 3430/69.1 milliseconds, FOV: 24 cm, b-value: 50 and 800, slice thickness: 4.0 mm, interslice distancing: 0 mm); and IDEAL-IQ
(TR/TE: 8.9/4.0 milliseconds, FOV: 40 cm, NEX: 3, echoes: 6, slice thickness: 4.0 mm,
interslice distancing: 0.4 mm). Gadolinium-based intravenous contrast was administered
on a case-to-case basis when required, and postcontrast T1WI was acquired in sagittal
and axial planes.
Computed Tomography–Guided Biopsy
Computed tomography (CT) guided percutaneous biopsy was done from vertebral lesions
as per standard management protocol. Under strict aseptic precaution, percutaneous
vertebral biopsy using a Jamshidi bone biopsy needle through the transpedicular/posterolateral
extrapedicular technique was performed after administration of adequate amount of
local anesthesia. Precaution was taken to avoid injury to exiting nerve roots and
great vessels. In the presence of multiple lesions, the largest and most approachable
lesion was selected, for example, a lumbar vertebral lesion was preferred over dorsal
and cervical vertebral lesions. In patients with associated paravertebral soft-tissue
component, both bone and soft-tissue components were biopsied simultaneously. In patients
with associated paravertebral collection, ultrasonography (USG)/CT-guided aspiration
was also done as per the feasibility. A sample for microbiological examination was
also obtained if an infection was suspected.
In patients with known primary malignancy elsewhere in the body, biopsy was not done
if there were multiple vertebral lesions considering the same as metastasis. However,
biopsy was done in the solitary indeterminate vertebral lesion in case of known malignancy
to guide the clinical staging, treatment planning, and overall prognosis of the patient.
Elderly patients with suspected osteoporotic collapse underwent a dual-energy X-ray
absorptiometry (DEXA) scan to measure bone density. A T-score of ≤ –2.5 was considered diagnostic of osteoporosis and biopsy was exempted
in these cases. Patients with a history of trauma were also exempted from vertebral
biopsy.
Reports of all of the above-mentioned investigations were collected. Patients, in
whom biopsy/aspiration was not done, were followed up either with imaging or clinically,
depending on the etiology. If the lesion appearance remained the same after 6 months
of follow-up without progression or the patient improved clinically, the lesion was
considered benign.
Data Collection and Image Analysis
MR images were transferred to the Advantage Workstation Server (AWS), GE Healthcare.
Two experienced radiologists having more than 12 years' experience analyzed the MR
images. In case of interobserver variation, final imaging diagnosis was made by consensus.
Imaging findings and qualitative and quantitative MRI parameters were recorded. MRI
features were correlated with histopathological diagnosis and also with microbiological
or DEXA scan reports and with history and clinical follow-up wherever suitable.
Involvement of vertebral bodies, posterior elements, presence of paravertebral or
epidural collection, paravertebral soft-tissue lesion, posterior vertebral bulge,
cortical disruption, and presence/absence of fracture were noted. Signal intensity
of the involved vertebra was qualitatively analyzed by comparing with that of an uninvolved
vertebra, on T1W, T2W, STIR, and DWI sequence.
Quantitative analysis of DWI was done by calculating the ADC value using “READY View”
postprocessing application. Regions of interest (ROIs) of varying sizes were drawn
over the lesion on DWI that corresponded to signal changes on the T1WI and STIR. Three
ROIs were drawn over the lesion and the ADC values were obtained. The mean ADC was
calculated by averaging them. The ADC values were also obtained from the adjacent
normal vertebrae by drawing the ROIs.
The ROI was dependent on the size of the lesion in focal discrete lesions, but in
the cases where there was diffuse vertebral marrow involvement, it was drawn as large
as possible placed in the antero-central aspect of the vertebral body avoiding the
basivertebral venous plexus and endplate degenerative changes. The ROIs varied between
10 and 60 mm2 in each lesion.
FF was obtained from the Iterative Decomposition of water and fat with Echo Asymmetry
and Least squares estimation Quantitation (IDEAL-IQ) sequence that is a modified multi-echo
Dixon technique. ROIs as placed on DWI were also placed in a similar way in the FF
image. Normalized FF was computed by dividing the FF of the involved vertebrae by
the FF of the normal-appearing vertebra.
The final diagnosis that was made on the basis of biopsy results or results of at
least 6 months of clinical or radiological follow-up. This was used as the “gold standard”
to classify the vertebral lesion as benign or malignant.
Statistical Analysis
All the statistical analyses were done using IBM SPSS 29.0 version. Continuous variables
were summarized in the form of means and standard deviation (SD) and categorical variables
were expressed as frequencies and percentages. Nonparametric variables between two
groups were compared using the Mann–Whitney U test. The correlation between two nonparametric variables wase assessed using Spearman's
rank correlation coefficient. The chi-squared test was applied for comparing categorical
variables between benign and malignant groups. Receiver operating characteristics
(ROC) curve analysis was used to find out the cutoff value for ADC, FF, and normalized
FF to determine the optimal cutoff.
The diagnostic value of diffusion restriction was examined by two-by-two contingency
tables with the ultimate classification of lesions into two broad categories, that
is, benign and malignant. The sensitivity and specificity were then calculated.
For all the statistical tests used, the level of significance was set at a p-Value less than 0.05.
Results
A total of 72 patients were included in our study. Out of the total patients enrolled,
39 (45.8%) were males. Details of the demographic findings are given in [Table 1]. Out of 72 patients, 43 cases were benign and 29 were malignant as per the final
diagnosis. CT-guided biopsy was done in 56 patients (out of which 34 turned out to
be benign and 22 malignant). The most common presenting complain was back pain in
62 patients [86.1%], followed by lower limb weakness in 6 (8.3%) and inability to
walk in 4 (5.6%) patients. Twenty-one of 72 (29.2%) patients showed solitary vertebral
lesions; the remaining 51 (70.8%) patients showed multiple vertebral involvements.
Eighty-two vertebrae were involved in the benign category, whereas 63 vertebrae were
involved in the malignant category.
Table 1
Clinical and demography of the patients in the study (n = 72)
|
Characteristics
|
Benign (n = 43)
|
Malignant (n = 29)
|
|
Mean age (y), mean ± SD (range)
|
46.86 ± 14.22 (18–82)
|
52.55 ± 13.33 (18–83)
|
|
Duration of symptoms (d), mean ± SD (range)
|
42.16 ± 26.76 (2–90)
|
37 ± 26.35 (10–90)
|
|
Sex
|
Male
|
24
|
15
|
|
Female
|
19
|
14
|
|
No. of lesions (%)
|
82 (56.6)
|
63 (43.4)
|
Abbreviation: SD, standard deviation.
Twenty-five of 43 patients in the benign category were of tubercular etiology. Other
benign causes of vertebral lesions included pyogenic spondylosis (n = 9), traumatic vertebral fracture (n = 5), and osteoporotic vertebral collapse (n = 4). The most common malignant cause included metastasis (n = 12), followed by multiple myeloma (n = 12), plasmacytoma (n = 3), Ewing's sarcoma (n = 1), and giant cell tumor (n = 1; [Table 2]). Out of 12 patients of vertebral metastasis, 7 patients had lung carcinoma, 3 had
breast carcinoma, and 2 had stomach carcinoma. Diagnosis of the same was confirmed
from biopsy from the primary site.
Table 2
MRI findings in benign and malignant vertebral lesions
|
Parameters
|
Benign (n = 43), number (%)
|
Malignant (n = 29), number (%)
|
p-Value
|
|
Hypointensity on T1WI
|
42 (97.7)
|
29 (100)
|
0.71
|
|
Hyperintensity on T2WI
|
42 (97.7)
|
28 (96.6)
|
0.54
|
|
Hyperintensity STIR
|
43 (100)
|
29 (100)
|
1
|
|
Posterior element involvement
|
24 (55.8)
|
28 (96.6)
|
<0.001
|
|
Epidural/paravertebral collection
|
30 (69.8)
|
0 (0)
|
<0.001
|
|
Paravertebral soft-tissue lesion
|
1 (3.8)
|
25 (96.2)
|
<0.001
|
|
Diffusion restriction
|
5 (11.6)
|
26 (89.7)
|
<0.001
|
|
Posterior vertebral bulge
|
1 (2.3)
|
22 (75.9)
|
<0.001
|
|
Intervertebral disk space involvement
|
26 (60.5)
|
0 (0)
|
<0.001
|
|
Fracture present
|
24 (55.8)
|
10 (34.5)
|
0.075
|
Abbreviations: MRI, magnetic resonance imaging; STIR, short tau inversion recovery;
T1WI, T1-weighted imaging; T2WI, T2-weighted imaging.
In our study, all the vertebrae in the malignant category (n = 29) and 42 (97.7%) vertebrae in the benign category showed hypointense signal on
T1WI. One vertebra in the benign category was isointense on T1W imaging in comparison
with normal marrow.
On T2WI, 42 of 43 vertebrae in benign group were hyperintense; one case of sclerotic
metastasis was hypointense. In the benign group (n = 29), 28 were hyperintense on T2WI and 1 was isointense. All the involved vertebrae,
whether benign or malignant, were hyperintense on STIR sequence.
The signal intensity of conventional MRI sequences was not statistically significant
in distinguishing between neoplastic and non-neoplastic lesions. However, some additional
findings like involvement of posterior elements and presence of paravertebral soft
tissue or abscess were significant between the two groups. Details of the MRI findings
are given in [Table 2].
We could not find a significant correlation between the ADC values of normal-appearing
vertebra and age (Spearman's correlation coefficient: –0.04; p = 0. 72). However, a weak but significant positive correlation was found between
the FF values of normal vertebrae and age (Spearman's correlation coefficient: 0.3;
p = 0.009).
Diffusion restriction was noted more commonly in the malignant lesion. FF was reduced
in both benign and malignant lesions although to a greater degree in malignant lesions
([Figs. 1] and [2]). The mean ADC value for benign lesion (1.25 ± 0.27 × 10−3 mm2/s) was significantly higher than that of malignant lesion (0.88 ± 0.19 × 10−3 mm2/s; p = 0.001). The ROC curve shows an ADC cutoff of 1.05 × 10−3 mm2/s can differentiate between benign and malignant vertebral lesion with 86% sensitivity
and 82.8% specificity, and area under the curve (AUC) of 0.9 ([Fig. 3]).
Fig. 1 Magnetic resonance imaging (MRI) of dorsal spine in a 65-year-old man with D11 vertebral
lesion. (A) Sagittal T1-weighted imaging (T1WI) and (B) T2-weighted imaging (T2WI) show T1 hypointense and T2 hyperintense lesion involving
the D11 vertebra with posterior bulge of the vertebra. The lesion appears hyperintense
on (C) diffusion-weighted imaging (DWI) as well as on (D) apparent diffusion coefficient (ADC) map suggesting T2 shine through. (E) Fat fraction (FF) of the lesion was 8.1%. (F) Histopathology shows well-formed, coalescent, epithelioid granulomas comprising
multifocal localized collections of epithelioid histiocytes admixed with small mature
lymphocytes (hematoxylin and eosin, ×200,) and patchy areas of central caseous necrosis
(black asterisk), suggestive of mycobacterial etiology.
Fig. 2 Spinal magnetic resonance imaging (MRI) of a 38-year-old woman with a biopsy-proven
plasmacytoma involving the D9 vertebra. (A) Sagittal T1-weighted imaging (T1WI), (B) T2-weighted imaging (T2WI) show T1 hypointense, T2 hyperintense, lesion involving
the body and posterior element of the D9 vertebra with an epidural component causing
cord compression. The lesion appears hyperintense on diffusion-weighted imaging (DWI)
(C) and hypointense on corresponding apparent diffusion coefficient (ADC) map. (D) The ADC value was 0.77 × 10−3 mm2/s. (E) The fat fraction (FF) of the lesion was 3.1%. (F) Histopathology, Hematoxylin eosin, × 200 shows cellular lesion comprising of plasma
cells with eccentrically placed nuclei showing moderate atypia.
Fig. 3 Receiver operating characteristic (ROC) curve showing sensitivity and specificity
of apparent diffusion coefficient (ADC), fat fraction (FF), and normalized FF in differentiating
between benign and malignant vertebral lesions.
The mean FF of vertebral lesions in the benign group was 12.7 ± 7.49, which was significantly
higher than that of the malignant group (4.04 ± 2.6; p = 0.001). The ROC curve for FF shows an AUC of 0.95. Considering a cutoff value of
FF of 6.9, benign vertebral lesions can be differentiated from malignant lesions with
a 93% sensitivity and 96.6% specificity ([Fig. 3]).
The mean normalized FF (FF of the vertebral lesion divided by normal-appearing noncontiguous
vertebra) of vertebral lesions in the benign group was 0.37 ± 0.24, which was significantly
higher than that of the malignant group (0.1 ± 0.06; p = 0.001). The ROC curve for normalized FF shows an AUC of 0.954. Considering a cutoff
value of normalized FF of 0.17, benign and malignant vertebral lesions can be differentiated
with a 90.7% sensitivity and 89.7% specificity ([Fig. 3]). Details of the ADC and FF are been given in [Table 3].
Table 3
Quantitative diffusion and CSI parameters of the benign and malignant vertebral lesions
|
Parameters
|
Benign (n = 43), mean ± SD (range)
|
Malignant (n = 29), mean ± SD (range)
|
p-Value
|
|
ADC
|
1.25 ± 0.27 (0.84–2.61)
|
0.88 ± 0.19 (0.56–1.53)
|
<0.001
|
|
Normalized ADC
ADC vertebral lesion/ADC normal-appearing vertebra
|
2.57 ± 0.78 (1.6–5.6)
|
2.02 ± 1.16 (1.16–7.5)
|
<0.001
|
|
Fat Fraction (%)
|
12.7 ± 7.49 (3.4 ± 39.7)
|
4.04 ± 2.6 (0.22–13.8)
|
<0.001
|
|
Normalized FF (FF involved vertebra/FF normal-appearing vertebra)
|
0.37 ± 0.24 (0.12- 1.2)
|
0.1 ± 0.06 (0.0–0.3)
|
<0.001
|
Abbreviations: ADC, apparent diffusion coefficient; CSI, chemical shift imaging; FF,
fat fraction; SD, standard deviation.
Discussion
This study describes the imaging findings of vertebral lesions in 72 patients and
the role of DWI and chemical shift imaging in distinguishing between benign and malignant
vertebral lesions.
Distinguishing benign from malignant vertebral lesions is often a clinical dilemma.
The limitations of modalities like plain X-ray, bone scan, CT scan, and MRI in diagnosing
benign and malignant lesions have been reported.[7] Bone scintigraphy has high sensitivity but low specificity. Fluorodeoxyglucose-PET
(FDG-PET) may distinguish between osteoporotic fractures and malignant fractures;
however, it cannot distinguish the inflammatory process from a malignancy as it shows
high uptake in both. Another disadvantage is that it exposes patients to ionizing
radiation and hence is not recommended in young patients.[8]
MRI is a noninvasive imaging modality that is often used to study the signal intensity
of bone marrow as well as the complications like vertebral fracture and compressive
myelopathy. On routine MRI, vertebral lesions are usually seen as T1 hypointense signal
and T2 hyperintense signal. STIR is even more sensitive in the detection of vertebral
lesion because the fat signal of the vertebral marrow is suppressed and even slightest
increase in water content stands out prominently.[2] The majority of cases in our study showed T1 hypointensity and T2/STIR hyperintensity.
Although MRI is highly sensitive in detecting marrow changes, it lacks specificity
because the conventional MRI sequences show similar signal intensity in both benign
and malignant vertebral lesions.[9]
[10]
Some of the coexisting findings may help in narrowing the differentials of a vertebral
lesion. Involvement of the posterior elements is common in metastasis; however, spinal
tuberculosis often affects the posterior elements of the vertebrae along with the
body and intervertebral disk. Isolated involvement of the posterior elements is rare
in tuberculosis. A combination of paravertebral collection and posterior element involvement
was found in infective lesions. Involvement of the posterior element along with a
paravertebral soft-tissue lesion is commonly seen in malignant vertebral lesions.[11] At times, organized collection or granulation tissue may mimic paravertebral soft
tissue. Intervertebral disk space is commonly involved in infective lesions, more
so in pyogenic spondylodiskitis and also in the later stage of tuberculosis. Intervertebral
disk space is almost never involved in metastasis. Many times, a diagnostic dilemma
exists, especially when there is isolated vertebral involvement without involvement
of the intervertebral disk or the paraspinal and epidural soft tissue or abscesses.
Macroscopic information obtained by routine sequences can be supplemented by DWI,
which gives information about tissue organization at the microscopic level. Brownian
motion of water molecules is affected due to pathological changes in tissue, which
alter the signal intensity. In cases of neoplastic pathologies, there is high cellularity
with increased nucleus-to-cytoplasmic ratio, which causes inhibition of movement of
water molecules resulting in restricted diffusion that is seen as hyperintense signal
on DWI and hypointense signal on ADC map. However, in cases of benign pathologies,
there is comparatively free diffusion due to abundance of cytoplasm, loose arrangement
of cells and more free water content.[12] The value of DWI in spine imaging has been successfully implied in various clinical
situations.[13]
[14]
Several studies have analyzed DWI qualitatively for neoplastic and non-neoplastic
vertebral lesions.[15] However, visual assessment of hyperintensity on DWI lacks specificity as it can
also be caused by active hematopoietic red marrow and inflammation. Quantitative analysis
of DWI through measurement of ADC has been tried by many authors.[15]
[16]
[17] The importance of ADC is that the T2 effect from diffusion images is eliminated
and a quantifiable signal is obtained, which is directly proportional to the degree
of Brownian motion of water molecules.[18]
Sheikh et al[19] reported a mean ADC value of 0.81 ± 0.19 mm2/s for malignant lesions and 1.2 ± 0.24 mm2/s for benign lesions. This is akin to many previous studies that showed higher ADC
measurements in benign vertebral lesions compared with malignant vertebral lesions.[18]
[20]
[21] We also found a significantly higher mean ADC value in benign lesions compared with
malignant lesions (p < 0.001). The results of our study are also in congruence with Allam et al who reported
85.7% sensitivity and 91.3% specificity with a cutoff value of 0.9 × 10−3 mm2/s.[22] Contrary to this, Turna et al reported that ADC measurements were not helpful in
differentiating neoplastic from non-neoplastic vertebral lesions and there was considerable
overlapping in the two groups.[23] This disparity might have arisen due to the size and placement of ROI and variations
in the technique and acquisition of MRI. This could also be due to different stages
of the pathological conditions affecting the vertebrae.
Lavdas et al[24] reported ADC varies significantly with age; however, we could not find any significant
correlation of ADC of vertebral marrow with age. It may be due to the exclusion of
patients younger than 18 years. Also, many patients were middle-aged (interquartile
range: 39–59.75 years). Another cause could be that the normal-appearing vertebra
in some cases as in infiltrative diseases like multiple myeloma may not actually be
normal.
The fundamental basis of chemical shift MRI is that hydrogen protons in water and
fat precess slightly differently. At 3 T, fat and water protons are in phase with
each other at TE of 2.24 milliseconds and out of phase at TE of 1.12 milliseconds.
This results in cyclical addition (in phase) and cancellation (out of phase) of signal
intensities of water and fat. So the presence of both water and fat molecules in a
single voxel results in signal drop on opposed phase imaging. The advantages of CSI
include a short acquisition time, high signal-to-noise ratio and no contrast administration.
IDEAL-IQ is a newer fat–water separation method based on chemical shift imaging for
assessing bone marrow FF. IDEAL-IQ is a rapid and highly reproducible method to separate
fat and water.[25] It is a method that uses the six-echo Dixon method to quantify FF by correcting
all the confounding factors like inhomogeneity effects of the main magnetic field,
T2* effects, multiple peaks in fat spectrum, T1 effects, and eddy currents, which
affect dual-echo chemical shift-encoded imaging.[26]
Estimation of FF from these methods should improve the diagnostic performance of chemical-shift
MRI in differentiating neoplastic and non-neoplastic lesions.
Kim et al[27] investigated the feasibility of FF in differentiating malignant marrow-replacing
lesions from benign red marrow deposition with a T2*-corrected FF map using a 3D volume
interpolated breath-hold gradient echo Dixon sequence. They observed that FF and normalized
FF can be used to differentiate benign vertebral lesions from malignant vertebral
lesions with sensitivity of 85.7% and specificity of 100%. FF at a cutoff of 5.26%
had high diagnostic performance (AUC: 0.98). In another study, Yoo et al[26] reported the cutoff of 6.34 with 95% sensitivity and 95% specificity for distinguishing
between benign and malignant lesions. These are in agreement with our study, where
the mean value of FF in the benign group was significantly higher than that of the
malignant group allowing differentiation between two types of lesions.
We found a weak positive correlation between the FF of normal vertebrae and age. The
FF of the vertebra increases significantly with increasing age.[28]
[29]
The ADC value, FF, and normalized FF can adequately distinguish benign vertebral lesions
from malignant ones.
The strength of our study is a good sample size and the fact that definitive diagnosis
was obtained in most of the cases. However, our study has few limitations. First,
lack of histopathological diagnosis in few cases for ethical reasons. Patients with
prior definitive diagnosis of primary malignancy elsewhere in the body, history of
trauma, and osteoporosis confirmed on DEXA scan were exempted from undergoing biopsy.
Second, although we were careful to draw the ROI that best represented the lesion,
the readers made a subjective decision on the area of the ROI and the outer margins
of the lesion. Third, no subgroup analysis was done in patients with various benign
and malignant etiologies.
Conclusion
We conclude that conventional MRI with STIR sequence is highly sensitive in the detection
of vertebral lesions; however, it cannot differentiate between a benign and a malignant
vertebral lesion. Certain features such as posterior element involvement, paravertebral
soft tissue, and collection may help in characterizing a lesion. Advanced imaging
modalities like DWI and CSI can be helpful in distinguishing between benign and malignant
vertebral lesions with more accuracy and can be added to the routine imaging protocol
while dealing with focal or diffuse vertebral lesions.
