Bone marrow lesions in knee osteoarthritis: MR-assessment by manual
segmentation and computer-assisted thresholding
Purpose
The purposes of the study were to evaluate a manual segmentation method and
a computer-assisted thresholding technique for estimating bone marrow lesions
(BMLs) in knee osteoarthritis (KOA) over time and compare the results with the
most used conventional grading systems.
In the commonly used grading methods BMLs are evaluated regarding their
approximate size of the total area and in three grades. Thus, in the newly
published MOAKS method (1), representing a synthesis of the two most common
grading tools, WORMS and BLOKS (2;3), there are three grades of BMLs; grade
1=<33% BML of the total area, grade 2=33-66% and grade 3=>66%.
Material and Methods
A total of 13 patients with medial femorotibial KOA according to the ACR criteria
were examined by MRI at baseline and follow-up after 3-12 months. Female/male
ratio =12/1; median age 60.5 years (41.1-72.3). Among several sequences
performed using a 1.5 T unit (Vision, Siemens, Erlangen, Germany) with a
transmit receive four-channel knee coil, the post-contrast sagittal T1 fatsuppressed (T1FS) sequence was analyzed. The technical sequence parameters
were: TR/TE = 860/20 ms, FOV = 16 cm, slice thickness/interslice gap = 4.0/0.8
mm, matrix 256 x 256, one excitation, TA 7.23. The dose of Gadolinium (GdDTPA 0.2 mmol/ml) was standardized to 0.1 mmol/kg.
BMLs were defined as ill-delineated areas of increased signal intensity (SI) on the
post-contrast T1FS images. Volumes (mm3) of BMLs in the medial weight-bearing
femoral and tibial condyle (52 observations) were measured/calculated on
anonymized images by two observers. The manual segmentation (MS) was
performed using Agfa Impax software and 2K Bracho screens. The computer
assisted tresholding (CAT) method was performed using a graphical user interface
for drawing regions of interest (ROIs) and thresholding images written in MATLAB
(the MathWorks, Sweden) by D.P. at the Medico-technical Department, Aarhus
University Hospital.
The areas/volumes of interest of the femoral condyles were separated from the
trochlea area/volume as suggested in BLOKS/MOAKS (Figs. 1-3). The
area/volume of the tibia included the proximal 2 cm’s of the tibial condyles (MS
only). By both methods the mean SI (gray scale value, GY) plus one standard
deviation (STD) of the normal bone marrow of the lateral femoral condyle was
used as a relative reference (Figs. 1A and 2). Areas/volumes with contiguous
pixels above this gray scale threshold were considered bone marrow lesions. The
total volume of BML was obtained by multiplying the BML areas in each section
with the section thickness including the intersection gap.
By the manual segmentation, the margins of the areas of BML in each section
were constructed by a curved line joining the pixels with threshold values. The
correct position of the borderline were controlled by a 5 mm2 ROI (Figs. 1B, 6)
and the margins were adjusted if necessary. The computer calculated BML area
was based on counting (with visual coloring) the number of pixels above the
threshold in the ROI (Fig. 3, 4). Small clusters of pixels <5 and areas <3 mm2
were not registered by the CAT and manual method, respectively.
The MS and CAT method were tested regarding inter-observer reliability. The
results of MS and CAT estimation of BMLs were compared and related to a MOAKS
grading of BML.
Results
The inter-observer agreement for BML volumes by MS was good, linear weighted
kappa value 0.88 (CI 0.84-0.93) with no difference regarding femoral and tibial
volumes (kappa 0.85), respectively. Based on 24 estimations the inter-observer
agreement for BML volume by CAT was also good, linear weighted kappa values
0.84 (CI 0.79-0.89).
The CAT method failed in two examinations due to apparently uneven contrastenhancement with varying signal intensity of normal bone across the knee. A
consensus was made regarding these examinations by drawing the ROI in close
proximity to observed BML and avoiding areas of unwanted signal variation (Figs.
4-6). The consensus results were used in the comparison with the MS results.
The BML values obtained by MS and CAT, respectively, were significantly
correlated (ơ=0.94 (CI 0.89-0.96)) and the median values were similar.
MOAKS grade/percentage BML of the total femoral or tibial condyle volume were
1/<33%: n=19; 2/33-66%: n=4; 3/>66%: n=3. Detected BML changes in
volumes during follow-up were: <4%: n=15; <33%: n= 9; 33-66%: n=0;
>66%: n=2. Thus, the change over time was only detectable in two knees by
MOAKS.
Conclusion
MS and CAT can estimate BML changes over time not detectable by MOAKS. The
CAT method should, however, be used with caution.
The presented manual segmentation grading method, though time consuming,
can be used without dedicated computer software. It was found to be sensitive to
detecting even minor changes in BML volume making it advantageous specifically
given the fluctuating nature of BML (4).
Thresholding is a popular technique in image segmentation (5;6) in which a
number of pixels are selected based on pixel intensity. The results can be
obtained fast and the use of computerized thresholding therefore seems
encouraging but should be used with caution. In two of the present examinations
the CAT method failed due to the signal intensity of normal bone varying from the
outside toward the inside of the knee. The source of error is most likely due to
partial volume artifact, poor positioning of the knee inside the receiving coil, B1
inhomogeneity or poor shimming. This has not been fully explored. Furthermore,
CAT does not differentiate between pathological or physiological entities, including
e.g. blood vessels, resulting in a potential overestimation of the BML volume.
Due to large and ill-defined transitions of BMLs in KOA, precise area/volume
measurements remain a challenge. Additional grading of SI and/or dynamic
contrast MR imaging may add to clarify the clinical significance of BMLs in OA.
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