• View in gallery
    Figure 1—

    Representative transverse CT and MR images obtained for the assessment of subchondral bone density in the left metacarpal condyle of a horse with subchondral bone sclerosis. A—Each limb was placed lateral side down over a Cann-Genant density calibration phantom, which was used to correct CT attenuation values. B—Reformatted dorsal CT image of the metacarpophalangeal joint illustrating the localization of 1-mm-thick transverse images that were obtained at 5 (c), 6 (d), and 7 (e) mm proximal to the subchondral plate of the third metacarpal condyle. C—Transverse CT image of the third metacarpal condyle at level c in panel B illustrating the locations of six 40-mm2 ROIs for QCT attenuation measurements. D—Transverse CT image of the third metacarpal condyle at level d in panel B. E—Transverse CT image of the third metacarpal condyle at level e in panel B. F—Transverse 3-mm-thick T1-GRE image obtained 6 mm proximal to the subchondral plate illustrating the locations of QMRI signal measurements. An additional 150-mm2 circular ROI was placed in the air as close as possible to the limb as a correction phantom.

  • View in gallery
    Figure 2—

    Illustrations of the QMRI assessment of subchondral bone density in the palmar metacarpal region of a horse performed with dorsal T1-GRE and dorsal T2*-FIESTA images. A—Sagittal T1-GRE image illustrating the palmar (dashed line) and dorsal (solid line) assessment planes of the left metacarpal condyle. B—Dorsal T1-GRE image at the palmar aspect of the third metacarpal condyle illustrating the placement of three 40-mm2 ROIs that were centered 6 mm proximal to the distal extent of the condyle. C—Dorsal T2*-FIESTA image at the palmar aspect of the third metacarpal condyle illustrating the placement of three 40-mm2 ROIs that were centered 6 mm proximal to the distal extent of the condyle. For each MR imaging sequence, mean SI values were recorded in the 6 ROIs and corrected by use of the mean SI value obtained from an additional 150-mm2 ROI (not represented) that was placed in the air as close as possible to the limb. Notice the signal reduction in the medial and lateral palmar regions in this horse with osteoarthritis and subchondral bone sclerosis, which correlated to the hyperattenuation (increased bone density) detected via CT in Figure 1.

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Correlation of signal attenuation–based quantitative magnetic resonance imaging with quantitative computed tomographic measurements of subchondral bone mineral density in metacarpophalangeal joints of horses

Julien OliveDépartement des Biomédecine, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC J2S 7C6, Canada.

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Marc-André d'AnjouDépartement des Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC J2S 7C6, Canada.

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Kate AlexanderDépartement des Sciences Cliniques, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC J2S 7C6, Canada.

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Guy BeauchampDépartement des Pathologie, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC J2S 7C6, Canada.

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Christine L. TheoretDépartement des Biomédecine, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC J2S 7C6, Canada.

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Abstract

Objective—To evaluate the ability of signal attenuation–based quantitative magnetic resonance imaging (QMRI) to estimate subchondral bone mineral density (BMD) as assessed via quantitative computed tomography (QCT) in osteoarthritic joints of horses.

Sample Population—20 metacarpophalangeal joints from 10 horse cadavers.

Procedures—Magnetic resonance (MR) images (dorsal and transverse T1-weighted gradient recalled echo [GRE] and dorsal T2*-weighted GRE fast imaging employing steady-state acquisition [T2*-FIESTA]) and transverse single-slice computed tomographic (CT) images of the joints were acquired. Magnetic resonance signal intensity (SI) and CT attenuation were quantified in 6 regions of interest (ROIs) in the subchondral bone of third metacarpal condyles. Separate ROIs were established in the air close to the joint and used to generate corrected ratios and SIs. Computed tomographic attenuation was corrected by use of a calibration phantom to obtain a K2HPO4-equivalent density of bone. Correlations between QMRI performed with different MR imaging sequences and QCT measurements were evaluated. The intraobserver repeatability of ROI measurements was tested for each modality.

Results—Measurement repeatability was excellent for QCT (R2 = 98.3%) and QMRI (R2 = 98.8%). Transverse (R2 = 77%) or dorsal (R2 = 77%) T1-weighted GRE and QCT BMD measurements were negatively correlated, as were dorsal T2*-FIESTA and QCT (R2 = 80%) measurements. Decreased bone SI during MR imaging linearly reflected increased BMD.

Conclusions and Clinical Relevance—Results of this ex vivo study suggested that signal attenuation–based QMRI was a reliable, clinically applicable method for indirect estimation of subchondral BMD in osteoarthritic metacarpophalangeal joints of horses.

Abstract

Objective—To evaluate the ability of signal attenuation–based quantitative magnetic resonance imaging (QMRI) to estimate subchondral bone mineral density (BMD) as assessed via quantitative computed tomography (QCT) in osteoarthritic joints of horses.

Sample Population—20 metacarpophalangeal joints from 10 horse cadavers.

Procedures—Magnetic resonance (MR) images (dorsal and transverse T1-weighted gradient recalled echo [GRE] and dorsal T2*-weighted GRE fast imaging employing steady-state acquisition [T2*-FIESTA]) and transverse single-slice computed tomographic (CT) images of the joints were acquired. Magnetic resonance signal intensity (SI) and CT attenuation were quantified in 6 regions of interest (ROIs) in the subchondral bone of third metacarpal condyles. Separate ROIs were established in the air close to the joint and used to generate corrected ratios and SIs. Computed tomographic attenuation was corrected by use of a calibration phantom to obtain a K2HPO4-equivalent density of bone. Correlations between QMRI performed with different MR imaging sequences and QCT measurements were evaluated. The intraobserver repeatability of ROI measurements was tested for each modality.

Results—Measurement repeatability was excellent for QCT (R2 = 98.3%) and QMRI (R2 = 98.8%). Transverse (R2 = 77%) or dorsal (R2 = 77%) T1-weighted GRE and QCT BMD measurements were negatively correlated, as were dorsal T2*-FIESTA and QCT (R2 = 80%) measurements. Decreased bone SI during MR imaging linearly reflected increased BMD.

Conclusions and Clinical Relevance—Results of this ex vivo study suggested that signal attenuation–based QMRI was a reliable, clinically applicable method for indirect estimation of subchondral BMD in osteoarthritic metacarpophalangeal joints of horses.

Alterations to subchondral BMD variably occur during development of osteoarthritis. Results of several studies1–3 have linked subchondral bone sclerosis to cartilaginous loss in the disease process, and it seems widely accepted that subchondral bone alteration is a manifestation of cyclic-overload metacarpophalangeal osteoarthritis.4–6 Although the temporal changes in bone and cartilage have yet to be clearly defined, their interdependence justifies dual assessment in clinical settings as well as in animals with experimentally induced osteoarthritis.7

In the preceding 2 decades, the use of various techniques such as DEXA, peripheral QCT, micro-CT, and conventional QCT for image-based quantitative assessment of trabecular bone density and architecture has been investigated.8–10 Unlike DEXA, the tomographic nature of peripheral and conventional QCT allows independent evaluation of trabecular and cortical bone densities and obviates interference by periarticular osteophytes,11,12 thereby justifying their consideration as gold-standard methods for the assessment of mineral density in specific subchondral regions.12,13

More recently, different methods of quantitative measurement of bone density involving MR imaging have also been developed, primarily focusing on the problem of osteoporosis.14–26 By use of high-resolution MR imaging, the trabecular network can be directly visualized in a manner similar to that of histomorphometry, but with the drawback of long acquisition times that limit its clinical applicability.21,22,25,27,28 Another method does not require high spatial resolution. It measures MR imaging relaxation variables, which are sensitive to the local magnetic field heterogeneity induced by the differences in magnetic susceptibility between bone trabeculae and bone marrow as well as by the orientation of the trabeculae relative to the static magnetic field.16,19,20,26,29 Alternatively, trabecular bone volume fraction can be measured but at a spatial resolution that is not sufficient to discriminate individual elements.17,23 This third method is based on signal attenuation due to fractional occupation of the imaging voxel by trabecular bone, which does not generate a signal, in contrast to the high signal generated by adipose tissue that fills the bone marrow.

Although QMRI assessment of osteoporosis appears promising, the capacity of QMRI to assess subchondral bone sclerosis in the context of osteoarthritis has been less extensively investigated.2,3,30–32 As a predilection site for osteoarthritis and stress fractures in equine athletes, the third metacarpal condyle has been the focus of much research. The subchondral bone density in this proximal component of the metacarpophalangeal joint in horses has been studied by use of DEXA33,34 and QCT1,35–37 and correlates variably with articular cartilage degeneration.

In horses with naturally occurring or experimentally induced osteoarthritis, MR imaging is a single imaging technique with which all joint components can be assessed, and the additional ability to quantify BMD via MR imaging may provide further insight into osteoarthritis severity and progression. The purpose of the study reported here was to evaluate the ability of signal attenuation–based QMRI to estimate subchondral BMD as assessed via QCT in osteoarthritic joints of horses and determine the repeatability of QCT and QMRI assessments.

Materials and Methods

Joints—Twenty paired thoracic limbs from 10 mature horses (5 Standardbreds and 5 Thoroughbreds) were selected at a slaughterhouse. The choice of racing breeds, as opposed to other breeds, was based on the anticipation of finding osteoarthritic changes (varying from minor to severe) among metacarpophalangeal joints. Within 48 hours after slaughter of the horses, each limb was sectioned proximally to the carpus and then refrigerated at 4°C until the imaging procedures were performed. Computed tomography and MR imaging were performed within 1 hour after retrieval of each limb from the refrigerator, thereby ensuring uniform temperature throughout the limb. Articular cartilage surfaces were then immediately inspected grossly to detect any osteoarthritis process.

Gross inspection of cartilage—For the purpose of evaluating the severity of osteoarthritis, gross cartilage lesions were assessed. Fourteen areas were designated within the metacarpophalangeal joints: 6 areas for the proximal phalanx, 6 areas for the third metacarpal condyle, and 1 area for each proximal sesamoid bone. Indian ink (3% dilution) was applied to all articular surfaces to enhance detection of eroded hyaline cartilage.38 A semiquantitative morphological grading system (scale of 0 through 3)38–40 was used to assess the cartilage, independently of the size or shape (circular vs linear) of the lesion. The grading system was as follows: grade 0 = smooth and regular cartilage, grade 1 = mildly irregular surface but no ink staining, grade 2 = partial-thickness erosion with ink staining, and grade 3 = full-thickness erosion and visual evidence of the subchondral bone. Gross scores were assigned by consensus between the primary author (JO) and a board-certified equine surgeon (CLT). Only the most severe lesion of each joint area was considered. Individual area scores (range, 0 to 3) were summed to produce a total joint score (range, 0 to 42).

MR imaging—Each metacarpophalangeal joint was positioned in lateral recumbency at the isocenter of a 1.5-T MR imaging unita by use of a 2-part phased-array, 4-channel, soft torso coil.a Dorsal and transverse 3-D T1-GRE (slice thickness/gap, 3.0 mm/0 mm; time to echo, 5.0 milliseconds; repetition time, 28.0 milliseconds; flip angle, 15°; number of acquisitions, 2; field of view, 170 mm; matrix, 320 × 192; and pixel size, 0.89 × 0.53 mm) and dorsal 3-D T2*-FIESTA (slice thickness/gap, 2.0 mm/−1.0 mm; time to echo, 1.8 milliseconds; repetition time, 4.9 milliseconds; flip angle, 55°; number of acquisitions, 3; field of view, 260 mm; matrix, 384 × 384; and pixel size, 0.68 × 0.68 mm) images were obtained. The total acquisition time was approximately 18 minutes. The MR imaging coil and sequences were selected and optimized to be clinically applicable to live horses.

CT image acquisition—Each joint underwent third-generation, single-slice helical CT.b To standardize BMD measurements, each limb was placed longitudinally in lateral recumbency on a Cann-Genant solid K2HPO4 reference phantom,c which was composed of 5 parallel rods of different reference materials: water; K2HPO4 in concentrations of 50, 100, and 200 mg/mL; and high-density polyethylene.41 Transverse images were acquired helically (slice thickness, 1.0 mm; pitch, 1; display field-of-view, 25 cm [including the entire phantom]; exposure, 120 kVp and 120 mA; number of rotations/s, 1; matrix, 512 × 512; and pixel size, 0.49 × 0.49 mm) and reconstructed with a high-pass filter (bone) algorithm. The spatial resolution provided by this clinically applicable CT scanner was expected to assess macrostructural changes in, rather than fine microstructure of, bones.

CT bone density measurements—Images were analyzed using a diagnostic workstationd by a single evaluator (JO). For each limb, 1-mm-thick contiguous CT images were evaluated at 5, 6, and 7 mm from the most distal aspect of the metacarpal condyle. A preliminary evaluation revealed that these positions systematically ensured avoidance of the subchondral bone plate in horses without trabecular bone sclerosis at the most distopalmar and distodorsal aspects of the metacarpal condyle. In each image, a circular 150-mm2 ROI was centrally placed in each phantom rod. The mean Hounsfield unit values measured in each rod were used to construct a bone density linear regression formula and were converted into K2HPO4-equivalent BMD values as follows:

article image

where μROI is the voxel intensity (Hounsfield units) in an ROI of the reference material, ρwater is the water equivalent BMD of material within the measured ROI, ρK2HPO4 is the K2HPO4-equivalent BMD of material within the measured ROI, and Bref is an imaging technique–specific variable characteristic of the Hounsfield unit scale.41,42

Six 40-mm2 circular ROIs were then defined in each image—in the dorsolateral, dorsomedial, palmarolateral, and palmaromedial portions of the distal metacarpal condyle and in the dorsal intermediate and palmar intermediate aspects of the sagittal ridge (Figure 1). Preliminary MR image evaluations determined that regions without trabecular bone sclerosis had subchondral bone plate thickness consistently < 1 mm. Therefore, ROIs were defined to avoid cortical bone and the healthy subchondral bone plate and were therefore placed 1 mm from the osteochondral junction. Then, metacarpal ROI Hounsfield unit values were converted into K2HPO4-equivalent BMD values (mg/mL) according to the linear regression equation. The measurements obtained from 7-mm-deep images of 10 randomly selected limbs were repeated by the same evaluator after an interval of 2 weeks.

Figure 1—
Figure 1—

Representative transverse CT and MR images obtained for the assessment of subchondral bone density in the left metacarpal condyle of a horse with subchondral bone sclerosis. A—Each limb was placed lateral side down over a Cann-Genant density calibration phantom, which was used to correct CT attenuation values. B—Reformatted dorsal CT image of the metacarpophalangeal joint illustrating the localization of 1-mm-thick transverse images that were obtained at 5 (c), 6 (d), and 7 (e) mm proximal to the subchondral plate of the third metacarpal condyle. C—Transverse CT image of the third metacarpal condyle at level c in panel B illustrating the locations of six 40-mm2 ROIs for QCT attenuation measurements. D—Transverse CT image of the third metacarpal condyle at level d in panel B. E—Transverse CT image of the third metacarpal condyle at level e in panel B. F—Transverse 3-mm-thick T1-GRE image obtained 6 mm proximal to the subchondral plate illustrating the locations of QMRI signal measurements. An additional 150-mm2 circular ROI was placed in the air as close as possible to the limb as a correction phantom.

Citation: American Journal of Veterinary Research 71, 4; 10.2460/ajvr.71.4.412

MR bone density measurements—Six 40-mm2 circular ROIs (Figure 1) were similarly placed in 1 transverse, 3-mm-thick T1-GRE image that was obtained at a mean depth of 6 mm from the distal aspect of the metacarpal condyle, and the mean SI (in gray level) was reported for each ROI. To avoid errors due to inherent contrast and noise variations that occur among individuals and imaging sessions, a 150-mm2 ROI was defined in the air as close as possible to the limb on every image. Two separate corrections were applied to the data to evaluate their respective impact on the correlation. First, a noise correction (SIcorr) was calculated as follows: SIcorr = (SIROI2 − SIAir2)0.5, where SIROI is the mean condyle ROI SI and SIAir is the mean air ROI SI. This calculation generated an SI value in gray level.23 Next, a simple ratio (RSI) between the SIROI and the SIAir was calculated. On 3-mm-thick dorsal T2*-FIESTA and T1-GRE images obtained at the dorsal and palmar portions of the condyle, 40-mm2 circular ROIs were placed in the same bone regions as in the transverse plane by use of the software multiplanar localizer, and the same measurement technique was used (Figure 2). The localizer was composed of a reference line on 1 plane to indicate the localization of another image in another plane, with both images being visualized at the same time. Measurements obtained from transverse T1-GRE images of 10 randomly selected limbs were repeated by the same evaluator (JO) after an interval of 2 weeks.

Figure 2—
Figure 2—

Illustrations of the QMRI assessment of subchondral bone density in the palmar metacarpal region of a horse performed with dorsal T1-GRE and dorsal T2*-FIESTA images. A—Sagittal T1-GRE image illustrating the palmar (dashed line) and dorsal (solid line) assessment planes of the left metacarpal condyle. B—Dorsal T1-GRE image at the palmar aspect of the third metacarpal condyle illustrating the placement of three 40-mm2 ROIs that were centered 6 mm proximal to the distal extent of the condyle. C—Dorsal T2*-FIESTA image at the palmar aspect of the third metacarpal condyle illustrating the placement of three 40-mm2 ROIs that were centered 6 mm proximal to the distal extent of the condyle. For each MR imaging sequence, mean SI values were recorded in the 6 ROIs and corrected by use of the mean SI value obtained from an additional 150-mm2 ROI (not represented) that was placed in the air as close as possible to the limb. Notice the signal reduction in the medial and lateral palmar regions in this horse with osteoarthritis and subchondral bone sclerosis, which correlated to the hyperattenuation (increased bone density) detected via CT in Figure 1.

Citation: American Journal of Veterinary Research 71, 4; 10.2460/ajvr.71.4.412

Equivalent images obtained via CT and MR imaging were registered and matched by calculation of their respective distance from a reference slice on which the metacarpal condyle subchondral plate became first apparent when viewing images from distal to proximal locations. During CT and MR image acquisitions, special care was taken to avoid any obliquity. The reference 3-mm-thick transverse T1-GRE image of the subchondral bone plate was considered to represent a mean depth of 0 mm (−1.5 to +1.5 mm). The next contiguous image represented a mean depth of 3 mm (+1.5 to +4.5 mm), and the next image represented a mean depth of 6 mm (+4.5 to +7.5 mm). Similarly, the reference 1-mm-thick CT image was considered to represent a mean depth of 0 mm (−0.5 to + 0.5 mm); additional 1-mm-thick CT images were considered to represent a mean depth of 5 mm (+4.5 to +5.5 mm), 6 mm (+5.5 to +6.5 mm), and 7 mm (+6.5 to +7.5 mm).

Statistical analysis—Repeatability of results obtained via QCT or QMRI was evaluated by use of linear mixed-effect model regression. The K2HPO4-equivalent BMD QCT measurements obtained at multiple depths (three 1-mm-thick images at 5, 6, and 7 mm) for a single metacarpal subregion were averaged (QCTmean) for comparison with the QMRI measurement obtained at the same level (3-mm-thick images at depths of 5 to 7 mm). A linear mixed-effect model, with the individual considered as a random effect to account for the multiple measurements for a single limb, was applied to these QCT and QMRI data. The outcome was the MR image RSI, and the fixed effect was either the K2HPO4-equivalent BMD measurement or another MR image RSI for the specific comparison of T1-GRE and T2*-FIESTA sequences. To evaluate the degree of precision of the QMRI method, the mean of all 95% SDs of the QCT values derived from each QMRI measurement was calculated for each MR sequence. Mean QCT BMD and mean QMRI RSI were compared by use of a Student t test. A value of P < 0.05 was considered significant. All statistical analyses were performed using dedicated softwaree by an experienced statistician (GB).

Results

Gross inspection and MR imaging of the 20 cadaveric limbs revealed that the metacarpal condyles had a variable degree of osteoarthritis-related lesions including marginal osteophytosis, increased subchondral bone density, joint effusion, and cartilage damage. Mean articular cartilage gross score was 21 (range, 6 to 39); prevalence of cartilage lesions scored as grade 0, 1, 2, or 3 was 17.5%, 32.9%, 32.9%, and 16.8%, respectively.

Repeatability of measurements was excellent for QCT (R2 = 98.3%) and QMRI (R2 = 98.8%). There was no systematic bias observed between the 2 evaluations for either technique. Mean ± SD corrected BMD values for each condylar ROI obtained via QCT and with both MR image signal correction methods were calculated (Table 1).

Table 1—

Mean ± SD corrected BMD values for third metacarpal condylar ROIs in 20 metacarpophalangeal joints from 10 horse cadavers obtained via QCT and via 2 QMRI signal correction methods.

Type of imageMR signal correction methodThird metacarpal condylar region
DLDIDMPLPIPM
Transverse CT857.8 ± 79.9a755.2 ± 100.0b912.0 ± 68.4c881.4 ± 72.8a,d700.9 ± 126.3e907.4 ± 67.3c,d
Transverse T1-GRERSI7.9 ± 2.1f8.4 ± 2.7f,h5.7 ± 2.3g6.5 ± 2.6g9.9 ± 3.1h6.3 ± 2.2g
SIcorr84.7 ± 22.290.9 ± 32.561.2 ± 26.269.3 ± 30.7107.2 ± 36.566.9 ± 25.1
Dorsal T1-GRERSI7.4 ± 1.7j8.0 ± 1.8j5.7 ± 2.0k5.7 ± 1.8k8.8 ± 3.0j5.7 ± 1.7k
SIcorr89.0 ± 21.398.2 ± 27.468.7 ± 27.369.3 ± 26.2107.3 ± 37.568.5 ± 23.2
Dorsal T2*-FIESTARSIr8.9 ± 3.1m13.3 ± 4.6n6.1 ± 3.0p6.4 ± 3.2p13.4 ± 5.9n6.7 ± 3.4p
SIcorr792.9 ± 283.91,199.5 ± 44.4540.3 ± 75.9572.8 ± 318.51,233.3 ± 580.7597.1 ± 316.1

Phantom-corrected QCT results are expressed as K2HPO4-equivalent BMD (mg/mL); QMRI results are expressed as ratios (RSI, which is the ratio of bone ROI SI to air SI [SIROI:SIAir]) and as SI values for noise-corrected QMRI data (SIcorr = [SIROI2 – SIAir2]0.5).

DI = Dorsointermediate. DL = Dorsolateral. DM = Dorsomedial. PI = Palmarointermediate. PL = Palmarolateral. PM = Palmaromedial.

For transverse CT, values with different superscript letters differ significantly (P < 0.05).

For transverse T1-GRE, values with different superscript letters differ significantly (P < 0.05).

For dorsal T1-GRE, values with different superscript letters differ significantly (P < 0.05).

For dorsal T2*-FIESTA, values with different superscript letters differ significantly (P < 0.05).

With signal correction obtained by use of the equation SIcorr = (SIROI2 − SIAir2)0.5, significant correlations were detected between QCTmean and QMRI measurements (Table 2). These correlations were negative and considered good between T1-GRE (in either the transverse or dorsal planes) and QCTmean as well as between dorsal T2*-FIESTA and QCTmean. With signal correction obtained by use of the ratio SIROI:SIAir, similar significant correlations were detected between QCTmean and QMRI measurements and between QMRI sequences. Good, negative correlation was evident between T1-GRE (in either the transverse or dorsal planes) and QCTmean as well as between dorsal T2*-FIESTA and QCTmean. Very good correlation was also evident between dorsal T1-GRE and dorsal T2*-FIESTA and between dorsal T1-GRE and transverse T1-GRE.

Table 2—

Correlation data and regression equations for BMD values of metacarpal condylar ROIs in 20 metacorpophalangeal joints from 10 horse cadavers obtained via QCT and via 2 MR imaging signal correction methods.

VariableImaging sequence
QCT and transverse T1-GREQCT and dorsal T1-GREQCT and dorsal T2*-FIESTA
P value< 0.001< 0.001< 0.001
Correlation (r)0.880.880.89
Regression (R2 [%])777780
Regression equation (RSI values)RSI T1-GRE = (23.51 ± 0.91) − ([0.019 ± 0.001]•QCT)RSI T1-GRE = (20.78 ± 0.78) − ([0.017 ± 0.001]•QCT)RSI T2*-FIESTA = (41.66 ± 1.69) − ([0.039 ± 0.002]•QCT)
Regression equation (SIcorr values)SIcorr T1-GRE = (254.16 ± 10.19) − ([0.208 ± 0.012]•QCT)SIcorr T1-GRE = (253.49 ± 9.80) − ([0.203 ± 0.011•QCT)SIcorr T2*-FIESTA = (3,825.17 ± 156.82) − ([3.593 ± 0.180]•QCT)

See Table 1 for key.

Means of all 95% SDs of the QCTmean values derived from the QMRI ratio measurements according to the regression equation were ± 37.5 mg/mL, ± 36.1 mg/mL, and ± 37.9 mg/mL (K2HPO4-equivalent density) for transverse T1-GRE, dorsal T1-GRE, and dorsal T2*-FIESTA values, respectively.

Discussion

Interest in MR imaging for the investigation of sports-related musculoskeletal disease in horses is increasing. As high-level athletes with joints that sustain frequent naturally occurring pathological changes, racehorses can be used for experimental investigations of osteoarthritis. Magnetic resonance imaging is the only imaging technique that allows direct evaluation of all joint components, including bone. Moreover, MR imaging avoids the use of ionizing radiation and generates multiplanar images. Whereas several QMRI methods have been developed and validated to assess cartilage,43 most other features of osteoarthritis such as sclerosis are semiquantitatively assessed in whole-organ scoring schemes.44 Although the strength of correlation between QCT and QMRI may not be considered sufficiently strong to validate the described signal attenuation–based QMRI technique for precise measurement of subchondral bone density via MR imaging, the results of the present study address the interpretation of signal attenuation in the subchondral area. Our results indicated that signal attenuation–based QMRI is a reliable, clinically applicable method with which to indirectly estimate subchondral bone density changes, allowing comparison of findings over time or among individuals. Yet the sensitivity of this method for detection of subtle changes in BMD still has to be determined. Some authors have reported19 that QCT and MR imaging scanners cannot distinguish subtle changes in bone quality that may occur at the tissue level, whereas application of micro-MR imaging methods appears promising for such purposes.27

Several noninvasive methods have already been proposed and validated to assess BMD. The tomographic characteristics of QCT justify its use as a reference method for evaluation of QMRI.12,45 However, volume averaging and beam hardening artifacts may also alter QCT measurements from true bone density,46 especially in metacarpal condyles of horses, which often have pronounced bone density gradients.13,47 In the present study, we attempted to evaluate a simple, clinically applicable method to indirectly evaluate bone density on the basis of a standard clinical MR protocol and assess the method's repeatability and precision. Most of the previously described QMRI techniques require several signal corrections and data postprocessing techniques, which limit their applicability in clinical settings. In the few QMRI studies17,23 that focused on signal intensity attenuation due to fractional occupation of the imaging voxel by bone, various techniques were used to homogenize data. Some authors corrected heterogeneous sensitivity of the receiver coil as well as SI by dividing the ROI SI by that of a fat phantom reference area.23 A lack of homogeneity of the receiver coil or the static magnetic field may have distorted the data obtained in our study, but these imperfections are inherent to any MR imaging unit that is used clinically. Moreover, the simple ratio method yielded correlation of similar strength as that derived via noise correction as well as satisfactory repeatability and precision. In another study,14 a binarizing-map method obtained from gradient echo images to evaluate trabecular bone fraction yielded only moderate correlation with peripheral QCT measurement of bone density, even with pixel size as small as 0.234 mm on MR images. With regard to the data obtained in the present study, calculation of a simple ratio between SI of the ROI and that of air allowed at least partial reduction of inherent noise and contrast variations among imaged tissue sections and individuals.

Interpretation paradigms for MR images of horses have been derived from human imaging data. The signal void associated with bone in MR images is attributable to its poor mobile proton content and to the very short T2 relaxation time of the protons contained in bone that result in a very fast signal decay during image acquisition.24 It has therefore been assumed that a reduction in SI in subchondral bone relates to an increase in bone density. However, little is known about signal interpretation and its exact importance in assessment of bones in horses. Other pathological processes related to osteoarthritis, such as bone marrow lesions that are characterized by various types of lacunae cellular infiltration (eg, hematopoiesis, fibrosis,48 and sometimes necrosis49,50), may cause distortion of data in potentially all described QMRI techniques. In MR images, bone marrow lesions typically appear as ill-defined hyperintense subchondral areas on fat-suppressed, T2-weighted spin echo sequences or short-tau inversion recovery images and correspondingly hypointense on T1-weighted fast spin echo sequences or GRE sequences,48,51 thereby possibly mimicking bone sclerosis on T1-weighted sequences. The present study of metacarpophalangeal joints of horses is part of a more comprehensive MR imaging evaluation of naturally occurring osteoarthritis, and signal alterations suggesting bone marrow lesions were not seen on T2-weighted, fat-saturated sequences in the measured regions.52 Moreover, the correlation identified between QMRI and QCT, regardless of the sequence used, confirmed that the subchondral hypointensity was the result of increased mineral density, which is the only factor to explain the strong hyperattenuation detected with QCT. Hence, despite measuring different physical properties of trabecular bone by use of QMRI and QCT in the context of bone sclerosis, MR imaging SI decreases linearly when CT attenuation increases.

Via QMRI, assessment of BMD is possible at lower spatial resolution than that used in micro-MR imaging investigations. However, worse correlation between QMRI and QCT has been detected at lower resolution (pixel size, 2.4 vs 0.6 mm) by use of GRE sequences.53 Pixel size of clinical range in our study was 0.89 × 0.53 mm on T1-GRE and 0.68 mm on T2*-FIESTA sequences, but correlation might have been better with increased resolution. Correlation of T1-weighted spin echo54 and T2*-GRE53 sequences with DEXA has also been established. Correlation of a proton density-weighted sequence with direct and QCT measurement of BMD has also been proved.19 In our study, GRE sequences were chosen on clinical grounds, mainly because of their increased spatial resolution with reduced acquisition time, compared with equivalent spin echo sequences. Bone density was reflected similarly and linearly by use of T1-GRE or T2*-FIESTA in our study. These MR sequences were selected from a clinical protocol established at our institution for the routine assessment of the distal portions of equine limbs, hence the absence of additional sequences such as transverse T2*-FIESTA or transverse 1-mm-thick sequences that might have facilitated and possibly improved correlation with transverse QCT. It was the authors' impression that subchondral bone alterations were better assessed subjectively in dorsal or sagittal plane images.

Limitations to the QMRI method used in the present report and that warrant discussion include errors in manual positioning of ROIs; such errors may have affected signal measurements, although ROIs were placed similarly during QCT by use of anatomic landmarks and excluding the subchondral plate and metaphyseal cortex. Additionally, the thickness of the subchondral bone plate was probably variable among specimens, but it was deemed most important to place the ROIs consistently for comparative purposes. Manual positioning reflects clinical conditions, and given the excellent measurement repeatability, this factor may not have played a major role in the discrepancy between QCT and QMRI measurements. These positioning errors may have been more frequent when using different anatomic landmarks on 2 planes. However, a strong correlation between QMRI intensity measurements obtained in transverse and dorsal GRE images was identified. This indicates that, although transverse images were initially selected to match the slices obtained via CT, use of another plane such as the dorsal plane may be equally accurate for estimation of BMD. Other factors related to the MR imaging technique or system (eg, heterogeneous noise, nonuniformity in the radiofrequency field amplitude, and effects of the slice profile17), susceptibility artifacts created by bone trabeculae and lacunae interfaces in gradient echo sequences,29,55 and limited resolution53 may have contributed to decreased intermodality or intersequence correlations. The use of an MR imaging fat or porosity calibration phantom might have resulted in superior correlations for QCT than did the air correction because the MR characteristics of these structures are closer to the imaging target (ie, the bone marrow).

The QCT technique used in the present study also had limitations. Use of polyethylene material is a validated technique with which to measure BMD.56–58 It has density equivalence with K2HPO4, which has attenuation coefficients and chemical characteristics comparable to potassium pyrophosphate (K4P2O7), a main constituent of bone.59 However, the polyethylene phantom rods did not include material as dense as the high-density value ranges that are commonly detected in equine limbs. Because a more dense calcium-based phantom was not available at our facility, it was assumed that higher densities could be extrapolated from the linear standard regression data generated from the polyethylene phantom.1 Moreover, this phantom was previously used for the same purpose,1 and a highly linear relationship was found between dipotassium and calcium-based phantoms with regard to measurement of BMD.60 A CT-based technique used to measure bone density is also inherently limited by volume-averaging errors. Slice thickness of 1 mm (acquired helically) was chosen to limit volume averaging and allow reformatting in other planes for subsequent investigations.52 Although volume averaging with the subchondral plate might have occurred because of the CT slice thickness, this was a systematic error that should not affect correlation because the same ROI placement technique was used for both QCT and QMRI. Pixel size was limited by the absolute necessity to include the whole phantom section in each image with the maximal available matrix size (ie, 512 × 512).

Finally, factors related to the individual limb may also influence SI measurements. Variations in bone marrow composition (hematopoietic vs fatty content) may influence bone marrow SI, although those errors are considered negligible.17 Variations in distance and tissue attenuation characteristics between ROIs and receiving coils may also affect QMRI measurements. However, all bones examined in the present study were surrounded by a constant, minimal amount of soft tissues, and the central part of receiving coil components was systematically placed on the axial and abaxial surfaces of the limb, respectively, thereby limiting variations in signal attenuation among individual acquisitions. Moreover, the joints were systematically placed at the isocenter of the magnetic field. Also, it was found that areas with low trabecular density may have poorer correlation coefficients between QMRI and QCT.53 However, subchondral bone areas physiologically have high bone density and may be less affected. Newly deposited bone that fills lacunae in the sclerosing process is less dense than the original trabeculae; thus, CT may underestimate the increase in bone volume fraction.61 Nonetheless, this newly accumulated bone may already have a low signal on MR images and may account for some distortion of the data between QCT and QMRI. Our data analysis in the present study was therefore limited to the type of tissue and the range of BMDs evaluated.

Results of the present study have confirmed that, in the context of osteoarthritis of the metacarpophalangeal joint in horses, the reduction in subchondral bone marrow SI on both T1-weighted and T2*-weighted GRE sequences was mainly and linearly attributed to an increase in BMD. Despite potential shortcomings, a signal ratio method can be used with MR imaging to indirectly estimate BMD. More research is justified to clarify the importance of BMD changes associated with osteoarthritis in horses as well as in other species.

ABBREVIATIONS

BMD

Bone mineral density

CT

Computed tomography

DEXA

Dual-energy x-ray absorptiometry

FIESTA

Fast imaging employing steady-state acquisition

GRE

Gradient recalled echo

MR

Magnetic resonance

QCT

Quantitative computed tomography

QMRI

Quantitative magnetic resonance imaging

ROI

Region of interest

SI

Signal intensity

T1-GRE

T1-weighted gradient recalled echo

T2*-FIESTA

T2*-weighted gradient recalled echo fast imaging employing steady-state acquisition

a.

GE Signa Echospeed HDx, General Electric Healthcare, Mississauga, ON, Canada.

b.

Hi-Speed ZXi, General Electric Healthcare, Mississauga, ON, Canada.

c.

13002 Model 3 CT Calibration Phantom, Mindways Software Inc, San Francisco, Calif.

d.

Advantage Workstation 4.3, General Electric, Mississauga, ON, Canada.

e.

SAS, version 9.1, SAS Institute Inc, Cary, NC.

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Contributor Notes

Dr. Olive's present address is Service d'Imagerie Médicale, VetAgro Sup–Campus Vétérinaire, Université de Lyon, 1 Ave Bourgelat, Marcy l'Etoile F-69280, France.

Supported by a grant from the Association des Vétérinaires Equins du Québec (AVEQ).

Presented in part as an abstract at the American College of Veterinary Radiology Annual Scientific Meeting, San Antonio, Tex, October 2008.

The authors thank Sonia Bernier, Suzie Lachance, Eric Norman Carmel, and Martin Guillot for technical assistance.

Address correspondence to Dr. d'Anjou (marc-andre.danjou@umontreal.ca).