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Do Changes in the Femoral Neck Box Size Make Significant Differences in Femoral Neck BMD?
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Annual Meeting Abstracts 2011 Central DXA
DO CHANGES IN THE FEMORAL NECK BOX SIZE MAKE SIGNIFICANT DIFFERENCES IN FEMORAL NECK BMD? Sarah Morgan, The University of Alabama at Birmingham Frederick Peace, School of Public Health; Nancy Nunnally, The UAB Osteoporosis Prevention and Treatment Clinic; Leandria Burroughs, The UAB Osteoporosis Prevention and Treatment Clinic The default size of the femoral neck box on a Hologic scanner is 49 x 15 pixels. Occasionally when reviewing DXA scans the size of the analyzed femoral neck box differs from 49 x 15 pixels. We hypothesized that alterations in the size of the femoral neck box would significantly change the femoral neck bone mineral density (BMD). After obtaining institutional review board approval, we systematically evaluated the effect of altering the pixel size on femoral neck BMD in the same individual. One hundred scans were randomly selected and the DXA technologists systematically changed the length of the femoral neck box by adding or subtracting pixels (51 x 15 pixels and 47 x 15 pixels). In addition, the width of the femoral neck box was systematically changed by either adding or subtracting one pixel (49 x 16 and 49 x 14). The population randomly selected was 14% male, 86% female, 25% African American, 4% Asian, 1% Hispanic and 70% Caucasian. The mean age of the population was 60 12.1 years. The BMD of differing femoral neck box size is displayed below. There was not a significant difference in the femoral neck bone mineral density, compared to the default pixel size for any other pixel box size. Clinicians should be alert to the size of the femoral neck box in pixels; however, small differences in femoral neck size have no significant effect on femoral neck BMD. Relationship between size of femoral neck box and femoral neck BMD* Size of femoral neck box (pixels) Femoral neck BMD (gm/cm2) 49 15 (default) 47 15 51 15 49 14 49 16
0.718 0.115 0.718 0.116 0.717 0.114 0.710 0.115 0.725 0.115
*
There were no significant differences in EMD.
105
Central DXA
EVALUATION OF AN AUTOMATED MORPHOMETRY SOFTWARE PROGRAM (SPINEANALYZERTM) ON VFA IMAGES Diane Krueger, University of Wisconsin Osteoporosis Clinical Research Program Joes Staal, Optasia Medical, Inc; Peter Steiger, Optasia Medical, Inc; Bjoern Buehring, Cleveland Clinic; Harry Genant, University of California San Francisco/Synarc; Neil Binkley, University of Wisconsin Osteoporosis Clinical Research Program Prior vertebral fracture increases future fracture risk. Thus, knowledge of fracture status is important in clinical practice. However, as many vertebral fractures are unappreciated, spine imaging is necessary for optimal clinical decision-making. Densitometric vertebral fracture assessment (VFA) to determine fracture status is a valuable addition to clinical densitometry. However, VFA identification of mild fractures is challenging. It is plausible that morphometry may facilitate VFA fracture identification. As such, this study evaluated the utility of SpineAnalyzerTM, a proprietary software program using 95-point morphometry, on VFA images acquired with a GE Healthcare iDXA. VFA was performed in 103 subjects (79 F/24 M). Their mean (range) age, lowest T-score (spine/hip) and BMI was 72.6 (47.7 to 91.5) years, -1.5 (+3.7 to -3.4) and 26.5 kg/m2 (17.1 to 36.5) respectively. Many individuals had spinal degenerative changes making fracture identification challenging. VFA interpretation was performed using printed images and applying the Genant visual semi-quantitative approach (VSQ) by a recognized expert whose reading was defined as the ‘‘gold standard’’ and by a non-radiologist clinician experienced in VFA interpretation. An ISCDcertified technologist used SpineAnalyzer to identify vertebral deformities in these same scans. Manual morphometry point adjustment was required on most images, primarily limited to some abnormal and/or upper thoracic vertebrae. The main outcome parameter was vertebral fracture number and grade from T4-L4 using SpineAnalyzer compared with gold standard and clinician. In this cohort, the gold standard analysis identified 53 vertebral fractures;
Journal of Clinical Densitometry: Assessment of Skeletal Health
SpineAnalyzer identified 43 and the clinician 41. For analysis as normal (VSQ 0) or fracture (VSQ 1, 2 or 3), moderate agreement was observed between the gold standard and both SpineAnalyzer and the clinician (kappa 0.54 and 0.50 respectively). When limiting evaluation to just grade 2 and 3 fractures (VSQ 0, 1 together vs. VSQ 2, 3 together) moderate agreement with the gold standard was again observed; kappa 0.57 for SpineAnalyzer and 0.56 for clinician. In conclusion, when evaluating VFAs in a cohort with substantial degenerative disease, SpineAnalyzer morphometry performed by a technologist is similar to an experienced clinician when comparing to a gold standard. Studies evaluating other populations are needed to better characterize the utility of SpineAnalyzer application to VFA image
106
Central DXA
EVALUATION OF STANDARDIZATION EQUATIONS AS A SUBSTITUTE FOR SCANNER SPECIFIC IN VIVO MEASUREMENTS Kenneth Gaither, CCBR-Syanrc, San Francisco, CA Thomas Fuerst, CCBR-Syanrc, San Francisco, CA; Gillian Moyle, CCBR-Syanrc, San Francisco, CA; Elsa Griffith, CCBR-Syanrc, San Francisco, CA Background: When switching from one scanner manufacturer to another, obtaining correction factors derived from volunteer subject measures on the two scanners is the current best practice method but these data can be logistically difficult to obtain, exposes volunteer subjects to additional radiation and is time consuming. Using published data of standardized BMD (sBMD) it is possible to create generic equations to convert from one scanner make to another which would have the advantage of being available when a scanner is no longer serviceable or volunteer subject measures are not practical. Methods: Measures of AP Spine and Femur were obtained for two volunteer subject groups on both QDR-4500’s and Prodigy’s for the purpose of creating scanner specific cross calibration correction factors. Scans were analyzed at CCBR-Synarc using standardized procedures and result data were loaded into CCBR-Synarc’s data systems for analysis. The mean and standard deviation for AP Spine and Femur data were calculated for both subject groups (Table 1). Lunar data from both subject groups were converted to Hologic equivalent data using conversion equations derived from published sBMD equations. Means and standard deviations of the generically converted data were then compared against the original in vivo Hologic data and percent differences calculated (Table 1). Results: For Group 1 and 2, mean Spine BMD for the QDR-4500, converted data and percent difference were 0.864g/cm2, 0.874g/cm2 and 1.2%; and 1.044g/cm2, 1.071g/cm2 and 2.7%. Similarly, Group 1 and 2’s mean Femur BMD for the QDR-4500, converted data and percent difference were 0.851g/ cm2, 0.834g/cm2 and -2.0%; and 0.958g/cm2, 0.988g/cm2 and 3.1%. Conclusion: Generic conversion equations were used to compare data acquired from two groups of volunteer subjects. While the generic conversion equations reduced much of the difference between the QDR-4500 and Prodigy data, there remained a significant difference between the two. This could be due to either a second order variation in the individual scanner calibrations or a systematic difference between the models used for these two subject groups and the models used for the standardization equations. This tends to suggest that using generic conversion equations may be a useful tool when no volunteer subject data is available but should not be considered an adequate or appropriate substitute for specific scanner to scanner conversion factors.
Spine Group 1
Group 2
QDR4500 Converted Percent diff. Mean SD
0.864 0.157
0.874 0.163
1.2%
QDR4500 Converted Percent diff. Mean SD
1.044 0.132
1.071 0.144
2.7%
Femur Group 1
Group 2
QDR4500 Converted Percent diff. Mean SD
0.851 0.131
0.834 0.133
-2.0%
QDR4500 Converted Percent diff. Mean SD
0.958 0.148
0.988 0.156
3.1%
Volume 14, 2011
Annual Meeting Abstracts 2011 Central DXA
DO CHANGES IN THE FEMORAL NECK BOX SIZE MAKE SIGNIFICANT DIFFERENCES IN FEMORAL NECK BMD? Sarah Morgan, The University of Alabama at Birmingham Frederick Peace, School of Public Health; Nancy Nunnally, The UAB Osteoporosis Prevention and Treatment Clinic; Leandria Burroughs, The UAB Osteoporosis Prevention and Treatment Clinic The default size of the femoral neck box on a Hologic scanner is 49 x 15 pixels. Occasionally when reviewing DXA scans the size of the analyzed femoral neck box differs from 49 x 15 pixels. We hypothesized that alterations in the size of the femoral neck box would significantly change the femoral neck bone mineral density (BMD). After obtaining institutional review board approval, we systematically evaluated the effect of altering the pixel size on femoral neck BMD in the same individual. One hundred scans were randomly selected and the DXA technologists systematically changed the length of the femoral neck box by adding or subtracting pixels (51 x 15 pixels and 47 x 15 pixels). In addition, the width of the femoral neck box was systematically changed by either adding or subtracting one pixel (49 x 16 and 49 x 14). The population randomly selected was 14% male, 86% female, 25% African American, 4% Asian, 1% Hispanic and 70% Caucasian. The mean age of the population was 60 12.1 years. The BMD of differing femoral neck box size is displayed below. There was not a significant difference in the femoral neck bone mineral density, compared to the default pixel size for any other pixel box size. Clinicians should be alert to the size of the femoral neck box in pixels; however, small differences in femoral neck size have no significant effect on femoral neck BMD. Relationship between size of femoral neck box and femoral neck BMD* Size of femoral neck box (pixels) Femoral neck BMD (gm/cm2) 49 15 (default) 47 15 51 15 49 14 49 16
0.718 0.115 0.718 0.116 0.717 0.114 0.710 0.115 0.725 0.115
*
There were no significant differences in EMD.
105
Central DXA
EVALUATION OF AN AUTOMATED MORPHOMETRY SOFTWARE PROGRAM (SPINEANALYZERTM) ON VFA IMAGES Diane Krueger, University of Wisconsin Osteoporosis Clinical Research Program Joes Staal, Optasia Medical, Inc; Peter Steiger, Optasia Medical, Inc; Bjoern Buehring, Cleveland Clinic; Harry Genant, University of California San Francisco/Synarc; Neil Binkley, University of Wisconsin Osteoporosis Clinical Research Program Prior vertebral fracture increases future fracture risk. Thus, knowledge of fracture status is important in clinical practice. However, as many vertebral fractures are unappreciated, spine imaging is necessary for optimal clinical decision-making. Densitometric vertebral fracture assessment (VFA) to determine fracture status is a valuable addition to clinical densitometry. However, VFA identification of mild fractures is challenging. It is plausible that morphometry may facilitate VFA fracture identification. As such, this study evaluated the utility of SpineAnalyzerTM, a proprietary software program using 95-point morphometry, on VFA images acquired with a GE Healthcare iDXA. VFA was performed in 103 subjects (79 F/24 M). Their mean (range) age, lowest T-score (spine/hip) and BMI was 72.6 (47.7 to 91.5) years, -1.5 (+3.7 to -3.4) and 26.5 kg/m2 (17.1 to 36.5) respectively. Many individuals had spinal degenerative changes making fracture identification challenging. VFA interpretation was performed using printed images and applying the Genant visual semi-quantitative approach (VSQ) by a recognized expert whose reading was defined as the ‘‘gold standard’’ and by a non-radiologist clinician experienced in VFA interpretation. An ISCDcertified technologist used SpineAnalyzer to identify vertebral deformities in these same scans. Manual morphometry point adjustment was required on most images, primarily limited to some abnormal and/or upper thoracic vertebrae. The main outcome parameter was vertebral fracture number and grade from T4-L4 using SpineAnalyzer compared with gold standard and clinician. In this cohort, the gold standard analysis identified 53 vertebral fractures;
Journal of Clinical Densitometry: Assessment of Skeletal Health
SpineAnalyzer identified 43 and the clinician 41. For analysis as normal (VSQ 0) or fracture (VSQ 1, 2 or 3), moderate agreement was observed between the gold standard and both SpineAnalyzer and the clinician (kappa 0.54 and 0.50 respectively). When limiting evaluation to just grade 2 and 3 fractures (VSQ 0, 1 together vs. VSQ 2, 3 together) moderate agreement with the gold standard was again observed; kappa 0.57 for SpineAnalyzer and 0.56 for clinician. In conclusion, when evaluating VFAs in a cohort with substantial degenerative disease, SpineAnalyzer morphometry performed by a technologist is similar to an experienced clinician when comparing to a gold standard. Studies evaluating other populations are needed to better characterize the utility of SpineAnalyzer application to VFA image
106
Central DXA
EVALUATION OF STANDARDIZATION EQUATIONS AS A SUBSTITUTE FOR SCANNER SPECIFIC IN VIVO MEASUREMENTS Kenneth Gaither, CCBR-Syanrc, San Francisco, CA Thomas Fuerst, CCBR-Syanrc, San Francisco, CA; Gillian Moyle, CCBR-Syanrc, San Francisco, CA; Elsa Griffith, CCBR-Syanrc, San Francisco, CA Background: When switching from one scanner manufacturer to another, obtaining correction factors derived from volunteer subject measures on the two scanners is the current best practice method but these data can be logistically difficult to obtain, exposes volunteer subjects to additional radiation and is time consuming. Using published data of standardized BMD (sBMD) it is possible to create generic equations to convert from one scanner make to another which would have the advantage of being available when a scanner is no longer serviceable or volunteer subject measures are not practical. Methods: Measures of AP Spine and Femur were obtained for two volunteer subject groups on both QDR-4500’s and Prodigy’s for the purpose of creating scanner specific cross calibration correction factors. Scans were analyzed at CCBR-Synarc using standardized procedures and result data were loaded into CCBR-Synarc’s data systems for analysis. The mean and standard deviation for AP Spine and Femur data were calculated for both subject groups (Table 1). Lunar data from both subject groups were converted to Hologic equivalent data using conversion equations derived from published sBMD equations. Means and standard deviations of the generically converted data were then compared against the original in vivo Hologic data and percent differences calculated (Table 1). Results: For Group 1 and 2, mean Spine BMD for the QDR-4500, converted data and percent difference were 0.864g/cm2, 0.874g/cm2 and 1.2%; and 1.044g/cm2, 1.071g/cm2 and 2.7%. Similarly, Group 1 and 2’s mean Femur BMD for the QDR-4500, converted data and percent difference were 0.851g/ cm2, 0.834g/cm2 and -2.0%; and 0.958g/cm2, 0.988g/cm2 and 3.1%. Conclusion: Generic conversion equations were used to compare data acquired from two groups of volunteer subjects. While the generic conversion equations reduced much of the difference between the QDR-4500 and Prodigy data, there remained a significant difference between the two. This could be due to either a second order variation in the individual scanner calibrations or a systematic difference between the models used for these two subject groups and the models used for the standardization equations. This tends to suggest that using generic conversion equations may be a useful tool when no volunteer subject data is available but should not be considered an adequate or appropriate substitute for specific scanner to scanner conversion factors.
Spine Group 1
Group 2
QDR4500 Converted Percent diff. Mean SD
0.864 0.157
0.874 0.163
1.2%
QDR4500 Converted Percent diff. Mean SD
1.044 0.132
1.071 0.144
2.7%
Femur Group 1
Group 2
QDR4500 Converted Percent diff. Mean SD
0.851 0.131
0.834 0.133
-2.0%
QDR4500 Converted Percent diff. Mean SD
0.958 0.148
0.988 0.156
3.1%
Volume 14, 2011