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Journal of Dentistry logoLink to Journal of Dentistry
. 2019 Sep;20(3):159–164. doi: 10.30476/DENTJODS.2019.44904

Correlation between Skeletal Age and Metacarpal Bones and Metacarpophalangeal Joints Dimensions

Abdolaziz Haghnegahdar DMD, MsC 1, Hamidreza Pakshir DMD, MsC 2, Ilnaz Ghanbari DMD 3
PMCID: PMC6732183  PMID: 31579689

Abstract

Statement of the Problem:

Currently, two major methods have been introduced for bone age assessment using left hand radiography. The first approach is Greulich and Pyle, which is very subjective. The second method is Tanner and Whitehouse, which is very time consuming and its morphological criteria are not quantitative, therefore it is hardly used.

Purpose:

The purpose of this study is to evaluate the relationship between skeletal age and bone size and joint space measurements among Asian children using hand radiographs and using this correlation as an aid in determining bone age.

Materials and Method:

In this analytic research, 304 hand radiographs from Asian children with normal development have been included in this study (155 female, 149 male). Two radiologists using Greulich and Pyle method assessed their bone ages. The 2nd-5th metacarpal bones length and width and 2nd-5th metacarpophalangeal joints width and length were manually measured by Adobe Photoshop and compared with subjects’ skeletal age. Pearson correlation was used to determine the relationship.

Results:

Pearson correlation between bone age and metacarpal bones length was 0.902-0.938; metacarpal bones width was 0.452-0.850; metacarpophalangeal joints width was 0.656 - 0.811, and metacarpophalangeal joints length was 0.920 - 0.947.

Conclusion:

Regarding Pearson correlation, metacarpophalangeal joints length, metacarpal bones length, metacarpophalangeal joints width, and metacarpal bones width showed significant relationship with bone age, respectively. These measurements can be used as accessory criteria for bone age assessment using left hand radiography, to reduce inter-observer reading differences.

Keywords: Skeletal age , Metacarpal bones , Metacarpophalangeal joints , Dimensions

Introduction

Bone age assessment and its comparison with chronological age is a common measure for diagnosis of pediatric syndromes, growth disorders, and endocrine problems[1]. Biological development is more accurately described by bone age than chronological age[2]. Bone age is also used to predict final height and for correcting bone deformities when orthopedic surgery is planned[3]. Bone age assessment is mainly based on recognition of changes in maturity indicators in hand radiographs including calcification centers and bone morphological features[3].

The most common method to evaluate bone age is using Greulich and Pyle atlas (1950)4. Using this approach, the radiologist compares an individual’s hand radiograph with a series of standard images in the atlas. The most similar image is selected and its age is considered as the individual’s bone age.[3] Simplicity and speed in bone age determination has made this atlas the most popular method; however, this approach is very subjective. Inter-observer reading differences ranging from 0.37 to 0.6 years and intra-observer reading differences ranging from 0.25 to 0.96 years have been reported[5-6].

A more subjective method was introduced by Tanner and Whitehouse in 1975[7]. Using this approach, bone age is determined from the sum of developmental scores from twenty ossification centers[7]. Since this approach is both complicated and time-consuming, it is rarely used.

With the advent of digital imaging, many investigators have tried to develop computer-based methods to determine bone age. Currently, several software have been introduced that can extract morphological features from hand radiographs and assess bone age regarding these informations. However, converting these morphological features into quantitative measures for bone age determination has been hindered due to the great variability in development of multiple bones in hand and wrist[8-12].

Regarding the wide usage of Greulich and Pyle atlas and its shortcomings, we have tried to find and introduce indices that are more objective in hand radiographs and subsequently, using them as an accessory data to increase inter- and intra-observer reliability in bone age determination.

This study was conducted to evaluate the correlation between skeletal age and 2nd to 5th metacarpal bones length and width and 2nd to 5th metacarpophalangeal joints length and width and to determine their normative values so that they can be employed as a quantitative measurements in assessing bone age.

Materials and Method

In this study, we enrolled 304 digital left hand radiographs out of 333 radiographies available from normal Asian subjects that were derived from digital hand atlas data base system (available from http//www.ipilab.org/ BAAweb/)[13]. The system includes 1103 left hand radiographs from normally developed children of four races: Asian, African-American, Hispanic, and Caucasian, both male and female. These radiographs are available for education and research only.

Exclusion criteria comprised of the subjects that were chronologically younger than 3 years (27 cases), and radiographs with unacceptable quality (2 cases).

Each radiograph was read by two radiologists using Greulich and Pyle atlas and the bone age was assessed based on their agreement. For measurements, first, the resolution of every image was determined using Photostudio (version 5.5). The resolution of all radiographs was equal to 250 dpi (dot per inch).

In the next phase, Adobe Photoshop CS5 Extended (Middle Eastern, version 12) was used for image processing and measurements. The processing phase was conducted for sharpening and edge detection, during which smart sharpening filter was used. It was set on 500% and 5X radius. The measurement scale was appropriately customized regarding the resolution of images (250 pixel=25 millimeters). All measurements were acquired in millimeters.

The ruler tool was used for linear measurements of metacarpal bones length and width and metacarpophalangeal joints width and length. The measurements indicated by L1, was considered the length of the line drawn by ruler tool. The zoom level was set on 200% while measuring the width and length of joints and bones width, and was set on 100% while measuring bones length.

Metacarpal bones length and width were measured as shown in Figure 1. The line drawn to measure each bone length was parallel with the long axis of the diaphysis region of the bone. The thinnest part of each bone was measured as its width. Metacarpophalangeal joints width and length were measured as shown in Figures 2 and 3. The line drawn to measure each joint space width was parallel with the long axis of the adjacent proximal phalangeal bone diaphysis.

Figure1.

Figure1

2nd Metacarpal bones length and width in hand radiographs

Figure2.

Figure2

4th Metacarpophalangeal joint width in hand radiographs

Figure3.

Figure3

4th Metacarpophalangeal joint length in hand radiograph

Finally, for each subject, 17 features were acquired, including bone age, 2nd-5th metacarpal bones length and width and 2nd-5th metacarpophalangeal joints width and length. All 17 records for each of the 304 subjects were manually entered and saved in two Microsoft Office Excel worksheets (one for male subjects and one for female subjects).

The linear correlations between estimated bone ages and 2nd to 5th metacarpal bones length and width and 2nd to 5th metacarpophalangeal joints width and length were assessed using SPSS (version 17) by Pearson correlation coefficient (p< 0.001).

Results

In this study, hand radiographs of 155 female subjects (50.99%) and 149 male subjects (49.01%) were included. Chronological age of female subjects ranged from 3 to 19 years (mean=11.96) and male subjects ranged from 4 to 19 years (mean=12.27). Table 1 shows the Pearson correlation between bone age and each feature. All features showed a significant correlation with bone age (p< 0.001). A strong correlation (r: 0.924 to 0.947) was found between bone age and both metacarpal bones length and metacarpophalangeal joints length. Metacarpophalangeal joints width and bone age showed a close negative correlation (r: -0.656 to -0.811). Metacarpal bones width and bone age had a close positive correlation in male subjects (r: 0.671 to 0.850), in female subjects this relationship was positive too (r: 0.452 to 0.729). Tables 2 to 5 show the mean values of metacarpal bones and metacarpophalangeal joints dimensions.

Table 1.

The results of Pearson correlation test between bone age and bones and joints dimensions

Pearson Correlation between Bone age Male Female
2nd Metacarpophalangeal joint width 0.780- -0.656
2nd Metacarpophalangeal joint length 0.945 0.920
3rd Metacarpophalangeal joint width -0.793 -0.803
3rd Metacarpophalangeal joint length 0.947 0.925
4th Metacarpophalangeal joint width -0.806 -0.811
4th Metacarpophalangeal joint length 0.946 0.934
5th Metacarpophalangeal joint width -0.747 -0.704
5th Metacarpophalangeal joint length 0.946 0.940
2nd Metacarpal bone length 0.936 0.912
2nd Metacarpal bone width 0.850 0.729
3rd Metacarpal bone length 0.935 0.911
3rd Metacarpal bone width 0.799 0.684
4th Metacarpal bone length 0.935 0.902
4th Metacarpal bone width 0.671 0.489
5th Metacarpal bone length 0.938 0.913
5th Metacarpal bone width 0.699 0.452

Table 2.

Metacarpophalangeal joints length normative values

Bone Age 2nd Metacarpophalangeal Joint length Normative Values 3rd Metacarpophalangeal Joint length Normative Values 4th Metacarpophalangeal Joint length Normative Values 5th Metacarpophalangeal Joint length Normative Values
Female Male Female Male Female Male Female Male
3 7.658 6.680 7.488 6.600 6.700 5.580 5.437 3.070
4 7.903 7.738 7.814 7.630 6.849 6.782 5.581 5.424
5 9.244 8.172 9.026 8.282 7.874 7.294 6.744 6.000
6 10.010 9.033 9.818 8.905 8.842 7.837 7.340 6.552
7 10.659 9.178 10.331 9.117 9.160 8.074 7.916 6.869
8 11.583 10.528 11.053 10.136 9.695 9.004 8.841 7.952
9 12.510 11.168 11.750 10.555 10.670 9.222 9.530 7.968
10 12.553 11.961 11.891 11.450 10.668 10.010 10.185 8.701
11 12.798 12.713 12.123 12.048 11.153 10.626 10.806 9.920
12 13.388 13.288 12.670 12.566 11.749 10.969 11.384 10.242
13 13.507 14.648 12.959 13.941 11.937 12.483 11.448 11.957
14 13.725 15.590 13.195 15.166 12.136 13.568 11.729 13.118
15 14.050 15.540 13.753 15.161 12.668 13.534 12.027 13.046
16 13.974 16.174 13.446 15.442 12.320 13.888 11.866 13.188
17 14.224 15.917 13.755 15.438 12.618 14.029 12.196 13.294
18 14.225 16.189 13.598 15.679 12.845 14.227 12.243 13.785
19 16.100 15.678 13.833 13.708

Table 3.

Metacarpophalangeal joints width normative values

Bone Age 2nd Metacarpophalangeal Joint width Normative Values 3rd Metacarpophalangeal Joint width Normative Values 4th Metacarpophalangeal Joint width Normative Values 5th Metacarpophalangeal Joint width Normative Values
Female Male Female Male Female Male Female Male
3 2.495 3.320 2.575 3.550 2.703 3.500 2.417 4.590
4 2.280 3.050 2.364 3.352 2.437 3.512 2.156 3.136
5 1.956 2.686 2.042 2.766 2.080 2.940 1.906 2.376
6 1.838 2.618 1.857 2.723 1.945 2.823 1.697 2.452
7 1.894 2.447 1.849 2.526 1.821 2.486 1.527 2.229
8 1.854 2.240 1.796 2.196 1.811 2.182 1.720 2.172
9 1.680 2.230 1.550 2.110 1.550 2.248 1.490 2.033
10 1.819 2.145 1.784 2.120 1.619 2.248 1.501 1.968
11 1.751 1.959 1.601 1.866 1.574 1.729 1.473 1.740
12 1.806 1.992 1.631 1.899 1.556 1.796 1.468 1.699
13 1.621 1.944 1.540 1.949 1.577 1.848 1.475 1.828
14 1.689 2.008 1.534 2.013 1.502 1.885 1.357 1.918
15 1.521 1.970 1.451 1.759 1.402 1.680 1.368 1.563
16 1.574 1.870 1.493 1.764 1.391 1.650 1.276 1.704
17 1.547 1.749 1.368 1.747 1.348 1.642 1.312 1.606
18 1.385 1.611 1.313 1.493 1.200 1.488 1.205 1.475
19 1.463 1.465 1.248 1.223

Table 4.

Metacarpal bones length normative values

Bone Age 2nd Metacarpal Bone Length Normative Values 3rd Metacarpal Bone Length Normative Values 4th Metacarpal Bone Length Normative Values 5th Metacarpal Bone Length Normative Values
Female Male Female Male Female Male Female Male
3 38.963 34.820 37.122 32.800 33.250 29.600 30.047 24.980
4 39.237 38.322 37.322 36.596 33.367 32.572 30.081 29.454
5 44.850 41.138 42.850 38.944 37.630 34.378 34.616 31.536
6 46.947 45.195 45.228 43.782 39.810 39.070 36.337 35.832
7 48.762 44.809 47.559 43.161 41.881 38.250 38.346 34.820
8 51.430 49.296 50.139 47.962 44.414 42.528 40.653 39.342
9 54.520 51.503 53.520 49.868 47.310 44.387 42.980 41.032
10 53.688 52.293 51.763 50.482 45.729 44.335 41.891 40.558
11 54.958 56.749 53.292 55.088 46.985 49.194 43.307 45.426
12 58.429 57.735 56.241 56.126 49.928 49.632 46.884 45.448
13 60.507 61.464 58.132 59.309 51.874 52.828 47.994 48.657
14 61.478 66.976 59.164 64.582 52.844 57.745 48.931 53.185
15 63.316 66.324 60.988 64.867 54.012 57.779 49.610 53.250
16 61.684 70.760 58.970 68.544 52.340 60.660 48.863 56.342
17 63.158 68.111 61.207 65.547 54.228 58.774 50.214 54.291
18 63.973 68.467 60.928 66.194 54.213 59.582 50.825 55.213
19 67.028 64.880 57.033 53.640

Table 5.

Metacarpal bones width normative value

Bone Age 2nd Metacarpal Bone Width Normative Values 3rd Metacarpal Bone Width Normative Values 4th Metacarpal Bone Width Normative Values 5th Metacarpal Bone Width Normative Values
Female Male Female Male Female Male Female Male
3 5.185 5.060 5.343 4.960 4.602 4.360 6.107 5.050
4 5.051 5.194 5.104 5.134 4.287 4.588 5.364 5.718
5 5.658 5.568 5.760 5.756 4.800 5.028 6.278 6.122
6 5.287 5.518 5.227 5.368 4.697 4.672 5.810 5.988
7 5.613 5.851 5.588 5.982 4.887 5.098 5.823 6.488
8 5.813 6.088 6.070 5.696 5.166 4.984 6.565 6.146
9 6.570 5.963 6.200 6.057 4.620 5.220 7.080 6.540
10 6.458 6.252 6.160 6.230 5.158 5.603 6.256 6.548
11 6.298 6.633 6.242 6.204 5.148 5.240 6.423 6.721
12 6.651 6.624 6.541 6.531 5.376 5.582 6.596 6.863
13 6.801 7.231 6.689 7.018 5.392 6.034 6.656 7.069
14 6.654 7.653 6.464 7.213 5.340 6.089 6.794 7.491
15 7.006 7.531 6.684 7.033 5.289 6.034 6.719 7.409
16 6.841 8.022 6.651 7.464 5.355 6.176 6.599 7.382
17 6.834 8.185 6.634 7.694 5.284 6.241 6.652 7.603
18 6.880 8.155 6.743 7.676 5.113 6.287 6.523 7.882
19 8.155 7.610 5.875 7.895

Discussion

To date, all methods that have been introduced for bone age assessment, both conventional and automatic, are based on assessment of morphological features of bones and calcification centers. Weight and height had been the only quantitative indices in determining bone age.

In this study, we have introduced 16 quantitative indices, including bones and joints measurements, to be used for bone age estimation. In 2006 and 2008, Pfeil et al.[14-15] determined normative values for metacarpophalangeal and interphalangeal joints width using computer-aided joint space analysis (CAJSA) in 896 subjects from 6 to 95 years of age, in order to provide an index for early diagnosis of osteoarthritis and rheumatoid arthritis. Their studies showed a significant continuous decrease in joints width especially up to the age of 26 [14-15]. Since they measured the reduction and mean values of joints width only, and the age groups were significantly wide (5 years), and since their study was based on chronological age, their results may not be compared with this study. Considering the significant changes in joint space width that occurs from birth to age 20, we studied and introduced this value as one of quantitative indicators of bone age.

In 2010, Thodberg et al.[16] introduced new software to determine the pediatric bone index, using metacarpal bones length, width, and cortical thickness. However, these measurements have never been compared with bone age, and the measurements were used to determine bone mass in children. Nevertheless, these studies and similar researches have introduced software, which can measure bones and joints dimensions faster and more accurately, which can be used to accelerate extracting and utilizing these measurements for bone age assessment.

Regarding the results of this study, metacarpophalangeal joints measurements (especially length) and metacarpal bones length have revealed a strong correlation with bone age; therefore, we primarily suggest these values to be used as accessory indices in bone age assessment.

Regardless of the significant results of this study, increasing the number of the subjects can definitely increase the accuracy of both correlations and mean values. The current study has focused on metacarpal bones, metacarpophalangeal joints; however, further studies regarding other regions of hand radiographs such as phalangeal and carpal bones, and proximal and distal-interphalangeal joints are suggested. Utilizing available software for extracting these values would increase speed and precision in measurements and eventually help this method be easier and more applicable.

In this study, we have only enrolled Asian subjects. However, African-American, Hispanic, and Caucasian subjects can be further investigated and their normative values can be extracted.

Another limitation of this study is that these measurements are useful in normally developed children within normal range of body statue; such developmental problems should be investigated with traditional methods although they are more subjective.

Conclusion

A strong correlation was found between bone age and metacarpal bones length. Similarly, metacarpophalangeal joints length also showed a close correlation with skeletal age. Therefore, these quantitative features can be used as accessory indices for bone age estimation of individuals, at least in doubtful cases. Other measurements can be used together with these values to increase reliability and accuracy in bone age determination.

Footnotes

Conflict of Interest: None declared.

References

  • 1.Poznanski AK, Hernandez RJ, Guire KE, Bereza UL, Garn SM. Carpal length in children– a useful measurement in the diagnosis of rheumatoid arthritis and some concenital malformation syndromes. Radiology. 1978; 129:661–668. doi: 10.1148/129.3.661. [DOI] [PubMed] [Google Scholar]
  • 2.Tanner JM, Whitehouse RH, Cameron N, Marshall WA, Healy MJR, Goldstein H. Assessment of skeletal maturity and prediction of adult height (TW3 Method) 3rd ed. London: WB Saunders, Harcourt Publishers Ltd; 2001. pp. 110–117. [Google Scholar]
  • 3.Pyle SI, Waterhouse AM, Greulich WW. A radiographic standard of reference for the growing hand and wrist. 1st ed. Cleveland, OH: The Press of Case Western Reserve University; 1971. pp. 73–86. [Google Scholar]
  • 4.Greulich WW, Pyle SI. Radiographic atlas of skeletal development of the hand and wrist. 2nd ed. California: Stanford University Press; 1959. pp. 61–64. [Google Scholar]
  • 5.Roche AF, Rohmann CG, French NY, Dávila GH. Effect of training on replicability of assessments of skeletal maturity (Greulich-Pyle) Am J Roentgenol Radium Ther Nucl Med. 1970; 108: 511–515. doi: 10.2214/ajr.108.3.511. [DOI] [PubMed] [Google Scholar]
  • 6.King DG, Steventon DM, O'Sullivan MP, Cook AM, Hornsby VP, Jefferson IG, et al. Reproducibility of bone ages when performed by radiology registrars: an audit of Tanner and Whitehouse II versus Greulich and Pyle methods. Br J Radiol. 1994; 67: 848–851. doi: 10.1259/0007-1285-67-801-848. [DOI] [PubMed] [Google Scholar]
  • 7.Tanner JM, Whitehouse RH, Marshall WA, Healy MJR, Goldstein H. Assessment of skeletal maturity and prediction of adult height. 2nd ed. London, UK: Academic Press; 1975. pp. 92–98. [Google Scholar]
  • 8.Tanner JM, Gibbons RD. A computerized image analysis system for estimating Tanner-Whitehouse 2 bone age. Horm Res. 1994; 42: 282–287. doi: 10.1159/000184210. [DOI] [PubMed] [Google Scholar]
  • 9.Tanner JM, Oshman D, Lindgren G, Grunbaum JA, Elsouki R, Labarthe D. Reliability and validity of computer-assisted estimates of Tanner-Whitehouse skeletal maturity (CASAS): comparison with the manual method. Horm Res. 1994; 42:288–294. doi: 10.1159/000184211. [DOI] [PubMed] [Google Scholar]
  • 10.Dickhaus H, Wastl S. Computer assisted bone age assessment. Medinfo. 1995; 8 Pt 1: 709–713. [PubMed] [Google Scholar]
  • 11.Cao F, Huang HK, Pietka E, Gilsanz V. Digital hand atlas and web-based bone age assessment: system design and implementation. Comput Med Imaging Graph. 2000; 24: 297–307. doi: 10.1016/s0895-6111(00)00026-4. [DOI] [PubMed] [Google Scholar]
  • 12.Pietka BE, Pośpiech S, Gertych A, Cao F, Huang HK, Gilsanz V. Computer automated approach to the extraction of epiphyseal regions in hand radiographs. J Digit Imaging. 2001; 14: 165–172. doi: 10.1007/s10278-001-0101-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Gertych A, Zhang A, Sayre J, Pospiech-Kurkowska S, Huang HK. Bone age assessment of children using a digital hand atlas. Comput Med Imaging Graph. 2007; 31: 322–331. doi: 10.1016/j.compmedimag.2007.02.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Pfeil A, Böttcher J, Seidl BE, Heyne JP, Petrovitch A, Eidner T, et al. Computer-aided joint space analysis of the metacarpal-phalangeal and proximal-interphalangeal finger joint: normative age-related and gender-specific data. Skeletal Radiol. 2007; 36: 853–864. doi: 10.1007/s00256-007-0304-8. [DOI] [PubMed] [Google Scholar]
  • 15.Pfeil A, Böttcher J, Schäfer ML, Seidl BE, Schmidt M, Petrovitch A, et al. Normative reference values of joint space width estimated by computer-aided joint space analysis (CAJSA): the distal interphalangeal joint. J Digit Imaging. 2008; 21 Suppl 1: 104–112. doi: 10.1007/s10278-007-9031-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Thodberg HH, van Rijn RR, Tanaka T, Martin DD, Kreiborg S. A paediatric bone index derived by automated radiogrammetry. Osteoporos Int. 2010; 21: 1391–1400. doi: 10.1007/s00198-009-1085-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

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