Association of ulnar variance with three-dimensional carpal alignment and demographics in asymptomatic volunteers

Abstract

Background

Several carpal pathologies are considered to be related to ulnar variance. Recently, computer-aided computed tomography (CT) analysis software was introduced to quantify three-dimensional (3D) carpal alignment with high accuracy and reliability.

Purpose

To determine the association of ulnar variance with 3D carpal alignment and demographics.

Material and Methods

A wrist of 121 asymptomatic volunteers (69 men, 52 women; mean age = 38 ± 10.4 years) was imaged in the neutral wrist position with cone-beam CT. Computer-aided CT analysis software (Bonelogic), based on segmentation and numerical modelling, was used to define ulnar variance and standardized 3D axes for all carpal bones. The association of ulnar variance with 3D carpal alignment, age of the volunteer, and side and dominance of the imaged wrist was assessed.

Results

The mean ulnar variance was −1.6 ± 1.5 mm (range = −5.3 to 2.4 mm). The mean ulnar variance was −1.9 mm and −1.1 mm in men and women (P = 0.007), respectively. Of the imaged 121 wrists, 18 (15%) had positive and 103 (85%) negative ulnar variance. There was no association between ulnar variance and any of the radio- or intercarpal angle values in either the sagittal or coronal plane (ρ = −0.16…0.17, r = −0.13….0.12). The ulnar variance showed no association with side (P = 0.51) or dominance (P = 0.27) of the imaged wrist.

Conclusion

3D carpal alignment is not affected by ulnar variance. The association of ulnar variance with sex may in part explain the difference in reported prevalence of some carpal pathologies, such as ulnar impaction syndrome and Kienböck’s disease.

Keywords

Alignment carpal computer-aided computed tomography ulnar variance wrist

Introduction

The evaluation of ulnar variance and carpal alignment is used when diagnosing wrist pathologies. Ulnar variance is the relative length of the distal articular surfaces of the ulna and radius. In positive ulnar variance, the ulnar length is increased in relation to the radius and is associated with ulnar carpal impaction syndrome and may also be a risk factor for idiopathic carpal tunnel syndrome (1). Negative ulnar variance is a condition in which the ulna is relatively shorter than the radius. This may be associated with ulnoradial impingement, Kienböck’s disease (2 –4), and post-traumatic scapholunate dissociation (5,6). Surgical interventions are used to alter the ulnar variance as a treatment in some of these disorders.

Ulnar variance is typically determined on posteroanterior (PA) radiographs by measuring the axial distance between the ulnar corner of the distal radius and the most distal cortical rim of the dome of the ulnar head excluding the ulnar styloid (7 –9). The evaluation of carpal alignment is traditionally assessed by manually tracing carpal bone axes on lateral radiographs and calculating the angles between them. Their normal values show a relatively wide range (7,10 –14). This results from anatomical variance, but the manual measurements are also unreliable due to varying methods, difficulties in identifying landmarks, and errors in projection (10 –14).

Cone-beam computed tomography (CBCT) is increasingly used in the evaluation of wrist pathologies (15,16) due to the high spatial resolution and relatively low radiation dose (17). With the introduction of computer-aided CT analysis software based on segmentation, numerical modelling, and statistical shape models, quantification of the radiographic parameters of the wrist can now be studied with high accuracy and almost perfect reliability (8,13,14). This also allows quantification of three-dimensional (3D) axes for all carpal bones allowing more detailed alignment analysis (14).

The aim of the present study was to investigate whether ulnar variance influences 3D carpal bone alignment in asymptomatic wrists using computer-aided CT analysis. In addition, the association of ulnar variance with patient age and sex, as well as side and dominance of the imaged wrist, was analyzed. The normal ranges of ulnar variance are reported using computer-aided analysis in 121 asymptomatic wrists imaged with CBCT in neutral rotation.

Material and Methods

Participants and imaging

The study was approved by the ethics committee of Helsinki University Central Hospital (HUS/147/2019) and the institutional review board (HUS/913/2019) approved the study. Written informed consent was obtained from all participants before the study.

The wrists (right/left ratio 61/60; dominant/non-dominant side ratio 63/58) of 121 volunteers (69 men, 52 women; mean age 38 ± 10.4 years; age range = 20–60 years) with no history of wrist trauma or recurrent pain were imaged with a CBCT device (Planmed Verity; Planmed Oy, Helsinki, Finland) as previously reported (13,14). Imaging was performed in a standard neutral wrist position with the shoulder at 90° of abduction, elbow at 90° of flexion, and the forearm and wrist in neutral alignment (13).

Data analysis

Images were pseudonymized and exported to the Bonelogic Ortho Hand and Wrist software (Disior Ltd., Helsinki, Finland) in Digital Imaging and Communications in Medicine (DICOM) format. The segmentation process of the software is semi-automatic and requires manual identification and labelling of each bone by placing a marker point on the rendered surface. Thereafter, the software automatically registers a numerical 3D model for each bone to obtain a patient-specific shape and measures bone orientations by specifying a 3D axis through the final shape of each bone as described earlier (9,13,14).

The geometric axis of the radius was defined using a segment in the range of 28.8–53.3 mm from the central reference point (CRP) (9) (Fig. 1). The CRP was defined as a landmark midway between the volar and dorsal ulnar rim corners of the distal articular surface of the distal radius (7,9). Ulnar variance was measured along the longitudinal axis of the radius as the distance from the most distal point of the ulnar head excluding the ulnar styloid process to the CRP (Fig. 1). Ulnar variance was positive if the CRP was more proximal and negative if the CRP was more distal. As reported previously in detail, the 3D carpal bone axes were defined as follows: geometric axis for the middle metacarpal, scaphoid, and capitate; and distal articular surface normal for the lunate, triquetrum, and hamate (14) (Fig. 2). For the radio- and intercarpal angle measurements, the coronal plane was determined by the geometric axis of the distal radius and the line connecting the tip of the radial styloid with the CRP, whereas the sagittal plane was perpendicular to the geometric axis of the distal radius and the coronal plane (14).

Fig. 1.

Reference points used for the measurement of ulnar variance. Ulnar variance was measured as the distance between the most distal point of the ulnar head excluding the ulnar styloid process and the CRP, measured along the longitudinal axis of the radius. Dotted red line: Longitudinal axis of the radius (determined between 28.8 and 53.3 mm proximally from the CRP. Green dot: CRP (determined as a landmark midway between the volar [brown dot] and dorsal [dark blue dot] ulnar rim corners of the distal articular surface of the distal radius). Orange dot: the most distal point of the head of the ulna excluding the styloid. CRP, central reference point.

Fig. 2.

Three-dimensional axes of the carpal bones in the (a) palmar and (b) radial views. Scaphoid axis (geometric), light green. Lunate axis (distal articular surface normal), yellow. Triquetrum axis (distal articular surface normal), dark purple. Capitate axis (geometric), dark green. Hamate axis (distal articular surface normal), orange. Middle metacarpal (geometric), black dotted. Radial axis (geometric), red.

Statistical analysis

Normal distribution of the ulnar variance and carpal angle measurement results was confirmed with the Kolmogorov–Smirnov and Shapiro–Wilk tests. Normally distributed data are presented as mean with standard deviation (SD) and range (minimum–maximum). Pearson correlation (r) was calculated between ulnar variance and normally distributed continuous variables. Spearman's correlation coefficient (ρ) was calculated between ulnar variance and non-normally distributed continuous variables (age, sagittal radiotriquetral angle, sagittal radiocapitate angle, sagittal radiometacarpal angle, sagittal triquetrohamate angle, coronal radioscaphoid, coronal scapholunate, coronal scaphocapitate). The correlation coefficients, whether positive or negative, were classified as strong (0.75–1), moderate (0.5–0.75), weak (0.25–0.5), or as no (0–0.25) correlation. The association of ulnar variance with class variables was assessed using the Student's t-test. A two-tailed P value <0.05 was considered statistically significant.

Results

The mean ulnar variance was −1.6 ± 1.5 mm and was in the range of −5.3 to 2.4 mm. Of all 121 imaged wrists, 18 (15%) had a positive (>0 mm) and 103 (85%) had a negative ulnar variance (<0 mm). Table 1 presents the ulnar variances according to sex (male/female), side (right/left), and dominance (dominant/nondominant) of the analyzed wrist. The results of the ulnar variance measurements showed a significant difference between men and women (P = 0.007). There was no correlation between the ulnar variance and age of the patient (ρ = 0.17). There was no correlation between the ulnar variance and any of the radio- or intercarpal angle values in the sagittal or coronal planes (ρ = −0.16…0.17, r = −0.13….0.12) (Table 2).

Table 1.

Comparison of ulnar variance according to class variables.

	Ulnar variance (mm)	P
Sex		0 . 007
Male	−1.9 ± 1.5 (−5.2 to 2.4)
Female	−1.1 ± 1.4 (−5.3 to 1.7)
Side of the imaged wrist		0.51
Right	−1.5 ± 1.4 (−5.2 to 0.9)
Left	−1.7 ± 1.7 (−5.3 to 2.4)
Dominance of the imaged wrist		0.27
Dominant	−1.4 ± 1.4 (−5.2 to 2.4)
Non-dominant	−1.7 ± 1.6 (−5.3 to 1.7)

Values are given as mean ± SD (range). Significant value shown in bold.

Table 2.

Correlation between ulnar variance and radiocarpal and intercarpal angles.

Radio- and intercarpal angle	Sagittal plane	Coronal plane
Radioscaphoid	r = −0.13	ρ = 0.16
Radiolunate	r = −1.10	r = −0.03
Radiotriqueral	ρ = −0.16	r = 0.10
Radiocapitate	ρ = −0.09	r = − 0.05
Radiohamate	r = −0.02	r = 0.10
Radiometacarpal*	ρ = 0.05	r = 0.03
Scapholunate	r = 0.03	ρ = −0.16
Scaphocapitate	r = 0.09	ρ = −0.16
Scaphotriquetral	r = 0.02	r = −0.04
Lunocapitate	r = 0.06	r = −0.04
Lunotriquetral	r = −0.02	r = 0.12
Triquetrohamate	ρ = 0.17	r = 0.03

Pearson correlation (r) or Spearman's correlation coefficient (ρ) was calculated between ulnar variance and normally or non-normally distributed continuous variables, respectively.

*Middle metacarpal.

Discussion

This study showed that ulnar variance is not associated with either sagittal or coronal alignment of any of the carpal bones in the asymptomatic wrists of healthy volunteers. This is consistent with previous results by Larsen et al. (1992) (18) and Tosun et al. (2017) (19), in which the sagittal intercarpal angles between the scaphoid, lunate, and capitate were measured manually on lateral radiographs in normal wrists. Earlier studies have demonstrated that there is a negative association between ulnar variance and triangular fibrocartilage complex thickness (20,21). However, our results demonstrate that the coronal alignments of the lunate and triquetrum representing the curvature of the second carpal arc of Gilula (14,22) are not affected by the ulnar variance. Similarly, no association between ulnar variance and the force transmitted through the ulnocarpal joint was found in cadavers with variable idiopathic ulnar variance (21), but surgical radial shortening or ulnar lengthening was seen to increase the load on the ulnocarpal side (23).

In our cohort, the mean ulnar variance was −1.6 ± 1.5 mm (range = −5.3 to 2.4 mm) in neutrally positioned asymptomatic wrists of 121 healthy volunteers. Of these, 18 volunteers had positive (>0 mm) and 103 negative ulnar variance (<0 mm). This relatively high normal variation in ulnar variance is consistent with the literature. However, the direct comparison of our numerical values with previously reported values is not reasonable, as various methods and reference points have been used for measuring ulnar variance in the literature (10 –12). Furthermore, variations in projections and in rotation of the forearm (24) and elbow flexion (25) influence ulnar variance. In the present study, ulnar variance was measured as the axial distance between the most distal point of the ulnar head and the CRP along the longitudinal axis of the distal radius, as suggested by Medoff (7,9,11). A similar method and the same reference points were used by Medoff (7) and Parker et al. (11) on PA radiographs, with reported mean ulnar variance values of −0.6 mm and −1.46 mm, respectively. In most other radiographic studies, the more proximal rim of the lunate facet of the distal radius has been used as the reference point instead of the CRP (11). This method has demonstrated the highest inter- and intra-observer reliabilities in the manual measurement of normal wrist radiographs (11). Compared with the CRP, this reference point yields greater ulnar variance values of 1.5–2 mm in normal wrists (11) due to the more proximal anatomical location of the landmark (9). However, this reference point is not optimal in clinical practice because it may represent either the volar or dorsal rim of the lunate facet in PA projection depending on the volar or dorsal angulation of the radius articular surface. The use of CRP as a reference point for ulnar variance measurement minimizes variation caused by fracture angulation (7,9). Recently, excellent reliability (ICC value 0.94) was documented for computer-aided analysis using the CRP as a reference point for the measurement of ulnar variance (8)

Our study demonstrated that negative ulnar variance is lower in men than in women. This is consistent with the results by Nakamura et al. (26), Jung et al. (24), Elsaftawy (27), and Sayit et al. (28). However, some other studies did not show any association between ulnar variance and sex (2,29,30). The association between ulnar variance and sex may in part explain that idiopathic ulnar impaction syndrome is more prevalent in women (31), whereas Kienböck's disease shows a male predominance (32,33). Although previous studies have suggested an association between negative ulnar variance and Kienböck's disease (2,3,26), the causality is uncertain (4).

In the present study, no significant differences in ulnar variance were found for age. In the literature, some studies suggest that the relative length of the ulna increased (26,34) or decreased (2) with age, whereas others have found no association (29,30,35). There may be several reasons for this discrepancy. Our cohort included only healthy volunteers aged 20–60 years, and it is possible that advanced ulnar variance will not develop before older age along with degeneration. Consistent with our results, previous studies revealed that ulnar variance is independent to dominance and side of the imaged wrist (29). However, ulnar variance is not symmetrical in right and left wrists, but there is a side-to-side difference of ≥1 mm in more than one-third of healthy volunteers (29).

Our computer-aided CT analysis software enables a highly accurate and reliable assessment of 3D carpal alignment and ulnar variance (13,14). Furthermore, the coronal and sagittal measurements were projective measurements performed on anatomically specified planes, thus avoiding variation in imaging projections during the scanning procedure. Each bone was manually identified and labelled in the software. Visually, the software captured all bones in the correct location and shape and no modelling failures were noted. CBCT allowed imaging the wrist in a standard neutral wrist position. Therefore, the analysis of anatomical parameters in the present study can be considered very comprehensive.

The present study has some limitations. First, only asymptomatic volunteers aged 20–60 years were recruited in our cohort, of which only a few patients had a markedly positive ulnar variance using the CRP as a reference point. Further studies are needed to examine the ulnar variance in patients with increased age, with greater positive variance, and with secondary positive ulnar variance. Ulnar impaction syndrome results in a spectrum of triangular fibrocartilage complex injuries and associated lunate, triquetrum, and ligamentous damage that may be manifested as carpal malalignment. Second, the wrists were imaged only in the neutral position. Ulnar variance has a dynamic nature and is at its maximum in pronation and grip (24).

In conclusion, there was no association between ulnar variance and carpal alignment in asymptomatic wrists of healthy volunteers. There was a greater idiopathic ulnar variance in women than in men. No association between ulnar variance and age, side or dominance was seen. This knowledge may help to elucidate the relationship between ulnar variance and various wrist pathologies.

Footnotes

Acknowledgments

The authors thank Disior Ltd. for developing the software, Planmed Ltd. for providing the facilities for imaging, and Pasi Ohtonen for conducting the statistical analysis.

Declaration of conflicting interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: EW has owned stock in Disior Ltd., Helsinki, Finland and sold them in January 2022. The other authors have no conflicts of interest to declare.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the University of Helsinki and Helsinki University Hospital. The authors have not had any writing assistance.

ORCID iD

Eero Waris

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