Can patient anthropometry predict the anterior cruciate ligament footprint dimensions? - An MRI-based observational study on north Indian population

Abstract

Background

Anterior Cruciate Ligament (ACL) reconstruction is one of the most common surgeries being currently done. As we usher into the era of Individualized Anatomic Reconstruction, it is very important to understand the native anatomy of ACL. We aimed to assess the ACL footprint dimensions in our patients and correlate it with anthropometric variables, which can help in preoperative decision making.

Method

A total of 143 eligible patients with suspected ACL injury presented during the study period. Out of which 92 were included in the study. Data on patient's age, sex, height, weight and body mass index (BMI) was recorded. The length and area of both the tibial and femoral footprints were measured on MRI. The footprint dimensions were correlated with the recorded anthropometric data.

Results

The ACL tibial footprint length and area, and femoral footprint length and area were found to be 13.3 ± 2.23 mm, 142.6 ± 26.16 mm², 11.2 ± 1.97 mm, 125.8 ± 28.75 mm² respectively. Footprint in males was significantly larger than females. A weak (ρ- 0.21 to 0.4) correlation with weight and moderate (ρ- 0.41 to 0.6) correlation with height was observed. Multivariate linear regression analysis yielded height to be the only significant predictor of footprint dimension from which predictive equations were drawn.

Conclusions

Height was found to be the most significant predictor of footprint dimensions in our patients. The predictive equations and graphs can aid in preoperative surgical decision making resulting in a more anatomical ACL reconstruction and improve the post-operative results.

1. Introduction

Anterior cruciate ligament injury (ACL) is one of the most common ligamentous injuries to the knee.¹ Individualized anatomic ACL reconstruction has recently gained attention owing to an improved understanding of the potential ACL anatomy and function. An individualized ACL reconstruction is a surgical procedure that is adjusted to each patient's lifestyle, activity level, and native anatomy and is believed to restore normal knee kinematics.² Van Eck et al. used the current literature to develop a flowchart that can be helpful to the surgeon in performing an anatomic ACL reconstruction. According to them, an ACL footprint smaller than 14 mm makes double bundle reconstruction challenging, and thus, they recommend a single bundle reconstruction in such cases.³

Recent studies have shown that a double bundle reconstruction has lesser re-rupture rates and a better antero-posterior and rotator stability.^4,5 But, it is paramount to preserve at least a 2 mm bony bridge between the two tunnels to avoid failure.⁶ Hence the preoperative knowledge of native ACL insertion would help make better surgical decisions.

Most of the literature on ACL footprint morphology considers the western population. It is paramount to attain the data of our indigenous populace to provide better clinical results for our patients. It is cumbersome to measure the footprint dimensions in each patient individually. Kim et al. proved that ACL tibial footprint sizes measured on magnetic resonance imaging (MRI) showed strong correlation with its actual sizes.⁷ Moreover, pre-operative prediction of the footprint sizes can help the surgeon tailor-make the surgery for each individual. The main objective of the study was to evaluate the footprint dimensions of our native populace to generate this essential data which has been lacking in literature currently. The second objective was to find the correlation between the footprint dimension and readily available patient anthropometric variables. We hypothesized that the footprint dimensions will significantly correlate with patients’ height, weight and Body mass index (BMI).

2. Materials and methods

The present observational study was conducted in a university-level tertiary care teaching hospital in North India from January 2020 to November 2021. The Institutional review board approved the study, and informed consent was taken from all the patients fulfilling the inclusion criteria. Being the first study conducted in Indian population, a standard deviation of 1.9 mm was taken from a previous study conducted in Asian population.⁸ For estimating the mean value of footprint dimensions with 95 % confidence and a precision of 0.5 mm a sample size of 59 was calculated. All the patients with a suspected ACL injury undergoing an MRI scan, aged 18–50 years, presenting to us during the study period were included. We excluded the patients with an open growth plate, who have undergone any previous knee surgery or ligament injury, multi-ligament injury, hyperslack ligaments, degenerative changes, or significant osteophyte formation near the ligamentous insertion sites. Patients' weight, height, and Body Mass Index (BMI) were recorded. An MRI from Discovery^TMMR750w3 Tesla MRI machine was done.

2.1. Measurement of footprint dimensions

T1 weighted images at the level of footprint were use for measurements. RadiAnt DICOM Viewer v. 2021.1 was used for all measurements.

2.2. Tibial footprint

To measure the exact length of the tibial insertion site, a sagittal image showing the largest exposure of the ACL fibers at the tibial attachment site was selected. The length of the ACL tibial footprint was measured as the distance from the most anterior to the most posterior fiber of the ACL tibial attachment site.^3,7,9,10 (Fig. 1a).

Fig. 1.

Measurement of ACL footprint sizes on MRI images: a) Tibial footprint length, b) Femoral footprint length, c) Tibial footprint area, d) Femoral footprint area.

2.3. Femoral footprint

To measure the length of femoral footprint (origin), a sagittal image showing the largest exposure of ACL fibers at the lateral condyle of femur was selected and the distance between the most anterior and the most posterior fibers was measured.^3,10 (Fig. 1b).

2.4. Femoral footprint area

To measure the area of femoral footprint, sagittal image showing the largest exposure of ACL fibers at lateral condyle of femur was used. The software's polygon tool was used to measure the footprint area (Fig. 1c).

2.5. Tibial footprint area

To measure the area of tibial footprint, axial image in 3D MPR feature of the software was used. After orienting the axis parallel to the tibial slope, the cut showing the largest exposure of ACL fibers at the tibial plateau was used. The software's polygon tool was used to measure the footprint area (Fig. 1d).

The above method was used by two of the investigators who were undergoing training in the orthopedics department. The investigators took two sets of measurements from the same MRIs at an interval of 2 weeks to assess the reliability and consistency of the measurements.

2.6. Statistical analysis

Data was entered in Microsoft (MS) Excel spreadsheet and analyzed using IBM SPSS Statistics ver.23 (SPSS Inc., Chicago, IL, USA)for Windows. Descriptive data are represented as mean±Standard deviation (SD) for continuous variables, while percentages and proportions were used for categorical variables. Kolmogorov-Smirnov test was used to check the normality of data in which all variables other than age were normally distributed. Spearman's rank correlation was used to calculate the correlation between footprint sizes and age, while Pearson correlation coefficient was used to calculate the correlation with height, weight, and BMI. The significance level was set at a p-value <0.05. The accuracy of footprint measurements was analyzed by interand intra-observer reliability with the intraclass correlation (ICC). The parameters showing a significant correlation with footprint dimensions were entered into a multiple linear regression model to determine the equation for calculating the footprint dimensions.

3. Results

A total of 143 eligible patients presented to our institute with a suspected ACL ligament injury. After using the inclusion and exclusion criteria, 92 patients who consented to participate were included in the study, as shown in Fig. 2. The mean age of the patients was 27.75 ± eight years and included 77 male and 15 female patients with 50 right and 42 left knees. Eighty-three patients had complete ACL tears, while nine had a partial ACL tear with 5 Anteromedial bundle tears and 4 Posterolateral bundle tears. The mean weight, height, and BMI of the group were 71.85 ± 12.27 Kg, 1.68 ± 0.10 m, and 25.53 ± 3.6 kg/m². The mean Tibial footprint length and area were 13.3 ± 2.23 mm (95 % C·I. - 12.88–13.80) and 142.6 ± 26.16 mm² (95 % C·I. - 137.25–147.94) respectively. While the mean Femoral footprint length and area were 11.2 ± 1.97 mm (95 % C·I. - 10.80–11.60) and 125.8 ± 28.75 mm² (95 % C·I. - 119.92–131.67) respectively. A total of 31.5 % (29/92) patients had a tibial footprint larger than 14 mm. While only 8.7 % of patients had femoral footprint lengths also larger than 14 mm. A detailed description of the ACL footprint dimensions is given in Table 1. A graphical representation of the measured footprints is given in Fig. 3a and b.

Fig. 2.

Flowchart of patient recruitment for the study.

Table 1.

Anterior cruciate ligament footprint dimensions.

ACL Footprint	Mean ± SD	95 % C·I.	Min - Max	Gender
Tibial Footprint Length (mm)	13.34 ± 2.23	12.88–13.80	8.7–22.6	Male- 13.56 ± 2.24
				Female- 12.20 ± 1.83
Femoral Footprint Length (mm)	11.20 ± 1.97	10.80–11.60	7.2–17.1	Male- 11.53 ± 1.91
				Female- 9.49 ± 1.32
Tibial Footprint Area (mm2)	142.61 ± 26.16	137.25–147.94	80.3–237.5	Male- 145.85 ± 25.02
				Female- 127.39 ± 27.41
Femoral Footprint area (mm2)	125.79 ± 28.75	119.92–131.67	69.8–223.0	Male- 130.80 ± 27.30
				Female- 100.07 ± 21.91

SD- Standard Deviation; 95 % C·I. - 95 % confidence interval; Min- Minimum; Max- Maximum.

Fig. 3.

Box and Whisker plot of the measured ACL footprint dimensions: a) Tibial and Femoral footprint lengths, b) Tibial and Femoral footprint areas.

It was observed that the footprint in males was significantly larger than females, as shown in Table 2 with a p-value< 0.05. Intra- and Inter-observer reliability was found to be good in two observers, with ICC >0.8 indicating a good agreement (Table 3). A weak (r- 0.21 to 0.4) positive correlation was observed between weight and footprint dimensions. In contrast, a moderate (r- 0.41 to 0.6) positive correlation was observed with height (Fig. 4). No significant correlation was found between BMI and the laterality of the knee (Table 2). Statistically significant variables were used in a multivariate linear regression model (Table 4), which yielded height to be the only significant predictor of footprint dimensions, and the following predictive equations were drawn from it.

• •Tibial Footprint Length (mm) = 10 x Height(m) - 3.42 (R² = 0.21, P < 0.001)
• •Femoral Footprint Length (mm) = 9.09 x Height(m) - 4.05 (R² = 0.23, P < 0.001)
• •Tibial Footprint Area (mm²) = 129.8 x Height(m) - 75.05 (R² = 0.26, P < 0.001)
• •Femoral Footprint Area (mm²) = 141.7 x Height(m) - 112 (R² = 0.26, P < 0.001)

Table 2.

Correlation table of footprint dimensions with patient characteristics: Males had a larger footprint then females while a weak and moderate positive correlation was found with weight and height respectively.

	Gendera	Lateralitya	Ageb		Weightc		Heightc		BMIc
	p value	p value	Correlation Coefficient (rho)	p value	Correlation Coefficient (R)	p value	Correlation Coefficient (R)	p value	Correlation Coefficient (R)	p value
Tibial Footprint Length (mm)	0.025	0.799	0.03	0.764	0.32	0.002	0.46	<0.001	−0.02	0.856
Femoral Footprint Length (mm)	<0.001	0.849	−0.19	0.068	0.31	0.002	0.47	<0.001	−0.03	0.762
Tibial Footprint Area (mm2)	0.015	0.879	−0.02	0.823	0.37	<0.001	0.51	<0.001	0	0.928
Femoral Footprint Area (mm2)	<0.001	0.357	−0.17	0.104	0.38	<0.001	0.5	<0.001	0	0.928

Significant p-values highlighted in bold and italics.

^aUnpaired student t-test.

^bSpearman correlation.

^cPearson correlation.

Table 3.

Intra and Inter-rater agreement of measurements of footprint dimensions: A good intra- and inter-observer agreement was between the measurements as suggested by ICC >0.8

Measurement	Intra-observer Reliability (ICC, 95 % CI)	Inter-observer Reliability (ICC, 95 % CI)
Tibial footprint length (mm)	0.95 (0.93–0.97)a	0.90 (0.86–0.94)
	0.95 (0.92–0.97)b
Femoral footprint length (mm)	0.95 (0.93–0.97)a	0.92 (0.89–0.95)
	0.94 (0.90–0.96)b
Tibial footprint area (mm2)	0.91 (0.86–0.94)a	0.92 (0.88–0.95)
	0.89 (0.84–0.93)b
Femoral footprint area (mm2)	0.93 (0.90–0.96)a	0.86 (0.81–0.91)
	0.89 (0.84–0.93)b

^aIntra-observer reliability ICC between observations taken by observer 1 at 2 separate occasions 2 weeks apart.

^bIntra-observer reliability ICC between observations taken by observer 2 at 2 separate occasions 2 weeks apart.

Fig. 4.

Scatter diagram showing correlation between footprint dimensions and patients height: a) Correlation between Tibial footprint length and height shows a moderate positive correlation (R = 0.46), b) Correlation between Femoral footprint length and height shows a moderate positive correlation (R = 0.47).

Table 4.

Multivariate linear regression analyses for association of anthropometric variables with ACL footprint dimensions: Height was found to be the only significant predictor of footprint dimensions.

	Tibial footprint length			Femoral footprint length			Tibial footprint area			Femoral footprint area
	Coefficients	SE	P-value	Coefficients	SE	P-value	Coefficients	SE	P-value	Coefficients	SE	P-value
Intercept	−5.86	4.23	0.17	−2.01	3.72	0.59	−100.58	47.88	0.04	−80.1	52.94	0.13
Gender	−0.85	0.76	0.26	0.67	0.67	0.32	−10.61	8.57	0.22	7.81	9.47	0.41
Weight (kg)	0	0.02	0.81	0	0.02	0.96	0.14	0.21	0.51	0.12	0.23	0.59
Height (m)	11.69	2.96	<0.01	7.58	2.6	<0.01	144.55	33.5	<0.01	113.65	37.04	<0.01

SE; Standard error; significant p-values highlighted in bold and italics.

Using the equations, the minimum cutoff height of patient for tibial footprint length<14 mm was found to be 174 cm. Fig. 5 shows a graphical representation of the above equations allowing the surgeon a quicker analysis of the native footprints.

Fig. 5.

Graphical representation of the regression equations derived for estimation of ACL footprint size using patient's height.

4. Discussion

The present study evaluates the dimensions of ACL footprint in the North Indian population, which can aid us in better understanding the native anatomy of our cohort of patients. The study's key finding is that the footprint size shows a significant variation with patients' height, weight, and gender. Out of these, height proved to be the single most predictive variable in multivariate regression analysis. The regression equations and the charts can further supplement the surgeon in choosing the appropriate surgical technique and graft size. As calculated by the regression equations, individuals with a height of more than 174 cm are likely to have a tibial footprint size of more than 14 mm, requiring a double bundle reconstruction.

Multiple studies have been done to quantify the size of the ACL footprint using cadavers, tibial slices in knee arthroplasty patients, and MRI. Kupczik et al. used coronal MRI to measure the tibial insertion and oblique coronal cut to measure the femoral origin and measured to be 13.3 mm and 12.3 mm, respectively.¹¹ Pontoh et al. also used sagittal and oblique coronal MRI cuts to measure tibial insertion length and width, respectively, which came out to be 11.9 ± 1.8 mm and 9.98 ± 1.5 mm.¹² In the present study, we used the sagittal MRI image to evaluate both the tibial and femoral footprint lengths, which came out to be 13.34 ± 2.23 mm and 11.20 ± 1.97 mm, respectively. The only previous study conducted on the Indian population by Raja et al. measured only the tibial footprint length, which was reported to be 15.4 ± 1.29 mm.¹³

Recent research has proposed the concept of reconstruction of native footprint area for restoration of proper knee biomechanics, which takes into account the footprint's length, width, and shape.¹⁴ We found the tibial footprint area 142.61 ± 26.16 mm² and the femoral footprint area 125.79 ± 28.75 mm². Our findings were similar to the South Asian studies reporting the tibial footprint size from around 133.8 mm² to 143.4 mm²and the femoral footprint size from 69.8 mm² to 125 mm^2.15–18 This finding differs significantly from the Western population, whose reported footprint areas are considerably higher.19, 20, 21, 22, 23, 24, 25 A comprehensive list of studies evaluating the footprint dimensions of ACL with their findings has been given in Table 5. This finding emphasizes taking into consideration the ethnicity of the patient and the need for individualization of surgery for restoration of the native anatomy.

Table 5.

Summarization of studies evaluating footprint dimensions of ACL as compared to the present study.

S. No.	Study	Country	Method	Sample (n)	Tibial Footprint length (mm)	Femoral footprint length (mm)	Tibial Footprint area (mm2)	Femoral footprint area (mm2)
1	Girgis et al., 197526	U·S.A.	Cadaver and fresh	44	29.3	23
2	Odensten and Gillquist, 198527	Sweden	Cadaveric	33	17 ± 3	18 ± 2
3	Stäubli and Rauschning, 199428	Switzerland	Cadaver; Cryoplanning; MRA	10 5 35	15 ± 3.2 18.5 16.5
4	Morgan et al., 199522	U·S.A.	TKR patients	50	18 (14–21)
5	Muneta et al., 199715	Japan	Cadaveric	16	17 ± 2.4	16 ± 2.8	143.4 ± 31.6	93.3 ± 34.1
6	Tan et al., 199829	Singapore (China)	Cadaveric	30	13.1 ± 4.4	13.9 ± 4
7	Harner et al., 199930	U·S.A.	Cadaveric	5			113 ± 27 AM-47 ± 13 PL- 49 ± 13	136 ± 33 AM-56 ± 21 PL- 53 ± 21
8	Cuomo et al., 200623	Italy	Cadaveric	21	17 ± 2 (12–19)
9	Colombet et al., 200624	France	Cadaveric	7	17.6 ± 2.1	18.3 ± 2.3
10	Dargel et al., 200625	Germany	Cadaveric	60			L- 114.6 ± 44.9 R- 121.6 ± 49.1	L- 95.8 ± 37.4 R- 101.9 ± 35.1
11	Mochizuki et al., 200631	Japan	Cadaveric	20	AM- 9.2 ± 0.7 PL- 6 ± 0.8
12	Steckel et al., 200632	Germany	Cadaveric	6			AM- 69.3 (65–75) PL- 55.7 (48–63)	AM- 66 (62–72) PL- 52.3 (48–63)
13	Takahashi et al., 200633	Japan	Cadaveric	32		AM-11.3 ± 1.6 PL-11 ± 1.7	AM- 67 ± 18.4 PL- 52.4 ± 17.6	AM- 66.9 ± 2.3 PL- 66.4 ± 2.3
14	Ferretti et al., 200734	U·S.A.	Cadaveric	16		17.2 ± 1.2 AM- 9.8 ± 1 PL- 7.3 ± 0.5		196 ± 23.1 AM- 120 ± 19.8 PL- 76.8 ± 15.6
15	Heming et al., 200735	U·S.A.	Cadaveric	12	18.5 ± 1.5	18.4 ± 0.6
16	Luites et al., 200719	Netherlands	Cadaveric	35			229 ± 53 AM- 136 ± 37 PL- 93 ± 33	184 ± 52 AM- 81 ± 27 PL- 103 ± 39
17	Edwards et al., 200720	U·K.	Cadaveric	55	18 ± 2 (11–23)
18	Edwards et al., 200821	U·K.	Cadaveric	22		14 ± 2 AM- 7.6 ± 1.5 PL- 6.2 ± 2.3
19	Tállay et al., 200836	Australia	Tibial Plateaus from TKR patients	36	19.5 ± 2.6
20	Siebold et al., 200837	Germany	Cadaveric	50	14 ± 2 AM- 12 ± 2 PL- 10 ± 2		114 ± 36 AM- 67 ± 31 PL- 52 ± 20
21	Siebold et al., 200838	Germany	Cadaveric	50		15 ± 3 AM- 7 ± 1 PL- 7 ± 2		83 ± 19 AM- 44 ± 13 PL- 40 ± 11
22	Kupczik et al., 201311	Brazil	MRI	52	13.3 (9.1–17.5)	12.3 (9.7–15.4)
23	Iriuchishima et al., 201318	Japan	Cadaveric	18			144 ± 35.9	84 ± 25.3
24	Iriuchishima et al., 201517	Japan	Cadaveric	26			133.8 ± 31.3	69.8 ± 25
25	Ichiba et al., 20148	Japan	MRI	100	15.2 ± 1.9
26	Abreu-e-Silva et al., 201539	Brazil	3D CT of cadaveric knees	8	AP- 18.5 ± 1.9 ML- 15.5 ± 1	AP- 9.4 ± 0.8 CC- 15.6 ± 0.9
27	Kim et al., 20187	South Korea	MRI and Gross evaluation	164	MRI- 12.4 (9.7–15.3) Gross- 13.8 (10.6–17.8)
28	Suruga et al., 201916	Japan	Cadaveric	30				125 ± 67
29	Raja et al., 202013	India	MRI	70	15.4 ± 1.29
30	Pontoh et al., 202112	Indonesia	MRI	117	11.9 ± 1.8
31	Present study, 2023	India	MRI	92	13.3 ± 2.23	11.2 ± 1.97	142.6 ± 26.16	125.8 ± 28.75

U·S.A- United States of America; MRA- Magnetic Resonance Arthrography; TKR- Total Knee Replacement; U.K- United Kingdom; MRI- Magnetic Resonance Imaging; 3D CT- 3 Dimensional Computed Tomography.

The aim of correlating the footprint dimensions with anthropometric variables is to identify the individuals with a larger footprint using readily available parameters. We found a significant correlation between the ACL footprint measurementsand patient height, weight, and gender, with males having a larger footprint than females. Although using multiple linear regression analysis, height was the sole predictor of footprint dimension. In terms of gender differences, the study by Muneta et al. and Raja et al. showed no differences between the two genders in footprint sizes, while studies by Siebold et al. and Pontoh et al. have found significantly larger footprint dimensions in males as compared to females.^{12,13,15,37,38} A 2019 systematic review including 92 studies to evaluate gender-based differences in ACL dimensions found a considerable variation in the literature and couldn't draw a definite conclusion.⁴⁰

Various studies have shown an association between patients' weight, height, leg length, femur length, and tibia length.^8,41,42 The study by Gali et al. on Brazilian patients undergoing TKA showed a statistically significant association between patient height and ACL tibial fovea width.⁴³ Park et al. conducted a study in which they found that only tibial length is associated with footprint length. In contrast, weight and tibial length are associated with footprint width on multivariate analysis.⁴⁴ Our findings were similar to the study done by Pontoh et al. on the Indonesian population, where they found a significant correlation of tibial footprint length with weight, height, and BMI. The multivariate logistic regression showed height as the sole predictor for a larger footprint. The cut-off value for tibial footprint length <14 mm was calculated to be 170 cm.¹² In our study, the cutoff for tibial and femoral footprint lengths larger than 14 mm were found to be 174 cm and 198.5 cm respectively. Our findings show that a very small proportion of our population has both femoral and tibial ACL footprint lengths larger than 14 mm, which is 8.7 %. For most of the patients it will be difficult to execute a double bundle reconstruction while leaving an adequate bony bridge between the two tunnels. The patients requiring a double bundle reconstruction or a larger graft size can be speculated by the measurement of patients’ height. This way the surgeon can be well prepared for the surgery in the preoperative period itself and assure best results postoperatively with an individualized reconstruction.

There are a few shortcomings of the study. First of all, the study was conducted in a single center; hence the overall generalization of the study finding cannot be highlighted. Most of the patients presenting to us belong to Northern India, and the findings correspond the best to the North Indian population. A more extensive study with multiple centers conducted over a larger geographical area will yield a more generalizable result. We have only taken into account footprint lengths and not breadths. The measurement of footprint dimensions has been based on previously existing literature which has only evaluated footprint lengths in MRI. Also, the study did not include any intraoperative measurements of the footprint sizes. To the best of our knowledge, this is the first study in any Indian population evaluating the lengths and areas of tibial and femoral footprint of ACL and correlating them with anthropometric parameters of the ACL deficient patients.

5. Conclusion

MRI-based femoral and tibial footprint dimensions can be ascertained based on the patient's anthropometric variables like height, weight, and gender, with height being the most important predictor. The predictive equations and graphs can be helpful in pre-operative surgical decision-making regarding the type of surgery and the graft size to reconstruct the maximum possible native footprint dimensions. This may improve our patients' overall post-operative outcomes and satisfaction, enabling them to return to their optimal pre-injury status.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Ethical approval

Approval from Institutional Ethics Committee taken.

Informed consent

Informed written consent taken from all the participants.

CRediT authorship contribution statement

Kshitij Gupta: Methodology, Writing – original draft. Arghya Kundu Choudhury: Writing – review & editing. Balgovind S. Raja: Visualization, Formal analysis. Abhishek Chandra: Data curation, Investigation. Md Quamar Azam: Validation, Resources. Roop Bhushan Kalia: Conceptualization, Supervision, Project administration.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.