Alteration of foot loading pattern in patients with lower limb endoprothesis surgery and functional outcome: A pilot study

Abstract

Introduction

Endoprosthetic reconstruction is a widely used technique; however, it is associated with various postoperative complications. One often overlooked complication is the alteration of foot loading patterns. This pilot study evaluated functional outcomes with postoperative static foot loading patterns in patients undergoing endoprosthesis replacements compared to the contralateral limb.

Objective

This study evaluates static foot loading patterns in patients undergoing endoprosthetic replacements. It explores the relationship between the functional outcomes of the operated limb and foot loading patterns in a standing position. Additionally, the study considers factors such as the anatomical location of the endoprosthetic reconstruction, limb length discrepancy, age, gender, and body mass index (BMI).

Materials and Methods

This prospective cross-sectional study included 100 patients over 15 years who had undergone lower limb endoprosthetic reconstruction at least 1 year prior and could walk unaided. Data collection encompassed patient demographics, diagnosis, anthropometric measurements, postoperative functional status (evaluated using AOFAS-Hindfoot, MSTS, and TESS scores), and postoperatively analysis of foot loading patterns.

Results

The patient group has a significantly higher prevalence of abnormal foot arches compared to the expected population proportion. Notably, 10% of patients transitioned from a normal arch to flatfoot, while 40% developed a high arch post-surgery. Asymmetrical arches were observed in 30 patients. Post-surgery, 18.5% of patients experienced a transition from a normal foot arch to a high arch, and 4.6% transitioned to flatfoot. Analysis of variables such as surgical site, limb length discrepancy, age, gender, BMI, foot loading patterns and functional scores (MSTS, TESS and AOFAS) showed no significant associations with these changes.

Conclusion

Although no significant correlation was identified between functional scores and foot loading patterns following lower limb endoprosthetic surgery, a notable prevalence of abnormal foot arches was observed. We recommend routine podiatry consultations for these patients to address and manage potential foot-related complications.

Keywords

endoprosthesis foot loading patterns functional outcomes abnormal arch gait

Introduction

Over the past few decades, endoprosthetic reconstruction has emerged as a fundamental limb-salvage procedure for patients diagnosed with malignant bone tumours.¹ Contemporary tumour endoprostheses’ modular design provides orthopaedic oncology surgeons with intraoperative flexibility to tailor reconstruction length, significantly enhancing functional outcomes.²

Over the past 30 years, innovations in surgical techniques, prosthetic design, and the introduction of neoadjuvant chemotherapy have resulted in a remarkable increase in the 5-year survival rate for these patients, climbing from 20% to an impressive 85%.³

However, despite these advancements, endoprosthetic reconstruction as a limb-sparing strategy is not without complications.⁴ A key challenge remains the attainment of symmetrical gait patterns, particularly in cases necessitating extensive muscle excision to secure adequate surgical margins

The assessment of foot loading has advanced significantly in recent decades, offering valuable insights into the distribution of forces between the foot’s sole and the supporting surface. This information reflects the foot’s anatomical structure, functional capacity, and postural stability, influencing overall body posture and mechanics.

This study evaluates static foot loading patterns in patients following endoprosthetic reconstruction. Specifically, it seeks to identify discrepancies or changes in foot loading and to explore their correlation with functional outcomes of the lower limb in individuals who have undergone this procedure.

Endoprosthesis surgeries are commonly performed as limb-salvage interventions, and the resultant functional outcomes are generally deemed satisfactory. However, a lack of consensus remains on which assessment tests or parameters most accurately represent these outcomes. In our research, we will employ the Musculoskeletal Tumour Society (MSTS) score, the Toronto Extremity Salvage Score (TESS), and the American Orthopaedic Foot and Ankle Society (AOFAS) Hindfoot Rating System, which focuses on the functional outcomes of the ankle joint and foot, to evaluate the lower limb functional outcomes in our patient cohort.

Material and methodology

This prospective cross-sectional study was conducted in the Orthopaedic Oncology Department of a tertiary hospital. We recruited patients who had undergone lower limb endoprosthesis reconstruction following the resection of bone and soft tissue sarcomas, with a minimum follow-up period of 1 year. Data collected included demographic variables such as gender, age, diagnosis, and any history of revision surgery, along with anthropometric measurements (i.e., height, weight, and Body Mass Index [BMI]). Additionally, the functional status of patients was evaluated using the Musculoskeletal Tumour Society (MSTS) Score for lower limbs, the Toronto Extremity Salvage Score (TESS), and the American Orthopaedic Foot and Ankle Society (AOFAS) Ankle-Hindfoot Scale. Bilateral foot loading patterns were also measured to determine the foot pattern. The operated foot loading pattern was compared with the non-operated contralateral foot. All data were collected at a minimum 1 year postoperatively. Unfortunately, no foot loading patterns were measured preoperatively.

Exclusion criteria included patients who could not ambulate independently, those with implant failures, patients experiencing active implant infections, individuals with joint infections, and those with neurological deficits. A total of 100 patients were selected for inclusion in the study. To ensure consistency, the same researcher conducted all assessments throughout the study.

Ethical approval was granted by The Medical Ethics Committee (MECID. NO: 2019923-7851), and written consent was obtained from all participants prior to their inclusion in the study.

Footprint mapping device (podoscope)

We used a podoscope developed in our department, which was used for several studies before, and clinically compared with the Harris mat at the Foot & Ankle Clinic. It measures static foot loading pattern and is similar to commercially available podoscopes. Our podoscope produces the same images, but the raw material used to manufacture it was significantly cheaper than the commercial podoscope. The data collection process using this device is outlined below:

Respondents were instructed to step onto designated columns created with a transparent platform. Upon activation, the platform illuminates, and a smartphone captures a high-resolution photograph of the bilateral plantar surfaces of the foot.

The highest-resolution image of each respondent’s plantar foot was selected and transferred to a computer for further analysis (Figure 1). Measurements were performed using the Staheli Index, which represents the ratio of the minimal distance in the midfoot region to the maximum distance in the rearfoot region. Specifically, the Staheli Index quantifies the relationship between the midfoot minimal width and the hindfoot maximal width.

Figure 1.

Podogram recorder: (a) Transparent foot mapper with grids (b) Battery for light source. (c) and (d) Base and structure of podogram recorder. (e) Images of foot loading pattern were captured using a smart phone placed under the podogram. (f) Sample of foot loading pattern. The grids on the platform are 10 mm × 10 mm.

Measurements were conducted using Adobe Photoshop. A line connecting the inner edges of the forefoot and the heel was drawn. The midpoint of this line was identified, and a perpendicular line was constructed through this point, intersecting the footprint. At the heel, another perpendicular line was drawn at the maximum width of the footprint. This procedure allows for the measurement of the widths of the central region (A) and the heel region (B) in millimeters.

The Staheli Plantar Arch Index (SPAI) was calculated by dividing the measurement of the central region (A) by that of the heel region (B), expressed mathematically as SPAI = A/B (Figure 2). To ensure accuracy, three orthopaedic consultants independently measured and cross-checked the results.

Figure 2.

Staheli plantar arch index (SPAI).

Result interpretation based on staheli arch index calculation

Foot arches were categorised into three types based on the Staheli Plantar Arch Index: high, normal, and flat. Specifically, a high arch was defined by a ratio of 0.1 to 0.4. A normal arch exhibits a ratio between 0.5 and 0.7, while a flat arch was characterised by a ratio between 0.8 and 1.2.⁵

True limb length measurements are conducted using a tape measure to assess any discrepancies in limb length. The discrepancies were classified according to the degree of inequality, expressed in centimeters (cm): mild discrepancies are less than 3 cm, moderate discrepancies range from 3 to 6 cm, and severe discrepancies exceed 6 cm.

Sample size calculation

According to Tareco et al.,⁶ the prevalence of flatfoot is at 6% in patients with no history of foot problems using the single leg stance footprint. We want to calculate this sample size with a precision/absolute error of 5% and a type 1 error of 5%. This sample size calculation formula was obtained from Charan and Biswas.⁷

The sample size for this study, with a precision/absolute error of 5% and a type 1 error of 5%, came to a minimum of 95 subjects.

Statistical analysis

Data were analysed using IBM SPSS (Statistical Package for the Social Sciences) version 25. The normality of the data was assessed using the Kolmogorov-Smirnov test, revealing that the data did not follow a normal distribution. Consequently, the Kruskal-Wallis test, a non-parametric method, was employed to analyse the relationship between functional scores and foot-loading patterns.

A Chi-square test was also utilised to examine the association between two categorical groups. The comparison between the observed and expected proportions for foot changes was assessed using a Binomial test. All probability values were calculated as two-sided, with a significance level set at less than 0.05 (p-value <.05) considered statistically significant.

Results

A total of 100 subjects were recruited for this study. The mean age of the participants was 38.8 years (SD ± 18.4, Range: 15 to 85 years), with a distribution of 65% females and 35% males. Among the subjects, 73% received femoral implants, 23% received tibial implants, and 3% received both distal femur and proximal tibia implants.

Limb length discrepancies were observed in 63% of the cohort, with a mean shortening of 1 cm (SD ± 1.5, Range: 0.1 to 2.4 cm), while 37% experienced lengthening, with a mean increase of 1.6 cm (SD ± 0.7, Range: 0.1 to 6.9 cm). Regarding body mass index (BMI), 40% of subjects had a normal BMI, 15% were classified as having low BMI, 19% were overweight, 18% were obese, and 8% were extremely obese.

Notably, our study revealed that 50% of the subjects exhibited an altered arch postoperatively compared to the opposite foot. This rate is significantly higher than the 11% reported in the general population by Wicaksono et al.,⁸ with a statistically significant difference (p = .00). The comparison between the non-operated and operated limbs is presented in Table 1. The most significant changes observed were from normal to high arch and from flatfoot to normal arch, each at a rate of 40%.

Table 1.

Frequency and percentage distribution in asymmetrical arches between non-operated and operated limbs (n = 30).

Asymmetrical foot arch (non operated vs operated)	n	Percentage (%)
Normal - flatfoot	3	10.0
Normal - High arch	12	40.0
Flatfoot - normal	12	40.0
Flatfoot - high arch	0	0.0
High arch - normal	3	10.0
High arch - flatfoot	0	0.0

Among the patients who underwent endoprosthesis reconstruction, half exhibited abnormal foot structures. 12 patients (18.5%) in this group experienced changes in foot patterns post-surgery compared to the contralateral foot, transitioning from a normal foot to a high arch, while 3 patients (4.6%) developed a flatfoot condition. Conversely, 12 patients (42.9%) saw improvements, transitioning from flatfoot to a normal arch, and 3 patients (42.9%) shifted from a high arch to a normal foot in the operated limb (Table 2).

Table 2.

Frequency and percentage distribution of foot loading pattern in operated and non-operated limbs.

Foot pattern non-operated limb	Foot pattern operated limb			Total n (%)
Foot pattern non-operated limb	Normal n (%)	Flatfoot n (%)	High arch n (%)	Total n (%)
Normal	50 (76.9)	3 (4.6)	12 (18.5)	65 (100.0)
Flatfoot	12 (42.9)	16 (57.1)	0 (0.0)	28 (100.0)
High arch	3 (42.9)	0 (0.0)	4 (57.1)	7 (100.0)

When examining the relationship between the site of endoprosthesis replacement and foot loading patterns, no significant correlation was found, as indicated by a Chi-square value of 5.11 and a p-value of .544 (ꭓ² = 5.11, p = .544) (see Table 3). Additionally, limb length discrepancies in the operated limb did not show a significant correlation with foot loading patterns, with a Chi-square value of 2.09 and a p-value of .348 (ꭓ² = 2.09, p = .348) (see Table 4).

Table 3.

Association between site and foot loading pattern in operated limb.

Site	Foot pattern			X ²	p
Site	Normal n (%)	Flatfoot n (%)	High arch n (%)	X ²	p
Femur	44 (60.3)	17 (23.3)	12 (16.4)	5.11	.544
Tibia	18 (78.3)	2 (8.7)	3 (13.0)
Femur & tibia	2 (66.7)	0 (0.0)	1 (33.3)
Knee	1 (100.0)	0 (0.0)	0 (0.0)

Table 4.

Comparison between limb length discrepancy and foot loading pattern in operated limb.

Limb length discrepancy	Foot pattern			X ²	p
Limb length discrepancy	Normal n (%)	Flatfoot n (%)	High arch n (%)	X ²	p
Shortening	41 (65.1)	14 (22.2)	8 (12.7)	2.09	.348
Lengthening	24 (64.9)	5 (13.5)	8 (21.6)	2.09	.348

Our analysis further demonstrated no significant association between foot loading patterns and functional scores. The non-significant H values and p-values for the AOFAS (H (2) = 1.52, p = .467), MSTS (H (2) = 0.27, p = .874), and TESS (H (2) = 0.39, p = .823) scores (Table 5). No association was found between AOFAS classification and foot loading patterns in the operated limb, with a Chi-square value of 3.09 and a p-value of .558 (ꭓ² = 3.09, p = .558) (Table 6).

Table 5.

Association between functional scores and foot loading pattern in operated limb.

	Foot pattern	n	Mean rank	df	H	p
AOFAS	Normal	65	52.27	2	1.52	.467
	Flatfoot	19	43.16
	High arch	16	52.03
MSTS	Normal	65	49.78	2	0.27	.874
	Flatfoot	19	53.61
	High arch	16	49.75
TESS	Normal	65	49.88	2	0.39	.823
	Flatfoot	19	49.16
	High arch	16	54.59

Table 6.

Association between AOFAS classification and foot loading pattern in operated limb.

AOFAS classification	Foot pattern			X ²	p
AOFAS classification	Normal n (%)	Flatfoot n (%)	High arch n (%)	X ²	p
Excellent	29 (69.0)	5 (11.9)	8 (19.0)	3.09	.558
Good	31 (63.3)	12 (24.5)	6 (12.2)
Fair	5 (55.6)	2 (22.2)	2 (22.2)

Furthermore, we found no significant correlation between patients’ age (comparing those below 50 years and those 50 years and above), with a Chi-square value of 0.31 and a p-value of .848; gender, with a Chi-square value of 2.77 and a p-value of .215; or Body Mass Index (BMI), with a Chi-square value of 13.47 and a p-value of .093 (Table 7).

Table 7.

Association between age and foot loading pattern in operated limb.

Age	Foot pattern (OL)			X ²	p
Age	Normal n (%)	Flatfoot n (%)	High arch n (%)	X ²	p
<50	48 (66.7)	13 (18.1)	11 (15.3)	0.31	.848
≥50	17 (60.7)	6 (21.4)	5 (17.9)	0.31	.848

Association between gender and foot loading pattern in operated limb
Gender	Foot pattern			X ²	p
Gender	Normal n (%)	Flatfoot n (%)	High arch n (%)	X ²	p
Male	19 (54.3)	9 (25.7)	7 (20.0)	2.77	.215
Female	46 (70.8)	10 (15.4)	9 (13.8)

Association between Body Mass Index (BMI) and foot loading pattern in operated limb
BMI	Foot arch pattern			X ²	p
BMI	Normal n (%)	Flatfoot n (%)	High arch n (%)	X ²	p
Normal	30 (75.0)	5 (12.5)	5 (12.5)	13.47	.093
Underweight	9 (60.0)	2 (13.3)	4 (26.7)
Overweight	13 (68.4)	3 (15.8)	3 (15.8)
Obese	11 (61.1)	4 (22.2)	3 (16.7)
Extreme obese	2 (25.0)	5 (62.5)	1 (12.5)

Discussion

In this study, we utilised an in-house designed and constructed podoscope to assess foot morphology. Musaid et al. noted that commercially available podoscope systems are often expensive, complex, and difficult to access, particularly in developing countries. Our low-cost podoscope system enhances accessibility for foot morphology assessments, especially in resource-limited settings. Our podoscope has a simple design that is user-friendly, automated, and portable, thus making it a valuable tool for healthcare professionals and researchers.⁹

The primary aim of this study was to determine whether foot loading patterns affect the functionality of patients who underwent lower limb endoprosthesis replacement surgery, as evaluated through functional scores, specifically AOFAS, MSTS, and TESS. Surprisingly, none of the functional scores significantly correlated with foot-loading patterns. We found that 50 patients (50%) exhibited abnormal foot arches on the operated limb, substantially higher than the expected prevalence of 11% reported in the general population.⁸ This discrepancy highlights the potential impact of surgical procedures on foot arch development.

Furthermore, literature from various Western populations provides valuable comparative data on foot arch prevalence. An Australian study with 92 subjects aged 18-45 years reported a higher prevalence of low arches (33.7%) and high arches (28.3%), with a total of 62% classified as having abnormal arches.¹⁰ In an American study involving 61 subjects aged 18-77 years, the prevalence of low arches was 36.1%, and high arches were reported at 19.6%, resulting in an overall abnormal arch prevalence of 55.7%.¹¹ These findings suggest significant variability in abnormal arch prevalence across different populations, and age groups.

Our analysis revealed that 30 out of 100 patients had asymmetrical arches, while 70 exhibited similar arches bilaterally, regardless of their respective patterns. This suggests that transitions in foot arch patterns may be related to surgical interventions. We focused on the changes in individual patients’ foot arches post-surgery, particularly in those with asymmetry. Notably, 18.5% of patients transitioned from a normal arch to a high arch, indicating potential increases in arch rigidity. Conversely, 4.6% of patients exhibited a transition from a normal arch to a flatfoot condition, suggesting a reduction in arch support.

Encouragingly, 42.9% of patients with pre-existing flatfoot conditions transitioned to a normal arch in the operated limb, indicative of possible improvements in biomechanics and gait. Similarly, 42.9% of patients initially had a high arch in the non-operated limb transitioned to a normal arch after surgery, reflecting a potential decrease in excessive arch rigidity.

While there is limited literature on foot arch changes following endoprosthesis replacement, prior studies indicate that these patients may experience slower walking speeds¹² or equivalent walking speeds¹³ compared to healthy individuals. Changes in step length may occur in the contralateral limb,¹⁴ likely due to muscle and nerve excision during surgery. Ultimately, these factors might lead to compensatory changes in the affected limb as the body attempts to restore normal function relative to the contralateral limb.¹⁵

Our additional analyses explored the associations between the surgery site (femur, tibia, femur and tibia, or knee), limb length discrepancy (shortening or lengthening), age, gender, BMI, and foot loading patterns in the operated limb. However, no significant associations were found among these factors.

We acknowledge the limitations of our study, particularly the lack of preoperative arch status for the operated foot due to the study design, which only included patients 1-year post-surgery. This limitation could impact the interpretation of our results relative to other studies that provide more detailed pre-surgical arch information. Comparing the operated limb to the non-operated limb also presents inherent challenges in isolating the specific effects of surgery from potential pre-existing differences.

This pilot study also investigated functional scores associated with foot loading patterns and not just pre- and post-operative foot alterations in loading patterns. However, future studies should include preoperative foot patterns for an accurate conclusion.

In conclusion, while our study found no significant link between functional scores and foot loading patterns following lower limb endoprosthesis surgery, it did reveal a notable prevalence of abnormal arches compared to the general population. This suggests that endoprosthesis surgery may contribute to arch changes. While orthotic insoles may not be necessary unless patients report foot pain or abnormal gait, this study recommends routine podiatry consultations for these patients to address and manage potential foot-related complications.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Vivek Ajit Singh

Amber Haseeb

Nor Faissal Yasin

References

Sluga

Windhager

Lang

, et al. Local and systemic control after ablative and limb sparing surgery in patients with osteosarcoma. Clin Orthop Relat Res 1999; 358: 120–127. https://www.ncbi.nlm.nih.gov/pubmed/9973983

Bickels

Wittig

Kollender

, et al. Distal femur resection with endoprosthetic reconstruction: a long-term followup study. Clin Orthop Relat Res 2002; 400: 225–235.

Mittermayer

Krepler

Dominkus

, et al. Long-term followup of uncemented tumor endoprostheses for the lower extremity. Clin Orthop Relat Res 2001; 388: 167–177.

Donati

Zavatta

Gozzi

, et al. Modular prosthetic replacement of the proximal femur after resection of a bone tumour a long-term follow-up. J Bone Joint Surg Br 2001; 83(8): 1156–1160.

Ramos

Fernandes

Panicker

, et al. Assessment of flat foot using plantar arch index in young adults. Basel: Biomedicine, 2021.

Tareco

Miller

MacWilliams

, et al. Defining flatfoot. Foot Ankle Int 1999; 20(7): 456–460.

Charan

Biswas

. How to calculate sample size for different study designs in medical research? Indian J Psychol Med 2013; 35(2): 121–126.

Wicaksono

Kusumaningtyas

Tulaar

Foot Arch and Plantar Pressure in the Age of 17-21 Years [foot arch; plantar pressure; normal gait]. Mutiara Medika Jurnal Kedokteran dan Kesehatan 2021; 21(2): 6.

Musaid

Ghazwan

Al-Saadan

. A low-cost podoscope for extracting morphological features of the foot. Ottawa: Periodicals of Engineering and Natural Sciences, 2023.

10.

Buldt

Forghany

Landorf

, et al. Centre of pressure characteristics in normal, planus and cavus feet. J Foot Ankle Res 2018; 11: 3.

11.

Hillstrom

Song

Kraszewski

, et al. Foot type biomechanics part 1: structure and function of the asymptomatic foot. Gait Posture 2013; 37(3): 445–451.

12.

De Visser

Mulder

Schreuder

, et al. Gait and electromyographic analysis of patients recovering after limb-saving surgery. Clin Biomech 2000; 15(8): 592–599.

13.

Carty

Bennett

Dickinson

, et al. Electromyographic assessment of Gait function following limb salvage procedures for bone sarcoma. J Electromyogr Kinesiol 2010; 20(3): 502–507.

14.

Rompen

Ham

Halbertsma

, et al. Gait and function in patients with a femoral endoprosthesis after tumor resection: 18 patients evaluated 12 years after surgery. Acta Orthop Scand 2002; 73(4): 439–446.

15.

Zan

Wang

Cai

, et al. Revision surgeries for tumor endoprostheses around the knee joint: a mid-long-term follow-up of 20 cases. World J Surg Oncol 2022; 20(1): 76.