Association of Bone Quality Measured by Noncontrast Computed Tomography Scan and Three-dimensional Computed Tomography-based Fracture Pattern in Intertrochanteric Femur Fracture in Adults

Abstract

Background:

Understanding intertrochanteric (IT) femur fractures, their causes, classifications, and the role of bone quality is crucial for management. Poor bone quality associated with osteoporosis increases fracture risk and poorer outcomes. While dual-energy X-ray absorptiometry is the gold standard, Hounsfield units (HUs) derived from computed tomography (CT) scans are a valuable, noninvasive alternative for assessing bone quality.

Aim and Objectives:

To determine the association of bone quality, measured by noncontrast CT scan, with three-dimensional CT (3D-CT)-based fracture patterns in IT femur fractures in adults.

Materials and Methods:

Over a period of 18 months, 137 patients with IT femoral fractures were included. Fracture classification using Evans (1949), Boyd and Griffin (1956), and Arbeitsgemeinschaft für Osteosynthesefragen/Orthopaedic Trauma Association (AO/OTA) (2018) was done. Bone quality was assessed by calculating the HU value from the largest spherical region of interest in the IT region of the unaffected side. 3D-CT-based classification system by Dr. R. B. Kalia and Dr. Shobha S. Arora was used.

Results:

The mean age was 65.4 ± 10.2 years, with females comprising 59.9%. AO/OTA type 31A2.2 was the most common, indicating frequent unstable fractures. Patients with stable fractures had significantly higher mean HU values (130.2 ± 22.1) compared to those with unstable fractures (105.4 ± 24.3) (P < 0.001). A significant correlation (P < 0.001) between the AO/OTA (2018) classification and the CT-based classification is evident.

Conclusion:

Lower HU values, indicating poorer bone quality, are strongly associated with unstable fracture patterns. The significant correlation between CT-based assessments and AO/OTA classification validates the utility of advanced imaging techniques in assessing bone strength and fracture risk.

INTRODUCTION

Proximal femur fractures, mostly intertrochanteric (IT) femur fractures, are a major public health concern among the elderly population worldwide.[1] They are also associated with high morbidity, leading to substantial healthcare costs globally.[2] Thus, we need a better understanding of etiology and the role of bone quality in determining fracture pattern and treatment outcomes.

Bone quality consists of bone mineral density (BMD) and trabecular microstructure.[3] Poor bone quality is characterized by low BMD and reduced cortical thickness and is linked to an increased fracture risk and poorer outcomes after surgical fixation. Osteoporosis, defined by low bone mass and disrupted bone microarchitecture, is strongly associated with fragility fractures like IT femur fractures resulting from low-energy trauma.[4] The cortical thinning and loss of trabecular bone mass seen in osteoporosis impair biomechanical stability, leading to increase in susceptibility to fractures, mainly in weight-bearing areas like the hip and spine.

Traditional assessment of BMD is done using dual-energy X-ray absorptiometry (DEXA), which is considered the gold standard.[5] DEXA gives a T-score which is compared with the general population. Osteoporosis is defined as a T-score of <2.5. While DEXA remains the gold standard for measuring BMD, its limited availability and being a two-dimensional measurement have spurred interest in alternative methods. Computed tomography (CT) scans with their ability to provide Hounsfield unit (HU) values and to measure volumetric density, such as those with quantitative CT, offer a promising alternative for evaluating bone quality in patients with fractures.[6] HU values derived from noncontrast CT (NCCT) scans correlate strongly with BMD measurements obtained through DEXA. Studies, such as those by Pickhardt et al., have demonstrated that HU thresholds can be used to categorize bone quality into normal, osteopenic, and osteoporotic ranges.[7] In addition, three-dimensional CT (3D-CT) reconstructions provide detailed visualizations of fracture patterns, enabling the identification of comminution, displacement, and cortical disruption. These imaging modalities not only aid in classifying fractures but also provide valuable information for surgical planning, such as the selection of implants and fixation techniques.

Classification systems for IT femur fractures have evolved from traditional X-ray-based methods like Evans’ and Boyd and Griffin classifications to the more comprehensive Arbeitsgemeinschaft für Osteosynthesefragen/Orthopaedic Trauma Association (AO/OTA) classification.[8] More recent CT-based classifications, such as the system by Dr. R. B. Kalia and Dr. Shobha Arora, offer detailed assessment of fracture morphology, including comminution, displacement, and stability, vital for surgical planning and outcome prediction.[9] This CT-based system classifies fractures based on the stability of three columns: anteromedial (AM), posteromedial (PM), and lateral, defining a column as unstable if two or more fracture lines create an intermediate fragment.

Understanding the association between bone quality and these detailed fracture patterns is crucial for better preoperative planning. Patients with poor bone quality may require augmented fixation strategies to achieve stable fixation such as the use of locking plates, intramedullary nails with augmentation, and bone grafting. In addition, the use of pharmacological interventions to improve bone quality, such as bisphosphonates, denosumab, and parathyroid hormone, has gained traction in the perioperative management of these patients. This study aimed to evaluate the bone quality determined by NCCT scan in IT IT femur fracture in adults and assess its association with 3D-CT-based fracture patterns with the ultimate goal of improving the care and outcomes of patients with IT fractures.

MATERIALS AND METHODS

This observational study was conducted over 18 months in the Department of Orthopaedics and Department of Radiology, Rajendra Institute of Medical Sciences (RIMS), Ranchi, Jharkhand. The study population included adult patients (aged 18 years and above) presenting with IT femur fractures to the outpatient department and emergency department of RIMS. Ethical clearance was obtained from the Institutional Ethics Committee of RIMS, Ranchi. The Clinical Trials Registry-India (CTRI) registration number was CTRI/2024/11/077141. The sample size was 137. Data collection involved obtaining plain radiographs: anteroposterior (AP) pelvis with bilateral hip, AP hip with traction and internal rotation, and lateral hip view [Figure 1]. Fracture patterns were evaluated using Evans, Boyd and Griffin, and AO/OTA (2018) classifications based on these radiographs. Subsequently, 3D-CT scans were performed [Figure 2]. Bone quality was assessed by calculating the HU value from the NCCT scan [Figure 3]. HU measurements were performed using the Syngo.Via platform (Siemens Healthineers) on coronal CT images of the pelvis. To get consistent HU value irrespective of the observer, CT scan of the pelvis with bilateral hip was done. Coronal plane of the unaffected hip was taken and that cut section was chosen in which all the outer cortices were seen and continuous in the IT region, part of the neck, and proximal femur. A spherical or oval region of interest of largest possible diameter including the outer cortices was drawn, and the HU value was calculated using Syngo.Via software (Siemens Healthineers) [Figure 4].

Figure 1.

X-ray pelvis with bilateral hip – anteroposterior view

Figure 2.

Three-dimensional computed tomography with a reconstruction of the pelvis with bilateral hip

Figure 3.

Multiplanar computed tomography scan of the pelvis with bilateral hip with images in coronal (top 3 rows), axial (4^th and 5^th rows), and sagittal planes (bottom 2 rows)

Figure 4.

Coronal plane of the computed tomography scan of the pelvis – Measurement of Hounsfield unit by drawing spherical region of interest with largest possible diameter including the marginal cortical bone

Fracture patterns were also analyzed from 3D-CT scans using the CT-based classification system by Dr. R. B. Kalia and Dr. Shobha S. Arora. This system categorizes fractures based on the stability of the AM, PM, and lateral (L) columns, with a column considered stable if it has a single fracture line and unstable if two or more fracture lines create an intermediate fragment.[9]

Other collected parameters included age, sex, comorbidities (diabetes and hypertension based on the World Health Organization criteria), and mode of injury (self-fall or road traffic accident).

Statistical analysis was performed using SPSS Statistics for Windows, Version 16.0 (Released 2007; SPSS Inc., Chicago, Illinois, United States) has been used for statistical analysis which adheres to the objectives of our study. Numerical (dichotomous/continuous) variables were summarized as mean and standard deviation, whereas categorical variables were presented as counts and percentages. The Chi-square test was used for qualitative data comparison, and the Student’s t-test was applied to quantitative data. P < 0.05 was considered statistically significant.

RESULTS

A total of 137 patients with IT femur fractures were included in the study. The mean age of the patients was 65.4 years (standard deviation [SD] = 10.2) [Figure 5 and Table 1]. The majority of patients were female (59.9%, n = 82). The most common age group was 61–70 years (40.2%) [Figure 6 and Table 2]. Hypertension and diabetes were prevalent comorbidities, affecting 21.9% and 16.1% of patients, respectively [Figure 7 and Table 3].

Figure 5.

Frequency distribution table for age distribution

Table 1.

Age group distribution

Age Group (Years)	Frequency (%)
40-50	12 (8.8%)
51-60	42 (30.7%)
61-70	55 (40.2%)
>70	28 (20.3%)

Figure 6.

Pie chart diagram for gender distribution

Table 2.

Gender distribution and their mean age (years)

Gender	Frequency (%)	Mean Age (years)
Male	55 (40.1%)	64.1±9.8
Female	82 (59.9%)	66.3±10.5

Figure 7.

Pie chart diagram for comorbidities – hypertension and diabetes mellitus

Table 3.

Co-morbidities

Comorbidity	Frequency (%)
Hypertension	30 (21.9%)
Diabetes	22 (16.1%)

The predominant mode of injury was self-fall, accounting for 89.1% of fractures. Road traffic accidents constituted 10.9% [Figure 8 and Table 4]. Right-sided fractures were more common (66.4%) than left-sided fractures (33.6%) [Figure 9 and Table 5]. The AO/OTA (2018) classification identified 31A 2.2 as the most frequent subtype (46.7%), indicating a high prevalence of unstable fractures [Figure 10 and Table 6].

Figure 8.

Pie chart for mode of injury (self-fall/road traffic accident). RTA: Road traffic accident

Table 4.

Mode of injury

Mode of Injury	Frequency (%)
Self-fall	122 (89.1%)
RTA	15 (10.9%)

Figure 9.

Pie chart for laterality of fracture (right/left)

Table 5.

Laterality of fracture

Side	Frequency (%)
Right	91 (66.4%)
Left	46 (33.6%)

Figure 10.

Frequency distribution table for Arbeitsgemeinschaft für Osteosynthesefragen/Orthopaedic Trauma Association (AO/OTA) classification (2018)

Table 6.

AO/OTA (2018) classification distribution

AO/OTA Classification (2018)	Percentage (%)
31A 2.2	46.7
31A 1.3	19.7
31A 1.2	16.8
31A 3.3	8.8
31A 2.3	4.4
31A 3.1	2.2
31A 3.2	1.5

Females were predominantly found to sustain fractures due to self-falls, aligning with the understanding that osteoporotic fractures are more common in postmenopausal women.

Bone quality assessment using HU values revealed a mean HU value of 118.5 (SD = 26.7) for the entire study population. Critically, patients with stable fractures had significantly higher mean HU values (130.2 ± 22.1) compared to those with unstable fractures (105.4 ± 24.3 [Figure 11 and Table 7]. A t-test confirmed this as a statistically significant difference (P < 0.001) between the HU values of stable and unstable fractures. According to the 2018 AO/OTA classification, only 31A 1.2 fractures are considered stable, with all other subtypes being unstable.[10] This finding underscores the association between lower HU values, indicative of poorer bone quality, and unstable fracture patterns.

Figure 11.

Frequency distribution table for mean Hounsfield unit value of stable and unstable fracture

Table 7.

Mean HU values of stable and unstable fracture type

Classification	Mean HU Value±SD
Stable	130.2±22.1
Unstable	105.4±24.3

A Chi-square test also demonstrated a strong and statistically significant correlation (P < 0.001) between the AO/OTA classification (2018) and the CT-based classification by Dr. R. B. Kalia and Dr. Shobha Arora. This suggests good agreement between the systems in categorizing fracture patterns and reinforces the reliability of CT imaging for fracture stability assessment.

DISCUSSION

The demographic profile, with a mean age of 65.4 years and a majority being female, coincides with the established epidemiology of IT femur fractures, which predominantly affect elderly postmenopausal women prone to osteoporosis. The high prevalence of self-falls (89.1%) as the mode of injury further supports the link between low-energy trauma and osteoporosis among the elderly population.

The assessment of bone quality using CT-derived HU values provided crucial insights. The study demonstrated that lower HU values were significantly associated with unstable fracture patterns. This finding is consistent with previous research validating the use of HU values as a surrogate marker for BMD and their correlation with fracture risk and stability.[11] The mean HU value difference between stable and unstable fractures was statistically significant (P < 0.001), reinforcing the clinical utility of HU measurements in predicting fracture stability.

The significant association between gender and mode of injury (P < 0.001) highlights increased susceptibility to low-energy fragility fractures in postmenopausal elderly women. This finding underscores the importance of targeted osteoporosis screening and fall prevention strategies, particularly in elderly women, to mitigate the risk of IT fractures.

The strong correlation between the AO/OTA (2018) classification and the CT-based classification by Dr. R. B. Kalia and Dr. Shobha Arora (P < 0.001) validates the use of advanced imaging, such as 3D-CT, in providing a detailed and reliable assessment of fracture patterns. While AO/OTA is a widely used system, CT imaging offers enhanced visualization of comminution, displacement, and the stability of critical columns, which is invaluable for surgical planning, especially in complex or unstable fractures [Table 8].

Table 8.

Summary of comparative analysis between HU values, stability of fracture, mode of injury, gender and CT based classification with AO/OTA (2018) classification

Comparative Factor	Test Used	Statistical Value	P	Interpretation
HU Values: Stable vs. Unstable	t-test	8.81	<0.001	Lower HU values indicate higher risk of unstable fractures.
Mode of Injury vs. Gender	Chi-square test	17.42	<0.001	Females are more prone to fractures due to self-fall.
CT Classification vs. AO/OTA (2018)	Chi-square test	685.0	<0.001	Strong correlation between CT-based fracture assessment and AO/OTA classification (2018).

Thus, incorporating preoperative bone quality assessment using CT-derived HU values will help healthcare providers identify patients at higher risk of unstable intertrochanteric femur fractures in adults. This knowledge leads to better surgical planning like selection of augmented fixation techniques or specific implants designed to enhance stability in compromised bone, thereby improving patient outcomes and reducing complication rates of fixation failure.

Limitations of the study include its observational nature and the sample size. However, the statistically significant findings support the conclusions drawn. Future research could explore the direct impact of HU-guided surgical planning on long-term functional outcomes and complication rates in patients with IT femur fractures.

CONCLUSION

This study provides strong evidence for a statistically significant association between bone quality, assessed using CT-derived HU values, and fracture patterns in IT femur fractures in adults. Lower HU values, indicative of poorer bone quality, are significantly associated with more unstable fracture configurations. The findings highlight that elderly females are particularly susceptible to these fractures due to low-energy falls, reinforcing the need for targeted osteoporosis screening. The strong correlation between CT-based fracture assessment and the AO/OTA classification validates the crucial role of advanced imaging in accurately characterizing fracture patterns and predicting stability. Integrating HU-based bone quality assessment into routine clinical practice offers a valuable tool for early identification of patients at risk of unstable fractures, thereby guiding preoperative planning, optimizing surgical decision-making, and ultimately improving outcomes in the management of IT femur fractures.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.