https://orcid.org/0000-0001-9332-4757
Figures
Abstract
Background
Computed tomography (CT) Hounsfield Units (HU) offer valuable insights into the changes in bone and soft tissue densities, playing a crucial role in the diagnosis and management of various proximal femur conditions. This systematic review aims to consolidate the application of HU in assessing tissue quality in the proximal femur, with a special focus on osteonecrosis of the femoral head (ONFH) and implications for total hip arthroplasty (THA), thereby addressing unresolved issues in these areas.
Methods
We conducted a comprehensive literature search on MEDLINE/PubMed, EMBASE, Google Scholar, SpringerLink, Scops, Web of Science, and Bentham Science Publishers from inception to January 2024, following the PRISMA guidelines, to retrieve all studies relevant to the application of HU in assessing both bone and soft tissue quality of the proximal femur, particularly in the context of ONFH and THA. We systematically evaluated the key findings extracted from the included articles.
Results
This systematic review included a total of 58 studies, involving 15,668 patients. The sample sizes ranged from 50 to 685, with the CT slice thickness varying from 0.5 mm to 10 mm. The results mainly focused on three areas: (1) the relationship between HU and the density of proximal femoral tissues (n = 33); (2) the assessment of HU in predicting the risk of femoral head collapse (n = 10); (3) the application of HU during the perioperative period of THA (n = 15).
Conclusion
(1) HU can effectively contribute to the evaluation of bone and soft tissue densities in the proximal femur, and reflect local stress changes. (2) In ONFH patients, bone density does not decrease in the necrotic area of the femoral head before collapse. However, abnormally elevated HU at the outer boundary of the necrotic lesion are significant in assessing collapse risk. (3) HU can be used to preoperatively assess hip bone quality for THA, guide surgical approaches, predict intraoperative fractures, monitor postoperative bone ingrowth or absorption, identify and quantitatively evaluate periprosthetic loosening, and guide postoperative rehabilitation.
Citation: Yang T-j, Wen P-p, Ye X, Wu X-f, Zhang C, Sun S-y, et al. (2025) CT Hounsfield units in assessing bone and soft tissue quality in the proximal femur: A systematic review focusing on osteonecrosis and total hip arthroplasty. PLoS ONE 20(3): e0319907. https://doi.org/10.1371/journal.pone.0319907
Editor: Giulia Pascoletti, University of Perugia: Universita degli Studi di Perugia, ITALY
Received: June 12, 2024; Accepted: February 10, 2025; Published: March 26, 2025
Copyright: © 2025 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting information files.
Funding: This work was supported by the Scientific and Technological Innovation Project of China Academy of Chinese Medical Sciences [grant numbers CI2021A05406].
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Osteonecrosis of the femoral head (ONFH) poses a significant challenge in orthopedic practice, often leading to femoral head collapse and necessitating total hip arthroplasty (THA) in advanced stages [1,2]. The ability to accurately assess the quality of bone and soft tissue in the proximal femur is crucial for diagnosing ONFH, predicting femoral head collapse, and planning THA. Computed tomography (CT) Hounsfield Units (HU) have emerged as a valuable tool in this regard, offering insights into bone and soft tissue densities that are indicative of underlying pathological changes.
CT is a medical imaging technique that uses the absorption and attenuation of X-ray photons to produce cross-sectional images. Each tissue’s X-ray absorption is determined by its linear attenuation coefficient μ, with water typically set at 1. The CT value, expressed in Hounsfield Units (HU), represents tissue density [3]. Water has a CT value of 0 HU, air -1000 HU, and bone tissue typically ranges from 300 to 3000 HU. HU values are directly proportional to tissue density, with higher values indicating denser tissues [4].
Despite the potential of HU in clinical application, the literature presents a fragmented view, with studies focusing on various aspects of proximal femur assessment in isolation. This systematic review aims to consolidate current knowledge on the application of HU in the proximal femur, with a special emphasis on its role in ONFH and THA. By providing a comprehensive analysis of the available evidence, we seek to highlight the clinical utility of HU measurements, address unresolved issues, and suggest directions for future research.
2. Materials and methods
The authors adhered to the criteria outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for this review [5].
2.1. Search strategy
Two researchers (Cheng Zhang and Shiyi Sun) conducted a comprehensive literature search from inception to January 2024 on multiple databases including MEDLINE/PubMed (National Center for Biotechnology Information, NCBI), EMBASE(Ovid), Web of Science, Google Scholar, SpringerLink, Scops(Directscops), and Bentham Science Publishers. The search string included medical subject headings (MeSH) and free-text terms. By applying Boolean logic, the keywords used to select a maximum number of relevant studies were: (“Hounsfield Unit” or “HU” in subject terms) AND (“Osteonecrosis of Femoral Head” or “ONFH” or “Femoral Head Avascular Necrosis” or “FHAN” or “osteonecrosis” or “hip” or “coxa” in subject terms) AND (“microarchitectural” or “Collapse” or “subchondral” or “crescent sign” or “acetabular” or “Trabecular bones” or “bone marrow edema” or “double-line sign” or “sclerotic rim” in abstract). Additionally, a search was conducted in the reference lists of the selected articles and reviews to identify any potentially missed studies.
2.2. Inclusion and exclusion criteria
To guarantee quality and accuracy, only peer-reviewed journal papers with full-text availability were included. This study establishes the inclusion and exclusion criteria outlined in Table 1. Each paper is thoroughly reviewed to ascertain its eligibility for analysis.
2.3. Evidence quality assessment
Based on these criteria, the researchers conducted the PRISMA review process (Fig 1), which included identification, screening, eligibility assessment, and analysis. When discrepancies arose between the researchers, a third physician made the final decision regarding paper inclusion or exclusion. Additionally, the studies were evaluated using a modified Oxford Centre for Evidence-Based Medicine 2011, and each association was assigned a level of evidence [6] (S4 File). The assigned levels of evidence were discussed among team members until a consensus was reached.
To assess the robustness of the synthesized results, sensitivity analyses were conducted by excluding studies with the highest risk of bias. The results remained consistent, indicating that the overall findings are robust and not unduly influenced by any single study. Specific sensitivity analyses conducted include: Excluding studies with less than 50 patients; Removing studies that did not use standardized CT slice thickness; Analyzing the impact of excluding studies with the highest heterogeneity scores.
3. Results
3.1. Overview of findings
After several rounds of screening, 58 papers meeting the standard were eventually retained, involving 15,668 patients. The sample sizes ranged from 50 to 685, with the CT slice thickness varying from 0.5 mm to 10 mm. The results mainly focused on three areas: (1) the relationship between HU and the density of proximal femoral tissues (n = 33); (2) the assessment of HU in predicting the risk of femoral head collapse (n = 10); (3) the application of HU during the perioperative period of THA (n = 15).
3.2. HU can effectively detect the density of bone tissues in the proximal femur
Based on a literature review, we identified 15 studies demonstrating a strong correlation between HU and bone density in the proximal femur. These datas can help evaluate and quantify the bone quality of the proximal femur [7–21]. Ye [11] examined data from 680 patients who underwent CT and DEXA scans of the proximal femur between 2010 and 2020. HU was measured in four axial slices of the proximal femur, and Pearson correlation coefficients were utilized to compare these measurements with DEXA results. The study revealed a strong positive correlation between HU in the proximal femur and T-score, neck bone mineral density, and total hip bone mineral density (r = 0.777, r = 0.748, r = 0.746; all p < 0.001). The area under the curve for diagnosing osteoporosis using HU was 0.893 (p < 0.001), with a cutoff of 67 HU resulting in a sensitivity of 84%, specificity of 80%, positive predictive value of 92%, and negative predictive value of 65%. This trial not only confirmed the strong positive correlation between HU at the proximal femur and DEXA results, but also demonstrated the potential of HU for opportunistic screening of osteoporotic patients (other pertinent studies are presented in Table 2). Importantly, a study by Daniel [8] discovered that the correlation between HU and DEXA remained consistent across various age, sex, and scan interval groups when comparing patients with osteoporosis, osteopenia, and normal bone density. Based on the aforementioned studies, it can be concluded that HU obtained through CT can evaluate the bone density of the proximal femur.
3.3. HU can effectively detect the density of soft tissues in the proximal femur
We conducted a literature search and included 18 studies that demonstrated the use of HU for assessing and quantitatively measuring tissue density and mechanical changes in the vicinity of the hip joint [22–38] (refer to Table 3). In a longitudinal study involving 473 individuals focusing on health and aging, Jung discovered a significant positive correlation between HU in thigh muscles and femoral neck bone density [26]. Lu indicated a significant correlation between the density of the overall hip joint bones and the density of the gluteus maximus (males: P = 0.012; females: P = 0.043) [38]. Thomas suggested that HU can be used to quantify the impact of resistance exercise on bone and muscle, including describing the spatial heterogeneity response of bone to different loads caused by muscle contractions [39]. The selected participants engaged in 16 weeks of resistance exercise. The first group (squat/deadlift, n = 7) performed 4 sets each of squats and deadlifts, while the second group (abduction/adduction, n = 8) performed 4 sets each of standing hip abduction and adduction exercises. Participants exercised three times a week, gradually increasing the load to reach maximum intensity. CT scans were conducted before and after training to evaluate the cortical bone density and volume, as well as muscle density and volume associated with each group. The results indicated that the squat/deadlift group experienced increases in both femoral neck cortical bone density and volume, as well as hip extensor cross-sectional area and HU. Similarly, the abduction/adduction group demonstrated increases in trochanteric cortical bone density and volume, along with hip adductor cross-sectional area and HU. Expanding on these findings, Fernandez [40] conducted further investigations by utilizing a specialized calculation formula that combined HU and hip muscle force. The study revealed that enhancing hip muscle strength could effectively reduce peak stresses experienced within the pelvis and acetabulum, with the rectus femoris, gluteus maximus, and iliac muscle playing crucial roles. Considering the research discussed earlier, HU measurements can effectively evaluate the density of soft tissues in the proximal femur.
4. Discussion
4.1. Advantages of HU in assessing proximal femur bone density compared to dual-energy X-ray absorptiometry (DEXA)
While DEXA is widely recognized as the “gold standard” for assessing bone quality [41], its application in ONFH patients presents challenges. Due to structural changes like trabecular loss, femoral head collapse, and increased density at certain regions, DEXA often struggles to accurately assess bone density in the proximal femur [8,42]. In response, multiple studies have explored HU measurements as an alternative for assessing bone quality in this region, demonstrating several distinct advantages over DEXA.
Firstly, HU offers a broad application scope, with quantitative bone density assessments that do not require additional radiation or costs. In addition to hip-specific CT scans, HU measurements can also be obtained from existing abdominal [8] or pelvic CT images [ 16,18], making it easier to identify high-risk patients with localized osteoporosis. This accessibility facilitates early intervention, helping to reduce the risk of fragility fractures and associated conditions.
Secondly, HU enables enhanced visualization of bone microstructure. Unlike DEXA, which cannot distinguish between cortical and trabecular bone [43], HU can separately quantify these components. For instance, studies by Lim [44] demonstrated a positive correlation between certain HU measurements in trabecular regions and osteoporosis presence, while specific cortical HU values correlated negatively with osteoporosis. These findings illustrate HU’s ability to offer insights into osteoporosis progression based on distinct cortical and trabecular characteristics.
Lastly, HU minimizes interference from overlapping tissues, a common issue with DEXA. DEXA measurements can be affected by overlapping tissues such as muscle, fat, and water, potentially leading to inaccurate bone density readings [7]. For example, subclinical femoral head collapse can cause bone marrow edema, reducing radiographic density and potentially masking the actual bone condition on DEXA scans [45]. In obese patients, excess fat around the hip and abdomen further complicates DEXA readings, as adipose tissue absorbs X-ray energy, resulting in lower apparent bone density. Conversely, CT scans using HU can directly measure the density of trabecular bone layers, accurately distinguishing bone from surrounding tissues and providing a clearer, interference-free assessment [9].
4.2. HU guiding insights into proximal femur bone density and its mechanical implications
HU is closely associated with the mechanical strength of local tissue. The distribution of subchondral bone density, as indicated by HU, can indirectly infer the distribution of stress and the joint’s loading history [46]. Initial studies combining HU-based bone density with indentation tests revealed that high HU values strongly correlate with increased mechanical strength, while low HU values indicate lower strength, with density concentrated primarily in the medial and central regions of the proximal femur [47]. Other studies reported strong correlations, with determination coefficients (R²) from 0.74 to 0.97 and Pearson coefficients between 0.86 and 0.98, when comparing density with mechanical strength across various sites [48]. Hoechel’s findings [49] further confirmed that high-density regions, such as the anterior superior acetabulum and femoral head articular surface, align with areas of high mechanical strength, although individual variation exists. While quantitative comparisons between bone density and mechanical strength are still developing, these findings support HU’s utility in inferring localized stress changes within bone tissue.
4.3. HU reveals contrasts between fat and muscle in the proximal femur
In addition to analyzing and quantifying muscle tissue composition, HU can precisely distinguish between fat and muscle by utilizing specific attenuation coefficients for each tissue type. This capability enables the description of various physiological and pathological conditions. Anton’s study [33] demonstrated that a 10% increase in tissue fat decreases HU by 0.75-1, with higher fat levels in gluteal muscles indicating significant muscle wasting and reduced mobility in hip osteoarthritis patients. In-depth research by Mustafa [28] revealed that fatty degeneration of the lumbar muscles can influence the type of hip fracture. Elderly patients with robust lumbar muscles may experience femoral neck fractures due to contraction and twisting during falls. Overall, HU effectively identifies ectopic fat in skeletal muscles, linking increased fat deposition to impaired muscle function and metabolic health. This makes HU a valuable tool for assessing soft tissue around the hip [27], supporting early intervention and non-invasive treatment strategies [40].
4.4. The application of HU in the evaluation of ONFH
Femoral head collapse is a critical event in the progression of ONFH, impacting the hip joint’s outcome. However, ONFH is often asymptomatic prior to collapse, making early diagnosis and timely intervention challenging. Current consensus suggests that collapse risk depends on factors like necrotic lesion size, location, and stress distribution, emphasizing the need to assess collapse risk for appropriate treatment planning [50].
Currently, there are varying opinions on changes in density within the pre-collapse area of osteonecrosis. Lulu suggested that bone resorption in the necrotic area lowers density, weakens mechanical strength, and serves as an early indicator of collapse risk [51]. However, previous studies have not demonstrated a decrease in bone density within the necrotic lesion. Notably, prior evaluations using DEXA may have introduced inaccuracies due to overlapping images from the acetabular wall and femoral head. To address this, several researchers have employed HU for a more precise assessment of femoral head density and bone microstructure, offering clearer insights into actual bone density conditions within necrotic regions.
Consistently, multiple studies have demonstrated that bone density in pre-collapse necrotic lesions remains unchanged [20,52,53]. For instance, Shoji [20] used HU to assess bone density in pre-collapse ONFH patients compared to controls, selecting the upper one-third of the femoral head as the region of interest (ROI). The study, using propensity score matching, found no significant difference in HU values between ONFH patients and controls within this ROI. Similarly, Cheng’s research revealed no significant differences in bone density or micro-mechanical properties between the necrotic and healthy trabecular areas [52]. This study also conducted histopathological and immunohistochemical analyses, finding increased osteoclast activity in the subchondral bone and necrotic areas, alongside increased osteoblast activity in the sclerotic region, indicating a reduction in macroscopic mechanical strength associated with shifts in osteoblast and osteoclast activity. Kazuyuki’s study corroborated these findings, observing heightened osteoclast activity within the necrotic femoral head [53]. These results suggest that HU values within the necrotic lesion remain stable until structural disruptions such as trabecular rupture, bone resorption, or bone marrow edema occur, leading to collapse. Thus, HU does not typically decrease in the pre-collapse stage.
Given that the HU of the necrotic lesion does not decrease, the question arises: How can we predict femoral head necrosis? Numerous studies have indicated that the outer boundary of the necrotic lesion plays a pivotal role in assessing the risk of collapse [20,54–58].
In ONFH, a demarcation line separates necrotic from viable tissue, marking the onset of pathological phases including ischemia, repair, and sclerosis. Baba’s study [20] revealed that ONFH patients who experienced femoral head collapse had significantly higher HU values at the lesion’s outer boundary compared to non-collapse cases, though there was no significant HU difference in the anterior upper part of the femoral head between groups. Histological studies of femoral head specimens consistently link collapse with subchondral fractures at the lesion’s boundary [54]. Finite element analysis further supports this, showing stress concentration at the outer border of the femoral head prior to collapse, coinciding with alterations in the sclerotic margin [55]. According to Li’s research data [56], the variation in local stress distribution is responsible for the HU changes at the lateral border before the occurrence of femoral head collapse. In a retrospective study of 40 ARCO stage II ONFH patients, the mean maximum von Mises stress levels were significantly higher in the collapse group (2.955 ± 0.540 MPa) than in the non-collapse group (1.923 ± 0.793 MPa) (P < 0.01). Building on these findings, Kubo reported that collapse rates at the sclerotic border in the acetabulum’s weight-bearing region varied significantly across different sections, with the highest rate (81%) in the outer third [57]. These findings indicate that stress is concentrated at the outer border, leading to shear stress between the thickened repair zone and adjacent necrotic trabeculae, resulting in subchondral fractures [55,58]. Note that HU can also differentiate stress-induced femoral head insufficiency fracture (SIF) from ONFH. Kawano’s research [59] reported significantly lower bone volume fraction, trabecular thickness, and bone density in collapsed areas of ONFH compared to adjacent non-collapse regions, whereas SIF cases showed no such microstructural differences between collapsed and non-collapsed areas, highlighting distinct pathogenic mechanisms between the two conditions.
In conclusion, detecting HU changes at the outer boundary of necrotic lesions offers valuable insights into collapse risk in ONFH patients, supporting timely evaluation and intervention to potentially alter the disease course.
4.5. Application of HU in perioperative THA
HU provides localized insights into bone and soft tissue quality around the hip, making it valuable for preoperative assessment, surgical planning, and prognosis in THA patients.
4.5.1. Application of HU in preoperative assessment for THA.
Patients undergoing orthopedic surgery often experience poor bone health, with over 50% of joint replacement patients presenting with osteoporosis or osteopenia [60]. A cross-sectional study found that 26% of THA patients had osteoporosis [61], yet fewer than 4% of surgeons routinely measure bone density [60]. Even when osteoporosis is diagnosed, targeted pharmacological interventions are rarely used [62], despite evidence linking poor skeletal health with negative recovery outcomes, higher complication rates, and increased revision surgeries [63, 64]. Utilizing HU for osteoporosis diagnosis enables effective intervention, reducing complications and revision rates [65], and preserving bone mass post-surgery [66]. Additionally, HU’s adaptability allows measurements from any targeted region, enhancing its utility in clinical practice.
4.5.2. Surgical approach guidance and intraoperative fracture prediction in THA using HU.
HU measurements offer valuable guidance for optimizing surgical approaches and predicting fracture risks in THA. A retrospective study involving 64 patients found that the lateral approach significantly reduced HU values in obturator muscles, indicating potential muscle degeneration, whereas the anterior-lateral approach increased HU in gluteus medius and tensor fasciae latae muscles, suggesting better muscle preservation [34]. Noda’s comparison of the “Bald Spot” technique with conventional trochanteric nail insertion further supports the role of HU in surgical planning, showing that the BS technique minimizes damage to the gluteus medius [67],
Additionally, Boomsma’s study of 317 THA patients found that HU values above the acetabulum were significantly lower on the operated side [68], highlighting changes in bone density that could signal the need for revision surgery [69]. Building on this, Nishi’s study of 301 patients linked lower preoperative HU levels in specific acetabular regions to a higher intraoperative fracture risk, with fractures most common in the superior aspect of the acetabulum (40%) [70]. These findings demonstrate that HU effectively predicts fracture risk in “weaker” regions, underscoring the importance of preoperative HU assessment in enhancing surgical precision and patient safety.
4.5.3. Application of HU in the assessment of postoperative THA.
HU effectively assesses changes in bone and muscle density following THA. In a 12-year retrospective study of 11 THA patients, Lengsfeld observed a 50-150 HU decrease (10%) in femoral density within the first year post-surgery, reaching up to 400 HU (30%) after 12 years, with the most significant density loss near the distal lesser trochanter [71]. Gislason’s findings supported this trend [72]. Additionally, research has shown sustained muscle atrophy up to two years post-THA, with reductions in radiodensity of key hip muscles, including the gluteus maximus (10.1 HU) and gluteus medius (5.6 HU), compared to the healthy limb [36]. These insights support the need for targeted postoperative rehabilitation.
HU also enables monitoring of bone remodeling and implant stability. In animal studies, Miori [73] found a strong correlation between HU values and implant stability metrics—such as insertion and removal torque values—indicating HU’s potential for quantifying primary implant stability and identifying peri-implant loosening. Retrospective studies by Jixing Fan further demonstrated a significant correlation between lower femoral head HU values and higher prosthesis failure rates, with failure group HU values significantly lower than non-failure group values (133.25 ± 34.10 vs. 166.12 ± 42.68, p = 0.004) [74]. These findings highlight HU’s role in specific monitoring of bone remodeling and implant success.
4.6. Advantages and shortcomings
From a technical standpoint, HU is a relative value obtained through attenuation coefficients calibrated against water, rather than absolute value. Consequently, variations in CT scanner parameters, including slice thickness, brands, models, algorithms, or detection conditions can lead to differences in the data generated by HU, resulting in a lack of repeatability in image measurement data [75–77]. Calibration of CT scanners, ensuring standardized imaging protocols and calibration procedures, is essential to mitigate these discrepancies. Standardizing scanning parameters across different devices and protocols would enhance the reproducibility and consistency of HU measurements. Future research should prioritize not only standardizing these parameters but also establishing a universal calibration system for HU measurements, reducing variability and improving diagnostic reliability. Consequently, HU can only serve as a supplementary tool for diagnosing osteoporosis in conjunction with DEXA. Future research should aim to establish a more comprehensive and standardized evaluation system based on HU, which would enhance the guidance for diagnosing and treating patients with ONFH.
Regarding specific operations, because three-dimensional ROI selection cannot encompass the entire necrotic lesion of the femoral head and due to variations in trabecular bone density, errors may occur in HU depending on the position and size of the ROI. This can hinder the accurate reflection of the likelihood of collapse in extensive necrotic lesions [78]. Further research is needed to improve the accuracy of these measurements.
Regarding the methodological quality of the included studies, we recognize significant heterogeneity due to variations in study design, population characteristics, outcome measures, and the observational and retrospective nature of most studies, affected by differences in race, gender, age, and socioeconomic patterns. This diversity, compounded by moderate to low levels of evidence, selection bias, and limited sample sizes, may challenge the generalizability of our findings. Future research must prioritize standardized approaches, employing rigorous frameworks, and incorporating larger and more diverse sample sizes as well as prospective designs. A critical appraisal of study quality using standardized tools will aid in identifying and addressing potential biases, including publication bias. This rigorous evaluation is essential for enhancing the review’s robustness and advancing our understanding of HU’s role in assessing osteonecrosis of the femoral head (ONFH), ensuring findings are more reliably applied in clinical contexts.
5. Conclusions
The systematic review demonstrates that Hounsfield Units (HU) can effectively assess the density of bone and soft tissue in the proximal femur, reflecting local stress changes. Additionally, bone density in the necrotic area of the femoral head of ONFH patients does not decrease before collapse, and abnormally elevated HU at the outer boundary of the necrotic lesion is significant in assessing the risk of collapse. HU can also evaluate hip bone quality prior to THA, predict intraoperative fracture, and monitor postoperative bone growth or absorption. Furthermore, HU can identify and quantify periprosthetic loosening, guide surgical approaches and postoperative rehabilitation. In conclusion, despite limitations, CT Hounsfield Units remain a valuable tool for evaluating osteonecrosis of the femoral head and deserve further investigation and promotion.
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