|Year : 2021 | Volume
| Issue : 1 | Page : 17-20
Comparison of Radiographic Singh Index with Dual-Energy X-Ray Absorptiometry Scan in Diagnosing Osteoporosis
Furqan Rasul Mir, Imran Nazir, Mohammad Naseed
Department of Orthopaedics; Department of Radio Diagnosis and Imaging, SKIMS, Srinagar, Jammu and Kashmir, India
|Date of Submission||06-Aug-2020|
|Date of Acceptance||26-Aug-2020|
|Date of Web Publication||12-Jan-2021|
Dr. Mohammad Naseed
SKIMS, Soura, Srinagar, Jammu and Kashmir
Source of Support: None, Conflict of Interest: None
Objective: The objective of this study was to assess the accuracy of radiographic Singh index (SI) with respect to dual-energy X-ray absorptiometry (DEXA) scan in diagnosing osteoporosis. Materials and Methods: We conducted a cross-sectional study on 100 postmenopausal women in the Department of Radiodiagnosis, SKIMS, Soura, Srinagar, from June 2019 to December 2019. We obtained right or left standard anteroposterior hip radiograph in each patient and compared its SI grade to the densitometry results obtained from the DEXA study of the corresponding hip. Results: Out of the selected patients, 7% had DEXA bone mineral density (BMD) values in normal range (T-score ≤1), 81% in osteopenic range (T-score >1.00–<2.5), and 12% in osteoporotic range (T-score ≥2.5). There was no statistically significant correlation (r = −0.108, P = 0.286) between SI grade and WHO BMD category (normal, osteopenia, or osteoporosis). There was no statistically significant correlation (r = 0.191, P = 0.057) between the SI grade and the mean absolute DEXA BMD value. There was also no statistically significant correlation (r = −0.195, P = 0.052) between SI grade and mean DEXA T-score. Conclusion: Our study found a poor correlation between radiographic SI and DEXA densitometry results. We concluded that the SI cannot be used as a substitute for DEXA study in diagnosing osteoporosis.
Keywords: Dual-energy X-ray absorptiometry scan, fracture, osteoporosis, Singh index
|How to cite this article:|
Mir FR, Nazir I, Naseed M. Comparison of Radiographic Singh Index with Dual-Energy X-Ray Absorptiometry Scan in Diagnosing Osteoporosis. Matrix Sci Med 2021;5:17-20
|How to cite this URL:|
Mir FR, Nazir I, Naseed M. Comparison of Radiographic Singh Index with Dual-Energy X-Ray Absorptiometry Scan in Diagnosing Osteoporosis. Matrix Sci Med [serial online] 2021 [cited 2023 Apr 1];5:17-20. Available from: https://www.matrixscimed.org/text.asp?2021/5/1/17/306857
| Introduction|| |
Osteoporosis is defined as a reduction in the strength of bone that leads to an increased risk of fractures. Osteoporosis is prevalent among postmenopausal women but also occurs in men and women with underlying predisposing conditions associated with bone demineralization. Its major clinical manifestations are vertebral and hip fractures, although fractures can occur at almost any skeletal site. Common risk factors for osteoporosis include old age, postmenopausal status, long-term steroid therapy, alcohol use, smoking, Vitamin D deficiency, and sedentary lifestyle. Data from the European Vertebral Osteoporosis Study have demonstrated that the age-standardized prevalence of osteoporosis in the European population is 12% for women and 12.2% for men aged 50–79 years, with an overall age-standardized incidence of 10.7/1000 person-years in women and 5.7/1000 person-years in men. Worldwide, it is estimated that 1 in 3 women above the age of 50 years will experience osteoporotic fractures, as well as 1 in 5 men.
Osteoporosis is called the “silent disease” because bone loss often does not have any symptoms until a bone breaks. The resultant fractures, particularly those of the hip, are associated with a high incidence of deep-vein thrombosis and pulmonary embolism and significant morbidity and mortality. Hip and spine fractures may result in chronic pain, deformity, dejection, disability, and death. The Surgeon General's “Report on Bone Health and Osteoporosis” and the National Osteoporosis Foundation's “Physician's Guide to Prevention and Treatment of Osteoporosis” identify osteoporosis as a major public health concern and emphasize the importance of using bone mineral density (BMD) testing as a clinical tool to diagnose patients at high risk of fracture before the first fracture occurs.,
The early detection of osteoporosis is important because many drug treatments are available that have proven effective in reducing the rate of fractures and subsequent complications. Radiologic imaging lies at the core of such early diagnostic capability. Several noninvasive imaging techniques are available for detecting osteoporosis based on the degree of mineralization or demineralization of osseous tissue. These include dual-energy X-ray absorptiometry (DEXA), single-energy X-ray absorptiometry, radiogrammetry quantitative computed tomography (CT), and quantitative ultrasound (US). However, CT is expensive and involves greater radiation exposure. Limited experience is available with quantitative US.
DEXA is a highly accurate X-ray technique that has become the standard for measuring BMD at most centers. In addition, radiation dose with DEXA is relatively low. It represents the “gold standard” for diagnosis of osteoporosis and fracture risk prediction. This X-ray technique utilizes two differing kVp (30–50 and >70 keV) to enable subtraction of the overlying soft tissues and allow measurement of BMD in a given area of bone measured in g/cm2. This is typically done in the lumbar spine, proximal femur, and distal radius. In addition to areal density values in g/cm2, DEXA provides T-Scores that are standard deviations compared to a healthy young adult reference population. For postmenopausal women, constituting a significant proportion of osteoporotic patients, osteoporosis using DEXA is defined as T-Score ≥2.5 and osteopenia as T-Score between >1 and <2.5. However, DEXA scan is quite expensive and not readily affordable by a majority of patients with risk factors for osteoporosis, particularly in developing countries.
Plain radiographs allow qualitative and semi-quantitative evaluation of osteoporosis based on decreased radiodensity of bone, trabecular loss, and thickening of residual trabeculae due to redistribution of stresses. However, with radiographs, only advanced bone loss can be identified. The temptation of using X-rays as a screening method for osteoporosis stems mainly from easy availability and inexpensiveness, particularly in developing countries. The Singh Index (SI), which shows trabecular patterns in the proximal femur on plain radiographs, has been used as a predictor of osteoporosis. Singh suggested that the index could be used to differentiate patients with osteoporosis from normal individuals. Singh devised a scale from 1 to 6 to describe the degree of trabecular bone loss from the proximal femur (SI) [Figure 1]. Several studies identified the usefulness of SI as an inexpensive screening tool for osteoporosis,, whereas other studies refuted its role in osteoporosis., Therefore, we did a study to assess the accuracy of SI with respect to DEXA scan and whether SI can be a reliable substitute for DEXA scan in a primary care setting.
|Figure 1: Grades of singh index based on trabecular pattern of proximal femur|
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| Materials and Methods|| |
The study was carried out on postmenopausal women aged 50 years and above referred for imaging of osteoporosis. Patients with a clinical history of hip arthritis or radiographic evidence of proximal femur/acetabular fracture and those with prosthetic hardware in the region of groin were excluded from the study. After obtaining consent, 100 patients were selected for the study.
To determine SI, the anteroposterior digital radiograph of the right or left hip joint was taken in each patient with radiography conditions at 85 kVp and 25 mAs. Each selected radiograph was examined by an experienced observer, blinded to the DEXA study, and was assigned a grade from 1 to 6 by using the reference radiographic charts of SI method of proximal femoral trabecular features. Each radiographic grade was then compared with the densitometry results obtained from the DEXA study of the corresponding proximal femur.
Statistical analysis was performed using SPSS version 20 (the Statistical Package for the Social Sciences; IBM Software, NY). Spearman's correlation coefficient (r) was used. P < 0.05 was considered statistically significant.
| Results|| |
The following results were obtained in our study:
- [Table 1] represents distribution of cases on the basis of singh index.
- Out of the selected patients, 7% had DEXA BMD values in normal range (T-score ≤1), 81% in osteopenic range (T-score >1.00 to <2.5), and 12% in osteoporotic range (T-score ≥2.5) [Table 2].
- There was no statistically significant correlation (r = −0.108, P = 0.286) between SI grade and WHO BMD category (normal, osteopenia, or osteoporosis) [Table 3].
- There was no statistically significant correlation (r = 0.191, P = 0.057) between SI grade and mean absolute DEXA BMD value [Table 4].
- There was also no statistically significant correlation (r = −0.195, P = 0.052) between SI grade and mean DEXA T-score [Table 5].
|Table 2: Distribution of cases on the basis of dual-energy X-ray absorptiometry T-score|
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|Table 3: Distribution of dual-energy X-ray absorptiometry T-score on the basis of Singh index|
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|Table 4: Association between Singh index and the corresponding mean bone mineral density value|
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|Table 5: Association between Singh Index and the corresponding mean dual-energy X-ray absorptiometry T- score|
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| Discussion|| |
DEXA scan is considered the gold standard for the diagnosis of osteoporosis. Plain radiographs, which are tempting many physicians in developing countries for screening of patients with risk factors, are inexpensive and easily available but have a very low sensitivity, as around 30%–40% of demineralization must take place before changes appear on a plain radiograph. Several studies identified the usefulness of radiographic SI grade of proximal femur as an inexpensive screening tool for osteoporosis,, whereas other studies refuted its role in osteoporosis., Glüer et al. found radiographic measurements of SI, trochanteric region width, femoral neck, and femoral shaft cortex thickness capable of predicting hip fractures as powerfully as femoral neck BMD measured using DEXA. Julka et al. found SI as an inexpensive screening tool for osteoporosis and perhaps even predict the risk of fracture neck femur in patients with SI <4 and the highest risk in patients with an Sl of 2 or below. In contrast, Koot et al. concluded that the SI has no value in assessing the grade of osteoporosis. In a study on sixty healthy women, which was conducted by Soontrapa et al., it was shown that the SI has had poor reliability and poor diagnostic value in the screening of femoral neck osteoporosis. Salamat et al. concluded that the inter-observer variation of SI was large and there was no significant correlation between the SI and bone densitometry. Similarly, Epanov et al. and Lems demonstrated that the SI has had poor reliability and poor diagnostic value in the screening of femoral neck osteoporosis. Qadir and Bukhari concluded that there is “slight agreement” between DEXA scan and SI, which means that SI cannot be a reliable substitute for the gold standard DEXA scan. The results of our study showed that radiographic SI has a statistically insignificant correlation with mean DEXA bone mineral densitometry measurement (r = 0.191, P = 0.057), mean DEXA T-score (r = −0.195, P = 0.052), and DEXA-based WHO BMD category, that is, normal, osteopenia, or osteoporosis (r = −0.108, P = 0.286). No individual grade of SI could discriminate normal, osteopenic, and osteoporotic patients with adequate sensitivity and specificity in our study.
| Conclusion|| |
Our study showed a poor correlation between radiographic SI grade and densitometry results obtained from DEXA scan. No individual grade of SI discriminates normal, osteopenic, and osteoporotic patients with adequate sensitivity and specificity. Therefore, radiographic SI cannot be used as a substitute for DEXA study in diagnosing osteoporosis.
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Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]