Proximal femur fracture risk quantitative prediction method based on dimensional analysis

Abstract

The invention provides a proximal femur fracture risk quantitative prediction method based on dimensional analysis. According to the method, the influence of cancellous bone parameters, cortical bone parameters and proximal femoral geometric parameters is considered, and the fracture risk of a patient can be evaluated more accurately and comprehensively. In addition, according to the method, the effects of the various parameters are decoupled, and the quantitative relation of the influences of the various parameters on the proximal femur fracture is accurately obtained. Parameters measured by the method are a plurality of easily-measured parameters such as the femoral neck shaft angle and the femoral neck slenderness ratio in clinical CT, so that the method is simple and convenient to operate and easy to learn, and has a wide clinical application prospect.

Description

Technical Field

[0001] The present invention relates to the technical field of intersection of mechanics and medicine, and in particular to a quantitative prediction method for proximal femoral fracture risk based on dimensional analysis. Background Art

[0002] Proximal femoral fractures in the elderly are a common and serious type of osteoporotic fracture. The mortality rate of elderly people within one year after proximal femoral fractures is as high as 20% to 30%, so proximal femoral fractures are also called "the last fracture in life." The annual treatment cost in China is as high as tens of billions of yuan, which has imposed a heavy burden on patients, families and society. Accurate prediction of the risk of proximal femoral fractures can screen high-risk groups in advance and prevent them, thereby reducing the incidence of fractures, which has significant clinical value and social significance.

[0003] At present, bone mineral density (BMD) measurement based on dual-energy X-ray (DXA) and quantitative CT (QCT) is widely used in clinical practice to predict fracture risk. It reflects the cancellous bone quality of the measured area based on the grayscale of the image. In 1994, the World Health Organization (WHO) divided the degree of cancellous bone lesions into normal (T-scores>-1), osteopenia (-1>T-scores>-2.5) and osteoporosis (T-scores<-2.5) based on the peak standard deviation score (T-scores) of BMD measured by DXA, and the fracture risk was also divided into three levels: low, medium and high. This method has been widely used due to its convenience and economy and is regarded as the gold standard for fracture risk assessment. However, its prediction accuracy for hip fractures is only 40%~60%. Currently under development are the WHO-recommended fracture risk assessment tools FRAX and TBS trabecular bone scoring technology. However, FRAX has subjective qualitative limitations due to the use of questionnaires; TBS technology can currently only be used for lumbar vertebral positions with simpler cancellous bone structures. In addition, since fracture is the result of the combined effect of multiple parameters, all existing methods are unable to decouple the specific effects of various parameters, resulting in low prediction accuracy. Overall, it is urgent to develop a more scientific, reliable, and easy-to-use comprehensive prediction method for proximal femoral fracture risk. Summary of the invention

[0004] In view of the existing problems, the present invention proposes a quantitative prediction method for the risk of proximal femoral fracture based on dimensional analysis. This method takes into account the influence of cancellous bone parameters, cortical bone parameters and proximal femoral geometric parameters, and can more accurately and comprehensively evaluate the patient's fracture risk. In addition, this method decouples the effects of multiple parameters and accurately obtains the quantitative relationship of the influence of multiple parameters on proximal femoral fracture. Since the parameters measured by this method are multiple parameters that are easy to measure in clinical CT, such as femoral neck-shaft angle and femoral neck slenderness ratio, the operation is simple and easy to learn, and the clinical application prospect is broad.

[0005] The above object is achieved by the following technical solution: a method for quantitatively predicting the risk of proximal femoral fracture based on dimensional analysis, the method comprising the following steps:

[0006] Step 1: Read the CT image file of the proximal femur of the subject to be tested, and collect the geometric parameters of the proximal femur and the grayscale value of the Ward triangle; the geometric parameters of the proximal femur include the cortical thickness of the femoral neck SP area, the angle between the femoral neck and the femoral shaft, and the length and width of the femoral neck;

[0007] Step 2: Substitute the information collected from the CT image file into the quantitative prediction formula for the risk of proximal femoral fracture to calculate the anti-fracture strength of the proximal femur;

[0008] Step 3: Calculate the ratio of the proximal femoral anti-fracture strength to the estimated side-fall load, obtain the fracture risk factor, and evaluate the probability of proximal femoral fracture.

[0009] The present invention has the following beneficial effects:

[0010] The present invention takes into account the influence of cancellous bone parameters, cortical bone parameters and proximal femoral geometric parameters, and can more accurately and comprehensively assess the patient's fracture risk. In addition, the present invention decouples the effects of various parameters, and accurately obtains the quantitative relationship of the influence of various parameters on proximal femoral fractures. Since the parameters measured by the present invention are easy-to-measure parameters in multiple clinical CT such as femoral neck-shaft angle and femoral neck slenderness ratio, the operation is simple and easy to learn, and the clinical application prospects are broad. In addition, the present method is widely applicable and can play an accurate prediction role for patients of different genders and age groups. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0012] Figure 1 It is a schematic diagram of the implementation process of the method for quantitatively predicting the risk of proximal femoral fracture based on dimensional analysis of the present invention;

[0013] Figure 2 It is a schematic diagram of the geometric parameters of the proximal femur;

[0014] Figure 3 Schematic diagram of Ward's triangle. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] Specifically, Figure 1 As shown in FIG. 1 , an embodiment of the present invention is provided, which provides a method for quantitatively predicting the risk of proximal femoral fracture based on dimensional analysis, comprising the following steps:

[0017] Step 1: Read the CT image file of the proximal femur of the object to be tested, and collect the geometric parameters of the proximal femur and the grayscale value of the Ward triangle.

[0018] Step 2: Substitute the information collected from the CT image file into the quantitative prediction formula for the risk of proximal femoral fracture to calculate the anti-fracture strength of the proximal femur.

[0019] Step 3: Calculate the ratio of the proximal femoral anti-fracture strength to the estimated side-fall load, obtain the fracture risk factor, and evaluate the probability of proximal femoral fracture.

[0020] Furthermore, if Figure 2 As shown, the macroscopic geometry of the proximal femur described in step 1 includes the cortical thickness of the femoral neck SP region, the angle between the femoral neck and the femoral shaft, the length and width of the femoral neck (or the femoral neck length / diameter ratio), and the above macroscopic geometry is significantly correlated with the risk of fracture. Figure 2 middle, is the angle between the femoral neck and the femoral shaft, is the femoral neck length, Represents the width of the femoral neck.

[0021] Furthermore, the Ward triangle described in step 1 is a triangular area surrounded by the main compression trabeculae, the main tension trabeculae and the secondary compression trabeculae. The trabeculae in this area are relatively sparse, with large pores and are relatively weak, and are a common site for femoral neck fractures. Figure 3 As shown, the grayscale value of the Ward triangle in step 1 is obtained by obtaining the standard coronal image of the femur through Mimics software, manually identifying and selecting the Ward triangle in the coronal position of the femur, and calculating the total average CT value of the selected area.

[0022] Furthermore, the quantitative prediction formula for the risk of proximal femoral fracture described in step 2 is obtained by fitting dimensional analysis with finite element calculation results. Dimensional analysis can analyze the general laws followed by the quantitative relationship between things based on the form that all quantities must have. Dimensional analysis can be used to check whether the equations reflecting the laws of physical phenomena are correct in terms of measurement, and can also provide clues to finding certain laws of physical phenomena. The parameters involved in the quantitative prediction formula for the risk of proximal femoral fracture are the five parameters measured in step 1, namely:

[0023] ;

[0024] in, Indicates the cancellous bone gray value in Ward's triangle. is the angle between the femoral neck and the femoral shaft, is the femoral neck length, represents the width of the femoral neck, is the cortical thickness of the SP area.

[0025] As a preferred solution of the present invention, considering the actual physical laws, the function form obtained by dimensional analysis is:

[0026] ;

[0027] in, is the coefficient to be determined, , , represent the femoral neck length / diameter ratio and the relative thickness of the SP cortex, respectively.

[0028] As a preferred embodiment of the present invention, the numerical calculation results of the anti-fracture strength are obtained by using the finite element method based on the CT data of multiple patients, and the best fitting coefficient is obtained by multivariate nonlinear regression analysis. The specific form of the final quantitative prediction formula for the risk of proximal femoral fracture is:

[0029] ;

[0030] in, The unit is N, The unit is HU, The unit is m.

[0031] As a preferred embodiment of the present invention, the estimated side fall load is defined as the peak value of the impact load applied to the proximal femur during the process of a human body falling sideways from a standing height and colliding with the ground, and is calculated using the following formula:

[0032] ;

[0033] in, The unit is N; is the patient's height in cm; is the patient's weight, in N; is the thickness of the soft tissue on the trochanter side of the patient, in mm.

[0034] As a preferred embodiment of the present invention, the fracture risk factor FraR is defined as the ratio of the predicted side fall load of the patient to the anti-fracture strength of the proximal femur, specifically:

[0035] ;

[0036] The larger the value of FraR, the higher the risk of proximal femur fracture for the measured object. Specifically: if FraR > 1.1, it indicates that the measured object has an extremely high risk of proximal femur fracture; if 0.9 < FraR < 1.1, it indicates that the measured object has a relatively high risk of proximal femur fracture; if FraR < 0.9, it indicates that the measured object has a relatively low risk of proximal femur fracture.

[0037] The specific embodiments of the present invention have been described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that these embodiments can be modified and perfected without departing from the principles and spirit of the present invention defined by the claims and their equivalents, and these modifications and perfections should also be within the protection scope of the present invention.

Claims

1. A quantitative prediction method for proximal femoral fracture risk based on dimensional analysis, characterized in that: The method includes the following steps: Step 1: Read the CT image file of the proximal femur of the object to be measured, and collect the geometric shape parameters of the proximal femur and the gray values of the Ward's triangle area; the geometric shape parameters of the proximal femur include the cortical thickness of the S-P area of the femoral neck, the angle between the femoral neck and the femoral shaft, the length and width of the femoral neck; Step 2: Substitute the information collected from the CT image file into the quantitative prediction formula for the proximal femur fracture risk, and calculate the anti-fracture strength of the proximal femur; Step 3: Calculate the ratio of the anti-fracture strength of the proximal femur to the estimated side-fall load, calculate the fracture risk factor, and evaluate the probability of proximal femur fracture.

2. The method for quantitatively predicting the risk of proximal femoral fracture based on dimensional analysis according to claim 1, characterized in that: In Step 2, The quantitative prediction formula for the proximal femur fracture risk is: ； in, Indicates the cancellous bone gray value in Ward's triangle. is the angle between the femoral neck and the femoral shaft, is the femoral neck length, represents the width of the femoral neck, is the cortical thickness of the SP area; Considering the actual physical laws, the form of the quantitative prediction formula for the proximal femur fracture risk obtained through dimensional analysis is: ； in, is the coefficient to be determined, , , represent the femoral neck length / diameter ratio and the relative thickness of the SP cortex, respectively.

3. According to the method for quantitatively predicting the proximal femur fracture risk based on dimensional analysis described in claim 2, characterized in that, The best fitting coefficients are obtained through multiple non-linear regression analysis, and the specific form of the final quantitative prediction formula for the proximal femur fracture risk is: ； in, The unit is N, The unit is HU, The unit is m.

4. The method for quantitatively predicting the risk of proximal femoral fracture based on dimensional analysis according to claim 1, characterized in that: In Step 3, The estimated side-fall load is defined as the peak value of the impact load applied to the proximal femur during the process of a person falling sideways from the standing height and hitting the ground, and is calculated using the following formula: ； in, The unit is N; is the patient's height in cm; is the patient's weight, in N; is the soft tissue thickness on the trochanteric side of the patient, in mm.

5. According to the method for quantitatively predicting the proximal femur fracture risk based on dimensional analysis described in claim 4, characterized in that, Define the fracture risk factor FraR as the ratio of the patient's estimated side-fall load to the anti-fracture strength of the proximal femur, specifically: ； If FraR > 1.1, it indicates that the risk of proximal femur fracture for the object to be measured is extremely high; if 0.9 < FraR < 1.1, it indicates that the risk of proximal femur fracture for the object to be measured is relatively high; if FraR < 0.9, it indicates that the risk of proximal femur fracture for the object to be measured is relatively low.

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