A method and system for detecting vBMD based on PCCT

Abstract

The application relates to a PCCT-based vBMD detection method and system, which comprises the following steps: collecting an original image through PCCT scanning, reconstructing the original image to obtain a spectral image in SPP format, inputting the spectral image in SPP format into a post-processing workstation to generate a calcium map and obtain a CaCT value, converting the CaCT value into a vBMD value according to a conversion coefficient of the CaCT value into the vBMD value, and obtaining the vBMD value through the CaCT value; wherein the conversion coefficient of the CaCT value into the vBMD value is established as follows: taking the real hydroxyapatite concentration of a phantom as the vBMD value, setting an ROI in the phantom, scanning the ROI through PCCT, reconstructing to obtain a spectral image in SPP format, inputting the spectral image in SPP format into the post-processing workstation to obtain a calcium map and obtain an average CaCT value of the ROI, and obtaining the conversion coefficient of the CaCT value into the vBMD value according to the vBMD value and the average CaCT value. Compared with the prior art, the application saves labor and improves cost efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of bone density detection, in particular to a PCCT-based vBMD detection method and system. BACKGROUND

[0002] In recent years, with the development of population aging, the incidence of osteoporosis characterized by bone loss and bone tissue microstructure disorder gradually increases, which increases the risk of bone fracture and social and economic burden of patients. Bone mineral density (BMD) value is the most commonly used quantitative index of osteoporosis, which is considered to be an independent predictor of fracture risk and all-cause mortality.

[0003] Dual-energy X-ray absorptiometry (DXA) can generate area BMD (aBMD) values of the entire vertebrae, which is a convenient and cost-effective method for detecting osteoporosis. However, the accuracy of this two-dimensional measurement method is subject to spinal degeneration, vascular calcification, and spinal scoliosis. Quantitative computed tomography (QCT) uses a three-dimensional method to define the region of interest in cancellous bone, which can obtain more real volume BMD (vBMD) values without the interference of tissue overlap artifacts. However, QCT requires regular phantom calibration to maintain the accuracy of the measurement values, which is time-consuming and labor-intensive. Dual-energy CT (DECT) can distinguish materials by using the energy dependence of the photoelectric effect under different X-ray spectra. Compared with QCT, BMD quantification based on DECT hydroxyapatite specificity has comparable diagnostic accuracy in detecting abnormal BMD in vivo. However, except for dual-layer detector CT, the current commonly used DECT method requires a preset sequence, and vBMD values cannot be obtained in conventional CT scans, so it is difficult to perform opportunistic screening for osteoporosis. SUMMARY

[0004] The purpose of the present application is to overcome the defects of the prior art and provide a PCCT-based vBMD detection method and system, which saves labor and improves cost-effectiveness.

[0005] The purpose of the present application can be achieved by the following technical solutions:

[0006] A PCCT-based vBMD detection method, comprising the following steps:

[0007] Collecting original images by PCCT scanning and reconstructing the original images to obtain spectral images in SPP format;

[0008] Inputting the spectral images in SPP format into a post-processing workstation to generate a calcium map and obtain CaCT values;

[0009] Obtaining vBMD values from CaCT values according to the conversion coefficient of CaCT values to vBMD values.

[0010] The conversion coefficient of the CaCT value into the vBMD value is established as follows:

[0011] The real hydroxyapatite concentration of the phantom is taken as the vBMD value;

[0012] An ROI is set in the phantom, the ROI is scanned by PCCT, and a spectral image in SPP format is reconstructed;

[0013] The spectral image in SPP format is input into the post-processing workstation to obtain a calcium map, and an average CaCT value of the ROI is obtained;

[0014] The conversion coefficient of the CaCT value into the vBMD value is obtained according to the vBMD value and the average CaCT value.

[0015] Further, the reconstruction parameters include multiple of the layer thickness, the layer spacing, the quantitative kernel, the quantum iterative reconstruction level, the matrix size, and the scanning field of view.

[0016] Further, the phantom is a standardized European spine phantom, and includes three artificial vertebrae.

[0017] Further, the ROI is drawn at the center, the upper third, and the lower third of each of the artificial vertebrae.

[0018] Further, the conversion coefficient of the CaCT value into the vBMD value is:

[0019] vBMD = CaCT × 0.82

[0020] In the formula, vBMD is the vBMD value, and CaCT is the CaCT value.

[0021] Further, the calcium map is generated based on decomposition of three substances, including water, air, and calcium.

[0022] Further, the spectral image in SPP format is analyzed on the post-processing workstation to separate water, air, and calcium.

[0023] Further, the QCT value obtained by QCT scanning is compared with the vBMD value obtained by the conversion coefficient of the CaCT value into the vBMD value, to verify the feasibility of the conversion coefficient.

[0024] Further, the phantom for the QCT scanning is calibrated once every three days.

[0025] According to another aspect of the present application, a PCCT-based vBMD detection system is provided, including:

[0026] a PCCT scanning module for acquiring a spectral image by PCCT scanning and reconstructing the spectral image to obtain a spectral image in SPP format;

[0027] a CaCT value obtaining module for generating a calcium map by inputting the spectral image in SPP format into a post-processing workstation to obtain a CaCT value;

[0028] a vBMD value obtaining module for obtaining a vBMD value from the CaCT value according to a conversion coefficient of converting the CaCT value into the vBMD value;

[0029] The conversion coefficient of converting the CaCT value into the vBMD value is established as follows:

[0030] a real hydroxyapatite concentration of the phantom is taken as the vBMD value;

[0031] an ROI is set in the phantom, the ROI is scanned by PCCT, and a spectral image in SPP format is obtained by reconstruction;

[0032] the spectral image in SPP format is input into the post-processing workstation to obtain a calcium map, and an average CaCT value of the ROI is obtained;

[0033] a conversion coefficient of converting the CaCT value into the vBMD value is obtained according to the vBMD value and the average CaCT value.

[0034] Compared with the prior art, the present application has the following beneficial effects:

[0035] 1. The present application takes a real hydroxyapatite concentration of the phantom as the vBMD value, sets an ROI in the phantom, scans the ROI by PCCT, and obtains a SPP image by reconstruction, obtains a calcium map from the SPP image, obtains an average CaCT value of the ROI, and obtains a conversion coefficient of converting the CaCT value into the vBMD value according to the vBMD value and the average CaCT value. The error of the area BMD value obtained from the two-dimensional image is avoided, and the interference of overlapping artifacts such as spinal degeneration, spinal scoliosis and vascular sclerosis is avoided.

[0036] 2. The present application establishes a conversion coefficient of converting the CaCT value into the vBMD value, obtains a spectral image by PCCT scanning, reconstructs the spectral image to generate a SPP format image, generates a calcium map by a post-processing workstation to obtain a CaCT value, and obtains a vBMD value of a human body by using the conversion coefficient of converting the CaCT value into the vBMD value. The present application can be performed without using a calibrated phantom and a relatively expensive QCT post-processing workstation, saves labor, and improves cost-effectiveness. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1This is a schematic diagram of the vBMD detection method based on PCCT proposed in this invention;

[0038] Figure 2 This is a schematic diagram illustrating the conversion coefficient from CaCT value to vBMD value in the vBMD detection method based on PCCT proposed in this invention. Detailed Implementation

[0039] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0040] The following English abbreviations are involved:

[0041] Photon Counting Computed Tomography (PCCT)

[0042] Volumetric bone mineral density (vBMD)

[0043] Region of Interest (ROI)

[0044] Volume of Interest (VOI)

[0045] Spectral Processing Package (SPP)

[0046] Quantitative Computed Tomography, QCT

[0047] Hounsfield unit: HU

[0048] Calcium CT attenuation (CaCT)

[0049] Example 1

[0050] This embodiment provides a vBMD detection method based on PCCT, such as... Figure 1 As shown, it includes the following steps:

[0051] S1. Acquire the original image through PCCT scanning and reconstruct the original image to obtain a spectral image in SPP format.

[0052] The patient was placed in supine position for PCCT examination, with arms straight up over the head, and the chest-abdomen or (ultra-high resolution) lumbar spine scan mode was selected for scanning. The scan range of the ultra-high resolution lumbar spine scan was the 11th thoracic vertebra to the 1st sacral vertebra, and the scan range of the chest-abdominal scan was 2 cm above the diaphragm to the bottom of the pelvis, both of which used spiral scanning mode.

[0053] The specific scan parameters of the chest-abdominal scan were as follows: tube voltage, 120 kV; CARE keV image quality grading, 145; CareDose 4D, optimized for non-contrast enhancement; collimation, 144x0.4 mm; pitch, 0.8; rotation time, 0.25 s.

[0054] The specific scan parameters of the ultra-high resolution lumbar spine scan were as follows: tube voltage, 120 kV; CARE keV image quality grading, 285; CareDose 4D, optimized for bone / calcium; collimation, 120x0.2 mm; pitch, 0.8; rotation time, 0.50 s.

[0055] The specific reconstruction parameters of the SPP image were as follows: slice thickness / pitch was 1.0 / 0.7 mm, quantitative kernel was Qr40, quantum iterative reconstruction level was 3, and matrix size was selected as 512x512 pix 2 , the field of view of the chest-abdominal scan and the lumbar spine scan was set to 413x413 mm 2 and 185x185 mm 2 , respectively. A threshold three-dimensional image was reconstructed and generated, which was used to evaluate the QCT-derived vBMD (the threshold three-dimensional image was equivalent to the image obtained by a standard energy-integrating detector CT scan at the same X-ray tube voltage, and was reconstructed from a data stream containing all X-ray quanta with energy higher than the minimum threshold energy).

[0056] S2, input the spectral image in SPP format into the Syngovia VB60 workstation to generate a calcium map to obtain the CaCT value.

[0057] On the Syngovia VB60 workstation, the "calcium quantification" module in the "dual-energy" module was used to generate a calcium map using the SPP format image. The calcium map was generated based on the decomposition of three substances, including tissue, fat and calcium. PCCT can set different energy thresholds, so that photons can be divided into two or more energy bins according to their energy size for comprehensive energy analysis. In the low energy bin, the Hounsfield unit (HU) value of tissue is 55, the HU value of fat is -110, and the relative contrast material value is 1.55; in the high energy bin, the HU value of tissue remains 55, the HU value of fat also remains -96, and the relative contrast material value is 1.67.

[0058] In the target vertebral body, a volume of interest (VOI) generated by a QCT post-processing workstation (QCT Pro V6.1, Mindways Software Inc.) was imitated, and the VOI was drawn manually in the Syngovia VB60 workstation to make its size and position as consistent as possible with the QCT Pro-derived VOI. The specific steps of drawing the VOI are as follows: first, a 9mm straight line parallel to the longitudinal axis of the vertebral body is drawn in the sagittal plane, and as large as possible ROIs are drawn on the cross sections at both ends of the straight line, while avoiding the surrounding cortical bone and the posterior vertebral venous plexus, then a cylindrical VOI is created with 9mm high and the two ROIs as the upper and lower bases, and the CT value of the VOI is automatically generated by the workstation, which is the CaCT value of the vertebral body.

[0059] S3, the conversion coefficient of CaCT value to vBMD value, vBMD value is obtained by CaCT value.

[0060] Wherein, the conversion coefficient of CaCT value to vBMD value is established as shown in Figure 2 The steps include the following steps:

[0061] On the PCCT system (NAEOTOM Alpha, VA50, Siemens Healthcare), a standardized European Spine Phantom (ESP, QRM GmbH) containing three artificial vertebrae with true hydroxyapatite concentrations of 49, 102 and 198 mg / mL representing vBMD was scanned three times repeatedly using six different scanning protocols at a tube voltage of 120 kV. The ESP was scanned in the ultra-high resolution lumbar spine scan mode with the following specific scan parameter settings: voltage: 120 kV; CARE keV image quality level: 285; CareDose 4D: optimized for bone / calcium; collimation, 120x0.2mm; pitch, 0.8mm; rotation time, 0.50s.

[0062] After the PCCT scanner collects binary raw data, the system generates spectral post-processing (SPP) format images for vBMD measurement according to the following parameters, and the reconstruction parameters are set as follows: slice thickness: 1.0mm; slice pitch: 0.8mm; quantitative kernel: Qr40; quantum iterative reconstruction level: 3; matrix size, 512x512pix 2 ; scan field size: 336x336mm 2 ; collimator width: 144x0.4mm. All images are transmitted to the post-processing workstation (Syngovia VB60, Siemens Healthcare) to achieve material separation according to spectral analysis, so as to calculate the calcium concentration.

[0063] The above scanning and reconstruction were repeated twice to verify the repeatability, and the average of the three measurements was taken as the result to reduce the measurement error.

[0064] On the Syngovia VB60 workstation, the calcium map was generated using the calcium quantification module in the "dual energy" module, which was generated based on the decomposition of three substances, including water, air and calcium. The PCCT can set different energy thresholds, so that the photons are divided into two or more energy boxes according to the size of the energy, so as to carry out comprehensive energy analysis. In the low energy box, the HU value of water is 0, the HU value of air is -1000, and the relative contrast material (Rel.CM) value is 1.55; in the high energy box, the HU value of water remains 0, the HU value of air also remains -1000, and the relative contrast material value is 1.67.

[0065] The measurement of bone density was performed by a radiologist with 12 years of musculoskeletal radiology experience, three ROIs were drawn at the central, upper third and lower third levels of each vertebra, as large as possible, avoiding contact with the cortical bone. After the completion of ROI drawing, the ROI was scanned by PCCT and reconstructed to obtain a spectral image in SPP format. The spectral image in SPP format was input into the post-processing workstation to obtain a calcium map, and the CaCT value of each ROI was obtained. The average of the CaCT values of the three ROIs was taken as the final CaCT value of the artificial vertebra, which was included in the calculation of the conversion coefficient.

[0066] Hydroxyapatite calcium Ca 10 (PO4)6(OH)2 is the main mineral component in the ESP phantom and the human body, and calcium accounts for 39.9% of its total weight. The CaCT value can be measured by the calcium map. Therefore, based on the true concentration of the phantom, the conversion coefficient and the fitting curve for converting the CaCT value to the vBMD value can be calculated for obtaining the vBMD value in the human body. The conversion coefficient for converting the CaCT value to the vBMD value is:

[0067] vBMD = CaCT x 0.82

[0068] In the formula, vBMD is the vBMD value, and CaCT is the CaCT value.

[0069] Thirty adult patients who received lumbar or thoracolumbar scans on the PCCT were continuously included. The QCT values of the 30 patients were taken as the reference standard. The QCT needs to be calibrated regularly to maintain the accuracy of the measurement value. The QCT phantom in this embodiment was calibrated once every 3 days. The QCT value was compared with the vBMD value obtained by the conversion formula for converting the CaCT value to the vBMD value, and the correlation and consistency between the two were compared. The results showed that the two had good correlation (r s= 0.797, p < 0.001) and very high agreement (bias, -2.4; 95% LOA, -26.7 to 21.8 mg / cm 3 ), indicating that the conversion factor of CaCT value to vBMD value is applicable to human body.

[0070] Embodiment 2

[0071] The embodiment provides a vBMD detection system based on PCCT, comprising:

[0072] a PCCT scanning module, configured to collect original images by PCCT scanning and reconstruct the original images to obtain spectral images in SPP format;

[0073] a CaCT value obtaining module, configured to generate a calcium map by inputting the spectral images in SPP format into a post-processing workstation to obtain a CaCT value;

[0074] a vBMD value obtaining module, configured to obtain a vBMD value from the CaCT value according to a conversion factor of the CaCT value to the vBMD value;

[0075] The conversion factor of the CaCT value to the vBMD value is established by the following steps:

[0076] the real hydroxyapatite concentration of the phantom is taken as the vBMD value;

[0077] an ROI is set in the phantom, the ROI is scanned by PCCT, and spectral images in SPP format are obtained by reconstruction;

[0078] the spectral images in SPP format are input into the post-processing workstation to obtain a calcium map, and the average CaCT value of the ROI is obtained;

[0079] the conversion factor of the CaCT value to the vBMD value is obtained according to the vBMD value and the average CaCT value.

[0080] The rest is the same as in Embodiment 1.

[0081] The above detailed the preferred embodiments of the present application. It should be understood that those of ordinary skill in the art can make many modifications and variations without creative work based on the concept of the present application. Therefore, any technical solution obtained by logical analysis, reasoning or limited experiment based on the prior art according to the concept of the present application shall be within the protection scope determined by the claims.

Claims

1. A method for PCCT-based vBMD detection, characterized in that, The method comprises the following steps: Collecting original images by PCCT scanning and reconstructing the original images to obtain spectral images in SPP format; Inputting the spectral images in SPP format into a post-processing workstation to generate a calcium map and obtain a CaCT value; Obtaining a vBMD value from the CaCT value according to a conversion coefficient of the CaCT value into the vBMD value, wherein the conversion coefficient of the CaCT value into the vBMD value is: wherein is the vBMD value, is the CaCT value; The conversion coefficient of the CaCT value into the vBMD value is established by the following steps: Taking a real hydroxyapatite concentration of a phantom as the vBMD value; Setting an ROI in the phantom, scanning the ROI by PCCT, and reconstructing to obtain spectral images in SPP format; Inputting the spectral images in SPP format into the post-processing workstation to obtain a mean CaCT value of the ROI; Obtaining the conversion coefficient of the CaCT value into the vBMD value according to the vBMD value and the mean CaCT value.

2. The PCCT-based vBMD detection method according to claim 1, characterized in that, The reconstruction parameters include multiple parameters in layer thickness, layer spacing, quantitative kernel, quantum iterative reconstruction level, matrix size and scanning field of view.

3. The PCCT-based vBMD detection method of claim 1, wherein, The phantom is a standardized European spine phantom, which comprises three artificial vertebrae.

4. The PCCT-based vBMD detection method according to claim 3, characterized in that, An ROI is drawn at the central, upper third and lower third levels of each of the artificial vertebrae.

5. The PCCT-based vBMD detection method of claim 1, wherein, The calcium map is generated based on decomposition of three substances, including water, air and calcium.

6. The PCCT-based vBMD detection method of claim 1, wherein, The spectral images in SPP format are separated into water, air and calcium based on spectral analysis on the post-processing workstation.

7. The PCCT-based vBMD detection method of claim 1, wherein, The feasibility of the conversion coefficient is verified by comparing a QCT value obtained by QCT scanning with a vBMD value obtained by the conversion coefficient of the CaCT value into the vBMD value.

8. The PCCT-based vBMD detection method according to claim 7, characterized in that, The phantom for the QCT scanning is calibrated once every three days.

9. A PCCT-based vBMD detection system, characterized by, The method comprises: A PCCT scanning module for collecting spectral images by PCCT scanning and reconstructing the spectral images to obtain spectral images in SPP format; A CaCT value obtaining module for inputting the spectral images in SPP format into a post-processing workstation to generate a calcium map and obtain a CaCT value; A vBMD value obtaining module for obtaining a vBMD value from the CaCT value according to a conversion coefficient of the CaCT value into the vBMD value, wherein the conversion coefficient of the CaCT value into the vBMD value is: wherein is the vBMD value, is the CaCT value; The conversion coefficient of the CaCT value into the vBMD value is established by the following steps: Taking a real hydroxyapatite concentration of a phantom as the vBMD value; Setting an ROI in the phantom, scanning the ROI by PCCT, and reconstructing to obtain spectral images in SPP format; Inputting the spectral images in SPP format into the post-processing workstation to obtain a mean CaCT value of the ROI; Obtaining the conversion coefficient of the CaCT value into the vBMD value according to the vBMD value and the mean CaCT value.

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