CN113796878B - Application of energy spectrum technology based on virtual anatomy in drowning case - Google Patents
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- 206010013647 Drowning Diseases 0.000 title claims abstract description 71
- 238000001228 spectrum Methods 0.000 title claims abstract description 32
- 238000005516 engineering process Methods 0.000 title claims abstract description 28
- 210000004072 lung Anatomy 0.000 claims abstract description 63
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 40
- 238000000034 method Methods 0.000 claims abstract description 12
- 238000001514 detection method Methods 0.000 claims abstract description 11
- 229910052740 iodine Inorganic materials 0.000 claims abstract description 6
- 239000011630 iodine Substances 0.000 claims abstract description 6
- 238000007405 data analysis Methods 0.000 claims abstract description 4
- ZCYVEMRRCGMTRW-UHFFFAOYSA-N 7553-56-2 Chemical compound [I] ZCYVEMRRCGMTRW-UHFFFAOYSA-N 0.000 claims abstract description 3
- 239000000126 substance Substances 0.000 claims description 29
- 238000002591 computed tomography Methods 0.000 claims description 6
- 229910052791 calcium Inorganic materials 0.000 claims description 4
- 239000011575 calcium Substances 0.000 claims description 4
- 230000003595 spectral effect Effects 0.000 claims description 3
- OYPRJOBELJOOCE-UHFFFAOYSA-N Calcium Chemical compound [Ca] OYPRJOBELJOOCE-UHFFFAOYSA-N 0.000 claims description 2
- 238000004611 spectroscopical analysis Methods 0.000 claims 2
- 210000001519 tissue Anatomy 0.000 abstract description 34
- 210000000988 bone and bone Anatomy 0.000 abstract description 13
- 238000000926 separation method Methods 0.000 abstract description 5
- 239000000463 material Substances 0.000 abstract description 4
- 238000002224 dissection Methods 0.000 abstract description 2
- 241000283973 Oryctolagus cuniculus Species 0.000 description 19
- 238000002474 experimental method Methods 0.000 description 17
- 241001465754 Metazoa Species 0.000 description 12
- 239000007788 liquid Substances 0.000 description 12
- 238000004458 analytical method Methods 0.000 description 9
- 238000003384 imaging method Methods 0.000 description 8
- 239000011159 matrix material Substances 0.000 description 7
- 238000012545 processing Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 239000012530 fluid Substances 0.000 description 3
- 238000004451 qualitative analysis Methods 0.000 description 3
- 208000019693 Lung disease Diseases 0.000 description 2
- 206010035664 Pneumonia Diseases 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 238000010171 animal model Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 230000001575 pathological effect Effects 0.000 description 2
- 238000004445 quantitative analysis Methods 0.000 description 2
- 238000010183 spectrum analysis Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 206010014561 Emphysema Diseases 0.000 description 1
- 238000011887 Necropsy Methods 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 210000003484 anatomy Anatomy 0.000 description 1
- 238000011888 autopsy Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000005315 distribution function Methods 0.000 description 1
- 230000037406 food intake Effects 0.000 description 1
- 239000005337 ground glass Substances 0.000 description 1
- 238000013427 histology analysis Methods 0.000 description 1
- 230000003902 lesion Effects 0.000 description 1
- 208000020816 lung neoplasm Diseases 0.000 description 1
- 208000037841 lung tumor Diseases 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000011527 multiparameter analysis Methods 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 101150058164 phoE gene Proteins 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000013076 target substance Substances 0.000 description 1
- 238000003325 tomography Methods 0.000 description 1
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- A—HUMAN NECESSITIES
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Abstract
The invention relates to application of a spectrum technology based on virtual anatomy in a drowning case, which is used for carrying out spectrum CT detection on cadavers and obtaining characteristic information of drowning. The method comprises the steps of carrying out data analysis and image reconstruction by taking water and iodine as base material pairs, and taking characteristic information describing drowning in lung tissues as characteristic information of drowning, wherein the characteristic information comprises effective atomic numbers or average effective atomic numbers of lung areas, presentation of the drowning in the lung tissues in effective atomic number images, presentation of the drowning in the lung tissues in reconstructed single-energy images, presentation of the drowning in the lung tissues in water and bone images, presentation of the drowning in the lung tissues in water density images after separation of the base material pairs and the like. The invention is used for drowning identification, does not need invasive dissection, has high detection speed, good safety, strong specificity and high accuracy, and is easy to accept by families.
Description
Technical Field
The invention relates to application of a spectrum technology based on virtual anatomy in a drowning case, and discloses a novel method for detecting and identifying a drowned cadaver simply, conveniently, quickly and accurately.
Background
Because the drowned cadaver usually has no specific expression, the actual case needs forensic personnel to synthesize cadaver signs, adopts a traditional anatomic method, makes pathological sections after extracting main organs, observes under a microscope, usually needs about 40 days to send out forensic identification reports, and has the defects of complex operation, result deviation caused by different levels of inspection personnel, long waiting time of a case handling unit, high cost, and in addition, the condition that family members are difficult to accept autopsy often occurs in reality.
Virtual dissection is a non-invasive novel dissection technology provided for estimating death reasons and death modes by means of scanning, image processing and the like of cadavers by using imaging technologies (CT, MRI and the like). The technology has the greatest advantages of being non-invasive, simple, convenient and quick, and can analyze and store the image data of the whole corpse. In recent two years, forensics have applied CT technology to scan the lung in drowning cases, and by observing the imaging performance, such as the density of the lung parenchymal tissue, the CT value of the lung, and comparing the lung volume with the control group through 3D reconstruction, these technologies provide a basis for the death factor identification to a certain extent, but other diseases such as lung inflammation, emphysema, lung tumor, etc. can also show the density, CT value and the size change of the lung parenchymal tissue, so these technologies have the problems that the specificity is not strong enough and the substances in the lung tissue cannot be identified, so these technologies cannot be widely popularized. Further research is therefore needed to find a method that can rapidly, accurately, safely and humanizedly identify or assist in the identification of drowning, an important direction and difficulty in forensic fields involving drowning.
On the other hand, energy spectrum technology has been developed and put into practical use, and energy spectrum CT utilizes the characteristic that substances generate different absorption under different X-ray energies (photon energies), so that more image information than conventional CT can be provided, not only can the density of the substances and the distribution images thereof be obtained, but also single energy images of different kV levels can be obtained, and the effective atomic number of lesions or tissues can be calculated according to the obtained energy spectrum curves.
Disclosure of Invention
The invention aims to apply energy spectrum technology, in particular energy spectrum CT technology, to drowning identification to form a rapid, accurate, safe and humanized drowning identification or auxiliary identification method.
The technical scheme of the invention is as follows: the application of the energy spectrum technology based on virtual anatomy in the drowning case is to perform energy spectrum CT detection on cadavers and acquire the characteristic information of the drowning.
Characteristic information describing drowning in lung tissue may be taken as characteristic information of said drowning.
Preferably, the characteristic information of drowning includes the effective atomic number (pixel value or pixel distribution function) or average effective atomic number of the lung region.
Preferably, the characteristic information of drowning includes a presentation of drowning fluid in lung tissue in an effective atomic number image.
Preferably, the characteristic information of drowning includes a presentation of drowning fluid in lung tissue in reconstructing a single energy image.
Preferably, the characteristic information of drowning comprises the presentation of drowning fluid in lung tissue in water, bone map (water-bone (water) image).
Preferably, the characteristic information of drowning comprises a presentation of drowning in lung tissue in a water density image of a pair of basis substances after separation, the basis substances of the pair of basis substances comprising water.
The presentation of drowning in the lung tissue in the image may be a visual presentation of a visual image, a data presentation of an electronic image (electronic image data) or a parameter presentation obtained based on the electronic image, or any other presentation capable of showing the presence or absence of drowning in the lung tissue.
The characteristic information of any one, any plurality or all of the drowning can be analyzed individually or comprehensively to judge whether the drowning is the drowning.
If necessary, the judgment can be performed by combining other information.
According to the actual situation, any one, any multiple or all characteristic information of drowning disclosed by the invention can be used as a sufficient basis, a main basis or an auxiliary basis for judging the drowning.
When any one, any plurality or all of the characteristic information of the drowning according to the invention is sufficient to make a deterministic conclusion, the drowning judgment can be performed only according to the corresponding one, any plurality or all of the characteristic information of the drowning according to the invention, and further, other information can be used as a evidence or auxiliary evidence of the judgment conclusion.
Preferably, the water and iodine based substance pairs or the water and calcium based substance pairs.
The spectral CT detection should generally include high-level X-ray scanning and low-level X-ray scanning.
The photon energy of the high-level X-rays is preferably 140keV, and the photon energy of the low-level X-rays is preferably 70keV or 80keV.
The data/energy spectrum analysis platform (software) of energy spectrum CT scanning can be adopted for scanning data analysis and image reconstruction operation.
The analysis platform may be interacted with through a computer communication network such as the internet.
On the basis of the post-mortem lung specific imaging change, the invention obtains a lung tissue CT value, an effective atomic number image, the change of a water-bone base substance to a water content value and an energy spectrum curve of drowning and the like through an energy spectrum technology, can effectively reflect the characteristics of the lung of a drowned cadaver, and provides a new basis for the diagnosis of drowning.
The invention applies the energy spectrum CT technology to the drowning identification, can obtain the drowning characteristic information with good specificity through the lung energy spectrum CT detection of cadavers, directly carries out the drowning identification by utilizing the drowning characteristic information or cooperatively carries out the drowning identification with other information, does not need to carry out invasive anatomy, has high detection speed, good safety, strong specificity and high accuracy, and is easy to accept for families.
Drawings
FIG. 1 is a flow chart of an animal (rabbit) experiment of the present invention;
FIG. 2 is a graph of effective atomic coefficients of a control group of an animal (rabbit) experiment of the present invention;
FIG. 3 is a graph of effective atomic coefficients of an experimental group of an animal (rabbit) experiment of the present invention;
FIG. 4 is a histogram of effective atomic coefficients of a control group of an animal (rabbit) experiment of the present invention;
FIG. 5 is a histogram of effective atomic coefficients of an experimental group of an animal (rabbit) experiment of the present invention;
FIG. 6 is a water and bone map of a control group of an animal (rabbit) experiment of the present invention;
FIG. 7 is a graph of experimental water and bone for an animal (rabbit) experiment of the present invention;
FIG. 8 is a graph of water content values of experimental group water and bone map for an animal (rabbit) experiment of the present invention.
Detailed Description
The invention develops qualitative and quantitative description of drowning liquid in the lung tissue of a drowned cadaver by utilizing the energy spectrum technology, the technology not only can solve the defects of complex operation, unacceptable family members and the like of the traditional necropsy, but also can make up the technical problem that CT detection cannot accurately distinguish between the drowned lung and lung diseases, and the flow of an animal experiment (pre-experiment) related to the invention is shown in figure 1, and the experimental animal is a rabbit.
Based on the application of the energy spectrum (CT) technology in clinic at present, the experiment is carried out by establishing a rabbit drowning model, changing the lung image of a drowned animal, analyzing CT values, and carrying out qualitative analysis on drowning liquid by utilizing the energy spectrum technology, so as to provide support for a drowning diagnosis mode with simple operation, high efficiency, high accuracy and strong specificity.
CT tomography is carried out within 1h after death of the experimental animal according to the requirements of the French medical virtual anatomic operation procedure (SF/Z JD 0101003-2015). All CT scan datasets are stored in DICOM format. Performing tomogram morphology reading on CAMPO IMAGING software systems; and the single energy image of the lungs and drowning of the experimental rabbits, the effective atomic number calculation, the matrix substance pair analysis and the spectral curve drawing are displayed by using the peak analysis-energy spectrum display function on the software.
SPSS 26.0 statistical software is adopted for data processing and analysis, data are expressed in the form of x+/-s, variance analysis is adopted for the variance analysis method of multiple groups of data, and multiple comparison analysis is carried out by adopting a minimum significant difference method (LEASTSIGNIFICANT DIFFERENCE, LSD) in a pairwise comparison mode. Check level α=0.05.
Satisfactory results were obtained by animal pre-experiments (see fig. 2-8), demonstrating that the invention is viable.
The lung CT images of the drowned group all show the change of ground glass, the diffuse uniformity of the lung parenchyma density is increased, the lung field texture is thickened and increased, the lung interval is thickened, and the lung CT images of the control group are not obviously abnormal.
The effective atomic coefficient related data of the lungs of the control group are max=6, min=0, mean=1.79, sd=2.24, while the effective atomic coefficient related data of the lungs of the experimental group of drowned rabbits are max=8, min=6, mean=6.91, sd=0.38, MAX, MIN, MEAN, SD respectively represent the maximum value, the minimum value, the average value and the standard deviation of the effective atomic numbers in the target. It is clear whether drowning exists in the lung, and the two data are significantly different and statistically significant (see fig. 2-3).
The experimental data are compared to show that the lung tissue CT values of the drowned rabbits are obviously different from those of the control group, the lung water-bone map water content value of the drowned group is increased compared with that of the control group, and the difference has statistical significance. (P < 0.05) (Table 1).
TABLE 1 lung CT values for drowned and control groups
Note that: p < 0.05 compared with the drowned group
For more direct observation, the effective atomic coefficient is made into a histogram, the effective atomic coefficient of water is taken as a reference, so that the lung tissue liquid of the control group is obviously observed to be far away from the water value, and the lung tissue of the experimental group contains drowned liquid, and the obtained effective atomic coefficient mostly overlaps with the effective atomic coefficient of water, so that the experimental result of the invention is more verified to be accurate and reliable (see figures 4-5).
In the effective atomic number histogram of the drowned lung, the baseline of water is mostly coincident with the lung tissue, and the data indicate that the water content in the drowned lung tissue is about 87.8%; in the effective atomic number histogram of the lungs of the control group, the baseline of water is not coincident with the lung tissue, and the data indicate that the water content in the lung tissue of the control group is low.
The experimental result shows that the drowning liquid in the lung tissue has obvious difference between the intake of water and bone-based substances and the control group, the water content value of the separation of the water and bone substances in the experimental group is MAX=912 mg/cm 3、 MIN＝565mg/cm3、MEAN＝749.33mg/cm3, which is obviously higher than that in the control group, MAX=684 mg/cm 3、MIN＝131mg/cm3、MEAN＝370.98mg/cm3, wherein MAX, MIN, MEAN represents the maximum value, the minimum value and the average value of the water content of the separation of the water and bone substances respectively (see fig. 6-7).
Experiments show that drowning in lung tissue of the drowned group has a significant difference in uptake of water-bone matrix material from the control group, and the water content value of water-bone material separation of the drowned group is significantly higher than that of the control group (see fig. 8). The water content value of the lung water-bone map of the drowned group is increased compared with that of the control group, the difference is obvious, and the water content value of the drowned group has statistical significance (P is less than 0.05) (table 2).
TABLE 2 Water content values of Water-bone map for drowned and control groups
(n＝3,mg/cm3)
Note that: p < 0.05 compared with the drowned group
And (3) making HE sections from the lung tissues of the drowned rabbits, and determining that the lung tissues of the drowned rabbits accord with pathological signs of the lung tissues of the pre-living drowning.
By longitudinally comparing the spectrum graphs obtained by the experiments, the spectrum graphs of the liquid in the lungs of the drowned group and the spectrum graphs of the liquid in the lungs of the control group are opposite in running and do not cross, and the difference between the liquid in the lungs of the drowned group and the liquid in the lungs of the control group is indicated.
According to the prior art, the energy spectrum CT scanning and data processing mainly comprises the following steps:
The experimental group is a drowned rabbit, which is kept for scope days after drowning, the control group is a normal sacrificed rabbit, and is kept for scope days after the sacrifice.
The drowned rabbits are subjected to experiments after lung diseases such as pneumonia are eliminated by energy spectrum CT scanning before drowning.
The lungs of the rabbit carcasses of the experimental group and the control group were subjected to energy spectrum CT scan by using X-rays with energy levels of 80keV and 140 keV.
Water-iodine is used as the detection matrix substance pair for the drowning of lung tissue. Meanwhile, water-calcium is also adopted as a base material to carry out parallel analysis, so as to obtain a similar conclusion.
The energy analysis image mainly adopts a 40-140keV single energy level image, a mixed energy image, an effective atomic number image, a substance density image and a water-iodine diagram.
According to the prior art, a mathematical model is established, image histology analysis and other methods, sample data are collected through animal experiments, drowning liquid in lung tissues is enabled to be presented under the action of a single-energy X-ray source, collected numerical values are converted into a histogram based on identification requirements, the condition of the drowning liquid in the lung tissues on the ingestion of a matrix substance pair is intuitively analyzed, then substance density imaging, qualitative and quantitative analysis are carried out, and finally, the characteristic information of drowning is obtained by utilizing the change of different absorption values generated by substances under different X-ray energies.
Compared with the conventional CT image, the imaging technology provided by the invention has the brand new imaging technology of multiparameter, qualitative and quantitative analysis and has more valuable information. Experiments and theoretical analysis both reveal that different substances and components in a human body can be found by utilizing a single-energy image, an effective atomic number, a substance density imaging and an energy spectrum attenuation curve of an X-ray-single-energy imaging technology and combining an image histology technology, and the problem that the traditional CT only can obtain image data and can not be used for qualitatively and quantitatively determining a target in the human body is solved.
The theoretical basis or prior art on which the experimental and data analysis and processing are based is briefly described as follows:
Establishment of a matrix substance pair: the mass attenuation coefficient of any one substance in the human body can be obtained by linear combination of the mass attenuation coefficients of two substances, and is calculated by prjL＝fL(imgw+imgb)、 prjH＝fH(imgw+imgb), wherein:
prj L and prj H are projection data acquired using low kv and high kv respectively, typically 80kv for low kv and 140kv for high kv;
img w and img b are equivalent water-bone images of the scanned object;
f L and f H are the function of the equivalent water bone combination of the X-ray and the scanned object, and corresponding prj L and prj H values can be calculated in advance by using different img w and img b combinations, so that lookup tables of prj L and prj H and img w and img b, namely f L and f H, can be obtained.
In practical use prj L and prj H are projection values obtained by scanning an object, f L and f H are pre-calculated values, and img w and img b combination can be obtained by using prj L and prj H to look up a table in f L and f H.
The water-iodine can be used as a detection matrix substance pair of lung tissue drowning liquid or other matrix substance pairs such as water-calcium.
② Spectral analysis + image generation: wherein the single energy image formula is: wherein img (E) is a single energy image, E is a corresponding single energy value, and the general value range is 40-140; m w (E) and m b (E) are mass attenuation coefficients of water and bone at a single energy E.
The substance pair image formula is ：img1＝cw1×imgw+cb1×imgb、img1＝cw1×imgw+cb1×imgb,, wherein img 1 and img 2 are target substance pair images, the water bone substance pair images img w and img b can be obtained by linear combination, and the combination coefficient c w1、cb1、cw2、cb2 can be obtained by taking img 1、img2、imgw、imgb as a known value and then performing iterative calculation.
The effective atomic number image formula is: Wherein, k=4.4,
Wherein,Is the electron density of water,/>Z (w) is the equivalent atomic number of water, taking 7.6; c w,ph、cb,ph is the photoelectric effect coefficient of the water bone, c w,ρ、cb,ρ is the Compton scattering coefficient of the water bone, and the photoelectric effect coefficient is obtained by iterative calculation according to the following formula:
mw(E)＝cw,ph×mphoE(E)+cw,ρ×mcompt(E)
mb(E)＝cb,ph×mphoE(E)+cb,ρ×mcompt(E)
Wherein m phoE (E) and m compt (E) are mass attenuation coefficients corresponding to the photoelectric effect and Compton scattering.
The invention provides a brand-new forensic inspection and identification mode for application of virtual anatomic technology in forensic identification of drowned cases.
The preferred and optional technical means disclosed in the invention may be combined arbitrarily to form a plurality of different technical schemes, except for the specific description and the further limitation that one preferred or optional technical means is another technical means.
Claims (4)
1. The application method of the energy spectrum technology based on virtual anatomy in the drowning case is characterized in that energy spectrum CT detection is carried out on cadavers to obtain characteristic information of drowning, the characteristic information of the drowning comprises effective atomic numbers or average effective atomic numbers of lung areas, and the drowning identification is directly carried out or carried out in cooperation with other information by utilizing the characteristic information of the drowning.
2. The method of using the virtual anatomic-based spectroscopy according to claim 1 in drowning cases, wherein the pair of water and iodine-based substances or the pair of water and calcium-based substances are used.
3. The method of applying virtual anatomic-based spectroscopy in drowning cases according to claim 1, characterized in that the spectral CT detection comprises a high-level X-ray scan with photon energy of 140keV and a low-level X-ray scan with photon energy of 70keV or 80keV.
4. The method for applying the energy spectrum technology based on the virtual anatomy to the drowning case according to claim 1, wherein the data of the energy spectrum CT scan is adopted for the scan data analysis and the image reconstruction operation.
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