CN114983477A - Computing device, liver elasticity measuring device, remote workstation and medium for evaluating liver lesion status - Google Patents
Computing device, liver elasticity measuring device, remote workstation and medium for evaluating liver lesion status Download PDFInfo
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Abstract
The present application relates to a computing device, a liver elasticity measurement device, a remote workstation and a medium for assessing a liver lesion status. The computing device includes a first processor configured to: determining a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement and a liver inflammation parameter comprising a liver inflammation index based on ultrasound data acquired by a liver elasticity measurement device for a subject; and displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display such that a user can view the liver fibrosis parameter, the liver steatosis parameter together with the liver inflammation parameter. In this way, the user can diagnose the changeful and complicated pathological condition of the liver more sensitively and accurately by contrasting and referring to the three parameters.
Description
Technical Field
The present application relates to a medical diagnostic apparatus, a medical detection apparatus and a medium, and more particularly, to a computing apparatus, a liver elasticity measuring apparatus, a remote workstation and a medium for evaluating a liver lesion status.
Background
Liver disease has become an important cause of health in humans worldwide. The progression of various liver diseases is accompanied by liver fibrosis, which is also accompanied by changes in the elasticity of the liver. Recent studies have been conducted on transient elastography techniques for diagnosis of liver fibrosis. Liver hardness values (Liver firm testing Measurement, abbreviated LSM in english) are usually measured by transient elastography and the degree of fibrosis of the Liver is diagnosed based on these measurements.
However, for various liver diseases, if only the hardness value of the liver is known, the physician cannot timely and accurately diagnose the current pathological condition and the potential development possibility of the liver. Sometimes, excessive administration is not needed even for higher fibrosis degree, and the disease course of the patient is stable and even stagnated; on the contrary, some livers with low fibrosis degree will develop rapidly if not paid attention and not reviewed in time. Physicians now rely on clinical pathology to perform liver biopsies to diagnose the condition of the liver pathology. However, liver biopsy has many limiting factors, its invasive disadvantages, and risk of complications make it impossible to continuously perform two-track liver verification, and moreover, liver biopsy is also affected by sampling errors. Therefore, there is still room for improvement in noninvasive liver lesion assessment.
Disclosure of Invention
The present application is proposed to solve the above technical problems.
To the above technical problem that exists among the prior art, this application provides an aassessment liver pathological change situation's computing device, liver elasticity measuring device, remote workstation and medium, it can be based on ultrasonic data with noninvasive mode rapidly and accurately confirm liver fibrosis parameter liver steatosis parameter and liver inflammation parameter to make the user can look at three kinds of parameters, namely liver fibrosis parameter liver steatosis parameter and liver inflammation parameter, the changeable complicated pathological change situation of liver can be diagnosed more sensitively and accurately to these three parameters of user's contrast reference.
According to a first aspect of the present application, a computing device for assessing a liver lesion status is provided. The computing device includes a first processor configured to: determining a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement and a liver inflammation parameter comprising a liver inflammation index based on ultrasound data acquired by a liver elasticity measurement device for a subject; and displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display such that a user can view the liver fibrosis parameter, the liver steatosis parameter, and/or the liver inflammation parameter.
According to a second aspect of the present application, there is provided a liver elasticity measurement device. This liver elasticity measuring device includes: an ultrasonic transducer configured to transmit and receive ultrasonic waves to a subject with a shear wave generated by vibration excitation; a transmission/reception control circuit configured to output a transmission and reception sequence to the ultrasonic transducer to control transmission and reception thereof of ultrasonic waves; a computing device according to various embodiments of the present application is adapted to be configured in a liver elasticity measurement device.
According to a third aspect of the present application, there is provided a remote workstation communicably connected to a computing device and comprising: an interface configured to: receiving a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement, and a liver inflammation parameter comprising a liver inflammation index determined by the computing device; receiving a biological or biochemical parameter of the subject; and a second processor configured to: calculating a composite score of liver lesions of the subject based on the received liver fibrosis parameter, liver steatosis parameter and liver inflammation parameter of the subject, with consideration of the biological or biochemical parameters, the composite score of liver lesions being a continuous numerical value or a discrete scale; displaying a composite score of liver lesions of the subject.
According to a fourth aspect of the present application, there is provided a non-transitory computer storage medium having stored thereon computer instructions which, when executed by a third processor, implement a method of assessing a liver lesion status. The evaluation method comprises the following steps: determining a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement and a liver inflammation parameter comprising a liver inflammation index based on ultrasound data acquired by a liver elasticity measurement device for a subject; and displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display such that a user can view the liver fibrosis parameter, the liver steatosis parameter and/or the liver inflammation parameter.
In some embodiments, the evaluation method further comprises: calculating a liver fibrosis score according to the liver fibrosis parameters; calculating a liver steatosis score based on the liver steatosis parameter; calculating a liver inflammation score according to the liver inflammation parameters; displaying one or more of the liver fibrosis score, the liver steatosis score, and the liver inflammation score on a display.
In some embodiments, the liver fibrosis score, the liver steatosis score, and the liver inflammation score are continuous numbers, or discrete levels.
In some embodiments, the evaluation method further comprises: receiving operation of selecting and viewing parameters or scores of a user; displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display in case the user selects a viewing parameter, and displaying one or more of the liver fibrosis score, the liver steatosis score and the liver inflammation score on a display in case the user selects a viewing score.
In some embodiments, the evaluation method further comprises: obtaining a biological parameter of the subject, the biological parameter comprising at least one of a weight, a height, a waist circumference, a hip circumference, a chest circumference, an age, a gender, a BMI, a subcutaneous tissue thickness, and a subcutaneous fat thickness of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biological parameter.
In some embodiments, the evaluation method further comprises: obtaining biochemical parameters of the subject, the biochemical parameters including a level of at least one of AST, ALT, transaminase, GGT, PAL, iron serum, ferritin, transferrin saturation, lipoxygenase oxidizing hormone, cytokinin, cholesterol HDL, blood glucose, insulinemia, bilirubin, a2 macroglobulin, hemophilin, apolipoprotein a1, CK-18, triglycerides, high density lipoprotein, low density lipoprotein, very low density lipoprotein, adiponectin, urea, polymorphic genes, CRP, leptin, and metabolic biochemical parameters of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter, and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biochemical parameter.
In some embodiments, the liver fibrosis parameter further comprises a liver viscosity parameter.
With the computing device for evaluating liver pathological condition, the liver elasticity measuring device, the remote workstation and the medium according to the embodiments of the present application, it is possible to rapidly and accurately determine the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter in a non-invasive manner based on the ultrasound data (even the same batch of ultrasound data), and enable the user to check the three parameters, namely the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter, at the same time, by referring to these three parameters in contrast, the user can diagnose the changeable complex pathological condition of the liver more sensitively and accurately.
Drawings
In the drawings, which are not necessarily drawn to scale, like reference numerals may describe similar components in different views. Like reference numerals having letter suffixes or different letter suffixes may represent different instances of similar components. The drawings illustrate various embodiments generally by way of example and not by way of limitation, and together with the description and claims serve to explain the disclosed embodiments. Such embodiments are illustrative, and are not intended to be exhaustive or exclusive embodiments of the present apparatus or method.
Fig. 1 shows a schematic diagram of a computing device for assessing a liver lesion condition according to an embodiment of the present application, built into a liver elasticity measurement device according to an embodiment of the present application;
fig. 2 shows an interface diagram of a first example of displaying a liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display according to an embodiment of the present application;
fig. 3 shows an interface diagram showing a second example of a liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display according to an embodiment of the present application;
FIG. 4 illustrates an operational schematic of a remote workstation in accordance with an embodiment of the present application;
FIG. 5 shows a block diagram of a remote workstation according to an embodiment of the present application; and
fig. 6 shows a flow chart of a method of assessing a liver lesion status according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the present application is described in detail below with reference to the accompanying drawings and the detailed description. The embodiments of the present application will be described in further detail with reference to the drawings and specific embodiments, but the present application is not limited thereto.
As used in this application, the terms "first," "second," and the like do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element preceding the word covers the element listed after the word, and does not exclude the possibility that other elements are also covered. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
Fig. 1 shows a schematic diagram of a computing device 100a for assessing a liver lesion status according to an embodiment of the present application. Note that the computing device 100a may be embedded in the liver elasticity measurement device 100 according to the embodiment of the present application, as illustrated in fig. 1, but may also be disposed in other locations, such as, but not limited to, a remote workstation, a cloud server, and the like. The computing device 100a may be disposed in the liver elasticity measurement device 100, or may be communicably connected to the liver elasticity measurement device 100, as long as the ultrasound data acquired by the liver elasticity measurement device 100 for the subject can be acquired.
The following description will be given taking a computing device 100a incorporated in the liver elasticity measuring device 100 as an example.
As shown in fig. 1, the computing device 100a may include a first processor 103, the first processor 103 configured to: based on ultrasound data acquired by the liver elasticity measurement device 100 for a subject, a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement, and a liver inflammation parameter comprising a liver inflammation index are determined. The liver elasticity measurement may employ various parameters that characterize liver elasticity, such as, but not limited to, a liver hardness measurement (often LSM for english acronym). In some embodiments, the liver fibrosis parameter may also include a liver viscosity parameter, and the co-analysis of the liver elasticity parameter and the viscosity parameter may enable a more comprehensive assessment of the degree of fibrosis of the liver. Steatosis in the liver is the accumulation of fat in the liver and can be quantified using a measurement of the attenuation of ultrasound propagation (ultrasound attenuation measurement is often abbreviated as UAP). The liver inflammation parameters include various parameters that characterize the degree of inflammatory activity. In some embodiments, the liver inflammation activity or tissue inflammation activity related information may be obtained as the liver inflammation index according to a preset liver hardness or a corresponding relationship between a parameter reflecting the liver hardness and the liver inflammation activity. The liver inflammation index is often abbreviated as LID or RFIn, etc. For example, the correspondence may include: when the liver hardness LSM is 6.1-8.7kpa, the corresponding tissue inflammation activity is mild group inflammation necrosis; when the LSM is 8.7-13.2kpa, the corresponding tissue inflammation activity is moderate tissue inflammation necrosis; when the LSM value is more than 13.2kpa, the corresponding tissue inflammation activity is severe tissue inflammation necrosis. In some embodiments, the correspondence further comprises: the corresponding relation between LSM and the activity of the liver inflammation is preset respectively for the viral hepatitis, the autoimmune hepatitis, the primary biliary cholangitis, the non-alcoholic fatty liver disease, the drug-induced liver disease and the liver disease with unknown etiology.
The first processor 103 may be further configured to: displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display 105, such that a user can view the liver fibrosis parameter, the liver steatosis parameter together with the liver inflammation parameter. Note that it is not necessary that all three parameters be presented on the display 105 at the same time, but they may be presented sequentially or in response to a user operation, and the user can view any one of the parameters, particularly the liver inflammation parameter, as long as the user needs. In this way, the user can compare and refer to the three parameters (or compare and refer to partial parameters thereof) to diagnose the changeful and complex pathological condition of the liver more sensitively and accurately. For example, in the case of high liver fibrosis parameter but low liver inflammation parameter, the doctor can accurately judge that the liver lesion is in a stable stage and does not rapidly progress, and the dosage can be controlled as appropriate. For another example, in the case of a low liver fibrosis parameter but a significantly high liver inflammation parameter, a physician may evaluate that the liver is still in a compensatory stage, but rapid fibrosis may occur, and if the liver steatosis parameter is not good at the same time, the physician may be alerted and may intervene in a timely manner, and the physician may need to check periodically at short intervals to monitor the effect of the medical intervention, adjust the medication, and so on.
In some embodiments, the ultrasound data may be acquired by the liver elasticity measurement device 100 on the same time for the subject. That is, the first processor 103 may perform a rapid analysis on the ultrasound data of the same time interval of the subject to derive the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter of the same time interval of the subject. For example, the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter of the time period can be presented immediately even after the liver elasticity detection is performed on the detected person, so that a doctor can more conveniently and timely pay attention to the correlation and the synergistic action of the three parameters, and the pathological condition of the liver can be more accurately evaluated.
In some embodiments, the first processor 103 may be further configured to: calculating a liver fibrosis score according to the liver fibrosis parameters; calculating a liver steatosis score based on the liver steatosis parameter; calculating a liver inflammation score according to the liver inflammation parameters; the liver fibrosis score, the liver steatosis score and the liver inflammation score are displayed together on the display 105, as shown in fig. 3. The correspondence between the respective parameters and the scores may be established based on ground truth values including the respective parameters and the scores manually noted by the doctor, which are measured in advance, as training data. The corresponding relation can be established as a mathematical model and can also be realized by utilizing a learning network. In some embodiments, a score prediction model may be constructed based on a set of the above three types of parameters (liver fibrosis parameter, liver steatosis parameter, and liver inflammation parameter) measured in advance and three types of scores (liver fibrosis score, liver steatosis score, and liver inflammation score) manually labeled by a doctor as training data, so that the score prediction model can more accurately predict scores at various levels in consideration of the interaction between the three parameters. In particular, the liver fibrosis score, the liver steatosis score and the liver inflammation score are continuous numerical values, or discrete grades. By displaying the hepatic fibrosis score, the hepatic steatosis score and the hepatic inflammation score, doctors (particularly doctors with general expertise) can be helped to more intuitively understand the development conditions of three layers of fibrosis, steatosis and inflammatory activity of liver lesions, so that the lesion conditions of the liver can be more accurately evaluated.
The user may be given the freedom to choose whether to view the parameters or the score, which may be more desirable for a more patent skilled physician to obtain the original parameter values for more refined analysis, and for a more specialized physician to rely on the score for more reliable analysis. Accordingly, the first processor 103 may be further configured to: and receiving the operation of selecting the viewing parameters or the scores by the user. In the case where the user selects the viewing parameter, the first processor 103 may display the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter together on the display 105, as shown in fig. 2. In the event that the user selects a viewing score (as outlined in figure 3 by "display score"), the first processor 103 may display the hepatic fibrosis score 40, the hepatic steatosis score 60, and the hepatic inflammation score 70 together on the display 105. The three-level scores shown in figure 3 are indicative of a condition with a low degree of fibrosis but a high level of inflammatory activity, with rapid fibrosis.
As described above, the computing device 100a may be configured as the liver elasticity measurement device 100 or as a remote workstation.
Returning to fig. 1, a liver elasticity measurement device 100 is illustrated. The liver elasticity measurement apparatus 100 may include an ultrasonic transducer 101 configured to transmit and receive ultrasonic waves to a subject under a condition that a vibration excitation generates a shear wave; a transmission/reception control circuit 102 configured to output a transmission and reception sequence to the ultrasonic transducer to control transmission and reception thereof of ultrasonic waves; and a computing device 100a according to various embodiments of the present application, implemented via the first processor 103. That is, the computing device 100a multiplexes the first processor 103 of the liver elasticity measurement device itself. The liver elasticity measurement apparatus 100 may include a memory 104 and a display 105, wherein the memory 104 may be configured to store ultrasound data, may also store or load an evaluation method of liver lesion status according to various embodiments of the present application, may also store intermediate data generated when the evaluation method is implemented, and the like.
In some embodiments, the first processor 103 may be a processing device including more than one general purpose processing device, such as a microprocessor, Central Processing Unit (CPU), Graphics Processing Unit (GPU), or the like. The memory 104 may be a non-transitory computer-readable medium, such as Read Only Memory (ROM), Random Access Memory (RAM), phase change random access memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), other types of Random Access Memory (RAM), flash disk or other forms of flash memory, cache, registers, static memory, compact disk read only memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes or other magnetic storage devices, or any other possible non-transitory medium that can be used to store information or instructions that can be accessed by a computer device, and so forth.
In some embodiments, the display 105 may include a Liquid Crystal Display (LCD), a light emitting diode display (LED), a plasma display, or any other type of display, and provides a Graphical User Interface (GUI) presented on the display, as shown in fig. 2 and 3. Display 105 may comprise many different types of materials (such as plastic or glass) and may be touch sensitive to receive commands from a user. For example, the display 105 may comprise a substantially rigid touch sensitive material (such as Gorilla glass (TM)) or a substantially flexible touch sensitive material (such as Willow glass (TM)).
As shown in fig. 1, a shear wave generating device 106 may be included in the liver elasticity measurement device 100 to perform ultrasound data acquisition under external vibration excitation or acoustic radiation force excitation. For example, the frequency range of the external vibration excitation is 10-1000Hz, the vibration amplitude range is 0.001-10mm, and the vibration cycle number is 0.5-1000. As another example, the frequency range of the acoustic radiation force excitation is 0.5-50Mhz, the excitation pulse length is more than 10 mus, and the excitation position has more than one.
In some embodiments, the liver elasticity measurement device 100 may also not rely on a dedicated shear wave generating device 106 to induce shear waves, but rather acquire ultrasound data with an endogenous vibrational excitation including the subject's heartbeat or the subject's vocalization. In this way, the liver elasticity measurement device 100 can be made more compact.
In the case of intrinsic vibrational excitation, the ultrasound signals of the liver elasticity measurement device 100 have a frame frequency greater than 100Hz in order to capture shear waves with sufficient resolution.
In case of using intrinsic vibrational excitation, the first processor 103 or the liver elasticity measurement device 100 may be further configured to: filtering the acquired ultrasonic data, wherein the filtering range is 20-2000Hz, performing principal component analysis with the rank number larger than 3 on the filtered ultrasonic data, and determining the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter according to the data obtained after the principal component analysis. Therefore, background noise excited by endogenous vibration can be fully filtered, the data processing capacity is reduced, and the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter are accurately determined.
As shown in fig. 4, if the computing device 100a is configured at a remote workstation 400, the first processor 103 may obtain richer subject information via a network 401. For example, the first processor 103 may acquire a biological parameter of the subject, the biological parameter including at least one of a weight, a height, a waist circumference, a hip circumference, a chest circumference, an age, a gender, a BMI, a subcutaneous tissue thickness, and a subcutaneous fat thickness of the subject. These biological parameters may be interrogated by the physician while visiting the subject or acquired while performing the underlying physical examination and transmitted to the remote workstation 400 via the network 401. As such, the first processor 103 may calculate a liver lesion composite score of the subject, which is a continuous numerical value or a discrete scale, in consideration of the biological parameter, while based on the liver fibrosis parameter, the liver steatosis parameter, and the liver inflammation parameter. The biological parameters also influence the liver lesion comprehensive score to a certain extent, the fluctuation is small in a short period, the specificity is not enough when the biological parameters are independently considered, and the biological parameters are considered as auxiliary factors, so that the liver lesion comprehensive score of the detected person can be calculated more accurately.
In some embodiments, the biochemical parameters from the clinical laboratory may be transmitted to the remote workstation 400 via the network 401. Further, various department test data relating to liver pathology may be transmitted to the remote workstation 400 for aggregate analysis. Accordingly, the first processor 103 may be further configured to: obtaining biochemical parameters of the subject, the biochemical parameters including a level of at least one of AST, ALT, transaminase, GGT, PAL, iron serum, ferritin, transferrin saturation, lipoxygenase oxidizing hormone, cytokinin, cholesterol HDL, blood glucose, insulinemia, bilirubin, a2 macroglobulin, hemophilin, apolipoprotein a1, CK-18, triglycerides, high density lipoprotein, low density lipoprotein, very low density lipoprotein, adiponectin, urea, polymorphic genes, CRP, leptin, and metabolic biochemical parameters of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter, and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biochemical parameter. These biochemical parameters may fluctuate with the subject's food structure and detection time, resulting in insufficient specificity, but considered as an adjunct factor, the subject's liver lesion composite score can be calculated more accurately. For example, ALT and AST are distributed mainly in hepatocytes, and elevation of ALT and AST indicates damage to hepatocytes. ALT is the most sensitive. A 1-fold increase in ALT in serum indicates 1% hepatocyte necrosis. The elevation of ALT and AST is generally consistent with the degree of hepatocyte damage. ALT is mainly distributed in the liver cell plasma, ALT elevation reflects damage of liver cell membranes, and AST is mainly distributed in the liver cell plasma and liver cell mitochondria. Therefore, the elevation of ALT and AST is different in different liver inflammations, and the ratio of ALT to AST is also different. Take ALT as an example. ALT normal values are affected by many factors, such as age and sex, and the baseline level of ALT varies greatly from individual to individual. In practical applications, ALT can not completely and accurately reflect the 'inflammatory cell infiltration' of liver, and a considerable part of patients find moderate or severe 'inflammatory cell infiltration' of liver through liver biopsy, but ALT is still at a normal level, namely less than or equal to 40U/L. Thus ALT alone is normal and does not negate the vigilance of liver lesions, but needs to be combined with other parameters. When ALT is abnormal, when the liver inflammation parameters are in the boundary range between normal and abnormal, the liver inflammation can be determined, and more accurate assessment can be carried out by matching with the liver fibrosis parameters and the liver steatosis parameters.
Fig. 5 shows a block diagram of a remote workstation according to an embodiment of the present application. As shown in FIG. 5, the remote workstation 400 includes an interface 501, a second processor 502, and a display 503, and is communicatively coupled to a computing device according to various embodiments of the present application. The interface 501 may include a network adapter, cable connector, serial connector, USB connector, parallel connector, high speed data transmission adapter (such as fiber optic, USB 3.0, thunderbolt interface, etc.), wireless network adapter (such as WiFi adapter), telecommunications (3G, 4G/LTE, 5G, etc.) adapter, and the like. The second processor 502 and the display 503 may adopt similar hardware configurations of the first processor 103 and the display 105 shown in fig. 1, which are not described herein again.
The interface 501 may be configured to: receiving a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement, and a liver inflammation parameter comprising a liver inflammation index determined by the computing device; receiving a biological or biochemical parameter of the subject. The second processor 502 may be configured to: calculating a liver lesion composite score of the subject based on the received liver fibrosis parameter, liver steatosis parameter and liver inflammation parameter of the subject, with the biological parameter or biochemical parameter taken into account, the liver lesion composite score being a continuous numerical value or a discrete scale; causing the display 503 to display the subject's liver lesion composite score.
In some embodiments, the biological parameter of the subject comprises at least one of weight, height, waist circumference, hip circumference, chest circumference, age, gender, BMI, subcutaneous tissue thickness, and subcutaneous fat thickness of the subject. In some embodiments, the biochemical parameter of the subject comprises a level of at least one of AST, ALT, transaminase, GGT, PAL, iron serum, ferritin, transferrin saturation, lipoxygenase, cytokinin, cholesterol HDL, blood glucose, insulinemia, bilirubin, a2 macroglobulin, hemophilin, apolipoprotein a1, CK-18, triglycerides, high density lipoprotein, low density lipoprotein, very low density lipoprotein, adiponectin, urea, a polymorphic gene, CRP, leptin, and a metabolic biochemical parameter of the subject.
These biological and biochemical parameters may carry a measurement time when transmitted to the remote workstation 400, such that the measurement time of the biological and biochemical parameters of the subject may not exceed a time threshold from the acquisition time of the ultrasound data. In this way, it is ensured that these biological, biochemical and ultrasound parameters (and the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter or even the score calculated therefrom) can characterize the medical information reflecting the condition of the liver lesion at various levels of the subject at the same time period, thereby helping the doctor to evaluate the condition of the liver lesion more accurately.
In some embodiments, the present application further provides a non-transitory computer storage medium having stored thereon computer instructions that, when executed by a third processor, implement a method of assessing a liver lesion status.
Fig. 6 shows a flow chart of a method for evaluating a liver lesion status according to an embodiment of the present application. As shown in fig. 6, the evaluation method may include the steps 601: based on ultrasound data acquired by the liver elasticity measurement device for the subject, a liver fibrosis parameter comprising a liver elasticity measurement (and may also comprise a liver viscosity parameter), a liver steatosis parameter comprising an ultrasound attenuation measurement, and a liver inflammation parameter comprising a liver inflammation index are determined. The evaluation method may comprise step 602: displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display such that a user can view the liver fibrosis parameter, the liver steatosis parameter together with the liver inflammation parameter.
In some embodiments, the evaluation method may further include: calculating a liver fibrosis score according to the liver fibrosis parameters; calculating a liver steatosis score based on the liver steatosis parameter; calculating a liver inflammation score according to the liver inflammation parameters; displaying the hepatic fibrosis score, the hepatic steatosis score and the hepatic inflammation score together on a display.
For example, the hepatic fibrosis score, the hepatic steatosis score and the hepatic inflammation score are continuous numbers, or discrete levels.
In some embodiments, the evaluation method further comprises: receiving operation of selecting viewing parameters or scores by a user; in a case where a user selects a viewing parameter, the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter are displayed together on a display, and in a case where a user selects a viewing score, the liver fibrosis score, the liver steatosis score and the liver inflammation score are displayed together on a display.
In some embodiments, the evaluation method may further include: obtaining a biological parameter of the subject, the biological parameter comprising at least one of a weight, a height, a waist circumference, a hip circumference, a chest circumference, an age, a gender, a BMI, a subcutaneous tissue thickness, and a subcutaneous fat thickness of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biological parameter.
In some embodiments, the evaluation method may further include: obtaining biochemical parameters of the subject, the biochemical parameters including a level of at least one of AST, ALT, transaminase, GGT, PAL, iron serum, ferritin, transferrin saturation, lipoxygenase oxidizing hormone, cytokinin, cholesterol HDL, blood glucose, insulinemia, bilirubin, a2 macroglobulin, hemophilin, apolipoprotein a1, CK-18, triglycerides, high density lipoprotein, low density lipoprotein, very low density lipoprotein, adiponectin, urea, polymorphic genes, CRP, leptin, and metabolic biochemical parameters of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter, and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biochemical parameter.
The order of the various steps in this application is exemplary only and not limiting. The execution order of the steps can be adjusted without affecting the implementation of the present application (without destroying the logical relationship between the required steps), and various embodiments obtained after the adjustment still fall within the scope of the present application.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs unless specifically defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
The above description is intended to be illustrative and not restrictive. For example, the above-described examples (or one or more versions thereof) may be used in combination with each other. For example, other embodiments may be used by those of ordinary skill in the art upon reading the above description. In addition, in the above detailed description, various features may be grouped together to streamline the application. This should not be interpreted as an intention that a non-claimed disclosed feature is essential to any claim. Rather, inventive subject matter may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the detailed description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that these embodiments may be combined with each other in various combinations or permutations. The scope of the invention should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
Claims (21)
1. A computing device for assessing liver lesion status, comprising a first processor configured to:
determining a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement and a liver inflammation parameter comprising a liver inflammation index based on ultrasound data acquired by a liver elasticity measurement device for a subject; and
displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display such that a user can view the liver fibrosis parameter, the liver steatosis parameter and/or the liver inflammation parameter.
2. The computing device of claim 1, wherein the ultrasound data is acquired by the liver elasticity measurement device on a subject at a same time.
3. The computing device according to claim 1 or 2, wherein the computing device is configured in or communicatively connected with the liver elasticity measuring device.
4. The computing device of claim 1, wherein the ultrasound data is acquired by the liver elasticity measurement device with an endogenous vibrational excitation comprising a heartbeat of the subject or a vocalization of the subject.
5. The computing device of claim 4, wherein the ultrasound signals of the liver elasticity measurement device have a frame rate greater than 100 Hz.
6. The computing device of claim 4 or 5, wherein the first processor or the liver elasticity measurement device is further configured to: filtering the acquired ultrasonic data, wherein the filtering range is 20-2000Hz, performing principal component analysis with the rank number larger than 3 on the filtered ultrasonic data, and determining the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter according to the data obtained after the principal component analysis.
7. The computing device of claim 1, wherein the ultrasound data is acquired by the liver elasticity measurement device with external vibration excitation or acoustic radiation force excitation.
8. The computing device of claim 7, wherein the external vibration stimulus has a frequency in the range of 10-1000Hz, a vibration amplitude in the range of 0.001-10mm, and a vibration cycle number in the range of 0.5-1000.
9. The computing device of claim 7, wherein the acoustic radiation force excitation has a frequency range of 0.5-50Mhz, an excitation pulse length greater than 10 μ s, and more than one excitation location.
10. The computing device of claim 1 or 2, wherein the first processor is further configured to: calculating a liver fibrosis score according to the liver fibrosis parameters; calculating a hepatic steatosis score based on the hepatic steatosis parameter; calculating a liver inflammation score according to the liver inflammation parameters; displaying one or more of the liver fibrosis score, the liver steatosis score, and the liver inflammation score on a display.
11. The computing device of claim 10, wherein the liver fibrosis score, the liver steatosis score, and the liver inflammation score are continuous numerical values, or discrete levels.
12. The computing device of claim 10, wherein the first processor is further configured to: receiving operation of selecting viewing parameters or scores by a user; displaying one or more of the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter on a display in case the user selects a viewing parameter, and displaying one or more of the liver fibrosis score, the liver steatosis score and the liver inflammation score on a display in case the user selects a viewing score.
13. The computing device of claim 1 or 2, wherein the computing device is configured at a remote workstation, and wherein the first processor is further configured to: acquiring a biological parameter of the subject, the biological parameter comprising at least one of a weight, a height, a waist circumference, a hip circumference, a chest circumference, an age, a gender, a BMI, a subcutaneous tissue thickness, and a subcutaneous fat thickness of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biological parameter.
14. The computing device of claim 1 or 2, wherein the computing device is configured at a remote workstation, and wherein the first processor is further configured to: obtaining biochemical parameters of the subject, the biochemical parameters including a level of at least one of AST, ALT, transaminase, GGT, PAL, iron serum, ferritin, transferrin saturation, lipoxygenase oxidizing hormone, cytokinin, cholesterol HDL, blood glucose, insulinemia, bilirubin, a2 macroglobulin, hemophilin, apolipoprotein a1, CK-18, triglycerides, high density lipoprotein, low density lipoprotein, very low density lipoprotein, adiponectin, urea, polymorphic genes, CRP, leptin, and metabolic biochemical parameters of the subject; calculating a composite score of liver lesions of the subject based on the liver fibrosis parameter, the liver steatosis parameter, and the liver inflammation parameter, the composite score of liver lesions being a continuous numerical value or a discrete scale, with consideration of the biochemical parameter.
15. The computing device of claim 1 or 2, wherein the liver fibrosis parameters further comprise a liver viscosity parameter.
16. A liver elasticity measurement device, comprising:
an ultrasonic transducer configured to transmit and receive ultrasonic waves to a subject with a shear wave generated by vibration excitation;
a transmission/reception control circuit configured to output a transmission and reception sequence to the ultrasonic transducer to control transmission and reception thereof;
the computing device of any of claims 1-12.
17. A remote workstation communicatively coupled to a computing device as claimed in any one of claims 1 to 12 and comprising:
an interface configured to: receiving a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement, and a liver inflammation parameter comprising a liver inflammation index determined by the computing device; receiving a biological or biochemical parameter of the subject; and
a second processor configured to: calculating a composite score of liver lesions of the subject based on the received liver fibrosis parameter, liver steatosis parameter and liver inflammation parameter of the subject, with consideration of the biological or biochemical parameters, the composite score of liver lesions being a continuous numerical value or a discrete scale; displaying a composite score of liver lesions of the subject.
18. The remote workstation of claim 17, wherein the biological parameter of the subject includes at least one of a weight, a height, a waist circumference, a hip circumference, a chest circumference, an age, a gender, a BMI, a subcutaneous tissue thickness, and a subcutaneous fat thickness of the subject.
19. The remote workstation of claim 17, wherein the biochemical parameters of the subject include a level of at least one of AST, ALT, transaminase, GGT, PAL, iron serum, ferritin, transferrin saturation, lipoxygenase oxidizing hormone, cytokinin, cholesterol HDL, blood glucose, insulinemia, bilirubin, a2 macroglobulin, hemophilin, apolipoprotein a1, CK-18, triglycerides, high density lipoprotein, low density lipoprotein, very low density lipoprotein, adiponectin, urea, polymorphic genes, CRP, leptin, and metabolic biochemical parameters of the subject.
20. The remote workstation of claim 18 or 19, wherein a time of measurement of a biological parameter and a biochemical parameter of the subject is no more than a time threshold away from an acquisition time of the ultrasound data.
21. A non-transitory computer storage medium having stored thereon computer instructions that, when executed by a third processor, implement a method of assessing a liver lesion status:
determining a liver fibrosis parameter comprising a liver elasticity measurement, a liver steatosis parameter comprising an ultrasound attenuation measurement and a liver inflammation parameter comprising a liver inflammation index based on ultrasound data acquired by a liver elasticity measurement device for a subject; and
displaying one or more of the liver fibrosis parameter, the liver steatosis parameter, and the liver inflammation parameter on a display such that a user can view the liver fibrosis parameter, the liver steatosis parameter, and/or the liver inflammation parameter.
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| CN202210769486.XA CN114983477A (en) | 2022-06-30 | 2022-06-30 | Computing device, liver elasticity measuring device, remote workstation and medium for evaluating liver lesion status |
| PCT/CN2022/143958 WO2024001142A1 (en) | 2022-06-30 | 2022-12-30 | Computing device for assessing liver lesion conditions, liver elasticity measurement device, remote workstation, and medium |
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