Method and system for predicting the condition of an individual's spine

Abstract

The invention relates to a method for predicting the state of a spine of an individual, said method comprising: - a first estimation (E1) of personalized information of the spine from first input data (d1); - a second estimation (E2) of mechanical loads likely to be applied to the spine from second input data (d2); - a calculation (E3) for a prediction of the state of the spine from the first estimation (E1) and the second estimation (E2). Figure for abstract: Fig. 1

Description

Title of the invention: Method and system for predicting the condition of an individual's spine Technical field

[0001] The present invention relates to a method for predicting the state of an individual's spine. The present invention also relates to a system for predicting the state of an individual's spine. The invention also relates to a computer program implementing such a method. The invention finally relates to a recording medium on which such a program is recorded. Prior Art

[0002] The spine has a mechanical role in maintaining the human body and a neurological role in ensuring the protection of the spinal cord in the vertebral canal. A healthy spine supports the body's weight painlessly, ensures good mobility and a balanced posture. With increasing life expectancy, it appears important to preserve the health of the spine to ensure a good quality of life for individuals. The condition of the spine is a key parameter of an individual's overall health.

[0003] Solutions exist for detecting the presence of a pathology when performing an imaging examination of an individual's spine, for example a radiological examination. The prescribing physician and / or the radiologist use the data from the examination to propose a diagnosis of the state of the patient's spine at the time of the examination.

[0004] Furthermore, solutions exist to refine a surgeon's surgical gesture during a spinal operation. However, the effectiveness of treating a pathology in the long term remains uncertain and the relapse rate approaches 10%. Indeed, the initial surgery may fail and / or negatively affect neighboring areas of the spine which could in turn become pathological and painful for the patient.

[0005] Existing solutions do not allow for the estimation of the evolution of the state of health of the spine over time, particularly for patients at risk due to their lifestyle or previous surgical treatment.

[0006] The invention aims to overcome at least in part the aforementioned drawbacks of the prior art. More particularly, the invention aims to provide a method and a system for predicting the state of a spine of an individual which is simple, effective, reliable and accurate. Summary of the invention

[0007] An object of the invention is therefore a method for predicting the state of a spinal column of an individual, said method comprising:

[0008] - a first estimate of personalized information of the spine to from initial input data;

[0009] - a second estimate of mechanical loads likely to be applied to the spine from second input data;

[0010] - a calculation for a prediction of the state of the spine from the first estimate and second estimate.

[0011] By “personalized information” we mean in particular information dependent on each individual or specific to each individual.

[0012] The personalized information may be biochemical and / or structural information of an individual's spine.

[0013] The first input data can be obtained by imaging and possibly image processing techniques.

[0014] The second input data may be derived from data concerning an individual's lifestyle.

[0015] An advantage of such a method is that it is based on a multi-scale, multi-physical model of the spine, making it possible to describe the physical, biological, and chemical phenomena at the heart of the matter. Such a method thus makes it possible to obtain an accurate prediction of the progression of degeneration of intervertebral discs and vertebrae, as well as changes in the shape of the spine. Such a method makes it possible to improve prevention and treatment related to spinal problems, thus opening up new perspectives in the field of spinal health.

[0016] An advantage of such a method is that it allows the state of the spine to be predicted in the future in order to inform an individual of the risks concerning his spine before he develops a pathology.

[0017] An advantage of such a method lies in the fact that predictions can be obtained based on different scenarios. Such a method thus makes it possible to estimate the effects of different treatments, in particular medicinal and / or surgical and / or based on a change in lifestyle.

[0018] The condition of the spine may include the grade of at least one intervertebral disc and / or the grade of at least one vertebra.

[0019] The first input data may include:

[0020] - personal information relating to the individual, for example his age and / or his height and / or its weight; and / or

[0021] - imaging data obtained by at least one medical imaging technique, for example from magnetic resonance imaging (MRI), the data imaging including in particular the thickness (height) and / or the surface area and / or the position of intervertebral discs.

[0022] The second input data may include information about the individual's lifestyle, for example his or her occupation and / or physical habits and / or sleep and / or diet.

[0023] The method may include obtaining a digital twin of the spine.

[0024] The first estimate may use artificial intelligence.

[0025] The second estimate may use artificial intelligence.

[0026] The method may further comprise providing at least one message, in particular:

[0027] - at least one personalized recommendation; and / or

[0028] - at least one directive intended to help a practitioner to choose at least one treatment, for example in the group including drug treatments, physical or bodily treatments, surgical treatments; and / or

[0029] - at least one directive for personalized surgical planning purposes.

[0030] The invention also relates to a system for predicting the state of a spinal column of an individual, the system comprising a first storage unit capable of storing first input data, a second storage unit capable of storing second input data and at least one hardware processor capable of implementing:

[0031] - a first estimate of personalized information of the spine to from the first input data;

[0032] - a second estimate of mechanical loads likely to be applied on the spine from the second input data;

[0033] - a calculation for a prediction of the state of the spine from the first estimate and second estimate.

[0034] The invention also relates to a computer program product comprising instructions which, when the program is executed by a computer, cause the latter to implement the method defined previously.

[0035] The invention also relates to a data recording medium, readable by a computer, on which a computer program product defined above is recorded. Description of the figures

[0036] [Fig. 1] is a flowchart of one embodiment of a method for predicting the condition of a spinal column.

[0037] [Fig.2] is a plan view schematically showing an inter-disc vertebral.

[0038] [Fig.3] represents an embodiment of a system for predicting the state of a spinal column. Detailed description of the invention

[0039] The invention proposes a method for predicting the state of an individual's spine in the future, in particular from imaging data of a spine or spine.

[0040] An embodiment of a method for predicting the condition of a spine of an individual is described below with reference to [Fig.l].

[0041] The method comprises a first estimation El (ESTIM1) of personalized information of the spine, in particular biochemical and / or structural, from first input data dl.

[0042] By “personalized information” we mean in particular information dependent on each individual or specific to each individual.

[0043] The first input data dl can be obtained by imaging techniques and possibly image processing.

[0044] The first input data dl may include personal information related to the individual, for example the age, gender, height, weight, ethnic origin of the individual.

[0045] By age of an individual is meant a measure of the time elapsed since birth. By sex of an individual is meant a biological classification of an individual as male or female. By weight of an individual is meant a measure of body mass of an individual.

[0046] The first input data dl may further comprise demographic data. The demographic data may be obtained from scientific literature.

[0047] The first input data dl may comprise imaging data. The imaging data may be obtained by at least one medical imaging technique.

[0048] Imaging data can be obtained from magnetic resonance imaging (MRI). MRI uses radio waves and a strong magnetic field to create detailed images of the spine. MRI is advantageous for evaluating the soft tissues of the spine such as intervertebral discs, ligaments, and spinal cord.

[0049] The imaging data may be obtained from a medical imaging technique other than an MRI.

[0050] Imaging data may be obtained from an X-ray. A ra Diography can provide an overview of the bony structures of the spine and help detect possible fractures or deformities.

[0051] Imaging data can be obtained from a computed tomography (CT) scan. CT uses X-rays to create detailed cross-sectional images of the spine. This provides accurate information about the bones, intervertebral discs, and surrounding structures.

[0052] For all the variants described above for obtaining imaging data, the imaging data may undergo processing, in particular implemented via software. Such processing of the imaging data makes it possible in particular to estimate physical parameters, describing for example the state of at least one intervertebral disc.

[0053] An anatomical structure of an intervertebral disc 1 is shown in [Fig.2].

[0054] The intervertebral disc 1 comprises a central part called the nucleus pulposus or nucleus pulposus NP surrounded by a ring called the annulus fibrosus or annulus fibrosus AF.

[0055] The annulus fibrosus AF of the intervertebral disc 1 comprises lamellar layers 3, oriented collagen fibers 5 and interlamellar layers 7.

[0056] The annulus fibrosus AF of the intervertebral disc 1 comprises a fluid portion and a solid portion. The fluid portion comprises water. The solid portion comprises an extracellular matrix and collagen.

[0057] The intervertebral disc 1 comprises an Anterior-Internal region AI, an Anterior-External region AO, a Posterior-Internal region PI, a Posterior-External region PO.

[0058] The volume fractions of the different constituents of the fibrous ring AF of the intervertebral disc 1 depend on the region AI, AO, PI, PO of the intervertebral disc 1.

[0059] The oriented collagen fibers 5 have, for example, dimensions of the order of 250 micrometers.

[0060] The intervertebral disc 1 further comprises elastic fibers of nanometric dimensions, for example of the order of 150 nanometers.

[0061] The first input data dl may include intrinsic chemo-mechanical properties of the constituents of the spine.

[0062] By “chemo-mechanical properties” we mean in particular properties linked to chemical and mechanical phenomena.

[0063] The first input data dl may include biochemical information of the constituents of the spine, including the densities of water, collagen and the extracellular matrix.

[0064] The first input data dl may comprise intrinsic information of the intervertebral discs, in particular biochemical information, linked to the individual.

[0065] The first input data dl may include the fiber orientations and distributions of the collagen network of the intervertebral discs.

[0066] The first input data dl may comprise a definition of the multi-scale distribution, from the nanometric scale, of collagen networks of the spine.

[0067] The imaging data may include at least one dimension of the intervertebral discs. The imaging data may include the thickness (height) of at least one intervertebral disc and / or the surface area of ​​at least one intervertebral disc and / or the position of at least one intervertebral disc.

[0068] By thickness or height of an intervertebral disc, we mean a dimension of an intervertebral disc in a direction A parallel or substantially parallel to the main direction in which the spinal column extends.

[0069] The imaging data may include the amount of water in at least one intervertebral disc.

[0070] A mathematical model can be used to exploit the first input data dl to obtain the first estimate EL

[0071] Advantageously, in the first estimate E1, the imaging data can be coupled with personal information related to the individual and / or demographic data deemed relevant according to the scientific literature, to estimate the personalized information, in particular biochemical and / or structural, of the spine. This results in a first estimate having high precision.

[0072] The first estimate E1 may comprise an evaluation of the state of the spine of an individual at an initial moment, in particular from a result of a medical imaging technique of the spine.

[0073] Assessing the condition of an individual's spine may include determining the grade of the intervertebral discs and / or the grade of the vertebrae of the spine at the initial time.

[0074] Intervertebral discs can be classified according to their condition and degeneration.

[0075] As soon as growth ends and under the effects of everyday life, the intervertebral discs are the site of degenerative phenomena, corresponding in particular to cracks in the periphery of the disc (fibrous ring AF) and dehydration of its center (nucleus pulposus NP).

[0076] An example of classification of intervertebral disc grades is described below.

[0077] According to a first grade, called Grade I, the intervertebral disc is considered normal, with no significant signs of degeneration. The structure of the intervertebral disc is intact, with good hydration and normal height.

[0078] According to a second grade, called Grade II, the intervertebral disc shows slight degeneration, often characterized by minor signs of loss of hydration or slight alteration of the structure. The height of the intervertebral disc may be slightly reduced.

[0079] According to a third grade, called Grade III, the degeneration of the intervertebral disc is moderate. The intervertebral disc shows more obvious signs of loss of hydration, a decrease in height and more pronounced structural changes, such as cracks or deformations.

[0080] According to a fourth grade, called Grade IV, the degeneration of the intervertebral disc is severe. The intervertebral disc is considerably dehydrated, with a significantly reduced height. There may be significant structural deformations, disc herniations or disc protrusions.

[0081] According to a fifth grade, called Grade V, the degeneration of the intervertebral disc is at the most advanced stage. The intervertebral disc is completely dehydrated, with a total loss of height. Adjacent structures, such as the vertebrae and surrounding tissues, may be affected and show signs of deterioration.

[0082] It should be noted that this classification may vary slightly depending on the classification systems used by health professionals, such as the Pfirrmann classification or the Modic classification. These classification systems aim to assess the condition of the intervertebral discs and provide useful information for the diagnosis and management of spinal problems.

[0083] The vertebrae of the spine can also be classified according to different criteria, such as their shape, position and condition.

[0084] An example of vertebral grade classification is described below.

[0085] The classification of vertebral grades according to the VBQ (Vertebral Bone Quality) system is linked to the evaluation of the bone mineral density of the vertebrae. The VBQ system allows the mineral density of the vertebrae to be quantified using a medical imaging technique. The VBQ system allows vertebrae to be graded according to their mineral density, thus reflecting their health status and their risk of fracture.

[0086] According to a first grade, called Grade 1, the bone mineral density of the vertebra is normal, indicating a healthy vertebra.

[0087] According to a second grade, called Grade 2, the bone mineral density of the vertebra is slightly reduced, but without signs of fracture.

[0088] According to a third grade, called Grade 3, the bone mineral density of the vertebra is moderately reduced, presenting an increased risk of fracture.

[0089] According to a fourth grade, called Grade 4, the bone mineral density of the vertebra is significantly reduced, indicating a high risk of fracture.

[0090] The method may comprise a prior step E01 (MODEL) of biomechanical modeling of the spinal column.

[0091] The biomechanical modeling of the spine may include a geometric representation of the spine.

[0092] The geometric representation of the spine is for example a three-dimensional representation of the series of intervertebral discs and vertebrae of the spine.

[0093] The geometric representation can take into account the shape of the intervertebral discs, the fact that they comprise several layers, the variable thickness (height) of the intervertebral discs.

[0094] The geometric representation can take into account the multi-scale distribution of intervertebral discs.

[0095] The geometric representation can take into account the regional variation of the morphology of the intervertebral disc, in particular as a function of the different regions described in relation to [Fig.2].

[0096] Biomechanical modeling of the spine may include discretizing the geometry of the intervertebral discs and vertebrae into material points to represent these anatomical structures in a simplified manner.

[0097] A geometric representation of an intervertebral disc may comprise a set of material points that are distributed along the surface of the intervertebral disc. The general shape of an intervertebral disc may be considered as a circular surface of variable diameter relative to the center of the intervertebral disc. A number of points equidistant from the perimeter of the intervertebral disc may be determined. The material points notably geometrically represent the approximate positions of the lamellae of the annulus fibrosus AF as well as the area that separates the annulus fibrosus AF from the nucleus pulposus NP.

[0098] The biomechanical modeling of the spine may include an association with the material points of the intervertebral discs of biochemical information of the constituents of the intervertebral discs, in particular water and / or collagen and / or the extracellular matrix. The biomechanical modeling of the spine may take into account the multi-scale distribution, from the nanometric scale, of collagen networks.

[0099] The number of material points of the biomechanical modeling of the spinal column can be chosen so as to optimize a compromise between precise discretization and reduced calculation time.

[0100] A geometric representation of a vertebra may comprise a set of material points which are distributed along the contact surfaces of the vertebra with the intervertebral discs. The contact surfaces of a vertebra with the intervertebral discs can be represented by a set of regularly spaced points, for example in the form of a grid of points. A discrete representation of the geometry of a vertebra can thus be obtained. A set of material points can be added along the contours of the vertebrae to represent the complex shape of the vertebrae.

[0101] Biomechanical modeling of the spine may include associating biochemical information with material points of the vertebrae.

[0102] An advantage of such biomechanical modeling lies in the fact that it is simple to implement because it makes it possible to take into account the interactions between the three-dimensional geometric representations of the intervertebral discs and vertebrae comprising material points and the intrinsic bio-chemo-mechanical properties of the intervertebral discs and vertebrae.

[0103] By “intrinsic bio-chemo-mechanical properties” is meant in particular properties linked to biological, chemical and mechanical phenomena or aspects inherent to biological tissues.

[0104] Once the three-dimensional geometric representations of the intervertebral discs and vertebrae have been produced, biomechanical simulations can be implemented using the material points to calculate the forces, deformations and movements of the intervertebral discs and vertebrae. The simulations are intended in particular to study the evolution of the microstructural behavior of the different components of the spinal column and the effects of this evolution on the health of the spinal column.

[0105] Such biomechanical modeling using a discretization of the three-dimensional geometric representations of the intervertebral discs and vertebrae makes it possible to simplify the calculations while preserving the essential characteristics of the anatomical geometry. This results in an improved understanding of the mechanical behaviors and interactions within the spine.

[0106] The first estimate El may include a definition of the relationship between microstructure and intrinsic bio-chemo-mechanical properties for each material point by including the regional variation in the initial state.

[0107] The method may comprise obtaining a digital twin of an individual's spine, in particular using digital means to represent the spine. The digital twin is for example created from an MRI.

[0108] The first estimate El can be carried out using a mathematical model, in particular using equations integrated into the digital twin of the individual's spine.

[0109] The first estimate El may comprise sub-steps for obtaining the first input data dl.

[0110] The first estimate El may comprise a sub-step of collecting the first input data dl.

[0111] In the collection sub-step, first input data dl may be collected through an analysis of at least one image, for example at the location of each material point.

[0112] In the collection sub-step, first input data dl can be collected, in particular systematically, from existing scientific literature. The first input data dl can be extracted from journal articles, experimental studies, specialized databases.

[0113] Advantageously, automatic data extraction techniques may be used, for example by focusing on specific key terms and search criteria. This results in a simple to implement sub-step of collecting the first input data.

[0114] The first estimate El may comprise a sub-step of normalization of the first input data dl.

[0115] Once the first input data dl is collected, the first input data dl can be normalized. The normalization substep is intended to ensure the consistency, uniformity and comparability of the first input data dl.

[0116] Advantageously, the normalization sub-step can comprise a definition of formats and structures of the first input data dl.

[0117] Optionally, the first estimation El may comprise a sub-step of converting units of measurement of at least a part of the first input data dl when this is required.

[0118] Optionally, the first estimate El may include a sub-step of using standardized references.

[0119] The first estimate El may comprise a sub-step of integrating the first input data dl into a first centralized database.

[0120] The definition of formats and structures of the first input data dl during the normalization sub-step described above is in particular intended to facilitate the integration of the first input data dl into the first database during the integration sub-step.

[0121] The first database is for example a relational database or another storage system suitable for organizing the first input data dl, in particular so as to be able to query them efficiently.

[0122] The first estimate El may include a sub-step of validation of the first input data dl. The validation sub-step is intended to ensure the quality and reliability of the first input data dl.

[0123] The validation sub-step may include a comparison with other reliable sources of data and / or consultation with domain experts and / or the use of specific validation methods for each type of first input data dl.

[0124] The first estimate El may comprise a sub-step of updating the first input data dl.

[0125] Advantageously, the update sub-step can be carried out several times over time, in particular regularly.

[0126] The update sub-step is intended to guarantee the quality and relevance of the first input data dl over time.

[0127] The update sub-step may include monitoring of new scientific publications, research advances and additional discoveries. The most recent information can thus be taken into account to make the first EL estimate.

[0128] Optionally, the first estimate E1 can be carried out using artificial intelligence AIL II. This results in a first estimate having increased precision.

[0129] The first estimate El can in particular use a random forest type learning algorithm.

[0130] The first estimation El may comprise training an artificial intelligence model. The first input data dl may be used to train at least one artificial intelligence model, such as neural networks. Artificial intelligence models may be developed to capture the complex relationships between the different variables corresponding to the first input data dl.

[0131] The method comprises a second estimation E2 (ESTIM2) of mechanical loads likely to be applied to the spinal column from second input data d2.

[0132] Second input data d2 can be used to carry out the second estimation E2, in particular to predict the mechanical loads, in particular the most severe ones, likely to affect the spinal column, as well as the movements, in particular the most repetitive ones, of the spinal column.

[0133] The second input data d2 may come from data concerning an individual's lifestyle.

[0134] The second input data d2 may include information about an individual's lifestyle, for example occupation, physical habits, an individual's diet, sleep, factors and / or stress level.

[0135] The second input data d2 may include information about an individual's occupation. Some occupations may expose the spine to specific stresses. For example, construction workers or movers are often subjected to heavy and repetitive lifting movements, which can put additional stress on the spine. People who work in offices may sit for long periods, which can lead to poor posture and back problems. By taking the occupation into account, it is possible to assess the mechanical loads and stresses imposed on the spine.

[0136] The second input data d2 may include information about an individual's physical habits. Physical activities, including sports and regular exercise, can have an impact on spinal health. For example, regularly playing high-impact sports such as rugby or weightlifting can increase the risk of spinal injuries. In contrast, muscle strengthening and flexibility exercises can help maintain a healthy spine.

[0137] The second input data d2 may include information about an individual's posture. Poor posture can put excessive pressure on the spine and lead to problems such as back pain or spinal misalignments.

[0138] The second input data d2 may comprise data relating to the environment of an individual.

[0139] The second estimate E2 may comprise an estimate, from the second input data d2, of modes or types of mechanical loadings which will be applied in the future to the spinal column, for example mechanical loadings in compression and / or traction and / or torsion and / or flexion and / or extension.

[0140] The second estimate E2 may comprise a definition of the loading conditions, in particular monotonous and / or cyclic, for different mechanical loading modes.

[0141] The second estimate E2 may comprise a determination of cyclic numbers of the mechanical loads applied to the vertebrae and intervertebral discs.

[0142] The second estimate E2 may comprise an estimate, from the second input data d2, of the amplitude of the mechanical loads which will be applied in the future to the spinal column, that is to say of the level of the forces which will be applied in the future to the spinal column.

[0143] The second estimate E2 may comprise an estimate, from the second input data d2, frequencies of mechanical loads that will be applied in the future to the spine.

[0144] A mathematical model can be used to exploit the second input data d2 to obtain the second estimate E2.

[0145] In the second estimation E2, an algorithm can use the second input data d2 to estimate the types of mechanical loadings and the force levels applying locally on each intervertebral disc.

[0146] A mathematical model can be used to estimate the interactions within the material, in particular the mechanical constraints, from the forces applied to the spine. Such a model can be defined in such a way as to take into account microstructural phenomena at the origin of the evolution of the behavior of the spine over time.

[0147] In the second estimation E2, an estimation of the state of stresses and biomechanical damage within the spine can be carried out using the second input data d2.

[0148] The mathematical model makes it possible to describe the biomechanical fatigue behavior of the intervertebral discs to predict the future state of the spinal column, in particular the grades of degeneration in the future of the intervertebral discs and vertebrae as well as their geometric evolutions thanks to a behavior law.

[0149] The second estimate E2 makes it possible to predict the mechanical damage to the spine over time.

[0150] The second estimate E2 may use a mechanical protocol to mimic the mechanical loads applied to an individual's spine.

[0151] The second estimation E2 may comprise a sub-step of collecting the second input data d2.

[0152] Advantageously, the second input data d2 can be collected by qualified health professionals, such as doctors specializing in the field of the spine or physiotherapists.

[0153] The second input data d2 can be collected using a questionnaire, in particular a generic one, to collect information on an individual's lifestyle, in particular on his profession, his physical habits, his diet, his sleep, his stress factors, in particular from the initial moment until the moment of the second estimation.

[0154] The second input data d2 may be obtained from a questionnaire. Such a questionnaire is intended to collect relevant information about an individual's lifestyle and to determine a personalized mechanical loading for each individual. The answers to the questionnaire questions may be used as a starting point to better understand an individual's context and to provide more specific information.

[0155] Examples of questions from such a questionnaire regarding an individual's occupation may include:

[0156] • What is your profession?

[0157] • How long have you been practicing this profession?

[0158] • What are your main responsibilities and tasks in your job?

[0159] Examples of questions from such a questionnaire regarding an individual's physical habits may include:

[0160] • How often do you practice physical activity?

[0161] • What type of physical activity do you do? (e.g. running, swimming, mus culture, etc.)

[0162] • How much time do you spend on physical activity each week?

[0163] • Do you have any hobbies or leisure activities that involve activity regular physical?

[0164] Examples of questions from such a questionnaire regarding an individual's diet may include:

[0165] • Briefly describe your general diet. Are you a vegetarian, vegan, or vegan, do you eat everything, etc.?

[0166] • How often do you eat home-cooked meals versus meals from the outside?

[0167] • Do you consume specific foods or food supplements for support your health and well-being?

[0168] Examples of questions from such a questionnaire regarding an individual's sleep may include:

[0169] • How many hours of sleep do you get on average each night?

[0170] • Do you have a regular sleep routine?

[0171] • Do you experience sleep problems such as insomnia or sleep disturbances? sleep ?

[0172] Examples of questions from such a questionnaire regarding an individual's stressors may include:

[0173] • Identify the main stressors in your life (work, family, finances, etc.).

[0174] • How do you manage stress on a daily basis?

[0175] • Do you have any stress management practices, such as meditation, yoga or other relaxation techniques?

[0176] The second input data d2 makes it possible to determine the mechanical loads, in particular the most severe ones, which can affect the spine of an individual, and possibly the most repetitive movements of the spine.

[0177] The second estimate E2 may include a determination of the ultimate mechanical loads supported by the vertebrae and intervertebral discs.

[0178] The second input data d2 may be collected from various sources, such as lifestyle surveys, occupational activity records, physical activity tracking devices, medical studies, existing literature searches.

[0179] The second estimation E2 may comprise a sub-step of integrating the second input data d2 into a second centralized database.

[0180] The second database is for example a relational database or another storage system suitable for organizing the second input data d2, in particular so as to be able to query them efficiently.

[0181] Optionally, the second estimate E2 can be performed using artificial intelligence AI2. This results in a second estimate with increased accuracy.

[0182] The second estimate E2 may comprise training of an artificial intelligence model.

[0183] Machine learning models may be trained from the second input data d2, notably using algorithms capable of detecting complex patterns and correlations between the data.

[0184] In the case where the first estimation and the second estimation use artificial intelligence, the processing of the first input data d1 and the second input data d2 can be carried out independently of each other.

[0185] The second estimate E2 can make it possible to determine different types of loadings or mechanical loads which will be applied in the future to the spine depending on different scenarios concerning the lifestyle of an individual.

[0186] The method comprises a calculation E3 (CALC) for a prediction of the state of the spine from the first estimate El and the second estimate E2.

[0187] The method makes it possible in particular to precisely model the evolution of the degradation of the mechanical, biochemical and geometric properties of the spinal column as a function of the age of an individual.

[0188] The E3 calculation makes it possible to obtain a prediction of the evolution of the bio-chemo-mechanical properties, in particular kinematics, hydration and pressure of the spine, the geometry of the spine and the grade in the future.

[0189] The E3 calculation makes it possible to obtain a prediction of the evolution of the level of damage to the spinal column.

[0190] The E3 calculation can take into account the mechanical, chemical and physiological behavior of tissues.

[0191] The E3 calculation makes it possible to predict the temporal evolutions of the degradation of intervertebral discs and vertebrae thanks to relationships between bio-chemo-mechanical properties (resistance, rigidity, ultimate stress-deformation, hydration, osmotic pressure) and grades.

[0192] The E3 calculation can implement a reconstruction by segmentation.

[0193] The E3 calculation can be performed on each material point of the biomodeling spinal mechanics, preferably across the entire spine.

[0194] In the E3 calculation, the degradation coefficients of each material point can be calculated.

[0195] The E3 calculation can be based on physical, mechanical, fluidic, mechanical / fluid interaction, biological / chemical interaction equations that represent the behavior of an individual's spine.

[0196] Advantageously, the E3 calculation can be multi-physical, that is to say that it takes into account different phenomena, in particular biological, mechanical, biochemical, for example osmolarity, the behavior of soft tissues, the non-homogeneous nature of the tissues, the plurality of elements which interact (fluid, matrix, fibers, microfibers).

[0197] Advantageously, the E3 calculation can be multi-scale, that is to say that it concerns dimensions ranging from millimetric dimensions to nanometric dimensions via micrometric dimensions. The E3 calculation can in particular take into account fiber networks at different scales, for example micrometric and nanometric.

[0198] The E3 calculation can be carried out from a behavior law between the deformation and the stress of the spine.

[0199] The applicant carried out tests and experiments in order to determine the constants of the behavior law and the adequate resistance of the intervertebral tissues.

[0200] Volumetric change effects can be taken into account in the E3 calculation via hydro-chemo-mechanical coupling.

[0201] The total strain gradient can be taken into account in the E3 calculation in the form of a multiplication of the mechanical strain gradient of the solid phase and the anisotropic volumetric strain gradient induced by the chemically induced fluid phase transfer.

[0202] The volumetric deformation gradient can be expressed mathematically by a non-linear function taking into account the chemical expansion at equilibrium and its temporal evolution.

[0203] The deformation energy of the extracellular matrix can depend on both a measurement of deformation, intrinsic characteristics and a damage variable to describe the failure of the extracellular matrix.

[0204] The strain energy of the collagen network can be expressed mathematically by at least one relationship between a strain measure, intrinsic characteristics, the orientation of the network constituents, their realignment and a damage variable making it possible to describe the failure of each network constituent.

[0205] The hydro-chemical strain energy of the fluid portion, resulting from the chemically induced volumetric change, can be evaluated by means of a non-linear function depending on the volumetric variation, the osmotic property, as well as the amount of damage resulting from failure events of the collagen network and the extracellular matrix.

[0206] The stress-strain response can be defined by a micromechanical approach dependent on the densities, the first derivatives of the strain energies with respect to a strain measurement, as well as the layer fractions.

[0207] The continuous variation of the layer fraction across the areas of the annulus fibrosus AF can be accounted for by a particular function depending on both the thickness and the volume change of the layers of the annulus fibrosus AF.

[0208] The stress-strain response can take into consideration the fatigue behavior by a mathematical relationship depending on both the number of cycles, the intensity of the stress, as well as the grade of the intervertebral disc 1.

[0209] Hydration level can be calculated from grayscale via spinal MRI.

[0210] Collagen level and orientation can be estimated from multiple MRI mapping and machine learning.

[0211] Cellular activity can be estimated.

[0212] The condition of the spine can include biological damage to the spine. Biological damage occurs when cells can no longer produce enough collagen because they experience a decrease in nutrient intake during a sedentary lifestyle, for example.

[0213] The condition of the spine may include mechanical damage to the spine.

[0214] The E3 calculation may include an estimation of the mechanical damage under monotonic loading and / or under cyclic loading.

[0215] The condition of the spine may include the grade of at least one intervertebral disc and / or the grade of at least one vertebra. The grade may be determined in particular according to the Pfirrmann classification and / or the Modic classification and / or according to the VBQ system.

[0216] The condition of the spine may include Pfirrmann grade.

[0217] The Pfirrmann grade allows the level of degeneration of the column to be estimated vertebral.

[0218] The Pfirrmann grade can be calculated, in particular automatically, from two parameters:

[0219] - hydration via MRI mapping with a distinction of hydrations of the nucleus pulposus NP and annulus fibrosus AF after MRI image processing;

[0220] - the disc height, that is to say the ratio between the height of the intervertebral disc and the height of the vertebra to take into account the size of the individual.

[0221] An advantage of a method of the type described above is that it is based on a multi-scale, multi-physical model of the spine, making it possible to describe the physical, biological and chemical phenomena at the heart of the matter. Such a method thus makes it possible to obtain an accurate prediction of the progression of degeneration of intervertebral discs and vertebrae, as well as changes in the shape of the spine. Such a method makes it possible to improve prevention and treatments related to spinal problems, thus opening up new perspectives in the field of spinal health.

[0222] The method may further comprise a provision E4 (SUP) of at least one message.

[0223] The at least one message may be at least one personalized recommendation, in particular intended to be transmitted to the individual.

[0224] The at least one message may be at least one directive intended to help a practitioner choose at least one treatment, for example from the group comprising drug treatments, physical or bodily treatments, surgical treatments.

[0225] The at least one message may be at least one directive for personalized surgical planning purposes.

[0226] In the provision E4 of at least one message, a report can be obtained corresponding to different mechanical load scenarios which will be applied in the future to the spine depending on the second input data d2.

[0227] The provision E4 of at least one message, in particular at least one personalized recommendation, advantageously makes it possible to offer an individual solutions and advice intended to maintain their spine in good health for as long as possible.

[0228] A method of the type described above makes it possible to assess potential risks linked in particular to the lifestyle, profession and physical habits of an individual. Such a method makes it possible in particular to identify harmful postures, excessive repetitive movements or heavy loads that could lead to spinal injuries.

[0229] Specific recommendations could be provided to an individual who spends long hours sitting in front of a computer to adopt correct posture in order to prevent possible problems with his spine.

[0230] Based on the results of the E3 calculation, at least one personalized recommendation could be provided to an individual upon providing E4, e.g., ergonomic adjustments, strengthening exercises, regular breaks to avoid mechanical overload. Tailored strategies could be recommended to maintain an individual's spinal health and prevent injuries. Personalized recommendations may include, among other things, appropriate stress and movement limits.

[0231] An E4 provision of at least one personalized recommendation would enable individuals to take proactive steps to reduce the risks of chronic spinal injuries and disorders, thereby helping to improve their well-being and quality of life.

[0232] An advantage of a method of the type described above is that it allows the condition of the spine to be predicted in the future in order to inform an individual of risks concerning his spine before he develops a pathology.

[0233] An advantage of a method of the type described above is that it allows a pathological condition of a spine to be avoided by providing recommendations to an individual.

[0234] An advantage of a method of the type described above lies in the fact that predictions can be obtained based on different scenarios. Such a method thus makes it possible to estimate the effects of different treatments, in particular medicinal and / or surgical and / or based on a change in lifestyle.

[0235] [Fig. 3] represents a system 10 for predicting the state of a spinal column of an individual according to an embodiment of the invention. A system 10 for predicting the state of a spinal column of an individual is capable of implementing a method for predicting the state of a spinal column of an individual of the type described in relation to [Fig. 1].

[0236] The system 10 may comprise hardware and / or software elements configured to implement a method of the type described above.

[0237] The system 10 may comprise at least one hardware processor 11.

[0238] The at least one hardware processor 11 may be capable of implementing:

[0239] - a first estimate El of personalized information, in particular bio chemical and / or structural, of the spine from first input data dl;

[0240] - a second estimate E2 of mechanical loads likely to be applied on the spine from second input data d2;

[0241] - an E3 calculation for a prediction of the state of the spine from the first estimate El and the second estimate E2.

[0242] The system 10 may comprise at least one storage unit.

[0243] The system 10 may comprise a first storage unit 13. The first storage unit 13 is capable of storing the first input data dl.

[0244] The system 10 may comprise a second storage unit 15. The second storage unit 15 is capable of storing the second input data d2.

[0245] The first storage unit 13 and / or the second storage unit 15 may be formed by any suitable means capable of storing data in a computer-readable manner.

[0246] The system 10 may comprise a delivery unit 17. The delivery unit 17 is capable of generating at least one message, in particular at least one personalized recommendation, from the calculation provided by the processor 11. The delivery unit 17 may provide at least one message intended to be transmitted to a health information system and / or to a practitioner, in particular a doctor, and / or directly to an individual. The at least one message may be a notification.

[0247] Although the method has been described above in the case where first input data and second input data are used, the method could be implemented using a single database. The first database and the second database could be combined.

[0248] The first estimate and the second estimate can be performed in any order or simultaneously.

Claims

Claims

1. Method for predicting the state of a spine of an individual, said method comprising: - a first estimation (El) of personalized information of the spine from first input data (dl); - a second estimation (E2) of mechanical loads likely to be applied to the spine from second input data (d2); - a calculation (E3) for a prediction of the state of the spine from the first estimation (El) and the second estimation (E2).

2. The method of claim 1, wherein the condition of the spine comprises the grade of at least one intervertebral disc and / or the grade of at least one vertebra.

3. 3. Method according to claim 1 or 2, wherein the first input data (dl) comprises: - personal information relating to the individual, for example his age and / or his height and / or his weight; and / or - imaging data obtained by at least one medical imaging technique, for example from magnetic resonance imaging (MRI), the imaging data comprising in particular the thickness (height) and / or the surface and / or the position of intervertebral discs.

4. 4. Method according to any one of claims 1 to 3, wherein the second input data (d2) comprises information on the lifestyle of the individual, for example his profession and / or his physical habits and / or his sleep and / or his diet.

5. A method according to any one of claims 1 to 4, comprising obtaining a digital twin of the spine.

6. 6. Method according to any one of claims 1 to 5, in which the first estimate (El) uses an artificial intelligence (Ail) and / or the second estimate (E2) uses an artificial intelligence (AI2).

7. 7. Method according to any one of claims 1 to 6, further comprising a provision (E4) of at least one message, in particular: - at least one personalized recommendation; and / or - at least one directive intended to help a practitioner to choose at least one treatment, for example in the group comprising drug treatments, physical or bodily treatments, treatments surgical; and / or - at least one directive for personalized surgical planning purposes.

8. 8. System (10) for predicting the state of a spine of an individual, the system comprising a first storage unit (13) capable of storing first input data (dl), a second storage unit (15) capable of storing second input data (d2) and at least one hardware processor (11) capable of implementing: - a first estimation (El) of personalized information of the spine from the first input data (dl); - a second estimation (E2) of mechanical loads likely to be applied to the spine from the second input data (d2); - a calculation (E3) for a prediction of the state of the spine from the first estimation (El) and the second estimation (E2).

9. 9. Computer program product comprising instructions which, when the program is executed by a computer, cause the latter to implement the method according to any one of claims 1 to 7

10. 1 d / .

10. Computer-readable data storage medium on which a computer program product according to claim 9 is recorded.

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