288 results about "Therapy planning" patented technology

The invention discloses an ultra-high dose rate radiotherapy plan optimization system based on compensator modulation, and relates to the technical field of radiotherapy. A data acquisition module is used for acquiring medical image data of a patient and receiving a clinical target; the clinical target comprises a target region prescription dose, an organ-endangering limit and a minimum dose rate threshold value required for triggering and maintaining a FLASH effect; and the FLASH biological effect evaluation module is used for calculating FLASH biological effective dose distribution corresponding to the physical dose distribution through an embedded biological effect model based on the input physical dose distribution and dose rate distribution. According to the method, the physical dose is converted into the accurate FLASH biological effective dose through the improved linear quadratic model embedded with the FLASH correction factor, the target tumor killing effect is guaranteed, normal tissue protection is enhanced with the help of the tissue differentiation correction factor, the industrial pain point that the physical dose reaches the standard but the biological effect does not reach the expectation is effectively solved, and the application prospect is wide. And the treatment plan better meets the clinical curative effect and safety core requirements.

A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

The invention relates to the field of radiotherapy plan design, and discloses a radiotherapy parameter intelligent recommendation system based on disease species, target area volume and dose characteristics, and the system comprises the steps: constructing a response surface model of machine physical parameters and plan quality indexes, generating a Pareto optimal solution set through a non-dominated sorting genetic algorithm, and building an optimization rule base; extracting anatomical and geometric features of historical cases, and training a CART decision tree to establish a mapping relation between the features and clinical scenes; analyzing to-be-planned case features, matching a target scene through the decision tree, and retrieving an optimal machine physical parameter combination in the rule base according to the user preference weight. According to the method, the width, the screw pitch and the modulation factor of the collimator can be automatically recommended, the problem that manual trial and error efficiency is low and depends on experience is solved, and balance between treatment plan quality and machine execution efficiency is achieved.

Systems and methods are provided for modeling and for providing a graphical representation of tissue heating and electric field distributions for medical treatment devices that apply electrical treatment energy through one or a plurality of electrodes. In embodiments, methods comprise: providing one or more parameters of a treatment protocol for delivering one or more electrical pulses to tissue through a plurality of electrodes; modeling electric and heat distribution in the tissue based on the parameters; and displaying a graphical representation of the modeled electric and heat distribution. In another embodiment, a treatment planning module is adapted to generate an estimated target ablation zone based on a combination of one or more parameters for an irreversible electroporation protocol and one or more tissue-specific conductivity parameters.

A computer-implemented system includes one or more processing devices configured to receive comorbidity information that includes a plurality of comorbidities or comorbidity-related conditions associated with a user, generate a selected set of the comorbidity information, determine, based on the selected set of the comorbidity information, respective probabilities of a plurality of different outcomes related to the comorbidity information, and generate, based on the respective probabilities and the selected set of the comorbidity information, a treatment plan comprising one or more exercises directed to changing the respective probabilities. A treatment apparatus is configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

A method for diagnosing and recommending treatment to a patient that may or may not present with occlusal disease includes acquiring 3D scans of the patient's maxillary and mandibular arches, and acquiring occlusal assessment data of the patient's teeth and dental arches. The method also includes automatically generating a treatment plan recommendation, and a recommended treatment plan projection and a non-treatment projection based, at least in part, on the acquired 3D scans of the patient's maxillary and mandibular arches, and the acquired occlusal assessment data of the patient's teeth and dental arches. The method also includes automatically displaying a rendering of the patient's simulated dental arch N years in the future based on the automatically generated recommended treatment plan projection, and a rendering of the patient's simulated dental arch N years in the future based on the automatically generated non-treatment projection, where N is greater than 1.

A system for real-time generation of therapeutic plans based on predictive analytics of patient profile data including a processor of a therapeutic plan server (TPS) node configured to host a machine learning (ML) module and connected to at least one patient-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: receive the patient profile data including patient nutrients intake data and medications intake data from the at least one patient-entity node; parse the patient profile data to derive a plurality of key classifying features; query a local database to retrieve local historical patients-related data based on the plurality of key classifying features; generate at least one classifier feature vector based on the plurality of key classifying features and the local historical patients-related data; provide the at least one feature vector to the ML module coupled to an Artificial Neural Network (ANN); receive a plurality of nutrients-medications correlation parameters from a therapeutic plan predictive model generated by the ML module using outputs of the ANN based on the at least one feature vector; and generate a therapeutic plan for the at least one patient-entity node based on the nutrients-medications correlation parameters.

Systems, methods, and computer-readable media for and improvement rehabilitation infrastructure. The method includes receiving data associated with a user that uses a electromechanical machine to perform a treatment plan. The method also includes generating, using an artificial intelligence engine, a unique data signature associated with a regression of the user's condition. The unique data signal is generated when an indicator in the data satisfies a threshold indicator level. The method further includes generating, using the artificial engine and based on the unique data signature associated with the regression of the user's condition, a modified treatment plan that modifies a parameters or activity associated with at least one of the pain measurement, the measurement of revolutions per minute, and the session pedaling time. The method also includes controlling, while the user uses the electromechanical machine and using the modified treatment plan, the electromechanical machine.

Methods of representing user edits or modifications of a treatment plan for a dental apparatus (e.g., one or a series of aligners) by managing an original clinical data set and a set of modifications of the clinical data set. Also described herein are methods of displaying, condensing, storing and reconstructing collision regions between two or more teeth.

A method provides a palatal expansion management tool. The method includes receiving scan data of a craniofacial structure of a patient, providing the scan data as input to an artificial intelligence (AI) model trained to provide a recommended palatal expansion treatment plan for the patient; receiving, as output from the AI model, the recommended palatal expansion treatment plan; and providing, to a user device, the recommended palatal expansion treatment plan.

One or more embodiments described herein relate to predicting, using adaptive artificial intelligence techniques, typical and aberrant physiological reactions of a patient to psychiatric counseling. Treatment plans can be determined and calculated based on previously-gathered demographic and / or biometric data, and / or modifications to treatment plans can be determined and / or implemented based on emergent recognition of reaction types, such as reclassifying reactions that would previously have been deemed typical as aberrant (or vice versa).

The application discloses a multi-leaf collimator motion control method, computer equipment and a storage medium. The multi-leaf collimator motion control method comprises the following steps: acquiring field shape data corresponding to a plurality of fields in a target treatment plan; determining the motion range of a multi-leaf collimator blade box corresponding to the plurality of fields according to the field shape data; and determining the motion value of the multi-leaf collimator blade box corresponding to the target treatment plan according to the motion range of the multi-leaf collimator blade box corresponding to the plurality of fields, so that the motion frequency of the multi-leaf collimator blade box is not greater than the number of fields during the execution of the target treatment plan. The motion value of the multi-leaf collimator blade box is determined in advance before the execution of the target treatment plan, so that the motion frequency of the multi-leaf collimator blade box during the execution of the target treatment plan is reduced as much as possible, the field forming speed of the multi-leaf collimator is improved, the field forming noise is reduced, and the service life of the multi-leaf collimator blade is prolonged.

The application relates to the technical field of image lesion recognition, and discloses a high-intensity focused ultrasound treatment plan generation method based on a three-dimensional lesion mask, which comprises the following steps: obtaining a three-dimensional image and a lesion mask and converting a coordinate system, identifying a treatment area to determine a Y-axis range, generating a treatment layer according to an interlayer spacing and a boundary mode, splitting a processing unit and generating a treatment line and a treatment point, filling a blind area through a point supplementing algorithm after grouping, and finally outputting a structured plan. The method realizes three-dimensional accurate coverage through hierarchical planning, various boundary modes are flexibly adapted to different lesion boundaries, the point supplementing algorithm solves the coverage blind area for special lesions, and the ablation coverage rate and the treatment plan integrity are significantly improved.

Techniques and systems for using spectroscopy, and / or image-based sensing with an intravascular blood pump are provided. The techniques generally include capturing a spectral response to light of a measured tissue and / or blood. Based on the specific needs, the method may include, e.g., determining a type of the measured tissue based on the spectral response, determining if the type of the measured tissue matches a target tissue type, determining a health of the measured tissue based on the spectral response, determining a treatment plan based on the health of the measured tissue, determining a type and / or quantity of components and / or characteristics in the blood, and / or determining a degree of heart recovery based on the type and / or quantity of the components and / or characteristics in the blood.

To provide a treatment planning system for boron neutron capture therapy.SOLUTION: A treatment planning system for BNCT comprises storage means which stores an ideal patient position that is considered to be a position determined for each patient with respect to a neutron beam irradiation port of a neutron beam irradiation device and an ideal position for a neutron beam treatment for the patient, an estimated gradually-reduced boron concentration value that is estimated from the in-blood boron concentration measurement value right before assumed multiple times of irradiation, and an assumed boron concentration application dose that is calculated by calculation means that calculates the application dose based on each estimated gradually-reduced boron concentration value. The treatment planning system for BNCT selects the estimated gradually-reduced boron concentration value closest to the measurement value upon receiving the in-blood boron concentration measurement value right before irradiation, and transmits the assumed boron concentration application dose based on the boron concentration value to a BNCT system.SELECTED DRAWING: Figure 20

The present disclosure relates to devices, systems, and techniques for determining the efficacy of a treatment plan. For example, a medical device system includes a medical device including one or more sensors configured to generate signals indicative of a parameter of a patient. Additionally, the medical device system includes processing circuitry configured to receive data indicative of a user’s selection of a reference time; determine a plurality of parameter values of the parameter based on a portion of the signals corresponding to a period of time including the reference time. Additionally, the processing circuitry is configured to identify a reference parameter value based on a first set of parameter values; calculate a parameter change value; and determine whether the patient has experienced an improvement or a worsening in response to a treatment administered beginning at the reference time based on the parameter change value.

A multi-layer orthodontic appliance has an extra soft or rubbery first layer for contacting the patient's teeth. The first layer is supported by a harder second sheet. The second harder sheet provides a repositioning force to move the patient's teeth according to a treatment plan. The extra soft first layer grips the teeth, and in preferred embodiments, is characterized by a contact angle sufficient to create a non-adhesive hydrophobic bond with the teeth. The appliance is operable to grip and move the patient's teeth according to a treatment plan without the need of attachments, or in the alternative, significantly reduces their prominences or the number of attachments required to treat a case, and without permitting water into the interface between the appliance and the teeth.

The disclosure provides gait modification or treatment apparatus, systems and methods that are appropriate for everyday life, have a significant mechanical effect, and provide a mechanism for tracking the compliance and performance of the patient to allow for individualized management of a gait modification prescription or treatment plan or sequence. Gait modification / treatment apparatus, systems and methods utilizing substantially rectilinear projections in the hindfoot and the forefoot are disclosed. Gait modification / treatment apparatus, systems and methods utilizing a projection that defines an engagement surface extending from the hindfoot to the forefoot are also disclosed. Gait modification / treatment apparatus, systems and methods utilizing a non-linear guide rail extending from the hindfoot to the forefoot are also disclosed. Further, gait modification / treatment apparatus, systems and methods utilizing an array of discrete pegs of differing stiffness / compression that provide load instability at least in the hindfoot and the forefoot are disclosed.

The invention relates to a plurality of plan evaluation functions in radiotherapy plan search and selection. A radiotherapy treatment plan generation apparatus for searching and selecting a radiotherapy treatment plan by an iterative process is provided. One or more first radiotherapy treatment plans (312) are received. In a first iteration: receiving one or more first plan evaluation functions (324); calculating a first cost (336) associated with each first radiotherapy treatment plan (312) using each first plan evaluation function (312); a first visual arrangement (335) is constructed that depicts the identity of each first radiotherapy treatment plan (312), the identity of each first plan evaluation function (324), and the first cost (336), and the first visual arrangement (335) is displayed. Subsequent similar iterations are performed until a plan is selected.

A computer-implemented system includes one or more processing devices configured to receive user information associated with a user, generate a selected set of the user information, determine, based on the selected set of the user information, at least one of a first probability of surviving one or more procedures and a second probability indicating an improvement, resulting from the one or more procedures, in quality-of-life metrics for the user, generate, based on the at least one of the first probability and the second probability and on the selected set of the user information, one or more recommendations of whether the user should undergo the one or more procedures, and generate, based on the one or more recommendations, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability.

The invention discloses a proton treatment plan verification and optimization device and method and related equipment, and relates to the technical field of radiotherapy. The device comprises an image acquisition module which is used for acquiring a PET image of a patient after completing at least one proton treatment irradiation; the dose prediction module is used for mapping the treated PET image into actual deposited dose distribution in the body of the patient based on the trained generative model so as to predict actual distribution dose distribution; and the adjustment and optimization module is used for generating an adjusted fractional treatment plan when the deviation between the predicted actual distribution dose distribution and the initial planned dose distribution is greater than a deviation threshold value. Based on in-vivo measurement information, the actual deposition dose is accurately verified and dynamically optimized, and accurate and safe proton therapy is achieved.

Methods and systems for positioning and positioning a patient for irradiation therapy without fiducial markers. Platform settings including parameters of the patient support platform are obtained. Platform position data is obtained in which a patient is placed on a platform for imaging without fiducial markers, the platform position data including 3D coordinates of the platform relative to an imager coordinate system calibrated to a predefined fixed set of initialized coordinates in a treatment room. Target tissue is imaged with the patient on the platform. A treatment plan is generated based on the target tissue imaging. The treatment plan comprises a treatment radiation field of a treatment angle, and the treatment angle comprises a platform positioning parameter. When treatment is initiated, the patient is placed on the platform without fiducial markers according to the platform settings. In accordance with the treatment plan, the platform position data, and a coordinate system transformation of the imager coordinate system to the treatment room coordinate system, the platform is adjusted to position the patient at the placement position in the treatment room such that the target tissue is positioned at the isocenter of the treatment room.

In one embodiment, a computer-implemented system includes an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan. The treatment plan includes a high-intensity interval training (HIIT) session. A processing device is configured to initiate, using the electromechanical machine, the HIIT session, receive, via one or more sensors, one or more measurements pertaining to the electromechanical machine, determine whether the one or more measurements exceed one or more of one or more corresponding thresholds, and in response to determining that the one or more measurements exceed one or more of the one or more corresponding thresholds, modify the treatment plan to cause operation of the electromechanical machine to be modified.

A method for simulating the transport of charged particles in an external magnetic field B is provided, in which the unit direction vector of the charged particle, according to Newton's second law u′(t) = F(u(t), η(t)), includes a force term F, which depends on the unit direction vector u(t) and further nonlinearly depends on the particle's motion variable η(t). According to this method, Newton's second law is solved using an implicit finite difference method, where, over the duration of a time step, the force term is approximated by interpolated values ​​of the unit direction vector and the motion variable, where the interpolation of each quantity is a combination of the values ​​of that quantity at the endpoints t and t+Δt of the time step. This method can be used to calculate the dose when a radiation delivery system 300 delivers a treatment plan P to a patient 310.

Disclosed is a treatment planning apparatus for radiotherapy, the apparatus comprising: a processing circuit; a network interface; and a non-transitory computer readable medium storing instructions that, when executed by the processing circuitry, cause the processing circuitry to: in a first mode of operation, receive input data including imaging data and one or more medical targets, and perform an optimization procedure using the input data to generate a treatment plan; and in a second mode of operation, outputting data including the imaging data and the one or more medical targets to an external treatment plan server via the network interface, and receiving a treatment plan from the external treatment plan server via the network interface.

A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a cardiovascular health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the cardiovascular health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. Wherein a machine learning model is used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

The invention provides a BNCT treatment dose accelerated calculation method, a terminal and a treatment planning system. The method comprises the steps of equally dividing each voxel block into a first voxel block and a second voxel block based on a three-dimensional coordinate of each voxel block in a voxel model; alternately iteratively executing the parallel computing process of the first voxel block and the parallel computing process of the second voxel block on the basis of a pre-constructed computing dependency relationship, and obtaining the neutron ejection flow and the neutron flux of each voxel block until an iteration stop condition is met; wherein the dependency calculation relation includes that parallel calculation of the first voxel block depends on neutron outgoing flow of the second voxel block, and parallel calculation of the second voxel block depends on neutron outgoing flow of the first voxel block; and calculating the BNCT therapeutic dose based on the neutron flux of each voxel block. According to the method, on the premise of strictly guaranteeing the calculation precision, a large-scale parallel calculation task set can be formed, the iteration convergence period and the overall calculation time consumption are reduced to the maximum extent, and the requirement for clinically and rapidly calculating the BNCT treatment dose is met.

Disclosed is a computer-implemented method for determining a treatment plan for a radiotherapy treatment including a dose distribution, the method comprising the steps of (a) determining a plurality of clinical goals, the plurality of clinical goals associated with a dose distribution, (b) determining, based at least in part on a user input, a priority for each of the clinical goals, (c) automatically determining a subset and order of scripts among a plurality of scripts, based on the plurality of clinical goals and their respective priority, each script configured to, when executed, adapt one or more optimization objectives and / or adapt weightings for optimization and / or provide and / or adapt an optimization structure, (d) generating a dose distribution, wherein the generating of the dose distribution comprises executing the subset of scripts in the determined order, wherein executing the subset of scripts comprises, for each of the scripts, obtaining at least one of an optimization structure, optimization objectives, and weightings for optimization,