41 results about "Adaptive radiation therapy" patented technology

A method for delivering radiation therapy to a patient using a three-dimensional planning image for radiation therapy of the patient wherein the planning image includes a radiation therapy target includes the steps of: determining a digitally reconstructed radiograph from the planning image; identifying a region of the target's projection in the digitally reconstructed radiograph; capturing a radiographic image corresponding to the digitally reconstructed radiograph; identifying a region in the captured radiographic image; comparing the region of the target's projection in the digitally reconstructed radiograph with the identified region in the captured radiographic image; and determining a delivery of the radiation therapy in response to this comparison.

Methods and systems are disclosed for radiation treatment of a subject involving one or more fractional treatments. A fractional treatment comprises: obtaining fractional image data pertaining to a region of interest of the subject; performing a fractional optimization of a radiation treatment plan to determine optimized values of one or more radiation delivery variables based at least in part on the fractional image data; and delivering a fraction of the radiation treatment plan to the region of interest using the optimized values of the one or more radiation delivery variables as one or more corresponding parameters of the radiation treatment plan. A portion of performing the fractional optimization overlaps temporally with a portion of at least one of: obtaining the fractional image data and delivering the fraction of the radiation treatment plan.

In planning of radiation therapy treatment of at least one structure in a region of a patient body, a first treatment plan is generated on the basis of a planning image of the body region and on the basis of dose objectives. A further image of the body region of the patient body is received, and a transformation is determined for generating an adapted treatment plan from the first treatment plan and / or for generating an adapted dose distribution from the dose distribution corresponding to the first treatment plan on the basis of the further image and determines an adapted treatment plan on the basis of the transformation and / or the adapted dose distribution. The transformation on the basis of the dose objectives. In adapting the dose distribution, an efficient iterative dosimetric patient setup optimization may be employed to reduce the dose computations.

The invention discloses an offline dose verification method based on improved CBCT (cone beam computed tomography) images. The offline dose verification method includes: subjecting the CBCT images of an individual patient to scatter correction on the basis of Monte-Carlo simulation to acquire a first CBCT image; rectifying the first CBCT image with a planned CT (computed tomography) image to acquire target-region deformation field information; verifying outline information of the planned CD image according to the target-region deformation field information, transplanting the verified outline information to the CBCT images to acquire a second CBCT image; establishing HU-ED calibration curves of the CBCT images according to average HU value of a particular tissue area of the individual patient in the second CBCT image and ED value of a particular tissue area of the planned CT image; performing dose calculation and planned validation on the basis of the second CBCT image, the HU-ED calibration curves, the planned CT and standard CT-ED calibration curves. By the technical scheme, treatment time and cost of the patient can be saved, and accurate adaptive radiation therapy and individual radiation therapy are realized.

The present invention provides a method for updating and optimizing a treatment plan for radiotherapy. An initial treatment plan, calculated using a constraint-driven method, may be updated using a weighted-sum method, where Lagrange multipliers generated in the constraint method are reused as the weights for the weighted sum. This method results in acceptable updated treatment plans that are generated in a small fraction of the time taken to generate an entirely new treatment plan, reducing patient discomfort and ensuring the radiotherapy facility can treat more patients.

An adaptation radiotherapy system and device and a storage medium, including: acquiring a planning image of a target region related to first gradation treatment of a first treatment plan; acquiring afirst image of the target region related to first scanning of the target region based on first dosage level; comparing the planning image and the first image so as to generate a first comparison result; determining whether the first comparison result meets a first re-planning condition; responding to determine that the first comparison result meets the first re-planning condition, wherein one or more scanners execute the second scanning of the second dosage level so as to provide a second image; and according to the second image, generating a second treatment plan, wherein the second dosage level can be higher than the first dosage level.

The present invention provides a method for updating and optimizing a treatment plan for radiotherapy. An initial treatment plan, calculated using a constraint-driven method, may be updated using a weighted-sum method, where Lagrange multipliers generated in the constraint method are reused as the weights for the weighted sum. This method results in acceptable updated treatment plans that are generated in a small fraction of the time taken to generate an entirely new treatment plan, reducing patient discomfort and ensuring the radiotherapy facility can treat more patients.

A system and method for validating the accuracy of delineated contours in computerized imaging using statistical data for generating assessment criterion that define acceptable tolerances for delineated contours, with the statistical data being conditionally updated and / or refined between individual processes for validating delineated contours to thereby adjust the tolerances defined by the assessment criterion in the stored statistical data, such that the stored statistical data is more closely representative of a target population. The present invention may be used to facilitate, as one example, on-line adaptive radiation therapy.

Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.

The invention relates to system and a method for adapting a radiotherapy treatment plan for treating a target structure within a target region of a patient body, where a planning unit (7) adapts the treatment plan on the basis of a set of influence parameters quantifying an influence of the radiation on the target region per unity intensity emission in accordance with an anatomical configuration of the target region. In a storage (8), a plurality of sets of influence parameters is stored, each set being associated with an image of the body region representing a particular anatomical configuration of the target region and the planning unit (7) is configured to select the set of influence parameters from the stored sets on the basis of a comparison between a captured image of the body region and at least one of the images associated with the sets of influence parameters.

The present invention provides a method for delivering radiation therapy to a patient using a three-dimensional planning image for radiation therapy of the patient wherein the planning image includes a radiation therapy target includes the steps of: determining a digitally reconstructed radiograph from the planning image; identifying a region of the target's projection in the digitally reconstructed radiograph; capturing a radiographic image corresponding to the digitally reconstructed radiograph; identifying a region in the captured radiographic image; comparing the region of the target's projection in the digitally reconstructed radiograph with the identified region in the captured radiographic image; and determining a delivery of the radiation therapy in response to this comparison.

A therapy system includes a diagnostic image scanner (12) that acquires a diagnostic image of a target region to be treated. A planning processor (70) is configured to generate a patient specific adaptive radiation therapy plan based on patient specific biomarkers before and during therapy. A first set of patient specific biomarkers is determined then used for the determination of a first normal tissue complication probability (NTCP) model and a first tumor control probability (TCP) model. A radiation therapy device (40) administers a first dose of radiation to the target region with a protocol based on the first NTCP model and the first TCP model. A second set of patient specific biomarkers is determined. A relationship between the first set and second set of patient specific biomarkers is used to determine a second NTCP model and a second TCP model. The radiation therapy device (40) administers a second dose of radiation to the target region with a protocol based on the second NTCP model and second TCP model.

The application discloses a system and a method for adaptive radiation therapy. The method may include: obtaining an initial treatment plan of a region of interest, wherein the initial treatment planincludes a first initial treatment fraction and a second initial treatment fraction; causing a radiation treatment device to deliver the first initial treatment fraction; obtaining a treatment fraction based on the second initial treatment fraction and the treatment record.

In one embodiment of the invention, a computerized method for producing a treatment decision for adaptive radiation therapy (ART) is disclosed. The method comprises several steps. First, patient specific input data regarding a patient and general patient population data are input into a treatment decision engine. Next, this data is analyzed in order to adjust a set of interrelationships and thresholds to fit the ART regimen for which a decision is being processed. In a third step, the interrelationships and thresholds are applied to the data using a processing module which formulates a decision regarding the current ART regimen, and metadata regarding the medical condition of the patient. Finally, the decision and metadata are outputted such that they are accessible to a user. Using such a method, a treatment decision for ART is produced.

The present disclosure relates to systems, methods, and computer-readable storage media for segmenting a medical image. Embodiments of the present disclosure may locate and track a moving, three-dimensional (3D) target in a patient undergoing image-guided radiation therapy. For example, an adaptive filter model for a region of interest in the patient may be received, wherein the adaptive filter model is based on the target to be tracked. An image acquisition device may obtain a two-dimensional (2D) slice of a region of interest in the patient. A processor may then apply the adaptive filter model to the 2D slice, wherein the adaptive filter model includes an offset value. The processor may also determine a location of the target in the 2D slice based on the adaptive filter model. The processor may also estimate a potential location of the target based on the offset value. The processor may then repeat one or more of the above steps to track the moving target during image-guided radiation therapy of the patient.

The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical image. Embodiments of the present disclosure may locate a target in a three-dimensional (3D) volume. For example, an image acquisition device may provide a 3D medical image containing a region of interest of the target. A processor may then extract a plurality of two-dimensional (2D) slices from the 3D image. The processor may also determine a 2D patch for each 2D slice, wherein the 2D patch corresponds to an area of the 2D slice associated with the target. The processor may also convert the 2D patch to an adaptive filter model for determining a location of the region of interest.

A system and method for validating the accuracy of delineated contours in computerized imaging using statistical data for generating assessment criterion that define acceptable tolerances for delineated contours, with the statistical data being conditionally updated and / or refined between individual processes for validating delineated contours to thereby adjust the tolerances defined by the assessment criterion in the stored statistical data, such that the stored statistical data is more closely representative of a target population. The present invention may be used to facilitate, as one example, on-line adaptive radiation therapy.

In planning of radiation therapy treatment of at least one structure in a region of a patient body, a first treatment plan is generated on the basis of a planning image of the body region and on the basis of dose objectives. A further image of the body region of the patient body is received, and a transformation is determined for generating an adapted treatment plan from the first treatment plan and / or for generating an adapted dose distribution from the dose distribution corresponding to the first treatment plan on the basis of the further image and determines an adapted treatment plan on the basis of the transformation and / or the adapted dose distribution. The transformation on the basis of the dose objectives. In adapting the dose distribution, an efficient iterative dosimetric patient setup optimization may be employed to reduce the dose computations.

Systems and methods for automatically generating and optimizing radiation therapy treatment plans, and systems and methods for automatically generating and optimizing adaptive plans in an adaptive radiation therapy workflow. In one embodiment, an automatic treatment planning system includes: a user interface; and a treatment planning module configured to automatically generate S110 one or more treatment planning candidates based on a weighted combination of a first set of targets derived for clinical data of the first data source and a second set of targets derived for clinical data of a different second data source received via the user interface.

The invention relates to a system for generating a radiotherapy treatment plan (33; 34) for treating a target structure within a patient body. The system comprises (i) a modeling unit configured to determine a series of estimates (31a-d; 32a-d) of a delineation of the target structure for consecutive points of time during the radiation therapy treatment on the basis of a model quantifying changes of the delineation with time, and (ii) a planning unit configured to determine the treatment plan (33; 34) on the basis of the series of estimates (31a-d; 32a-d) of the delineation of the target structure. Further, the invention relates to method carried out in the system.

The invention relates to a system for generating a radiotherapy treatment plan (33; 34) for treating a target structure within a patient body. The system comprises (i) a modeling unit configured to determine a series of estimates (31a-d; 32a-d) of a delineation of the target structure for consecutive points of time during the radiation therapy treatment on the basis of a model quantifying changes of the delineation with time, and (ii) a planning unit configured to determine the treatment plan (33; 34) on the basis of the series of estimates (31a-d; 32a-d) of the delineation of the target structure. Further, the invention relates to method carried out in the system.

The present invention provides an optimization method and system for adaptive radiation therapy. The method includes: determining the initial anatomical structure of the patient, and determining an initial scheme suitable for initial irradiation based on the initial anatomical structure, and performing a radiotherapy according to the initial anatomical structure. The fluence map is optimized to obtain the distribution of the fluence map; before each fractional irradiation, the current anatomical structure of the patient is determined, and the fluence map is optimized according to the current anatomical structure to obtain the fluence map distribution of the current fractional irradiation; Register the fluence map distribution of the current fractional irradiation with the fluence map distribution of the reference irradiation to obtain the deformation matrix, and the reference irradiation is any irradiation before the current fractional irradiation; Correction is performed to obtain the subfield shape of the current fractional irradiation, and the subfield weight optimization algorithm is used to determine the subfield weight of the current fractional irradiation. The invention can more accurately and quickly determine the shape of subfields in fractionated radiation therapy schemes.

A resource management system for better operation of a plurality of devices. The system comprises an input interface (IN) for receiving input data including one or more characteristics of at least one work object (P1-P3) and / or including context data. The at least one work object (P1-P3) can be processed by one or more processing devices (Mij). The said processing is specified in a respective work specification (S1-S3). A predictor component (PC) of the system is configured to predict, based on the input data, a change to the work specification. The system comprises an output interface (OUT) for providing output data that represents said predicted change.

Radiation treatment methods for breast cancer following resection, both intraoperative and post operative, involve mapping preferably using an electronic x-ray source, and can include rotation of a direction source. By using a very rapid, near-instantaneous method of pathology of tissue margins following resection, the invention carries out intraoperative radiation treatment, preferably with the patient remaining anesthetized. Whether or not radiation is intraoperative, the invention preferably includes a mapping procedure using an electronic source that is progressed through the resection cavity while radiation dose is sensed at one or more points, to determine the shape of the resection cavity.

The invention relates to a precise control method of a radio-therapeutic apparatus during adaptive radiotherapy of an ocular tumor. An accelerator is gated during adaptive radiotherapy of the ocular tumor; when the position of the ocular tumor is deviated from a planned position, operation of the accelerator is stopped, and damage of radio-therapeutic rays on normal ocular cells is prevented; andwhen the position of the ocular tumor returns to the planned position, operation of the accelerator is recovered, and precise radiotherapy of the ocular tumor is realized. During radiotherapy of the ocular tumor, automatic tracking adaption of a multi-leaf collimator is realized, the multi-leaf collimator can track and adjust the position in real time according to the real-time position of the ocular tumor, and precise adaptive radiotherapy of the ocular tumor is realized. A gated therapeutic system of the ocular tumor and the automatic tracking system of the multi-leaf collimator can be designed and used for precise positioning radiotherapy of the ocular tumor, the social and economical benefit is high, complication of radiotherapy is reduced, and the life quality of patients is improved.

Systems and methods for adaptive radiation therapy planning are provided. In some aspects, provided systems and methods include generating composite images from magnetic resonance data using relaxation mapping. The method includes applying a correction to the data and generating a relaxation map therefrom. In other aspects, a method for adapting a radiation therapy plan is provided. The method involves determining an objective function based on dose gradients from an initial dose distribution, and generating an optimized plan based on updated images using aperture deformation and gradient maintenance algorithms without at-risk organ contouring. In yet other aspects, methods are provided for obtaining 4D MR imaging using temporal shuffling of data acquired during normal respiration for deformable images using a sequentially applied semi-physical model regularization method for multimodal images A method of registration, and a method for generating a 4D plan based on 4D CT or 4D MR imaging using an aperture deformation algorithm.

The invention discloses a radiotherapy system self-adaptive target area method and the radiotherapy system thereof. The radiotherapy system self-adaptive target area method includes obtaining the position change amount of the target area identification position; collecting the current time of the target area identification position the direction of movement; read the position change amount of the movement direction at the current time in the database; and control the radiation therapy device to move in the direction opposite to the movement direction at the current time. The radiotherapy system includes, for acquiring the position change amount of the target region identification position; a movement direction acquisition device for acquiring the movement direction of the target region identification position at the current time; for reading the position change of the movement direction at the current time in the database A processing device that issues an instruction to the radiation therapy device to move in a direction opposite to the current time motion direction; and a radiation therapy device that is used to move in a direction opposite to the current time motion direction according to the command issued by the processing device.

A method for performing automatic contouring in medical images. The method may include receiving an image containing a region of interest and determining a first contour of the region of interest using a boundary detector. The method may include refining the first contour based on the shape dictionary to generate a second contour of the region of interest and updating at least one of the boundary detector or the shape dictionary based on the second contour.