42 results about "Dose optimization" patented technology

The present invention utilizes a series of optical and electronic elements to detect and image cancerous and / or pre-cancerous cells in living tissue. The invention further uses the images thus obtained to adaptively and dynamically shape a treatment light beam so as to maximize the beam's intensity in proportion to the areas with the most cancer or pre-cancer and to minimize the irradiation of normal tissue by the beam.

A novel approach to generating radiation treatment plans through a nested partitions framework provides an optimization of radiation delivery. The nested partitions approach couples beam angle selection and dose optimization to solve treatment planning problems. An optimal beam angle selection is provided to best treat tumors, while minimizing exposure to the surrounding healthy tissues.

The invention relates to an ion beam radiotherapy dosage verification method based on water equivalent coefficients. The ion beam radiotherapy dosage verification method based on the water equivalent coefficients includes the following steps that A, CT image data of a cancer patient are obtained, a treatment planning system (TPS) is utilized for plan design according to a CT-water equivalent coefficient transformation curve, and ion beam radiation parameters are recorded after the plan is determined; B, a virtual three-dimensional water phantom CT image is generated based on the water equivalent coefficients, the ion beam radiation parameters are transplanted to the water phantom through the TPS, dosage optimal computation is carried out again, and three-dimensional rasterization dose distribution in the water phantom is obtained; C, an ionization chamber is placed at an interest point in the three-dimensional water phantom, interpolating calculation is carried out in the three-dimensional rasterization dose distribution according to the three-dimensional coordinates of the sensitive volume of the ionization chamber in the water phantom, and planned dosage of the interest point is obtained; D, the ion beam radiation parameters designed as planned control a medical heavy-ion accelerator to perform simulated irradiation on the water phantom, and the measured absolute dosage value of the interest point for the ionization chamber in the water phantom is compared with the planned dosage.

A system and a method is disclosed for consistently and verifiably optimizing computed tomography (CT) radiation dose in the clinical setting. Mathematical models allow for estimation of patient size, image noise, size-specific radiation dose, and image quality targets based on digital image data and radiologists preferences. A prediction model estimates the scanner's tube current modulation and predicts image noise and size-specific radiation dose over a range of patient sizes. An optimization model calculates specific scanner settings needed to attain target image quality at the minimum radiation dose possible. An automated system processes the image and dose data according to the mathematical models and stores and displays the information, enabling verification and ongoing monitoring of consistent dose optimization.

A novel approach to generating radiation treatment plans through a nested partitions framework provides an optimization of radiation delivery. The nested partitions approach couples beam angle selection and dose optimization to solve treatment planning problems. An optimal beam angle selection is provided to best treat tumors, while minimizing exposure to the surrounding healthy tissues.

The present invention belongs to the field of improved personalized medicine. More precisely, the present invention relates to a method for progressively optimizing the 5-FU dose administered by continuous infusion in patients treated by a FOLFIRI regimen or a similar regimen, based on the 5-FU plasmatic concentration measured during the previous 5-FU continuous infusion and on a herein described decision algorithm. The present invention also relates to a method for treating a cancer patient in which the 5-FU dose administered in continuous infusion in each FOLFIRI or similar treatment cycle is optimized using the decision algorithm according to the invention.

By using the Al module, the method of the present invention calculates, i.e. predicts, the dependency Ci (pi) of a radiotherapy (RT) quality criterion C, from an adjustment of such a radiotherapy planning parameter pi. In this way, the decision making process in RT treatment plan optimization is streamlined by prediction of promising settings of one or more radiotherapy planning parameters p, before the actual time intensive iterative optimization process is carried out. This is achieved by applying an Al module, which has been trained to predict the specific behaviour of the dose optimization algorithm, i.e. the optimizer, with respect to geometric patient data, dose prescription and treatment indication data. Thus, a computer-implemented medical method of predicting a dependency Ci (pi) of a radiotherapy (RT) quality criterion Ci from an adjustment of a radiotherapy planning parameter p, is presented. The method comprises the following steps of providing geometric patient data geometrically describing an area of a patient, which is to be irradiated according to a radiotherapy treatment plan (step S1), providing dose prescription data and treatment indication data for said patient (step S2), and predicting with a trained Artificial Intelligence (Al) module the dependency Ci (pi) of the radiotherapy quality criterion Ci from the radiotherapy planning parameter p, when adjusting said radiotherapy planning parameter pi, thereby using the geometric patient data, the dose prescription data and the treatment indication data as input for the Al module (step S3).

A method for obtaining a digital chest x-ray image of a patient. The method includes providing a default set of technique settings for the chest x-ray, wherein the default set is selectable by an operator command and includes using a peak kilovoltage exposure setting that is below 90 kVp with beam filtration of the x-ray, and applying a rib contrast suppression algorithm to the digital chest x-ray image data acquired from the exposure.

The invention provides a dosage optimization method and a system. The method comprises the following steps of acquiring a first dosage volume histogram, wherein a first dosage volume histogram is a result of fluxgraph optimization; providing a second optimization model, and taking the first dosage volume histogram as an optimization target so as to optimize a parameter of a second optimization model and acquiring a second dosage volume histogram, wherein if a comparison result of the second dosage volume histogram and the first dosage volume histogram is less than a threshold, optimization is finished; otherwise, the optimization is continued.

The invention provides a method for generating control points of a dynamic wedge plate, comprising: determining a target isodose curve and a target dose; generating a one-dimensional fluence distribution according to the target isodose curve and the target dose; The dose is optimized for the one-dimensional fluence distribution, and the control points of the dynamic wedge are generated according to the optimized one-dimensional fluence distribution.

A system includes a modeler (214) that generates a model that models quality of conclusions in a radiologist's report as a function of deposited dose for a scan, and a dose optimizer (216) , creating a radiologist's report from the scan, the dose optimizer (216) determines an optimal dose value for the planned scan based on the model and one or more optimization rules (218). A method comprising: generating a model that models the quality of conclusions in a radiologist's report as a function of deposited dose of a scan, creating the radiologist's report from the scan; and, based on the model and one or Multiple optimization rules to determine optimal dose values ​​for planned scans.

A radiation therapy planning system (10) includes an isodose line unit (36), a region of interest unit (52), and an optimization unit (58). The isodose line unit (36) receives isodose lines planned for a volume of a subject. The region of interest unit (52) defines at least one isodose region of interest based on the received isodose lines. The optimization unit (58) generates an optimized radiation therapy plan based on the at least one defined isodose region of interest and at least one dose objective for the defined region of interest.