Koninklijke Philips Corporation N.v.

Elekta, Inc.

Pedro Jorge Da Silva Rodrigues

Andreia Maria Araujo Trindade Rodrigues

Alfonso Agatino Isola

Vanda Lucia De Carvalho Vittorino De Almeida

Reinhold Wimberger-Friedl

Reinhold Wimberger Friedl

Amy Perkins

Vanda Lúcia De Carvalho Vitorino De Almeida

Gereon Vogtmeier

Herfried Karl Wieczorek

Andreas Goedicke

Manoj Narayanan

Maria Luiza Bondar

Davide Fontanarosa

Andreia Maria Araujo Trinadade Rodrigues

Vanda Lucia De-Carvalho Vittorino De Almeida

Thereto a method and a system for planning radiation therapy are provided, as well as an arrangement for radiation therapy planning and a computer program product for carrying out the method. For planning the radiation therapy, the following steps are performed. Patient data of a subject to be treated is received as well as image data of the subject to be treated. The image data comprises anatomical image data of one or more organs at risk associated with the functioning of the immune system. Next, the patient 122 data and the image data are processed to obtain a risk score for the one or more organs at risk associated with the functioning of the immune system. The risk score is indicative of the risk of hematologic toxicity in the subject to be treated in response to the radiation therapy. Then the radiation therapy treatment is planned using the obtained risk score.

Planning radiation therapy using a personalized hematologic risk score

A computer-implemented method for determining tumor heterogeneity is provided. Embodiments of the method involve analyzing a radiological image of a tumor to calculate a value indicative of tumor activity at each of a plurality of locations in the tumor; determining whether each calculated value is above a predetermined threshold; and calculating a heterogeneity score for the tumor; wherein the heterogeneity score is calculated based on a volume fraction of the tumor having a value indicative of tumor activity above the predetermined threshold. Also provided are associated systems and computer program products.

Radiology-based risk assessment for biopsy-based scores

Methods and systems for calibrating radiological data associated with a tissue in a subject are provide. Various embodiments described herein analyze a radiological image of the tissue to calculate a raw value indicative of a biological parameter such as metabolic activity in the tissue, and analyze a microscopy image of the tissue to identify a distribution of cells of interest within the tissue. A calibrated value indicative of a biological parameter (e.g. metabolic activity) of cells of interest within the tissue is then calculated, by correcting the raw value based on the identified distribution of cells of interest within the tissue.

Calibrating radiological data based on cell distribution

A method () is disclosed for determining a medical imaging schedule for a subject receiving treatment at a target site. The method comprises obtaining () first blood panel information from a first blood sample acquired from the subject prior to the treatment commencing; obtaining () initial imaging data acquired in respect of the target site prior to the treatment commencing; obtaining () information regarding the treatment being received; and determining (), based on at least the first blood panel information, the initial imaging data and the treatment information, a time at which to capture first imaging data in respect of the target site in order to assess a response to the treatment. A system and a computer program product are also disclosed.

Determining a medical imaging schedule

A method of generating a strategy for performing a radiotherapy-based treatment and a system for performing the method. During a radiotherapy-based treatment, characteristics of side-effects are monitored and a risk model of the subject modified based on the characteristics. A new treatment strategy for the radiotherapy-based treatment is obtained based on the modified risk model.

Methods and apparatus for reducing risk to a subject undergoing radiotherapy-based treatment

A method includes identifying an imaging workflow process and constructing and displaying, in a graphical user interface, a graphical process tree for the imaging workflow process and a plurality of steps thereof. The method further includes identifying a standard of interest and mapping the plurality of steps into the standard of interest in the displayed graphical process tree. The method further includes receiving, via the graphical user interface, an input indicating a potential failure mode information for two or more of the steps, calculating at least one risk priority number for each step, evaluating the numeric assessment of risk based on a risk priority number threshold, and visually highlighting displayed steps corresponding to steps with risk priority numbers that exceed the risk priority number threshold. The method further includes determining a risk management plan to mitigate risk based on the highlighted steps.

Quality management of imaging workflows

The invention relates to a device () for standard uptake value, SUV, determination during an emission tomography imaging procedure of a patient. The device receives SUV-related data required for SUV determination, and event data relating to one or more events that may affect the SUV determination. The SUV-related data includes a time of administration of the radiotracer dose to the patient. The event data includes at least one of: a time at which an emission tomography imaging procedure of the patient is performed, patient motion data, patient position data, and patient vital signs data. An anomalous event determination unit () determines, based on the event data, anomalous event information indicative of one or more anomalous events that affect the SUV determination. An SUV determination unit () determines the SUV based on said SUV-related data taking into account the anomalous event information.

Determining standard uptake value (SUV) in emission tomography imaging using SUV-related data and event data

The invention relates to a system for generating a radiotherapy treatment plan () for treating a target structure within a patient body. The system comprises (i) a modeling unit configured to determine a series of estimates (--) 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 () on the basis of the series of estimates (--) of the delineation of the target structure. Further, the invention relates to method carried out in the system.

Adaptive radiation therapy planning

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 () 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 (), 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 () 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.

A multimodal imaging apparatus () including scintillator elements () for capturing incident gamma quanta () and for emitting scintillation photons () in response to said captured gamma quanta (). Photosensitive elements () capture the emitted scintillation photons () and determine a spatial distribution of the scintillation photons. The imaging apparatus () is configured to be switched between a first operation mode for detecting low energy gamma quanta and a second operation mode for detecting high energy gamma quanta. The scintillator elements are arranged to capture incident gamma quanta () from the same area of interest () in both operation modes. The scintillator elements () include a first region with high energy scintillator elements () for capturing high energy gamma quanta and a second region with low energy scintillator elements () for capturing low energy gamma quanta. A positioning mechanism () changes the orientation of the scintillator elements (), in particular for tilting the scintillator elements (), to switch between operation modes.

Multimodal imaging apparatus

The present invention relates a detector () for detecting megavoltage X-ray radiation (), comprising a scintillator () including a plurality of heavy scintillating fibers () for emitting scintillation photons in response to incident megavoltage X-ray radiation (), a support structure () for supporting said plurality of heavy scintillating fibers () and holding them in place; and a photodetector () for detecting the spatial intensity distribution of the emitted scintillation photons. The present invention further relates to an apparatus () for radiation therapy comprising a particle accelerator () and a detector () for detecting megavoltage radiation. Still further, the present invention relates to methods for detecting X-ray radiation and for radiation therapy.

Detector for radiotherapy treatment guidance and verification

A medical system () for normalization correction of an imaging system () includes a detector geometry correction unit (), a crystal efficiency unit (), and a normalization unit (). The detector geometry correction unit () mathematically calculates a detector geometry correction component for a type of scanner () of interest. The crystal efficiency unit () configured to empirically determine a crystal efficiency component for at least one individual scanner (). The normalization unit () generates a normalization data set () which corresponds to a normalization correction factor of the at least one individual scanner () in accordance with the detector geometry correction component and the crystal efficiency component.

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Veldhoven, Netherlands

Pedro Jorge Da Silva Rodrigues