SYSTEM FOR DETERMINING TEMPERATURE AND / OR TEMPERATURE DISTRIBUTION IN AN ABLATION AREA

Description

[0001] The present disclosure relates to a method for determining a temperature and / or a temperature distribution in an ablation area. Furthermore, the disclosure relates to a system, an ablation device, and a computer program product.

[0002] Percutaneous ablative procedures target the treatment of localized tumors in solid organs of the body. During the procedure, the physician, guided by CT or ultrasound, inserts a probe through the patient's skin into the target organ (e.g., liver) and the tumor (e.g., HCC, CRM). Heat or cold is then applied to destroy the tissue. With heat application, the latest systems generate a local microwave field to heat the tissue within a radius of up to 5 cm.

[0003] In medical technology, certain applications, particularly ablation procedures, require temperature measurement at specific body sites or areas of interest. One method could involve inserting a probe into the patient and positioning it at the relevant location. However, this only allows for the determination of the temperature at a single point, not the creation of a temperature distribution or map, which is desirable for applications such as thermal tumor ablation, especially radiofrequency ablation, laser-induced thermotherapy, or cryotherapy.

[0004] In principle, the temperature can also be determined by recording an image data set with an X-ray computed tomography scanner, since the temperature is correlated with the material density, which in turn influences the X-ray absorption.

[0005] For example, an increase in temperature in living tissue leads to a reproducible decrease in density and thus in X-ray absorption. However, such temperature determination is no longer possible in the simultaneous presence of another material with a variable concentration, such as contrast agent. Temperature determination based on CT scans currently only allows for the determination of a relative temperature; in particular, determining an absolute temperature in the ablation area based on CT scans is not possible.

[0006] Even modeling based on tabulated parameters does not allow for a satisfactory temperature determination of an ablation zone. Due to the individual physiology of the patient, the extent and shape of a generated ablation zone cannot be predicted solely by mathematical models. The ablation volumes typically deviate by up to 20% (~1 cm) from ex vivo measurements, the current form of ablation modeling, and can only be assessed after completion of the procedure. Currently, the physician is virtually blind during an ongoing ablation and must rely entirely on thermal models derived from ex vivo models.

[0007] Relevant prior art publications include DE 10 2008 049604 A1 and the scientific publication "Non-invasive real-time thermometry via spectral CT physical density quantifications" by Shapira Nada V et al. (Proceedings of the Spie, Spie, US, Vol. 12304, October 18, 2022 (2022-10-18), pages 1230404-1230404, XP060166589, ISSN: 0277-786X, 001: 10.1117 / 12.2647018, ISBN: 978-1-5106-5738-0).

[0008] The purpose of the present disclosure is to specify a method for determining a temperature and / or temperature distribution in an ablation area, wherein the temperature and / or temperature distribution is based on image data, and wherein the determined temperature and / or temperature distribution is in particular an absolute temperature.

[0009] The problem is solved by the ablation arrangement according to claim 12 and the computer program product comprising program code means to cause the ablation arrangement to execute a method for determining a temperature and / or a temperature distribution in an ablation area according to claim 1.

[0010] Regardless of the grammatical gender of a particular term, persons with male, female or other gender identities are included.

[0011] The subject matter of the disclosure is a method for determining a temperature and / or a temperature distribution in an ablation area, comprising the steps: Providing a first image dataset of an object area, wherein the first image dataset comprises medical image data acquired under different spectral distributions of X-ray radiation, the object area comprising the ablation area; determining a first density, a first density distribution, a first attenuation value, a first attenuation value distribution and / or a first tissue distribution in at least one section of the object area based on the first image dataset; determining a first sensor position in the object area based on the first image dataset; providing a first temperature for the first sensor position; providing a second image dataset of the object area, wherein the second image dataset comprises medical image data acquired under different spectral distributions of X-ray radiation; determining a second sensor position in the object area based on the second image dataset.Providing a second temperature for the second sensor position, determining a second density, a second density distribution, a second attenuation value, a second attenuation value distribution and / or a second tissue distribution in an area surrounding the second sensor position based on the second image data set, in particular determining a density, an attenuation value, a density distribution and / or attenuation value distribution in the ablation area, preferably based on the second, third or further image data set, determining a temperature and / or a temperature distribution in the ablation area based on the first temperature, the first sensor position, the second temperature, the second sensor position, the first density, the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second density, the second density distribution, the second attenuation value.the second attenuation value distribution and / or the second tissue distribution, preferably the determination of the temperature and / or the temperature distribution is based on the determined density, attenuation value, attenuation value distribution and / or density distribution in the ablation area, providing the determined temperature and / or temperature distribution of the ablation area.

[0012] The method is designed to determine and / or ascertain a temperature and / or a temperature distribution. The determined temperature is a temperature within the ablation area. The temperature distribution describes the distribution of temperature within the ablation area. The temperature distribution describes an absolute temperature, for example, a temperature in degrees Celsius, Fahrenheit, or Kelvin. The method is specifically designed for calibrating a procedure or system for determining a temperature or temperature distribution. In particular, the method is designed for determining a temperature and / or temperature distribution based on a calibration. The ablation area is, in particular, a region or section of an organ, a body, a patient, and / or tissue. The ablation area is, for example, the area around an ablation probe.The ablation area describes, for example, the area to be treated by ablation, particularly with microwaves, thermal ablation, or other methods. The temperature and / or temperature distribution preferably describes the temperature within a tissue, organ, or body. The determination of the temperature and / or temperature distribution is specifically designed to determine the temperature and / or temperature distribution before, during, and / or after a thermal ablation. The method for determining the temperature and / or temperature distribution is based, in particular, on image data, especially X-ray and / or CT scans of the ablation area. The method is specifically designed and / or suitable for use and / or execution during an ablation procedure.The method makes it possible in particular to determine an absolute temperature and / or absolute temperature distribution based on the image data set, a density, tissue distribution and / or an attenuation value, for example HU value.

[0013] The first image dataset is preferably provided via an interface. The provision of the first image dataset, and specifically subsequent image datasets, can also be achieved through a data storage system, such as a PACS, an imaging modality, such as a computed tomography scanner, or a cloud service. The first image dataset comprises and / or depicts an object area. The first image dataset is acquired for a patient, with the object area depicting and / or representing a section of the patient's body. The first image dataset can also be referred to as the reference or origin image dataset. The first image dataset is acquired, for example, before the start of ablation treatment and / or the application of heat and / or cold for ablation.Preferably, the first image dataset is acquired after an ablation probe, ablation needle, or sensor device has been positioned and / or is located at a desired or planned position within the patient. The object area can be a two-dimensional or three-dimensional section. The first image dataset preferably comprises 3D or 2D images and / or image data of the object area. The object area comprises the ablation area. Specifically, the object area comprises and / or shows an organ, a tumor, or an area to be treated within the patient, in particular the area to be treated by ablation.

[0014] The first image dataset comprises and / or preferably consists of an image dataset acquired by computed tomography. The first image dataset includes medical image data, for example, 3D or 2D image data. Specifically, the medical image data includes tomographic images and / or cross-sectional images of the object area, e.g., as X-ray or CT images. The first medical image dataset is based on an acquisition of the object area with a different spectral distribution of X-ray radiation. In other words, the first image dataset is based on dual-energy, multi-energy, or spectral computed tomography of the patient and / or object area. By acquiring the object area with X-ray radiation of different spectral distributions, tissues can be differentiated and / or distinguished, particularly based on their density and / or different attenuation values.Specifically, the first image dataset is based on an X-ray image and / or computed tomography scan using a single photon counting detector. Specifically, the first image dataset includes medical image data and / or X-ray images acquired using X-rays with different spectral distributions and / or energies.

[0015] The step of determining an initial density, density distribution, attenuation value, attenuation value distribution, and / or initial tissue distribution is hereinafter referred to as the first determination step. The first determination step is preferably based on image evaluation and / or image analysis. In particular, the first determination step can be based on the application of a neural network, machine learning, and preferably a deep learning algorithm. The determination in the first determination step includes, in particular, image evaluation, for example, segmentation, clustering, and / or classification of areas and / or sections in the medical image data or the first image dataset. For example, areas are segmented and / or clustered with respect to their attenuation values, densities, and / or grayscale values. For example, areas with the same attenuation value or grayscale value are assigned a common or identical density value.The densities determined in the first step are primarily relative densities. Specifically, this first step can be performed using a provided atlas or other medical imaging data, such as MRI data, and / or image registration. For example, in the first step, an organ is segmented and / or detected, and its density or average density is known from the literature, allowing the densities determined in the first step to be calculated as absolute densities. The values ​​determined in the first step, particularly densities, attenuation values, and / or distributions, are established for at least one section of the target area. Specifically, the values ​​and / or distributions determined in the first step are established for the ablation area and / or its surroundings.Preferably, the values ​​and / or distributions determined in the first investigation step are determined and / or calculated for a first, second or further sensor position.

[0016] The first sensor position within the object area is determined and / or ascertained based on the first image data set. Specifically, the determination of the first sensor position is based on image evaluation and / or image analysis; this determination can be performed together with the initial identification step, the first identification step, and thus form a single step. The first sensor position is, in particular, a position within the image or in the coordinates of the image data. For example, the sensor position can be determined and / or ascertained relative to the ablation area. The sensor position is, in particular, the position and / or orientation of a first sensor element or sensor device. For example, the sensor device and / or sensor element is detected and / or segmented in the medical image data or the first image data set.The determination of the first sensor position can be based, for example, on image analysis algorithms, in particular the application of machine learning and / or deep learning algorithms. The sensor position can be defined as an absolute position, for example, in image or world coordinates. The sensor position can be defined and / or interpreted as a point coordinate, area, or volume.

[0017] The provision of the initial temperature can be achieved, for example, via the interface, the memory, preferably via the sensor element, the system, and / or the ablation device or the sensor assembly of the ablation device. The initial temperature is, in particular, a measured temperature, measured with a temperature sensor. For example, the ablation needle and / or ablation probe includes a sensor element for determining the initial temperature. The initial temperature is thus, in particular, an absolute temperature measured in the patient's body or in the target area. The temperature is, for example, measured and / or provided in Kelvin, Fahrenheit, or degrees Celsius.In particular, the first temperature can comprise multiple temperature values, for example, if the ablation needle and / or the sensor device includes multiple sensor elements that are spaced apart, such that different temperature values ​​are determined and provided for the different locations of the sensor elements. The provided first temperature is, in particular, a temperature measured before the start of the ablation and / or at the time of acquisition of the first image data set. In other words, the first temperature describes the temperature or the measured temperature that existed or was measured at the specific sensor position at the time of acquisition of the first image data set.

[0018] The provision of the second image dataset is preferably designed and / or performed as described for the acquisition and provision of the first image dataset. The second image dataset is also based on the acquisition of the object area using X-rays with different spectral distributions. In other words, the second image dataset constitutes a multi-energy, dual-energy, spectral computed tomography scan of the object area. Specifically, the medical image data provided in the second medical dataset is based on the use of a single-photon counting detector. The medical image data of the second image dataset is preferably acquired using the same settings and / or parameters as the medical image data of the first image dataset.In other words, the medical image data of the first and second image datasets are directly comparable, and / or changes can be detected and / or identified by comparing the image data, particularly without preprocessing and / or image adjustment. The medical image data of the second image dataset, or the second image dataset itself, was acquired at a time point after the first image dataset. Specifically, the medical image data of the second image dataset was acquired after the start of the thermal ablation or ablation treatment. This is based on the assumption that a temperature increase in the object area is to be expected with the start of the ablation treatment, and that this increase should be visible in the medical image data.

[0019] The second sensor position within the object area is determined based on the medical image data of the second image dataset. Specifically, the determination of the second sensor position is carried out in a similar and / or identical manner to the determination of the first sensor position. In other words, the first and second sensor positions are determined in the same or a comparable way, so that the determined first and second sensor positions can be used for direct comparison. The second sensor position corresponds, in particular, to the position of the sensor element(s) during the acquisition of the medical image data of the second image dataset.

[0020] The provision of the second temperature is designed in the same way as the provision of the first temperature. The second temperature is, for example, acquired and provided by the sensor elements. The second temperature is based on the measurement of the temperature at the second sensor position. The second temperature is, in particular, an absolute temperature in Kelvin, degrees Celsius, or Fahrenheit. The provided second temperature thus corresponds, in particular, to the temperature after the start of the ablation treatment.

[0021] The step of determining a second density, density distribution, attenuation value, attenuation value distribution, and / or tissue distribution is referred to below as the second determination step. The second determination step is specifically designed and / or identical to the determination of the values ​​in the first determination step. In the second determination step, the values ​​and / or distributions are determined and / or ascertained based on the second image dataset or the medical image data of the second image dataset. Specifically, the second determination step is based on image evaluation and / or image analysis. The second density, density distribution, attenuation value, attenuation value distribution, and / or tissue distribution is determined and / or ascertained for a section of the object area or for the entire object area. Specifically, the determination in the second determination step is performed for the area surrounding the second sensor position.This is based on the consideration that, in addition to the second temperature, a density, density distribution, attenuation value, attenuation value distribution, or tissue distribution are also known for the second sensor position or its surroundings. In particular, the density, density distribution, attenuation value, attenuation value distribution, and / or tissue distribution for the surroundings of the first sensor position are determined and / or ascertained in the first determination step.

[0022] Determining a temperature and / or temperature distribution in the ablation area is based on the values ​​and / or distributions obtained in the first and second measurement steps, as well as the provided first and second temperatures and sensor positions. By determining density and / or attenuation at two different time points, for which a measured temperature is provided, it is possible to convert further densities and / or attenuation values ​​into a temperature. This is based on the consideration that density and / or attenuation in medical imaging data, particularly data acquired for different spectral distributions of X-rays, correlate with temperature, especially approximately linearly, so that an extrapolated relationship between density or attenuation and temperature can be established.

[0023] The present disclosure allows the determination of an absolute temperature in an ablation area based on medical image data acquired using X-rays with different spectral distributions. Thus, it is possible to monitor the absolute temperature during an ablation process or application within the ablation area based on medical image data, thereby preventing overheating of the surrounding environment and / or a protected area, and / or ensuring that a minimum required ablation temperature is reached.

[0024] It is particularly preferred that in the second determination step, a second density distribution, as a distribution of the density, or a second attenuation value distribution, as a distribution of the attenuation value, is determined for the object area, in particular the entire object area. In other words, a density value or an attenuation value is determined for the object area, in particular for areas or spatial sections, for example, of a mesh or a point cloud. In particular, in the second determination step, a density, density distribution, attenuation value, and / or attenuation value distribution is determined in the ablation area. In other words, the second density distribution describes a spatial distribution of the density in the object area, while the attenuation value distribution describes a spatial distribution of the attenuation values ​​in the object area. In particular, it may be provided that the temperature distribution is the distribution or...The spatial distribution of temperature within the object area is determined and / or ascertained. In other words, the distributions describe a mapping of density, attenuation values, and / or temperature. Specifically, the first determination step involves ascertaining the initial density, density distribution, attenuation value, attenuation value distribution, and / or tissue distribution in a section and / or area around the first sensor position. This is based on the premise that by determining the values ​​and / or distributions in the environment around the first sensor position, the initial temperature can be assigned to a density or attenuation value.

[0025] It is particularly preferred that, based on the first and second image datasets, specifically based on the densities, attenuation values, and / or their distributions determined in the first and second analysis steps, a change in density, attenuation value, and / or tissue distribution is determined. The change in density describes, for example, the change in density, density values, and / or density distribution between or with respect to the first and second image datasets. The change in attenuation value describes the change in the attenuation value or attenuation value distribution with respect to the first and second image datasets. The change in tissue distribution describes the change in tissue distribution determined based on or in the first and second analysis steps.The temperature and / or temperature distribution within the ablation area can be determined based on the first temperature, the second temperature, and changes in density, attenuation, and / or tissue. For example, changes in attenuation can be correlated with temperature changes. The same can be assumed for density values ​​and / or tissue distribution changes to determine temperature and / or temperature changes. For example, changes in attenuation for a first sensor position and a second sensor position with spatial overlap can be correlated with the temperature change between the second and first temperatures.

[0026] It is particularly preferred that a calibration function be determined. The calibration function can be an analytical function or relation. Specifically, the calibration function can also be a non-analytical function, such as a tabular function or lookup function. The calibration function can also be a machine learning function or algorithm and / or be based on one. The calibration function is designed and / or suitable for assigning a temperature to a density, a density change, an attenuation value, and / or a change in attenuation value. The calibration function is specifically determined or defined with respect to the first and second image datasets. In other words, the calibration function is based on the first and second image datasets and the imaging modalities, parameters, and / or settings used for them.Furthermore, the calibration function can take into account anatomical and / or patient-specific characteristics, which are reflected in particular in the medical image data of the first and second image data sets.

[0027] According to an optional embodiment of the invention, the step of providing the first and / or second image data set includes artifact removal and / or the provided image data sets are based on or have been artifact-removed. The artifact removal process is designed to eliminate artifacts in the medical image data that are caused, for example, by metal objects in the object area during image acquisition. For instance, the use of metallic and / or metal-containing ablation needles and / or sensor devices can cause artifacts in the medical image data or image data sets. By applying the artifact removal process, such artifacts in the medical image data can be eliminated and / or reduced.For example, the step of providing the first and / or second image dataset includes applying an artifact correction algorithm to the images acquired using tomography and / or X-ray imaging. The artifact-corrected medical image data, or first and second image datasets, are used to determine the first and / or second density, density distribution, attenuation value, attenuation value distribution, sensor position, and / or tissue distribution.

[0028] The first temperature and / or the second temperature is provided by a sensor device. The sensor device comprises at least one first sensor element, as well as a second and / or further sensor elements. The sensor elements are configured to detect and / or determine a temperature.

[0029] The sensor elements are designed as temperature sensors.

[0030] The first and second, and especially the subsequent, sensor elements are spaced apart from each other, arranged at a fixed sensor distance and / or equidistantly. For example, the sensor elements are arranged along a common axis, which may be defined, for instance, by the longitudinal extension of the ablation needle.

[0031] Determining the first sensor position involves, in particular, determining a first sensor element position, a second sensor element position, and / or further sensor element positions. In other words, the determined first sensor position encompasses a plurality of sensor element positions. Similarly, determining the second sensor position may also involve determining a first sensor element position, a second sensor element position, and / or further sensor element positions. For example, tuples of numbers are provided as sensor positions, each representing a specific sensor element position. Furthermore, in this configuration, the provided first temperature and / or second temperature each include a first temperature value for the sensor element position, a second temperature value for the second sensor element position, and / or further temperature values ​​for additional sensor element positions.This design is based on the idea that using a sensor device with multiple sensor elements allows for the provision of multiple temperature values ​​for different sensor element positions, so that multiple measurable temperature values ​​and sensor element positions can be determined for sensor positions determined based on the first and second image data sets. This allows, in particular, for more accurate temperature determination based on medical image data.

[0032] It is particularly preferred that the sensor device is comprised of an ablation device. The ablation device comprises and / or forms, for example, an ablation needle and / or ablation probes. The sensor elements of the sensor device, which is comprised of the ablation needle, are preferably arranged along the longitudinal axis of the ablation needle. The ablation device, in particular the ablation needle, comprises an ablation section. The ablation section is preferably arranged in an end region of the ablation needle or the ablation device. The ablation section is configured to perform and / or apply thermal ablation in its surroundings. For example, a microwave generator for microwave application and / or thermal treatment of the surroundings is arranged in the ablation section. Alternatively and / or additionally, a heating element and / or a cooling element can be arranged in the ablation section.The sensor device and / or the sensor elements are arranged at a distance from the ablation section, preferably at least 1 cm, preferably at least 5 cm. This spacing between the sensor element and the ablation section allows for the use of more sensitive sensor elements and / or increases their service life.

[0033] Preferably, it is provided that third and / or further image data sets are provided and / or acquired. The provision of the third and / or further image data sets is carried out in the same manner as the provision of the first and / or second image data sets. The third and / or further image data sets comprise medical image data of the object area, which in turn were acquired and / or provided for different spectral distributions of X-ray radiation. The third and / or further image data sets are acquired, in particular, after the second image data set. For example, it may be provided that further image data sets of the object area are acquired and / or provided at regular intervals after the second image data set has been provided. The first, second, third, and / or further image data sets constitute, in particular, a time series of medical image data of the object area.This configuration further provides for the determination and / or ascertainment of a third temperature and / or temperature distribution, specifically an additional temperature and / or temperature distributions within the ablation area, particularly within the object area. In other words, a time series of temperature and / or temperature distribution within the ablation area and / or within the object area can be determined and / or ascertained. The determination of the third temperature and / or temperature distribution, in particular the additional temperatures and / or temperature distributions, is based specifically on the first temperature, the first sensor position, the second temperature, the second sensor position, and the values ​​and / or distributions determined in the first and second determination steps. Specifically, it is not necessary to determine a third temperature or a third sensor position based on the third image data set.In other words, the determination of the third and / or subsequent temperature or temperature distribution is based on the medical image data, or the third image data set, and / or without determining, measuring and / or providing a temperature or sensor position for a time point after the acquisition of the second image data set.

[0034] Furthermore, it is preferably provided that, based on the first, second, and third temperatures or temperature distributions, a planned temperature profile, also called the extrapolated temperature profile, is determined in the ablation area or in the object area. In particular, the determination of the planned temperature profile can be based on the first and second temperatures or temperature distributions as well as the third image data set and / or further image data sets. The determined planned temperature profile is then made available, for example, displayed to a user. Based on the planned temperature profile, the user can monitor the progress of the ablation application and thus receives feedback on when a desired temperature or a temperature to be avoided is reached.

[0035] It is particularly preferred that the planned temperature profile be determined based on provided tissue parameters and / or ablation operating data. In other words, the planned temperature profile can be more precisely determined, extrapolated, and / or calculated using tissue parameters and / or ablation operating data, such as the power and / or operating parameters of the ablation device.

[0036] One implementation of the procedure involves determining a planned restabilization time based on the planned temperature profile. The planned restabilization time is, in particular, the time required to reach a desired and / or necessary temperature in the ablation area. The remaining restabilization time can, for example, be displayed to the user and / or operator, allowing them to better estimate the remaining treatment time and thus avoid damage to surrounding tissue due to excessively long ablation or insufficient ablation due to an insufficient restabilization time.

[0037] Furthermore, it is preferably provided that, based on the first temperature, the second temperature, the third temperature, the first temperature distribution, the second temperature distribution, and / or the third temperature distribution, heat loss or heat loss areas are determined and / or identified. For example, due to anatomical conditions, the ablation area may not be heated or cooled uniformly, for instance, due to material transport in the tissue and / or bloodstream, so that areas of the ablation area are not heated or cooled in the same way as the rest of the area, and thus these areas may not be treated sufficiently. Based on the determined temperatures and / or temperature distributions, such heat loss areas can be identified.In particular, the specific heat loss areas are displayed and / or made available to the user, for example in the medical image data, so that the user can, if necessary, subject these areas to separate and / or additional ablation.

[0038] Another object of the invention is an ablation arrangement comprising a system for determining the temperature and / or temperature distribution in an ablation area.

[0039] The system is specifically designed and / or configured to apply and / or implement the above procedure. The system for determining a temperature and / or a temperature distribution in an ablation area comprises an image data provision module, an image data evaluation module, a sensor data provision module, a position determination module, a temperature determination module, and a provision module, wherein: The image data provisioning module is configured to provide a first image data set of an object area, wherein the first image data set comprises medical image data acquired with different spectral distributions of X-ray radiation, the object area comprising the ablation area. The image data evaluation module is configured to determine a first density, a first density distribution, a first attenuation value, a first attenuation value distribution, and / or a first tissue distribution in at least one section of the object area based on the first image data set. The position determination module is configured to determine a first sensor position in the object area based on the first image data set. The sensor data provisioning module is configured to provide a first temperature for the first sensor position. The image data provisioning module is configured to provide a second image data set of the object area.wherein the second image dataset comprises medical image data acquired with different spectral distributions of X-ray radiation, the position determination module is configured to determine a second sensor position in the object area based on the second image dataset, the sensor data provision module is configured to provide a second temperature for the second sensor position, the image data evaluation module is configured to determine a second density, a second density distribution, a second attenuation value, a second attenuation value distribution and / or a second tissue distribution in an area surrounding the second sensor position based on the second image dataset, the temperature determination module is configured to determine a temperature and / or a temperature distribution in the ablation area based on the first temperature, the first sensor position, the second temperature, the second sensor position, and the first density.The provisioning module is designed to determine the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second density, the second density distribution, the second attenuation value, the second attenuation value distribution and / or the second tissue distribution.

[0040] The ablation arrangement is designed and / or configured for the ablation of tissue and / or a tumor. The ablation arrangement includes, in particular, an ablation device, for example, an ablation probe and / or an ablation needle. The ablation arrangement, and in particular the ablation device, includes a sensor device, wherein the sensor device is designed and / or configured for measuring and / or providing the first, second, and / or temperature. The ablation arrangement, the ablation device, and / or the sensor device, in particular, includes at least one sensor element, wherein the sensor element is designed and / or configured for measuring and providing a temperature.

[0041] Another object of the invention is a computer program product, wherein the computer program is designed and / or configured to perform and / or apply the above method.

[0042] Further details regarding parts, effects, and design can be found in the accompanying figures and their descriptions. These show: Figure 1 shows an embodiment of an ablation device; Figure 2 shows an exemplary image data set; Figure 3 shows an embodiment of providing the determined temperature in the ablation area; Figure 4 shows a flowchart of an embodiment of the method for determining the temperature in the execution area.

[0043] In the Fig. 1An ablation arrangement 1 is shown as an example. The ablation arrangement 1 comprises an ablation device 2, wherein the ablation device 2 includes an ablation probe 3, also called an ablation needle. The ablation arrangement 1 includes a system 4 for determining a temperature TA and / or a temperature distribution TA (x, y, z) in an ablation area 5. The ablation device 2 is configured to drive and / or control the ablation probe 3. The ablation device 2 supplies the ablation probe 3 with current and / or controls or regulates operating parameters. The ablation probe 3 is configured to heat, cool, and / or emit microwaves for heating an ablation area 5. The heating, freezing, and / or emission of microwaves constitutes an ablation application or ablation treatment.

[0044] System 1 is connected to a computed tomography system 6. Computed tomography system 6, also called a computed tomography scanner, is designed to acquire medical image data, specifically comprising an image data set. Computed tomography system 6 is designed to acquire medical image data using X-rays with different spectral distributions, specifically dual-energy, multi-energy, and / or spectral CT images. Specifically, computed tomography system 6 includes a photon counting detector, specifically a single-photon counting detector. Computed tomography system 6 is designed to provide system 1 with a first image data set, a second image data set, and specifically a third or further image data sets 7.

[0045] To observe a spatial temperature change in a predetermined area of ​​the patient, especially in the ablation area 5, which arises during the removal of a tumor by heat, CT scans can be created both before and during the ablation treatment and provided as first, second, third and / or further image data sets 6.

[0046] It should be noted that, for the purposes of this publication, a CT system also includes a C-arm system, which can also be used to generate CT image data sets.

[0047] The Fig. 2Figure 6 shows an example of an image data set 6, e.g., a first image data set. The image data set 6 comprises a plurality of medical image data 7 of an object area 8, e.g., cross-sectional images. The image data 7 show and / or the object area 8 comprises a target area, e.g., an organ 9, which contains a tumor, wherein the tumor is to be treated by means of the ablation probe 3 in an ablation procedure. Figure 6 shows a flowchart of the method according to the invention.

[0048] The ablation probe 3 comprises an ablation section 10. The ablation section 10 is arranged in an end region of the needle- and / or rod-shaped ablation probe 3. The ablation section 10 includes a heating element, a cooling element, and / or a microwave generator for applying cold, heat, or microwaves to the ablation area 5. The ablation area 5 is a volume and / or area section surrounding the ablation section 10.

[0049] The ablation probe 3 comprises a sensor assembly, the sensor assembly comprising sensor elements 11. The sensor elements 11 are configured as temperature sensors and detect and / or measure a temperature, particularly in their environment. The sensor elements 11 are arranged along a longitudinal extent of the ablation probe 3. The ablation probe 3, in particular the ablation section 10 and / or the sensor elements 11, are visible in the image data sets 6 and the image data 7, respectively. Based on image analysis, specifically based on machine learning algorithms, the ablation probe 3, the ablation section 10, and the sensor elements 11 are detected and / or segmented in the image data 7, whereby a sensor position S(x,y,z) is determined. The sensor position S(x,y,z) comprises a first sensor element position SE1(x,y,z) and a second sensor element position SE2(x,y,z).For example, the sensor position S(x,y,z) forms a tuple S(x,y,z) = {S E1 (x,y,z), S E2 (x,y,z)}. The sensor device provides a temperature T x (t) measured at a time t at a position X, for example T E1 (t). In particular, the provided temperature can form a tuple comprising several temperatures, e.g., T(t) = { T E1 (t), T E2 (t)}.

[0050] Figure 3Figure 7 shows an example of a possible presentation of the determined temperature distribution TA (x,y,z). This presentation is, for example, on a display and / or a monitor. The section shows a portion of the ablation probe 3, in particular the ablation section 11. The section can, in particular, include and / or show a section of an image from the image data set 6. The temperature distribution TA (x,y,z) is defined as areas around the ablation section 10 that have the same temperature and / or lie within the same temperature intervals 12. The temperature distribution is preferably displayed in the image data 7 and / or superimposed with image data of the object area 8, so that a user and / or treating person receives visual feedback about the temperature in the ablation area 5 and the progress of the ablation treatment.

[0051] Figure 4shows a flowchart of an embodiment of a method for determining a temperature and / or temperature distribution in an ablation area.

[0052] In a provisioning step 100, an initial image data set 6 of an object area 8 is provided. Provisioning is carried out, for example, by a computed tomography system 6, particularly via an interface. The image data set is acquired at a first time point t1 and comprises a plurality of image data 7, for example, image data in the form of medical images and / or CT scans. The medical image data 7 consist of spectral computed tomography image data and / or multi-energy CT scans. The image data 7 show the ablation area 5 and the ablation probe 3.

[0053] In a determination step 200, a first sensor position S(x,y,z) is determined based on the first image data set 6, in particular the image data 7. The sensor position S(x,y,z) comprises and / or forms the position at which a first temperature is and / or has been determined. The sensor position S(x,y,z) is determined, for example, based on an image evaluation and / or image analysis of the image data 7, for example, by detection of the sensor elements 11 in the image data 7.

[0054] In a first investigation step 300, the image data 7 provided in step 100 are analyzed and / or evaluated. Based on the image data 7, a density distribution and / or attenuation value distribution is determined for the object areas. For example, areas with the same density and / or attenuation values ​​are identified, segmented, and / or clustered. The density can be determined based on the image data 7 because areas of the same density and / or the same tissue have the same and / or similar attenuation values. In particular, the density, density distribution, attenuation value, and / or attenuation value distribution are determined for areas around the sensor elements 11.

[0055] In provisioning step 400, a first temperature is provided. The first temperature is a temperature measured by at least one of the sensor elements 11. In particular, the first temperature is measured at time t1. In other words, the first temperature describes the temperature at the time of acquisition of the first image data set 6 at the first sensor position S(x,y,z).

[0056] In a provisioning step 500, a second image data set 6 of an object area 8 is provided. Provisioning is carried out, for example, by a computed tomography system 6, particularly via an interface. The image data set was acquired at a first time point t2 and comprises a plurality of image data 7, for example, image data in the form of medical images and / or CT scans. The medical image data 7 consist of spectral computed tomography image data and / or multi-energy CT scans. The image data 7 show the ablation area 5 and the ablation probe 3.

[0057] In a determination step 600, a second sensor position S'(x,y,z) is determined based on the second image data set 6, in particular the image data 7. The sensor position S'(x,y,z) comprises and / or forms the position at which a second temperature is and / or was determined. The sensor position S'(x,y,z) is determined, for example, based on an image evaluation and / or image analysis of the image data 7, for example, by detecting the sensor elements 11 in the image data 7.

[0058] In a second investigation step 700, the image data 7 provided in step 500 are analyzed and / or evaluated. Based on the image data 7, a density distribution and / or attenuation value distribution is determined for the object areas. In particular, the density, density distribution, attenuation value and / or attenuation value distribution are determined for areas around the sensor elements 11.

[0059] In provisioning step 800, a second temperature is provided. The second temperature is a temperature measured by at least one of the sensor elements 11. In particular, the second temperature is measured at time t2. In other words, the second temperature describes the temperature at the time of acquisition of the second image data set 6 at the second sensor position S'(x,y,z).

[0060] In determination step 900, a density, density distribution, attenuation value and / or attenuation value distribution is determined for the ablation area, whereby the determination is based on the image data of the first image data set, the second image data set and / or further provided image data sets 7 of the object area 8. The further image data sets 7 are acquired and / or provided in the same way as the first image data set 7.

[0061] In step 1000, a temperature and / or a temperature distribution TA (x,y,z) in the ablation area 5 is determined. This can be done based on a calibration function. The calibration function is, for example, based on the first temperature and the associated density, density distribution, attenuation value, and / or attenuation value distribution at sensor position S(x,y,z), as well as the second temperature and the associated density, density distribution, attenuation value, and / or attenuation value distribution determined from the second image data at the second sensor position S'(x,y,z). The calibration function is designed to assign a temperature to a density, density distribution, attenuation value, and / or attenuation value distribution. The temperature and / or temperature distribution TA (x,y,z) is obtained, for example, by applying the calibration function to the density, density distribution, attenuation value, and / or attenuation value distribution in the ablation area 5.

[0062] In deployment step 1100, the specified temperature and / or temperature distribution TA (x,y,z) in the ablation area 5 is provided, for example, visually displayed on a screen. Specifically, the temperature and / or temperature distribution TA (x,y,z) is plotted and / or displayed in the image data 7 and / or image data set. This allows a user to monitor the progress of the ablation treatment on the display.

Claims

1. Computer program product comprising program code means for causing an ablation assembly (1) according to claim 12 to perform a method for ascertaining a temperature and / or a temperature distribution (TA) in an ablation region (5), wherein the method comprises the following steps: - providing (100) a first image dataset (6) of an object region (8), wherein the first image dataset (6) comprises medical image data (7) recorded with varying spectral distribution of an X-ray, wherein the object region (8) comprises the ablation region (5), - ascertaining (200), based on the first image dataset (6), a first sensor position (S) in the object region (8), - determining (300), based on the first image dataset (6), a first density, a first density distribution, a first attenuation value, a first attenuation value distribution and / or a first tissue distribution in a region surrounding the first sensor position (S), - providing (400) a first temperature for the first sensor position (S), - providing (500) a second image dataset (6) of the object region (8), wherein the second image dataset (6) comprises medical image data (7) recorded with varying spectral distribution of an X-ray, - ascertaining (600), based on the second image dataset (6), a second sensor position (S') in the object region (8), - determining (700), based on the second image dataset (6), a second density, a second density distribution, a second attenuation value, a second attenuation value distribution and / or a second tissue distribution in a region surrounding the second sensor position (S'), - providing (700) a second temperature for the second sensor position (S'), - ascertaining (1000) a temperature and / or a temperature distribution (TA) in the ablation region (5) based on the first temperature, the first sensor position (S), the second temperature, the second sensor position (S'), the first density, the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second density, the second density distribution, the second attenuation value, the second attenuation value distribution and / or the second tissue distribution, - providing (1100) the ascertained temperature and / or temperature distribution (TA), wherein the first temperature and / or the second temperature is provided by a sensor facility, wherein the sensor facility comprises a first sensor element (11) and a second sensor element (11), wherein the first sensor element (11) and the second sensor element (11) are spaced apart at a sensor distance, wherein the first sensor position (S) comprises a first sensor element position (SE1) for the first sensor element (11) and a second sensor element position (SE2) for the second sensor element (11), wherein the first temperature and / or the second temperature comprises a first temperature value for the first sensor element (11) and a second temperature value for the second sensor element (11).

2. Computer program product according to claim 1, characterised in that in the step of determining (700) a second density distribution, a second attenuation value distribution and / or a second tissue distribution, the second density distribution, the second attenuation value distribution and / or the second tissue distribution are determined in the object region (8).

3. Computer program product according to claim 1 or 2, characterised in that in the step of determining (300) a first density, a first density distribution, a first attenuation value, a first attenuation value distribution and / or a first tissue distribution, the first density, the first density distribution, the first attenuation value, the first attenuation value distribution and / or the first tissue distribution are determined in the object region (8).

4. Computer program product according to one of the preceding claims, characterised by: - ascertaining a change in density, a change in attenuation value and / or a change in tissue distribution based on the first density, the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second attenuation value, the second attenuation value distribution and / or the second tissue distribution, wherein the temperature and / or the temperature distribution (TA) in the ablation region (5) is ascertained based on the first temperature, the second temperature, the change in density, the change in attenuation value and / or the change in tissue distribution.

5. Computer program product according to one of the preceding claims, characterised by - ascertaining a calibration function based on the first temperature, the first sensor position (S), the second temperature, the second sensor position (S'), the first density, the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second density, the second density distribution, the second attenuation value, the second attenuation value distribution and / or the second tissue distribution, wherein the calibration function assigns a temperature to a density, an attenuation value and / or a tissue.

6. Computer program product according to one of the preceding claims, characterised in that providing (100, 500) a first and / or a second image dataset (7) of an object region (8) comprises artifact correction, wherein the artifact correction corrects and / or reduces image artifacts and / or metal artifacts in the medical image data (7).

7. Computer program product according to one of the preceding claims, characterised in that the first temperature and / or the second temperature is / are provided by a sensor facility, wherein the sensor facility is comprised by an ablation apparatus (2), wherein the ablation apparatus comprises an ablation section (10) for thermal ablation.

8. Computer program product according to one of the preceding claims, characterised by: - providing a third image dataset of the object region, wherein the third image dataset (6) comprises medical image data (7) recorded with varying spectral distribution of an X-ray, - ascertaining a third temperature and / or a third temperature distribution in the ablation region (5) based on the first temperature, the first sensor position (S), the second temperature, the second sensor position (S'), the first density, the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second density, the second density distribution, the second attenuation value, the second attenuation value distribution and / or the second tissue distribution, - determining a planned temperature curve in the ablation region (5) based on the first, second and third temperature and / or temperature distribution (TA), - providing the planned temperature curve.

9. Computer program product according to claim 8, characterised in that the ablation operating data and / or the tissue parameters are provided, wherein the planned temperature curve is determined based on the ablation operating data and / or the tissue parameters.

10. Computer program product according to claim 8 or 9, characterised in that a planned residual ablation duration is determined based on the planned temperature curve, wherein the planned residual ablation duration is provided.

11. Computer program product according to one of the preceding claims, characterised in that heat loss regions in the ablation region (5) are determined based on the first temperature, the second temperature, the third temperature, the first temperature distribution, the second temperature distribution and / or the third temperature distribution, wherein the determined heat loss regions are provided.

12. Ablation assembly (1) comprising an ablation apparatus (2) and a system (1) for ascertaining a temperature and / or a temperature distribution (TA) in an ablation region (5), wherein the ablation apparatus (2) has a sensor facility for providing the first, second and / or third temperature and / or temperature distribution, wherein the system (1) comprises an image data provision module (20), an image data evaluation module (21), a sensor data provision module (22), a position ascertainment module (23), a temperature ascertainment module (24) and a provision module (25), wherein: - the image data provision module (20) is designed to provide a first image dataset (6) of an object region (8), wherein the first image dataset (6) comprises medical image data (7) recorded with varying spectral distribution of an X-ray, wherein the object region (8) comprises the ablation region (5), - the image evaluation module (21) is designed to determine, based on the first image dataset (6), a first density, a first density distribution, a first attenuation value, a first attenuation value distribution and / or a first tissue distribution in at least one section of the object region, - the position ascertainment module (23) is designed to ascertain, based on the first image dataset (6), a first sensor position (S) in the object region (8), - the sensor data provision module (22) is designed to provide (S) a first temperature for the first sensor position, - the image data provision module (20) is designed to provide a second image dataset (6) of the object region (8), wherein the second image dataset (6) comprises medical image data (7) recorded with varying spectral distribution of an X-ray, - the position ascertainment module (23) is designed to ascertain, based on the second image dataset (6), a second sensor position (S') in the object region (8), - the sensor data provision module (22) is designed to provide a second temperature for the second sensor position (S'), - the image evaluation module (21) is designed to ascertain, based on the second image dataset (6), a second density, a second density distribution, a second attenuation value, a second attenuation value distribution and / or a second tissue distribution in a region surrounding the second sensor position (S'), - the temperature ascertainment module (24) is designed to ascertain a temperature and / or a temperature distribution (TA) in the ablation region (5) based on the first temperature, the first sensor position (S), the second temperature, the second sensor position (S'), the first density, the first density distribution, the first attenuation value, the first attenuation value distribution, the first tissue distribution, the second density, the second density distribution, the second attenuation value, the second attenuation distribution value and / or the second tissue distribution, - the provision module (25) is designed to provide the ascertained temperature and / or temperature distribution (TA), - the sensor facility is designed to provide the first temperature and / or the second temperature, wherein the sensor facility comprises a first sensor element (11) and a second sensor element (11), wherein the first sensor element (11) and the second sensor element (11) are spaced apart at a sensor distance, wherein the first sensor position (S) comprises a first sensor element position (SE1) for the first sensor element (11) and a second sensor element position (SE2) for the second sensor element (11), wherein the first temperature and / or the second temperature comprises a first temperature value for the first sensor element (11) and a second temperature value for the second sensor element (11).