Patent Description:
In radiation therapy planning CT images (CT is an abbreviation for computed tomography) are used to compute and optimize dose distribution maps and radiation therapy plans. Depending on the location of a tumor, a respiratory phase correlated reconstruction may be needed if the location of the tumor is prone to motion to avoid radiation damage to healthy tissue and organs at risk.

Reference is made to <CIT>, <CIT> and <NPL>.

By using the information about the respiratory motion of the patient, a time-resolved reconstruction which is correlated to the breathing motion of the patient can be done and thereby the radiation therapy plans can be optimized for the breathing induced motion of the targeted tumor, e.g. a lung tumor.

To be able to do a high quality phase correlated reconstruction it is crucial to have a precise measurement of the breathing motion of a patient, a so-called respiratory surrogate.

Currently, the information about the breathing motion, i.e. the so-called respiratory surrogate, is gathered by an external device. Such an external device can be either an optical system that tracks the breathing motion by a camera system or a tension based system where an elastic belt is installed around the patient's thorax and which measures directly the breathing motion by a built-in tension sensor.

Respiratory information collected by a so-called "respiratory surrogate" have been used until now only in dedicated 4D (4D = <NUM> dimensional) respiratory scan modes and protocols of CT scan systems. Here, the respiratory surrogate has been used to determine the respiratory phase of a patient either during the scan in order to enable phase correlated scanning or after the scan in order to perform a phase correlated reconstruction of image data based on the scanned raw data.

In standard and non-respiratory scans and reconstructions, the respiratory surrogate is not recorded at all. The reason for this is that up to now the respiratory surrogate has been recorded by an external measurement system which is quite complicated and complex to attach to the patient.

Breathing commands are contained in almost any CT protocol. Typically, those commands are given right before or during the scan in order to give an advice to the patient how to control his breathing in order to avoid artifacts in the reconstructed images due to breathing movements. Currently, the commands are typically pre-recorded speech commands which can be recorded and stored by the clinical users of the CT scan units. Typically, every clinical imaging task, for example cardiac, dual energy, standard contrast and non-contrast exams, have their dedicated commands which are pre-recorded and stored in specific protocols by the clinical users according to their needs and clinical practice. The drawback of those pre-recorded commands is that they do not take into account the breathing properties of the current patient and that they cannot adapt to the current breathing status of the patient. For example, there is no way to detect whether the patient is following the commands or not which can in the worst case yield to non-diagnostic images and the need for a re-scan.

Hence, a problem underlying to the invention is to improve a CT scan process which is influenced by a respiratory movement of a patient.

That problem is solved by a Method for performing a CT imaging process depending on an individual respiration behaviour of a patient according to claim <NUM>, by an adaption device according to claim <NUM> and by a CT system according to claim <NUM>.

According to the Method for performing a CT imaging process depending on an individual respiration behaviour of a patient a respiratory movement of a patient is recorded by monitoring an intrinsic respiratory surrogate. An intrinsic respiratory surrogate is defined in contrast to an extrinsic surrogate as a surrogate which is not created by additional measurements, as for example using a marker or an external imaging device. The intrinsic respiratory surrogate is directly determined based on CT imaging data which are based on CT raw data which can be also used for reconstructing 4D-CT image data. 4D-CT image data comprise a sequence of subsequently recorded 3D-CT images.

According to the method according to the invention, CT raw data are acquired from an examination volume of a patient. Then, 3D-CT images of subsequent stacks of the examination volume at different z-positions are reconstructed preferably in real time and timely parallel to the acquisition of raw data in temporal increments (3D-CT image = three dimensional computer tomography image). A z-position is the value of the z-coordinate inside a CT system, wherein the z-coordinate is the coordinate value of the z-axis. The z-axis is the system axis and/or rotation axis of the rotating part of the CT system. One single stack can include a single layer, i.e. a layer with the thickness of one single voxel. One single stack can also include a plurality of layers. Since the 3D-CT images are reconstructed in real time and timely parallel in temporal increments to the acquisition of raw data, the reconstructed images are achieved as quasi fixed images, wherein subsequent images are assigned to subsequent different phases of breathing movement of the patient.

The real time reconstruction can be achieved, since the duration of a respiratory cycle is typically in the range of <NUM> to <NUM> (s is the abbreviation for seconds), which is at least an order of magnitude longer than the typical time for an acquisition and reconstruction of a minimum amount of raw data needed to reconstruct 3D-CT images, i.e. the time to acquire raw data in a range of <NUM>° plus the fan angle of the X-ray beam.

Further, an automatic segmentation, preferably an organ segmentation, is performed based on the 3D-CT images, wherein at least one portion, preferably an organ, of the examination volume is segmented.

One can also segment something other than an organ in order to calculate the respiratory surrogate. Segmentation means the generation of content-related regions by combining neighboring pixels or voxels according to a certain criterion of homogeneity. For example, different parts of a body, for example organs are demarcated from each other. Hence, the respiratory surrogate can be determined based a segmented organ. However, one could also imagine, for example, that the abdominal wall or the entire chest is segmented in order to draw conclusions about the breathing behavior of a patient. The level of detail of the reconstruction must be appropriate to the task. The reconstruction must be detailed enough that the relevant structures are still recognizable.

As mentioned-above, the segmentation is implemented as an auto-segmentation, preferably based on AI-algorithms (AI is an acronym for Artificial Intelligence). Such an auto-segmentation is described in <NPL>.

By performing a segmentation, the basis for the detection of a respiratory movement has been laid. That is because with the information about which organ is segmented and in which direction the organ moves, by comparing the temporal samples of the auto-segmentation results, respiratory parameters like moving direction of the organ, displacement and especially whether or not a complete respiratory cycle has been acquired, can be determined. The method will be more robust with larger detector z-coverage, i.e. a stack with a higher number of layers, because the larger the z-coverage of one z-stack (the z direction is the stacking direction of the z-stack) the easier will be the automatic segmentation, because a more extended image section can be used for detecting the segments.

Then the respiratory movement of the segmented portion, preferably an organ or a part of an organ, is detected and determined as the intrinsic respiratory surrogate. In detail, the segmentation enables to determine a time dependent position or extension of the segmented portion. Based on the time dependent position or extension, a breathing phase for the time interval of acquisition of raw data for each stack can be determined.

Hence, a time dependence of breathing phase and acquired raw data is achieved, which is the function of a respiratory surrogate. All these steps of a reconstruction of quasi-fixed images, the automatic segmentation and the determination of the intrinsic respiratory surrogate are performed in real time such that the result can be used for adapting the CT imaging process based on the intrinsic respiratory surrogate of the patient. For example, as an adaption, an x-ray on/off control of a respiratory correlated scan mode can be realized based on the determined intrinsic respiratory surrogate. As later described, also a phase-correlated reconstruction for generating 4D-CT images of organs that are prone to respiratory motion can be achieved in conformity with determined intrinsic respiratory surrogate. Advantageously, an extrinsic, i.e. a conventional respiratory surrogate, can be omitted, which simplifies the imaging process. In contrast to conventional methods, the method according to the invention does not need an external measurement system, but can deduce the respiratory surrogate simply from the measured CT raw data and therefore can be fully integrated into a conventional CT scan workflow. Furthermore, a function of a real-time adaption of the CT imaging is achieved which provides the advantage of a flexible and real-time reaction during an CT imaging process. For example, in case the CT imaging process is used for monitoring an X-ray therapy of a tumor, it is necessary to react in real-time when healthy tissue of the patient is inadvertently penetrated by the X-rays for preventing an unnecessary health burden for the patient.

The adaption device according to the invention comprises an acquisition unit for acquiring CT raw data from an examination volume of a patient. Further, the adaption device also includes a reconstruction unit for reconstructing 3D-CT images of subsequent stacks of the examination volume at different z-positions, preferably in real time and timely parallel to the acquisition of raw data in temporal increments. The adaption device also comprises a segmentation unit for performing an automatic segmentation of at least one portion of the examination volume, preferably an organ segmentation, based on the 3D-CT images of the subsequently reconstructed stacks. Part of the adaption device is also a surrogate determination unit for determining the respiratory movement of the segmented portion as the intrinsic respiratory surrogate. The adaption device also comprises an adaption unit for adapting the CT imaging process based on the intrinsic respiratory surrogate of the patient. The adaption unit can comprise a reconstruction unit for a reconstruction of image data in conformity with a respiratory movement of the patient. The adaption unit can also comprise a control function for controlling an x-ray source in a respiratory correlated scan mode. The adaption device shares the advantages of the method according to the invention.

The CT system according to the invention comprises a scan unit for carrying out a CT imaging from a patient and an adaption device according to the invention for adapting the CT imaging process of the scan unit to a recorded respiratory movement of the patient. The CT system shares the advantages of the method according to the invention.

The essential components of the adaption device according to the invention can for the most part be designed in the form of software components. This applies in particular to the reconstruction unit, the segmentation unit, the surrogate determination unit and the adaption unit of the adaption device but also parts of the input interfaces. In principle, however, some of these components can also be implemented in the form of software-supported hardware, for example FPGAs or the like, especially when it comes to particularly fast calculations, or be implemented using a computer processor. Likewise, the required interfaces, for example if it is only a matter of transferring data from other software components, can be designed as software interfaces. However, they can also be designed as hardware-based interfaces that are controlled by suitable software. Furthermore, some parts of the above-mentioned components may be distributed and stored in a local or regional or global network or a combination of a network and software, in particular a cloud system.

A largely software-based implementation has the advantage that CT systems that have already been used, can easily be retrofitted by a software update in order to work in the manner according to the invention. In this respect, the object is also achieved by a corresponding computer program product with a computer program that can be loaded directly into a memory device of for example a control device of a CT system, with program sections, in order to carry out all steps of the method according to the invention if the program is executed in the CT system, in particular the control device. In addition to the computer program, such a computer program product may contain additional components such as a documentation and/ or additional components, including hardware components such as Hardware keys (dongles etc.) for using the software.

For transport to the CT system and/ or for storage on or in the CT system, a computer-readable medium, for example a memory stick, a hard disk or some other transportable or permanently installed data carrier is used on which the program sections of the computer program that can be read in and executed by a computer unit of the medical imaging system are stored. The computer unit can comprise for example, one or more cooperating microprocessors or the like used for this purpose.

The dependent claims and the following description each contain particularly advantageous embodiments and developments of the invention. In particular, the claims of one claim category can also be further developed analogously to the dependent claims of another claim category. In addition, within the scope of the invention, the various features of different exemplary embodiments and claims can also be combined to form new exemplary embodiments.

In a variant of the method according to the invention
the adaption of the CT imaging process comprises an afterwards breathing phase correlated 4D-CT reconstruction of a 4D-CT image of the examination volume based on the determined intrinsic respiratory surrogate. As above-mentioned, a 4D-CT image is defined as a sequence of a plurality of 3D-CT images, for example assigned to different breathing phases. Advantageously, the information of the individual breathing behaviour of a patient can be used not only as real time information for a dynamic adaption of the scan process during the actual scan process, but also as information for the steps after having finished the scan process like the reconstruction of image data. Hence, the image quality of the 4D-CT image is improved compared to a reconstruction without a respiratory surrogate.

In a further variant of the method according to the invention, the reconstruction of the 3D-CT images of the subsequent stacks is performed non-phase correlated. Advantageously, due to the near motionlessness of the subsequent stacks during acquisition of raw data therefrom, phase related information at the stage of the acquisition of raw data is not necessary.

In a further variant of the method according to the invention, the determination of the intrinsic respiratory surrogate based on the respiratory movement of the segmented portion, preferably the segmented organ, comprises determining at least one of the following information:.

The above-mentioned information can be used for determining an intrinsic respiratory surrogate based on the segmented portion.

For realizing the real time reconstruction of fixed image data for the intrinsic respiratory surrogate, the time to determine a respiratory phase of a 3D-CT volume, which is the time for determining the intrinsic respiratory surrogate in one single stack of the examination volume, has to be smaller than a time interval of a breathing cycle. Preferably, the time to determine a respiratory phase of a 3D-CT volume is at least one magnitude, i.e. ten times smaller than the time interval of the corresponding breathing cycle. Advantageously, the reconstructed partial 3D-CT images of the subsequent stacks are reconstructed as quasi-fixed images such that an observance of the breathing movement is not required for an exact reconstruction of the subsequent stacks.

Preferably, the time to determine a respiratory phase of a 3D-CT volume is reduced by reducing the reconstruction time Trecon for reconstructing a 3D-CT image of one single stack of the examination volume. The time Tph to determine a respiratory phase of a 3D-CT volume is as follows: <MAT> wherein Trot is the rotation time of the detector and x-ray source of the CT system.

For reducing the reconstruction time Trecon the reconstruction can be implemented with a coarser pattern. For example, the matrix of reconstruction can be reduced.

Also preferred, the reduction of the reconstruction time Trecon comprises reduction measurements of switching off time consuming optimization algorithms for the reconstruction. For example, time consuming processes are iterative reconstructions or beam hardening corrections. Since the reconstruction of the images of the intrinsic breathing movement can be rough, a fine reconstruction at the first stage is not really necessary. The reduction of the reconstruction time enables to increase the phase-resolution of the reconstruction und enables to reduce artefacts caused by respiratory movement of a patient.

For achieving more precise results, after the 4D-CT reconstruction of a 4D-CT image of the examination volume, a final computation of the intrinsic respiratory surrogate can be additionally performed based on the reconstructed examination volume and the segmented portion, for example a segmented organ.

For achieving a complete set of raw data for each phase of breathing at each z-position, for every z-position, raw data of a complete breathing cycle are recorded. As mentioned-above, the knowledge of the respiratory movement of the patient for the whole breathing cycle of respiratory movement can be used for assigning raw data to the correct phase for an afterwards 4D-CT phase-correlated reconstruction.

According to the invention, during the acquisition of raw data, it is detected if the patient holds his breath properly based on the detected intrinsic respiratory surrogate, and in case the patient does not hold his breath properly,.

Advantageously, the behaviour of the patient or the control of the scan process can be adapted in real time during a scan process.

Preferably, the breathing phase correlated 4D-CT reconstruction of the examination volume is performed by sorting the 3D-CT images of the reconstructed subsequent stacks of the examination volume according to the computed intrinsic respiratory surrogate. If the resolution of the quite roughly reconstructed 3D-CT images is high enough for the present medical application, the 3D-CT images can be used as sequence of 3D-CT images, i.e. as a 4D-CT image. Advantageously, no additional reconstruction has to be carried out for achieving the breathing phase correlated 4D-CT reconstruction. Just a step of sorting the reconstructed 3D-CT images of subsequent stacks generated for determining the intrinsic respiratory surrogate has to be done such that the extent for generating the 4D-CT image can be reduced to a minimum.

Alternatively, the breathing phase correlated 4D-CT reconstruction of the examination volume is performed by using the segmentation results as 4D-CT-image results. That means that the 4D-CT image, i.e. a sequence of 3D-CT images, is generated by sorting the images of segmented portions, for example organs, according to the computed respiratory surrogate. Also for this variant, an afterwards reconstruction for the 4D-CT image can be dismissed. In other words, in this variant, the real-time auto-segmentation results can be reused in the same way as the real time 3D-CT images can be reused as final reconstructions. Also that alternative is appropriate in case the demands on resolution of the 4D-image sequence are not so high.

In a further variant, during the pre-scan phase an adaption can be realized by training the patient to breathing optimally for a given scan mode or task by taking into account the patients individual breathing behaviour for the given scan mode or task based on the determined intrinsic respiratory surrogate. Advantageously the recorded breathing behaviour of a patient can be used as feedback information for a feedback loop for training the patient for an individual scan mode or task.

Then, after completing the training phase, during the scan phase, it is determined if the patient holds his breath properly based on the intrinsic respiratory surrogate, and in case the patient does not hold his breath properly, a command is played to remind and motivate the patient to further hold the breath. Advantageously, a feedback of the behaviour of the patient can be used to try to influence the breathing behaviour of the patient in real time to save a current scan operation in case the patient does not exactly follow the breathing commands. Further, the scan process can also be dynamically reparametrized, for example by increasing the pitch based on the determined intrinsic respiratory surrogate if the patient seems to be not able to hold the breath properly. In that case, in particular if the patient does not improve his breathing behaviour, although he has been admonished to do so, the scan process can be altered such that the speed of recordation of raw data is increased such that the shortened breath-hold time of the patient can be tolerated.

In a further variant of the method according to the invention, during the scan phase, the scan process is aborted in an early stage if it is detected based on the recorded breathing behaviour derived from the intrinsic respiratory surrogate that the scan results are likely insufficient and a rescan cannot be avoided. Advantageously, scan resources and time resources can be saved if it is very likely that a current scan process would lead to a medical image with insufficient image quality.

Further, during the scan phase, it can be detected if the patient holds his breath properly based on the intrinsic respiratory surrogate. In case the patient does not hold his breath properly, the scan process can be stopped and a pause of the scan process can be carried out at a relevant z-position, where the patient is allowed to stop holding the breath. In that case, after the pause, the patient is instructed to perform breath-hold again and the scan process is continued at the z-position, where the scan process was stopped or at a position, where the patient still hold his breath properly. Advantageously, a current scan process can be saved although the patient is transiently not able to follow the breathing commands of the medical imaging system properly.

In a further variant of the method according to the invention, in the after-scan phase the individual breathing behaviour is analysed based on a recorded breathing curve derived from the intrinsic respiratory surrogate. In case it is detected that the patient did not follow the breathing commands properly during the scan phase, a re-scan is recommended if severe artifacts are expected. Advantageously, the decision if the scan has to be repeated or not can be automatically carried out based on the feedback information about the patient's breathing behaviour. In that case, a reconstruction based on deteriorated raw data can be dismissed and hence, time resources and medical examination capacities can be saved.

Furthermore, in a variant of the method according to the invention it is automatically determined based on the recorded breathing behaviour how to adapt the medical imaging process. That means that it is decided which measurement or which combination of the above-mentioned measurements for an improvement of the scan process is carried out based on the information of the intrinsic respiratory surrogate. The analysis for that decision can be implemented using classical signal processing approaches or by the means of deep learning-based algorithms. For example, the analysis of the respiratory curve can be done by some kind of artificial neural network.

The invention is explained below with reference to the figures enclosed once again. The same components are provided with identical reference numbers in the various figures. The figures are usually not to scale.

<FIG> shows a flow chart diagram <NUM>, which illustrates the Method for performing a CT imaging process depending on an individual respiration behaviour of a patient P. In step <NUM>. I, CT raw data RD are acquired from an examination volume of a patient. When a computer tomography system is in operation, an X-ray source emits X-rays in the direction of an X-ray detector, wherein the X-rays penetrate the patient and are transmitted by the X-ray detector in the form of raw data RD or measurement signals recorded. During the acquisition, the combination of X-ray source and X-ray detector moves around the z-axis of the CT system in a spiral manner (as shown in <FIG>) and acquires the raw data from all radial directions. In step <NUM>. II, subsequent stacks STi of the examination volume V, which are positioned at different z-positions are reconstructed in real time and timely parallel to the acquisition of raw data RD in temporal increments TPH. Hence, during the acquisition of raw data RD, a rough reconstruction of subsequent stacks STi of the examination volume V is performed. These stacks STi can be partial volumes of the examination volume V and may include an organ L to be examined or an additional organ, which are moved correlated to a breathing movement of the patient P. The temporal increments TPH are very small compared to a time interval of a breathing cycle Tbr of the patient P such that an image of a single stack STi can be regarded as a fixed-image and is assigned to a particular phase of the breathing movement of the patient P.

In step <NUM>. III, an automatic organ segmentation is performed based on the subsequent reconstructed stacks STi. For example, a region of an organ L is segmented, wherein the organ L is moved by the breathing movement of the patient.

Hence, in step <NUM>. IV, a respiratory movement of the segmented organ L is detected and determined as the intrinsic respiratory surrogate IRS based on the movement of the detected and segmented organ L.

In step <NUM>. V, the whole examination volume V is reconstructed, wherein a breathing phase correlated 4D-CT reconstruction 4D-CT-R of the examination volume V is performed by sorting reconstructed stacks STi of the examination volume V according to the computed respiratory surrogate IRS. That means that partial images of stacks STi belonging to the same breathing phase are combined to a final 3D-CT image and a sequence of phase-correlated 3D-CT images is achieved, which forms a 4D-CT image, i.e. a sequence of 3D-CT images.

<FIG> shows a schematic top view <NUM> on a patient P with an inner organ L moving due to a respiration movement of the patient P. In <FIG>, a liver L in the abdomen portion of the patient P is shown. The liver L is shown for two different breathing phases, once with continuous lines and once with dashed lines. It can be taken from <FIG> that the liver L moves between these two breathing phases in the moving direction D and a displacement of the liver L, represented by the displacement of the centerpoint PL is illustrated.

In <FIG>, a schematic view of a plurality of stacks STi (i = <NUM>, <NUM>, <NUM>) included by an examination volume V with an inner organ L is illustrated. Each single stack includes a part of the moving inner organ L. Since the inner organ L moves slowly, movement of the inner organ L during a short time Tph which is necessary for acquiring, reconstructing and segmenting a single stack STi can be neglected. In <FIG>, the examination volume V is divided into <NUM> stacks with assigned <NUM> fixed 3D-CT images of a partial volume of the examination volume V. Each single stack STi can be segmented by an auto-segmentation process such that the part of the inner organ L which is located in the respective stack STi is localized and detected. Based on the <NUM>3D-CT images of a partial volume for different respiratory phases, a movement and position of the inner organ L during different points of time in different time intervals Tph of a breathing cycle Tbr can be determined.

In <FIG>, a flow chart diagram <NUM> illustrating the Method for performing a CT imaging process depending on an individual respiration behaviour of a patient according to a second embodiment of the invention is shown. The steps <NUM>. I to <NUM>. V correspond to the steps <NUM>. I to <NUM>. V in <FIG> and are therefore not described again. In step <NUM>. VI, a more exact reconstruction of the 3D-CT volumes of the stacks STi of an examination volume V forming the intrinsic respiratory surrogate IRS is performed based on the knowledge of the relation between the raw data RD assigned to different stacks STi of the examination volume V and the different phases of a breathing cycle such that an enhanced intrinsic respiratory surrogate IRS-E is achieved. For example a portion or the whole 4D-CT image 4D-CT-R can be used to determine the enhanced intrinsic respiratory surrogate IRS-E. After that, in step <NUM>. VII, an enhanced 4D-CT image 4D-CT-R-E with higher image quality compared to the image sequence 4D-CT-R reconstructed in step <NUM>. V is reconstructed based on the acquired raw data RD and the enhanced intrinsic respiratory surrogate IRS-E.

In <FIG>, a flow chart diagram <NUM> illustrating the Method for performing a CT imaging process depending on an individual respiration behaviour of a patient according to the invention, is depicted.

Steps <NUM>. I to <NUM>. IV correspond to the steps <NUM>. I to <NUM>. IV and are not repeatedly described herein. In step <NUM>. V, based on the detection of the intrinsic respiratory surrogate IRS, it is determined if the patient P holds his breath properly HBP. In case the patient follows some predetermined commands correctly, which is symbolized with "y" in <FIG>, the process continues with step <NUM>. VI, wherein a breathing phase correlated 4D-CT reconstruction 4D-CT-R of the examination volume V based on the determined intrinsic respiratory surrogate IRS is performed. In case the patient P does not hold his breath properly, which is symbolized in <FIG> with "n", then in step <NUM>. VII, a command RI is played to remind and motivate the patient P to further hold the breath. Alternatively or additionally the scan process is dynamically reparametrized such that the scan process is adapted to the detected breathing movement of the patient. Hence, in the third embodiment, the intrinsic breathing surrogate IRS is additionally used for controlling a predetermined breathing behaviour of the patient P.

In <FIG>, a flow chart diagram <NUM> illustrating the Method for performing a CT imaging process depending on an individual respiration behaviour of a patient according to another embodiment of the invention is depicted. Steps <NUM>. I to <NUM>. IV correspond to the steps <NUM>. I to <NUM>. IV and are not repeatedly described herein. In step <NUM>. V, the breathing phase correlated 4D-CT reconstruction 4D-CT-R(L) of the examination volume V is performed by sorting the volumes of the segmented organ L according to the computed respiratory surrogate IRS. That means that an additional reconstruction of the 4D-CT image directly based on the acquired raw data RD is omitted. Instead, the final image sequence, i.e. the 4D-CT image, is achieved by a sorted combination of volumes, which are the segmented 3D-CT-images of the stacks STi, i.e. the segmented organ L, wherein the sortation and combination is performed based on the knowledge of the intrinsic breathing surrogate IRS.

In <FIG>, an adaption device according to an embodiment of the invention in form of a reconstruction device <NUM> is schematically illustrated. The reconstruction device <NUM> comprises an acquisition unit <NUM> for acquiring CT raw data RD from an examination volume V of a patient P. The acquired raw data RD are transmitted to a first reconstruction unit <NUM> for reconstructing subsequent stacks STi of the examination volume V at different z-positions in real time and timely parallel to the acquisition of raw data in temporal increments. The reconstructed rough image data of the subsequent stacks STi are transmitted to a segmentation unit <NUM> for performing an automatic organ segmentation based on the reconstructed rough image data of the subsequent reconstructed stacks STi. Then data of the segmented organ L are transmitted to a surrogate determination unit <NUM>, which is arranged to determine the respiratory movement of the segmented organ L as the intrinsic respiratory surrogate IRS. After completion of the acquisition, the completed intrinsic respiratory surrogate IRS is transmitted to an adaption unit which is implemented in this embodiment as a second reconstruction unit <NUM>. The second reconstruction unit <NUM> is arranged to reconstruct a sequence of so-called 4D-CT image data 4D-CT-R in conformity with the determined intrinsic respiratory surrogate ISR.

<FIG> shows a schematic representation of a computer tomography system <NUM> comprising a reconstruction device <NUM> according to an embodiment of the invention as discussed in detail in context with <FIG>. The arrangement comprises a gantry also called as scan unit <NUM> with a stationary part <NUM>, also referred to as a gantry frame, and with a part <NUM> which can be rotated about a system axis, also referred to as a rotor or drum. The rotating part <NUM> has an imaging system (X-ray system) which comprises an X-ray source <NUM> and an X-ray detector <NUM> which are arranged on the rotating part <NUM> opposite one another. When the computer tomography system <NUM> is in operation, the X-ray source <NUM> emits X-rays <NUM> in the direction of the X-ray detector <NUM>, penetrates a measurement object P, for example a patient P, and the result is transmitted by the X-ray detector <NUM> in the form of measurement data or measurement signals recorded.

In <FIG>, a patient table <NUM> for positioning the patient P can also be seen. The patient table <NUM> comprises a bed base <NUM>, on which a patient support plate <NUM>, which is provided for actually positioning the patient P, is arranged. The patient support plate <NUM> can be adjusted relative to the bed base <NUM> in the direction of the system axis z, i.e. in the z direction, so that it enters an opening <NUM> such that the patient P can be introduced into the opening <NUM> of the scan unit <NUM> for recording X-ray projections from the patient P. A computational processing of the X-ray projections recorded with the imaging system or the reconstruction of sectional images, 3D images or a 3D data set based on the measurement data or measurement signals of the X-ray projections is carried out in an image computer <NUM> of the computed tomography device <NUM>, wherein the sectional images or 3D images can be displayed on a display device <NUM>. The image computer <NUM> can also be designed as a control unit for controlling an imaging process for controlling the scan unit <NUM> and in particular the imaging system of the scan unit <NUM>. The image computer <NUM> also comprises the reconstruction device <NUM> as it is described in context with <FIG>.

Claim 1:
Method for performing a CT imaging process depending on an individual respiration behaviour of a patient (P), comprising the steps of:
- recording a respiratory movement of a patient (P) by monitoring an intrinsic respiratory surrogate (IRS), wherein
- CT raw data (RD) are acquired from an examination volume (V) of the patient (P),
- 3D-CT images of subsequent stacks (STi) of the examination volume (V) are reconstructed at different z-positions,
- an automatic segmentation is performed based on the reconstructed 3D-CT images of the subsequent stacks (STi), wherein at least one portion of the examination volume (V) is segmented,
- a respiratory movement (RM) of the at least one segmented portion is detected and determined as the intrinsic respiratory surrogate (IRS),
- adapting the CT imaging process based on the intrinsic respiratory surrogate (IRS) of the patient (P),
- characterised in that during the acquisition of raw data, it is detected if the patient holds his breath properly based on the detected intrinsic respiratory surrogate, and in case the patient does not hold his breath properly,
- a command is played to remind and motivate the patient to further hold the breath, and/or
- the scan process is dynamically reparametrized.