TISSUE IDENTIFICATION DEVICE

Description

[0001] The invention relates to an integrated therapy and diagnostic system (theragnostics system) for treatment (therapy) and tissue identification (diagnostics). In particular, the invention relates to a theragnostics system for detecting tissue characteristics, especially benignity or malignancy, during a surgical procedure. Furthermore, the invention relates to a method for evaluating data before, during, and / or after the operation to obtain information about the treated tissue.

[0002] From EP 2 659 846 B1, a device is known that includes a surgical instrument with an electrode connected to a generator which supplies the electrode with high-frequency alternating current. A spark is maintained between the electrode and biological tissue, from which light is emitted. This light is captured by a light-receiving device and fed to an analysis device that performs a spectral analysis. From the generated spectrum, targeted analysis, optionally including pattern recognition and comparison with light characteristics stored in a database, can determine whether the tissue is benign or malignant. This information can be displayed to the surgeon.

[0003] Furthermore, US patent 2007 / 0213704 A1 discloses a medical instrument for the cold ablation of tissue using very short high-frequency sparks. The light emitted by the sparks is fed to a spectral analyzer to generate control signals based on the recorded spectra and to enable tissue differentiation.

[0004] WO 2011 / 055369 A2 discloses a catheter for plaque removal from blood vessels. The spark used to remove the plaques generates light, which is transmitted via an optical fiber to a sensor. This sensor detects the phosphor line to distinguish plaques from living cells.

[0005] EP 3 319 313 A1 describes a network designed to aggregate data from multiple points. This data includes camera images and other sensor data, as well as information about the circumstances of a medical treatment.

[0006] Further prior art is described in DE 103 92 791 T5, DE 198 60 689 C2, US 2009 / 0326383 A1, DE 42 31 677 A1, WO 02 / 19243 A2, US 6 026 323, WO 03 / 020119 A2, EP 0 650 694 A1, DE 10 2020 105 853 A1, US 2019 / 0223728 A1, EP 2 491 882 A2 and BASTIAN HILLEBRAND ET AL: "Tissue differentiation using optical emission spectroscopy for gastric mucosal devitalisation", JOURNAL OF PHYSICS D: APPLIED PHYSICS, INSTITUTE OF PHYSICS PUBLISHING, BRISTOL, GB, Vol. 54, No. 26, (2021-04-23).

[0007] In the practical implementation of tissue detection by evaluating the light emitted by a spark, uncertainties arise that make reliable tissue detection difficult.

[0008] The object of the invention is to improve automatic tissue recognition during and during surgical intervention on biological tissue.

[0009] This task is solved by the device according to claim 1:

[0010] The device according to the invention comprises a surgical station and a storage and processing unit for processing data acquired in the surgical station. The storage and processing unit can be part of the surgical station or a separate device located remotely from the surgical station, which is connected to the surgical station via a transmission network. In particular, the device can also comprise several surgical stations which are connected or connectable to the common storage and processing unit by means of a data transmission device, for example, a network.

[0011] The surgical station includes at least one electrosurgical instrument suitable for surgically acting on biological tissue. The instrument has at least one electrode. The surgical station also includes at least one generator for supplying the instrument, particularly its electrode, with an electric current suitable for producing the surgical effect, typically a high-frequency current with a frequency above 100 kHz, preferably 300 kHz or higher. The voltage supplied by the generator and applied to the instrument's electrode is typically in the range of above 100 volts up to several thousand volts and, like the current, is correspondingly high-frequency. The high-frequency voltage can be subject to selectable modulation to achieve various surgical effects. Furthermore, various other parameters, such as power, maximum current, modulation, and the like, can be adjusted.Such presets of the generator for producing different surgical effects are called "modes".

[0012] The surgical station also includes a detection device designed to record the light emitted by the spark generated between the electrode and the tissue. This light is fed to a light analysis device, also part of the surgical station, which is designed to detect at least one optical characteristic of the recorded light. The optical characteristic can be, in particular, a spectral characteristic, such as a characteristic spectrum, a characteristic sub-spectrum, individual wavelengths of the characteristic spectrum, or one or more quantities derived from the spectrum. Furthermore, the surgical station includes a detection device for obtaining an electrical characteristic.The electrical characteristic may be the magnitude of the current, the fluctuation of the current, the voltage applied to the electrode, the fluctuation of the voltage, the modulation of the current and / or voltage, the resulting crest factor, the impedance of the tissue, the impedance of the series circuit consisting of tissue resistance and spark resistance, the power input, the energy input, the phase angle between current and voltage, or a calculated quantity derived from one or more of these quantities.

[0013] Both the optical and electrical characteristics are fed into the storage and processing unit. From the optical characteristics, and optionally additionally or alternatively from the electrical characteristics, the storage and processing unit determines a tissue label by comparison with existing data and transmits this label to the output unit of the surgical station for display. To determine the tissue label, i.e., for tissue identification, the system according to the invention primarily uses the optical characteristics. If reliable tissue identification is not possible based solely on these characteristics, the system additionally or alternatively (secondarily) uses the electrical characteristics. This makes tissue identification significantly more reliable and versatile than when using only optical or only electrical characteristics.

[0014] The tissue label is a signal indicating whether the treated tissue in contact with the spark is malignant or benign. The output device can be optical, acoustic, or tactile to signal to the surgeon or other practitioner whether the electrode is interacting with healthy or malignant tissue. In the case of tumor resection, this provides information about whether the procedure is performed within or outside the tumor. By using not only optical but also electrical characteristics—especially those closely linked to the spark—for tissue characterization, the storage and processing device can achieve greater precision and accuracy than previously known methods.

[0015] The light analysis system includes a spectral analysis unit configured to determine the spectrum, parts of the spectrum, or a quantity derived from the spectrum or parts thereof as an optical characteristic. The surgical station may include a local processing unit for this purpose. If the storage and processing unit containing reference spectra is located outside the surgical station, the optical characteristic is determined locally, and only the optical characteristic, not the entire spectrum, is transmitted to the remote storage and processing unit. This reduces data transmission overhead and thus increases the response speed of the entire system.

[0016] The spectral analysis device also includes a quality estimator that evaluates the reliability of the acquired optical feature and assigns the resulting rating to the optical feature. The quality estimator uses a quality criterion to evaluate the acquired optical feature. This quality criterion can depend on how the optical feature is acquired. For example, the optical feature can evaluate one or more spectral lines or spectral ranges, and in particular their maximum intensities, i.e., peaks that emerge from the background noise of the spectrum. Typical peaks might be, for example, the calcium line, the magnesium line, the zinc line, or bands originating from molecular fragments, such as CN, N₂, CH, CC, NH, etc. If such spectral lines or peaks are only faintly visible above the background noise, the acquired optical feature based on these peaks has a low quality factor.If the desired lines are clearly visible, the optical feature has a high quality. The quality criterion provided by the quality estimator can be a digital signal (valid / invalid) or an analog signal, for example, a value between 0 and 1, which can be used to assess the reliability of the optical feature.

[0017] In a preferred embodiment, the storage and processing unit is configured to determine the tissue label based on the electrical characteristic, with reduced or no regard for the optical characteristic, if the quality criterion indicates low or no reliability of the optical characteristic. This allows tissue differentiation even with inferior (i.e., poorly characteristic) spectra. The storage and processing unit can further be configured to provide a warning signal that is transmitted to the surgical station and output there by the output device to inform the clinician that the reliability of the output tissue label is reduced.

[0018] The system according to the invention can be designed as a self-learning system capable of merging various data into a data set. For example, an input device can be installed in the surgical ward through which the storage and processing unit can input the type of tissue to be treated (e.g., muscle tissue, adipose tissue, lung tissue, organ tissue such as liver tissue, kidney tissue, etc.). The input device can further be designed and configured to record additional data, e.g., metadata such as patient data, and forward it to the storage and processing unit. The input device is configured for entering specific data by displaying data-specific input masks into which the relevant data can be entered or imported.

[0019] The storage and processing unit can be further configured to record the optical and electrical characteristics acquired during the operation. Additionally, the input unit can be configured to allow the entry of a histological finding, which is likewise transmitted to the storage and processing unit and assigned to the optical and electrical characteristics. The resulting raw data set can then be verified by the storage and processing unit during subsequent operations and ultimately used as a reference data set for tissue identification in future operations. The data sets can be stored specifically for individual patients or for certain patient types or classes. Patient types or classes can be defined according to sex, age, weight, general health, pre-existing conditions, substance abuse, or similar criteria.

[0020] A corresponding input device can also be located outside the surgical ward to use laboratory data to populate the database. For example, explanted tissues can be examined histologically and experimentally treated in the laboratory with an electrical instrument to determine the resulting electrical and optical characteristics and store them in the database.

[0021] Furthermore, it is possible to control the operation of the generator with respect to at least one operating parameter based on the optical characteristic. For example, the voltage, current, modulation type, modulation depth, pulse-pause ratio (in the case of pulse-pause modulation), crest factor, power input, and / or energy input into the biological tissue can be controlled. In particular, it is possible to control the generator in such a way that the optical characteristics exhibit the highest possible quality, thus ensuring good reliability of the findings obtained based on the optical and electrical characteristics.

[0022] It is also possible to control the generator according to the surgeon's wishes to achieve the desired surgical effect, for example, by having it enter a first operating mode. In this mode, the optical feature may only be obtained with low quality. The system can also be configured to briefly operate the generator in a second mode, which is not selected by the surgeon but in which the optical feature exhibits high quality. The switch to this second mode is preferably so brief that the surgeon does not subjectively perceive any change in the behavior of the instrument he is using, or at least no significant change in its behavior with regard to the desired surgical effect on the tissue.In the second operating mode, electrical parameters such as voltage, current, power, crest factor, waveform, or similar can be changed briefly, i.e., for less than 100 milliseconds, preferably less than 10 milliseconds, and even more preferably less than 1 millisecond. The change is preferably one that improves the informative value of the generated spectrum. The generator can be configured to perform this change periodically or on an ad-hoc basis.

[0023] The system according to the invention allows a surgical station to be linked to a theragnostics cloud. Optical features are acquired in the surgical station using a light analysis device and transmitted to the cloud. Integrated, self-learning data analysis takes place in the cloud. This allows the surgical station and the surgeon's work to be monitored and, ideally, dynamically adapted to individual patients. A surgical robot can also be fully or partially automated. Both centrally and decentrally stored input and annotation systems can be used as data sources. The cloud-based theragnostics system comprises a cloud-based data storage system with a machine learning-based data processing unit.The data storage system regularly receives optical emission spectra, bioimpedance data, and / or other electrical data from clinically relevant tissues, along with associated histopathological or other additional identification, from local databases or directly from the surgical ward. Furthermore, the OES cloud (optical emission spectroscopy cloud) receives individual data, i.e., electrical data, bioimpedances, and optical emission spectra from surgical procedures performed in operating rooms. During procedures using electrosurgical technology (ESF), the system continuously acquires data from peripheral devices such as surgical cameras, operating room robotics, and sensor and imaging systems, as well as diagnostic imaging devices like ultrasound, optical coherence tomography, diffuse electrical tomography, impedance tomography, elastography, or similar equipment, either directly or via an operating room management system.Furthermore, the system can identify clusters of invalid system data, particularly RF surgical system data, which are essential for reliable theragnostics. If invalid system data is detected frequently or for extended periods, a corresponding alarm signal can be triggered. Tissue recognition is continuously improved through the input and classification of data for diagnostic purposes based on electrical and optical characteristics. This can be achieved using machine learning algorithms. Control parameters for robot-assisted surgery can be derived from the acquired electrical and optical characteristics and transmitted live to end devices. Additionally, the storage and processing unit can maintain a library of electrical and optical characteristics in conjunction with tissue and patient characteristics and suggest optimal generator settings (RF settings) for ongoing procedures.Personalized medicine is therefore feasible.

[0024] Details of the theragnostic system according to the invention will become apparent from the description of the following exemplary embodiments with the aid of the drawing with the following figures: Figure 1 a simple local theragnostics system in a schematic overview representation, Figure 2 a cloud-based theragnostics system in overview format, Figure 3 a spectrum for obtaining optical features, Figure 4 an illustration of a data collection for determining tissue characteristics, Figure 5 a theragnostics system with an improved generator, Figure 6 Generator output pulses of the generator after Figure 5 .

[0025] Figure 1Figure 10 shows a highly schematic representation of a surgical station 10, particularly with regard to data acquisition and processing. The surgical station 10 comprises the components of an operating room that are not further illustrated. In particular, it includes a surgical instrument 11 with an electrode 12 for acting on biological tissue 13 during a surgical procedure. The electrode 12 of the instrument 11 is supplied by a generator 14 with a treatment voltage u and treatment current i, which are supplied to the instrument 11 via a cable. The treatment voltage u and the treatment current i are preferably high-frequency with a frequency above 100 kHz, for example 300 or 400 kHz, or any other suitable frequency.The treatment voltage u and the treatment current i are preferably provided such that a spark 15 is generated at the electrode 12 which interacts with the tissue 13 and produces a desired surgical effect on the tissue 13, such as coagulation, a cut or another effect.

[0026] The generator 14 supplies the treatment voltage u and the treatment current i via a detection device 16, which determines at least one electrical characteristic E. Such an electrical characteristic E can be the treatment current, the treatment voltage, in the case of variable treatment voltage frequencies the frequency of the treatment voltage or treatment current, the modulation level of the treatment voltage, the modulation type of the treatment voltage, in the case of pulse-pause-tapped treatment voltage or treatment current the pulse / pause ratio, the tissue impedance, the nonlinearity of the spark impedance, a spark sensor value which is composed, for example, of the measured DC component of the actual AC voltage, or a combination of these quantities or a quantity derived from a combination of one or more of these quantities. The electrical characteristic E can also comprise several such quantities. It is supplied to a storage and processing device 17.

[0027] The surgical station 10 also includes a light-receiving device 18, which is specifically designed to receive the light emitted by the spark 15. The light-receiving device 18 can be part of the instrument 11 or separate from it. The light-receiving device 18 is connected to a light-analyzing device 19, which can be part of the instrument 11 or, alternatively, as described above, Figure 1 As schematically indicated, the light receiving device 18 can be connected via a light guide 20. The light analysis device 19 is designed to determine one or more optical features O from the received spark light.

[0028] The optical feature may have been obtained by spectral analysis and / or evaluation of the spectral analysis of the spark light. The optical feature may also be the spectrum itself, that is, optical signals or data representing the spectrum of the spark light or a subspectrum thereof. The optical feature O may, for example, comprise several individual features O₁, O₂ ... Oₙ, which are supplied to the storage and processing device 17. Likewise, the electrical feature E may comprise a number of individual electrical features E₁, E₂ ... Eₙ. The individual optical features O₁, O₂, ... Oₙ may, for example, be the intensities of certain intensities of individual wavelengths λ₁, λ₂, ... λₙ occurring in the spectrum S of the spark light.The individual optical features O 1 , O 2 , O n can be based on specific emission lines of characteristic chemical elements, such as atomic emission lines of calcium, magnesium, zinc, or emission lines, emission bands or partial spectra of characteristic molecular fragments, such as CN, N 2 +< , CH, CC, NH etc.

[0029] The storage and processing unit 17 includes a mass storage device 21 that organizes the data supplied by one or more surgical stations 10. The data can be organized, for example, according to a table, as described in Figure 4This table includes electrical characteristics E as well as optical characteristics O. These can be assigned to different patients P (P1, P2, P3...Pn) and different tissue types T (T1, T2, T3...Tn). Patients P1 to Pn can be individual patients or specific patient groups categorized according to common characteristics, such as age, weight, body fat percentage, disease status, or similar. The table according to Figure 4 It may contain further entries that are not listed there.

[0030] To create the data record according to the table after Figure 4In the mass storage device 21, the storage and processing unit 17 can be connected to an input unit 22, via which the patient or patient groups, as well as the electrical characteristics E and optical characteristics O occurring during surgical intervention on the tissue 13, and disease characteristics K (K₁, K₂, ..., Kₙ) can be assigned. Furthermore, each data record can be assigned a label L indicating whether malignant tissue m or benign tissue b is present. In Figure 4, a data record is understood to be a row of the table shown. However, as already mentioned, the table can have more columns and rows than shown and contain significantly more data, such as instruments and devices used, device settings, treating personnel, etc.

[0031] The storage and processing unit 17 can also be connected to a display and / or acoustic device 23 that provides the surgeon with information about the label of the tissue touched by the spark 15. Furthermore, the storage and processing unit 17 can include or be connected to an estimator 24, which in turn is connected to the light analysis device 19 and receives from it either the optical features O or another signal that, in any case, indicates the significance of the optical features O. The estimator can, for example, determine the signal-to-noise ratio or the signal-to-noise ratio between a sample and a sample. Figure 3 The apparent background noise G and the individual optical features O1, O2 to On are identified. If all or individual optical features O1 to On are not sufficiently distinguishable from the background noise G, the reliability of the optical features O decreases significantly and can fall to zero.

[0032] The estimator 24 sends a corresponding signal to the storage and processing unit 17, in the simplest form in Figure 1 The case shown is a yes / no signal.

[0033] Instead of the signal-to-noise ratio, the estimator can also calculate a signal-to-signal ratio, in which two or more optical features of the recorded spectrum are compared to each other. If this ratio falls below or exceeds a predefined threshold, or lies within a predefined interval, the spectrum is evaluated as valid or invalid.

[0034] In a simpler version, the Estimator 24 can also use only the intensity of one or more optical features to assess quality. The intensity can be either the maximum value of the optical feature or the integral of the optical feature within a defined wavelength range. If the determined value lies above or below a predefined limit, or within a predefined range, the spectrum is evaluated as valid or invalid.

[0035] The Estimator 24 can also be designed to check for the presence of certain optical features that indicate interaction with non-biological material. In particular, the optical features of metals are suitable for characterizing accidental interactions with other surgical instruments, e.g., metallic clamps, and for classifying such spectra as invalid.

[0036] Estimators 24 of other designs can also be used. For example, the estimator 24 can be configured to compare the acquired spectrum with many different spectra belonging to a sample library. This can be done by sample comparison, cross-correlation analysis, similarity analysis, or other methods. The estimator 24 can be configured to mark the acquired spectrum as unreliable if it is not correlated with or similar to any of the existing sample spectra.

[0037] It is also possible to combine the estimators listed separately here in any way to increase the quality of the assessment.

[0038] The surgical ward 10 described above operates, for example, as follows:

[0039] The storage and processing unit 17 has first been informed of the specific patient or the patient's affiliation with a patient group P1 or P2... or Pn. This information can be provided by an identifier attached to the patient (barcode, number, patient card) or by manually entering a patient identification, such as a name, via the input unit 22. For example, it is assumed that the patient belongs to patient group P2, which is part of the illustration in Figure 4 This means that only those data sets belonging to this patient's patient group are relevant. When the operation begins, both the electrical characteristics E and the optical characteristics O are determined. Additionally, the tissue type being treated, for example, lung tissue T1, can be entered, at least optionally. This means that in the example, after Figure 4Only the first three data records (the first three rows) are suitable for further analysis. The electrical characteristics E and the optical characteristics O are now recorded and compared to the table. Figure 4 The data was compared, although in practice it contains significantly more lines and data records than shown. Based on the individual electrical characteristics E1 to En and optical characteristics O1 to On, it can now be determined with relative certainty whether the tissue touched by the spark 15 should be labeled with a malignant label m or a benign label b. The corresponding information can then be displayed by the display device 23.

[0040] In addition, especially with large amounts of data and datasets, further boundary conditions, such as diseases K 1 to K n or other influencing factors, can be taken into account and thus included in the datasets according to Figure 4.

[0041] It is possible to follow the system Figure 1During operations, the system communicates the histological findings of the tissue and thus creates further datasets, each establishing a relationship between the electrical characteristics E, the optical characteristics O, and the corresponding label L. This allows the system to learn more and more and refine its predictions over time.

[0042] Furthermore, the system can be prevented from making erroneous suggestions based on uncertain optical features O by means of the estimator 24. If the reliability of the optical features O decreases or is ultimately non-existent, the system, i.e., the storage and processing unit 17, can still issue a valid label L (namely m or b) with some certainty based solely on the electrical features E in conjunction with the other available features.

[0043] The system 10 described so far can be used according to Figure 2The system also comprises several surgical stations 10, which are connected via a remote data connection 25 to a centralized part of the storage and processing unit 17, designated as the Cloud 26. The portion of the storage and processing unit 17 remaining in each surgical station 10 is formed by a local processing unit 27. In the present embodiment, the local processing unit 27 also includes an input device 28, via which inputs, for example, about the patient, their medical status, histological findings, or the like, can be entered in the surgical station 10. The processing unit 27 transmits this information, in whole or in part, to the Cloud 26. Likewise, the processing unit 27 transmits the electrical and optical characteristics E and O, in whole or in part, to the Cloud 26.In Cloud 26, the obtained patient characteristics, as well as the electrical and optical characteristics E, O, are processed based on the data collection according to . Figure 4 The tissue is examined, and a corresponding label indicating whether it is benign or malignant is returned to processing unit 27. The result can be displayed to the surgeon visually, audibly, or tactilely via display unit 23.

[0044] The surgical ward alone after Figure 1 or the surgical wards 10 after Figure 2 In conjunction with Cloud 26, they form a theragnostics system that supports both therapy and diagnostics.

[0045] Surgery ward 10 after Figure 1 or Figure 2The system can also feature feedback between the storage and processing unit 17 and the generator 14. For example, electrical parameters of the generator 14, such as the power transferred from the instrument 11 to the tissue 13, the voltage, the current, the modulation form, the waveform of the voltage or current, or other electrical parameters, can be varied depending on the detected electrical and / or optical features E and / or O. This can be done, for example, to prevent incorrect treatments or to improve diagnostic capabilities. For instance, the system 10 can be configured to switch off the generator 14 or to switch it to a different, for example, higher power level, upon detection of contact with malignant tissue.System 10 can also be configured to permanently or temporarily, or even very briefly and sporadically or repeatedly, modify the electrical parameters in such a way as to increase the significance of the optical features O. For example, in a first mode M1, in which the significance of the optical features O is low, a switch can be made very briefly, for example for a few milliseconds, to another mode M2, which provides a higher significance of the optical features O. The switch can be effected by a brief voltage change or a change in modulation. The feedback 29 provided for this purpose is particularly effective when the data set contains a value of . Figure 4 In addition to the electrical characteristics E and optical characteristics O, a identifier K is also stored, which indicates the reliability of the optical characteristics O.

[0046] Figure 5Figure 14 illustrates essential parts of a generator 14 in a surgical station, which is designed to improve the quality of optical, tissue-identifying signals. This generator 14 is in turn designed to operate the instrument 11, which, by means of the spark 15 acting on the tissue 13, achieves a surgical effect on the one hand and generates light on the other, which is supplied to the light analysis device 19 via the light receiving device 18 and the line 20.

[0047] The special feature of generator 14 according to Figure 5The feature lies in the fact that it is configured to output individual pulses I1, I2, I3, I4, I5, I6... which together form a monopolar or bipolar RF oscillation. For this purpose, the generator 14 is divided into a pulse generator 14a and a clock generator 14b. The clock generator 14b supplies a clock signal TS to the pulse generator 14a, which triggers each individual pulse I1 to I6... The clock generator 14b is also configured to supply an amplitude signal A to the pulse generator 14a, which determines the magnitude of each generated individual pulse I1 to I6... The pulse generator can include one or more flyback converters, each of which can be triggered to output a pulse simultaneously or at different times and which emit a single output pulse upon receiving a clock signal.By simultaneously delivering multiple output pulses through multiple flyback converters, larger output pulses are generated because the output pulses of the individual flyback converters add up.

[0048] The clock generator 14b is configured to specify the clock signal TS and the amplitude signal A such that the desired surgical effect is generated. For example, if an RF pulse train with a constant amplitude A is to be generated, a sequence of clock signals TS is supplied to the pulse generator 14a when the amplitude signal A is constant. If, on the other hand, the desired surgical mode requires an interrupted pulse train with pulses of constant amplitude, a corresponding interrupted sequence of clock signals TS is supplied to the pulse generator 14 when the amplitude signal A is constant.

[0049] The special feature of the in Figure 5The illustrated generator 14 is connected to the light analysis device 19 and the estimator 24. Both can operate according to any of the principles described above. However, the estimator 24 is additionally connected to a mode catalog memory 30, which stores mode data sets that characterize various pulse sequences I₁ ... I₆ ... belonging to different treatment modalities. In particular, the mode catalog memory 30 contains an identifier for each stored mode data set, indicating the extent to which the associated pulse sequence is suitable for producing an evaluable spectrum. Specifically, the mode catalog memory contains data for pulse sequences I₃ to I₅ that produce meaningful spectra. For example, the surgeon may require a treatment modality that yields spectra that are not very informative. In the example, this is illustrated by a sequence of constant pulses I₁, I₂, etc.If the generation of such a pulse sequence and the resulting sparks 15 lead to a light phenomenon whose spectrum, determined by the light analysis device 19, is classified as inconclusive by the estimator 24, a reliable optical tissue analysis cannot be performed with this pulse sequence. In the embodiment according to... Figure 5 However, this activates the mode catalog memory 30, which sends a corresponding signal to the clock generator 14b. This signal contains either information about a single pulse or a short pulse sequence I3, I4, I5, which leads to a light phenomenon with a more easily evaluable spectrum. The resulting pulse sequence is in Figure 6illustrated. While the mode desired by the surgeon requires a sequence of constantly high voltage pulses I 1 , I 2 , I 6 etc. with a repetition rate of, for example, 5 µs, the clock generator 14b is caused to insert an intermediate pulse sequence Z into the treatment signal sequence I 1 , I 2 , I 6 at recurring time intervals, for example every 0.5 seconds.

[0050] The intermediate pulse sequence Z can comprise one or more pulses I3, I4, I5, which have the same or different amplitudes and are delivered at the same or different time intervals to the treatment signal pulses I1, I2, I6...I9. The number, time intervals, and amplitude of the intermediate pulses I3 to I5 are preferably determined such that optimal, informative spectra are obtained. The duration of the intermediate pulse sequence Z is preferably set so short that the surgical effect expected from the treatment pulses I1, I2, and I6 to I9... is little or not at all altered or impaired.

[0051] A theragnostic system according to the invention comprises a surgical station 10 and a storage and processing unit 17, which contains a large amount of data in a suitable memory. This data includes patient data and treatment data, for example, in the form of electrical and optical features E and O. The electrical features E are derived from the electrical quantities of voltage and current used to power an instrument 11. The optical features are derived from the light of the spark 15 generated when the instrument acts on the tissue 13. By combining electrical features E and optical features O in a data collection, for example, a database, which may also contain further features such as tissue characteristics and optionally patient characteristics, it is possible to automatically determine with a high degree of certainty whether the instrument is acting on healthy or diseased tissue.Predictive accuracy can be improved through machine learning by adding histological data to the datasets in addition to the electrical features E and the optical features O. In a preferred embodiment, this data is collected in a cloud 26 that is connected to many surgical stations 10. Thus, data acquired in various surgical stations 10 can be collected in the cloud 26. Reference symbol:

[0052] 10 Surgical station 11 Instrument 12 Electrode 13 Biological tissue 14 Generator 14a Pulse generator I1, I6...I9 Treatment pulses I3...I5 Intermediate pulses 14b Clock generator TST Clock signal A Amplitude signal u Treatment voltage i Treatment current 15 Spark E Electrical feature 16 Electrical feature acquisition device E 17 Storage and processing device 18 Light acquisition device 19 Light analysis device 20 Optical fiber O Optical feature P Patient identifier T Tissue identifier 21 Mass storage 22 Input unit 23 Display device 24 Estimator 25 Remote data connection 26 Cloud 27 Processing device 28 Input device 29 Feedback 30 Mode catalog storage Z Intermediate pulse sequence

Claims

1. A theragnostic system: having at least one surgical station (10) that comprises at least: - a light receiving device (18) for detecting light emanating from a spark (15) generated between an electrode (12) of an electrosurgical instrument (11) and biological tissue (13), - a light analysis device (19) that is configured to detect at least one optical feature (O) of the received light, - a generator (14) for providing an electrical voltage (u) for supplying the instrument (11) and thereby for supplying the electrode (12) of the instrument (11) with electrical current (i), - an output device (23), and having a storage and processing device (17) that is configured to determine a tissue label (L) based on the at least one optical feature (0) and to transmit this to the output device (23) for output, characterized in that the surgical station (10) further comprises a detection device (16) for determining at least one electrical feature (E), the light analysis device (19) includes a spectral analysis device and has a quality estimator (24) that is configured to assess the reliability of the obtained optical feature based on a quality criterion and to assign the obtained assessment to the optical feature, the storage and processing device (17) is further configured, if the optical feature (O) is not sufficient for tissue identification, to additionally or alternatively determine a tissue label (L) based on the at least one electrical feature (E) and to transmit this to the output device (23) for output, and the storage and processing device (17) is configured to determine the tissue label (L) with reduced or without consideration of the optical feature (O) based on the electrical feature (E) if the spectrum does not have sufficient quality.

2. The system according to claim 1, characterized in that the spectral analysis device is configured to determine the spectrum, portions of the spectrum or parameters derived from the spectrum or from portions of the spectrum as optical feature (0).

3. The system according to claim 2, characterized in that the light analysis device (19) or the storage and processing device (17) comprises or is connected to the quality estimator (24) for the spectrum, portions of the spectrum or parameters derived therefrom.

4. The system according to claim 3, characterized in that the quality estimator is configured to determine the signal-to-noise ratio of at least one spectral line (O1) or a spectral range (O1, O2).

5. The system according to anyone of the preceding claims, characterized in that it comprises an input device (22, 28) via which tissue identifiers (T) can be entered, wherein the input device (22, 28) is connected to the storage and processing device (17) in order to transmit the tissue identifier (T) to the latter.

6. The system according to anyone of the preceding claims, characterized in that the storage and processing device (17) comprises a data collection in which at least one tissue label (L) is assigned to each set of optical and electrical features (0, E).

7. The system according to claim 5 or 6, characterized in that the tissue identifier (T) is defined based on the inputs entered via the input device (22, 28).

8. The system according to anyone of the preceding claims, characterized in that the storage and processing device (17) is part of the surgical station (10).

9. The system according to anyone of the preceding claims, characterized in that the generator (14) is controlled with regard to at least one operating parameter based on the optical feature (0).

10. The system according to anyone of the preceding claims, characterized in that it is configured so that the generator (14), if operated in a first operating mode (M1) in which the optical feature (O) does not allow reliable tissue identification, is operated at least for a short period in a second operating mode (M2) in which tissue identification is possible based on the optical feature.

11. The system according to anyone of the preceding claims, characterized in that it comprises a plurality of surgical stations (10).

12. The system according to claim 11, characterized in that a part (26) of the storage and processing device (17) is connected to the surgical station (10) via a data transmission device (25).

13. The system according to anyone of the preceding claims, characterized in that the storage and processing device (17) is connected to an input device (28) positioned outside the surgical station (10).