An adaptive x-ray exposure triggering method based on body surface monitoring

Abstract

The application discloses a kind of self-adapting X-ray exposure trigger method based on body surface monitoring, belong to medical image guidance and radiotherapy positioning technical field.The method includes: according to target region site determination and arrangement body surface marker;After first verification, reference template is constructed;Real-time acquisition body surface signal and calculate characteristic parameter;According to characteristic parameter, through the hierarchical trigger mechanism of fusion signal instantaneous characteristic, trend characteristic and time sequence information, whether trigger X-ray exposure is comprehensively judged, the instant response to sudden shift and the reliable capture to slow drift are considered, unknown risk is prevented through bottom mechanism, the safety of treatment process and the real-time of monitoring are comprehensively improved.The present application effectively solves the problems of radiation dose accumulation and response lag to sudden displacement caused by fixed time interval exposure in the prior art, and achieves the effect of significantly reducing the patient's exposure dose, improving the safety and real-time of treatment.

Description

Technical Field

[0001] This invention relates to an adaptive X-ray exposure triggering method based on body surface monitoring, belonging to the field of medical image guidance and radiotherapy positioning technology. Background Technology

[0002] In stereotactic radiotherapy (such as CyberKnife, Riekel, etc.), in order to ensure the accuracy of the target area location, the treatment equipment needs to take X-ray exposure images at regular intervals during the treatment process to verify the accuracy of the patient's static position or dynamic respiratory movement position.

[0003] Currently, whether for static treatments targeting the head and neck, pelvis, or dynamic respiratory tracking treatments targeting the chest and abdomen, the mainstream verification method involves X-ray exposure at preset fixed time intervals (e.g., 15-150 seconds). Patent CN109727672B, "Method for Predicting and Tracking Respiratory Motion in Patients with Chest and Abdominal Tumors," discloses a method that, after establishing a surface-to-in vivo respiratory motion correlation model, periodically uses an X-ray image-guided positioning system to acquire the target area location within the patient's body and compares it with the model's predicted location to verify and update respiratory tracking accuracy. While this approach can guide precise tracking radiotherapy, its timed exposure method has the following significant drawbacks: First, regardless of whether the patient's actual position shifts, a fixed frequency of X-ray exposure is continuously applied. For patients who remain in a good position, this extensive exposure is completely unnecessary, resulting in an accumulated additional radiation dose. Second, frequent X-ray exposures not only increase the wear and tear on the X-ray tube and detector but also consume system resources during image analysis and may prolong the overall treatment time due to waiting for exposures and verification, reducing treatment efficiency. Third, the fixed exposure interval cannot respond immediately to sudden positional shifts (such as patient coughing or movement), potentially missing critical shift events between exposures, posing a safety hazard. Shortening the exposure interval in pursuit of safety would further exacerbate the problems of radiation dose and resource waste. Summary of the Invention

[0004] To address the existing problems of excessive radiation dose, low treatment efficiency, and safety hazards caused by sudden positional deviations, this invention provides an adaptive X-ray exposure triggering method based on body surface monitoring. The technical solution is as follows: Step 1: Determine and place surface markers according to the target area; Step 2: After the initial X-ray image-guided positioning verification is successful, the signals of the surface markers are acquired to construct a reference template; Step 3: During the treatment process, collect surface signals in real time and calculate characteristic parameters for judgment; Step 4: Based on the characteristic parameters calculated in Step 3, a hierarchical triggering mechanism that integrates instantaneous signal characteristics, trend characteristics, and time series information is used to comprehensively determine whether to trigger X-ray exposure; The hierarchical triggering mechanism in step 4 includes at least two decision logics: (1) When the displacement or baseline signal instantaneously exceeds the preset high threshold, X-ray exposure is immediately triggered; (2) When the parameters after smoothing and filtering continuously exceed the preset threshold for a preset duration, X-ray exposure is triggered; (3) When the time since the last X-ray exposure exceeds the preset maximum time interval, X-ray exposure is forcibly triggered; (4) In the dynamic respiratory tracking treatment mode, when the uncertainty index of the position prediction model exceeds the preset threshold, X-ray exposure is triggered.

[0005] Optionally, when the treatment site is the respiratory site, in step 3, a dual-path peak-valley detector is used to identify the end-expiratory trough value point of each respiratory cycle in real time; the dual-path peak-valley detector includes a first detection path and a second detection path in parallel: The working process of the first detection path includes: starting to track after the signal reaches a temporary trough value; when the signal rises from the trough value by more than a dynamically calculated threshold, determining that the current respiratory cycle has ended and confirming that the temporary trough value is a valid end-expiratory trough value point. The working process of the second detection path includes: after the signal enters the expected end-expiratory stage, the rate of change of the signal is monitored in real time. When the rate of change of the signal is continuously lower than the preset small threshold, the current point is immediately confirmed as the end-expiratory valley point. The dual-path peak-valley detector selects the path that first meets the conditions to output the valley value point.

[0006] Optionally, when the treatment site is a rigid site, a real-time rigid body registration method with integrated geometric self-checking function is used, including: By performing rigid body registration between the reference point set and the current point set, the patient's overall motion is calculated, and the real-time position error of the target point is also calculated. Simultaneously, the geometric self-checking logic of the marked area is run in parallel to calculate the distance between each marked area in real time. If all the spacing changes are within the threshold, but the overall error exceeds the limit, it is determined to be real movement and an X-ray trigger signal is generated. If the spacing of some areas changes drastically, it is determined to be local skin sliding and the X-ray trigger signal is suppressed.

[0007] Optionally, for static treatment of the head and neck, the surface markers are selected as relatively rigid landmarks in the midline of the forehead and the bilateral brow ridges, and the monitoring data includes the six-degree-of-freedom rigid displacement of the skull.

[0008] Optionally, for static treatment of the chest and abdomen, the surface markers are selected from the relatively rigid thoracic region of the manubrium of the sternum or the lower edge of the costal arch, and the monitoring data include the stability of the respiratory baseline and overall body displacement.

[0009] Optionally, for static pelvic treatment, the pelvic triangle formed by the bilateral anterior superior iliac spines and pubic symphysis is selected as the surface marker, and the monitoring data includes the six-degree-of-freedom rigid displacement of the pelvis.

[0010] Optional, dynamic respiratory tracking therapy targeting the lungs or liver, with surface markers selected for relatively rigid areas of the chest or upper abdomen, and monitoring data including multidimensional characteristic parameters of respiratory waveforms.

[0011] Secondly, the present invention provides an adaptive X-ray exposure triggering system based on body surface monitoring, the system being used to implement the method described in any of the preceding claims, including: The data acquisition module is configured to acquire body surface markers and, after the initial X-ray image-guided positioning verification is passed, acquire the signals of the body surface markers to construct a reference template; The signal processing module is configured to perform calculations based on real-time acquired body surface signals during treatment to obtain characteristic parameters for judgment. The adaptive hierarchical triggering module is configured to comprehensively determine whether to trigger X-ray exposure based on the aforementioned feature parameters and through a hierarchical triggering mechanism that integrates instantaneous signal features, trend features, and timing information. The hierarchical triggering mechanism includes at least two decision logics: (1) When the displacement or baseline signal instantaneously exceeds the preset high threshold, X-ray exposure is immediately triggered; (2) When the parameters after smoothing and filtering continuously exceed the preset threshold for a preset duration, X-ray exposure is triggered; (3) When the time since the last X-ray exposure exceeds the preset maximum time interval, X-ray exposure is forcibly triggered; (4) In the dynamic respiratory tracking treatment mode, when the uncertainty index of the position prediction model exceeds the preset threshold, X-ray exposure is triggered.

[0012] Thirdly, the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the adaptive X-ray exposure triggering method based on body surface monitoring as described in any of the preceding claims.

[0013] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that: when the computer program is executed by a processor, it implements the steps of the adaptive X-ray exposure triggering method based on body surface monitoring as described in any of the preceding claims.

[0014] The beneficial effects of this invention are: This invention addresses the problems of unnecessary radiation dose accumulation, resource waste, and delayed response to sudden patient displacement caused by fixed-time intervals in existing X-ray exposure verification methods, by employing an adaptive X-ray exposure triggering method based on body surface monitoring. Specifically, this invention achieves intelligent on-demand triggering of X-ray exposure by real-time acquisition of body surface signals and calculation of characteristic parameters, and introduces a hierarchical triggering mechanism that integrates instantaneous signal characteristics, trend characteristics, and temporal information. This hierarchical triggering mechanism works collaboratively through the following decision logics: Instantaneous response logic triggers exposure immediately when the displacement or baseline signal instantaneously exceeds a preset high threshold, quickly capturing sudden positional shifts; trend confirmation logic effectively filters out instantaneous noise and accurately captures slow, continuous positional drift through a dual mechanism of "filtering + time confirmation"; safety margin logic forcibly triggers exposure when the preset maximum time interval is exceeded, preventing unknown silent internal changes; and model uncertainty logic ensures model fidelity by monitoring the uncertainty index of the prediction model in dynamic respiratory tracking mode.

[0015] Through the above technical solution, this invention transforms "timed blind exposure" into "on-demand intelligent verification," triggering X-ray exposure only when the patient's positional error risk reaches a preset condition. This significantly reduces the number of unnecessary X-ray exposures during treatment, thereby substantially lowering the patient's cumulative radiation dose. Secondly, the tiered triggering mechanism of this invention balances immediate response to sudden shifts with reliable capture of slow drifts, while a safety net mechanism mitigates unknown risks, comprehensively improving the safety and real-time monitoring of the treatment process. Finally, this invention reduces unnecessary wear and tear on X-ray tubes and detectors, lowers the system burden of image analysis, and makes the treatment process more efficient.

[0016] Furthermore, this invention introduces a dual-path peak-valley detector, solving the technical problem in dynamic respiratory tracking therapy where the variable breathing patterns of patients make it difficult for traditional single algorithms to accurately and in real-time identify end-expiratory trough points, thus affecting the accuracy of X-ray exposure timing. Specifically, this detector achieves complementary advantages by setting two detection paths in parallel: the first path judges based on a dynamic threshold of signal rise amplitude, effectively adapting to changes in respiratory depth and preventing missed detections due to shallow breathing; the second path detects based on the steady-state period of signal change rate, immediately confirming the trough point when the patient experiences brief respiratory arrest or end-expiratory pause, without waiting for a significant signal rise. By selecting the path that first meets the conditions to output the result, this invention not only significantly improves the robustness and accuracy of trough identification, ensuring the reliability of exposure timing under complex waveforms, but also significantly reduces exposure delay, shortening the waiting time from end-expiratory to triggering exposure. In addition, this mechanism enables the system to automatically adapt to changes in the patient's breathing habits during treatment, without frequent manual intervention to adjust parameters, greatly enhancing the system's adaptability and ensuring monitoring stability and overall treatment efficiency during long-term treatment. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the overall process of the adaptive X-ray exposure triggering method based on body surface monitoring of the present invention.

[0019] Figure 2 This is a schematic diagram of the arrangement of the head and neck marking areas in this invention.

[0020] Figure 3 This is a schematic diagram of the arrangement of the marking areas on the chest and abdomen of the present invention.

[0021] Figure 4 This is a schematic diagram of the arrangement of the pelvic supine position marking area according to the present invention.

[0022] Figure 5 This is the state machine and logic flowchart of the dual-path peak-valley detector of the present invention.

[0023] Figure 6 This is the block diagram of the adaptive hierarchical triggering decision logic of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0025] Example 1: This embodiment provides an adaptive X-ray exposure triggering method based on body surface monitoring, such as... Figure 1 As shown, the method includes: Step 1: Pre-treatment classification and marking.

[0026] Based on the treatment type (static / dynamic) and target area, determine the surface markers and key points for monitoring, as follows.

[0027] For static treatment of the head and neck: select relatively rigid landmarks (such as the midline of the forehead and bilateral brow ridges) for marking areas, and focus on monitoring the six degrees of freedom (6D) rigid displacement of the skull.

[0028] For static treatment of the chest and abdomen: mark relatively rigid thoracic areas (such as the manubrium of the sternum and the lower edge of the costal arch), and focus on monitoring the stability of the respiratory baseline (end-expiratory position) and overall body displacement.

[0029] For static pelvic treatment: mark and select relatively rigid pelvic triangles (bilateral anterior superior iliac spines and pubic symphysis), and focus on monitoring the 6D rigid displacement of the pelvis.

[0030] For dynamic respiratory tracking therapy targeting the lungs / liver: relatively rigid chest or upper abdomen are selected as markers, and multidimensional characteristic parameters of respiratory waveforms are monitored to assess the fidelity of the body surface-tumor association model.

[0031] There are several ways to mark the body surface, such as by placing marking points on the body surface area or by drawing marking areas on the patient's body surface outline.

[0032] Step 2: Establish a reference baseline.

[0033] After the initial X-ray image-guided positioning verification is successful, the coordinates of the body surface markers or respiratory signals are immediately acquired to construct a reference template.

[0034] For rigid parts: record the set of three-dimensional coordinate points of the markings, or the spacing / or the reference position of the target point.

[0035] For the respiratory site: collect several stable respiratory cycles to establish the end-expiratory baseline, average amplitude, and reference respiratory template waveform.

[0036] Step 3: Real-time body surface monitoring and characteristic parameter calculation.

[0037] Depending on the type of treatment, the corresponding algorithm module is invoked to extract the key parameters required for judgment from real-time body surface signals.

[0038] For rigid parts, this embodiment adopts a real-time rigid body registration method with integrated geometric self-checking function, which specifically includes the following steps: (1) By performing rigid body registration between the reference point set and the current point set, the rotation matrix and translation vector describing the overall motion of the patient are calculated, and then the real-time 3D position error of the target point and the rotation angle of each axis are calculated. (2) Lightweight low-pass filtering is applied to displacement and angle signals to remove optical jitter noise; Simultaneously, a geometric self-checking logic for the marked regions runs in parallel: it calculates the pairwise distances between each marked region in real time. If all distance changes are within the threshold and the overall target point error exceeds the limit, it is determined to be real movement, and an X-ray trigger signal is generated; if the distances between some regions change drastically, it is determined to be local skin slippage, at which point the X-ray trigger signal is suppressed, and instead an abnormal marked region prompt is output.

[0039] This logic enables the automatic differentiation between "actual patient movement" and "abnormalities in the marked area" at the body surface monitoring level.

[0040] For the respiratory site, this embodiment uses an adaptive end-expiratory mean square model, such as... Figure 5 As shown, the specific implementation method is as follows: (1) A parallel dual-path peak-valley detector is used to identify the end-expiratory trough point in real time for each respiratory cycle. The detector includes: The first detection path based on the rebound crossover: This path serves as a fundamental detection method applicable to all breathing patterns. Its working principle is as follows: after the signal reaches a temporary trough, tracking begins. When the signal rebounds from this trough by more than a threshold dynamically calculated based on historical respiratory amplitudes, the current respiratory cycle is considered complete, and the temporary trough is confirmed as a valid end-expiratory trough point. This method ensures reliable detection of troughs even when the patient is breathing rapidly without significant end-expiratory apnea.

[0041] The second detection path, based on stationary phase detection, is an optimized detection method designed to improve real-time performance. Its working principle involves real-time monitoring of the signal's rate of change after it enters the expected end-expiratory phase. When the rate of change consistently falls below a preset small threshold, indicating that respiratory movement has entered a stationary phase, the current point is immediately confirmed as the end-expiratory trough, without waiting for the signal to recover. This method effectively eliminates the detection delay caused by waiting for the signal to recover, and is particularly suitable for stable breathing patterns with significant end-expiratory apnea.

[0042] Through the aforementioned dual-path parallel detection mechanism, the system can intelligently select the path that first meets the conditions to output the valley point, thereby minimizing detection latency while ensuring detection robustness.

[0043] For dynamic treatment of respiratory sites, it is also necessary to extract the amplitude, period, waveform similarity, and stability index within the sliding window from the peak-valley detection results to evaluate the fidelity of the correlation model. Amplitude is obtained by calculating and smoothing the difference between the peak and trough values ​​for each period; period / frequency is obtained by calculating and smoothing the time difference between adjacent trough values; waveform similarity is obtained by resampling and normalizing the waveform of each respiratory cycle and calculating the Pearson correlation coefficient with a reference template; stability is calculated by taking the mean and variance of the coefficients of variation of amplitude, period, baseline, and similarity within the sliding window.

[0044] Step 4: Adaptive hierarchical triggering decision.

[0045] Based on the parameters and risk level extracted in step 3, a hierarchical triggering mechanism that integrates instantaneous signal characteristics, trend characteristics, and time-series information is used to make a decision on whether to perform X-ray exposure. Figure 6 As shown, the decision-making logic specifically includes the following: (1) Impact-type rapid response channel: When the unfiltered or lightly filtered displacement / baseline signal instantly exceeds the high threshold (such as target error > 3mm or baseline change > 5mm), X-ray exposure is immediately triggered within a single sampling period without waiting for filtering or confirmation to deal with sudden violent movement.

[0046] (2) Trend alarm channel: When the smoothed and filtered parameters continuously exceed the fine threshold (such as target error > 1mm / 1.5mm, or baseline drift > 2mm, or waveform similarity < 0.85) for a preset duration or number of consecutive frames (such as 10~20 seconds), X-ray exposure and image acquisition are triggered. This dual mechanism of "filtering + time confirmation" can filter out instantaneous noise and accurately capture slow drift.

[0047] (3) Maximum time interval guaranteed trigger channel: Based on the risk of the location, different maximum unverified time intervals are set (5 minutes for head and neck, 2-3 minutes for chest and abdomen static, 1-2 minutes for pelvic cavity, and 5-8 minutes for dynamic tracking). If the time limit is exceeded, X-ray exposure and imaging will be forcibly triggered to prevent any unknown silent internal changes.

[0048] (4) Dynamic Model Uncertainty Trigger Channel: This channel is only used in dynamic respiratory tracking treatment mode. If the uncertainty index of the position prediction model continues to accumulate and exceeds the preset threshold after the last X-ray calibration, it will trigger X-ray exposure and image acquisition for model recalibration. This channel will actively trigger verification to correct prediction bias when the respiratory waveform is regular but the fidelity of the internal-body surface correlation model decreases.

[0049] This embodiment first deploys corresponding surface markers before treatment based on different scenarios, such as static treatment of the head and neck, chest and abdomen, and pelvis, or dynamic respiratory tracking treatment. A reference baseline is established after the initial X-ray verification. Subsequently, during treatment, a real-time rigid body registration algorithm integrating geometric self-checking or an adaptive end-expiratory mean line model is used to perform high-precision monitoring of the 6D displacement of rigid parts or the baseline, waveform, and other multi-dimensional features of the respiratory parts. Finally, a hierarchical decision-making system, consisting of an impact-based rapid response channel, a trend alarm channel, a maximum time interval minimum trigger channel, and a dynamic model uncertainty trigger channel, comprehensively determines whether to trigger X-ray exposure. This embodiment, through the above technical solution, can significantly reduce unnecessary radiation dose to patients during treatment, while improving the response speed and robustness of position monitoring for sudden postural shifts, effectively balancing treatment safety and efficiency, and has significant clinical application value.

[0050] Example 2: Adaptive X-ray Exposure Triggering for Static Treatment of the Head and Neck This embodiment corresponds to stereotactic radiotherapy for head and neck tumors. The patient does not wear a mask, or wears an open-face mask that exposes the forehead, eyes, and nose. The specific implementation steps are as follows: Step 1: Arrange marker points and establish reference benchmarks.

[0051] like Figure 2 As shown, a passive reflective ball with a diameter of 11mm is attached to the center of the patient's forehead and to each of the brow ridges, with a center-to-center distance of more than 20mm. An additional ball may be attached to the tip of the nose to aid in assessing respiratory interference, but this is not included in rigid registration.

[0052] After the initial X-ray positioning verification was successful, a reference baseline was established. The optical system acquired the three-dimensional coordinates of the midpoint of the forehead, the left brow ridge, and the right brow ridge to form a reference point set.

[0053] Calculate the distance between reference points:

[0054]

[0055]

[0056] Record the coordinates of the center point of the planned target area in the reference coordinate system: .

[0057] Set trigger thresholds: Trend alarm channel translation threshold 1mm, rotation threshold 1°; Impact rapid response channel translation threshold 3mm; Maximum time interval guarantee trigger channel maximum guarantee interval is 5 minutes.

[0058] Step 2: Real-time optical monitoring of body surface and calculation of characteristic parameters.

[0059] For each frame (sampling rate 30Hz), obtain the real-time coordinates of three points and perform the following calculations: (1) Rigid body registration and displacement calculation. A closed-form solution method based on singular value decomposition (SVD) is used to calculate the current point set. P cur Compared to P ref Rigid body transformation: Calculate the centroid of a two-point set:

[0060]

[0061] Decentization of the point set:

[0062]

[0063] Calculate the 3×3 covariance matrix:

[0064] right H SVD decomposition yields:

[0065] Calculate the rotation matrix:

[0066] det( R If ) < 0, then V The last column is inverted to ensure that it is a right-handed rotation matrix.

[0067] Calculate the translation vector:

[0068] Calculate the real-time error of the target:

[0069] Calculated for each frame Perform first-order exponentially weighted moving average (EWMA) filtering, smoothing factor α =0.25:

[0070] The rotation angle is also from the matrix R Extract and perform EWMA filtering.

[0071] (2) Marker point geometry self-check.

[0072] Real-time pixel spacing is calculated simultaneously for each frame. , , And compare it with the reference spacing.

[0073] Step 3: Adaptive hierarchical triggering decision.

[0074] In each frame, the system performs the following judgments in parallel: (1) Impact-type rapid response channel: If It immediately triggers X-ray exposure and image acquisition without waiting for any filtering or frame confirmation; (2) Trend Alarm Channel: First, perform a geometric self-check; if a certain... If other spacings are normal, it is determined that the marker point is abnormal, the trend alarm signal of this frame is suppressed, and a "Please check marker point" prompt is sent to the host computer.

[0075] If the geometric self-check passes (all spacing deviations < 0.5mm), and Then, the "continuous over-limit time" begins to accumulate. When the continuous over-limit time reaches 15 frames, X-ray exposure and image acquisition are triggered.

[0076] (3) Maximum time interval guaranteed trigger channel: If the time since the last X-ray exposure exceeds 5 minutes, regardless of whether the above conditions are met, an X-ray exposure and image acquisition will be forcibly triggered.

[0077] (4) Dynamic model uncertainty triggering channel (optional): If the nose tip signal shows regular breathing fluctuations, and the displacement of the three points of the skull is synchronized with this and the amplitude is very small, it can be further confirmed that it is caused by respiratory conduction and will not trigger X-ray exposure imaging.

[0078] With this embodiment, for well-cooperative and securely fixed head and neck patients, the optical monitoring signal remains stable for most of the treatment time, with X-ray exposure triggered only at a minimum interval of 5 minutes. The total number of exposures can be reduced by more than 90% compared to traditional methods. Simultaneously, the impact channel ensures immediate response to sudden movement, and geometric self-checking eliminates false triggering caused by loose markers.

[0079] Example 3: Adaptive X-ray Exposure Triggering for Dynamic Respiratory Tracking in the Chest and Abdomen This embodiment corresponds to dynamic respiratory tracking therapy for lung or liver tumors, and includes the following implementation steps: Step 1: Arrange marker points and establish reference benchmarks.

[0080] like Figure 3 As shown, several optical markers are placed on the upper abdomen of the patient between the xiphoid process and the umbilicus, spanning both sides of the abdominal midline.

[0081] During the correlation model establishment phase (which typically requires multiple X-ray exposures for image acquisition), a reference baseline is established simultaneously, which includes the following steps: (1) Collect stable respiratory optical signals for at least 2 minutes; (2) Extract the initial end-expiratory baseline from the signal (The average of multiple end-expiratory trough values ​​within a stable period is taken.)

[0082] (3) Generate a normalized respiratory waveform template Select several stable respiratory cycles, and resample to [a specific location] for each cycle. N =50 points, perform z-score normalization (mean is 0, standard deviation is 1), and take the point average as the template.

[0083] (4) Set trigger thresholds: baseline drift threshold 2mm, amplitude trend change threshold 30%, waveform similarity threshold 0.85, maximum minimum interval 8 minutes.

[0084] Step 2: Specific implementation of the dual-path peak-valley detector.

[0085] In this embodiment, real-time peak-valley detection employs the following dual-path parallel logic to accommodate different breathing modes. The execution steps are as follows: (1) Signal preprocessing.

[0086] For the original optical respiratory signal s ( t A second-order Butterworth low-pass filter is applied with a cutoff frequency of 3Hz.

[0087] (2) The first detection path (safety path) based on the recovery and crossing: Maintain a state machine containing two states, SEARCHING_PEAK and SEARCHING_VALLEY, as well as dynamic breathing amplitude. .

[0088] State transition: In the SEARCHING_VALLEY state, track the temporary minimum. When the signal recovers from this minimum beyond the hysteresis... (And the refractory period has exceeded 0.8 seconds since the last confirmed trough), confirming a valid trough. The status is switched to SEARCHING_PEAK.

[0089] Dynamic threshold update: Dynamic upper threshold Dynamic threshold It is used to assist the state machine in determining trends. This indicates the last valid valley value.

[0090] Dynamic amplitude update: Once a valid peak-valley pair is confirmed, the amplitude is updated according to the following formula:

[0091] This indicates the respiratory amplitude in the current cycle.

[0092] (3) Second detection path (accelerated path) based on stationary period detection: Within the SEARCHING_VALLEY state, a stationary phase detector runs in parallel, and the detection method is as follows: Continuous calculation of the local first derivative of the signal When the following conditions are met simultaneously, the trough value is actively confirmed without waiting for a rebound: Signal amplitude is at dynamic lower threshold The following; absolute value of the derivative ,in The duration for which the above conditions are met consecutively exceeds [a certain duration]. T pause = 0.25 seconds.

[0093] This acceleration pathway allows patients with end-expiratory apnea to confirm their trough without waiting for the recovery process, eliminating the lag in recovery. For patients with shortness of breath and no steady-state period, this pathway naturally fails and automatically degenerates into a system where only the safety pathway works.

[0094] (4) Abnormal spike freezing mechanism In addition to peak and valley detection, a peak detector runs independently. If |s(t) - s(t-0.1s)|>10mm, it is immediately identified as an abnormal event such as coughing / hiccuping: the current state machine and baseline update are frozen, and the last valid parameters are retained; at the same time, a high-priority abnormal event flag is immediately output for triggering decision-making.

[0095] Step 3: Real-time respiratory baseline and multidimensional parameter calculation.

[0096] Obtaining an effective valley sequence Then, perform the following calculations: (1) Calculate the end-expiratory baseline (EWMA, β=0.15):

[0097] (2) Calculate the amplitude of each cycle:

[0098] in This is the peak value at the end of inspiration.

[0099] The smoothing amplitude is: .

[0100] (3) Calculate the duration of each cycle:

[0101] The smoothing period is:

[0102] (4) Calculate waveform similarity: For the k One cycle, extracting from arrive The waveform segment was resampled to 50 points, normalized by z-score, and compared with the template. Calculate the Pearson correlation coefficient:

[0103] (4) Calculate stability index: Take the most recent 10 effective periods and calculate the coefficient of variation (CV) of period, amplitude, baseline, and average similarity. r mean and similarity standard deviation r std .

[0104] Step 4: Multidimensional fusion triggers decision-making.

[0105] (1) Impact-type rapid response channel: If an abnormal spike event occurs, or the baseline... If the instantaneous jump exceeds 5mm, X-ray exposure and image acquisition are immediately triggered to verify the model.

[0106] (2) Trend Alarm Channel: Baseline drift: Continue for more than 3 respiratory cycles; Changes in amplitude trend: Continue for more than 5 cycles; Waveform distortion: r k <0.85 for 5 consecutive cycles; If any of the above conditions are met, X-ray exposure and imaging will be triggered.

[0107] (3) Maximum time interval guaranteed trigger channel: If more than 8 minutes have passed since the last X-ray exposure, forced triggering will occur. (4) Uncertainty triggering channel of dynamic model: Define an uncertain function:

[0108] in, Indicates the last time it was exposed. Indicates the current coefficient of variation. w 1. w 2. w3 represents the weighting coefficient. When U ( t When the preset safety threshold is exceeded, X-ray exposure and imaging are triggered to prevent situations where the respiratory waveform appears regular but the internal relationship has undergone silent drift.

[0109] In this embodiment, X-ray exposure is no longer triggered at a fixed frequency, but is precisely focused on moments when model fidelity may decrease, such as coughing, baseline drift, and waveform distortion. During normal, regular breathing periods, there is almost no additional exposure, reducing the total number of exposures by 60%-80%.

[0110] Example 4: Adaptive X-ray exposure triggering for pelvic area treatment This embodiment corresponds to the static treatment of pelvic tumors such as prostate and cervical tumors. The specific implementation steps are as follows: Step 1: Marker point placement and reference datum establishment like Figure 4 As shown, the patient is in a supine position, and an optical marker is attached above each of the bilateral anterior superior iliac spines and the pubic symphysis to form a pelvic monitoring triangle.

[0111] The reference datum establishment and rigid body registration calculation methods are the same as in Example 1.

[0112] Step 2: Set up monitoring mechanisms and core compensation strategies.

[0113] The pelvic target area is affected by internal factors such as bladder fullness and rectal contents, resulting in random, slow movements independent of the body surface bones, which cannot be directly detected by optical devices.

[0114] The optical monitoring in this embodiment is used for: first, to capture sudden large movements of the pelvis in real time (such as body vibrations caused by a patient raising their leg or coughing); and second, to eliminate invalid timed X-ray spot checks due to the absence of body movement.

[0115] The monitoring and triggering parameter configuration strategy in this embodiment includes: (1) Maximum time interval protection trigger channel: The maximum protection interval is forcibly set to a short clinical safety value, such as 1.5 minutes. This means that even if the optical signal shows that the pelvis is not moving, the system will still perform an X-ray exposure image verification at an interval of no more than 1.5 minutes to directly confirm the location of the internal target area.

[0116] (2) Trend alarm channel: The translation threshold can be appropriately relaxed to 1.5mm-2mm to avoid misleading alarms caused by imperceptible internal movements.

[0117] (3) Impact-type rapid response channel: The translation threshold is set to 3mm.

[0118] Compared to purely timed exposures (e.g., once every 30 seconds), this embodiment reduces the X-ray exposure frequency from once every 30 seconds to once every 1.5 minutes during periods when the patient is not moving, reducing the number of exposures by more than 60%. Simultaneously, the impact-type rapid response channel ensures immediate capture of sudden displacements, reducing the total number of exposures by 30%-50%.

[0119] Some steps in the embodiments of the present invention can be implemented using software, and the corresponding software program can be stored in a readable storage medium, such as an optical disc or a hard disk.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive X-ray exposure triggering method based on body surface monitoring, characterized in that, The method includes: Step 1: Determine and place surface markers according to the target area; Step 2: After the initial X-ray image-guided positioning verification is successful, the signals of the surface markers are acquired to construct a reference template; Step 3: During the treatment process, collect surface signals in real time and calculate characteristic parameters for judgment; Step 4: Based on the characteristic parameters calculated in Step 3, a hierarchical triggering mechanism that integrates instantaneous signal characteristics, trend characteristics, and time series information is used to comprehensively determine whether to trigger X-ray exposure; The hierarchical triggering mechanism in step 4 includes at least two decision logics: (1) When the displacement or baseline signal instantaneously exceeds the preset high threshold, X-ray exposure is immediately triggered; (2) When the parameters after smoothing and filtering continuously exceed the preset threshold for a preset duration, X-ray exposure is triggered; (3) When the time since the last X-ray exposure exceeds the preset maximum time interval, X-ray exposure is forcibly triggered; (4) In the dynamic respiratory tracking treatment mode, when the uncertainty index of the position prediction model exceeds the preset threshold, X-ray exposure is triggered.

2. The adaptive X-ray exposure triggering method based on body surface monitoring according to claim 1, characterized in that, When the treatment site is the respiratory site, in step 3, a dual-path peak-valley detector is used to identify the end-expiratory trough value point of each respiratory cycle in real time. The dual-path peak-valley detector includes a first detection path and a second detection path in parallel: The working process of the first detection path includes: starting to track after the signal reaches a temporary trough value; when the signal rises from the trough value by more than a dynamically calculated threshold, determining that the current respiratory cycle has ended and confirming that the temporary trough value is a valid end-expiratory trough value point. The working process of the second detection path includes: after the signal enters the expected end-expiratory stage, the rate of change of the signal is monitored in real time. When the rate of change of the signal is continuously lower than the preset small threshold, the current point is immediately confirmed as the end-expiratory valley point. The dual-path peak-valley detector selects the path that first meets the conditions to output the valley value point.

3. The adaptive X-ray exposure triggering method based on body surface monitoring according to claim 1, characterized in that, When the treatment site is a rigid site, a real-time rigid body registration method with integrated geometric self-checking function is used, including: By performing rigid body registration between the reference point set and the current point set, the overall motion of the target area is calculated, and the real-time position error of the target point is calculated. Simultaneously, the geometric self-checking logic of the marked area is run in parallel to calculate the distance between each marked area in real time. If all the spacing changes are within the threshold but the overall error exceeds the limit, it is determined to be real movement and an X-ray trigger signal is generated. If the spacing of some areas changes drastically, it is determined to be local skin sliding and the X-ray trigger signal is suppressed.

4. The adaptive X-ray exposure triggering method based on body surface monitoring according to claim 1, characterized in that, For static treatment of the head and neck, the surface markers selected are relatively rigid landmarks in the midline of the forehead and the bilateral brow ridges, and the monitoring data includes the six-degree-of-freedom rigid displacement of the skull.

5. The adaptive X-ray exposure triggering method based on body surface monitoring according to claim 1, characterized in that, For static treatment of the chest and abdomen, the surface markers are selected from the relatively rigid thoracic region of the manubrium of the sternum or the lower edge of the costal arch. The monitoring data include the stability of the respiratory baseline and the overall body displacement.

6. The adaptive X-ray exposure triggering method based on body surface monitoring according to claim 1, characterized in that, For static pelvic treatment, the pelvic triangle formed by the bilateral anterior superior iliac spines and pubic symphysis is selected as the surface marker, and the monitoring data includes the six-degree-of-freedom rigid displacement of the pelvis.

7. The adaptive X-ray exposure triggering method based on body surface monitoring according to claim 1, characterized in that, For dynamic respiratory tracking therapy targeting the lungs or liver, surface markers are selected from relatively rigid areas of the chest or upper abdomen, and monitoring data includes multidimensional characteristic parameters of respiratory waveforms.

8. An adaptive X-ray exposure triggering system based on body surface monitoring, characterized in that, The system is used to implement the method as described in any one of claims 1-7, comprising: The data acquisition module is configured to acquire body surface markers and, after the initial X-ray image-guided positioning verification is passed, acquire the signals of the body surface markers to construct a reference template; The signal processing module is configured to perform calculations based on real-time acquired body surface signals during treatment to obtain characteristic parameters for judgment. The adaptive hierarchical triggering module is configured to comprehensively determine whether to trigger X-ray exposure based on the aforementioned feature parameters and through a hierarchical triggering mechanism that integrates instantaneous signal features, trend features, and timing information. The hierarchical triggering mechanism includes at least two decision logics: (1) When the displacement or baseline signal instantaneously exceeds the preset high threshold, X-ray exposure is immediately triggered; (2) When the parameters after smoothing and filtering continuously exceed the preset threshold for a preset duration, X-ray exposure is triggered; (3) When the time since the last X-ray exposure exceeds the preset maximum time interval, X-ray exposure is forcibly triggered; (4) In the dynamic respiratory tracking treatment mode, when the uncertainty index of the position prediction model exceeds the preset threshold, X-ray exposure is triggered.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the adaptive X-ray exposure triggering method based on body surface monitoring as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the adaptive X-ray exposure triggering method based on body surface monitoring as described in any one of claims 1 to 7.

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