Morphology-driven two-dimensional Cine-MRI small intestine movement evaluation method

Abstract

The invention is suitable for the technical field of medical signal processing, and provides a form-driven two-dimensional Cine-MRI small intestine movement assessment method. The method shows a multi-dimensional remarkable effect in the aspects of quantitative evaluation and clinical application of small intestine movement. According to the method, enteric cavity geometric continuity is taken as a constraint, a closed space-time shell without holes is reconstructed through automatic segmentation, space-time screening and a weighted level set, time-consistent center lines are extracted and optimized, cavity wall movement is converted through radiation coding, and four types of quantitative indexes are constructed. According to the method, health and disease groups can be distinguished, the parameter difference is remarkable, the consistency with expert labeling is high, a reviewable quantitative baseline can be provided for curative effect follow-up visit, complementation with an MRE index can be achieved, and the comprehensive evaluation stability of the small intestine is improved. The method has the advantages that the acquisition protocol does not need to be changed, the equipment sensitivity is low, the single GPU performs near-real-time processing and is easy to integrate, a multi-module system can be constructed to adapt to the DICOM process, meanwhile, real deformation and interference factors can be distinguished, and the result reliability is guaranteed.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of medical signal processing, and particularly relates to a shape-driven two-dimensional Cine-MRI small intestine movement evaluation method. BACKGROUND

[0002] In recent years, the role of Cine-MRI in small intestine movement evaluation has been continuously improved. Its advantages lie in the absence of ionizing radiation, a large coverage range, high time resolution, and compatibility with conventional abdominal examination procedures. Clinical studies have shown that under the conditions of two-dimensional sequences with exhalation breath holding, a time span of at least 15-20 seconds and a time resolution of no less than 1 frame / s can stably observe one or several peristaltic cycles. Under these acquisition conditions, Cine-MRI has good visualization ability for movement patterns such as propulsion, segmentation, retardation, or disorder. In addition to Cine-MRI, current techniques for small intestine movement evaluation include pressure measurement, radionuclide imaging, and capsule endoscopy. However, these techniques all have obvious limitations: pressure measurement is limited to local assessment and cannot achieve large-scale evaluation; radionuclide imaging is limited by time resolution and cannot accurately capture dynamic changes; and capsule endoscopy is limited by morphological details and cannot clearly present relevant morphological features, making it difficult for all three to balance "range-resolution-explainability".

[0003] Although two-dimensional Cine-MRI has advantages, its quantification has long been subject to two types of physical constraints: first, due to insufficient local intestinal lumen expansion, there may be discontinuous segments in the time sequence, forming "holes" in the space-time domain, leading to distortion in registration or lumen diameter estimation; second, the displacement of the intestinal tract in the cross-layer direction can be manifested as "false contraction" on a single slice, which is easily misjudged as "contraction-dilation", leading to ambiguity in intensity optical flow methods after brightness compensation. In recent years, although there have been productized attempts based on "motion heat maps" or intensity change fields for compensation, when factors such as contrast agent dynamics, respiratory motion, cross-device differences, and brightness drift are superimposed, the pixel intensity consistency assumption is easily invalidated, and the correspondence of the same intestinal loop on the time axis may also be destroyed, leading to subsequent statistical analysis only being able to stay at the global average level, lacking local reliability. In addition, existing registration methods based on intensity consistency cannot distinguish between true tissue movement and brightness changes, further introducing systematic errors.

[0004] In view of the above problems of existing methods, it is necessary to establish a "shape-anchored" space-time geometric representation and index system around two-dimensional Cine-MRI, so that it remains repeatable under cross-center and cross-device conditions, becoming a more practical approach. Therefore, the present application proposes a shape-driven two-dimensional Cine-MRI small intestine movement evaluation method. SUMMARY

[0005] The purpose of this invention is to provide a morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility, aiming to solve the problems mentioned in the background art.

[0006] The objective of this invention is achieved through the following technical solution: A morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility includes the following steps: Automatic segmentation and spatiotemporal filtering: The small intestine segmentation network based on JointSwinUNETR is used to automatically segment the complete time series of two-dimensional Cine-MRI images and generate a binarized three-dimensional mask; the connected regions obtained by segmentation are marked in three-dimensional space, and the connected region with the largest number of voxels is retained as the quantization target region; Spatiotemporal shell reconstruction and centerline extraction: Using frame-by-frame segmentation results as data items, the weighted minimum surface energy is minimized in the spatiotemporal domain. Stable conserved difference is used to achieve numerical calculation. The calculation stops when the energy decreases to a set threshold or the upper limit of iteration. At this time, the zero level set is defined as a closed spatiotemporal shell. Through shortest path optimization and inter-frame smoothing constraints, temporally consistent cavity centerlines are extracted from the spatiotemporal shell. After B-spline fitting of the extracted centerlines, equal arc length resampling is performed to obtain a smooth and structurally stable centerline sequence. Radiation coding and core index construction: Taking each node in the centerline sequence as the source point, equiangular rays are emitted outward, and the intersection points of the rays with the spatiotemporal shell boundary are recorded. The average value of the distance and direction of the intersection points is calculated to obtain the radial length and phase, which together constitute the spatiotemporal matrix characterizing the small intestinal motility state. Based on the radial length and phase, four types of indicators are extracted: amplitude dominance, synchronicity, spatial heterogeneity, and rhythm stability, and a quantitative index system for evaluating small intestinal motility is constructed.

[0007] Furthermore, the small intestine segmentation network based on JointSwinUNETR consists of a local sequential encoder, a global multi-scale encoder, and a spatial sequential hybrid decoder.

[0008] Furthermore, the calculation of the weighted minimum surface energy follows the formula below: ; in, The weighted minimum surface energy; It is a 2-dimensional spatial domain; For the time domain; For smoothing the Heaviside function; for difference; Spatial coordinates; For a specific moment; The weights are differential proportions; To increase the confidence weight of reliable region fit; For segmentation mask.

[0009] Furthermore, the radial length and phase are calculated using the following formulas: ; ; in, Radial length; For phase; The total number of rays; For the first ray; Center Online point t Time of the first Length of the ray; Center Online point t Time of the first The direction angle of the ray.

[0010] Furthermore, the amplitude dominance is constructed by calculating cumulative energy, which measures the kinetic energy generated from the previous... K The proportions explained by each main model depict the dominance and energy concentration of the main model.

[0011] Furthermore, the synchronicity is calculated using Kuramoto order, and the time mean of Kuramoto order is taken as the synchronicity index to measure the degree of phase synchronization of different spatial locations of the small intestine throughout the entire time series. The larger the index value, the stronger the synchronicity.

[0012] Furthermore, the spatial heterogeneity is calculated using the Laplacian of the chain graph to determine the spatial roughness of each frame. After normalizing the spatial roughness, the time mean is taken to obtain the spatial heterogeneity index. The larger the index value, the stronger the local inconsistency and the lower the compliance.

[0013] Furthermore, the rhythm stability is obtained by performing Vietoris-Rips filtering on the point cloud and then performing persistent cohomology analysis to obtain the birth and death pair thresholds of one-dimensional loop features. The lifetime of all one-dimensional loop features is aggregated to obtain a rhythm stability index. The larger the index value, the stronger the topological stability of the small intestinal motility rhythm under multi-scale distance thresholds.

[0014] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0015] An electronic device includes 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 perform the steps of the method described above.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention proposes a morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility, which demonstrates significant multi-dimensional effects in the quantitative assessment and clinical application of small bowel motility.

[0017] At the core technical level, it takes the geometric continuity of the intestinal lumen as a key constraint. After automatically segmenting and generating a three-dimensional mask, it retains the continuous intestinal loops through spatiotemporal screening. Then, it uses weighted level sets to reconstruct a closed spatiotemporal shell without holes, repairing the original mask breakage problem. At the same time, it extracts and optimizes the time-consistent centerline, laying a precise geometric foundation for subsequent analysis. Subsequently, it uses radiation coding to transform the lumen wall motion into a spatiotemporal matrix of "radial length" and "phase", and then constructs four complementary indicators: amplitude dominance, synchronicity, spatial heterogeneity and rhythm stability, to achieve a comprehensive quantification of the small intestine's motility. Moreover, the indicator definitions and physical meanings are clearly corresponding, which is convenient for reporting and decision support.

[0018] In terms of clinical application value, this method performs excellently in distinguishing between healthy and disease groups. The parameter distributions of the two groups are significantly different and linearly separable, and the consistency with the annotations of imaging experts is high. It can serve as an important basis for clinically distinguishing between small bowel health and lesions. At the same time, it provides a verifiable quantitative baseline for efficacy follow-up and can complement MRE indices (such as MaRIA and Clermont) to improve the stability of comprehensive small bowel assessment.

[0019] In terms of technology implementation and promotion, it only relies on conventional two-dimensional Cine-MRI acquisition, without changing the acquisition protocol. The key parameter range is clear, and it is not sensitive to equipment and centers, which is conducive to multi-center reuse. It adopts a lightweight segmentation backbone and analytical geometric computing, and a single GPU can achieve near real-time processing. The interface is unified and easy to integrate into research stations. It can also build a system with multiple modules (segmentation and screening module - level set shell module - centerline alignment module - radiometric coding and index module - reporting module) to form an independent quantitative assessment terminal or hospital server. It is compatible with the standard DICOM process and has the ability to implement hardware and software in an integrated manner.

[0020] Furthermore, this method uses the geometric shell and centerline as anchor points to effectively distinguish between real deformation and brightness changes and layer loss, avoids the influence of contrast agents, breathing and cross-device conditions on the strength model, eliminates ambiguity, and ensures the reliability of the evaluation results. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the technical process of the present invention.

[0022] Figure 2 The graph shows the effect of using motion description indicators for clinical classification; where a is a box plot and b is a confusion matrix. Detailed Implementation

[0023] In order to provide a clearer understanding of the technical features, objectives and beneficial effects of the present invention, the technical solution of the present invention will now be described in detail below, but it should not be construed as limiting the scope of implementation of the present invention.

[0024] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0025] This invention provides a morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility, the flowchart of which is shown below. Figure 1 As shown, this method begins with frame-by-frame segmentation to obtain the small intestinal mask; maximum connected component (3D-LCC) screening is performed in the space-time voxel domain, retaining only intestinal loops that remain coherent throughout the sequence, and stable analysis regions are then trimmed accordingly. Subsequently, a closed, pore-free spatiotemporal shell is reconstructed in the (x,y,t) domain based on weighted level sets, allowing the cavity walls to transition naturally in time; a temporally consistent centerline is extracted inside the shell and resampled with equal arc lengths. An isoangular radiation ray is emitted with the centerline as a reference, and the intersection points with the shell boundary are recorded to obtain the spatiotemporal matrices of "radial length" and "phase"; based on this, indices such as amplitude dominance (PMC), synchronicity (MSI), spatial heterogeneity (LS), and rhythmic stability (PHI) are constructed. Finally, a lightweight model is used to determine small intestinal health or disease based on motility. The specific process is as follows: I. Automatic segmentation and spatiotemporal filtering; Automatic small intestine segmentation: A small intestine segmentation network based on JointSwinUNETR is used to automatically segment complete time-series 2D Cine-MRI images, generating a binarized 3D mask. This network consists of a local sequential encoder, a global multi-scale encoder, and a spatial sequential hybrid decoder, which can effectively balance fine-grained and large-scale features, thereby achieving high-precision segmentation.

[0026] Spatiotemporal filtering: The segmented connected regions are marked in three-dimensional space, and the connected region with the largest voxel number is retained as the quantization target region.

[0027] II. Spatiotemporal shell reconstruction and centerline extraction; Spatiotemporal shell reconstruction: Using the results obtained from frame-by-frame segmentation as data items, the weighted minimum surface energy is minimized in the spatiotemporal domain (x,y,t). The energy calculation follows the formula: ; in, The weighted minimum surface energy; It is a 2-dimensional spatial domain; For the time domain; For smoothing the Heaviside function; for difference; Spatial coordinates; For a specific moment; The weights are differential proportions; As a confidence weight, it is used to improve the fit of reliable areas and suppress noise and holes; The segmentation mask is used. The numerical implementation adopts a stable conserved difference. The calculation stops when the energy decreases to a set threshold or the upper limit of iteration. At this time, the zero level set is defined as a closed "spacetime shell". This shell allows the small intestinal wall to transition naturally in the time dimension, without holes and with a complete structure.

[0028] Centerline extraction: Through shortest path optimization and inter-frame smoothing constraints, temporally consistent cavity centerlines are extracted from the spatiotemporal shell. The extracted centerlines are then fitted with B-splines and resampled with equal arc lengths to obtain a smooth and structurally stable centerline sequence, providing an accurate reference benchmark for subsequent radiometric coding.

[0029] III. Radiation Coding and Construction of Core Indicators; Radiation coding: Using each node in the centerline sequence as the source point, radiation is emitted outwards. M An isoangular ray is used to record the intersection points of the ray with the spacetime shell boundary. The radial length is obtained by calculating the average of the distance and direction of the intersection points. With phase The calculation formulas are as follows: ; ; in Used to describe the spatiotemporal variation of cavity diameter, The phase coordination characteristics used to characterize small intestinal motility, together with the phase coordination characteristics, constitute a spatiotemporal matrix characterizing the state of small intestinal motility. The total number of rays; For the first ray; Center Online point t Time of the first Length of the ray; Center Online point t Time of the first The direction angle of the ray.

[0030] Core metric construction: based on radial length With phase Four complementary indices were extracted: amplitude dominance (PMC), synchronicity (MSI), spatial heterogeneity (LS), and rhythm stability (PHI). These indices quantify small intestinal motility from different dimensions. The calculation logic and correlation formulas for each index are as follows: ① Amplitude Dominance (PMC): This index is constructed by calculating cumulative energy. Used to measure the energy of motion from the previous K The proportions explained by each principal model characterize the dominance and energy concentration of the principal model; among them The total number of energy modes; This is the kth pattern; Amplitude; This represents the total number of sampling points along the center line. This represents the total number of frames.

[0031] ② Synchronicity (MSI): with For each spatial location i At any moment t The motion phase is determined using Kuramoto order. Its time average It is used to measure the degree of phase synchronization of different spatial locations of the small intestine throughout the entire time series. (The larger the value, the more synchronized the data). This represents the total number of sampling points along the center line. Spatial coordinates; It is the direction angle; These are equivalent phases; For equivalent modulus; Total number of frames; For a moment.

[0032] ③ Spatial Heterogeneity (LS): Laplace's expression in a chain diagram L Calculate the spatial roughness of each frame After normalizing to energy, the time average is obtained. LS This is used to characterize the spatial heterogeneity of radial variation (a larger value indicates stronger local inconsistency and lower compliance); among which Let be the combined vector of ray lengths at time t; for The transpose of .

[0033] ④ Rhythm Stability (PHI): For point clouds { , Vietoris-Rips filtering was performed on the ,t / T)}, followed by persistent cohomology analysis to obtain the birth and death pair thresholds of one-dimensional loop features ( , );in The birth threshold; The death threshold is defined as the aggregated lifetime of all one-dimensional loop features to obtain the index. This is used to quantify the topological stability of small intestinal motility rhythms under multi-scale distance thresholds (the larger the sum, the more stable the rhythm).

[0034] Using four complementary indices—PMC, MSI, LS, and PHI—a lightweight model was employed to differentiate between healthy and disease groups based on small intestinal motility. The results, as seen in the box plot, demonstrate... Figure 2 (a) The parameter distributions obtained using this method show significant differences between the disease group and the healthy group. The parameters in the disease group are generally lower than those in the healthy group, and the parameters of the two groups are not overlapping and are linearly separable, indicating that the motion quantification method has good discriminative power. The confusion matrix can characterize the consistency between the health and disease discrimination results based on motion parameters and the annotations by imaging experts. The results show that (a) Figure 2 (b) In the figure, there are 25 cases with a true label of 0 (corresponding to the healthy group) and a predicted label of 0, and 30 cases with a true label of 1 (corresponding to the disease group) and a predicted label of 1. This shows that the method is in good agreement with the expert score, proving that it has high clinical application value.

[0035] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent.

Claims

1. A morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility, characterized in that, Includes the following steps: Automatic segmentation and spatiotemporal filtering: The small intestine segmentation network based on JointSwinUNETR is used to automatically segment the complete time series of two-dimensional Cine-MRI images and generate a binarized three-dimensional mask; the connected regions obtained by segmentation are marked in three-dimensional space, and the connected region with the largest number of voxels is retained as the quantization target region; Spatiotemporal shell reconstruction and centerline extraction: Using frame-by-frame segmentation results as data items, the weighted minimum surface energy is minimized in the spatiotemporal domain. Stable conserved difference is used to achieve numerical calculation. The calculation stops when the energy decreases to a set threshold or the upper limit of iteration. At this time, the zero level set is defined as a closed spatiotemporal shell. Through shortest path optimization and inter-frame smoothing constraints, temporally consistent cavity centerlines are extracted from the spatiotemporal shell. After B-spline fitting of the extracted centerlines, equal arc length resampling is performed to obtain a smooth and structurally stable centerline sequence. Radiation coding and core index construction: Taking each node in the centerline sequence as the source point, equiangular rays are emitted outward, and the intersection points of the rays with the spatiotemporal shell boundary are recorded. The average value of the distance and direction of the intersection points is calculated to obtain the radial length and phase, which together constitute the spatiotemporal matrix characterizing the small intestinal motility state. Based on the radial length and phase, four types of indicators are extracted: amplitude dominance, synchronicity, spatial heterogeneity, and rhythm stability, and a quantitative index system for evaluating small intestinal motility is constructed.

2. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The small intestine segmentation network based on JointSwinUNETR consists of a local sequential encoder, a global multi-scale encoder, and a spatial sequential hybrid decoder.

3. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The calculation of the weighted minimum surface energy follows the formula below: ； in, The weighted minimum surface energy; It is a 2-dimensional spatial domain; For the time domain; For smoothing the Heaviside function; for difference; Spatial coordinates; For a specific moment; The weights are differential proportions; To increase the confidence weight of reliable region fit; For segmentation mask.

4. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The radial length and phase are calculated using the following formulas: ； ； in, Radial length; For phase; The total number of rays; For the first ray; Center Online point t Time of the first Length of the ray; Center Online point t Time of the first The direction angle of the ray.

5. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The amplitude dominance is constructed by calculating cumulative energy, which measures the kinetic energy generated from the previous... K The proportions explained by each main model depict the dominance and energy concentration of the main model.

6. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The synchronicity is calculated using Kuramoto order, and the time mean of Kuramoto order is taken as the synchronicity index to measure the degree of phase synchronization of different spatial locations of the small intestine in the entire time series. The larger the index value, the stronger the synchronicity.

7. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The spatial heterogeneity is calculated using the Laplacian of the chain graph to determine the spatial roughness of each frame. After normalizing the spatial roughness, the time mean is taken to obtain the spatial heterogeneity index. The larger the index value, the stronger the local inconsistency and the lower the compliance.

8. The morphology-driven two-dimensional Cine-MRI method for assessing small bowel motility according to claim 1, characterized in that, The rhythm stability is obtained by performing Vietoris-Rips filtering on the point cloud and then performing persistent cohomology analysis to obtain the birth and death pair thresholds of one-dimensional loop features. The lifetime of all one-dimensional loop features is aggregated to obtain the rhythm stability index. The larger the index value, the stronger the topological stability of the small intestinal motility rhythm under multi-scale distance thresholds.

9. 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 method as described in any one of claims 1-8.

10. 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 method as described in any one of claims 1-8.

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