Spinal surgery planning method based on one-dimensional images

Abstract

The present invention provides a spinal surgery planning method based on one-dimensional images, minimizing radiation exposure and enabling the calculation of the shortest path to a target site and the insertion length and angle of a needle, only from one-dimensional images, without an adjustment process using a calibrator in spinal surgery planning.

Description

A one-dimensional image-based spinal surgery planning method

[0001] The present invention relates to a method for planning spinal surgery, and more particularly, to a one-dimensional image-based spinal surgery planning method.

[0002] The spine, the central structure of our body, serves as a pillar, supporting the head above and connecting to the pelvis below. Our body is composed of 33 vertebrae. The muscles surrounding the spine support and protect it, enabling movement. The spine contains seven types of ligaments, made of elastic fibers that protect and maintain balance. Blood vessels and the spinal nerves also distribute sensory information to the brain and relay commands from the brain to other tissues. The spine is not a straight line, but rather a gentle S-shaped curve. Intervertebral discs connect the spine, allowing it to expand and absorb shock depending on the direction of movement. Various causes, such as a decrease in height or displacement between vertebrae, weaken the interconnected vertebrae, leading to various spinal disorders, including disc herniation, spinal stenosis, and spondylolisthesis. To correct such unstable vertebrae, spinal fusion surgery is performed to connect and fix the vertebrae into a single spine. This requires determining the appropriate length and diameter of the pedicle screw depending on the patient and the surgical site, and planning the insertion location and path. In this regard, Korean Patent No. 2394901 discloses a device and method for planning spinal surgery based on two-dimensional medical images.

[0003] However, the above prior art may be inefficient because it requires an alignment procedure using a calibrator for spinal surgery planning, which may expose the patient to excessive radiation.

[0004] The present invention aims to solve various problems, including the above-described problems, by providing a one-dimensional image-based spinal surgery planning method that minimizes radiation exposure and can calculate the shortest path to a target area and the insertion length and angle of a needle using only one-dimensional images without the need for an adjustment procedure using a corrector during spinal surgery planning. However, these tasks are exemplary and the scope of the present invention is not limited thereby.

[0005] According to one aspect of the present invention, there is provided a step of acquiring a one-dimensional spinal image of a patient requiring spinal surgery;

[0006] A feature point designation step of identifying the location of the vertebral body in the spinal image and designating feature points of the vertebral body using a pre-learned U-net structure;

[0007] Step of setting a virtual coordinate space for the target area based on the above-mentioned feature points:

[0008] A step of deriving a triangular point by applying the coordinate values ​​of the above virtual coordinate space to a trigonometric function;

[0009] A step of calculating the insertion length and angle of the needle from the entry point to the target site from the above triangulation point; and

[0010] A method for planning spinal surgery is provided, which includes a planning completion step of determining the length, diameter, etc. of a pedicle screw and determining a plan for the insertion location and path.

[0011] The one-dimensional image-based spinal surgery planning method of the present invention, as described above, finds anatomical landmarks on an X-ray AP (Anterior-Posterior) without a corrector, thereby minimizing additional radiation exposure, enabling more accurate surgery planning based on knowledge of pre-learned structures, and enabling smooth performance of the targeted surgery according to the surgery planning, thereby enabling the rapid treatment of spinal diseases. Of course, the scope of the present invention is not limited by these effects.

[0012] Figure 1 is a schematic diagram (left) and a photograph (right) showing a pedicle screw inserted into a vertebral body in spinal fusion surgery.

[0013] Figure 2 is a photograph showing an AP X-ray view of a patient requiring spinal fusion. The red dot indicates the pedicle, and the yellow dot indicates the spinous process.

[0014] Figure 3 is a schematic diagram illustrating the schematic structure of the vertebral body plane. In the drawing, α1 and α3 represent pedicles, and α2 represents the spinous process. In the spinal cord surgical planning method of the present invention, the red dot (α3) represents the target site.

[0015] Figure 4 is a schematic diagram showing the schematic structure of the posterior portion of the vertebral body. In the drawing, the red dot (α3) indicates the target area.

[0016] Figure 5 is a schematic diagram schematically showing a configuration for calculating the insertion length and angle of a surgical needle using trigonometric functions based on a planar image of the vertebral body.

[0017] Figure 6 is a schematic diagram showing the shortest path to the target site when inserting a needle in the spinal surgery planning method of the present invention.

[0018] Figure 7 is a flowchart showing the procedure of the spinal surgery planning method of the present invention step by step.

[0019] Figure 8 is an AP image and an LL image showing the fixation of a pedicle screw in spinal fusion.

[0020] Figure 9 is a schematic diagram showing the angle of the screw thread for estimating the angle between the screw and the patient's vertebral plane based on the change in distance of the thread.

[0021] Figure 10 is a schematic diagram showing the angle of the screw thread for estimating the angle between the screw and the plane of the patient's vertebral body based on the change in the distance of the thread.

[0022] Glossary of terms:

[0023] The term "spinal fusion" used in this document refers to a fundamental treatment method that removes all diseased discs between the vertebrae, inserts a disc-shaped support called a cage between them, and fixes them with screws to stabilize and treat unstable spinal segments. It is performed by surgically immobilizing two or more adjacent vertebrae, and is performed following the removal of lesions such as spinal caries or spinal tumors, or to resolve spinal instability such as vertebral dislocation fractures, spondylolysis, and spondylolisthesis. The latter method is also used in cases of herniated discs and cervical spondylosis. The methods include anterior fixation, which invades the vertebral body from the front, and posterior fixation, which invades the laminae, facet joints, and spinous processes from the back. Recently, the latter method has also been used to fix the intertransverse process.

[0024] The term "U-net" used in this document refers to the most fundamental deep learning architecture in the field of image semantic segmentation. In the present invention, a variant of the artificial intelligence CNN is optimized for specific object recognition. In the AP imaging situation of a C-arm, where various noises may be present, the algorithm identifies the locations of spinous processes and pedicles of interest. This model takes a 2D image as input and predicts a class (e.g., spine, intervertebral disc, etc.) for each pixel.

[0025] The term "intervertebral foramen" used in this document refers to the space between the vertebrae through which the spinal cord emerges. The spinal cord passes through these openings, connecting the spinal canal with the bodies on either side. Furthermore, although the upper and lower parts of the sacrum are fused together and not readily visible from the outside, foramina of the same name extend from the sacral canal on both sides, connecting to the anterior and posterior sacral foramina, through which the spinal cord also passes.

[0026] Detailed description of the invention:

[0027] According to one aspect of the present invention, there is provided a step of acquiring a one-dimensional spinal image of a patient requiring spinal surgery;

[0028] A feature point designation step of identifying the location of the vertebral body in the spinal image and designating feature points of the vertebral body using a pre-learned U-net structure;

[0029] Step of setting a virtual coordinate space for the target area based on the above-mentioned feature points:

[0030] A step of deriving a triangular point by applying the coordinate values ​​of the above virtual coordinate space to a trigonometric function;

[0031] A step of calculating the insertion length and angle of the needle from the entry point to the target site from the above triangulation point; and

[0032] A method for planning spinal surgery is provided, which includes a planning completion step of determining the length, diameter, etc. of a pedicle screw and determining a plan for the insertion location and path.

[0033] In the above planning method, the feature point designation step

[0034] A step of training the model using spinal image data with specified feature points marked after preparing the UNET model;

[0035] A step of extracting feature point location information from the model through the above training;

[0036] A step of representing the above feature point location information as a specific pixel location in a spine image; and

[0037] It may include a step of identifying and analyzing the structure of the vertebral body by interpreting the location information of the above-mentioned feature points.

[0038] In the above planning method, the structure of the vertebral body may be a spinous process, a transverse process or a pedicle, the feature point may be a position value of the spinous process, the first pedicle or the second pedicle of the vertebral body, and the planning completion step may include the shortest path from the entry point to the target site.

[0039] In the above planning method, the triangulation point refers to a point for calculating a path to a target point such as a pedicle or foramen based on the coordinates of the cutting edge of the spinous process and transverse process of the vertebral body, which are known in advance. For example, the path can be calculated by applying triangulation, and the triangulation method means "a method of finding the coordinates and distance to the point by measuring the angles formed by the base and the other two sides of the triangle formed by the point and the two reference points, measuring the lengths of the sides, and then performing a series of calculations using the law of sines, etc., when a point and two reference points are given."

[0040] In the above planning method, the one-dimensional image may be an X-ray (C-arm) or a spine CT, and the spinal surgery may be a spinal fusion, an endoscopic spinal surgery, or a minimally invasive spinal surgery, and the spinal fusion may be selected from the group consisting of a transforaminal lumbar interbody fusion (TLIF), a posterior lumbar interbody fusion (PLIF), anterior lumbar interbody fusion (ALIF), and a direct lumbar interbody fusion (DLIF).

[0041] Hereinafter, the present invention will be described in more detail through examples. However, the present invention is not limited to the examples disclosed below, but can be implemented in various different forms. The following examples are provided to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention.

[0042] In the case of patients with severe symptoms that are difficult to treat with non-surgical treatments, such as spinal diseases such as spinal stenosis, herniated disc, scoliosis, or degenerative kyphosis, spinal fusion is generally performed by approaching from the back to restore and fix the vertebral body due to the nature of the thoracic spine being protected by the sternum. This surgery inserts pedicle screws at both ends of the affected vertebrae and fixes them together to prevent abnormal movement between the vertebrae and eliminate the resulting pain. Unlike the cervical or lumbar vertebrae, the thoracic vertebrae are protected by the sternum, and the height of the intervertebral discs is low and the space for the neural passages is small, so the thoracic vertebrae are generally approached from the back (dorsal) rather than the anterior. Figure 1 is a drawing (left) and a photograph (right) showing a pedicle screw inserted into a vertebral body during spinal fusion. For these spinal conditions, it is preferable to avoid surgery and instead seek treatment. However, spinal fusion should be performed only in limited cases, such as stenosis with spinal instability and spondylolysis. Spinal fusion is a widely used surgical procedure that uses screws to fix dislocated vertebrae back into their normal positions. It requires minimal skin incision, significantly less muscle damage compared to conventional surgery, and a transforaminal approach reduces the risk of nerve damage. Spinal fusion requires determining the appropriate length and diameter of pedicle screws for each patient and surgical site, and planning the insertion location and path. An axial view of the spine is optimal for surgical planning for pedicle screw fixation. Traditionally, preoperative computed tomography (CT) scans were used to provide the surgeon with axial images, allowing for surgical planning based on these images.The conventional planning method based on the above CT image has the advantage of being able to perform planning on axial images, but has the problem of being harmful to the human body due to long-term exposure to radiation during CT scanning.

[0043] Specifically, in order to perform a root block (nerve root block), which is one of the pain blocks that injects painkillers into the relevant nerve segments during spinal surgery planning to treat spinal diseases such as spinal fusion, the conventional technique is to roughly identify the location based on the doctor's experience by observing the cross-section of the structure with ultrasound under the AP image of X-ray (C-arm) or sono guide, and target the anatomical landmark. After identifying the location of the affected area, a needle can be inserted through the back to avoid the lateral processes and inject the drug into the intervertebral foramen, which is the space between the vertebrae through which the spinal nerves exit.

[0044] Typically, needles are inserted while viewing the ultrasound and X-ray (C-arm) in real time. However, X-rays require continuous radiation exposure during the insertion process while checking the front and side, and ultrasound requires skilled experience on the part of the doctor because it must be performed with one hand. In the case of conventional spinal surgery planning, a process of adjusting the image of the target area by taking a calibrator together with the image, that is, a process of matching the 2D image to the surgical space is required. This is because the alignment is not accurate when the images are virtually superimposed after taking the images. However, there is a possibility of being exposed to excessive radiation during the process of matching with the calibrator, and in the case of sono-guided (ultrasound-guided) spinal nerve root block, when blocks are to be performed in multiple segments, each segment must be targeted and the pain injection (pain block) must be placed in multiple places as the probe is used to explore, which is a problem that consumes time and resources. However, the one-dimensional image-based spinal surgery planning method of the present invention replaces the two-dimensional image of the above-mentioned registration process with only one-dimensional X-ray (C-arm) or a previously taken spine CT, so that an image for surgery planning only needs to be taken once and a CT image taken for preoperative diagnosis can be used, thereby minimizing additional radiation exposure for surgery planning while calculating the length and angle of the insertion needle to target the spinal nerve root of the vertebral foramen through the shortest path.

[0045] Fig. 2 is a photograph showing an X-ray AP view of a patient requiring spinal fusion. The red dot represents a pedicle, and the yellow dot represents a spinous process. The surgical planning method of the present invention uses U-net to find feature points, establishes a virtual coordinate space, and calculates the insertion length and angle of a needle to effectively insert a pain block into the tip of the transverse process and the intervertebral foramen or insert a percutaneous pedicle screw. Both the transverse process and the spinous process can be used for accurate alignment, and in the case of the cutting edge selected as the feature point, the tip points of the transverse process and the spinous process, which are features of the spinal structure, are not limited to the above processes, but as an embodiment of the present invention, the tip points of the transverse process and the spinous process, which are features of the spinal structure, can be replaced with calibration markers and utilized.

[0046] As described above, the surgical planning method of the present invention can target the intervertebral foramen using only AP, unlike the conventional technology that utilizes AP (anteroposterior) and lateral images based on process feature points determined without a corrector, and can be used to calculate the position and distance of the insertion device when performing spinal fusion using pedicle screws as well as endoscopic spinal surgery. The endoscopic spinal surgery removes the cause of pain by inserting an endoscope and a treatment device through two small incisions of about 5 mm, and then checking the lesion from various angles with the endoscope. Although the incisions are small, the use of an endoscope allows for a magnified confirmation of the lesion and its surrounding tissues, enabling much more precise surgery.

[0047] The present invention can set up a virtual coordinate space of relative values ​​(ratios) based on feature points designated in advance through a CT image of the spine for spinal surgery planning, and if two points at different locations are known on one plane (x, y-axis information), the z-axis from where the other point is located to the target point can also be calculated. In addition, during spinal fusion surgery, the CT or AP image of the patient in question can be reconstructed into a spine CT, and even if there is no CT image, the insertion length and angle of a needle that can target the spinal nerve root through the shortest path can be estimated without a correction procedure using only the AP lateral image. At this time, the spinal fusion may be selected from the group consisting of, but is not limited to, transforaminal lumbar interbody fusion (TLIF), posterior lumbar interbody fusion (PLIF), anterior lumbar interbody fusion (ALIF), and direct lumbar interbody fusion (DLIF).

[0048] Hereinafter, a method for calculating the needle insertion length and angle of the one-dimensional image-based spinal surgery planning method of the present invention will be described through the following examples.

[0049] Example 1: Calculating the insertion length and angle of the needle

[0050] As an example of the one-dimensional image-based spinal surgery planning method of the present invention, the needle insertion length and angle can be calculated using trigonometric functions as follows. First, Fig. 3 is a plan view showing the structure of the vertebral body in a three-dimensional plane, and based on the plan view, α1 represents the right pedicle, α2 represents the spinous process, α3 represents the left pedicle, and the circular structure represents the vertebral body. In addition, the direction of the spinous process points dorsally, and the vertebral body points ventrally. In addition, Fig. 4 is a front view looking from the dorsal side showing the structure of the vertebral body, and the positions of α1 to α3 are the same as in Fig. 3. If the y-axis information of α1 to α3 of Fig. 3 is known in advance, the y-axis change value according to the x-axis movement value in Fig. 4 can be mathematically predicted, and this can be calculated with reference to the trigonometric function configuration of Fig. 5. For example, if the above α3 (indicated by a red dot) is a target, the orthogonal plane constant (α2-α3) of FIG. 4 can be calculated by applying the following equation 1 according to the needle insertion length (Da) and the external incident angle (a).

[0051] (Formula 1)

[0052] Da·cos a = Xa - α3 = O (observed value)

[0053] Da·sin a = α2 y - α3 y = K (base value)

[0054]

[0055] Since the shape of the vertebral body varies slightly for each surgical patient, once the triangulation point is derived according to the above formula, the needle entrance length and angle corresponding to the shortest distance from the back to the target area can be estimated. At this time, the vertebral body is divided into left and right based on the back, but it can be divided into the first and second pedicles without distinction between left and right at points symmetrical to the left and right based on the center of the intervertebral foramen.

[0056] In addition, in the same way, the optimized root block skin incidence angle and length can be calculated by applying the principle of rotation transformation using the transformation and inverse matrix of the three-dimensional matrix based on the coordinates of the feature point at the y-axis end (top) of the spinous process and the center of the target intervertebral foramen in the three-dimensional structure. The application of the principle of rotation transformation using the transformation and inverse matrix of the three-dimensional matrix will be described. First, the coordinates of the feature point at the y-axis end (top) of the spinous process and the center of the intervertebral foramen are obtained. The coordinates of the feature point at the y-axis end (top) of the spinous process and the center of the intervertebral foramen are measured or calculated. Thereafter, the coordinates are used to determine the incidence angle and length of the root block skin based on the rotation transformation.

[0057] The composition of the rotation transformation matrix is ​​explained. The rotation transformation is a transformation that rotates an object in three-dimensional space by a desired angle, and this can be expressed as a matrix. The rotation matrix is ​​composed according to a given angle. For example, the transformation matrix in the case of rotation around the x-axis is as follows in Equation 2: Here, θ is the rotation angle.

[0058] (Formula 2)

[0059] R_x(θ) = | 1 0 0 |

[0060] | 0 cos(θ) -sin(θ) |

[0061] | 0 sin(θ) cos(θ) |

[0062] The transformation calculation uses the acquired rotation matrix to rotate the coordinates of the spinous process feature points relative to the coordinates of the center of the intervertebral foramen. This produces transformed coordinates. Furthermore, applying the inverse matrix requires performing a reverse rotation to return the calculated transformed coordinates to the original coordinate space. Since the inverse matrix of a rotation matrix is ​​equal to its transpose, the inverse rotation matrix is ​​given by Equation 3 below:

[0063] (Formula 3)

[0064] R_x(-θ) = | 1 0 0 |

[0065] | 0 cos(θ) sin(θ) |

[0066] | 0 -sin(θ) cos(θ) |

[0067] The coordinates obtained through the above reverse rotation are the positions of the spinous process feature points in the original space. The incidence angle and length of the spinous process can be estimated using the above coordinates.

[0068] Fig. 6 is a schematic diagram showing the shortest path from the entry point (back) to the target site during needle insertion for spinal surgery planning of the present invention. As shown, the blue arrow represents the spinous process, the red arrow represents the pedicle, the line passing from top to bottom based on point P represents the foramen, and the blue line extending from left to right represents the spinal nerve root. In the case of a root block by the one-dimensional image-based spinal surgery planning method of the present invention, the nerve root extends like a wire, and A is the back, and the shortest path for needle insertion from A to point P can avoid bone structures.

[0069] Figure 7 is a flowchart illustrating the steps of a spinal surgery planning method of the present invention. The process is described step-by-step: a 1D spinal image of a patient requiring spinal surgery is acquired (S1). This 1D spinal image may be an X-ray image or a spinal CT image. Then, using a pre-trained U-net structure, feature points for the spinous process, pedicle, and intervertebral foramen of the vertebral body can be designated (S2). The U-net consists of a contracting path and an expansive path, with a bottleneck structure in the middle. The contracting path image is downsampled to extract abstracted features, and the expansive path upsamples the extracted features to restore them to the original image size. After preparing a U-net model for model training, the model is trained using preprocessing data marked with predetermined feature points. The input is a spinal image, and the output is a mask indicating the location of the feature points. During model training, a pixel-level loss function is primarily used. After that, it goes through an inference and postprocessing process, and inference is performed on a new spinal image using the trained model. The feature point locations are extracted from the output of the model. Since the extracted feature point location information indicates a specific pixel location in the image, a task of converting it into actual coordinates may be required. The feature point location information obtained as the result of the inference is interpreted to identify and analyze structures such as the spinous process and the transverse process, and through this, information on the spinal structure is extracted, so that stereotactic functional spinal surgery and operation can be performed on a one-dimensional plane during the surgery or procedure. Therefore, the height change according to the distance change of the incident angle of a certain angle can be calculated based on the distance between the position of the tip of the spinous process and the center of the pedicle.In the step (S3) of setting a virtual coordinate space based on the above-mentioned characteristic points, the coordinate values ​​of two points with different locations known in advance on a plane can be applied to a trigonometric function to derive a triangular point (S4). After calculating the insertion length and angle of the needle from the entry point to the target site through the above-mentioned virtual coordinate space (S5), when the planned insertion path of the spinal surgical instrument (pedicle screw) is determined, the spinal surgery planning for the patient is completed (S6).

[0070] In addition, the spinal surgery planning method of the present invention enables more accurate surgery planning by providing the surgeon with three-dimensional information, such as an axial image that can be obtained from a CT (Computed Tomography) from a two-dimensional spinal image of the patient. To implement this, a two-dimensional spinal image of the surgical patient is specifically required, and a process of aligning the two-dimensional spinal image and the spinal surgery site location using a surgery planning program is required. The alignment can be performed by applying a surgery planning program including an algorithm for alignment to derive spatial coordinates for the surgical site location. At this time, the alignment method can generate spatial coordinates of the two-dimensional spinal image and align the surgical site location corresponding to the spatial coordinates using the program. In addition, alignment can be performed based on an image generated by backprojecting the two-dimensional spinal image onto another plane on the X-ray projection path. At this time, the two-dimensional spinal image may use an AP (Anterior-Posterior) or LL (Lateral-Lateral) image, but is not limited thereto.

[0071] Thereafter, based on the alignment information as described above, a surgical planning program is used to apply and superimpose a virtual three-dimensional figure to the surgical site of the two-dimensional spinal image so that it corresponds to an anatomical landmark corresponding to the target during surgery, and then a step of adjusting the shape, size, and position of the three-dimensional figure to fit the actual surgical site is performed. The surgical site location can be automatically detected and adjusted by directly inputting the corresponding location information or performing deep learning using an algorithm capable of recognizing images or videos. Thereafter, a three-dimensional image is finally generated based on the alignment information and the adjusted three-dimensional figure information and can be confirmed through a display.

[0072] The above three-dimensional image is an axial image obtained from a two-dimensional spinal image, and can provide the surgeon with an axial image of the spine most suitable for planning a pedicle screw fixation surgery, thereby increasing the accuracy and efficiency of the surgery. At this time, the algorithm can utilize a convolutional neural network (CNN), a convolutional deep belief network (CDBN), a deep belief network (DBN), or a residual network (ResNet), which are effective in extracting and classifying features from two-dimensional data of an image or video. In addition, the anatomical landmark may be a vertebra body, and the step of adjusting the shape, size, and position of the three-dimensional figure may be adjusted so that the boundary of the three-dimensional figure corresponds to the boundary (left, right, top, and bottom) of the three-dimensional figure, and the virtual three-dimensional figure may be a figure having a columnar shape, such as a cylinder or a polygonal column, but is not limited thereto.

[0073] Furthermore, the spinal surgery planning method of the present invention utilizes software to create a three-dimensional image from a two-dimensional spinal image, and can perform accurate and efficient surgery planning based on the three-dimensional image. The spinal surgery planning method of the present invention utilizes a deep learning model to generate a three-dimensional image from a two-dimensional spinal image obtained from a patient, thereby visualizing the structure and size of the bone in the surgical area, thereby obtaining various information necessary for spinal surgery.

[0074] Specifically, in 2D-3D reconstruction, which can extract anatomical landmarks from 2D images and implement 3D shapes, it is important to train structured data using a deep learning model. A representative example is convolutional neural networks (CNNs), which are deep learning models optimized for structured data learning. The CNNs are deep learning models mainly used in image processing, and are used to extract image features through convolution operations and generate 3D volumes by receiving 2D slice images as input. However, since it is realistically difficult to prepare a large amount of learning data, there is a method of utilizing digitally reconstructed radiography (DRR) images. The DRR is efficient in extracting additional information such as bone structure by digitally reconstructing 2D radiographic images.

[0075] In order to train the above deep learning model, a large amount of DRR images are generated using a generative adversarial network (GAN), which is an artificial intelligence model for data generation, and a conditional adversarial network (PIX2PIX) model for image-to-image conversion is used to learn actual X-ray images and DRR images, and a DRR-like image converted from the actual X-ray image is generated. After that, a 3D image is reconstructed from the 2D DRR-like image based on a deep learning model, CNNs. After that, axial information, etc. are confirmed through the 3D image, and the shortest path of the surgical target area and the insertion length and angle of the needle are calculated through an algorithm, and the length and diameter of the pedicle screw are determined, etc., so that basic information on the insertion location and optimal path can be obtained.

[0076] Figure 8 is an AP image (left) and an LL image (right) showing the shape of a vertebral body fixed using a pedicle screw. According to the one-dimensional image-based spinal surgery planning method of the present invention, the optimal path for inserting a pedicle screw can be guided according to changes in the height of the spinous process and pedicle based on a predetermined entry point. In addition, the angle between the screw and the patient's vertebral plane can be estimated based on the screw thread and the change in the distance between the threads, and the error in the entry angle and direction between the guided image and the actual surgery can be notified, and the appropriate direction can be guided. Through this, accurate screw fixation results can be obtained even in the lateral view after surgery using only the AP image. The method for estimating the angle between the screw and the patient's vertebral plane based on the change in the distance of the thread first uses C-arm fluoroscopy to photograph an object with a screw, and then acquires an image of the process of the thread length changing when rotating 360°. These acquired images interpret the relative positional changes between the screw or needle and the virtual fixed patient plane due to thread changes. By combining the estimated screw angle and plane angle, the screw's rotation on a one-dimensional plane can be interpreted, and the spatial position and rotational state of the screw can be understood by referring to Table 1 below (Figs. 9 and 10).

[0077] Screw thread angle 60°Indication methodIndication by pitchSizePitch(Pitch)NumberOuter diameterInner diameterRecommended punching size#16(M16)1.51614.417#20(M20)1.52018.421#25(M25)1.52523.426#32(M32)1.53230.433#40(M40)1.54038.442#50(M50)1.55048.452#63(M63)1.56361.465#75(M75)1.57573.477

[0078] Based on the fluoroscopic image of the screw thread, the angle of the virtual patient plane and the inserted structure of the screw or needle can be estimated, and the error in the calculated angle can be corrected through the changed position during 360° rotation.

[0079] While the present invention has been described with reference to the above-described embodiments, these are merely exemplary, and those skilled in the art will understand that various modifications and equivalent alternative embodiments are possible. Therefore, the true scope of technical protection of the present invention should be determined by the technical spirit of the appended claims.

[0080] (National Research and Development Project that supported this invention)

[0081] (Project ID) 23041

[0082] (Task Number) 2022R1C1C2008148

[0083] (Ministry Name) Ministry of Science, ICT and Future Planning

[0084] (Name of Project Management (Specialist) Institution) National Research Foundation of Korea

[0085] (Research Project Name) Sejong Science Fellowship

[0086] (Research Project Title) Optimizing Vagus Nerve Stimulation to Promote Neuroplasticity

[0087] (Contribution rate) 1 / 1

[0088] (Name of the project performing organization) Eulji University Industry-Academic Cooperation Foundation

[0089] (Research Period) March 1, 2022 - February 29, 2024

Claims

1. A step of acquiring a one-dimensional spinal image of a patient requiring spinal surgery; A feature point designation step of identifying the location of the vertebral body in the spinal image and designating feature points of the vertebral body using a pre-learned U-net structure; Step of setting a virtual coordinate space for the target area based on the above-mentioned feature points: A step of deriving a triangular point by applying the coordinate values ​​of the above virtual coordinate space to a trigonometric function; A step of calculating the insertion length and angle of the needle from the entry point to the target site from the above triangulation point; and A spinal surgery planning method, comprising a planning completion step of determining the length, diameter, etc. of a pedicle screw and determining a plan for the insertion location and path.

2. In paragraph 1, The above feature point designation step is A step of training the model using spinal image data with specified feature points marked after preparing the UNET model; A step of extracting feature point location information from the model through the above training; A step of representing the above feature point location information as a specific pixel location in a spine image; and A method comprising a step of identifying and analyzing a structure of a vertebral body by interpreting the location information of the above-mentioned feature points.

3. In paragraph 2, The structure of the above vertebral body is a spinous process, a transverse process or a pedicle.

4. In paragraph 1, The above characteristic point is a location value of the terminal end of the spinous process of the vertebral body, the first pedicle, or the second pedicle.

5. In paragraph 1, A method wherein the above planning completion step includes the shortest path from the entry point to the target area.

6. In paragraph 1, The above one-dimensional image is an X-ray (C-arm) or spine CT.

7. In paragraph 1, The above spinal surgery is a method of spinal fusion, spinal endoscopic surgery, or minimally invasive spinal surgery.

8. In paragraph 7, A method wherein the spinal fusion is selected from the group consisting of transforaminal lumbar interbody fusion (TLIF), posterior lumbar interbody fusion (PLIF), anterior lumbar interbody fusion (ALIF), and direct lumbar interbody fusion (DLIF).

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