Method for establishing biomimetic nerve graft model for nerve fascicles of extremities

Abstract

The present invention provides a method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities, which comprises the steps of: establishing a database of fascicles structures from nerve fascicles of the extremities with an imaging technique; obtaining information of a defective nerve trunk to be repaired of the extremities; and matching and fitting the information of the defective nerve trunk to be repaired of the extremities with/to the data in the database of fascicles structures, to establish a biomimetic nerve graft model that conforms to the characteristics of fascicles microstructure for nerve fascicles of the defective nerve trunk. In the present invention, the imaging technique and clinical data are fully utilized, to establish a biomimetic nerve graft model conforming to the characteristics of fascicles microstructure for varying types of detects, thus providing more accurate model information for repair of nerve trunk defects in the extremities.

Claims

1. A method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities, comprising the steps of: S1: establishing a database of fascicles structures from nerve fascicles of the extremities with an imaging technique; S2: obtaining information of a defective nerve trunk to be repaired of the extremities; and S3: matching and fitting the information of the defective nerve trunk to be repaired of the extremities with/to the data in the database of fascicles structures, to establish a biomimetic nerve graft model that conforms to the characteristics of fascicles microstructure for nerve fascicles of the defective nerve trunk; wherein Step S1 comprises the following steps: obtaining ex-vivo nerve samples from nerve fascicles of the extremities; obtaining two-dimensional image data of each of the ex-vivo nerve samples by Micro-CT and/or Micro-MRI; and obtaining a three-dimensional reconstruction model for each of the ex-vivo nerve samples by using the two-dimensional image data, storing, and thereby establishing the database of fascicles structures; and wherein the ex-vivo nerve sample is taken from one or more of upper limb nerves below the axillary plane, including the median nerve, radial nerve, ulnar nerve, and musculocutaneous nerve; and lower limb nerves below the inguinal plane, including the femoral nerve, sciatic nerve, tibial nerve and common peroneal nerve.

2. The method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities according to claim 1, wherein the two-dimensional image data includes consecutively scanned images of cross sections, sagittal planes, and/or coronal sections of each of the ex-vivo nerve samples.

3. The method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities according to claim 1, wherein Step S2 comprises the following steps: determining the type and time of injury of the patient, and preliminarily locating the target injured nerve; scanning the gross forms of nerve trunks respectively on both healthy side and affected side of the patient, and obtaining a scanned image of a defect area on the affected side and a scanned image of a normal area on the healthy side corresponding to the defect area; and comparing and analyzing the scanned image of the defect area on the affected side and the scanned image of the normal area on the healthy side to determine the type, spatial position, length, and nerve branching of the nerve trunk in the defect area, and measuring the diameter and length of the nerve trunk in the defect area, such that the information of the defective nerve trunk to be repaired is obtained.

4. The method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities according to claim 3, wherein Step S3 comprises the following steps: according to the information of the defective nerve trunk to be repaired, searching the database of fascicles structures to find out a segment of nerve having a fascicles structure with a type, spatial position, length, and nerve branching of the nerve matching those of the defective nerve, and extracting the spatial structure data of the fascicles structure of the segment; fitting data in the information of the defective nerve trunk to be repaired to the spatial structure data extracted from the database, and establishing a rough three-dimensional model with the fitted data; adjusting the established three-dimensional model according to the general nerve morphology, the nerve branching, and the three-dimensional spatial position distribution of nerve fascicles at both proximal and distal ends of the nerve trunk in the defect area; modifying the form, curvature and smoothness of the adjusted three-dimensional model; matching the modified three-dimensional model with the proximal and distal ends of the nerve trunk in the defect area with respect to the general nerve morphology, the nerve branching, and the three-dimensional spatial position distribution of nerve fascicles; if a parameter for evaluating the degree of matching is less than a preset value, repeating the fitting, adjusting, modifying, and matching steps until the parameter for evaluating the degree of matching reaches or exceeds the preset value; and if the parameter for evaluating the degree of matching is equal to or greater than the preset value, taking the matched three-dimensional model as a biomimetic nerve graft model for the nerve in the defect area.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) FIG. 1 shows a three-dimensional model of fascicles structures in peripheral nerves established in conjunction with an imaging technique.

(2) FIG. 2 shows a main flow chart of a method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities according to an embodiment of the present invention.

(3) FIGS. 3A-3F show Micro-MRI scanned images of nerve fascicles and three-dimensional reconstruction thereof according to some embodiments.

(4) FIGS. 4A-4F show an embodiment of establishing a biomimetic nerve graft model conforming to the characteristics of fascicles microstructure based on a database of fascicles structures.

DESCRIPTION OF THE EMBODIMENTS

(5) To make the technical problems to be solved, the technical solutions and advantageous effects of the present invention more clearly, the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of and are not intended to limit the present invention.

(6) FIG. 2 shows a main flow chart of a method for establishing a biomimetic nerve graft model for nerve fascicles of the extremities according to an embodiment of the present invention, which comprises mainly the following steps:

(7) S1: establishing a database of fascicles structures from nerve fascicles of the extremities with an imaging technique;

(8) S2: obtaining information of a defective nerve trunk to be repaired of the extremities; and

(9) S3: matching and fitting the information of the defective nerve trunk to be repaired of the extremities with/to the data in the database of fascicles structures, to establish a biomimetic nerve graft model that conforms to the characteristics of fascicles microstructure for nerve fascicles of the defective nerve trunk.

(10) Particularly, the method of this embodiment comprises specifically the following steps.

(11) (1) Establish a database of fascicles structures from nerve fascicles of the extremities with an imaging technique.

(12) Ex-vivo nerve samples from nerve fascicles of the extremities are obtained. The nerves are obtained within 2 hours after ligation of the major vessel of the amputated limb specimen, including upper limb nerves below the axillary plane and lower limb nerves below the inguinal plane. The upper limb nerves include the median nerve, radial nerve, ulnar nerve, and musculocutaneous nerve. The lower limb nerves include the femoral nerve, sciatic nerve, tibial nerve and common peroneal nerve. The obtained nerves are immediately fixed in 4% paraformaldehyde, and prepared into ex-vivo nerve samples for scanning. At least 3 samples are taken for scanning for each segment of each type of nerves.

(13) Two-dimensional image data of each of the ex-vivo nerve samples is obtained by an imaging technique. The imaging technique herein includes Micro-CT and/or Micro-MRI. The scanning parameters of Micro-CT and/or Micro-MRI are set, and the pre-treated ex-vivo nerve samples are scanned to obtain the two-dimensional image data. Preferably, the two-dimensional image data includes consecutively scanned images of cross sections, sagittal planes, and/or coronal sections of each of the ex-vivo nerve samples. FIGS. 3A and 3D illustratively show consecutively scanned two-dimensional images of the cross sections of the ex-vivo nerve samples of the tibial nerve and the common peroneal nerve obtained by Micro-MRI, respectively.

(14) Three-dimensional reconstruction of fascicles structures in nerves is performed to establish a database of fascicles structures. The two-dimensional image data obtained in the above steps is segmented using a three-dimensional reconstruction software to extract the nerve fascicles (FIGS. 3B and 3E illustratively show the segmentation of the nerve fascicles in the two-dimensional images of the tibial nerve and the common peroneal nerve respectively), the topological structure of the nerve fascicles is presented by visualization, and three-dimensional reconstruction of each of the ex-vivo nerve samples is performed, to obtain a three-dimensional reconstruction model presenting the configuration of the fascicles structure in each type of nerve (FIGS. 3C and 3F illustratively show the fascicles structure in the tibial nerve and the common peroneal nerve after three-dimensional reconstruction), and then to store it. In this way, the database of the fascicles structures is established.

(15) (2) Obtain information of a defective nerve trunk to be repaired of the extremities.

(16) The type and time of injury of the patient are determined, and the target injured nerve is preliminarily located.

(17) The gross forms of nerve trunks respectively on both healthy side and affected side of the patient are scanned by preferably high-precision MRI, and a scanned image of a defect area on the affected side and a scanned image of a normal area on the healthy side corresponding to the defect area are obtained.

(18) The scanned image of the defect area on the affected side and the scanned image of the normal area on the healthy side are compared and analyzed to determine the type, spatial position, length, and nerve branching of the nerve trunk in the defect area, and the diameter and length of the nerve trunk in the defect area are measured. In this way, the information of the defective nerve trunk to be repaired is obtained.

(19) (3) Match and fit the information of the defective nerve trunk to be repaired of the extremities with/to the data in the database of fascicles structures, to establish a biomimetic nerve graft model that conforms to the characteristics of fascicles microstructure for nerve fascicles of the defective nerve trunk.

(20) On the basis of the type, spatial position, and length of the nerve trunk in the defect area determined in the above step, the database of fascicles structures is searched to find out a segment of nerve having a fascicles structure with a type, spatial position, length, and nerve branching matching those of the defective nerve, and the spatial structure data of the fascicles structure of the segment is extracted.

(21) The measured data of the detect area obtained in the above step is fitted to the spatial structure data extracted from the database, and a rough three-dimensional model is established with the fitted data.

(22) The established three-dimensional model is adjusted according to the general nerve morphology, the nerve branching, and the three-dimensional spatial position distribution of nerve fascicles at both proximal and distal ends of the nerve trunk in the defect area.

(23) The form, curvature and smoothness of the adjusted three-dimensional model are modified using three-dimensional model software.

(24) The modified three-dimensional model is matched with the proximal and distal ends of the nerve trunk in the defect area with respect to the general nerve morphology, the nerve branching, and the three-dimensional spatial position distribution of nerve fascicles.

(25) If a parameter for evaluating the degree of matching is less than a preset value, the fitting, adjusting, modifying, and matching steps are repeated until the parameter for evaluating the degree of matching reaches or exceeds the preset value.

(26) If the parameter for evaluating the degree of matching is greater than or equal to the preset value, the matched three-dimensional model is taken as a biomimetic nerve graft model for the nerve in the defect area.

(27) FIGS. 4A-4F illustratively show an embodiment of establishing a biomimetic nerve graft model conforming to the characteristics of fascicles microstructure based on a database of fascicles structures. FIGS. 4A and 4B show the proximal and distal ends of the nerve trunk in the defect area. The fascicles structures in the proximal and distal ends and the difference therebetween can be clearly identified from FIG. 4B. FIG. 4C is an established three-dimensional model for the nerve trunk in the defect area. FIGS. 4D to 4F show the matching of the established three-dimensional model to the proximal and distal ends of the nerve trunk in the defect area.

(28) The above description is merely preferred specific embodiments of the present invention, and the scope of the present invention is not limited thereto. Simple variations of or equivalent substitutions to the resulting technical solutions made by any person skilled in the art without creative efforts and without departing from the technical scope disclosed herein are within the scope of the present invention.