Abstract:
A system and associated methodology for the generation of digital models that account for the adaptation of the shape of the patient&#39;s gingiva is provided. The exemplary system uses an initial scan of the patient&#39;s gingiva as a base model, taking into account the type and morphology of the teeth, the shape, orientation and movements of the roots inside the gingiva, and other factors for a more accurate prediction of the changes in the shape of the gingiva throughout every step of the treatment. In particular, the system proactively determines the areas of the model that will be covered by the aligner and prevents changes to such areas, whereas the shape of the model outside these areas is altered in a way to minimize the size of model and to add any necessary features for the manufacturing of the aligners.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This application claims the benefit of U.S. Provisional Application No. 62/340,960, filed May 24, 2016. 
     
    
     BACKGROUND 
       [0002]    Orthodontic aligners provide an alternative to traditional braces, which typically employ brackets connected by wires for the realignment of teeth. Aligners are suitable for patients with mildly or moderately crowded teeth, or minor spacing problems between teeth. A patient using aligners for orthodontic treatment periodically replaces the aligner with a new, progressively different aligner to gradually move the teeth from a first position to a second position, and ultimately, toward the desired, final position. The course of treatment may last several months to a couple of years, depending on the severity of the teeth misalignment. Aligners may be made from plastic materials such as acrylic, such as those manufactured by the current assignee, ClearCorrect® LLC of Round Rock, Tex. 
         [0003]    The current technologies available for producing plastic aligners used during orthodontic treatment are mainly based on a 3D scanning of the patient&#39;s current dentition, planning a course of treatment by defining the movement of the teeth in a computer system, printing the future or anticipated teeth models corresponding to each step of the treatment, and using the models for fabricating plastic aligners by thermoforming the printed models and/or via other manufacturing technologies, such as 3D printing. 
         [0004]    One of the biggest challenges in generating the teeth models is predicting and including a realistic 3D model of the patient&#39;s gingiva (“gums”) for each step of the treatment. When repositioning and moving the teeth during the various stages of treatment in the computer system, the geometrical shape of the teeth does not change, as it is only a solid object moved in finite directions. However, the bones and gingiva do change shape and evolve throughout the treatment. The plastic aligners cover parts of the gingiva as well as the teeth; therefore, to be able to create aligners that will fit properly in the patient&#39;s mouth, it is critical to accurately predict and generate precise shapes and dimensions of the gingiva when creating the 3D models of the teeth. 
         [0005]    There currently exist various software technologies that assist with generating the gingiva models when the teeth are moved to create a treatment plan. Some of the existing technologies generate completely virtual gingiva shapes with no wrinkles and warping on the surface, but do not accurately represent the realistic shape of the gingiva in the patient&#39;s mouth; neither for the initial nor for the future steps of the treatment. Examples of such systems include ClinCheck® by Align Technology of San Jose, Calif. Other systems use the actual shapes of the patient&#39;s gingiva as the starting point in the treatment, which makes the initial models fit perfectly, but as the teeth start moving the updates to the gingiva shapes is not accurate, and causes wrinkles in the gingiva shape. Examples of such systems include the Ortho Analyzer by 3Shape® of Copenhagen, Denmark. 
         [0006]    These known systems treat the gingiva and teeth geometries as a single mesh that are strictly stitched and attached together. Consequently, these systems update the gingiva shape in a way that will not match the actual gingiva changes in the patient&#39;s mouth as the teeth are repositioned. As a result, even though the aligners from the initial steps of the treatment fit properly, the inaccurate updates to the gingiva shapes will cause the aligners for the later steps of the treatment to progressively deteriorate in fit. 
       SUMMARY 
       [0007]    One of the most important steps in orthodontic treatment when using aligners is the prediction and generation of precise 3D teeth models for every step of the treatment plan. To generate such models, the future placement of the teeth and the future dimension/shape of the adapting gingiva need to be predicted accurately. An exemplary embodiment of the present invention provides a system and associated methodology for the generation of digital models that account for the adaptation of the shape of the patient&#39;s gingiva based on the treatment plan, patient records and the dental morphology. The exemplary system uses an initial scan of the patient&#39;s gingiva as a base model, taking into account the type and morphology of the teeth, the shape, orientation and movements of the roots inside the gingiva, and other factors for a more accurate prediction of the changes in the shape of the gingiva throughout every step of the treatment. In particular, the system proactively determines the areas of the model that will be covered by the aligner and prevents changes to such areas, whereas the shape of the model outside these areas is altered in a way to minimize the size of model and to add any necessary features for the manufacturing of the aligners 
         [0008]    The methodology generates and updates the dimension/shape of the gingiva, resulting in more precise models of the gingiva. The ability to account for adaptation of the shape of the gingiva during orthodontic treatment enhances aligner fitting, decreasing re-work on parts of the dentition. 
         [0009]    In the current inventive system, individual teeth are treated as separate objects that are floating inside the gingiva. Information such as the type and placement of the teeth, morphology of the roots, and the type of the root movements inside the bone is used to create a force field vector between the root models and the gingiva. Finite element analysis methods are then used to calculate the updated shape of the gingiva. Statistical data is also assessed and used to fine tune the parameters related to forces defined between the roots and the gingiva. As a result, a realistic model for how teeth movements affect the changes in the gingiva dimension/shape is created. Further, the corresponding aligners generated from each of these models fit properly in both the initial and later steps of the treatment. 
         [0010]    Aspects of an exemplary embodiment of the present invention include: a) receiving an initial oral profile, including teeth and gingiva spatial information, of a patient, b) generating an initial mold profile from the oral profile, wherein the initial mold profile includes numerical representations of the teeth and gingiva spatial information of the patient, c) assigning a plurality of tooth control points and a plurality of gingiva control points to the initial mold profile, d) identifying a first force field vector for a first gingiva control point based on a movement of a neighboring control point in a first group of neighboring gingiva and tooth control points, wherein the first gingiva control point is a member of the plurality of gingiva control points, e) repeating step d) to identify the remaining force field vectors for the first gingiva control point based on movements of remaining control points in the first group of neighboring gingiva and tooth control points, f) repeating steps d) and e) for the remaining gingiva control points in the plurality of gingiva control points, g) receiving tooth control points movements for the plurality of tooth control points, h) performing finite element analysis to calculate the movements of the plurality of gingiva control points in response to the received tooth control points movements, and i) generating a new mold profile. 
         [0011]    The area of the gingiva that will be covered by the aligner is detected and accurately preserved, while the shape of the model outside this area is altered in a way to minimize the size of model and to add any necessary features for the manufacturing of the aligners. Among different possibilities for creating the base model one includes using an optimization algorithm, one that minimizes the volume of the 3D model is selected while respecting criteria on the height of the base in different areas of the model. This leads to minimal consumption of printing materials during printing of the 3D teeth models. 
         [0012]    With more accurate models for predicting the change in shape of the gingiva during orthodontic treatment, aligners can be fabricated that both cover some areas of the gingiva and fit properly in the patient&#39;s mouth. This will lead to structurally robust aligners and success in moving teeth while doing orthodontic treatment using clear plastic aligners. 
     
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         [0013]      FIG. 1  shows an exemplary embodiment of a system for generating digital models that account for the adaptation of the shape of the patient&#39;s gingiva; 
           [0014]      FIG. 2  is a flow chart of an exemplary embodiment of a method for generating digital models that account for the adaptation of the shape of the patient&#39;s gingiva; 
           [0015]      FIG. 3  illustrates an exemplary cross sectional view of a tooth and gingiva profile; 
           [0016]      FIG. 4  illustrates a perspective view of a mold made using the method described in  FIGS. 2 ; and 
           [0017]      FIG. 5  illustrates frontal views of exemplary aligners. 
       
    
    
     DETAILED DESCRIPTION 
       [0018]    The present application describes a system and method for generating digital models that account for the adaptation of the shape of the patient&#39;s gingiva during orthodontic treatment. The initial teeth and gingiva profile is obtained from a 3-D scanning of the patient&#39;s teeth and gingiva replica, or a CT scan of the patient&#39;s teeth and gingiva impression. The initial profile, along with desired teeth movements, is sent to software that produces a new teeth and gingiva profile. The software assigns, based on collected statistical and anatomical data, force vectors between a number of gingiva control points and tooth control points. Each force vector represents the impact of a tooth gingiva control point movement on a neighboring gingiva control point. By integrating the desired teeth movements with the initial profile, the software is able to produce a new profile that includes the desired teeth movements and new gingiva topology. The new profile may be sent to a 3-D printer to fabricate a new mold. 
         [0019]      FIG. 1  shows an exemplary system  100  for generating digital models that account for the adaptation of the shape of the patient&#39;s gingiva during orthodontic treatment. The system  100  includes a central server  102 , a database  104 , a physician portal  106 , a scanning computer  110 , and a printing computer  120 . The physical portal  106  may be connected to the Internet  108 . The system  100  may be implemented on multiple computers, or integrated on a single computer. 
         [0020]    In some implementation, the central server  102  may be connected to the database  104 , the physician portal  106 , the scanning computer  110 , and the printing computer  120 . The central server  102  provides an interface for the remaining systems to properly and safely access the database  104 . The central server  102 , the database  104 , the physician portal  106 , the scanning computer  110 , and the printing computer  120  may be placed geographically in the same location. Alternatively, some or all of the components may communicate remotely via a virtual private network. 
         [0021]    In certain embodiments, the physician portal  106  may provide external users an interface for sending and receiving digital files to the central server  102 . The physician portal  106  may include a proxy server or a firewall to regulate remote access and protects the system  100  from hostile network intrusion. External users may transmit digital files to the physician portal  106  across the internet  108 . With proper authorization and authentication, the physician portal  106  may grant certain external users limited access to the scanning computer  110  and the printing computer  120 . 
         [0022]    In exemplary embodiments, the database  104  may store digital data used within the system  100 . The stored data may be provided via the central server  102 . The database  104  may implement local and/or remote routine back-up features for stored data. 
         [0023]    In some embodiments, the scanning computer  110  may be connected to an image capturing device  112  and an image output device  114 . The image capturing device  112  may scan a mold  118  representing a replica of a patient&#39;s teeth and gingiva profile placed on a positioner  116 . The image output device  114 , such as a screen, a monitor, a display, a projector or a printer, for example, may display the scanned image of the mold  118 . The image capturing device  112  may include 3D camera, two or more 2D cameras, CT scanner, or x-rays. Other devices for obtaining images are possible. 
         [0024]    In exemplary implementations, the positioner  116  includes a visual reference guide comprising lines that are on or within the positioner. The visual reference guide may be utilized to track locations of the mold within the positioner  116 . 
         [0025]    In certain implementations, the printing computer  120  may be connected to a mold fabricating device  122  and an aligner fabricating device  122 . The mold fabricating device  122  and the aligner fabricating device  124  may be 3D printers, for example. 
         [0026]      FIG. 2  is a flow chart illustrating an exemplary method  200  for generating digital models that account for the adaptation of the shape of the patient&#39;s gingiva during orthodontic treatment, which may be used to produce orthodontic aligners. The central server  102  first receives ( 202 ) patient teeth and gingiva profile from the scanning computer or a remote source. For example, the scanning computer  110  may rely on the image capturing device  112  to photogrammetrically collect spatial information about the mold  118 . In certain embodiments, the scanning computer  110  may utilize a 3-D scanner to capture spatial information relating to the mold  118 . The 3-D scanner may be contact-based or optics-based. Alternatively, the scanning computer  110  may use a CT computerized tomography (CT) scanner to piece-wise scan an impression of the patient teeth and gingiva. The scanning computer  110  integrates a plurality of x-ray images obtained from the CT scan to construction the patient teeth and gingiva profile. At the completion of the 3D or CT scan, a pre-processing may be performed on the scanned image to ensure compatibility with the central server  102 . 
         [0027]    In other embodiments, the central server  102  may receive ( 202 ) patient teeth and gingiva profile in digital format from a remote system via the physician portal  106 . The profile may be sent to the physician portal  106  over the internet  108  by an orthodontist that directly extracted the profile from the patient. The profile may be stored on the database  104 . Alternatively, the central server  102  may obtain the profile from the database  104 . Other methods of receiving teeth and gingiva profile data are possible. 
         [0028]    In certain implementations, after receiving the patient teeth and gingiva profile, the central server  102  may generate ( 204 ) the initial mold profile. The initial mold profile includes sufficient spatial information for the system  100  to, if necessary, produce a reproduction mold identical to the mold representing the patient&#39;s teeth and gingiva profile. The generated initial mold profile may be digitally stored by the system  100  either locally (on the database  104 ) or remotely. 
         [0029]      FIG. 3  illustrates an exemplary cross sectional view of a tooth and gingiva profile  300 . Referring to  FIGS. 2 and 3 , in some embodiments, the central server  102  assigns ( 206 ) numerous control points on the teeth and the gingiva of the initial mold profile. Each control point represents a spatial point on the surfaces of the teeth or the gingiva. The number of assigned control points for the initial mold profile may be 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, or 100000. Other numbers of control points are possible dependent upon the specific treatment and desired accuracy. 
         [0030]    In some implementations, the central server  102  may assign gingiva control points to surfaces of an inner wall  306   a  and an outer wall  306   b  of a gingiva  306 . In other embodiments, the central server  102  may assign gingiva control points to the surfaces of the inner wall  306   a  and the outer wall  306   b  of the gingiva  306  and within the gingiva  306 . 
         [0031]    The central server  102  may provide a coordinate system to numerically represent each control point. Exemplary coordinate systems include Cartesian coordinate, cylindrical coordinate, and spherical coordinate. Other coordinate systems may be used. 
         [0032]    Still referring to  FIGS. 2 and 3 , in exemplary embodiments, the central server  102  identifies ( 208 ) a first force field vector f(g 1 , t 1 ) to a first gingiva control point g 1  relating to a first tooth control point t 1 . The first gingiva control point g 1  is near the inner wall  306   a  of the gingiva  306 . The first tooth control point t 1  may represent a spatial point on a surface of a lower portion of a first tooth. Alternatively, the first tooth control point t 1  may represent a spatial point on other portions of the first tooth. The first force field vector represents a movement of the first gingiva control point g 1  in response to a movement of the first tooth control point t 1 . For example, if an upper portion of the first tooth moves inwardly  302  (i.e. toward the middle of the mold), the lower portion of the first tooth may move outwardly  304  (i.e. away from the middle of the mold). Consequently, the first tooth control point moves t 1  outwardly. This outward movement of the first tooth control point t 1  may cause the first gingiva control point g 1  to move outwardly. The first force field vector represents the movement of the first gingiva control point g 1  in response to the movement of the first tooth control point t 1 . In other exemplary embodiments, the central server  102  may identify ( 208 ) a different force field vector to the first gingiva control point g 1  relating to a different neighboring tooth control point, such as tooth control points t 2 , t 3 , or t 4 . 
         [0033]    Still referring to  FIGS. 2 and 3 , in some embodiments, the central server  102  may also identify ( 208 ) a force field vector for the first gingiva control point g 1  that represents the movement of the first gingiva control point g 1  in response to the movement of a neighboring gingiva control point. For the first gingiva control point the central server  102  may identify force field vectors f(g 1 , g 2 ), f(g 1 , g 3 ) relating to movements of gingiva control points g 2  and g 3 , or alternatively, identify force field vectors f(g 1 , g 2 ), f(g 1 , g 3 ), f(g 1 , g 4 ) relating to movements of gingiva control points g 2 , g 3 , and g 4 . In the first scenario, the central server  102  identifies force field vectors relating to neighboring gingiva control points on the inner wall  306   a  of the gingiva  306 . In the second scenario, the central server  102  identifies force field vectors relating to neighboring gingiva control points on the inner wall  306   a  and the outer wall  306   b  of the gingiva  306 . Other criteria for selecting neighboring gingiva control points are possible. 
         [0034]    As shown in  FIGS. 2 and 3 , in certain implementations, the central server  102  may identify ( 210 ) more force field vectors for the first gingiva control point g 1 . An exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 2 ), f(g 1 , t 3 ), f(g 1 , t 4 ), f(g 1 , g 2 ), and f(g 1 , g 3 ). Another exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 2 ), f(g 1 , t 3 ), f(g 1 , t 4 ), f(g 1 , g 2 ), f(g 1 , g 3 ), and f(g 1 , g 4 ). Yet another exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 4 ), and f(g 1 , g 3 ). Still another exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 4 ), f(g 1 , g 3 ), and f(g 1 , g 4 ). An exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 4 ), f(g 1 , g 2 ), and f(g 1 , g 3 ). A further exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 4 ), f(g 1 , g 2 ), f(g 1 , g 3 ), and f(g 1 , g 4 ). Another exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 2 ), f(g 1 , t 3 ), . . . f(g 1 , t N ), f(g 1 , g 2 ), f(g 1 , g 3 ), and f(g 1 , g 4 ), where N is a positive integer. Yet another exemplary set of force field vectors for the first gingiva control point g 1  may include f(g 1 , t 1 ), f(g 1 , t 2 ), . . . , f(g 1 , t N ), f(g 1 , g 2 ), f(g 1 , g 3 ), . . . and f(g 1 , g M ), where M is a positive integer that may be the same or different than N. Other combinations for the set are possible. 
         [0035]    Next, referring to  FIGS. 2 and 3 , the central server  102  may identify ( 212 ) force field vectors for other gingiva control points. For example, for gingiva control points g 2 , g 3 , g 4 , . . . g M  and tooth control points t 1 , t 2 , t 3 , . . . t N , the central server  102  identifies force vectors f(g 2 , t 1 ), f(g 2 , t 2 ), f(g 2 , t 3 ), . . . f(g 2 , t N ), and f(g 2 , g 1 ), f(g 2 , g 3 ), f(g 2 , g 4 ), . . . f(g 2 , g M ) to gingiva control point g 2 , f(g 3 , t 1 ), f(g 3 , t 2 ), f(g 3 , t 3 ), . . . f(g 3 , t N ), and f(g 3 , g 1 ), f(g 3 , g 2 ), f(g 3 , g 4 ), . . . f(g 3 , g M ) to gingiva control point g 3 , f(g 4 , t 1 ), f(g 4 , t 2 ), f(g 4 , t 3 ), . . . f(g 4 , t N ), and f(g 4 , g 1 ), f(g 4 , g 2 ), f(g 4 , g 3 ), . . . f(g 4 , g M ) to gingiva control point g 4 , . . . and f(g M , t 1 ), f(g M , t 2 ), f(g M , t 3 ), . . . f(g M , t N ), and f(g M , g 1 ), f(g M , g 2 ), f(g M , g 3 , . . . , f(g M , g M−1 ) to gingiva control point g M , where subscripts M and N are positive integers that are the same or different. In other embodiments, the central server  102  may identify subsets of the force field vectors for gingiva control points as explained above. 
         [0036]    For each gingiva control point g 1 , g 2 , g 3 , . . . g M , the central server  102  identifies a set of L vectors that represent the movement of each gingiva control point in response to the movements of the tooth control points t 1 , t 2 , t 3 , . . . t N , and the gingiva control points g 1 , g 2 , g 3 , g 4 , . . . g M , where L≦M+N. In certain embodiments, some of the vectors may be expressed as algebraic equations. Other mathematical expressions are possible. 
         [0037]    In certain embodiments, the force field vectors may be identified using statistical data stored within the database  104 . The statistical data may be related to previous orthodontic operations, orthodontic research data, patients anatomic record, and computer simulations. 
         [0038]    Referring to  FIG. 2 , in exemplary implementations, the central server  102  receives ( 214 ) tooth control points movements for tooth control points t 1 , t 2 , t 3 , t N . The tooth control points movements may be entered manually by an operator into the central server  102  via the graphical user interface. Another exemplary method for the central server  102  to receive ( 214 ) tooth control points movements is to receive the tooth control points movements from a remote system through the physician portal  106 . An orthodontist at the remote system may input the desired tooth control points movements into a digital file. The movements may represent the desired locations for the teeth of the patient associated with the initial teeth and gingiva profile. The distance between any two tooth control points for a same tooth may remain constant (i.e. each tooth moves as a fixed, solid unit). Alternative, central server  102  may allow small changes in the shape of tooth in response to the tooth control points movements. 
         [0039]    In certain embodiments, after receiving the tooth control points movements, the central server  102  performs ( 216 ) finite element analysis (FEA) using the identified force field vectors. Based on the individual movements of the associated tooth control points and the identified force field vectors, the central server  102  may compute the overall movement of each gingiva control point. By using FEA, the central server  102  may estimate the movement of a gingiva, or a portion of the gingiva, based on the movements of the control points on or within the gingiva. For example, the central server  102  may approximate the movement of the inner wall  306   a  using the average movements of the gingiva control points g 1 , g 3 , and g 3 . In another example, the central server  102  may approximate the movement of a first portion of the inner wall  306   a  between the gingiva control points g 1  and g 3  using the average movements of the gingiva control points g 1  and g 3 . Alternatively, the central server  102  may estimate the first portion of the inner wall  306   a  between g 1  and g 3  by assuming a point between g 1  and g 3  moves according to a weighted average of g 1  and g 3 . For example, assuming a distance of x from g 1  to g 3 , and the point is 0.4× from g 1 , than the movement of the point may be 0.6 (movement of g 1 )+0.4 (movement of g 3 ) in yet another example, the movement of a second portion of the gingiva  306  bordered by gingiva control points g 1 , g 3  and f 4  may be approximated by averaging the movements of g 1 , g 3  and g 4 . Other methods of approximations are possible. 
         [0040]    Referring now to  FIGS. 2, 4, and 5 , after performing the finite element analysis of the assigned gingiva control points, in exemplary embodiments, the central server  102  generates ( 218 ) a new mold profile including the movements of the teeth and gingiva. The new mold profile may be used to generate a new mold  400 , which in turn may be used to produce a new aligner for the patient associated with the initial teeth and gingiva profile. The new aligner, if worn by the patient, may gradually move his/her teeth to locations similar to the teeth locations in the new mold profile. A complete treatment plan may include 5, 10, 20, 50, and 100 aligners. Other numbers of aligners are possible. 
         [0041]    In exemplary embodiments, the central server  102  may send the new mold profile to the printing computer  120  for generating the new mold  400 . The printing computer  120  may instruct the mold fabricating device  122  to produce the new mold  400  based on the new mold profile. 
         [0042]    In some embodiments, the new mold profile may be stored in the database  104 . Alternatively, the system  100  may send the new mold profile, via the physician portal  106 , to a remote system. 
         [0043]    The new mold  400  produced by the mold fabricating device  122  of the system  100  using the new mold profile may include replica of teeth and gingiva. In some implementations, the gingiva may extend 2 millimeters from a gingival line  402 . Alternatively, the gingiva may extend 1 millimeter, 3 millimeters, 5 millimeters, 10 millimeters, or 15 millimeters from the gingival line  402 . 
         [0044]    Referring to now to  FIG. 5 , the new mold  400  may be utilized by the system  100  to produce a new aligner using the aligner fabricating device  124 . In some embodiments, a first aligner  502  may be produced using the new mold  400 , where the first aligner includes a contoured edge  502   a.  Alternatively, a second aligner  504  may be produced using the new mold  400 , where the second aligner includes a flushed edge  504   a,  In another example, a third aligner  506  may be produced by the system using the new mold  400 , where the third aligner includes an extended edge  506   a.  Other designs for the edge of the aligner is possible. 
         [0045]    A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of this disclosure. For example, preferable results may be achieved if the steps of the disclosed techniques were performed in a different sequence, if components in the disclosed systems were combined in a different manner, or if the components were replaced or supplemented by other components. The functions, processes and algorithms described herein may be performed in hardware or software executed by hardware, including computer processors and/or programmable circuits configured to execute program code and/or computer instructions to execute the functions, processes and algorithms described herein. Additionally, some implementations may be performed on modules or hardware not identical to those described. Accordingly, other implementations are within the scope that may be claimed.