Representation of Structural Relationships in the

Foundational Model of Anatomy

 

José L.V. Mejino, Jr. M.D.,1 Natalya F. Noy Ph.D., 2 Mark Musen M.D., Ph.D., 2 and Cornelius Rosse, M.D., D.Sc. 1

Structural Informatics Group, Department of Biological Structure,

University of Washington, Seattle, WA1 and

Section on Medical Informatics, Stanford University School of Medicine,

Stanford, CA 2

 


ABSTRACT

Previous attempts at the symbolic representation of anatomical relationships have been largely limited to partonomy. We propose an ontology of anatomical relationships and illustrate the inheritance of structural attributes in the Digital Anatomist Foundational Model. Our purpose is to generate a sharable resource that can support inference about the structural organization of the body.

INTRODUCTION

Text Box:  
Figure 1. Classes of 'Anatomical relationship' in the context of its superclasses in the AO of the FM.



The main objective of the terminologies correlated by UMLS is to serve as repositories of terms that can be reused with consistency by a variety of applications.1 In general, current biomedical and educational applications are designed to present hard-coded, didactic information, or they support low-level, look-up functions with no, or at best limited, capabilities for inference. The semantic structure of today's controlled medical terminologies (CMTs) seems adequate for the needs of such contemporary applications. Next-generation applications, however, will have to incorporate increasing levels of intelligence in order to meet the demands of the evolving environment in education and the practice of the various health professions. Such knowledge-based applications call for the representation of much deeper and richer knowledge than that retrievable from today's CMTs. Since these CMTs primarily target clinical medicine, they are deficient in basic science concepts necessary to support reasoning. Moreover, since relationships between concepts constitute an important dimension of knowledge, next-generation knowledge sources must model comprehensively not only the concepts but also the relationships that characterize a particular field of basic science.  Therefore, there is a need to generate enabling knowledge sources at least in those domains that generalize to diverse fields of education and clinical practice. Anatomy is such a fundamental domain.

 

We are developing the Foundational Model of anatomy (FM)2,3 as an evolving resource for knowledge-based applications4. Our intent is that the FM should furnish, at the highest level of granularity, not only anatomical concepts but also the relationships that comprehensively describe the structural organization of the body. Figure 1 illustrates that three of the four components of the FM (described elsewhere in these proceedings5,6) are, in fact,  based on different classes of relationships:

 

Fm = (AO, ASA, ATA, Mk)               (1)

 

AO, the Anatomy Ontology, is a type hierarchy based on the IS-A relationship; ASA, the anatomical structural abstraction, based on 'structural relationship', is the subject of this report; ATA, the anatomical transformation abstraction, is based on relationships that describe the morphological transformation of anatomical entities during pre- and postnatal development. 

Text Box:   Figure 2. The ontology of structural relationships. Only some of the subclasses are opened up.

Our reports in these proceedings,5,6 as well as elsewhere,2,3,7-10 are primarily concerned with the classification of physical anatomical entities (material objects, spaces, surfaces, lines and points). In this communication our objective is to illustrate the importance of anatomical relationships for the symbolic modeling of structural knowledge, a dimension unique to anatomy among the biomedical sciences.

 

ANATOMICAL STRUCTURAL ABSTRACTION

The FM is being developed as an anatomical enhancement of UMLS. Its classes and relationships extend the specificity of UMLS semantic types and relationships. We have proposed a scheme for representing anatomical structural relationships in terms of interacting networks:3,10

 

ASA = (DO, Pn, Bn, SAn)                   (2)

Where:  DO  =  Dimensional ontology

                Pn   =  Part-of network

                Bn   =  Boundary network

                                                                                                                        SAn =  Spatial Association network

 

DO is a type hierarchy of geometric objects and shapes, in terms of which the three networks of ASA may be described at an abstract level. Of the ASA networks, SAn itself consists of a number of subnets corresponding to the descendants of the 'Spatial association relationship' class shown in Figure 2. Since other reports tend to deal with part-whole relationships11,12, in this communication we illustrate spatial associations, which have received less attention. The descendants of this relationship class correspond to a number of axes or viewpoints in terms of which anatomical spatial associations, such as location, may be conceptualized. We illustrate the symbolic modeling of 'Anatomical adjacency', which poses a particular challenge, since adjacency is not simply a relationship between two objects; rather it has attributes, such as directional vector and right or left laterality.

 

An anatomical structure, such as the esophagus, or a part of it, inherits its shape from the DO class 'conventional hollow cylinder'. This shape specifies the set of adjacency relationships that is allowed for this shape class. Figure 3 shows these relationships graphically in terms of a qualitative radial coordinate system. In Figure 4 the qualitative coordinate system for cylinder are superimposed and centered on the esophagus in a section of the male Visible Human at the level of the eighth thoracic vertebra. In Figure 5 the adjacencies of 'T8 part of the esophagus' are expressed symbolically in terms of these qualitative coordinates. Although some of these adjacency relationships remain constant, others change from one vertebral level to the next. The AO of the FM represents each vertebral level of the esophagus as a discrete subzone, which permits the symbolic modeling of the changing adjacency relationships of the esophagus as it "passes" from the neck to the abdomen.

 

The spatial knowledge captured by the adjacency relationships shown in Figure 5 is of importance to a student dissecting the esophagus for the first time and also to a surgeon planning to remove a lymph node adjacent to the esophagus through a mediastinoscope. The FM can provide knowledge of adjacency relationships appropriate for applications developed for each of these types of users. Moreover, since we can represent inverse values for these relationships, and make inferences based on their transitivity, the FM could support inference required for answering user-generated spatial queries at different levels of complexity.

 

Text Box:  
  Figure 3. Qualitative radial coordinate system 
  for the DO shape class ‘conventional cylinder’.

Figures 4 and 5 invite comment about the relative usefulness of geometric and qualitative coordinates for representing such structural attributes as location and adjacency. The relationships expressed in terms of qualitative coordinates could be derived from the quantitative geometric matrix of the Visible Human data set. These geometric coordinates, however, would have to be expressed as qualitative coordinates in order to make them intelligible in anatomical discourse. Geometric coordinates are valid only for one instance, whereas anatomical qualitative coordinates describe relationships that hold true in all members of a species. Only those structures can be referenced by geometric coordinates that are visible with a particular imaging modality. Qualitative coordinates, on the other hand, can describe the relationship of invisible structures to visible ones, as illustrated in Figure 5 by the esophageal plexus, fibrous pericardium and mediastinal pleura; none of these structures can be identified in the image of the anatomical section.  Moreover, inference required for reasoning about structural relationships within the body must make use of qualitative coordinates. Therefore, the symbolic representation of structural relationships in terms of qualitative coordinates is an important component of the FM. 

 

IMPLEMENTATION

UWDA and FM. We began the development of the University of Washington Digital Anatomist (UWDA) vocabulary  (the initial iteration of the

Text Box:  
Figure 4. Coordinate system of conventional    cylinder superimposed on T8 part of esophagus.
FM) as an anatomical enhancement of UMLS13. Initially we were less concerned with the variety of anatomical relationships than with the classification and comprehensiveness of anatomical concepts. The authoring tool we developed was designed to generate parallel hierarchies (directed acyclic graphs) which were based on IS-A, PART-OF, BRANCH-OF and TRIBUTARY-OF relationships. As we populated classes of 'Organ part' in the IS-A hierarchy, for example, we also aligned the concepts along the transitive PART-OF relationship in another hierarchy. However, such a link-centric view and representation of anatomy proved to be inadequate once we began to appreciate the complexity of relationships that were necessary for comprehensively describing the anatomy of the body. The need for such a comprehensive, reusable resource led to the Foundational Model, a conceptualization of the physical organization (structure) of the human body.

 

Approximately 50,000 concepts in the AO of the FM are accessible through the UWDA vocabulary of UMLS, providing a comprehensive controlled terminology for macroscopic anatomy. Our current work entails the instantiation of the ASA networks of these concepts. The association of such multi-dimensional relationships with anatomical concepts calls for a node-centric view of anatomy, which is beyond the capacity of the link-centric representation we implemented. The frame-based knowledge acquisition system Protégé-200014 has the requisite expressivity and scalability for comprehensively modeling anatomical relationships encompassed by the ASA.  The same will be true for ATA relationships, once we begin the implementation of developmental transformations.  

Text Box:  Figure 5. Frame-based representation of 'T8 part of esophagus' in AO in the left pane and its attributes in the right pane.

 

 

 

 

 

Modeling the ASA in Protégé-2000.  Protégé-2000 has been adapted to meet current and evolving needs of the FM. It is being enhanced by customized active user-interface components as we encounter new challenges in modeling.

 

Protégé-2000 correlates four ontologies within the FM: the large 'Anatomical entity' ontology (the AO) and the smaller 'Dimensional object', 'Physical state' and 'Anatomical entity metaclass' ontologies. The first three ontologies provide the values for anatomical relationships, whereas the metaclass ontology assures the inheritance of the attributes of concepts represented in the AO. The 'Anatomical entity metaclass' ontology contains high level templates for the classes in the AO, which instantiate the template. Each template is a frame composed of a set of slots; each slot corresponds to a defining or other attribute manifested by a particular AO class. We define a hierarchy of templates and the attributes are inherited through the hierarchy. For instance, each concept has a UWDA-ID number and a preferred name, and it may have one or more synonyms. Therefore the template for 'Anatomical entity', which is the root of the AO, includes slots for each of these attributes. The templates of all descendants of the root inherit these slots. When a new concept is entered in the AO, values must be assigned to each of these slots (Figure 5).

 

Figure 5 presents the frame for 'T8 part of esophagus', which is highlighted in the AO (left pane). The right pane shows some of the values for the slots of the 'Zone of esophagus template' pertinent to the ‘T8 part of esophagus’. Although they would have different values, the same kinds of slots specify the anatomical relationships of cervical or thoracic parts of the esophagus as those of the parts that correspond to vertebral levels. The slots for the first two rows of values are inherited from the template of the root. The slot 'has intrinsic 3D shape' is first introduced in the 'Anatomical structure' template as a defining attribute. This attribute distinguishes 'Anatomical structure' from 'Body substance' (see Fig. 1.), as explained in a companion report in these proceedings.5 The intrinsic shape slot is inherited by all templates corresponding to descendants of 'Anatomical structure' in the AO, and its values are provided by the DO.

 

The 'has orientation' template slot, however, has to be introduced in the template of 'Physical anatomical entity', since not only anatomical structures but also surfaces and lines (classified as non-material physical anatomical entities) have orientation (for class hierarchy, see Fig.1). For the same reason, the location attribute is also introduced in the 'Physical anatomical entity template'. On the other hand, slots for the different classes of location relationships (see Fig. 2) must be introduced in the templates of selected descendant classes of 'Physical anatomical entity'. For instance, the 'contains' slot is introduced in the template of 'Anatomical space', whereas its inverse 'contained in' is inserted in the 'Material physical anatomical entity template', since both anatomical structures and body substances can be contained in anatomical spaces. Therefore, in the frame of 'T8 part of esophagus', 'posterior mediastinum' can be a value for the relationship 'contained in', since 'posterior mediastinum' is classified as a  'Compartment', which is a subclass of 'Anatomical space'.

 

Adjacencies also refer to location (see Fig.2). However, they are attributed relationships and therefore 'has adjacency' itself is modeled as a frame with its own slots. For a conventional cylinder, these slots correspond to the radial coordinates shown in Figure 3. 'Zone of esophagus template' inherits these slots from the 'Conventional cylinder template'. The adjacency relationships of 'T8 part of esophagus' are displayed in Figure 5 as the values of these radial coordinates. These values are the immediate adjacencies of this zone of the esophagus. The concepts that correspond to each of these values (e.g., fibrous pericardium, azygos vein, thoracic aorta) also contain adjacency relationships in their own frames. 'T8 part of esophagus' is a value for one of the adjacency coordinate slots along a vector reciprocal to that which relates 'T8 part of esophagus' to the concept. For example in the frame of Azygos vein the value for 'left anterior' coordinate of adjacency would be 'T8 part of esophagus'. Since adjacency relationships are transitive along a coordinate vector, it may be inferred from immediate adjacencies that T8 vertebra (labeled ‘T8’ in Fig 4) is located 'right posterior' in relation to ‘T8 part of esophagus'. It is these interacting adjacency relationships that constitute the adjacency subnet of the SAn component of the Anatomical Structural Abstraction.

DISCUSSION

We selected 'T8 part of esophagus' to illustrate the symbolic representation of detailed structural relationships within the Foundational Model of anatomy. We are validating the templates we have developed so far by assessing the extent to which they generalize to different classes of anatomical entities. Our contention is that a logical and comprehensive symbolic model of anatomical structure will be indispensable to programs and applications that call for reasoning about the human body. By making the FM available as the UWDA vocabulary of UMLS, we hope to obviate the need for ad hoc, repetitive and inconsistent modeling of anatomy by developers of educational or clinical applications who require detailed knowledge of specific parts of the body. Our objective is to enrich this resource by a comprehensive representation of structural relationships, which are an integral component of reasoning about the human body by both humans and machines.

Acknowledgments

This work was supported in part by contract LM03528 and grant LM06822, National Library of Medicine.

 

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