Revising the Anatomy Model to Improve Usability and Correctness

Some problems to solve Post-coordination of site and laterality is one of the most common requirements of users But anatomy names are confusing (“structure of…”, “entire …”) And anatomy organization appears awkward and duplicative, even when strictly correct The hierarchies in clinical findings and procedures depend on anatomy to determine their structure But anatomy contains many errors and omissions and inconsistencies, leading to “foot in the pelvis” kinds of errors Maintenance is difficult and error-prone and therefore costly It is unclear how to coordinate with “outside” resources Some specialties do their own clinical anatomy (cf Radlex) Some people suggest IHTSDO should outsource its anatomy, e.g. FMA

The nodes are all primitive Therefore, each line is edited SNOMED CT Concept Body structure Physical anatomical entity The nodes are all primitive Therefore, each line is edited individually – and error-prone Anatomical structure Body region structure Body part structure Neck, chest, abdomen, and pelvis Trunk structure Body system structure Neck, chest and abdomen Chest, abdomen, and pelvis Structure of subregion of trunk Upper body structure Cardiovascular structure Chest and abdomen Neck and chest Upper trunk structure Upper body part structure Body space structure Respiratory and/or intrathoracic structures Thoracic structure Body cavity structure Regional cardiovascular structure Body organ structure Thoracic cavity structure Cardiovascular structure of trunk Lung and/or mediastinal structures Structure of viscus Intrathoracic cardiovascular structure Mediastinal structure Organ part Structure of thoracic viscus Heart AND pericardium structure Developmental body structure Cardiovascular organ part Heart structure Embryonic structure Heart part Embryonic cardiovascular structure Cardiac internal structure Anatomical spatial entity Embryonic cardiac structure Cardiac chamber structure Anatomical junction Primitive cardiac septal structure Cardiac septum structure Atrial structure Anatomical orifice Primitive atrial septal structure Interatrial septum structure Ostium Septum primum structure Structure of ostium secundum Entire ostium secundum

A bit of background How did the anatomy section get to where it is? What is the current model?

Merging Anatomy concepts from CTV3 and SNOMED RT Features in common: concepts, terms, hierarchies logical subsumption Main difference: Part/whole representation RT used “part-of x” CTV3 used “x structure”

Example: Liver CTV3 SNOMED RT How is T-62000 used in coding? T-62000 Liver T-D0535 Liver part CTV3 XM0Ps Liver structure 7N330 Liver How is T-62000 used in coding? The site of tumors and other morphologies Does it necessarily mean the entire liver? No In what sense is liver (7N330) a subtype of liver structure (XM0Ps)? All instances of XM0Ps are either instances of "Liver" or they are related to some instance of liver via 'part-of' relations 7N330 means “entire liver”..

Where to put T-62000 “liver”? ? ? T-62000 Liver is-a is-a part-of is-a Liver structure ? T-62000 Liver XM0Ps Liver structure ? is-a is-a part-of Liver part Entire liver T-D0535 Liver part 7N330 Liver is-a Lobe of liver

Solution Adopted: “SEP” model Liver Structure XM0Ps Liver structure T-62000 Liver is-a is-a part-of LiPart Entire liver T-D0535 Liver part 7N330 Liver Note: This structure corresponds closely to the structure described in the paper “Stefan Schulz, Udo Hahn: Part-whole representation and reasoning in formal biomedical ontologies. Artificial Intelligence in Medicine 34(3): 179-200 (2005)

All of anatomy is primitive but it need not be The meaning of “S” is “PartOf <x> OR Entire <x>” The meaning of “P” is PartOf <x> Therefore, both “S” and “P” can be sufficiently defined if we have the right DL (description logic) constructs

SEP diagram: E2 part of E1 S1 P1 E1 S2 E2 P2 Current situation: Is-A Current situation: All nodes are primitive All Is-A links must be individually modelled P1 and P2 are seldom pre-coordinated in the terminology P1 E1 S2 E2 P2

SEP diagram: finger part of hand hand structure Is-A Current situation: All nodes are primitive All Is-A links must be individually modelled P1 and P2 are seldom pre-coordinated in the terminology part of hand entire hand finger structure entire finger part of finger

SEP diagram: E2 part of E1 with no P1 and no P2 (typical in CTV3) Is-A E1 S2 E2

SEP diagram: E2 part of E1 with no P1 and no P2 (typical in CTV3) hand structure Is-A entire hand Missing explicit representation that the finger is part of the hand finger structure entire finger

SEP diagram: E2 is-a E1 S1 Current situation: All nodes are primitive All Is-A links must be individually modelled P1 E1 S2 E2 P2

SEP diagram: index finger is-a finger finger structure Is-A Current situation: All nodes are primitive All Is-A links must be individually modelled part of finger entire finger structure of index finger entire index finger part of index finger

SEP diagram: E2 is-a E1 S1 Is-A E1 S2 E2

SEP diagram: index finger is-a finger structure of finger Is-A entire finger Usual situation: no “part of” nodes and sometimes the E2->E1 links are missing or incorrect structure of index finger entire index finger

Start of solution: the SEP table The SEP table provides a comprehensive classification of all SNOMED CT anatomy codes Each single row giving: A simple name for the anatomical entity (e.g. “hand”) The code for the “S”, if pre-coordinated (else blank) The code for the “E”, if pre-coordinated (else blank) The code for the “P”, if pre-coordinated (else blank)

Inferred relationships from SEP table part-of (inferred) is-a (inferred) P1 E1 Benefit: All three relationships derive automatically from a single row in the SEP table Requirement Maintenance burden of a valid SEP table (small burden)

Inferred relationships from SEP table structure of hand part-of (inferred) is-a (inferred) part of hand entire hand Benefit: All three relationships derive automatically from a single row in the SEP table: labelled “hand” Requirement Maintenance burden of a valid SEP table (small burden)

E2 part-of E1 S1 P1 E1 S2 E2 P2 Requirements: SEP table classifier part-of (inferred) is-a (inferred) Requirements: SEP table classifier E2: part-of = E1 must be directly modeled Benefit “reified” relations all come automatically P1 E1 S2 E2 P2

finger part-of hand structure of hand part of hand entire hand part-of (inferred) is-a (inferred) Requirements: SEP table classifier E2: part-of = E1 must be directly modeled Benefit “reified” relations all come automatically part of hand entire hand structure of finger entire finger part of finger

E2 isa E1 S1 P1 E1 S2 E2 P2 Requirements: 1. SEP table part-of (inferred) Is-A (inferred) Requirements: 1. SEP table 2. Capable classifier 3. E2 is-a E1 must be directly modeled Benefits Dotted line relations are automatic and reliable P1 E1 S2 E2 P2

What I have to model S1 P1 E1 S2 Is-A E2 P2

What is inferred S1 part-of Is-A P1 E1 S2 E2 P2

What I have to model S1 P1 E1 Part-of S2 E2 P2

What is inferred S1 part-of Is-A P1 E1 S2 E2 P2

Even better: eliminate “S” and “P” Migration path might maintain “S” and “P” algorithmically, for backwards compatibility Curation effort, and naming, can be focused on the “E” Drop the “entire” from the names Potentially major improvement in post-coordination ability Requires some systematic (automatic) substitution changes: new attributes in the definitions of clinical findings, procedures, events, and specimens Other steps: impact assessment revision of implementation advice

How do we model “finding-site” without “S” to refer to? Current situation: Entire limb -> is-a -> Limb structure (S) One attribute: finding-site Edema of extremity: finding-site = limb structure (S) Edema of entire limb: finding-site = entire limb (E) Proposed revision: One target concept: limb Two attributes: finding-site-entire (subrole of) finding-site Right identity: finding-site o part-of -> finding-site This means that findings with sites that are part of the limb will be inferred to have a site of limb Edema of extremity: finding-site = limb Edema of entire limb: finding-site-entire = limb

How does the right identity work? Edema of calf == clinical finding and (rolegroup (associated-morphology = edema)(finding-site = calf)) Calf := (part-of lower limb) Lower limb := limb Edema of limb == clinical finding and (rolegroup (associated-morphology = edema)(finding-site = limb)) Right identity is invoked by the following pair of assertions: (finding-site = calf) and calf := (part-of lower limb) For edema of calf, this infers that (finding-site = lower limb), and therefore edema of calf is a kind of edema of lower limb, which is a kind of edema of limb.

How do we model “procedure-site” without “S” to refer to? Current situation: Entire lung-> is-a -> lung structure (S) Lung excision: procedure-site-direct = lung structure (S) Total pneumonectomy: procedure-site-direct = entire lung (E) Proposed revision: One target concept: lung Two attributes: procedure-site-direct-entire (subrole of) procedure-site-direct Right identity: procedure-site-direct o part-of -> procedure-site-direct This means that procedures with sites that are part of the lung will be inferred to have a site of lung Lung excision: procedure-site-direct = lung Total pneumonectomy: procedure-site-direct-entire = lung

Additional improvements: Consider how to fully define the “E” nodes also Further increases correctness and reliability Further reduces curation burden Next section addresses how to fully define “skin” concepts Using systematic patterns

Kent A. Spackman, MD PhD Sept. 2011 Content Definition Substitution Patterns: Examples from Skin & Integument Kent A. Spackman, MD PhD Sept. 2011 Presentation © 2008 Clinical Terminology Consulting Inc SNOMED Clinical Terms is a Copyright Work of the IHTSDO (www.ihtsdo.org)

Substitution Patterns Define a pattern for concepts of the same type, with one or more variables that are substituted into the pattern to define individual concepts Examples in the past have typically come from the findings and situations hierarchies, but the technique can potentially be used anywhere

Example from situation hierarchy: Clinical finding absent + site Associated finding <finding> Group Finding-site <site> Finding context Known absent Temporal context Current or specified time Subject relationship context Subject of record Clinical-finding-absent-with-site (<finding>,<site>)

Femoral bruit absent Situation Associated finding bruit Group Finding-site Femoral artery Finding context Known absent Temporal context Current or specified time Subject relationship context Subject of record Clinical-finding-absent-with-site (<finding>,<site>)

Applying the approach in anatomy Requires a shift in thinking from the “Structure – Entire – Part” or “SEP” model Allow anatomy entities to be fully defined Manually curate only the “entire” entities Allow “S” to be algorithmically and systematically defined as the disjunction “E or P” Allow “P” to be algorithmically and systematically defined as simply “partOf E”

Consider user requirements Take the anatomical parts of the skin as an example There are multiple layers: Surface Integument Skin Epidermis Dermis Subcutaneous tissue (superficial fascia) There is laterality There are many regions and subregions of the body covered with skin

Using “skin” concepts: requirements (1) Users should be able to select from a (relatively) small list of body regions that are covered with skin Three questions suffice to specify the part intended: What region? (e.g. “hand”) What layer? (e.g. skin, skin and subcutaneous tissue, integument, epidermis, dermis, surface of skin) What laterality? (none, left, or right) Selection of the region should be from a small (ish) list of regions In some cases, a default layer might be assumed (e.g. surface, or skin) Selection of laterality should be prompted only when sensible (yes for ear or hand, no for mouth, nose)

Using “skin” concepts: requirements (2) Inferences should be reliable and consistent (for both terminology curation and patient data retrieval) Infer correct is-a relationships Record “skin of index finger” and infer “skin of finger” Infer correct part-of relationships Record “skin of finger” and infer “part of skin of hand”, but NOT subtype of “skin of hand” Include inferences of sub-layers Record “skin of finger” and infer “part of integument of finger” And include inferences of laterality Record “skin of finger of left hand” and infer “laterality = left”

Use capabilities of EL classifier (e.g. Snorocket) Allow multiple fully-defined clauses Gives the ability to infer partonomy in layers that are not mentioned or recorded Allow transitive object properties X part of Y, and Y part of Z, implies X part of Z Allow role-chaining assertions (object property chaining) Needed for handling laterality part-of o laterality -> laterality X part of Y, and Y laterality LR, implies X laterality LR. So-called “left identity”

Adopt FMA’s partonomy properties PartOf sub-properties: Constitutional part of The epidermis is a constitutional part of the skin Regional part of The skin of the finger is a regional part of the skin of the hand Systemic part of The thyroid gland is a systemic part of the endocrine system

Create common patterns for each layer: Layers where we already have concepts pre-coordinated: Surface Skin Skin and subcutaneous tissue (a.k.a. integument) Subcutaneous tissue (a.k.a. superficial fascia)

Make a list of all regions of the body with skin, integument, surface, or superficial fascia Develop a common list of regions and their pre-coordinated skin, subcutaneous tissue, and surface codes Result: 419 regions. (some currently have no separate code for the region, but only a code for “skin of <region>”) Total possible combinations: 419 regions x 3 (SEP) x 5 = 6285 Number of actually pre-coordinated codes: 1898 S E P Region 223 200 19 Skin 375 241 75 Integument 40 Fascia 240 235 Surface 91 158 1

Curation burden Curate arbitrary set of S, E, P, with no systematic approach (current situation): 1898 current codes, order of magnitude 10^4 possible is-a relationships Potential for additional requests to approach expansion to 6,285 codes Curate “E” only: 419 x 5 = 2,095 Still a large burden Develop systematic pattern for each layer, applied algorithmically (no curation required, all inferences automatic) Curation burden: define the “part-of” relationships of 419 regions Small enough to make this a consensus-based community effort

One more wrinkle: laterality Some regions are lateral (ear, arm, leg) Some regions are not lateral (nose, occipital scalp) Non-systematic curation: Laterality doubles the number of codes to be curated Systemic approach: No increase in manually curated codes. Requires that the 419 regions be classed as lateralizable (yes, no) This is already required to support post-coordination in the first place

Skin of <region> ≡ region of skin constitutional part of <region> ≡ region of skin constitutional part of zone of integument constitutional part of <region>

Skin of <region>, <side> ≡ region of skin constitutional part of <region> laterality <side> ≡ region of skin constitutional part of zone of integument constitutional part of <region> laterality <side> part of ◦ laterality → laterality

surface of <region> ≡ subdivision of surface of body constitutional part of <region> ≡ subdivision of surface of body constitutional part of zone of integument constitutional part of <region>

surface of <region>, <side> ≡ subdivision of surface of body constitutional part of <region> laterality <side> ≡ subdivision of surface of body constitutional part of zone of integument constitutional part of <region> laterality <side> part of ◦ laterality → laterality

subcutaneous tissue of <region> ≡ zone of superficial fascia constitutional part of <region> ≡ zone of superficial fascia constitutional part of zone of integument constitutional part of <region>

subcutaneous tissue of <region>, <side> ≡ zone of superficial fascia constitutional part of <region> laterality <side> ≡ zone of superficial fascia constitutional part of zone of integument constitutional part of <region> laterality <side> part of ◦ laterality → laterality

skin of part of <region> ≡ region of skin regional part of region of skin constitutional part of <region> ≡ region of skin constitutional part of regional part of <region>

skin of part of <region>, <side> ≡ region of skin regional part of region of skin constitutional part of <region> laterality <side> ≡ region of skin constitutional part of regional part of <region> laterality <side> part of ◦ laterality → laterality

Next steps Complete mapping to FMA, and compare is-a relationships ? Look at FMA-owl with enhanced object properties (Alan Ruttenberg is working on this) Create a draft editorial guide for the object properties and patterns used for the alpha version What is aligned with FMA, what is not? Comparison of the hierarchies of the alpha and official anatomy Look for additions and removals, assess correctness (? Sample) Revise alpha version ? Iterate

Next steps (2) Look at aligning object properties with RO (relation ontology) Particularly in the area of location and part-whole relationships Is there a need for has-part? Examine value and use case Comparison of the effect of introducing alpha anatomy as a substitute for “official” anatomy Impact analysis on: Implementation guidance and approaches/strategies Backwards compatibility Post-coordination patterns and advice Correctness of hierarchies Increased reliance on classifier for subsumption testing (difficulty for entry level?)

Next steps (3): Tooling Development of tooling strategy to accommodate: Nested definitions GCIs and multiple sufficient definitions Role chaining (left and right identity) User interface for defining the above Patterns Defining, setting domain for patterns Revision of RF2 implementation to repurpose for: Nested definitions, anonymous concepts?, distribution in relationships table vs refsets

Anatomy project group summary Simplified representation of anatomy Get rid of SEP More intuitive, aligned with FMA, can be partially automatically curated with rules More complexity on some attributes (site for findings and procedures) More expressive with some additional computational complexity Testing will be done to determine correctness and impact