KNOWLEDGE REPRESENTATIONS OF CONSTRAINTS FOR

PATIENT SPECIFIC IOL-DESTINATION

K. P. Scherer

Forschungszentrum Karlsruhe GmbH, Institut für Angewandte Informatik , P.O. Box 3640, 76021 Karlsruhe, Germany

Keywords: Knowledge based system, decision support, frame based representation, configuration system.

Abstract: A knowledge based system is a computer program, which simulates the problem solving process of a

human, who is an expert in this discipline. In the medical area there exist a lot of expert system components

for diagnosis of different diseases. In the ophthalmology, after a cataract surgical incision, the human lens is

removed and an artificial intraocular lens (IOL) is implanted. Because of many preconditions (patient

situation, operation technologies and IOL specifics) a knowledge based system is developed to support the

decision process of the IOL destination under the related (sometimes contradictory) constraints. A computer

aided IOL destination and decision support for a patient related individual optimized lens system can help to

enhance the life style of the bresbyope human. In comparison to classical software systems the heuristic

knowledge from the surgeons (aggregated over many years by research and clinical praxis) can be regarded

and user specific communication with the software system and an explanation part is available for the

decision making process. Useful representations of the situation are formalised knowledge representation

methods.

1 INTRODUCTION

Concerning reconstitute the vision quality for

presbyopes human eyes, a novel artificial

accommodation system (AAS) will be investigated

and developed in the institute of applied computer

science in the research centre Karlsruhe. This is

essential to guarantee life quality at an advanced age.

An optimized configuration and selection of such a

lens system can only guaranteed by a computer aided

decision support system. To do this, it is necessary to

generate and dispose of software structures for

storing and processing the information used in a

consistent manner (Scherer et al., 2006). Formal

representations have to be designed such, that the

information is accessed in a natural language. Based

on this acquired expert knowledge, new knowledge

can be produced and hypotheses and

recommendations can be validated or disproved. In

this proposal, the software components concern on

the selection and destination of parameterized

classical intraocular lenses. A transformation to the

ASS will be performed when the technical

development of the mechatronic system is nearly

finished.

2 BIOLOGICAL BACKGROUNDS

From the biological and medical point of view, a

mechatronic system is researched and developed for

the implantation into the capsule bag of a presbyope

Figure 1: Natural human eye as complex biological tissue.

human being after a cataract disease (Bergemann et

al, 2006). Fig. 1 shows a natural eye with a capsule

bag and an intraocular lens system before the

cataract operation. After extraction of the human

lens, the empty capsule bag should be filled with a

miniaturised complex self sustaining

290

P. Scherer K. (2008).

KNOWLEDGE REPRESENTATIONS OF CONSTRAINTS FOR PATIENT SPECIFIC IOL-DESTINATION.

In Proceedings of the Third International Conference on Software and Data Technologies - PL/DPS/KE, pages 290-294

DOI: 10.5220/0001869602900294

 SciTePress

accommodation system, which is nowhere existent

at time.

cornea

upil

chamber

lens

bulb

vitreous

lens shell

Figure 2: Abstract model of the human eye with the cornea

and the lens as refractive components.

Responsible for the refractive behaviour of the

human eye are the two components cornea with

different anterior and posterior surfaces and

furthermore the clear intraocular lens system (see

Fig. 2). The combination of these ray fractioning

surfaces leads to a more or less sharp image at the

retina. By replacing the human intraocular lens and

implanting a new technical lens system the

characteristic IOL features have to be configured in

such a way, that the desired refraction is performed

for each situation. This selection and component

characterisation must be performed by knowledge

based intelligent methods.

3 KNOWLEDGE DOMAINS

To destine a patient specific well parameterized

IOL, the following constraints must be regarded.

The eye parameter values, resulting from the

ophthalmologic measurement methods content

systematic measurement errors, which must be

corrected in an adequate manner. Furthermore the

IOL’s designed for implantations have fabrication

errors and must be accounted for the IOL parameter

calculation.

IOL

specifics

operational conditions

measure

ments

patient preconditions

relations

Figure 3: Different domain specific classes with relations.

Also any diseases before the cataract intervention

and specific surgeon dependent operational

techniques influence probably the results of the IOL

destination (Haigis et al, 2006). Additionally the

domains (patient preconditions, measurement

methods, fabrication related IOL features,

operational techniques) correlate among each other,

so the dependencies are very complex and they are

no longer linear (Fig. 3). A formalized description of

the different knowledge domains must be performed

(Fig. 4).

patient data:

- medical background

- physiological data

surgical conditions:

- operation techniques

Selection and characterization of an AAS, IOL:

knowledge representations

Figure 4: Knowledge based selection and destination of

the IOL implant.

4 FRAME REPRESENTATIONS

To describe the basic conditions for logical

reasoning a frame based approach is used. (Fig. 5)

Figure 5: Representation of a special class with attributes.

KNOWLEDGE REPRESENTATIONS OF CONSTRAINTS FOR PATIENT SPECIFIC IOL-DESTINATION

291

An extension to a so called concept is given by

evaluation of the possible attribute value by type

checking and range control (Fig. 5).

The class frame contains the following attributes:

• Name/name: name of the class or of the object

• Beschreibung/description: for more details and

specific features of the class

• Fragetext/user question: relevant for the

knowledge acquisition concerning filling the

knowledge base

• Fragetyp/type: specification of the question to

check the validity (real value or multiple-choice

or XML-text or other)

• Wertebereich/range: the range of values for

checking correct input data

• Autor/author: expert, responsible for the

knowledge

• Quelle/source: source of the information

5 RULE BASED APPROACH FOR

IOL SELECTION

For the overall correlated information a rule based

approach is applied with the known Boolean

operators of the predicate calculus of first order. The

evaluation of the attributes in the classes patient

precondition, IOL characteristics, operational

conditions and the ophthalmic measurements form

the symptom tree, otherwise any information about

the selected IOL, the correlated IOL parameters and

IOL types compose the diagnostic tree.

symptoms

(

conditions

)

diagnostics

(

selection

)

IOL

characteristics

operational

conditions

logical inference

Selection of IOL

parameters

types

rules, functions, interpretations

measurements

patient condition

Figure 6: Correlation between symptoms and diagnostics.

6 DOMAIN SPECIFIC

KNOWLEDGE

REPRESENTATION

The modelling of the natural information about the

mentioned semantic topics means the development

of structures, which are formulised in class-subclass-

element relations. Along the relation “is a” between

classes and subclasses and elements an inheritance

mechanism is available. For the attribute slots,

constraints can be formulated. These frame based

approaches form a well defined hierarchical tree

structure for the new information system and are a

prerequisite for starting logical conclusions (Görz et

al, 2007).

6.1 IOL factors

One class-subclass tree concern the different IOL

specific factors, which are relevant for the selection

of a good implant. Not only the thickness of the lens

or design or fabrication related data are responsible

for the choose, also the used mathematical formulas

(Haigis, Hoffer, SRKII) leads to different IOL

parameters, because different preconditions in the

formulas are integrated (Fig. 7) (Findl et al, 2007).

IOL factors

Lens thickness

calculation

radians

desi

fabrication

Hai

Hoffer

Figure 7: Class hierarchy of IOL factors (excerpt).

6.2 Diagnostics

For the implantation of the AAS or a classical lens

system different diagnostic methods are analysed. A

representation class is needed. The attributes of

these classes have both numerical and also linguistic

values. A basic a priori action of the ophthalmic

surgeons to destine a good lens system is the

ceratometry and the axis length measurement at the

patient’s eye. The measurement errors concern the

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different submethods within the two necessary

measurements and they must be taken into account

for IOL destination (see Fig. 8).

Figure 8: Class hierarchy of diagnostics (excerpt).

6.3 Patient Situation

Also the patient specific situation and the history of

personal diseases and former refractive interventions

must be regarded for a correct destination of the

IOL. Patient specific diseases or an ametropia like

myopia or hyperopia and furthermore the age of the

patient or the presence of contact lenses affect the

possible measurement methods and so directly the

IOL destination (see Fig. 9).

Figure 9: Class hierarchy of patient specifics (excerpt).

6.4 Operational Conditions

Last not least the operational methods themselves

like the length of the intracorneal section or the

special location of the surgical intervention of the

eye gives a contribution to the postoperative

behaviour of the selected IOL. Therefore it must be

regarded before a selection is performed (Fig. 10).

Figure 10: Class hierarchy of operational features.

The knowledge entities are inputted into the class-

objects-attribute variables (see also frame based

structures). The knowledge acquisition can be

enhanced by consistency checking during the

acquisition step. Consistence means a validation of

values in a predefined numerical range or linguistic

values within a predefined term set or the number of

allowed values from the whole acquisition set.

This indirect constraint representation prevents

formally correct conclusions from being drawn on

the basis of data that are not allowed.

7 KNOWLEDGE ACQUISITION

Related to many national ophthalmic conferences in

Germany information and statements, published in

different literature are acquired in natural language.

The natural language based predicates are given to a

special medical expert for validation. The question

concerning each special medical statement could be

answered by the possible values

1) The statement is absolutely correct

2) The statement is absolutely wrong

3) Truth is given by a interval [0, 1] value as a

gradually evidence

4) The question is formulated in a wrong way

5) no comment to this knowledge statement.

The catalogue of questions concern the IOL

destination for a cataract patient, dependant on IOL

specifics, the operational conditions regarding

equipment failures and the patient specific situation.

The result of the interview and the comments of the

expert are following (the answers were given in this

first step of knowledge acquisition only by one

expert)

- 65 predicates were formalized.

- 20 statements were absolutely correct.

- 7 statements were absolutely wrong.

diagnostics

ceratometry

axis lenght measurement

manual

automated

ultrasonic Immersion optical

patient specifics

diseases

ametropia

glaucoma

strabism

myopia

hyperopia

ceratoplastics

depth prechamber

pupil width

contact lenses

operational influences

intrao

erativ

postoperative

section len

section location

one-

iece

multi

art

IOL

osition

KNOWLEDGE REPRESENTATIONS OF CONSTRAINTS FOR PATIENT SPECIFIC IOL-DESTINATION

293

- There was no gradually acceptance of information.

- 34 statements remain without any comment.

- 4 statements were formulated in a wrong way.

This procedure has to be performed again by other

experts and the set of formulas has to be enhanced.

But the analysis of the prototypical answers is very

interesting and the conclusion is following (here

only concerning IOL destination)

1) The knowledge concerning the IOL destination

including the different preconditions and

situations is distributed on different experts.

2) The knowledge is not available any time for

each human specialist.

3) The meaning can be contradictory.

The human expert expressions concerning the IOL

destination have to be transformed into rules.

Premises of the rules will be to the domain specific

class and object, conclusions will be results,

attentions and other IOL specifics.

8 EXPLANATION OF

REASONING

The warnings, recommendations and results must be

comprehensible. The explanation component is

responsible for providing the user with explanations

as to how the selection process was performed. It is

essential to understand the reasoning process and to

obtain new ideas for further advanced solution

processes. In this way, the confidence into the

conclusion and the developed knowledge based

system is enhanced.

Due to the probably very complex and wide

solution paths (numerous conditions and constraints)

the user specific results have to be analysed by

backward chaining processes. This requires a

comfortable capacity to interact with the system

through text and graphics.

9 CONCLUSIONS

The benefit and necessity of knowledge based

structures for selection of an optimized

parameterized accommodation system (ASS) are

outlined. The acquired knowledge (in this proposal

for the selection of a classical IOL) must be

managed using intelligent processes, because

absolute information is lacking in the instantaneous

state. Original rules developed may be rewritten

later and redefined. The complex knowledge is more

circular than linear. In this meaning comfortable

formulised structures and refinement mechanisms

must be developed as well as comfortable decision

making processes including their explanation

(configuration and selection).

Hence, the classical algorithmic based system has to

be extended to a knowledge based system for

selection and optimizing the IOL’s with following

advantages:

 Natural language based user access

 Object oriented knowledge structuring

 Generation of network with causal relations

 Consistent extension of knowledge base

 Comfortable consistent refinement process

The advantage of a frame based information system

could be demonstrated. Formal representations are

designed for knowledge acquisition and the static

knowledge base, where an inference engine starts

with logical methods to select the desired patient

specific implant. Furthermore, causal relations and

interactive effects between the different

preoperational conditions have to be regarded in the

configuration and selection process.

REFERENCES

Scherer, K.P., Guth, H., Stiller, P., 2006, Computational

Biomechanics and Knowledge based Structuring of

Human Eye Components, International Congress on

Applied Modelling and Simulation, Rhodes, Greece,

June 26-28, 2006 ISBN 0-88986-561-2.

Bergemann, M., Gengenbach, U., Bretthauer, G., Guthoff,

R., 2006, Artificial Accommodation System – a new

approach to restore the accommodative ability of the

human eye. In: World Congress on Medical Physics

and Biomedical Engineering. Seoul.

Haigis W., IOL-Berechnung nach refraktiver

Laserchirurgie aus aktuellen Messwerten, in Klinische

Monatsblätter Augenheilkunde 2006, No. 223, Suppl.

1, 20. Jahrestagung DGII, 2006,

Puppe, F., Reinhardt, B., 2001, Multimediale wissens- und

fallbasierte Trainings- und Informationssysteme in der

Medizin, BMFT-Verbundprojekt, Projektträger DLR,

Förderkennz: 01EI9603/1,2001.

Görz G., Rollinger C.-R., Schneeberger J. (Ed.),

Handbuch der Künstlichen Intelligenz, in Fachbereich

1 „Künstliche Intelligenz“ der Gesellschaft für

Informatik e.V, Oldenburg Verlag München, Wien,

2007

Findl O., Biometry and intraocular lens power calculation

for cataract surgery, in Spektrum der Augenheilkunde,

Vol. 21, No. 2, Springer Verlag Wien, ISSN 09304282,

2007

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