Reproduced with permission from NeXT Computer, Inc., USA, NeXT on Campus, Fall 1990. ã 1990 NeXT Computer, Inc., USA

University of Washington
Building blocks to better medicine: developing a structural biology knowledge base
 
The practice of medicine depends on a comprehensive understanding of structural biology, which may be defined as the physical organization of the human body, ranging from gross anatomy to molecules.  Advances in medical imaging and biotechnology have caused an explosion in structural information. Making this ever-increasing information available to the medical community in a useful, accessible manner is a difficult task.
 
Bill Barker and Jim Brinkley of the University of Washington's Structural Informatics Group are using a network of NeXT and other computers to meet this challenge.  Structural knowledge is more than the separate facts and figures about individuals commonly stored in databases. Instead, a knowledge base contains general information about entire classes of individuals. For example, a database might contain a 3D reconstruction of a kidney, whereas a knowledge base would describe both the expected shape and the range of variation for the class of all normal kidneys. A knowledge base of structural biology could therefore improve a physician's (or a computer's) diagnostic and treatment-planning capabilities by allowing application of general medical knowledge to specific patients.

The amount of structural information is too great for one research group to gather, so the university's group is designing a framework to allow other research groups to build discrete portions of this knowledge base.
 
"We chose the NeXT Computer as our primary knowledge base-development platform because of its outstanding object-oriented programming environment, and because of the ease with which we'll be able to build distributed, object-oriented knowledge-based systems to test our ideas," explains Brinkley. 

Via computer networks, the modules will be able to run on different computers in scattered locations worldwide.  Groups of experts will work together to create larger systems than one group could create alone.  "The design is that of a distributed system consisting of many independently developed modules running either on the same or different computers," says Brinkley.

Since the problem of representing structural knowledge is far from solved, Brinkley's group is concentrating on specific problems whose incremental solution will lead to better methods for representing that knowledge.

One such problem is finding specific biological objects in medical images. This occurs in many areas of medicine, from identification of cells on microscopic slides to extraction of organs in 3D image data. For example, physicians need to extract the kidney from computed tomography images of patients undergoing radiation treatment for cancer. Once the kidney is isolated, other computer programs can plan the treatment so minimal radiation reaches the kidney and maximal radiation reaches the tumor.  Currently, experts trained in anatomy manually trace these structures in medical images.  Because manual tracing  takes a tremendous amount of time, Brinkley wrote an application that uses knowledge of anatomy to partially automate this process.

The application, called SCANNER, takes a cross-sectional image of part of the human body, and isolates a structure such as a kidney within the image. With an initial starting point entered by the user, SCANNER retrieves a stored model representing spatial knowledge of both the expected shape and the range of variation for the class of all kidneys. This model then defines a region on the image within which the computer searches for the kidney borders (the inner and outer lines in the figure). The model also defines a current "best guess" as to the contour of the kidney (the middle line). As kidney borders are found, the search region shrinks and the best guess contour is adjusted until it matches the shape of the kidney in the image.

As an offshoot of the SCANNER project, the group created an object-oriented medical image processing framework that works as a front-end to other image processors.  Brinkley credits the distributed object-oriented environment running on the NeXT Computer for making this task comparatively easy. Looking to the future, he says, "As our knowledge bases evolve, and as we work with other groups, we expect the NeXT Computer will continue to play a major role as an intelligent center of our knowledge-based systems."
 
Bill Barker
barker@ulnar.biostr.washington.edu
(206)543-7315
James F. Brinkley
brinkley@synapse.biostr.washington.edu 
(206)543-3954
Structural Informatics Group 
Department of Biological Structure
University of Washington