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A Software Engine to Justify the Conclusions of an Expert System for Detecting Renal Obstruction on ^99mTc-MAG3 Scans

Department of Radiology, Emory University School of Medicine, Atlanta, Georgia

Correspondence: For correspondence or reprints contact: Ernest V. Garcia, PhD, Emory University Hospital, Room E163, 1364 Clifton Rd., NE, Atlanta, GA 30322. E-mail: Ernest.Garcia{at}emoryhealthcare.org

The purposes of this study were to describe and evaluate a software engine to justify the conclusions reached by a renal expert system (RENEX) for assessing patients with suspected renal obstruction and to obtain from this evaluation new knowledge that can be incorporated into RENEX to attempt to improve diagnostic performance. Methods: RENEX consists of 60 heuristic rules extracted from the rules used by a domain expert to generate the knowledge base and a forward-chaining inference engine to determine obstruction. The justification engine keeps track of the sequence of the rules that are instantiated to reach a conclusion. The interpreter can then request justification by clicking on the specific conclusion. The justification process then reports the English translation of all concatenated rules instantiated to reach that conclusion. The justification engine was evaluated with a prospective group of 60 patients (117 kidneys). After reviewing the standard renal mercaptoacetyltriglycine (MAG3) scans obtained before and after the administration of furosemide, a masked expert determined whether each kidney was obstructed, whether the results were equivocal, or whether the kidney was not obstructed and identified and ranked the main variables associated with each interpretation. Two parameters were then tabulated: the frequency with which the main variables associated with obstruction by the expert were also justified by RENEX and the frequency with which the justification rules provided by RENEX were deemed to be correct by the expert. Only when RENEX and the domain expert agreed on the diagnosis (87 kidneys) were the results used to test the justification. Results: RENEX agreed with 91% (184/203) of the rules supplied by the expert for justifying the diagnosis. RENEX provided 103 additional rules justifying the diagnosis; the expert agreed that 102 (99%) were correct, although the rules were considered to be of secondary importance. Conclusion: We have described and evaluated a software engine to justify the conclusions of RENEX for detecting renal obstruction with MAG3 renal scans obtained before and after the administration of furosemide. This tool is expected to increase physician confidence in the interpretations provided by RENEX and to assist physicians and trainees in gaining a higher level of expertise.

Key Words: diuresis renography • expert systems • justification engines

COPYRIGHT © 2007 by the Society of Nuclear Medicine, Inc.

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				A. Taylor, E. V. Garcia, J. N. G. Binongo, A. Manatunga, R. Halkar, R. D. Folks, and E. Dubovsky Diagnostic Performance of an Expert System for Interpretation of 99mTc MAG3 Scans in Suspected Renal Obstruction J. Nucl. Med., February 1, 2008; 49(2): 216 - 224. [Abstract] [Full Text] [PDF]