Publications (3)10.31 Total impact
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ABSTRACT: Decision support systems for imaging analysis and interpretation are rapidly being developed and will have an increasing impact on the practice of medicine. RENEX is a renal expert system to assist physicians evaluate suspected obstruction in patients undergoing mercaptoacetyltriglycine (MAG3) renography. RENEX uses quantitative parameters extracted from the dynamic renal scan data using QuantEM™II and heuristic rules in the form of a knowledge base gleaned from experts to determine if a kidney is obstructed; however, RENEX does not have access to and could not consider the clinical information available to diagnosticians interpreting these studies. We designed and implemented a methodology to incorporate clinical information into RENEX, implemented motion detection and evaluated this new comprehensive system (iRENEX) in a pilot group of 51 renal patients. To reach a conclusion as to whether a kidney is obstructed, 56 new clinical rules were added to the previously reported 60 rules used to interpret quantitative MAG3 parameters. All the clinical rules were implemented after iRENEX reached a conclusion on obstruction based on the quantitative MAG3 parameters, and the evidence of obstruction was then modified by the new clinical rules. iRENEX consisted of a library to translate parameter values to certainty factors, a knowledge base with 116 heuristic interpretation rules, a forward chaining inference engine to determine obstruction and a justification engine. A clinical database was developed containing patient histories and imaging report data obtained from the hospital information system associated with the pertinent MAG3 studies. The system was fine-tuned and tested using a pilot group of 51 patients (21 men, mean age 58.2 ± 17.1 years, 100 kidneys) deemed by an expert panel to have 61 unobstructed and 39 obstructed kidneys. iRENEX, using only quantitative MAG3 data agreed with the expert panel in 87 % (34/39) of obstructed and 90 % (55/61) of unobstructed kidneys. iRENEX, using both quantitative and clinical data agreed with the expert panel in 95 % (37/39) of obstructed and 92 % (56/61) of unobstructed kidneys. The clinical information significantly (p < 0.001) increased iRENEX certainty in detecting obstruction over using the quantitative data alone. Our renal expert system for detecting renal obstruction has been substantially expanded to incorporate the clinical information available to physicians as well as advanced quality control features and was shown to interpret renal studies in a pilot group at a standardized expert level. These encouraging results warrant a prospective study in a large population of patients with and without renal obstruction to establish the diagnostic performance of iRENEX.European Journal of Nuclear Medicine 05/2012; 39(9):1483-91. · 4.53 Impact Factor
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ABSTRACT: Kidney motion during dynamic renal scintigraphy can cause errors in calculated renal function parameters. Our goal was to develop and validate algorithms to detect and correct patient motion. We retrospectively collected dynamic images from 86 clinical renal studies (42 women, 44 men), acquired using (99m)Tc-mercaptoacetyltriglycine (80 image frames [128 × 128 pixels; 3.2 mm/pixel]: twenty-four 2-s frames, sixteen 15-s frames, and forty 30-s frames). We simulated 10 types of vertical motion in each patient study, resulting in 860 image sets. Motion consisted of up or down shifts of magnitude 0.25 pixel to 4 pixels per frame and was either a gradual shift additive over multiple frames or an abrupt shift of one or more consecutive frames, with a later return to the start position. Additional horizontal motion was added to test its effect on detection of vertical motion. Original and shifted files were processed using a motion detection algorithm. Corrective shifts were applied, and the corrected and original (unshifted) images were compared pixel by pixel. Motion detected in the shifted data was also tabulated before and after correction of motion detected in the original data. A detected shift was considered correct if it was within 0.25 pixel of the simulated magnitude. Software was developed to facilitate visual review of all images and to summarize kidney motion and motion correction using linograms. Overall detection of simulated shifts was 99% (3,068/3,096 frames) when the existing motion in the original images was first corrected. When the original motion was not corrected, overall shift detection was 76% (2,345/3,096 frames). For image frames in which no shift was added (and original motion was not corrected), 87% (27,142/31,132 frames) were correctly detected as having no shift. When corrected images were compared with original images, calculated count recovery was 100% for all shifts that were whole-pixel magnitudes. For fractional-pixel shifts, percentage count recovery varied from 52% to 73%. Visual review suggested that some original frames exhibited true patient motion. The algorithm accurately detected motion as small as 0.25 pixel. Whole-pixel motion can be detected and corrected with high accuracy. Fractional-pixel motion can be detected and corrected, but with less accuracy. Importantly, by accurately identifying unshifted frames, the algorithm helps to prevent the introduction of errors during motion correction.Journal of Nuclear Medicine Technology 06/2011; 39(2):131-9.
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ABSTRACT: 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. 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. 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. 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.Journal of Nuclear Medicine 04/2007; 48(3):463-70. · 5.77 Impact Factor