Garcia Ernest V, Taylor Andrew, Halkar Raghuveer, Folks Russell, Krishnan Meghna, Cooke C David, Dubovsky Eva
Department of Radiology, Emory University School of Medicine Atlanta, Georgia 30322, USA.
J Nucl Med. 2006 Feb;47(2):320-9.
A renal expert system (RENEX) has been developed to assist physicians detect renal obstruction in patients undergoing pre- and postfurosemide 99mTc-mercaptoacetyltriglycine (99mTc-MAG3) scans. RENEX uses quantitative parameters extracted from the dynamic renal scan data and heuristic rules in the form of a knowledge base (KB) obtained from expert interpreters to conclude whether a kidney is obstructed.
Normal limits were established for 47 quantitative parameters extracted from the 99mTc-MAG3 scans of 100 potential renal donors. From these data the domain expert estimated 5 boundary conditions for each parameter: (i) definitely abnormal, (ii) probably abnormal, (iii) equivocal, (iv) probably normal, and (v) definitely normal. A sigmoid-type curve was then generated from these 5 boundary conditions, creating a parameter knowledge library used for converting the value of a prospective patient's individual quantitative parameters to a certainty factor (CF). Sixty heuristic rules were extracted from the domain expert to generate the KB for detecting obstruction. A forward-chaining inference engine was developed using the MYCIN combinatories (an approximation of Bayes theorem) to determine obstruction. A justification engine was implemented, which recorded the sequence of each rule that was fired and the current CF value of all input and output parameters at the time of instantiation to track and justify the logic of the conclusions. The entire system was fine tuned and tested using a pilot group of 32 patients (11 males, 21 females; mean age, 56.8 +/- 17.2 y; 63 kidneys) deemed by an expert panel to have 41 unobstructed kidneys, 13 obstructed kidneys,and 9 equivocal findings.
RENEX agreed with the expert panel in 92% (12/13) of the obstructed kidneys, 93% (38/41) of the unobstructed kidneys, and 78% (7/9) of the kidneys interpreted as equivocal for obstructions. Processing time per patient was practically instantaneous using a 3.0-GHz personal computer programmed using interactive data language.
We have developed a renal expert system for detecting renal obstruction using pre- and postfurosemide 99mTc-MAG3 renal scans, at a standardized expert level. These encouraging preliminary results warrant a prospective study in a large population of patients with and without renal obstruction to establish the diagnostic performance of this system.
已开发出一种肾脏专家系统(RENEX),以协助医生在使用速尿前后的99m锝-巯基乙酰三甘氨酸(99mTc-MAG3)扫描中检测患者的肾脏梗阻情况。RENEX利用从动态肾脏扫描数据中提取的定量参数以及从专家解释中获得的知识库(KB)形式的启发式规则,来判断肾脏是否梗阻。
为从100名潜在肾脏供体的99mTc-MAG3扫描中提取的47个定量参数确定正常范围。领域专家根据这些数据为每个参数估计了5个边界条件:(i)肯定异常,(ii)可能异常,(iii)不明确,(iv)可能正常,以及(v)肯定正常。然后根据这5个边界条件生成一条S型曲线,创建一个参数知识库,用于将未来患者个体定量参数的值转换为确定性因子(CF)。从领域专家那里提取了60条启发式规则,以生成用于检测梗阻的知识库。使用MYCIN组合(贝叶斯定理的一种近似)开发了一个正向链推理引擎,以确定是否存在梗阻。实现了一个理由引擎,它记录每条被触发规则的顺序以及实例化时所有输入和输出参数的当前CF值,以跟踪和证明结论的逻辑。整个系统使用由32名患者(11名男性,21名女性;平均年龄56.8±17.2岁;63个肾脏)组成的试验组进行了微调与测试,专家小组认为其中41个肾脏无梗阻,13个肾脏梗阻,9个结果不明确。
RENEX在92%(12/13)的梗阻肾脏、93%(38/41)的无梗阻肾脏以及78%(7/9)被解释为梗阻不明确的肾脏方面与专家小组的意见一致。使用交互式数据语言编程的3.0 GHz个人计算机,每位患者的处理时间几乎是即时的。
我们开发了一种肾脏专家系统,用于使用速尿前后的99mTc-MAG3肾脏扫描来检测肾脏梗阻,达到了标准化的专家水平。这些令人鼓舞的初步结果值得在大量有和没有肾脏梗阻的患者中进行前瞻性研究,以确定该系统的诊断性能。