Use Of Clinical Decision Analysis In Predicting The Efficacy Of Newer Radiological Imaging Modalities: Radioscintigraphy Versus Single Photon Transverse Section Emission Computed Tomography

Abstract Sensitivity, specificity, and predictive accuracy have been shewn to be useful measures of the clinical efficacy of diagnostic tests and can be used to predict the potential improvement in diagnostic certitude resulting from the introduction of a carpeting technology. This camtunication demonstrates how the informal use of clinical decision analysis may guide health planners in the allocation of resources, purchasing decisions, and implementation of high technology. For didactic purposes the focus is on a comparison between conventional planar radioscintigraphy (RS) and single photon transverse section emission conputed tomography (SPECT). For example, positive predictive accuracy (PPA) for brain RS in a specialist hospital with a 50% disease prevalance is about 95%. SPECT should increase this predicted accuracy to 96%. In a priinary care hospital with only a 15% disease prevalance the PPA is only 77% and SPEC! may increase this accuracy to about 79%. Similar calculations based on published data show that marginal improvements are expected with SPECT in the liver.It is concluded that: a) The decision to purchase a high technology imaging modality such as SPECT for clinical purposes should be analyzed on an individual organ system and institutional basis. High technology may be justified in specialist hospitals but not necessarily in primary care hospitals. This is more dependent on disease prevalance than procedure volume; b) It is questionable whether SPECT imaging will be competitive with standard RS procedures. Research should concentrate on the development of different medical applications.IntroductionThe rapid growth of imaging modalities in recent years1'^ has given impetus to the critical evaluation of the efficacy of these technologies. Criteria for such evaluations may include: (a) Improved diagnostic information, (b) Improved therapy planning, (c) Changes in long- and short-term health outcomes; either morbidity or mortality, and (d) Decreased financial costs associated with diagnosis or treatment3. In many cases in the initial phases of technology assessment, estimates of improvement in diagnostic information appears to be the method of choice.Receiver operator characteristic (ROC) curve analysis may be the best evaluator of the quality of diagnostic information3' . However, ROC analysis requires extensive clinical trials and considerable elapsed time before a consensus can be reached. Sensitivity, specificity, and predictive accuracy are useful measures of the clinical efficacy of diagnostic tests (See Table 1 for terminology) . These measures may also be useful in predicting the potential improvement in diagnostic information resulting from the introduction of a new, competing technology. The capability to estimate the future potential of a technology is important to guide scientists, physicians, and health planners in the allocation of resources for further evaluation of such technologies and to guide purchasing decisions and implementation of high technology.As an example of such an evaluation, the predictive accuracy of conventional radioscintigraphy (RS) of the liver and brain based on published data of sensitivity and specificity is compared with the expected predictive accuracy of single photon transverse section emission computed tomography (SPECT) .Liver ImagingSeveral reviews of the sensitivity and specificity of the radioscintigraphy of liver disease using conventional Tc-99m labelled colloid and Anger cameras have been published^-"1^. Reported sensitivities range from 15% to 97%. Possible reasons for these wide variations have been discussed by Drum11. In general, sensitivities from 85% to 95% and specificities from 75% to 85% should be expected with adequate technique11. For purposes of this paper a sensitivity of 90% and specificity 80% will be assumed for conventional RS.Data are meager and conflicting concerning the expected improvement resulting from SPECT imaging 12 '.1 ^ Dendy, et al , reported no significant increase whereas Berche, et al, reported a significant increase in accuracy of diagnosis in liver disease using SPECT. Instrumentation and technique of interpretation varied as a direct comparison of the two studies is difficult. Assuming a modest increase of 5% for both sensitivity and specificity using SPECT, the positive predictive accuracy (PPA) and negative predictive accuracy (NPA) for varying disease prevalences has been calculated. The results are given in Table 2.