DECISION-ANALYSIS METHODOLOGY IN THE WORK-UP OF WOMEN WITH SUSPECTED SILICONE BREAST IMPLANT RUPTURE

Despite numerous studies advocating ultrasonography and magnetic reson ance imaging (MRI) in the evaluation of women with possible silicone b reast implant rupture, an appropriate algorithm has not been published for the optimal use of these tests. To derive a diagnostic algorithm using ultrasonography and MRI, we applied a decision-analytic model us ing Bayes' theorem to calculate the probabilities of implant rupture f or three representative patient characteristics.A Medline search was c onducted to identify literature related to the diagnosis of silicone b reast implant rupture using ultrasonography and MRI since 1994. Also e xamined were case series of implant rupture to obtain rupture prevalen ce in cases in which rupture was dependent on patient presentation (sy mptomatic versus asymptomatic) and dependent on implant age. Test char acteristics (sensitivity and specificity) and implant rupture prevalen ce are used to calculate the probability of rupture by using Bayes' th eorem. These probabilities are derived for three patient categories: ( 1) asymptomatic, (2) symptomatic with implant age less than or equal t o 10 years, and (3) symptomatic with implant age >10 years. In asympto matic patients, the pretest rupture prevalence is 6.5 percent. If a sc reening ultrasonography shows no rupture, the probability of rupture d rops to 2.2 percent. If ultrasonography shows rupture, the probability of true rupture increases to 37.8 percent. Removal of implants in thi s setting will result in a high probability of extracting normal impla nts. However, if MRI after the ultrasonography shows rupture, the prob ability of true rupture increases to 86 percent, which gives better as surance of removing true-ruptured implants. In ''symptomatic'' patient s (i.e., breast asymmetry, capsular contracture) with implants less th an or equal to 10 years old, the prevalence of rupture is estimated at 31 percent. If ultrasonography shows no rupture, the probability of r upture drops to 16 percent. If ultrasonography shows rupture, the prob ability of true rupture is 79.7 percent, and this probability increase s to 97.5 percent if a follow-up MRI also shows rupture. In symptomati c patients with implants >10 years old, the prevalence of rupture is e stimated at 64 percent. If ultrasonography shows rupture, the probabil ity of true rupture increases to 94 percent, and no further diagnostic work-up is necessary. In an asymptomatic patient who is worried about the integrity of her implants, ultrasonography should be used as an i nitial diagnostic test because of its lower cost. If ultrasonography s hows no rupture, no further work-up is necessary. If ultrasonography s hows rupture, the low probability (37.8 percent) of true rupture requi res a confirmatory test using MRI. In ''symptomatic'' patients, the hi gh prevalence of rupture markedly raises the posttest probability of r upture for positive ultrasonography findings. Particularly in ''sympto matic'' patients with implants > 10 years old, the high posttest proba bility of rupture (94 percent) with a positive ultrasonography obviate s the need for any further diagnostic testing. This diagnostic algorit hm will assist plastic surgeons in counseling women who are worried ab out the integrity of their silicone breast implants.