Decision-analysis methodology in the work-up of women with suspected silicone breast implant rupture.
Despite numerous studies advocating ultrasonography and magnetic resonance imaging (MRI) in the evaluation of women with possible silicone breast 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 using Bayes' theorem to calculate the probabilities of implant rupture for three representative patient characteristics. A Medline search was conducted to identify literature related to the diagnosis of silicone breast implant rupture using ultrasonography and MRI since 1994. Also examined were case series of implant rupture to obtain rupture prevalence in cases in which rupture was dependent on patient presentation (symptomatic versus asymptomatic) and dependent on implant age. Test characteristics (sensitivity and specificity) and implant rupture prevalence are used to calculate the probability of rupture by using Bayes' theorem. These probabilities are derived for three patient categories: (1) asymptomatic, (2) symptomatic with implant age < or = 10 years, and (3) symptomatic with implant age >10 years. In asymptomatic patients, the pretest rupture prevalence is 6.5 percent. If a screening ultrasonography shows no rupture, the probability of rupture drops to 2.2 percent. If ultrasonography shows rupture, the probability of true rupture increases to 37.8 percent. Removal of implants in this setting will result in a high probability of extracting normal implants. However, if MRI after the ultrasonography shows rupture, the probability of true rupture increases to 86 percent, which gives better assurance of removing true-ruptured implants. In "symptomatic" patients (i.e., breast asymmetry, capsular contracture) with implants < or = 10 years old, the prevalence of rupture is estimated at 31 percent. If ultrasonography shows no rupture, the probability of rupture drops to 16 percent. If ultrasonography shows rupture, the probability of true rupture is 79.7 percent, and this probability increases to 97.5 percent if a follow-up MRI also shows rupture. In symptomatic patients with implants >10 years old, the prevalence of rupture is estimated at 64 percent. If ultrasonography shows rupture, the probability 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 initial diagnostic test because of its lower cost. If ultrasonography shows no rupture, no further work-up is necessary. If ultrasonography shows rupture, the low probability (37.8 percent) of true rupture requires a confirmatory test using MRI. In "symptomatic" patients, the high prevalence of rupture markedly raises the posttest probability of rupture for positive ultrasonography findings. Particularly in "symptomatic" patients with implants >10 years old, the high posttest probability of rupture (94 percent) with a positive ultrasonography obviates the need for any further diagnostic testing. This diagnostic algorithm will assist plastic surgeons in counseling women who are worried about the integrity of their silicone breast implants.
Chung
K C
KC
University of Michigan Medical Center and Department of Clinical Research, St. Joseph Mercy Hospital, Ann Arbor 48109-0340, USA.
Greenfield
M L
ML
Walters
M
M
D001499:Bayes Theorem; D018427:Breast Implants; D003661:Decision Support Techniques; D003663:Decision Trees; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008279:Magnetic Resonance Imaging; D011183:Postoperative Complications / Q000175:diagnosis* / Q000601:surgery; D011475:Prosthesis Failure; D012086:Reoperation; D012422:Rupture, Spontaneous; D012680:Sensitivity and Specificity; D012826:Silicone Elastomers; D016217:Ultrasonography, Mammary
D012826:Silicone Elastomers