• Lisbet R Hölmich, Ilse Vejborg, Carsten Conrad, Susanne Sletting, and Joseph K McLaughlin.
• Institute of Cancer Epidemiology, Danish Cancer Society, Strandboulevarden 49, DK-2100 Copenhagen, Denmark. lisbet@cancer.dk
• Eur J Radiol. 2005 Feb 1; 53 (2): 213-25.

Study ObjectiveThe aim of this study was to evaluate the accuracy of Magnetic Resonance Imaging (MRI) as performed according to a strict study protocol in diagnosing rupture of silicone breast implants.Material And MethodsThe study population consisted of 64 women with 118 implants, who had participated in either one or two study MRI examinations, aiming at determining the prevalence and incidence of silent implant rupture, respectively, and who subsequently underwent explantation. Implant rupture status was determined by four independent readers and a consensus diagnosis of either rupture (intracapsular or extracapsular), possible rupture or intact implant was then obtained. Strict predetermined rupture criteria were applied as described in this report and findings at surgery were abstracted in a standardised manner and results compared.ResultsAt MRI, 66 implants were diagnosed as ruptured, nine as possibly ruptured and 43 as intact. Among the ruptured implants, 27 were categorized as extracapsular. At surgery, on average 297 days after the MRI, 65 of the 66 rupture diagnoses were confirmed, as were 20 of the cases with extracapsular silicone. Eight of the nine possibly ruptured implants were in fact ruptured at surgery. Thirty-four of the 43 intact implants were described as intact at surgery. When categorising possible ruptures as ruptures, there were one false positive and nine false negative rupture diagnoses at MRI yielding an accuracy of 92%, a sensitivity of 89%, and a specificity of 97%. Correspondingly, the predictive value of a positive MRI examination was 99% and the predictive value of a negative MRI examination was 79%.ConclusionsWe conclude that MRI is highly accurate for identification of silicone breast implant rupture, with a high sensitivity and specificity when evaluation of images are based on presence of well-defined rupture criteria.

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