Millions of women worldwide have silicone breast implants. It has been reported that implant failure occurs in approximately a tenth of patients within 10 years, and the consequences of dissemination of silicone debris are poorly understood. Currently, silicone detection in histopathological slides is based on morphological features as no specific immunohistochemical technique is available. Here, we show the feasibility and sensitivity of stimulated Raman scattering (SRS) imaging to specifically detect silicone material in stained histopathological slides, without additional sample treatment. Histology slides of four periprosthetic capsules from different implant types were obtained after explantation, as well as an enlarged axillary lymph node from a patient with a ruptured implant.Abbreviations: CC, connected component; OPO, optical parametric oscillator; PDMS, polydimethylsiloxane; PU, polyurethane; RMSE, root mean square error; ROI, region of interest; SRS, stimulated Raman scattering.Ludo van Haasterecht and Liron Zada contributed equally to this work.

Raman spectroscopy is a valuable tool for non-destructive vibrational analysis of chemical compounds in various samples. Through 2D scanning, it one can map the chemical surface distribution in a heterogeneous sample. These hyperspectral Raman images typically contain spectra of pure compounds that are hidden within thousands of sum spectra. Inspecting each spectrum to find the pure compounds in the dataset is impractical, and several algorithms have been described in the literature to help analyze such complex datasets. However, choosing the best approach(es) and optimizing the parameters is often difficult, and the necessary software was not yet combined in a single program. Therefore, we introduce RamanLIGHT, a fast and simple app to pre-process Raman mapping datasets and apply up to eight unsupervised unmixing algorithms to find endmember spectra of pure compounds. The user can select from six smoothing methods, four fluorescence baseline-removal methods, four normalization methods, and cosmic-ray and outlier removal to generate a uniform dataset prior to the unmixing. We included the most promising pre-processing methods, since there is no routine that perfectly fits all types of samples. Unmixed endmember spectra can be further used to visualize the distribution of compounds in a sample by creating abundance maps for each endmember separately, or a single labeled image containing all endmembers. It is also possible to create a mean spectrum for each endmember, which better describes the true compound spectrum. We tested RamanLIGHT on three samples: an aspirin-paracetamol-caffeine tablet, Alzheimer’s disease brain tissue and a phase-separated polymer coating. The datasets were pre-processed and unmixed within seconds to gain endmembers of known and unknown chemical compounds. The unmixing algorithms are sensitive to noisy spectra and strong fluorescence backgrounds, so it is important to apply pre-processing methods to a suitable degree. RamanLIGHT is freely available as a MATLAB and soon as standalone app.

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ince its introduction, the use of silicone breast implants for reconstructive and cosmetic purposes has increased significantly; thus, breast implant surgery is one of the most frequently performed procedures by plastic surgeons worldwide. 1,2 Simultaneously, extensive research efforts and lively discussions on their safety and complications continue. [3][4][5][6][7][8][9][10][11][12] Although most of the recent attention is focused on breast implant-associated anaplastic large cell lymphoma 13 and breast implant illness, 14 the most common complications are still related to the capsule surrounding the implant. Capsule formation is a normal foreign Background: Breast implant surgery is one of the most frequently performed procedures by plastic surgeons worldwide. However, the relationship between silicone leakage and the most common complication, capsular contracture, is far from understood. This study aimed to compare Baker grade I with Baker grade IV capsules regarding their silicone content in an intradonor setting, using two previously validated imaging techniques. Methods: Twenty-two donor-matched capsules from 11 patients experiencing unilateral complaints were included after bilateral explantation surgery. All capsules were examined using both stimulated Raman scattering (SRS) imaging and staining with modified oil red O (MORO). Evaluation was done visually for qualitative and semiquantitative assessment and automated for quantitative analysis. Results: Using both SRS and MORO techniques, silicone was found in more Baker grade IV capsules (eight of 11 and 11 of 11, respectively) than in Baker grade I capsules (three of 11 and five of 11, respectively). Baker grade IV capsules also showed significantly more silicone content compared with the Baker grade I capsules. This was true for semiquantitative assessment for both SRS and MORO techniques (P = 0.019 and P = 0.006, respectively), whereas quantitative analysis proved to be significant for MORO alone (P = 0.026 versus P = 0.248 for SRS, respectively). Conclusions: In this study, a significant correlation between capsule silicone content and capsular contracture is shown. An extensive and continued foreign body response to silicone particles is likely to be responsible. Considering the widespread use of silicone breast implants, these results affect many women worldwide and warrant a more focused research effort.