# Confocal Raman Microscopy to Study Silicone Breast Implant's Early-Stage Degradation in Reconstructive Surgery

Duong Phu Le, Richard Younes, Frédéric Cuisinier, Frédéric Bodin, Nadia

Bahlouli, Simon Chatelin, Hamideh Salehi

► To cite this version:

Duong Phu Le, Richard Younes, Frédéric Cuisinier, Frédéric Bodin, Nadia Bahlouli, et al. Confo-cal Raman Microscopy to Study Silicone Breast Implant's Early-Stage Degradation in Reconstruc-tive Surgery. Journal of Biophotonics, 2026, 19 (1), pp.e202500510. 10.1002/jbio.202500510. hal-05472100

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# Confocal Raman microscopy to study silicone breast implant's early degradation in reconstructive surgery

Phu Duong Le<fnref n="1" /> | Richard Younes<fnref n="2" /> | Frédéric Cuisinier<fnref n="2" /> | Frédéric Bodin<fnref n="1" />,<fnref n="3" /> | Nadia Bahlouli<fnref n="1" /> | Simon Chatelin<fnref n="1" /> | Hamideh Salehi<fnref n="1" />

**Correspondence:** Phu Duong Le (pdle@unistra.fr)

**Keywords:** Raman spectroscopy | material degradation | silicon breast implant | polydimethylsiloxane (PDMS) | principal component

## ABSTRACT

The adverse effects of breast implants, especially silicone breast implants, are increasingly being shown. In addition to complications related to surgical technique and individual patient factors, the implant aging is suspected of being one of the main causes.

This study employs Raman technique, label-free, non-destructive method that provides chemical composition information, to clarify the structure of the membrane and its gel-bleeding prevention function. The results identified two important markers - diphenylsiloxane and CH₃ vibration - that can evaluate the degradation of silicone breast implants over time. In addition, two Raman bands at 1159 and 1524 cm⁻<fnref n="1" />, indicative of gel yellowing were identified, providing potential insights into the permeation of external substances into the gel through the membrane. The results are consistent with previous observations and highlight the potential of deep learning models to determine degradation time thresholds based on these identified markers.

analysis (PCA)

## 1 | Introduction

Breast implant rupture represents a serious complication, particularly in post-mastectomy breast reconstruction patients, who often have limited soft-tissue coverage over the device and may be further compromised by the effects of adjuvant radiation therapy [1][2]. Such ruptures may lead to a spectrum of consequences, ranging from local inflammatory responses and scar formation to swelling, redness, breast deformity, palpable masses, and even capsular contracture [3]. Implant rupture is classified according to its location relative to the fibrous capsule (intracapsular versus extracapsular) [4], and can also be categorized based on imaging findings, particularly magnetic resonance imaging (MRI) [5]. Among these types, only about 22% represent extracapsular ruptures [4]. Moreover, as demonstrated in several studies [3][6], many ruptures occur silently without apparent clinical symptoms - commonly referred to as silent breast implant ruptures.

Many studies have been conducted and have shown that degradation of the implant membrane is an important factor contributing to the rupture of silicone breast implants. This includes swelling and weakening of the membrane over time, as well as gel bleeding, which

<footnote n="1">¹ ICube, UMR 7357 CNRS, University of Strasbourg, Strasbourg, France</footnote>

<footnote n="2">² UR UM104, Université Montpellier, 34000 Montpellier, France</footnote>

<footnote n="3">³ Service de chirurgie plastique esthétique et reconstructrice, Hautepierre hospital, CHRU Strasbourg, HUS, 67000 Strasbourg, France</footnote>
further compromises membrane integrity [6][7][8]. All factors that undermine membrane durability highlight the critical need for systematic research and evaluation of silicone breast implant components - particularly the membrane - with careful consideration of implant exposure and implantation time. While numerous investigations have addressed breast implant rupture, they vary widely in scope, methodology, and research focus.

MRI is the gold standard for diagnosing implant rupture, with sensitivity and specificity exceeding 90% [9][10]. In efforts to diversify and improve diagnostic accuracy, Kim et al. confirmed that high-resolution ultrasound is a reliable tool for detecting implant rupture [11]. More recently, Ruffenach et al. applied a combined approach of shear wave elastography and Nuclear Magnetic Resonance (NMR) spectroscopy to suggest implant gel stiffness as biomarker of rupture risk [12]. In parallel, some research groups have focused on evaluating membrane quality. For instance, a notable study conducted by Jung et al. examined the aging of non-implanted breast implants by analysing stress parameters derived from tensile strength, elongation at break, and membrane thickness [13]. However, these methods provide limited insight into the chemical composition of implant materials, making it difficult to capture subtle compositional changes of the implants over time. This gap restricts a deeper understanding of rupture mechanisms as well as the identification of early indicators of implant failure.

Raman spectroscopy offers a promising solution to this limitation. Raman spectroscopy is known to be a non-destructive, minimally invasive, inelastic scattering spectroscopy method that provides highly sensitive results [14][15][16][17].

In 2020, Van Haasterecht et al. applied stimulated Raman scattering (SRS) to detect the presence of silicone in capsular tissue and axillary lymph nodes [18]. In cases of capsular contracture associated with implant rupture, de Bakker E et al. further demonstrated, using Raman SRS in 2023, that silicone quantification in Baker grade IV capsules was significantly higher compared with Baker grade I [19]. Two additional studies, conducted by Todorov et al. (2021) and Feng et al. (2023), utilized conventional Raman spectroscopy and reported the presence of silicone in peri-implant tissues and axillary lymph nodes [20][21]. The primary objective of these investigations was to identify spectroscopic markers that indicate the presence of silicone within surrounding tissues - a phenomenon typically occurring only after substantial gel leakage or implant rupture. Meanwhile, Keizers et al. (2015) applied Raman spectroscopy in combination with Infrared (IR) spectroscopy and NMR spectroscopy to elucidate the structure of the membrane and the gel in original implant samples from different manufacturers [22]. In addition to establishing characteristic chemical fingerprints for each type of implant, they also demonstrated that the barrier structure within the membrane helps to prevent gel bleeding. Depending on the manufacturer, the composition of the barrier layer can vary widely (e.g., diphenylsilicone or fluorosilicone). Subsequently, in 2019, Bachour et al. employed Raman spectroscopy in combination with IR and mass spectrometry to investigate PIP breast implants (a brand withdrawn from the market), which were explanted from patients [23]. Based on Raman spectra, this study showed that the main constituent of Poly Implant Prothèse (PIP) implants is dimethylsiloxane and that no barrier layer was present in any of the samples. This absence
was identified as a key factor underlying the gel bleeding and rupture reported in numerous PIP implants worldwide. Together, these studies clarified the structure of the implant shell and revealed the characteristic components of the barrier layer using Raman spectroscopy. However, to the best of our knowledge, no study to date has directly compared the chemical modifications of the two types of implants (un-implanted and explanted).

Raman spectroscopy can deliver comprehensive information on chemical composition changes within the implant, thereby providing a more holistic assessment of implant quality. Importantly, we expect that such compositional alterations may serve as early markers of implant degradation and rupture. In this study, we employed Raman spectroscopy to analyse two types of breast implants: explants retrieved from patients and pre-implants that had never been implanted with implantation times ranging from 7 to 15 years. By examining the acquired Raman spectra, we compared chemical differences across distinct regions and components of the implants. These differences provide insights into the multilayered structure of the implant membrane, which is specifically engineered to prevent gel bleeding and to enhance resistance to external factors. Furthermore, we aimed to identify potential markers of silicone breast implant aging. This was investigated by analysing peak ratios within both membrane and gel components across implants with varying implantation durations. Such markers, once validated with larger Raman spectral datasets, may serve as effective criteria for future modeling efforts.

## 2 | Materials and Methods

### 2.1 | Silicone breast implant samples

A typical breast implant consists of two main components: the membrane and the gel (Figure 1C). Depending on the manufacturer, the membrane may consist of multiple layers to enhance its durability and a layer of diphenylsilicone or fluorosilicone is introduced between the other layers of the silicone shell since 1996 to avoid bleeding [24]. The inner gel is amorphous, contributing to the natural shape of the patient's breast (Figure 1A). Mostly, the inner gel is made up of lightly crosslinked silicone elastomers cured using platinum catalyst and about 80% of high molecular mass polydimethylsiloxane (PDMS), even if molecules of lower molecular mass are also present in the inner gel.

<figure><img src="image_2.png" /><figcaption>**FIGURE 1** | Silicone breast implant samples: (A) Implant positions in the body. (B) Sampling positions. (C) Two basic components of a silicone breast implant: the membrane and the gel.</figcaption></figure>
All of the samples were Allergan Natrelle™ breast implants with BIOCELL™ textured surfaces, representing fifth-generation, anatomically shaped implants containing 295 g of gel [13][25]. The samples were prepared into two main groups: Pre-Implant and Explant. Both pre-implant and explant samples were collected in collaboration with the Department of Plastic, Reconstructive and Aesthetic Surgery at Hautepierre Hospital, part of the Strasbourg University Hospitals (CHRU Strasbourg).

Pre-implant samples were collected as pre-cut membrane fragments for parallel use in another research protocol [13]. In this study, a total of 10 membrane samples were obtained from 10 different pre-implants. For the explant group, the membrane was surgically separated from the gel. From each explant, small membrane fragments were cut from both the anterior and posterior surfaces (Figure 1A,B) for analysis. In total, four explants were examined, and since each explant provided samples from two locations, eight membrane samples were collected for this group.

Regarding the gel, only one representative gel sample was available for the pre-implant group. In contrast, for the explant group, two sampling locations were selected: one from the gel-membrane interface and one from the center of the gel (Figure 1B). To avoid cross-contamination between different sample components, the scalpel was thoroughly cleaned with ethanol, carefully dried, and gloves were changed between each sampling event (for both gel and membrane regions). All collected samples were stored in sealed glass vials and kept at room temperature until Raman analysis was performed.

More information can be found in the supplementary data.

## 2.2 | Raman spectroscopy – Confocal Raman microscope

Raman spectroscopy is an inelastic scattering technique that characterizes individual atoms or molecules through their distinct vibrational modes. For polymers with homogeneous structures, Raman spectroscopy demonstrates great potential owing to the sharpness and high quality of the acquired spectra [26][27].

The Raman spectra used in this study were acquired using a confocal Raman microscope (Newport, Évry, France) equipped with a frequency-doubled Nd:YAG laser ($\lambda$ = 532 nm). The nominal laser power was 50 mW, while the effective power at the sample was approximately 10 mW, corresponding to an estimated intensity of $3\times10^6$ W cm$^{-2}$. Combined with the WITec Alpha 300 R confocal Raman microscope, the system employed a NIKON 20× objective lens (NA = 1.0), a diffraction grating of 600 g/mm, and ten single spectra with an integration time of 10 s each (total fluence $3\times10^8$ J cm$^{-2}$). The recorded spectral range was 0 - 4000 cm$^{-1}$, centered at 2000 cm$^{-1}$.

## 2.3 | Experimental procedures

The study was conducted on two main types of samples: membranes and gels - the basic components of silicone breast implants. Within each component, we examined and compared two types of implants: pre-implant and explant. The study was structured in three parts: (i) investigation of the chemical differences between membranes and gels, (ii) analysis
of membranes, and (iii) analysis of gels to determine factors affecting longevity and the
detection of the presence of extra peaks - the cause of yellowing in the gels (iv).

In the first part, all Raman spectra of membranes and gels from all samples were pooled and their average spectra were compared to determine chemical differences. The detection of these compositional differences also highlighted the complex structure of the membrane and provided factors for assessing its durability. In addition, Raman mapping was performed on the entire cross-section of the membrane to obtain a more comprehensive view of its multilayer structure.

The second part of the study focused on evaluating the I<sub>1003</sub>/I<sub>493</sub> peak ratio. This analysis included ten pre-implant and four explant samples. As described previously, each pre-implant sample was measured as a single unit, whereas each implant sample was divided into two regions (anterior and posterior). All membrane samples were measured on both their inner and outer surfaces, and the I<sub>1003</sub>/I<sub>493</sub> ratio was extracted to assess variability across membranes based on median values.

The third part of the study focused on the gel samples, including one pre-implant gel and four explant gels. The I<sub>1266</sub>/I<sub>493</sub> peak ratio was calculated to evaluate gel quality and its evolution over implantation time. Finally, the relationship between the yellowing appearance of the gels and their Raman spectral characteristics was investigated. This correlation was explored through the combined use of average spectral analysis and multivariate principal component analysis (PCA) to better identify chemical signatures associated with discoloration.

## 2.4 | Data pre-processing and analysis

**Spectral pre-processing:** All spectra are observed and filtered with cosmic rays using the *despike*.WhitakerHayes function available in the RamanSpy library in Python [28]. However, we change the intensity value comparison to median instead of mean to avoid the influence of strong outliers, and also change the kernel size to 2 and the detection threshold to 12. All raw Raman datasets contain both chemical signal and background/fluorescence contributions. We therefore apply a peak-stripping baseline-correction procedure in combination with a Savitzky-Golay (SG) filter to obtain the baseline [29]. After background subtraction, the spectra are trimmed to the region of interest (ROI) to remove extraneous information. The ROI spectra are then smoothed once more with an SG filter before the final normalization step. L2-vector normalization is subsequently applied, because it is widely adopted in Raman studies [30][31].

**Spectral analysis:** The averaged spectra were used to detect differences in spectral shape and peak position. The spectral regions showing notable differences were extracted for multivariate principal component analysis (PCA), which identifies the specific wavenumbers contributing to these variations. In addition, peak intensity ratio analysis was performed to compare characteristic positions between the membrane and gel structures. The use of intensity ratios instead of absolute intensities minimizes the influence of noise and measurement fluctuations.
The trends observed from PCA loadings or from the boxplot representation of intensity ratios between groups were statistically tested to rule out random variations. Two types of nonparametric tests were performed depending on the data structure. For paired comparisons within the same sample group, the Wilcoxon signed-rank test was applied, and its results were evaluated through p-values, effect sizes ($r_{fb}$), and confidence intervals (CI) [32]. For comparisons between two independent groups, the Mann-Whitney U test was performed and assessed using p-values and Cliff's delta [33,34]. Furthermore, for data involving temporal variation (implantation time), the linear regression (linear fit) and Spearman rank correlation tests were used to evaluate the direction and strength of monotonic trends [35]. The linear regression provided the slope and $R^2$ value, indicating the rate of change per month, whereas the Spearman correlation coefficient ($\rho$) assessed the nonparametric trend consistency across samples.

All statistical analyses were performed in MATLAB R2025b (MathWorks, Natick, MA, USA). The built-in signrank function was used for Wilcoxon signed-rank tests, the ranksum function for Mann-Whitney U tests, and fitlm and corr functions for linear regression and Spearman correlation analyses, respectively.

# 3 | Results

## 3.1 | Chemical composition difference of membrane and gel

<figure><img src="image_3.png" /><figcaption>**FIGURE 2** | Comparison of average spectra between membrane and gel, showing distinct (dashed rectangles) and shared (colored, numbered 1–8) spectral regions.</figcaption></figure>

The chemical composition distinction between membrane and gel was made based on the average spectra (with *standard deviation* (SD)) of both groups. The Raman spectrum of the gel (blue - Figure 2) coincides with the spectrum of pure PDMS reported by Vesna et al. [36] and Bae et al. [37], indicating that the gel was formed from pure PDMS.

In the PDMS molecule, there are three main types of bonds: Si–O, Si–C (or Si–CH₃), and C–H₃. The Si–O–Si bond forms the backbone of the molecule, while the methyl (CH₃) groups act as a protective shell against external influences. The linkage between this methyl
shell and the siloxane backbone is provided by the Si–C bond. According to the Raman spectral analysis reported by Bae et al. (2005) [37], PDMS exhibits a total of eight fundamental Raman peaks (Figure 2), which can be classified into three main regions (red, green, and blue), corresponding to the three principal bond groups described above.

<table><caption>TABLE 1 | Raman spectrum peak composition of PMDS [37].</caption><thead><tr><td>Peak</td><td>Theoretical Raman shift (cm<sup>-1</sup>)</td><td>Measured Raman shift (cm<sup>-1</sup>)</td><td>Vibration modes</td></tr></thead><tbody><tr><td>1</td><td>488</td><td>493</td><td>v<sub>s</sub>(Si-O-Si)</td></tr><tr><td>2</td><td>708</td><td>713</td><td>v<sub>s</sub>(Si-C)</td></tr><tr><td>3</td><td>787</td><td>790</td><td>v<sub>as</sub>(Si-C) / ρ<sub>as</sub>(CH<sub>3</sub>)</td></tr><tr><td>4</td><td>862</td><td>864</td><td>ρ<sub>s</sub>(CH<sub>3</sub>)</td></tr><tr><td>5</td><td>1262</td><td>1265</td><td>δ<sub>s</sub>(CH<sub>3</sub>)</td></tr><tr><td>6</td><td>1412</td><td>1416</td><td>δ<sub>as</sub>(CH<sub>3</sub>)</td></tr><tr><td>7</td><td>2907</td><td>2908</td><td>v<sub>s</sub>(CH<sub>3</sub>)</td></tr><tr><td>8</td><td>2965</td><td>2968</td><td>v<sub>as</sub>(CH<sub>3</sub>)</td></tr></tbody></table>

There are three main types of vibrational modes in the Raman spectrum of PDMS: stretching (ν), bending (δ), and rocking (ρ). Among these, the Raman signal intensity of stretching modes is higher than that of bending and rocking modes [39]. Within each type of vibration, two forms are typically observed: symmetric and asymmetric. Raman signals from symmetric vibrations are always stronger than those from asymmetric vibrations because the synchronous motion of atoms in symmetric systems results in higher polarizability. However, the actual intensity also depends on molecular orientation and measurement configuration. This explains why, in Figure 2, peaks 1, 2, 7, and 8 display stronger signals.

Studies by Mark et al. [40][41] have elucidated the critical role of the siloxane backbone, particularly the Si–O–Si linkage. Owing to its long bond length, wide bond angle, and low torsional potential, Si–O–Si contributes to the high flexibility of PDMS chains. Furthermore, the Si–O bond is responsible for the remarkable thermal stability of PDMS, due to its high bond dissociation energy (Si–O: 498 kJ/mol, Si–C: 435 kJ/mol, C–H: 337.2 kJ/mol, C–C: 368 kJ/mol [42]) and its very low glass transition temperature (Tg) [41]. Consequently, breaking the siloxane backbone in PDMS is significantly more difficult than cleaving other chemical bonds. In the Raman spectrum, the Si–O–Si bond is clearly represented by the peak at 488 cm⁻¹, corresponding to the symmetric stretching vibration v□(Si–O–Si).

The methyl (CH₃) groups possess a crucial protective function against environmental stresses, particularly through their hydrophobic nature. As previously discussed, the flexible siloxane backbone allows for a high spatial density of CH₃ groups, thereby enhancing protection against radiation and chemical agents. Moreover, the low polarizability of CH₃ plays a key role in the hydrophobicity of PDMS [43], effectively repelling polar solvents (such as water, ethanol, and methanol) that might otherwise attack the siloxane backbone via hydroxyl (-OH) groups [44]. Due to this dense, low-polarity methyl shielding, PDMS exhibits strong chemical inertness against such agents. In the Raman spectrum, the C–H bonds of CH₃ generate multiple characteristic peaks corresponding to different vibrational
modes (Figure 2). Notably, the symmetric stretching v□(CH₃) at 2907 cm⁻¹ and the asymmetric stretching vₐ□(CH₃) at 2965 cm⁻¹ exhibit the highest intensities.

To preserve the protective function of the CH₃ shell around the siloxane backbone, the Si–C bond plays a pivotal role. Its relatively high bond energy (greater than that of C–C) enables Si–C to resist common environmental stressors, thereby maintaining the structural integrity of PDMS. However, under extreme conditions such as high temperature, plasma exposure, or ultraviolet (UV) irradiation [45][46][47], the Si–C bond may break. Once cleaved, the CH₃ groups lose their anchoring to the Si–O–Si core, leaving the siloxane backbone more vulnerable to external attack. The Raman spectral features of the Si–C bond include two vibrational modes: the symmetric stretching v□(Si–C) at 708 cm⁻¹ and the asymmetric stretching vₐ□(Si–C) at 787 cm⁻¹. Changes in the shape or intensity of these peaks reveal modifications in the bonding between the CH₃ shell and the siloxane core.

When the PDMS molecule is subjected to environmental stress, its characteristic Raman peaks are simultaneously affected. Initially, external factors target the CH₃ shell, detaching methyl groups from Si–C bonds and forming new chemical linkages [48]. Under harsher conditions (elevated temperatures, prolonged ultraviolet (UV) exposure, plasma treatment), condensation of Si–OH groups leads to structural rearrangements in the PDMS network, rendering it more brittle [49]. This degradation process aligns with the hierarchical bond dissociation energies [50]. Accordingly, the extent of peak shape alterations and intensity variations in the Raman spectra of PDMS reflects the progressive damage following the sequential bond-breaking mechanism described above.

In contrast, the membrane spectrum (red) also contains the characteristic peaks of pure PDMS but shows five additional peaks that are absent from the gel: 625, 1003-1035, 1128-1196, 1575-1599, 3056 cm⁻¹.

<figure><img src="image_4.png" /></figure>
**FIGURE 3** | (A) Three-layer structural model of the membrane. (B) Optical microscopy image (10×) of the membrane. (C-D-E) Raman mapping at the characteristic peaks of the membrane in the inner, middle, and outer layers.

From the differences in those five peak regions, we performed Raman scanning along the membrane thickness to explore the structural details instead of scanning on the membrane surface. Comparing the structural model (Figure 3A) with the microscopic image (Figure 3B), the membrane structure is clearly shown through three layers. The outermost layer has a rough surface because it is in contact with the breast tissue environment, the middle barrier layer and the inner layer are in contact with the gel part. Figures 3C-E present Raman mappings at seven characteristic bands (625, 714, 1003, 1035, 1128–1196, 1575–1599, and 3056 cm⁻¹). The inner and outer layers (Figures 3C and 3E) exhibit highly similar and uniform Raman intensities across all bands, indicating a consistent chemical composition throughout these regions. In contrast, the middle layer (Figure 3D) shows significantly stronger signals at five additional bands, suggesting localized enrichment or distinct characteristics within this layer. Meanwhile, the 714 cm⁻¹ band remains uniform in intensity across all three layers, reflecting its consistent presence throughout the membrane.

## 3.2 | Distribution of diphenylsiloxane in the inner and outer layers of the membrane

The characteristic difference for the membrane is the diphenylsiloxane component. In its Raman spectrum, the peak 1003 cm⁻¹ is the most stable and has the best signal (Figure 3A). Additionally, the 493 cm⁻¹ peak is commonly selected as the reference peak since it corresponds to the PDMS backbone and is stable [38]. Therefore, investigating the ratio I₁₀₀₃/I₄₉₃ can provide information about the diphenylsiloxane and eliminate errors in the measurement.

<figure><img src="image_5.png" /></figure>
**FIGURE 4** | Comparison of I<sub>1003</sub>/I<sub>493</sub> ratio between inside (purple) and outside (yellow) layer on membrane samples.

In Figure 4, there are two main groups: pre-implant (Pre) and explant (Ex). In the pre-
implant groups (red area), the I<sub>1003</sub>/I<sub>493</sub> ratio value of the outer layer is larger than that of the
inner layer, showing a similar trend between samples (median comparison). In contrast, the
explant group shows a more complex variation. For explant 1 with a shorter implantation
time (85 months), the trend of the I<sub>1003</sub>/I<sub>493</sub> ratio of the outer layer being larger than that of
the inner layer is still maintained. However, in the long-term implanted samples (Ex3, Ex4),
this trend is not observed and even shows an opposite tendency compared to the initial
condition. Explant 2 is considered an intermediate point between the two trends when the
anterior part still retains the trend of the I<sub>1003</sub>/I<sub>493</sub> ratio of the outside being higher than that
of the inside, while the posterior part has shown the opposite sign.

To further clarify the trend in the pre-transplant group (Pre), a Wilcoxon signed-rank test was conducted on group Pre (n = 10) to compare paired median values outside and inside, with the expectation that the outside median would be greater than the inside median. The analysis yielded a significant result (p = 0.02 < 0.05) with a strong effect (rank-biserial correlation, r<sub>rb</sub> = 0.946 (95% CI [0.78 1]). In addition, groups Pre and Ex were considered independent; therefore, a Mann-Whitney U test was performed to assess differences between group Pre (n = 10) and group Ex (consisting of Ex3 and Ex4 only, n = 4). The Mann-Whitney U test also indicated a significant difference (p = 0.04 < 0.05), with Cliff's delta = 0.95, reflecting a strong and even opposite discrimination between groups Pre and Ex.

**3.2** | Investigation of the bending vibration - δ<sub>s</sub>(CH<sub>3</sub>) of the gel sample

The gel is an internal component surrounded by a membrane. Therefore, changes in the gel
over time may primarily involve the peripheral Si–CH₃ bonds rather than the Si–O–Si
backbone. During spectral analysis and ratio evaluation, the stretching and rocking modes
exhibited complex and less reproducible variations across replicates, whereas the bending
mode showed a clearer and more consistent trend in both intensity and peak position.
Accordingly, the I₁₂₆₆/I₄₉₃ peak ratio—both corresponding to CH₃-related vibrations—was
selected to better capture the chemical evolution of the gel.
<figure><img src="image_6.png" /><figcaption>FIGURE 5 | $I_{1266}/I_{493}$ ratio survey results.</figcaption></figure>

Figure 5 clearly illustrates the distinction in the $I_{500}/I_{250}$ ratio between the Pre Gel and Ex Gel groups (Ex1, Ex2, Ex3, Ex4), particularly in terms of the median values (Pre Gel > 0.095, whereas all Ex Gel samples < 0.095). Furthermore, to evaluate the temporal evolution of the $I_{1266}/I_{493}$ ratio, both a linear regression and a Spearman correlation test were performed. The linear regression revealed that the ratio decreased by approximately $7.34 \times 10^{-5}$ per month of implantation, with a highly significant p-value of $1.01 \times 10^{-15}$. Similarly, the Spearman test showed a negative correlation ($\rho < 0$) with a low p-value ($1.06 \times 10^{-6}$), confirming a consistent downward trend over time. However, the $R^2 = 0.19$ indicates that time alone accounts for only a small portion of the observed variation. Other factors — such as sample preservation conditions, retrieval technique, and patient-specific physiological conditions — are also likely to contribute to these changes.

### 3.3 | Appearance of additional peaks in the gel sample (explant)

Figure 6A presents the four gel samples included in this study. They can be categorized into two groups: yellowing gels (explant 1 and explant 4) and normal gels (explant 2 and explant 3). Because of the similarity in color, we grouped the spectra of Ex1 and Ex4 gels into the same yellow gel group while the normal gel group will contain the spectra of Ex2 and Ex3. When comparing the mean spectra of the two groups, there are two positions $1159 \text{ cm}^{-1}$ and $1524 \text{ cm}^{-1}$ that show the appearance of peaks in the yellow gel group but not in the normal gel group. The score plot and loadings of PCA on the two spectral regions $1100-1200 \text{ cm}^{-1}$ (Figure 6 C-D) and $1500-1600 \text{ cm}^{-1}$ (Figure 6 E-F) also give similar results for the mean spectra.
<figure><img src="image_7.png" /><figcaption>**FIGURE 6** | (A) Gel samples. (B) Mean spectra. (C-D) Score plot and loadings in 1100-1200 cm⁻¹. (E-F) Score plot and loadings in 1500-1600 cm⁻¹.</figcaption></figure>

# 4 | Discussions

## 4.1 | Investigate the composition and fine structural features of the membrane

Among the five peaks appearing in the membrane, three peaks with high intensity are dominant: 1003–1035cm⁻¹, 1575–1599 cm⁻¹ and 3056 cm⁻¹ (Figure 2A). All three peak regions indicate the presence of the phenyl group: peak 1003 corresponds to ring breathing [51][52] and peak 1035 also appears in the benzene compound [53]; peaks 1575 and 1596 cm⁻¹ represent asymmetric and symmetric stretching C=C vibrations in the phenol group (ν(C=C) / phenolic) [54][55] and 3056 cm⁻¹ is assigned to the ν(CH) stretching of the benzene ring [56]. In addition, the peak region 1125-1196 is assigned to the Si-O-Ar stretching vibration, which here is specifically the phenyl group attached to the siloxane chain [57].

The high similarity when comparing the new peaks appearing only on the membrane spectrum with the reference spectrum of diphenyl siloxane [22] shows that diphenylsiloxane has been added to the PDMS of the membrane. The incorporation of phenyl groups into PDMS enhances the structural stability by increasing the glass transition temperature (Tg) [43] [45]. In addition, the phenyl group (diphenylsiloxane) is also larger than the methyl group (dimethylsiloxane – PDMS) which also prevents the diffusion of gel ologimers into the environment. The evidence is clearly shown through the patent of Allergan Inc. The company has affirmed that by mixing diphenyl into siloxane, it has reduced 40% of gel bleeding for breast implants [58].

Furthermore, Keizers et al. [22] described that in the membrane structure there exists a barrier layer between the shell layers, which is responsible for preventing the silicone gel
from diffusing out from inside the bag. This barrier structure has more recently been clearly
observed in the study conducted by Brown et al. (2024) [59]. Microscopic observation
(Figure 3A, B) on the membrane sample shows a clear three-layer structure, thereby
reinforcing the correctness of the above structural model. Moreover, Raman mapping at the
five characteristic bands (detected only in the membrane) (Figure 3D) clearly shows that the
barrier layer contains a higher diphenylsiloxane concentration, particularly at bands 1003,
1599, and 3056 cm⁻¹. In contrast, band 714 cm⁻¹ exhibits similar intensities across the
layers, confirming that the barrier layer is more enriched in ammonia than both the inner and
outer layers.

From the above analysis, the chemical composition and fine structure of the membrane have
been comprehensively described. The membrane of silicone breast implant is made of
PDMS combined with diphenylsiloxane. Mostly, diphenyl siloxane is highly concentrated in
the middle barrier layer to prevent gel bleeding.

## 4.2 | Diphenylsiloxane – a marker for monitoring membrane quality

The differences in the two sides (outer and inner) that occurred in the pre-implant and
explant groups showed the possibility of monitoring the membrane condition through the
I<sub>1003</sub>/I<sub>493</sub> standard marker. For the original membrane structure with three layers (inner,
barrier, and outer), the highest diphenylsiloxane concentration was in the barrier layer
(Figure 3A, B). However, in reality, the inner layer was formed first, so the cross-linking
process occurred earlier than the barrier and outer layers [60]. Furthermore, the final curing
of the three layers from the outside made the outer layer hotter than the other layers. Due to
the higher temperature and lower cross-linking density, the diphenylsiloxane in the barrier
layer diffused to the outer layer more easily than the inner layer. This result was confirmed
by the U.S. Food and Drug Administration (FDA) when comparing the composition of the
inner and outer layers, showing that only 32-620 ppm of phenyl siloxane oligomer was
measured in the outer layer without mentioning the inner layer [61].

The above explanations demonstrate that the membrane will initially have a high I₁₀₀₃/I₄₉₃
ratio in the outer layer. This is clearly shown by the results in Figure 4 where all 10 pre-
implant samples have a higher median value of the I₁₀₀₃/I₄₉₃ ratio on the outside than on the
inside. The results from the Wilcoxon test are consistent in that trend with a very low p-
value =0.002 and a strong effect of 0.964.

However, when implanted in the body, under the influence of external factors and the inner
gel, the distribution of diphenylsiloxane changed and tended to concentrate in the inner
layer. This was observed in the explant samples (Ex3 and Ex4), which represent long-term
implantation. The Mann-Whitney U test, with a very high Cliff's delta (0.95), clearly
confirmed the strong contrast in the trends between the Pre and Ex groups. In other words,
the reversal of the diphenylsiloxane gradient indicates that the barrier layer has been affected
by external forces and has undergone structural changes. This, in turn, impacts the gel
permeability performance of the barrier layer — a key functional property of this layer.
Notably, within the explant group, a transitional stage was also observed. In the short-term implanted sample (Ex1, 85 months), the trend of the outer side having a higher I₁₀₀₃/I₄₉₃ ratio than the inner side was still present. However, in the longer-term sample (Ex2, 110 months), a clear reversal occurred, particularly on the posterior side that contacts the chest wall.

These results highlight that the I₁₀₀₃/I₄₉₃ ratio can serve as an indicator for identifying the onset of membrane degradation. Furthermore, performing spectral scans on both sides of the barrier layer in samples with different implantation histories would provide a more comprehensive understanding of how the diphenylsiloxane distribution changes under various in-vivo conditions — without implying a simple time-dependent relationship.

## 4.3 | The bending vibration - δ<sub>s</sub>(CH<sub>3</sub>) reflects the gel stiffness over implantation time

In the Raman spectrum of PDMS, the peak at 1266 cm⁻¹ is assigned to the bending vibration of the CH₃ group (δ<sub>s</sub>(CH₃)). According to the results in Figure 5, after implantation—particularly as implantation time increases—the I<sub>1266</sub>/I<sub>493</sub> ratio gradually decreases. The linear fit analysis showed a slope of -7.34 × 10<sup>-5</sup> per month with a p-value of 1.01 × 10<sup>-15</sup>, indicating a statistically significant decreasing trend. In addition, the Spearman correlation analysis yielded ρ = -0.272 with p = 1.06 × 10<sup>-6</sup>, further supporting a negative relationship between the I<sub>1266</sub>/I<sub>493</sub> ratio and implantation time. Both analyses consistently demonstrate that this ratio decreases over time, although the rate of change is relatively small.

Furthermore, when examining the stiffness of the explant gel samples, Ruffenach et al. observed that the stiffness of the gel increased proportionally with implantation time [12]. Taken together, the gradual decrease in the I<sub>1266</sub>/I<sub>493</sub> ratio and the increase in gel stiffness during implantation may be interrelated. However, the in vivo gel stiffening process is highly complex, as it is influenced not only by oxidative agents but also by the infiltration and interaction of various other substances. Moreover, the linear regression analysis (R² = 19%) indicates that implantation time is only one of several factors contributing to the decrease in the I<sub>1266</sub>/I<sub>493</sub> ratio.

Therefore, given the potential of the I<sub>2 5 0</sub>/I<sub>1 2 5</sub> ratio demonstrated in this study, direct measurements could be established to investigate the relationship between the δ<sub>s</sub>(CH₃) vibration and gel stiffness over time.

## 4.4 | Presence of carotenoids in the yellowing gel

There are many studies that have hypothesized the yellowing of silicone breast implant gel. The yellowing of the gel may come from the povidone-iodine permeation during the pocket washing process during surgery [62]. Besides, Beretta et al. (2013) and Ramião et al. (2019) performed chemical analysis on PIP and showed that the gel significantly absorbed cholesterol from breast tissue leading to yellowing [63][64]. Recently, using mass spectrometry results, Ruffenach et al. showed the presence of 7-ketocholesterol - a cholesterol metabolite in the gel of explants. In addition, some studies also mentioned the oxidation process that occurs with silicone in the body [65][66].
In this study, the appearance of two peaks 1159 and 1524 cm⁻¹ in the Raman spectrum of Ex1 Gel and Ex4 Gel suggests the presence of carotenoids - a coloring agent present in the body especially in breast adipose tissue [67]. A close correspondence was observed between the Raman spectrum of carotenoids obtained in this study and that reported by Hiroto Horiue et al. [68], especially in the two prominent peaks located at 1154 and 1510 cm⁻¹. During the sample measurement, measuring a small sample extracted from the gel may reduce the concentration of substances in the gel, making it difficult to detect foreign substances. However, the appearance of two peaks 1159 and 1524 cm⁻¹ also brings a potential for the absorption of carotenoids from breast tissue by silicone breast implants through the membrane. Monitoring this process may reveal structural degradation of both the membrane and the gel upon implantation.

## 5 | Conclusion

This study used Raman spectroscopy to elucidate the composition and fine-structure features of the membrane, especially in the barrier region containing high concentrations of diphenyl siloxane. A deeper understanding of the membrane led to the identification of the I290/I412 marker ratio, which enables qualitative monitoring of diphenylsiloxane distribution across the inner and outer layers under pre-implant and post-implant conditions. It may be an indicator of membrane structural degradation through the change in the distribution gradient of diphenyl siloxane. In addition, the I₁₂₆₆/I₄₉₃ ratio in the gel was consistent with previous findings of gel stiffness over time, highlighting the clear advantage of using Raman spectroscopy. In the future, Raman imaging may provide more comprehensive insights through the markers identified from this study. This opens up the prospect of developing deep learning models to find the degradation threshold of silicone breast implants.

## Acknowledgments

This work is financed by the Interdisciplinary Thematic Institute HealthTech, as part of the ITI 2021-2028 program of the University of Strasbourg, CNRS and Inserm, supported by IdEx Unistra (ANR-10-IDEX-0002) and SFRI (STRAT'US project, ANR-20-SFRI-0012) within the framework of France 2030.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

## Code Availability

The MATLAB code used for the analysis in this study is available from the corresponding author upon reasonable request, or can be accessed via GitHub at the repository provided. (Raman spectroscopy analysis).

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