Use of High-resolution Ultrasound in Characterizing a Breast Implant and Detecting a Rupture of the Device Before Reoperation in Women Receiving Augmentation Mammaplasty

Nam, Sang Eun; Bang, Bum Sik; Lee, Eun Kyoung; Sung, Jaekyung; Song, Keun Yeong; Yoo, Young Bum; Park, Dong Wook; Kim, Jae Hong

doi:10.1097/prs.0000000000010201

Cited by 5 publications

(4 citation statements)

References 20 publications

(31 reference statements)

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“…An annual breast implant examination is recommended for patients to prevent the exacerbation of silicone migration to regional lymph nodes or adjacent tissue, which could prompt non-radical silicone removal and unnecessary lymph node biopsies. While it has been reported that patients with current extracapsular ruptures may commonly present with symptoms [21], our study found that approximately 90% of patients with snowstorm signs in ultrasonography, with or without silicone invasion to adjacent tissue or lymph nodes, were asymptomatic. This suggests that extracapsular ruptures may be overlooked, underscoring the importance of regular follow-up for early diagnosis.…”

Section: Discussioncontrasting

confidence: 72%

“…Several studies have compared the diagnostic accuracy of mammography, ultrasound, and MRI in detecting implant ruptures [13][14][15][16][17]. Recently, high-resolution ultrasonography (HRUS) has emerged as a valuable tool for diagnosing implant-related complications, including ruptures, and has demonstrated efficacy in identifying device types and manufacturers [9,[18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

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Exploration of Point-of-Care Ultrasonography for Silicone Breast Implant Rupture Detection and Classification

Kim,

Song

et al. 2024

Medicina

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Background and Objectives: The surge in breast-related surgeries in Korea underscores the critical need for an accurate early diagnosis of silicone breast implant-related issues. Complications such as BIA-ALCL and BIA-SCC add complexity to breast health concerns, necessitating vigilant monitoring. Despite advancements, discrepancies persist between ultrasonographic and pathologic classifications of silicone implant ruptures, highlighting a need for enhanced diagnostic tools. This study explores the reliability of ultrasonography in diagnosing silicone breast implant ruptures and determining the extent of silicone migration, specifically with a focus on guiding potential capsulectomy based on pathology. Materials and Methods: A comprehensive review of medical records encompassing 5557 breast implants across 2790 patients who underwent ultrasound-assisted examinations was conducted. Among the screened implants, 8.9% (249 cases) were diagnosed with silicone breast implant rupture through ultrasonography. Subsequently, 89 women underwent revisional surgery, involving capsulectomy. The pathological analysis of 111 periprosthetic capsules from these cases aimed to assess the extent of silicone migration, and the findings were juxtaposed with the existing ultrasonographic rupture classification. Results: The diagnostic agreement between preoperative sonography and postoperative findings reached 100% for silicone breast implant ruptures. All eighty prosthetic capsules exhibiting a snowstorm sign in ultrasonography demonstrated silicone migration to capsules upon pathologic findings. Conclusions: High-resolution ultrasonography emerged as a valuable and reliable imaging modality for diagnosing silicone breast implant ruptures, with a notable ability to ascertain the extent of free silicone migration to capsules. This diagnostic precision is pivotal in informing decisions about potential capsulectomy during revisional surgery. The study advocates for an update to the current binary ultrasonographic classification, suggesting a more nuanced categorization into three types (subcapsular, intracapsular, and extracapsular) based on pathology.

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Section: Discussioncontrasting

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Exploration of Point-of-Care Ultrasonography for Silicone Breast Implant Rupture Detection and Classification

Kim,

Song

et al. 2024

Medicina

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“…Mammograms and MRI, which are used to monitor breast implant-related complications, cannot identify the implant shell surface topography. Only ultrasonography can identify the inserted implant shell surface topography [13,14].…”

Section: Introductionmentioning

confidence: 99%

Developing a deep learning model to predict the breast implant texture types with ultrasonography image: feasibility study

Kim,

Jeong,

et al. 2024

Preprint

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Introduction Breast implants, including textured variants, have been widely used in aesthetic and reconstructive mammoplasty. However, the textured type, which is one of the shell types of breast implants, has been identified as a possible carcinogenic factor for lymphoma, specifically breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). Identifying the texture type of the implant is critical to the diagnosis of BIA-ALCL. However, distinguishing the shell type can be difficult due to human memory or loss of medical history. An alternative approach is to use ultrasonography, but this method also has limitations in quantitative assessment. Objective The objective of this study is to determine the feasibility of using a deep learning model to classify the textured shell type of breast implants and make robust predictions from ultrasonography images from heterogeneous sources. Methods A total of 19,502 breast implant images were retrospectively collected from heterogeneous sources, including images from both Canon (D1) and GE (D2), images of ruptured implants (D3), and images without implants (D4), as well as publicly available images (D5). The Canon (D1) images were trained using Resnet-50. The performance of the model on D1 was evaluated using stratified 5-fold cross-validation. Additionally, external validation was conducted using D2 and D5. The AUROC and PRAUC were calculated based on the contribution of the pixels with Grad-CAM. To identify the significant pixels for classification, we masked the pixels that contributed less than 10%, up to a maximum of 100%. To assess model robustness to uncertainty, Shannon entropy was calculated for four image groups: Canon (D1), GE (D2), ruptured implant (D3), and without implants (D5). Results The deep learning model achieved an average AUROC of 0.98 and a PRAUC of 0.88 in the Canon dataset (D1). For images captured with GE (D2), the model achieved an AUROC of 0.985 and a PRAUC of 0.748. Additionally, the model predicted an AUROC of 0.909 and a PRAUC of 0.958 for a dataset available online. For quantitative validation, this model maintained PRAUC up to 90% masking of less contributing pixels, and the remnant pixels located in breast shell layers. Furthermore, the prediction uncertainty increased in the following order: Canon (D1), GE (D2), ruptured implant (D3), no implant (D5) (0.066; 0072; 0.371; 0.777, respectively). Conclusion We have demonstrated the feasibility of using deep learning to predict the shell types of breast implants. With this approach, the textured shell types of breast implants can be quantified, supporting the first step in the diagnosis of BIA-ALCL.

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“…Its 3-year safety has been recently assessed using high-resolution ultrasound (HRUS) [ 24 ]. Indeed, the importance of the use of HRUS in assessing the safety of SGBIs has been well documented in the literature [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 51 , 52 ]. Along the continuum of these previous studies, we have efficiently used three-dimensional (3-D) simulation technology and HRUS to maximize both the aesthetic outcomes and safety of the Motiva Ergonomix TM Round SilkSurface.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Imaging Modalities Combined with a Silicone Gel-Filled Breast Implant in Korean Women

Hong

Kang

Hwang

et al. 2023

Gels

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With the occurrence of breast implant crises in Korea, it has become increasingly important to detect complications earlier in patients receiving a device. We have therefore combined imaging modalities with an implant-based augmentation mammaplasty. In this study, we assessed the short-term treatment outcomes and safety of the Motiva Ergonomix™ RoundSilkSurface (Establishment Labs Holdings Inc., Alajuela, Costa Rica) in Korean women. A total of 87 women (n = 87) were included in the current study. We compared preoperative anthropometric measurements between the right side and the left side of the breast. Moreover, we also compared the thickness of the skin, subcutaneous tissue and the pectoralis major measured on a breast ultrasound preoperatively and 3 months postoperatively. Furthermore, we analyzed the incidences of postoperative complications and the cumulative complication-free survival. Preoperatively, there was a significant difference in the distance from the nipple to the midline between the left and right side of the breast (p = 0.000). Both sides of the breast showed significant differences in the thickness of the pectoralis major preoperatively and 3 months postoperatively (p = 0.000). A total of 11 cases (12.6%) of postoperative complications occurred; these included five cases (5.7%) of early seroma, two cases (2.3%) of infection, two cases (2.3%) of rippling, one case (1.1%) of hematoma and one case (1.1%) of capsular contracture. Time-to-events were estimated at 386.68 ± 27.79 days (95% CI 334.11–439.27). Here, we describe our experience with imaging modalities in combination with the Motiva ErgonomixTM Round SilkSurface in Korean women.

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Use of High-resolution Ultrasound in Characterizing a Breast Implant and Detecting a Rupture of the Device Before Reoperation in Women Receiving Augmentation Mammaplasty

Cited by 5 publications

References 20 publications

Exploration of Point-of-Care Ultrasonography for Silicone Breast Implant Rupture Detection and Classification

Exploration of Point-of-Care Ultrasonography for Silicone Breast Implant Rupture Detection and Classification

Developing a deep learning model to predict the breast implant texture types with ultrasonography image: feasibility study

Feasibility of Imaging Modalities Combined with a Silicone Gel-Filled Breast Implant in Korean Women

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