3D simulation in primary breast augmentation: a real-world study of patient-reported outcomes in early independent practice

Introduction

Background

In breast surgery, and breast augmentation in particular, implant selection remains a crucial determinant of postoperative satisfaction, as the leading cause of revision procedures is a mismatch between the patient’s expectations and the actual postoperative outcome. This mismatch is partly related to the inherent limitations of traditional preoperative planning and counseling methods. Conventional tools such as bra sizers, external implant trials and reference photographs from previous cases often fail to provide accurate or individualized predictions (1). These approaches are largely subjective, highly dependent on patient imagination, and insufficiently account for individual anatomical variables and implant-tissue interactions. As a result, they offer limited accuracy in predicting patient-specific outcomes and may contribute to unrealistic expectations.

Rationale and knowledge gap

The technique of three-dimensional (3D) simulations is already widely used in disciplines like radiology, vascular surgery and orthopedic surgery for decades (2-4). However, its introduction in the modern-day practice of a plastic surgeon and the application in aesthetic breast surgery can be considered as a concept of recent years. Epstein et al. described the application of three-dimensional imaging in preoperative breast augmentation. Using a multi-camera stereoscopic system, a 220° 3D model of the torso is generated, allowing interactive simulation of augmentation or mastopexy (5). Gladilin et al. used 3D optical body scans and computational modelling of soft tissue mechanics which generates photo-realistic simulations of postoperative breast appearance for different surgical scenarios (6). 3D imaging has attracted considerable interest in recent years and offers a promising alternative to conventional techniques, yet it is not without shortcomings and pitfalls that must be carefully considered. Donfrancesco et al. reported high patient engagement and perceived accuracy of 3D simulations, yet noted that simulated images appeared “better” than actual postoperative results in 28.6% of cases, raising concerns regarding expectation management and potential medicolegal implications (7). Moreover, dissatisfaction with implant size persisted in approximately 19% of patients, a rate comparable to traditional sizing techniques, suggesting that 3D simulation does not fully eliminate postoperative reinterpretation of outcomes (8,9). These findings underscore that 3D simulation enhances counseling but remains an adjunct rather than a predictive substitute for clinical judgment.

Objective

Our manuscript examines the role of 3D simulation in breast augmentation, outlining both its benefits for patients and surgeons, and the limitations that may affect its adoption. We highlight several key considerations intended to give plastic surgeons a deeper understanding of this valuable technology. In addition, we present a retrospective analysis of the first 126 breast augmentations performed by a plastic surgeon using a 3D imaging system, offering several important findings. This article aims to serve as a practical guide for surgeons seeking to integrate 3D simulation into their workflow—as well as for those skeptical of its clinical relevance—by demonstrating its contribution to more accurate surgical planning and improved patient satisfaction. We present this article in accordance with the STROBE reporting checklist (available at https://abs.amegroups.com/article/view/10.21037/abs-2025-1-60/rc).

Methods

Study design and participants

The first 126 breast augmentations performed by a single plastic surgeon (M.G.), who had completed residency training and obtained board certification in plastic surgery in 2021, were retrospectively analyzed. The surgical interventions took place between December 2022 and January 2025 and were conducted in Breast Academy, Pacific Private Hospital, Gold Coast, Australia, and in AZORG, Aalst, Belgium. Prior to the study period, the surgeon (M.G.) had not independently performed breast augmentation procedures outside of supervised training during residency. All consecutive patients were included in this study, without postoperative exclusion. Patient selection was performed as part of routine clinical practice rather than through a predefined study-specific screening protocol. Some patients were referred through an external agency, where initial preselection (e.g., obesity or untreated medical conditions) had already taken place. Therefore, complete data on the total number of patients screened or excluded prior to surgical consultation were not available. Patients with unstable psychological conditions were assessed during consultation, and three patients were preoperatively excluded on this basis (Figure 1). Smoking cessation was routinely advised prior to surgery; however, no objective verification (e.g., cotinine testing) was performed. Male patients were referred to transgender specialists.

Figure 1 Flowchart illustrating the patient selection process. Patients were included consecutively from routine clinical practice. Some patients underwent external preselection prior to consultation. Three patients were excluded due to psychological instability. All operated patients completed follow-up and were included in the final analysis.

Preoperative planning

VECTRA 3D Imaging (Canfield Scientific, Parsippany, NJ, USA) was used during the preoperative planning for all patients. Standard preoperative measurements [width and height of the breast footprint, distance between sternal notch and inframammary fold (IMF) level, distance between sternal notch and nipple level, distance between nipple and IMF under stretch, distance between IMF level and umbilicus, distance between projected nipple height and IMF level] and standardized photographs were taken.

Surgical technique

All breast augmentations were performed under general anesthesia, applying sharp cautery dissection. All procedures were performed through an inframammary incision, with pocket creation in the subfascial or dual plane. Round or anatomical silicone cohesive gel implants were used. Round implants were smooth, nanotextured or microtextured. The used implant brands were Mentor [Johnson & Johnson (J&J) MedTech, CA, USA) and Motiva (Establishment Labs Holdings Inc., Costa Rica]. All surgical procedures were independently performed by the same surgeon (M.G.), thereby eliminating inter-surgeon variability.

Postoperative follow-up and patient-reported outcome measures (PROMs)

Follow-up visits were conducted routinely at 1 week postoperatively and every 3 months thereafter as part of standard clinical care. Standardized postoperative photographs and anthropometric measurements were obtained by M.G. at each visit using the same photographic setup and measurement protocol as preoperatively. PROMs were collected at a single predefined postoperative time point (3 months), consistent with a cross-sectional study design. Patient feedback was collected using a structured, standardized questionnaire administered during the 3-month postoperative follow-up visit. There were no missing data for the variables analyzed, as all included patients completed the questionnaire at the predefined 3-month postoperative follow-up. Questionnaires were completed by the patients themselves, without influence from the operating surgeon. The questionnaire assessed the following domains using 5-point Likert-scale responses: (I) overall postoperative satisfaction with the surgical outcome; (II) perceived predictive reliability of the preoperative 3D simulation compared with the actual postoperative result; (III) desire to alter implant volume postoperatively; and (IV) willingness to recommend preoperative 3D simulation to other patients (Table 1). Responses were recorded using a 5-point Likert scale, chosen for its simplicity, ease of administration, and ability to capture graded patient perceptions in a clinically meaningful way. Likert-scale-based response formats are widely used in aesthetic and plastic surgery research, and are considered appropriate for assessing subjective domains such as satisfaction and perceived outcome reliability. However, the questionnaire used in this study was not a formally validated PROM instrument and was specifically designed to assess patient perceptions of 3D simulation in routine clinical practice.

Statistical analysis

Descriptive statistical analysis was performed to summarize patient-reported outcomes. Continuous variables [e.g., age, body mass index (BMI), implant volume] are presented as mean and range. Categorical variables (e.g., satisfaction, perceived reliability, desire to change implant volume, willingness to recommend 3D simulation, implant profile, implant placement, and complications) are presented as frequencies and percentages. No inferential statistical tests were performed, as this study was primarily observational and descriptive in nature. Data management and analysis were conducted using Microsoft Excel (version 365, Microsoft Corp., Redmond, WA, USA).

Ethical consideration

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. According to local institutional and national regulations, formal ethics committee approval was not required for this retrospective study, as it involved only anonymized, routinely collected clinical data without any intervention or deviation from standard care. Written informed consent was obtained from all participants for the use of their clinical data and images for scientific publication.

Results

Patient reported outcomes

The patient-reported outcomes from 126 individuals undergoing primary breast augmentation with 3D simulation provide valuable insight into both satisfaction and the perceived utility of the imaging system. Overall satisfaction with the surgical outcome was high: 122 of 126 patients (96.8%) expressed satisfaction, with 76 (60.3%) selecting strongly agree and 46 (36.5%) selecting agree (Table 1). These findings indicate that early-career surgeons integrating 3D simulation can achieve outcomes meeting or exceeding established satisfaction benchmarks in the literature.

Perceived reliability of the 3D simulation tool also demonstrated strong endorsement, though with more variability than overall satisfaction. A total of 109 patients (86.5%) agreed or strongly agreed that the simulation reliably predicted their outcome, while 12 (9.5%) remained neutral and only 5 (4.0%) disagreed (Table 1). These results support the growing evidence that 3D imaging enhances patient understanding and expectation management. The small proportion expressing uncertainty or disagreement highlights an important limitation: despite technological precision, simulated outcomes remain approximations and are influenced by soft-tissue characteristics, healing behavior, and implant placement nuances.

The desire to change implant volume postoperatively—often used as a surrogate indicator of suboptimal counselling—was low. Only 3 of 126 patients (2.4%) expressed the wish to change their implant size, while 122 (96.8%) did not (Table 1). The three patients who desired a different volume all indicated they wanted a larger size and requested an upsizing procedure. Notably, 82 patients (65.1%) strongly disagreed with wanting a volume change. The distribution also reveals a second cluster (31.7% disagree) that may reflect patients who were satisfied but less emphatically so. This highlights the utility of simulation but also its limits: even precise preoperative tools cannot entirely eliminate subjective postoperative reinterpretation. One patient requested a conversion from anatomical to round implants to achieve more upper pole fullness. This request was not related to concerns about implant rotation or implant surface.

Finally, recommendation behavior – a strong proxy for perceived value—was highly favorable. A total of 116 patients (92.1%) would recommend preoperative 3D simulation to others, with 46 (36.5%) strongly agreeing and 70 (55.6%) agreeing (Table 1). Only 10 patients (7.9%) expressed neutrality or disagreement. Such overwhelmingly positive endorsement suggests that patients view the technology as an empowering decision-making tool. Nevertheless, the presence of neutral or negative responses underscores that simulation should complement, not replace, precise clinical measurements.

Patient demographics and follow-up

Patient age ranged from 18 to 52 years, with a mean of 29 years (Table 2). Average BMI was 21.9 (ranging between 18.7 and 23.9) kg/m². Parity ranged from 0 to 5 children (average 1.4 children). The follow-up ranged from a minimum of 3 months to a maximum of 15 months, with a mean follow-up of 8.6 months for the 126 patients included.

Implant characteristics

Implant profiles consisted of “Moderate” or “Mini” projection in 11% of cases, “Moderate Plus” or “Demi” projection in 69%, and “High” or “Full” projection in 20% (Table 3). Implant volumes ranged from 180 to 575 cc, with a mean volume of 318 cc. Implant placement was dual plane in 85.7% of cases and subfascial in 14.3%.

Complications

One major complication was observed: a postoperative infection occurring 2.5 months after surgery, which required implant removal followed by delayed replacement three months later (Table 4). Two minor complications were recorded, consisting of superficial wound dehiscence at the IMF; both cases were managed conservatively without the need for surgical intervention. No hematomas or seromas were observed. There were no cases of capsular contracture, symmastia, implant rupture, or clinically significant asymmetry, defined as the absence of patient requests for re-intervention due to asymmetry. No cases of double-bubble deformity or bottoming-out were identified after a minimum follow-up of 3 months. One case of lower pole blow-out was detected at eight months postoperatively.

Discussion

Key findings

In this cross-sectional study of 126 patients undergoing primary breast augmentation with 3D simulation, overall postoperative satisfaction was high, with 96.8% of patients expressing satisfaction with their surgical outcome. Most patients (86.5%) perceived the 3D simulation as a reliable predictor of their postoperative appearance, and the vast majority (92.1%) would recommend its use to others. Only a small proportion of patients expressed a desire to change implant volume postoperatively, highlighting the tool’s utility in expectation management.

The data demonstrate that 3D simulation can serve as a valuable adjunct, as it enhances patient understanding and supports informed decision-making, with choice of projection and volume guided by preoperative 3D simulation. We hypothesize that—through offering a visual representation of the potential result—it fosters a sense of control and involvement of the patient. This empowerment can enhance patient satisfaction and confidence in the surgical plan which can ultimately lead to higher conversion rates from initial consultations to scheduled surgeries.

Importantly, all procedures in this study represent the surgeon’s early independent experience following completion of training, without prior unsupervised practice in breast augmentation. While this may be perceived as a limitation, it also represents a unique strength. It allows evaluation of 3D simulation in a real-world setting where surgeons are transitioning to independent practice, a phase in which structured preoperative planning, patient communication, and expectation management are particularly critical. In this context, 3D simulation may serve not only as a visualization tool for patients, but also as a decision-support aid for the surgeon.

Additional observed advantages of 3D simulation

Visual alternative to sizers and “wish photos”

3D simulation offers patients a visual preview of expected outcomes, reducing reliance on physical sizers, which are often a poor representation of the pursued result as it only covers the breast rather than augmenting it (1,10). It makes pre-selected “wish pics” redundant, which may be unrepresentative (e.g., everyone is built different, often the women in the pictures wear a supportive garment) or edited.

Streamlining intraoperative decision-making

Importantly, the use of 3D simulation as a complement to meticulous preoperative measurements and planning makes intraoperative sizers redundant in our setting. As the implant size is chosen together beforehand, only one set of implants has to be ordered and operating times are reduced. This is extremely relevant as a patient under anesthesia cannot make the decision. If the implant and its size are not determined prior to surgery, it can create a reason for postoperative dissatisfaction as it makes the surgeon responsible for an ill-perceived result.

Identification of breast and chest asymmetries

3D simulation allows a more precise evaluation of anatomical asymmetries, including subtle differences in breast volume and chest wall contour, which may otherwise be overlooked. From a caudal perspective, the difference in breast projection, breast volume as well as the shape of the rib cage can be evaluated (Figure 2).

Figure 2 3D simulation helps to understand breast asymmetry. Especially the caudal view is crucial to assess asymmetry in projection as well as width, and assists in the decision whether or not asymmetric implants are indicated. Written informed consent for publication of clinical photographs was obtained from the patient. 3D, three-dimensional.

Although some authors advise not to use 3D simulations in case of asymmetry or specific anatomic variations such as a wide intramammary distance, an emptied upper pole, tuberous or (pseudo)ptotic breasts, unusual nipple-areola complex structures or thorax abnormalities, we propose the opposite (11). If a patient expresses concern about asymmetry, we recommend guiding her through targeted simulations using implants of varying projection and width. This typically results in at least three comparative simulations, each illustrating how subtle changes in implant characteristics influence breast morphology (Figure 3). To enhance comprehension, we provide the patient with digital copies of these simulations, allowing her to toggle between the images at her own pace. This sequential viewing method helps reveal nuanced differences in width and projection that can be difficult to appreciate when the images are displayed side by side.

Figure 3 Patient undergoing breast augmentation with nanotextured and round implants from the brand Motiva, type Ergonomix. She has asymmetry in terms of volume and projection (see Figure 2). We offered simulations with implants that are asymmetric in terms of width and implants that are asymmetric in terms of projection. Left: preoperative photo. Middle left: simulation with different width implants, demi profile and 320 cc on the left side, and demi profile and 360 cc on the right side. Middle right: simulation with same width but different projection implants, demi profile and 320 cc on the left side, and full profile and 375 cc on the right side. Right: result at 6 months postoperatively. (A) Frontal view. (B) Right side view. (C) Right oblique view. (D) Left oblique view. (E) Left side view. (F) Inferior view. (G) Superior view. Written informed consent for publication of clinical photographs was obtained from the patient.

3D imaging “under-promises”

Most simulation programs tend to “under promise”, meaning the predicted images are often less appealing than the actual postoperative results (Figure 4). This helps manage expectations and can reduce the risk of dissatisfaction for both patient and surgeon, particularly regarding upper pole fullness (underestimated) and cleavage width (overestimated) (Figure 5). This is reflected in our study results, as the overall satisfaction after the procedure scores higher than the patient-reported predictability of the 3D simulation tool.

Figure 4 Patient undergoing breast augmentation with nanotextured and round implants from the brand Motiva, type Ergonomix, with a demi profile, and a volume of 380 cc. Left: preoperative photo. Middle: result at 8 months postoperatively. Right: simulation. The 3D simulation underestimates lateral volume as well as implant height and upper pole fulness, flattens the nipple-areolar complex, creates a more dramatic transition from subclavicular area to the upper breast edge, and overall shows an understated predicted outcome. (A) Frontal view. (B) Right side view. (C) Right oblique view. (D) Left oblique view. (E) Left side view. Written informed consent for publication of clinical photographs was obtained from the patient. 3D, three-dimensional.

Figure 5 Patient undergoing breast augmentation with microtextured and teardrop-shaped implants from the brand Mentor, type CPG 323, with a high profile, and a volume of 440 cc. Left: preoperative photo. Middle: result at 3 months postoperatively. Right: simulation. The 3D simulation underestimates the lateral volume, the upper pole fulness and the convexity of the lower pole, overestimates the width of the cleavage, flattens the nipple-areolar complex, creates a more dramatic transition from subclavicular area to the upper breast edge, and overall shows an understated predicted outcome. The 3D simulation does not fully account for envelope filling. As a result, preoperative skin folds persist in the simulation, whereas they are reduced in the postoperative clinical photograph. (A) Frontal view. (B) Right side view. (C) Right oblique view. (D) Left oblique view. (E) Left side view. Written informed consent for publication of clinical photographs was obtained from the patient. 3D, three-dimensional.

Workflow efficiency and patient comfort

In our practice, consultations with 3D simulation improve patient comfort and consultation efficiency, as images can be captured by trained (female) staff, and reviewed on-screen while patients are dressed again.

Tool for education, shared decision-making and standardized follow-up

The simulation process serves as an educational experience, helping patients have more insight in their procedure. By facilitating shared decision-making, 3D simulation contributes to a sense of joint responsibility between surgeon and patient, which leads to fewer postoperative complaints and revision surgeries [as presented by Creasman et al. (12)].

3D simulation devices provide a standardized and reproducible postoperative follow-up. By capturing images in identical lighting, positioning, and camera geometry at each visit, the device allows surgeons to objectively track the dynamic evolution of breast shape over time. This consistency eliminates the variability inherent to traditional 2D photography, where differences in angle or posture can obscure subtle but clinically relevant changes. With 3D imaging, postoperative developments such as implant descent, expansion and rounding of the lower pole, progressive definition of lateral convexity, and the optical upward shift of the nipple-areolar complex become clearly visible (Figure 6).

Figure 6 Frontal, oblique and side views of our patient undergoing breast augmentation with smooth and round implants from the brand Mentor, type MemoryGel Xtra, with a moderate plus profile, and a volume of 545 cc. Left: preoperative photo. Middle: result at 1 week postoperatively. Right: result at 3 months postoperatively. The postoperative development can be evaluated in a visual and standardized fashion. Typically, we can see the anticipated descent of the implant and the subsequent shaping of the lower pole, the lateral convexity (“sideboob”) and the centralization of the nipple-areolar complex. (A) Frontal view. (B) Left oblique view. (C) Left side view. Written informed consent for publication of clinical photographs was obtained from the patient.

These visual timelines strengthen patient understanding and reassurance: many early concerns—such as high implant position, upper pole fullness, a boxy shape, or perceived asymmetry—can be addressed by showing the expected trajectory based on prior patients or on their own earlier scans.

Observed drawbacks of 3D simulation

Workflow considerations

Despite its multiple benefits, 3D simulation is not without limitations. The process can be time consuming, especially during initial implementation in practice, or when too many options are presented without prior filtering by the surgeon. It is the surgeon’s task to narrow down the spectrum of options based on measurements and physical assessment. In the authors’ experience, it is less time consuming compared to alternative methods such as using bra sizers.

Balancing investment and return

An important consideration in using 3D simulation technologies is the cost-effectiveness. High-quality, detailed 3D images typically require sophisticated scanners, which involve a substantial upfront investment. However, this expense can be justified by potential reductions in revision surgery and improved consultation-to-surgery conversion rates, as noted in previous reports (1,13,14).

From bulky to compact 3D simulation devices: addressing the space challenge

An additional consideration is the need for sufficient space to accommodate the device. Such systems are often used in private practices, where extra space may be limited. Modern, compact, and lightweight devices can mitigate these logistical issues and reduce associated costs (15).

Volume underestimation and shape distortion

In the authors’ experience, simulations often underestimate implant volume and height (Figure 4). This can lead to the selection of implants that appear appropriate on screen but are larger in reality. In our cohort, preoperative counseling helped patients anticipate this limitation, and no patient requested smaller implants postoperatively.

The 3D simulation device has tendency to display round implants as teardrop-like devices with a relatively empty lower pole, or shelf deformity, and strong projection, which can be misleading for the novice surgeon and patient. The choice between round and anatomical implants should not be influenced by the 3D simulation device, but is based on other parameters such as lower pole development, skin and tissue compliance, IMF type, and nipple position.

This brings us to the fact that 3D simulation does not replace the surgeon’s clinical judgment. It cannot predict how individual tissues will respond to augmentation—whether they are compliant, elastic, firm or resistant—which remains a critical factor in achieving optimal outcomes. It does not consider one’s proportions such as the chest-to-waist ratio. 3D simulation does not classify the IMF, nor does it predict the risk of bottoming-out or double-bubble deformity.

Image distortion in patients with tattoos

Tattoos can interfere with the surface-mapping algorithms used in 3D simulation systems, leading to changes in contour, minor irregularities or distortions in the simulated breast. They may temporarily distract or confuse both patients and novice surgeons during the consultation. It is therefore important to explain this limitation beforehand.

Study limitations

Our study has several limitations that should be acknowledged. First, its retrospective and descriptive design, with a relatively low patient number and without a control group, precludes direct comparison between patients evaluated with or without 3D simulation. As 3D simulation was used routinely for all patients during the study period, it was not possible to assess relative differences in satisfaction, predictability, or conversion rates compared with conventional consultation methods. Consequently, causal inferences regarding the superiority of 3D simulation cannot be drawn.

Second, the study reflects routine clinical practice rather than a controlled screening protocol. As part of the patient pathway, some individuals were preselected through external referral systems, and detailed data on all excluded patients were not available. This may introduce selection bias and limits the ability to fully characterize the screened population.

Third, outcome assessment relied primarily on patient-reported perceptions of satisfaction and perceived predictability rather than on objective measurements of surgical accuracy. While patient perception is highly relevant in aesthetic surgery, these findings should be interpreted as reflecting subjective reliability rather than objective concordance between simulated and postoperative outcomes. A Likert scale may oversimplify nuanced patient perception and introduce bias. Evaluating postoperative satisfaction at three months may still reflect transient positive emotions, courtesy bias, or the “honeymoon effect”.

Fourth, the follow-up period, although sufficient to assess early implant settling and patient satisfaction, was limited to a mean of 8.6 months and does not allow conclusions regarding long-term outcomes such as late capsular contracture or implant-related changes over time.

Finally, all procedures were performed by a single early-career, board-certified plastic surgeon, which may limit generalizability to surgeons at different stages of experience or with different practice patterns. However, this also represents a unique strength, as it reflects real-world early independent practice and highlights the potential role of 3D simulation as a decision-support tool during the learning curve.

Reflection and flexibility in implant selection

While more apprehensive colleagues have expressed the concern that patients will require achieving the “promised” result as shown on the screen, we stimulate patients to take copies of the 3D simulation(s) prior to leaving our office. It helps them to review the images when they are at ease, and discuss the options with partner or friends. Their decision can still change and therefore we recommend ordering the implants relatively late e.g., 1 week prior to surgery.

3D vs. no 3D: a comparison

Several recent studies have evaluated the accuracy and clinical value of 3D simulations in aesthetic breast surgery. Assaaeed et al. assessed the predictive accuracy of the Canfield VECTRA XT 3D imaging system in 42 patients (84 breasts). Preoperative 3D simulations were compared with actual postoperative results 3 months after surgery, focusing on breast volume, surface contour, projection, and internal angle. The mean volumetric discrepancy was only 21.5±10.3 cc, corresponding to an accuracy of 91.9%. Differences in projection and internal angle were minimal, indicating high geometric precision (16).

Zhou et al. compared breast morphology parameters between 3D simulations and actual postoperative outcomes in 103 patients who underwent breast augmentation. The study found a slight increase in the nipple-IMF distance and breast base width. Significant discrepancies were observed in upper and lower breast volume distribution between 3D images and actual results, a difference that disappeared in patients with larger chest circumferences. The authors emphasized that breast volume and thoracic dimensions should be carefully considered when using 3D simulations for preoperative planning (17).

Vorstenbosch et al. compared preoperative 3D images with 6-month postoperative outcomes in 20 patients. Thirteen plastic surgeons evaluated overall appearance, breast height, width, volume, projection, and nipple position. A strong similarity was found between simulated and actual postoperative results across all parameters (18).

La Padula et al. conducted a prospective study evaluating both patient satisfaction and aesthetic similarity between preoperative 3D simulations and actual outcomes. Forty patients rated simulation realism and satisfaction using a visual analogue scale, while surgical outcome satisfaction was assessed using the BREAST-Q Augmentation Module. Mean simulation satisfaction was 8.2, and postoperative BREAST-Q scores improved significantly across all domains compared with preoperative values. Volume prediction was more accurate than precise shape replication; therefore, patients should be informed that an exact match in breast shape cannot be guaranteed (19).

It is worth noting that emerging technologies such as artificial intelligence (AI) can contribute in large dataset studies, generating more high impact clinical evidence. Chartier et al. introduced BreastGAN, developed to simulate breast augmentation outcomes using real clinical images. The AI-generated postoperative images demonstrated concordance with actual postoperative results, underscoring the potential of AI to enhance preoperative planning (20).

A landmark study by Donfrancesco et al. (7) evaluated the role of 3D simulation in breast augmentation using both patient-reported outcomes and an independent panel assessment comparing simulated and postoperative results. In their prospective series of 150 patients, 86% perceived the simulation as very accurate, and the independent panel reported a high overall similarity score (mean 7.5/10) between simulated and actual outcomes. Our findings are consistent with these results, with 86.5% of patients in our cohort perceiving the simulation as reliable or very reliable. However, several important differences distinguish our study from this earlier work. Donfrancesco et al. investigated a highly standardized patient population within a single high-volume center, using exclusively anatomically shaped implants and a uniform surgical technique. In contrast, our study reflects a more heterogeneous, real-world patient population, including both round and anatomical implants, varying implant surfaces, and different implant placements. As such, our study extends their observations by demonstrating the applicability and effectiveness of 3D simulation in contemporary routine clinical practice.

Standardization and measurement parameters

Standardization of 3D simulation protocols is essential to ensure consistent, reproducible, and therefore comparable data across studies. Although multiple investigations have examined various aspects of 3D technology in aesthetic breast surgery, there is no universally accepted protocol for defining anatomical landmarks, reference points, or measurement parameters such as shape, distance, or volume. Additionally, several different companies offer 3D simulators each with their own characteristics, strengths and flaws. This lack of methodological consistency complicates the comparison and interpretation of results in current literature.

The VECTRA system software can automatically place specific landmarks on the virtual model, generating data used for implant selection. However, manual landmark placement on the patient before simulation has been shown to yield more consistent measurements of breast width and provides a more individualized and anatomically accurate approach. Although breast width remains an important factor in implant selection, several authors recommend positioning landmarks manually, guided not solely by existing breast dimensions but by the desired implant position and aesthetic goal (21-23). These findings reaffirm the superiority of clinical judgement.

As implant width is a key determinant in selecting the appropriate prosthesis, Akgun Demir et al. compared anatomical landmark positioning for determining implant width using clinical assessment (CA) versus 3D imaging, both automatically (VA) and manually (VM). The study aimed to predict the correct implant by measuring breast width and subtracting the medial and lateral breast tissue thickness. Compared to the actual implant dimensions, CA measurements were significantly smaller, while VA and VM measurements were significantly larger. These findings underscore the discrepancies between clinical and simulated measurements (21).

Conclusions

3D simulation has emerged as a valuable adjunct in aesthetic breast surgery, enhancing preoperative planning, improving patient-surgeon communication, and increasing postoperative satisfaction. When the advantages and limitations of 3D simulations are well understood, this innovative technology is a useful complement to standard measurements and clinical assessment. This paper is one of many studies which underscores the numerous benefits of 3D scanners, ultimately leading to favorable results for both patients and surgeons. The focus on an early-career, board-certified plastic surgeon, without case exclusion, represents a specific strength of this study. In this context, 3D simulation may function not only as a patient communication tool, but also as a decision-support aid for surgeons at the beginning of independent practice, particularly in implant size selection and expectation management.

Acknowledgments

The authors wish to thank Dr. Craig Layt and Dr. Luke Stradwick who trained the senior author (M.G.) in aesthetic breast surgery as well as the application and interpretation of 3D simulation during the advanced aesthetic fellowship at the Breast Academy, Gold Coast, Australia.

Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editor (Ayush Kapila) for the series “Innovations in Breast Surgery” published in Annals of Breast Surgery. The article has undergone external peer review.

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://abs.amegroups.com/article/view/10.21037/abs-2025-1-60/rc

Data Sharing Statement: Available at https://abs.amegroups.com/article/view/10.21037/abs-2025-1-60/dss

Peer Review File: Available at https://abs.amegroups.com/article/view/10.21037/abs-2025-1-60/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://abs.amegroups.com/article/view/10.21037/abs-2025-1-60/coif). The series “Innovations in Breast Surgery” was commissioned by the editorial office without any funding or sponsorship. The authors declare that they have no financial relationships, commercial interests, or other conflicts of interest with VECTRA (or any manufacturer of 3D imaging systems), nor with Mentor or Motiva (or any manufacturer of breast implants). No funding, sponsorship, or material support was received for this study. All equipment used was part of routine clinical practice. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. According to local institutional and national regulations, formal ethics committee approval was not required for this retrospective study, as it involved only anonymized, routinely collected clinical data without any intervention or deviation from standard care. Written informed consent was obtained from all participants for the use of their clinical data and images for scientific publication.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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