Visual Breast Asymmetry Assessment with Optical-Flow Algorithm

Monton, Javier; Kenig, Nitzan; Insausti, Ricardo; Jordan, Joaquin

doi:10.1007/s10916-020-01630-6

Cited by 3 publications

(5 citation statements)

References 20 publications

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“… 41 However, we established strict guidelines to mark fiducial points and mitigate subjectivity ( Figure ). Alternatively, automated algorithms, such as the one proposed by Monton et al 42 which uses an optical flow algorithm or the automated identification of fiducial points by Kawale et al, 43 may be used for unbiased symmetry assessment. It should be noted that our dataset lacks diversity in the demographics, thus the analysis may not be generalizable to non-Caucasian populations.…”

Section: Discussionmentioning

confidence: 99%

Objective Analysis of Breast Symmetry in Female Patients Undergoing Breast Reconstruction After Total Mastectomy

Sampathkumar

Bui

et al. 2022

Aesthetic Surgery Journal Open Forum

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Background Satisfaction with the breast aesthetic outcome is an expectation of breast reconstruction surgery, which is an integral part of cancer treatment for many patients. We evaluated post reconstruction breast symmetry in 82 female patients using distance and volume measurements. Objectives Clinical factors, such as reconstruction type (implant-based and autologous reconstruction), laterality, timing of reconstruction (immediate, delayed, and sequential), radiation therapy (RT), and demographic factors (age, BMI, race, and ethnicity) were evaluated as predictors of postoperative symmetry. Matched preoperative and postoperative measurements for a subset of 46 patients were used to assess correlation between preoperative and postoperative symmetry. Methods We used standardized differences between the left and right breasts for the sternal notch to lowest visible point distance and breast volume as metrics for breast, positional symmetry, and volume symmetry, respectively. We performed statistical tests to compare symmetry between subgroups of patients based on reconstruction type, laterality, timing, RT, and demographics. Results Overall, reconstruction type, reconstruction timing, and RT were observed to be factors significantly associated with postoperative symmetry, with implant reconstructions and immediate reconstruction procedures, and no RT showing better postoperative breast volume symmetry. Subgroup analyses, for both reconstruction type and laterality, showed superior volume symmetry for the bilateral implant reconstructions. No correlation was observed between preoperative and postoperative breast symmetry. Demographic factors were not significant predictors of post reconstruction symmetry. Conclusions This comprehensive analysis examines multiple clinical factors in a single study and will help both patients and surgeons make informed decisions about reconstruction options at their disposal.

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Section: Discussionmentioning

confidence: 99%

Objective Analysis of Breast Symmetry in Female Patients Undergoing Breast Reconstruction After Total Mastectomy

Sampathkumar

Bui

et al. 2022

Aesthetic Surgery Journal Open Forum

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“…[24][25][26] Subjective methods are difficult to quantify in a scientific manner because, even when measurements can be taken, the involvement of the human factor can lead to disagreement between observers. 8,27 According to some previous studies, computer-generated tools might be superior to subjective human evaluations because of differences between the observers, even in cases where observers are from the medical field. [28][29][30] The introduction of computer-generated neural networks in medical science has clear advantages, as this process can be generated by an objective system that applies similar parameters in each observation.…”

Section: Discussionmentioning

confidence: 99%

“…24–26 Subjective methods are difficult to quantify in a scientific manner because, even when measurements can be taken, the involvement of the human factor can lead to disagreement between observers. 8,27 According to some previous studies, computer-generated tools might be superior to subjective human evaluations because of differences between the observers, even in cases where observers are from the medical field. 28–30…”

Section: Discussionmentioning

confidence: 99%

“…2 However, objective evaluation methods have shown less variability when compared with subjective assessments, 3 and the need for quantitative procedures has been well established. 4,5 Different computer programs exist to evaluate symmetry in a more objective manner (ie, Breast Aesthetic Scale, 6 kOBCS, 7 VIBA-Calc 8 ), but in most cases, the operator must introduce the data manually or make calculations. Some of the key features used in breast symmetry evaluation are the sternal notch, the nipple-areola complex (NAC), and the inferior and lateral boundaries of the breast 9 (Fig.…”

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confidence: 99%

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Identification of key breast features using a neural network: applications of machine learning in the clinical setting of Plastic Surgery

Kenig¹,

Echeverria²,

Ossa³

2023

Plastic &Amp; Reconstructive Surgery

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Background: In plastic surgery, evaluation of breast symmetry is an important aspect of clinical practice. Computer programs have been developed for this purpose, but most of them require operator input. Artificial intelligence has been introduced into many aspects of medicine. In plastic surgery, automated neural networks for breast evaluation could improve quality of care. In this work, the authors evaluate the identification of breast features with an ad hoc trained neural network. Methods: An ad hoc convolutional neural network was developed on the YOLOV3 platform to detect key features of the breast that are commonly used in plastic surgery for symmetry evaluation. The program was trained with 200 frontal photographs of patients who underwent breast surgery and was tested on 47 frontal images of patients who underwent breast reconstruction after breast cancer surgery. Results: The program was able to detect key features in 97.74% of cases (boundaries of the breast in 94 of 94 cases, the nipple-areola complex in 94 of 94 cases, and the suprasternal notch in 41 of 47 cases). Mean time of detection was 0.52 seconds. Conclusions: The ad hoc neural network was successful in localizing key breast features, with a total detection rate of 97.74%. Neural networks and machine learning have the potential to improve the evaluation of breast symmetry in plastic surgery by automated and quick detection of features used by surgeons in practice. More studies and development are needed to further knowledge in this area.

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“…Further development in the objective assessment of breast asymmetry came to light with the application of convolutional neural network architecture for asymmetry recognition in mammography breast imaging data [26]. Another novel visual breast assessment method uses an optical flow algorithm in MATLAB which objectively classifies and numerically scores breast asymmetry [27]. Considering all the statistical data, 3D objective assessment has been proven to be more consistent and accurate, leading it to be a prospective replacement of subjective panel assessment in terms of aesthetic evaluation after breast conserving treatment [28].…”

Section: Introductionmentioning

confidence: 99%

Breast Asymmetry Evaluation Using Objective Measures after Breast Cancer Surgery

Park¹,

Haque²,

Chedjou³

et al. 2021

JBiSE

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Although a positive cosmetic outcome is an important goal of breast cancer reconstruction, the objective analysis of breast aesthetics has yet to reach a gold standard or unified method to quantify breast symmetry. Several scoring systems, both subjective and objective, have been developed over the years to ensure the desirable outcome in breast symmetry, but these methods have yet to reach the unanimous acceptance in terms of accuracy, value and ease of use to be implemented in the clinical setting. By assessing several existing symmetry scores, most of which are based on 2D imaging, along with our own set of symmetry parameters applied to 3D patient images, the goal of this study is to determine if there is an advantage of 3D imaging in formulating an accurate objective breast aesthetic score over the existing objective scores. A reliable breast aesthetic score would improve the decision-making in surgery as well as improve patient satisfaction. Additionally, knowing the quantity and degree of breast asymmetry objectively will improve outcome and reduce revision rates, minimizing patient suffering and improving the overall quality of patient life and body image.

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Visual Breast Asymmetry Assessment with Optical-Flow Algorithm

Cited by 3 publications

References 20 publications

Objective Analysis of Breast Symmetry in Female Patients Undergoing Breast Reconstruction After Total Mastectomy

Objective Analysis of Breast Symmetry in Female Patients Undergoing Breast Reconstruction After Total Mastectomy

Identification of key breast features using a neural network: applications of machine learning in the clinical setting of Plastic Surgery

Breast Asymmetry Evaluation Using Objective Measures after Breast Cancer Surgery

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