Autologous Mastopexy and Autoaugmention of the Breast

Raafat, Sarah; Ezzat, Sherif Z; Khachaba, Youssif; Aboul-Nasr, Laila A

doi:10.1097/gox.0000000000003126

Cited by 8 publications

(8 citation statements)

References 21 publications

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“…P malignant = 1 − P benign (2) In our work, W1 = W2 = W3 = 0.33. The parameters above are evaluated by experienced breast ultrasound doctors according to the performance of a single neural network.…”

Section: Ensemble Neural Networkmentioning

confidence: 64%

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An Intelligent Breast Ultrasound System for Diagnosis and 3D Visualization

Chen

et al. 2022

Electronics

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Background: Ultrasonography is the main examination method for breast diseases. Ultrasound imaging is currently relied upon by doctors to form statements of characteristics and locations of lesions, which severely limits the completeness and effectiveness of ultrasound image information. Moreover, analyzing ultrasonography requires experienced ultrasound doctors, which are not common in hospitals. Thus, this work proposes a 3D-based breast ultrasound system, which can automatically diagnose ultrasound images of the breasts and generate a representative 3D breast lesion model through typical ultrasonography. Methods: In this system, we use a weighted ensemble method to combine three different neural networks and explore different combinations of the neural networks. On this basis, a breast locator was designed to measure and transform the spatial position of lesions. The breast ultrasound software generates a 3D visualization report through the selection and geometric transformation of the nodular model. Results: The ensemble neural network improved in all metrics compared with the classical neural network (DenseNet, AlexNet, GoogLeNet, etc.). It proved that the ensemble neural network proposed in this work can be used for intelligent diagnosis of breast ultrasound images. For 3D visualization, magnetic resonance imaging (MRI) scans were performed to achieve their 3D reconstructions. By comparing two types of visualized results (MRI and our 3D model), we determined that models generated by the 3D-based breast ultrasound system have similar nodule characteristics and spatial relationships with the MRI. Conclusions: In summary, this system implements automatic diagnosis of ultrasound images and presents lesions through 3D models, which can obtain complete and accurate ultrasound image information. Thus, it has clinical potential.

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Section: Ensemble Neural Networkmentioning

confidence: 64%

“…As female sex organs, breasts have both internal function and external beauty, which are pivotal to women [1][2][3][4][5]. Usually, breasts are continuously undergoing developmental changes, and the structure of their glands is complex.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Breast Ultrasound System for Diagnosis and 3D Visualization

Chen

et al. 2022

Electronics

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“…This unplanned intraoperative draping may lead to postoperative asymmetries of the scarring or amounts of parenchymal and skin resection. 3 , 17 , 18 …”

Section: Discussionmentioning

confidence: 99%

“…This unplanned intraoperative draping may lead to postoperative asymmetries of the scarring or amounts of parenchymal and skin resection. 3,17,18 For patients with a greater degree of ptosis-a vertical excess of greater than 4 cm-we reverted to an inverted T-scar mastopexy, in which both vertical and horizontal excess are adequately managed. The choice of which pedicle to use, however, is independent of the incision design.…”

Section: Prs Global Open • 2022mentioning

confidence: 99%

Augmentation Mastopexy: A Five-step Standardized Strategy Approach

Abdelkader

Raafat

Sakr

et al. 2022

Plastic and Reconstructive Surgery - Global Open

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Introduction: Planning a combined procedure requires ensuring an optimal fill of the reduced breast skin envelope, which in turn requires a system to quantify skin excess to ensure that the selected implant achieves that optimal fill. This has led us to develop a five-step approach that a surgical team can use to assess patients scheduled to undergo an augmentation mastopexy and arrive at an optimal surgical strategy. Methods: This retrospective study included 50 consecutive cases where layered mastopexies combined with augmentation mammaplasties were performed. Step 1 entailed a preoperative examination and evaluation of the breasts. In step 2, the breast volume was assessed. The pocket plane was determined in step 3. The choice of which surgical technique to use was done in step 4, and in step 5, the horizontal skin excess was assessed. Results: The average implant size was 300 cm 3 (range: 170–350 cm 3 ). The overall revision rate was 4%: on average, revision surgeries were performed 24 months after the first surgery. The average implant size was 300 cm 3 (range: 170–350 cm 3 ). Conclusions: Early results of single-stage augmentation with mastopexy have shown that the design of this systematic five-step approach demonstrates a great potential for producing reliable results with minimal risk. Using this five-step approach will improve patient and surgeon satisfaction and help to replace the old concept of “fill and re-drape” with a new one of “plan, reduce, fill, and re-drape.”

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“…It included questions regarding surgical satisfaction with breast appearance, sexual wellbeing, and overall body image. 8 , 9 The surgeon’s satisfaction was also evaluated objectively by combining the presence of complications and postoperative measurements, including the suprasternal notch to nipple and nipple to inframammary fold distance.…”

Section: Methodsmentioning

confidence: 99%

Systematic Approach for Management and Prevention of Boxy Breast

Abdelkader

El-Noamany

Raafat

2021

Plastic and Reconstructive Surgery - Global Open

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Background: Although a boxy breast is a common aesthetic problem following breast reduction and mastopexy, literature regarding this deformity is scarce. It is vaguely described as a definitive postreduction deformity. To address this complication, it is important to fully analyze the problem, understand and predict its causes, and then try to prevent it. Methods: This study included two groups. Group 1 included 14 patients presenting with boxy postoperative breasts. Revision surgeries were conducted for all patients, and the first algorithm was created for quantifying breast surgery in revision cases. Group 2 included 37 cases of primary mammaplasty reduction/mastopexy performed between 2016 and 2019. All the patients in this group were treated as per the study algorithm. Results: Patient satisfaction was measured on a scale of one to 10, with one being extremely dissatisfied and 10 being extremely satisfied. The results indicated overall satisfaction, with average scores of 9.5 and 9.1 in groups 1 and 2, respectively; the scores of surgeon satisfaction were 8.2 and 8.6, respectively. Conclusions: The proposed algorithm, preoperative markings, intraoperative techniques, and postoperative orientation may help achieve optimal results and prevent undesired deformities or asymmetry. Applying a flexible and simplified algorithm provided a more objective plan, which enabled surgeons to attain more satisfactory results. Following a preset quantified plan supported and shortened learning curves and objectively addressed the common postoperative complication, breast boxing.

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Autologous Mastopexy and Autoaugmention of the Breast

Cited by 8 publications

References 21 publications

An Intelligent Breast Ultrasound System for Diagnosis and 3D Visualization

An Intelligent Breast Ultrasound System for Diagnosis and 3D Visualization

Augmentation Mastopexy: A Five-step Standardized Strategy Approach

Systematic Approach for Management and Prevention of Boxy Breast

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