Quantitative assessment of breast volume changes after whole-breast irradiation for breast cancer using breast auto-segmentation.

PURPOSE: This study aimed to quantitatively estimate the changes in breast volume associated with radiotherapy in patients undergoing breast-conserving surgery and whole-breast irradiation (WBI). METHODS: Pre-WBI simulation computed tomography (CT) scans and post-WBI follow-up chest CT scans from a total of 1,151 breast cancer patients were analyzed using a deep-learning-driven auto-segmentation approach. The CT-based asymmetry index (CTAI) was calculated by dividing the volume of the irradiated breast by the volume of the contralateral breast. Significant breast shrinkage was defined as a CTAI < 0.85. To quantify changes in CTAI over the follow-up period, the CTAI ratio was determined as the post-WBI CTAI divided by the pre-WBI CTAI. A multivariate logistic regression analysis was conducted to identify potential variables associated with post-WBI significant breast shrinkage. RESULTS: The median CTAI values for pre- and post-WBI CT scans were 0.973 (interquartile range: 0.887-1.069) and 0.866 (interquartile range: 0.773-0.967), respectively. The difference between them was statistically significant (p < 0.001). Following WBI, there was an increase in the rate of significant breast shrinkage from 16.3 to 44.8%. The CTAI ratio showed a negative association with the time interval (p < 0.001, Pearson r = - 0.310). In the multivariate logistic regression analysis, lower pre-WBI CTAI, younger age, and longer interval between CT scans were found to be significantly associated with a higher occurrence of post-WBI significant breast shrinkage. CONCLUSION: Breast volume decreases following WBI, and this decrease is correlated with an increased duration after WBI. These findings highlight the long-term consequences of WBI on breast asymmetry.

Untargeted serum metabolomic profiles and breast density in young women.

PURPOSE OF THE STUDY: Breast density is an established risk factor for breast cancer. However, little is known about metabolic influences on breast density phenotypes. We conducted untargeted serum metabolomics analyses to identify metabolic signatures associated with breast density phenotypes among young women. METHODS: In a cross-sectional study of 173 young women aged 25-29 who participated in the Dietary Intervention Study in Children 2006 Follow-up Study, 449 metabolites were measured in fasting serum samples using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariable-adjusted mixed-effects linear regression identified metabolites associated with magnetic resonance imaging measured breast density phenotypes: percent dense breast volume (%DBV), absolute dense breast volume (ADBV), and absolute non-dense breast volume (ANDBV). Metabolite results were corrected for multiple comparisons using a false discovery rate adjusted p-value (q). RESULTS: The amino acids valine and leucine were significantly inversely associated with %DBV. For each 1 SD increase in valine and leucine, %DBV decreased by 20.9% (q = 0.02) and 18.4% (q = 0.04), respectively. ANDBV was significantly positively associated with 16 lipid and one amino acid metabolites, whereas no metabolites were associated with ADBV. Metabolite set enrichment analysis also revealed associations of distinct metabolic signatures with %DBV, ADBV, and ANDBV; branched chain amino acids had the strongest inverse association with %DBV (p = 0.002); whereas, diacylglycerols and phospholipids were positively associated with ANDBV (p ≤ 0.002), no significant associations were observed for ADBV. CONCLUSION: Our results suggest an inverse association of branched chain amino acids with %DBV. Larger studies in diverse populations are needed.

Automated breast volume scanner based Radiomics for non-invasively prediction of lymphovascular invasion status in breast cancer.

PURPOSE: Lymphovascular invasion (LVI) indicates resistance to preoperative adjuvant chemotherapy and a poor prognosis and can only be diagnosed by postoperative pathological examinations in breast cancer. Thus, a technique for preoperative diagnosis of LVI is urgently needed. We aim to explore the ability of an automated breast volume scanner (ABVS)-based radiomics model to noninvasively predict the LVI status in breast cancer. METHODS: We conducted a retrospective analysis of data from 335 patients diagnosed with T1-3 breast cancer between October 2019 and September 2022. The patients were divided into training cohort and validation cohort with a ratio of 7:3. For each patient, 5901 radiomics features were extracted from ABVS images. Feature selection was performed using LASSO method. We created machine learning models for different feature sets with support vector machine algorithm to predict LVI. And significant clinicopathologic factors were identified by univariate and multivariate logistic regression to combine with three radiomics signatures as to develop a fusion model. RESULTS: The three SVM-based prediction models, demonstrated relatively high efficacy in identifying LVI of breast cancer, with AUCs of 79.00%, 80.00% and 79.40% and an accuracy of 71.00%, 80.00% and 75.00% in the validation cohort for AP, SP and CP plane image. The fusion model achieved the highest AUC of 87.90% and an accuracy of 85.00% in the validation cohort. CONCLUSIONS: The combination of radiomics features from ABVS images and an SVM prediction model showed promising performance for preoperative noninvasive prediction of LVI in breast cancer.

The Diagnostic Significance of the BI-RADS Classification Combined With Automated Breast Volume Scanner and Shear Wave Elastography for Breast Lesions.

OBJECTIVE: We herein compared the diagnostic accuracy of the BI-RADS, ABVS, SWE, and combined techniques for the classification of breast lesions. METHODS: Breast lesions were appraised using the BI-RADS classification system as well as the combinations of BI-RADS plus ABVS (BI-RADS + ABVS) and BI-RADS plus SWE (BI-RADS + SWE), and both methods (BI-RADS + ABVS + SWE) by two specialties Medical Ultrasound physician. The Fisher's exact and χ2 tests were performed to compare the degree of malignancy for the various methods with a pathology ground truth. Receiver operating characteristic curves (ROC) were generated and the corresponding area under the curve (AUC) values were determined to test the diagnostic efficacy of the various methods and identify the optimal SWE cut-off indicative of malignancy. RESULTS: The incidence of the retraction phenomenon on ABVS images of the malignant group was significantly higher (P < .001) than that of the benign group. The specificity, sensitivity, and positive and negative predictive values of the BI-RADS classification were 88.72, 79.38, 83.70, and 85.50%, respectively. BI-RADS plus SWE-Max exhibited enhanced specificity, sensitivity, and positive and negative predictive values of 88.72, 92.78, 85.70, and 94.40%, respectively. Similarly, when BI-RADS + ABVS was utilized, the sensitivity and negative predictive value increased to 95.88 and 96.40%, respectively. BI-RADS + ABVS + SWE possessed the highest overall sensitivity (96.91%), specificity (94.74%), and positive (93.10%) and negative (97.70%) predictive values from all four indices. CONCLUSION: ABVS and SWE can reduce the subjectivity of BI-RADS. As a result, BI-RADS + ABVS + SWE resulted in the best diagnostic accuracy.

Value of multimodal imaging in the diagnosis of breast sclerosing adenosis associated with malignant lesions.

AIM: To explore the diagnostic value of multimodal imaging techniques, including automatic breast volume scanner (ABVS), mammography (MG), and magnetic resonance (MRI) in breast sclerosing adenosis (SA) associated with malignant lesions. METHODS: From January 2018 to October 2020, 76 patients (88 lesions) with pathologically confirmed as SA associated with malignant or benign lesions were retrospective analyzed. All patients completed ABVS examination, 58 patients (67 lesions) with MG and 50 patients (62 lesions) with MRI were also completed before biopsy or surgical excision, of which, six patients (eight lesions) diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 3 by all imaging examinations underwent surgical excision without biopsy, other 70 patients (80 lesions) with BI-RADS category 4 or above by any imaging examination completed biopsy, including 65 patients (75 lesions) were further surgical excised and the other five patients (five lesions) were just followed up. All lesions were retrospectively described and classified, and were divided into benign group and malignant group according to their pathological results. Image features of different examination methods between the two groups were compared and analyzed. A ROC curve was established using the sensitivity of BI-RADS categories to predict malignant lesions in different imaging techniques as the ordinate and 1-specificity as the abscissa. RESULTS: 88 lesions including 26 purely SA and 45 SA associated with benign lesions were classified as benign group, and the remaining 17 SA associated with malignant lesions were classified as malignant group. On ABVS, 40 mass lesions, their heterogeneous echo, not circumscribed margin and coronal convergence signs were statistically significant for malignant lesions (p < .05), but the remain 48 nonmass lesions lack specific sonographic features. On MG, 12 showed negative results, 55 showed with microcalcification, mass, structural distortion, and asymmetric density shadow, of which 11 lesions had the above two signs at the same time, but only microcalcification had statistical difference between the two groups. 35 mass enhanced lesions and 27 nonmass enhanced lesions on MRI, but there were no significant difference between their pathological results. Time signal intensity curves showed no differences, but ADC value <1.10 × 10-3  mm2 /s is more significant in malignant lesions (p < .05). The area under the ROC curve (AUC) of BI-RADS classification of ABVS, MG, and MRI in the diagnosis of malignant lesions were 0.611, 0.474, and 0.751, respectively, and the AUC of the combined diagnosis of the three was 0.761. CONCLUSION: Mass lesions with heterogeneous echo, not circumscribed margin and coronal convergence sign on ABVS, microcalcification on MG and the ADC value <1.10 × 10-3  mm2 /s on MRI are significant signs for SA associated with malignant lesions. The combined diagnosis of the three methods was the highest, and the following were MRI, ABVS, and MG. Therefore, be cognizant of significant characteristics in SA associated with malignancy showed in different imaging examinations can improve the preoperative evaluation of SA and better provide basis for subsequent clinical decision-making.

Quantification of Breast Volume According to age and BMI: A Three-Dimensional MRI Analysis of 400 Women.

OBJECTIVE: Breast size alteration is the most common aesthetic surgical procedure worldwide. This study aimed to assess the correlation between breast volume and BMI or age. MATERIALS AND METHODS: The analyses were conducted utilizing 400 patients selected by a retrospective review of the archives at our institution. Epidemiological data and medical history were assessed. Adjusting for the age and BMI of patient from previously described cohorts, we calculated mean breast volumes per side and differences from the upper and lower percentiles to the mean volumes. RESULTS: The patients had a median BMI of 23.5 (range: 14.7-45.6) and a median age of 51 (range: 24-82). The average total breast volume increased strongly with BMI (r=0.834, p<0.01) and moderately with age (r=0.305, p<0.01). Within a BMI range of 18-24, breast volumes in the 8th and 18th percentile differ on average by about 50 ml. One BMI unit increase in women with breast sizes in the 10th percentile accounts for a breast volume difference of about 30 ml. CONCLUSION: BMI strongly correlates with breast size. To achieve natural results, preoperative consultation and planning of aesthetic and reconstructive breast surgery must recognize BMI as a major determinant of average breast size. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

How much error is associated with calculating breast volume from three-dimensional breast scans obtained when women are standing? Implications for bra design and bra fit.

BACKGROUND: A lying prone position is recommended when scanning women's breasts to ensure the entire breast can be visualised. However, several large databases contain three-dimensional scans of women's breasts and torsos that were obtained while the women were standing. This study aimed to establish the error associated with calculating breast volume from three-dimensional breast scans taken when women were standing relative to lying prone. METHODS: Breast volume was derived for 378 women with Small, Medium, Large and Hypertrophic breast sizes from scans taken while the women were standing and then lying prone. RESULTS: The magnitude of error associated with breast volume derived from scans obtained while women stood compared to lying prone, ranged from ∼8-22% and increased with increasing breast size. CONCLUSION: Errors associated with breast volume data derived from breast scans collected while women stand must be accounted for, particularly for women with Medium, Large and Hypertrophic breast sizes. Practitioner summary: This original research provides evidence for bra designers and manufacturers on the degree of error associated when using breast scans obtained while women were standing, such as those scans readily available in large scanning databases. These errors increase with increasing breast size and must be accounted for when sizing and designing bra cups.

An Optimized Radiomics Model Based on Automated Breast Volume Scan Images to Identify Breast Lesions: Comparison of Machine Learning Methods: Comparison of Machine Learning Methods.

OBJECTIVES: To develop and test an optimized radiomics model based on multi-planar automated breast volume scan (ABVS) images to identify malignant and benign breast lesions. METHODS: Patients (n = 200) with breast lesions who underwent ABVS examinations were included. For each patient, 208 radiomics features were extracted from the ABVS images, including axial plane and coronal plane. Recursive feature elimination, random forest, and chi-square test were used to select features. A support vector machine, logistic regression, and extreme gradient boosting were utilized as classifiers to differentiate malignant and benign breast lesions. The area under the curve, sensitivity, specificity, accuracy, and precision was used to evaluate the performance of the radiomics models. Generalization of the radiomics models was verified through 5-fold cross-validation. RESULTS: For a single plane or a combination of planes, a combination of recursive feature elimination, and support vector machine yielded the best performance when identifying breast lesions. The machine learning models based on a combination of planes performed better than those based on a single plane. Regarding the axial plane and coronal plane, the machine learning model using a combination of recursive feature elimination and support vector machine yielded the optimal identification performance: average area under the curve (0.857 ± 0.058, 95% confidence interval, 0.763-0.957); the average values of sensitivity, specificity, accuracy, and precision were 87.9, 68.2, 80.7, and 82.9%, respectively. CONCLUSIONS: The optimized radiomics model based on ABVS images can provide valuable information for identifying benign and malignant breast lesions preoperatively and guide the accurate clinical treatment. Further external validation is required.

3D Breast Volume Estimation.

INTRODUCTION: Breast volume estimation is considered crucial for breast cancer surgery planning. A single, easy, and reproducible method to estimate breast volume is not available. This study aims to evaluate, in patients proposed for mastectomy, the accuracy of the calculation of breast volume from a low-cost 3D surface scan (Microsoft Kinect) compared to the breast MRI and water displacement technique. MATERIAL AND METHODS: Patients with a Tis/T1-T3 breast cancer proposed for mastectomy between July 2015 and March 2017 were assessed for inclusion in the study. Breast volume calculations were performed using a 3D surface scan and the breast MRI and water displacement technique. Agreement between volumes obtained with both methods was assessed with the Spearman and Pearson correlation coefficients. RESULTS: Eighteen patients with invasive breast cancer were included in the study and submitted to mastectomy. The level of agreement of the 3D breast volume compared to surgical specimens and breast MRI volumes was evaluated. For mastectomy specimen volume, an average (standard deviation) of 0.823 (0.027) and 0.875 (0.026) was obtained for the Pearson and Spearman correlations, respectively. With respect to MRI annotation, we obtained 0.828 (0.038) and 0.715 (0.018). DISCUSSION: Although values obtained by both methodologies still differ, the strong linear correlation coefficient suggests that 3D breast volume measurement using a low-cost surface scan device is feasible and can approximate both the MRI breast volume and mastectomy specimen with sufficient accuracy. CONCLUSION: 3D breast volume measurement using a depth-sensor low-cost surface scan device is feasible and can parallel MRI breast and mastectomy specimen volumes with enough accuracy. Differences between methods need further development to reach clinical applicability. A possible approach could be the fusion of breast MRI and the 3D surface scan to harmonize anatomic limits and improve volume delimitation.

Diagnostic performance of combined use of automated breast volume scanning & hand-held ultrasound for breast lesions.

Background & objectives: Breast cancer being one of the most common malignant tumours among women, diagnostic modalities for early detection of the same become of paramount importance. In this context, the hand-held ultrasound (HHUS) and automated breast volume scanner (ABVS) could provide valuable information for clinicians to diagnose breast diseases. This study aimed to compare and evaluate the diagnostic performance of combined use of HHUS and ABVS for the differentiation of benign and malignant breast lesions. Methods: A total of 361 female patients, who underwent both HHUS and ABVS examinations were included in this study. ABVS and HHUS images were interpreted using the American College of Radiology Breast Imaging-Reporting and Data System (BI-RADS). The distributions of the BI-RADS categories and pathology results were shown as specific numbers. Kappa coefficients test (κ) was calculated to compare the diagnostic results amongst the ABVS, HHUS and ABVS combined with HHUS. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the three diagnostic methods were calculated and their respective diagnostic performance was analyzed by receiver operator characteristic curve. Results: Of a total of 431 lesions, 153 (35.5%) were malignant and 278 (64.5%) were benign. With respect to the pathology results, the value of κ was 0.713 (P<0.001) for HHUS, κ=0.765 (P<0.001) for ABVS and κ=0.815 (P<0.001) for HHUS+ABVS. The sensitivity, specificity, accuracy, PPV and NPV for HHUS combined with ABVS were 96.08 (147/153), 88.49 (246/278), 91.18 (393/431), 82.12 (147/179) and 97.62 per cent (246/252) respectively. For HHUS, these were 90.20 (138/153), 84.17 (234/278), 86.31 (372/431), 75.82 (138/182) and 93.98 per cent (234/249) respectively; and for ABVS these were 92.16 (141/153), 87.05 (242/278), 88.86 (383/431), 79.66 (141/177) and 95.28 per cent (242/254), respectively. There was no significant difference amongst these three methods, but the diagnostic performance of HHUS combined with ABVS was better than, or at least equal to, that of HHUS or ABVS alone. Interpretation & conclusions: The results of this study suggest that ABVS is a promising and advantageous modality for breast cancer detection. Furthermore, the combination of HHUS and ABVS showed a more comparable diagnostic performance than HHUS or ABVS alone for distinguishing between benign and malignant breast lesions.

Breast and tumor volumes on 3D-MRI and their impact on the performance of a breast conservative surgery (BCS).

Breast conservation rate is being increasingly used nowadays as a marker of breast cancer care among hospitals. Searching for the ideal technique to predict the feasibility of BCS is ongoing. For this matter, the preoperative MRIs of 169 patients operated with radical or conservative surgery were reviewed. We estimated the tumor volume (TV) and breast volume (BV) on enhanced 3D-MRI and compared the tumor-to-breast volume ratio (TV/BV) in both groups. The mean ratio was 9.5% in the mastectomy group and 1.7% in the BCS group. A tumor-to-breast volume ratio less than 4% seemed to favor the adoption of a conservative option. Our data suggest that preoperative 3D-MRI can orient the surgical approach by assessing the TV/BV ratio, increasing lumpectomy rates with clear margins and good cosmetic outcome.

Investigation into the Effect of Breast Volume on Irradiation Dose Distribution in Asian Women with Breast Cancer.

Reports on irradiation dose distribution in breast cancer radiotherapy with sufficient sample size are limited in Asian patients. Elucidating dose distribution in Asian patients is particularly important as their breast volume differs compared to patients in Europe and North America. Here, we examined dose distribution in the irradiation field relative to breast volume for three irradiation methods historically used in our facility. We investigated the influence of breast volume on each irradiation method for Asian women. A total of 573 women with early-stage breast cancer were treated with breast-conserving surgery and adjuvant radiotherapy. Three methods were compared: wedge (W), field-in-field (FIF), and wedge-field-in-field (W-FIF). In patients with small breast volume, FIF decreased low- and high-dose areas within the planning target volume, and increased optimal dose area more than W. In patients with medium and large breast volumes, FIF decreased high-dose area more than W. The absolute values of correlation coefficients of breast volume to low-, optimal-, and high-dose areas and mean dose were significantly lower in FIF than in W. The correlation coefficients of V107% were 0.00 and 0.28 for FIF and W, respectively. FIF is an excellent irradiation method that is less affected by breast volume than W in Asian breast cancer patients.

Automated breast volume scanner (ABVS) compared to handheld ultrasound (HHUS) and contrast-enhanced magnetic resonance imaging (CE-MRI) in the early assessment of breast cancer during neoadjuvant chemotherapy: an emerging role to monitoring tumor response?

OBJECTIVES: To investigate the role of automated breast volume scanner (ABVS) compared to handheld ultrasound (HHUS) and contrast-enhanced magnetic resonance imaging (CE-MRI) in the early detection of patients with locally advanced breast cancer who are more likely to reach a complete pathological response (pCR) during neoadjuvant chemotherapy (NAC). METHODS: A single-institution prospective study was performed in patients with histological diagnosis of invasive breast cancer, eligible for NAC, and who were to undergo surgery in our Hospital. Imaging examinations with ABVS, HHUS and CE-MRI were performed at diagnosis (basal time) and after 3 months of chemotherapy (middle time). The tumor size of each lesion was measured at the basal and middle times, and the dimensional variation was reported. Based on this, patients were divided dichotomously by the median value, obtaining "good responders" (goodR) versus "poor responders" (poorR). The results were correlated with the histological assessment (pCR versus No-pCR) with the use of the intergroup comparison of categorical data (Fisher's exact test). RESULT: A total of 21 patients were included; 5 obtained a pCR (23%). Both the ABVS and the CE-MRI found all 5 patients with pCR in the group of goodR (10 patients), while none of the poorR (11 patients) obtained a pCR [correlation was statistically significant (p 0.01)]. In the HHUS, goodR (10 patients) 1 obtained a pCR while in the poorR (11 patients) 4 obtained a pCR [correlation not statistically significant (p 0.31)]. CONCLUSIONS: ABVS could be a useful tool, appearing to be more reliable than HHUS, and as accurate as CE-MRI, in early detection of patients who could reach a pCR after NAC.

The Effect of Arm Position on Breast Volume Measurement Using Three-dimensional Imaging.

BACKGROUND: Three-dimensional (3D) imaging offers an objective and quantitative way to evaluate the breast volume. In this study, we aimed to investigate whether arm position can be a factor influencing the measurement of breast volume and which arm position is more stable when using 3D breast imaging in evaluating the fat volume retention rate in autologous fat grafting for breast augmentation. METHODS: Patients undergoing breast augmentation with autologous fat grafting in our department were selected for the first part of this study. Preoperative 3D breast imaging was performed at three different arm positions: at the sides, akimbo and with hands on the head. Scans on each arm position were repeated on the first day after surgery, taking six scans in total. Breast volume change (BVC) was compared before and after surgery. The patients planning to receive bilateral mammaplasty in our department were selected for the second part of this study. Two repeated 3D scans were performed at the sides, akimbo and hands on the head, and then, the breast volume change error (BVCE) was compared. RESULTS: Twenty-five patients (n = 50 breasts) were included in the first part of study. For the patients who received 100-200 ml fat injection, compared with hands on the head, a statistically significant difference in the average BVC was found at the sides and akimbo (p = 0.02). For the patients receiving more than 200 ml fat injection, there was no statistically significant difference between the groups (p > 0.05). Twenty-six patients (n = 52 breasts) were enrolled in the second part. For the average BVCE, there was no significant difference between the groups (p = 0.11). CONCLUSIONS: The arm position during 3D breast imaging, to some extent, affects the evaluation of BVC after breast augmentation using autologous fat grafting, particularly for patients receiving less fat grafting. The arm position should be kept consistent when using 3D breast imaging in evaluating the fat volume retention rate. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to Table of Contents or the online Instructions to Authors www.springer.com/00266.

Relationship between formulaic breast volume and risk of breast cancer based on linear measurements.

BACKGROUND: Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements, was present by applying propensity score matching (PSM). METHODS: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders. RESULTS: There was a significant difference in breast volume between the two groups before propensity score matching (P = 0.014). Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group(P = 0.009, OR = 1.002, 95%CI:1.000 ~ 1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446). CONCLUSIONS: After PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.

Oncoplastic breast-conserving surgery using chest wall perforator flaps: Three-dimensional quantitative analysis of the percentage of breast volume excised and changes over time in flap volume.

BACKGROUND AND OBJECTIVES: We investigated the effects of oncoplastic breast-conserving surgery (BCS) using chest wall perforator flaps (CWPFs) on the subsequent expected deformity and evaluated the longevity of flap volume. METHODS: We retrospectively reviewed oncological and cosmetic outcomes of 33 women who had undergone the above procedure. We calculated the percentage of breast volume excised (PBVE) from computed tomography volumetry and compared it between a historical BCS alone and the study (flap) group. We also sequentially evaluated flap volumes by magnetic resonance imaging volumetry. RESULTS: Oncoplastic BCS using 25 lateral flaps and eight inferior flaps, depending on the site of the defect, was performed; mean PBVEs were 31.1% and 19.0%, respectively. No local and two distant recurrences occurred in a median follow-up of 61 months. PBVE was 2.6 times larger in the flap than in the BCS alone group. Over half the patients in the BCS alone group had poor cosmetic results when PBVE exceeded 15%, whereas patients in the flap group achieved good cosmetic results with PBVE >25%. In most patients, 80% of flap volume was maintained 5 years after surgery. CONCLUSIONS: CWPF improves cosmetic outcomes in patients with predicted deformity after BCS alone and maintains its volume for at least 5 years.

Prediction of the Ideal Implant Size Using 3-Dimensional Healthy Breast Volume in Unilateral Direct-to-Implant Breast Reconstruction.

Background and objectives: There is no consensus regarding accurate methods for assessing the size of the implant required for achieving symmetry in direct-to-implant (DTI) breast reconstruction. The purpose of this study was to determine whether the ideal implant size could be estimated using 3D breast volume or mastectomy specimen weight, and to compare prediction performances between the two variables. Materials and Methods: Patients who underwent immediate DTI breast reconstruction from August 2017 to April 2020 were included in this study. Breast volumes were measured using 3D surface imaging preoperatively and at postoperative three months. Ideal implant size was calculated by correcting the used implant volume by the observed postoperative asymmetry in 3D surface imaging. Prediction models using mastectomy weight or 3D volume were made to predict the ideal implant volume. The prediction performance was compared between the models. Results: A total of 56 patients were included in the analysis. In correlation analysis, the volume of the implant used was significantly correlated with the mastectomy specimen weight (R2 = 0.810) and the healthy breast volume (R2 = 0.880). The mean ideal implant volume was 278 ± 123 cc. The prediction model was developed using the healthy breast volume: Implant volume (cc) = healthy breast volume × 0.78 + 26 cc (R2 = 0.900). The prediction model for the ideal implant size using the 3D volume showed better prediction performance than that of using the mastectomy specimen weight (R2 = 0.900 vs 0.759, p < 0.001). Conclusions: The 3D volume of the healthy breast is a more reliable predictor than mastectomy specimen weight to estimate the ideal implant size. The estimation formula obtained in this study may assist in the selection of the ideal implant size in unilateral DTI breast reconstruction.

Menstrual Cycle-Related Fluctuations in Breast Volume Measured Using Three-Dimensional Imaging: Implications for Volumetric Evaluation in Breast Augmentation.

BACKGROUND: Breast volume is a key parameter of breast measurement in breast augmentation. However, the correlation between menstrual cycle phases and variation in breast volume has not been well studied. METHODS: Young female patients with regular menstrual cycles underwent eight three-dimensional imaging scans during a single menstrual cycle from November 2017 to January 2018. Breast volumetric difference at each timepoint and basic breast volume were measured for each subject. Preovulatory phase and postovulatory phase values were compared using an unpaired t test. A Pearson's linear correlated analysis was performed to identify the correlation between the basic breast volume and maximum range of breast volumetric difference during the menstrual cycle. RESULTS: Thirteen patients (26 breasts) met the inclusion criteria. During the menstrual cycle, the breast volumetric difference showed first a rising trend followed by a fall. A significant difference in the breast volumetric difference between the preovulatory phase and postovulatory phase (- 19.6 ± 2.1 ml pre-ovulation vs. - 6.9 ± 3.3 ml post-ovulation, p = 0.002) was noted. There was a positive linear association between breast volume and maximum range of breast volumetric difference when a Pearson correlation was used (r = 0.45, p = 0.021). CONCLUSIONS: The breast volume fluctuates during the menstrual cycle, and there is a significant difference between the preovulatory phase and postovulatory phase for breast volumetric change. The influence of the menstrual cycle on breast volume should be taken into consideration by plastic surgeons performing breast augmentation. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The Effect of Respiration on Breast Measurement Using Three-dimensional Breast Imaging.

BACKGROUND: Three-dimensional (3D) imaging offers new opportunities to enable objective and quantitative analysis of the breast. Unlike scanning of rigid objects, respiration may be one of the factors that can influence the measurement of breast when using 3D imaging. In this study, we aimed to investigate how the different respiratory phases affect 3D morphologic and volumetric evaluations of the breast. METHODS: We performed preoperative 3D breast imaging at the end of expiration (EE) and the end of inspiration (EI). We repeated scans on each respiratory phase, taking four scans in total (EE1, EE2 and EI1, EI2). Using Geomagic Studio 12 software, measurements from the different respiratory phases (EE1 and EI1) were compared for differences in the linear distances of breast. Breast volumetric change error (BVCE) was measured between EE1 and EE2 (R1) and between EI1 and EI2 (R2). A multilevel model was used to analyze the difference of linear-distances parameters between EE1 and EI1 and a paired sample t-test was used to analyze the difference between R1 and R2. RESULTS: Our study included 13 Chinese women (26 breasts) with a mean age of 32.6 ± 6.3 years. Compared with EI, EE showed a longer sternal notch to the level of the inframammary fold and shorter nipple to midline (p < 0.05). During EI, breast projection increased by 0.23 cm (95% CI - 0.39, - 0.08) and breast base width increased by 0.27 cm (95% CI - 0.46, - 0.09). The position of the nipple moved by 0.18 cm (95% CI - 0.34, - 0.03) laterally, 0.41 cm (95% CI 0.18, 0.64) cranially, and 0.71 cm (95% CI - 0.92, - 0.51) anteriorly. Although there was no significant difference in BVCE between EE and EI, the result seen with EE appeared to be more consistent. CONCLUSIONS: The results of this study demonstrate that there was no difference in breast volume results when patients are in the expiratory or inspiratory state during 3D breast imaging. This study, however, holds potential benefits to both surgical practice as well as the 3D imaging industry. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Validation of the Vectra XT three-dimensional imaging system for measuring breast volume and symmetry following oncological reconstruction.

PURPOSE: Three-dimensional surface imaging (3D-SI) of the breasts enables the measurement of breast volume and shape symmetry. If these measurements were sufficiently accurate and repeatable, they could be used in planning oncological breast surgery and as an objective measure of aesthetic outcome. The aim of this study was to validate the measurements of breast volume and symmetry provided by the Vectra XT imaging system. METHODS: To validate measurements, breast phantom models of true volume between 100 and 1000 cm3 were constructed and varying amounts removed to mimic breast tissue 'resections'. The volumes of the phantoms were measured using 3D-SI by two observers and compared to a gold standard. For intra-observer repeatability and inter-observer reproducibility in vivo, 16 patients who had undergone oncological breast surgery had breast volume and symmetry measured three times by two observers. RESULTS: A mean relative difference of 2.17 and 2.28% for observer 1 and 2 respectively was seen in the phantom measurements compared to the gold standard (n = 45, Bland Altman agreement). Intra-observer variation over ten repeated measurements demonstrated mean coefficients of variation (CV) of 0.58 and 0.49%, respectively. The inter-observer variation demonstrated a mean relative difference of 0.11% between the two observers. In patients, intra-observer variation over three repeated volume measurements for each observer was 3.9 and 3.8% (mean CV); the mean relative difference between observers was 5.78%. For three repeated shape symmetry measurements using RMS projection difference between the two breasts, the intra-observer variations were 8 and 14% (mean CV), the mean relative difference between observers was 0.43 mm for average symmetry values that ranged from about 3.5 to 15.5 mm. CONCLUSION: This first validation of breast volume and shape symmetry measurements using the Vectra XT 3D-SI system suggests that these measurements have the potential to assist in pre-operative planning and also as a measure of aesthetic outcome.