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1.  Plastic Surgeon Expertise in Predicting Breast Reconstruction Outcomes for Patient Decision Analysis 
Background
Decision analysis offers a framework that may help breast cancer patients make good breast reconstruction decisions. A requirement for this type of analysis is information about the possibility of outcomes occurring in the form of probabilities. The purpose of this study was to determine if plastic surgeons are good sources of probability information, both individually and as a group, when data are limited.
Methods
Seven plastic surgeons were provided with pertinent medical information and preoperative photographs of patients, and were asked to assign probabilities to predict number of revisions, complications, and final aesthetic outcome using a questionnaire designed for the study. Logarithmic strictly proper scoring was used to evaluate the surgeons’ abilities to predict breast reconstruction outcomes. Surgeons’ responses were analyzed for calibration and confidence in their answers.
Results
As individuals, there was variation in surgeons’ ability to predict outcomes. For each prediction category, a different surgeon was more accurate. As a group, surgeons possessed knowledge of future events despite not being well calibrated in their probability assessments. Prediction accuracy for the group was up to six-fold greater than that of the best individual.
Conclusions
The use of individual plastic surgeon-elicited probability information is not encouraged unless the individual’s prediction skill has been evaluated. In the absence of this information, a group consensus on the probability of outcomes is preferred. Without a large evidence base for calculating probabilities, estimates assessed from a group of plastic surgeons may be acceptable for purposes of breast reconstruction decision analysis.
doi:10.1097/GOX.0000000000000010
PMCID: PMC4044723  PMID: 24910814
2.  Assessing Women’s Preferences and Preference Modeling for Breast Reconstruction Decision Making 
Background:
Women considering breast reconstruction must make challenging trade-offs among issues that often conflict. It may be useful to quantify possible outcomes using a single summary measure to aid a breast cancer patient in choosing a form of breast reconstruction.
Methods:
In this study, we used multiattribute utility theory to combine multiple objectives to yield a summary value using 9 different preference models. We elicited the preferences of 36 women, aged 32 or older with no history of breast cancer, for the patient-reported outcome measures of breast satisfaction, psychosocial well-being, chest well-being, abdominal well-being, and sexual well-being as measured by the BREAST-Q in addition to time lost to reconstruction and out-of-pocket cost. Participants ranked hypothetical breast reconstruction outcomes. We examined each multiattribute utility preference model and assessed how often each model agreed with participants’ rankings.
Results:
The median amount of time required to assess preferences was 34 minutes. Agreement among the 9 preference models with the participants ranged from 75.9% to 78.9%. None of the preference models performed significantly worse than the best-performing risk-averse multiplicative model. We hypothesize an average theoretical agreement of 94.6% for this model if participant error is included. There was a statistically significant positive correlation with more unequal distribution of weight given to the 7 attributes.
Conclusions:
We recommend the risk-averse multiplicative model for modeling the preferences of patients considering different forms of breast reconstruction because it agreed most often with the participants in this study.
doi:10.1097/GOX.0000000000000062
PMCID: PMC4120963  PMID: 25105083
3.  Plastic Surgeon Expertise in Predicting Breast Reconstruction Outcomes for Patient Decision Analysis 
Background:
Decision analysis offers a framework that may help breast cancer patients make good breast reconstruction decisions. A requirement for this type of analysis is information about the possibility of outcomes occurring in the form of probabilities. The purpose of this study was to determine if plastic surgeons are good sources of probability information, both individually and as a group, when data are limited.
Methods:
Seven plastic surgeons were provided with pertinent medical information and preoperative photographs of patients and were asked to assign probabilities to predict number of revisions, complications, and final aesthetic outcome using a questionnaire designed for the study. Logarithmic strictly proper scoring was used to evaluate the surgeons’ abilities to predict breast reconstruction outcomes. Surgeons’ responses were analyzed for calibration and confidence in their answers.
Results:
As individuals, there was variation in surgeons’ ability to predict outcomes. For each prediction category, a different surgeon was more accurate. As a group, surgeons possessed knowledge of future events despite not being well calibrated in their probability assessments. Prediction accuracy for the group was up to 6-fold greater than that of the best individual.
Conclusions:
The use of individual plastic surgeon–elicited probability information is not encouraged unless the individual’s prediction skill has been evaluated. In the absence of this information, a group consensus on the probability of outcomes is preferred. Without a large evidence base for calculating probabilities, estimates assessed from a group of plastic surgeons may be acceptable for purposes of breast reconstruction decision analysis.
doi:10.1097/GOX.0000000000000010
PMCID: PMC4044723  PMID: 24910814
4.  Automated Identification of Fiducial Points on 3D Torso Images 
Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D co-ordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship.
doi:10.4137/BECB.S11800
PMCID: PMC4147764  PMID: 25288903
3D surface mesh; breast reconstruction; curvature; breast morphology; landmark detection
5.  3D Symmetry Measure Invariant to Subject Pose During Image Acquisition 
In this study we evaluate the influence of subject pose during image acquisition on quantitative analysis of breast morphology. Three (3D) and two-dimensional (2D) images of the torso of 12 female subjects in two different poses; (1) hands-on-hip (HH) and (2) hands-down (HD) were obtained. In order to quantify the effect of pose, we introduce a new measure; the 3D pBRA (Percentage Breast Retraction Assessment) index, and validate its use against the 2D pBRA index. Our data suggests that the 3D pBRA index is linearly correlated with the 2D counterpart for both of the poses, and is independent of the localization of fiducial points within a tolerance limit of 7 mm. The quantitative assessment of 3D asymmetry was found to be invariant of subject pose. This study further corroborates the advantages of 3D stereophotogrammetry over 2D photography. Problems with pose that are inherent in 2D photographs are avoided and fiducial point identification is made easier by being able to panoramically rotate the 3D surface enabling views from any desired angle.
doi:10.4137/BCBCR.S7140
PMCID: PMC3140267  PMID: 21792310
three-dimensional; stereophotogrammetry; subject pose; validation; breast; symmetry; surgical planning; pBRA
6.  Validation of Stereophotogrammetry of the Human Torso 
The objective of this study was to determine if measurements of breast morphology computed from three-dimensional (3D) stereophotogrammetry are equivalent to traditional anthropometric measurements obtained directly on a subject using a tape measure. 3D torso images of 23 women ranged in age from 36 to 63 who underwent or were scheduled for breast reconstruction surgery were obtained using a 3dMD torso system (3Q Technologies Inc., Atlanta, GA). Two different types (contoured and line-of-sight distances) of a total of nine distances were computed from 3D images of each participant. Each participant was photographed twice, first without fiducial points marked (referred to as unmarked image) and second with fiducial points marked prior to imaging (referred to as marked image). Stereophotogrammetry was compared to traditional direct anthropometry, in which measurements were taken with a tape measure on participants. Three statistical analyses were used to evaluate the agreement between stereophotogrammetry and direct anthropometry. Seven out of nine distances showed excellent agreement between stereophotogrammetry and direct anthropometry (both marked and unmarked images). In addition, stereophotogrammetry from the unmarked image was equivalent to that of the marked image (both line-of-sight and contoured distances). A lower level of agreement was observed for some measures because of difficulty in localizing more vaguely defined fiducial points, such as lowest visible point of breast mound, and inability of the imaging system in capturing areas obscured by the breast, such as the inframammary fold. Stereophotogrammetry from 3D images obtained from the 3dMD torso system is effective for quantifying breast morphology. Tools for surgical planning and evaluation based on stereophotogrammetry have the potential to improve breast surgery outcomes.
doi:10.4137/BCBCR.S6352
PMCID: PMC3076012  PMID: 21494398
three-dimensional; anthropometry; validation; breast; photogrammetry; stereophotogrammetry; surgical planning

Results 1-6 (6)