BACKGROUND: Three-dimensional (3D) digital photography uses integrated image capture technology and rendering software to create 3D models. Volumetric measurements project simulated post-operative images prior to breast augmentation. OBJECTIVES: To evaluate the accuracy and reproducibility of breast volume measurements using the Portrait 3D Surgical Simulation Platform (Axis Three, Boston, Massachusetts). METHODS: Twenty-two patients underwent breast augmentation. 3D volumetric imaging analysis was performed by two independent observers preoperatively and at 6 weeks postoperatively. Simulated volumes were compared to actual implant volume using the Student's t test. Intra-observer reliability was evaluated by measuring internal consistency (Cronbach and 95% confidence interval [CI]) and test-retest reliability (intraclass correlation coefficient [ICC]) from the two observers' calculated volumes. RESULTS: Half (n = 11) of the patients received silicone implants and half saline; all were placed in the submuscular plane through an inframammary incision. No difference in volume estimation in preoperative or postoperative images (P = .49 and P = .14; and P = 1.0 and P = .37, in right and left breasts, respectively) was observed. The test-retest reliability between observers was excellent (ICC, 0.98; P < .001) and Cronbach's value (0.99; 95% CI 0.97-0.99; P < .001) demonstrated an excellent correlation. Regarding accuracy, difference in volume estimation between actual and simulated volumes varied between 0 to 106 mL (0 - 30%), with an absolute mean difference of 12.2% (42.5 mL). CONCLUSIONS: The Portrait 3D breast imaging system provides a highly reproducible 3D tool for measuring breast volume and simulating breast augmentation. Accuracy of the 3D models can vary up to 30% (mean 12.2%). This variability should be accounted for when using this technology to visually communicate with patients.
BACKGROUND: Three-dimensional (3D) digital photography uses integrated image capture technology and rendering software to create 3D models. Volumetric measurements project simulated post-operative images prior to breast augmentation. OBJECTIVES: To evaluate the accuracy and reproducibility of breast volume measurements using the Portrait 3D Surgical Simulation Platform (Axis Three, Boston, Massachusetts). METHODS: Twenty-two patients underwent breast augmentation. 3D volumetric imaging analysis was performed by two independent observers preoperatively and at 6 weeks postoperatively. Simulated volumes were compared to actual implant volume using the Student's t test. Intra-observer reliability was evaluated by measuring internal consistency (Cronbach and 95% confidence interval [CI]) and test-retest reliability (intraclass correlation coefficient [ICC]) from the two observers' calculated volumes. RESULTS: Half (n = 11) of the patients received silicone implants and half saline; all were placed in the submuscular plane through an inframammary incision. No difference in volume estimation in preoperative or postoperative images (P = .49 and P = .14; and P = 1.0 and P = .37, in right and left breasts, respectively) was observed. The test-retest reliability between observers was excellent (ICC, 0.98; P < .001) and Cronbach's value (0.99; 95% CI 0.97-0.99; P < .001) demonstrated an excellent correlation. Regarding accuracy, difference in volume estimation between actual and simulated volumes varied between 0 to 106 mL (0 - 30%), with an absolute mean difference of 12.2% (42.5 mL). CONCLUSIONS: The Portrait 3D breast imaging system provides a highly reproducible 3D tool for measuring breast volume and simulating breast augmentation. Accuracy of the 3D models can vary up to 30% (mean 12.2%). This variability should be accounted for when using this technology to visually communicate with patients.
Authors: Gregory P Reece; Fatima Merchant; Johnny Andon; Hamed Khatam; K Ravi-Chandar; June Weston; Michelle C Fingeret; Chris Lane; Kelly Duncan; Mia K Markey Journal: Med Eng Phys Date: 2015-02-18 Impact factor: 2.242
Authors: Rachel L O'Connell; Komel Khabra; Jeffrey C Bamber; Nandita deSouza; Farid Meybodi; Peter A Barry; Jennifer E Rusby Journal: Breast Cancer Res Treat Date: 2018-06-05 Impact factor: 4.872
Authors: Zhouxiao Li; Thilo Ludwig Schenck; Riccardo Enzo Giunta; Lucas Etzel; Konstantin Christoph Koban Journal: J Clin Med Date: 2022-07-11 Impact factor: 4.964