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Background: Direct-to-implant (DTI) breast reconstruction restores patient body image immediately after mastectomy but may increase postoperative complications compared to tissue expander (TE)-based breast reconstruction. Few studies have compared the surgical complications and patient-reported outcomes (PROs) of DTI and TE breast reconstructions in Asian women., Method: This study compared postoperative complications and PROs between DTI and TE breast reconstruction in Chinese women and explores the risk factors of postoperative complications and the influencing factors of PROs. A retrospective chart review of patients undergoing immediate breast reconstruction between 2008 and 2022 was conducted, and BREAST-Q questionnaires of the breast reconstruction module were distributed to eligible patients. Multivariate regression models were used to explore risk factors for postoperative complications and factors that influence BREAST-Q scores., Results: DTI was associated with lower rates of major complications and implant loss but had no significant influence on patient satisfaction or quality of life. Age and axillary lymph node dissection were important complication risk factors for both DTI and TE. The application of acellular dermal matrix significantly increased the risk of seroma or hematoma. In the DTI group, capsular contracture significantly reduced patient satisfaction with breast scores., Conclusion: DTI dual-plane breast reconstruction does not increase complication rates in appropriately selected Chinese patients. In DTI patients, the management of capsular contracture is crucial for improving patient satisfaction., (Copyright © 2024. Published by Elsevier Ltd.)

Rationale: Complications associated with breast implants pose a significant obstacle to improving the quality of life for patients undergoing implant-based breast reconstruction. Due to the intricate nature of their presentation, diagnosis often becomes challenging and perplexing. Herein, we present a case report detailing the diagnostic and therapeutic processes employed in managing implant-related complications in a patient with multiple malignancies who underwent immediate breast reconstruction following mastectomy., Patent Concerns: The patient, a 48-year-old woman, presented with severe pain and hardening in her left breast. She had previously undergone nipple-sparing mastectomy followed by immediate implant-based breast reconstruction 3 years ago., Diagnoses: Upon admission, we suspected a simple diagnosis of capsular contracture. However, upon investigation, she had a medical history of colon cancer, breast cancer, and acute B-lymphoblastic leukemia. Furthermore, she recently experienced nipple hemorrhage., Interventions: Considering her clinical manifestations, we postulated the possibility of tumor recurrence along with potential presence of breast implant-associated anaplastic large cell lymphoma. The situation took a new turn, as diagnostic imaging techniques including breast MRI, and ultrasound revealed indications of potential prosthesis rupture and periprosthetic infection., Outcomes: Ultimately, en bloc capsulectomy with implant removal was performed, revealing no evidence of implant rupture or infection but rather indicating delayed hematoma formation., Lessons: An accurate diagnosis of complications associated with breast prosthesis reconstruction is crucial for effective treatment. The examination and treatment processes employed in this case offer valuable insights toward achieving a more precise diagnosis of prosthesis-related complications, particularly in patients with complex medical histories., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Facial anthropometry based on 3-dimensional (3D) imaging technology, or 3D photogrammetry, has gained increasing popularity among surgeons. It outperforms direct measurement and 2-dimensional (2D) photogrammetry because of many advantages. However, a main limitation of 3D photogrammetry is the time-consuming process of manual landmark localization. To address this problem, this study developed a U-NET-based deep learning algorithm to enable automated and accurate anatomical landmark detection on 3D facial models., Methods: The main structure of the algorithm stacked 2 U-NETs. In each U-NET block, we used 3×3 convolution kernel and rectified linear unit (ReLU) as activation function. A total of 200 3D images of healthy cases, acromegaly patients, and localized scleroderma patients were captured by Vectra H1 handheld 3D camera and input for algorithm training. The algorithm was tested to detect 20 landmarks on 3D images. Percentage of correct key points (PCK) and normalized mean error (NME) were used to evaluate facial landmark detection accuracy., Results: Among healthy cases, the average NME was 1.4 mm. The PCK reached 90% when the threshold was set to the clinically acceptable limit of 2 mm. The average NME was 2.8 and 2.2 mm among acromegaly patients and localized scleroderma patients, respectively., Conclusions: This study developed a deep learning algorithm for automated facial landmark detection on 3D images. The algorithm was innovatively validated in 3 different groups of participants. It achieved accurate landmark detection and improved the efficiency of 3D image analysis., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-1108/coif). Y.A. and Q.H. report that they were full-time employees of Beijing Li-Med Medical Technology Co., Ltd. during the conduct of the study. The other authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)