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Artificial intelligence (AI) focuses on processing and interpreting complex information as well as identifying relationships and patterns among complex data. Artificial intelligence- and machine learning (ML)-driven predictions have shown promising potential in influencing real-time decisions and improving surgical outcomes by facilitating screening, diagnosis, risk assessment, preoperative planning, and shared decision-making. Fundamental understanding of the algorithms, as well as their development and interpretation, is essential for the evolution of AI in surgery. In this article, we provide surgeons with a fundamental understanding of AI-driven predictive models through an overview of common ML and deep learning algorithms, model development, performance metrics and interpretation. This would serve as a basis for understanding ML-based research, while fostering new ideas and innovations for furthering the reach of this emerging discipline.

To determine if global budget revenue (GBR) models incent the centralization of complex surgical care.In 2014, Maryland initiated a statewide GBR model. While prior research has shown improvements in cost and outcomes for surgical care post-GBR implementation, the mechanism remains unclear.Utilizing state inpatient databases, we compared the proportion of adults undergoing elective complex surgeries (gastrectomy, pneumonectomy/lobectomy, proctectomies, and hip/knee revision) at high concentration hospitals (HCHs) in Maryland and control states. Annual concentration, per procedure, was defined as hospital volume divided by state volume. HCHs were defined as hospitals with a concentration at least at the 75th percentile in 2010. We estimated the difference-in-differences (DiD) of the probability of patients undergoing surgery at HCHs before and after GBR implementation.Our sample included 122,882 surgeries. Following GBR implementation, all procedures were increasingly performed at HCHs in Maryland. States satisfied the parallel trends assumption for the centralization of gastrectomy and pneumonectomy/lobectomy. Post-GBR, patients were more likely to undergo gastrectomy (DiD: 5.5 p.p., 95% CI [2.2, 8.8]) and pneumonectomy/lobectomy (DiD: 12.4 p.p., 95% CI [10.0, 14.8]) at an HCH in Maryland compared to control states. For our hip/knee revision analyses, we assumed persistent counterfactuals and noted a positive DiD post-GBR implementation (DiD: 4.8 p.p., 95% CI [1.3, 8.2]). No conclusion could be drawn for proctectomy due to different pre-GBR trends.GBR implementation is associated with increased centralization for certain complex surgeries. Future research is needed to explore the impact of centralization on patient experience and access.

Autologous fat grafting is a useful tool in breast reconstruction. The authors have previously demonstrated a difference in the rate of processing adipose grafts in a randomized time and motion clinical trial. The purpose of this study was to compare clinical outcomes in commonly used grafting systems.Three methods to prepare adipose grafts were compared: a passive washing filtration system (Puregraft system), an active washing filtration system (Revolve system), and centrifugation (Coleman technique). Postoperative complications, rates of fat necrosis, revision procedures, and additional imaging were recorded.Forty-six patients were included in the prospective, randomized study (15 active filtration, 15 passive filtration, and 16 centrifugation). Their mean age was 54 years and mean body mass index was 28.6 kg/m 2 . The mean length of follow-up was 16.9 ± 4 months. The overall complication rate was 12.1 percent. The probability of fat necrosis was no different between the groups (active filtration, 15 percent versus passive filtration, 14.3 percent] versus centrifugation, 8 percent; p = 0.72). Fat necrosis was highest in patients with breast conservation before grafting (60 percent; p = 0.011). There was no significant difference in contour irregularity (active filtration, 40 percent versus passive filtration, 38 percent versus centrifugation, 36 percent; p = 0.96) or additional grafting (active filtration, 40 percent versus passive filtration, 24 percent versus centrifugation, 32 percent; p = 0.34).This is the first prospective, randomized study to compare clinical outcomes of adipose graft preparation. There was no significant difference in early complications, fat necrosis, or rates of additional grafting among the study groups. There was significantly higher risk of fat necrosis in patients with previous breast conservation treatment regardless of processing technique.Therapeutic, II.

The technology of artificial intelligence (AI) has made significant in-roads into the field of medicine over the last decade. With surgery being a discipline where repetition is the key to mastery, the scope of AI presents enormous potential for resident education through the analysis of technique and delivery of structured feedback for performance improvement. In an era marred by a raging pandemic that has decreased exposure and opportunity, AI offers an attractive solution towards improving operating room efficiency, safe patient care in the hands of supervised residents and can ultimately culminate in reduced health care costs. Through this article, we elucidate the current adoption of the artificial intelligence technology and its prospects for advancing surgical education.

Deep learning (DL) is a subset of machine learning that is rapidly gaining traction in surgical fields. Its tremendous capacity for powerful data-driven problem-solving has generated computational breakthroughs in many realms, with the fields of medicine and surgery becoming increasingly prominent avenues. Through its multi-layer architecture of interconnected neural networks, DL enables feature extraction and pattern recognition of highly complex and large-volume data. Across various surgical specialties, DL is being applied to optimize both preoperative planning and intraoperative performance in new and innovative ways. Surgeons are now able to integrate deep learning tools into their practice to improve patient safety and outcomes. Through this review, we explore the applications of deep learning in surgery and related subspecialties with an aim to shed light on the practical utilization of this technology in the present and near future.

Predatory journals have exploited the open access publishing model and are considered as a major threat to the integrity of scientific research. The goal of this study was to characterize predatory publishing practices in plastic surgery.To identify potentially predatory journals in the field of plastic surgery, the authors searched the Cabells' Predatory Reports and Beall's List using preidentified keywords. For presumed legitimate open access journals, the Directory of Open Access Journals (DOAJ) was queried. The characteristics of potentially predatory journals were compared to those of legitimate open access plastic surgery journals.The authors identified a total of 25 plastic surgery-focused journals. Out of the 25 potentially predatory journals, only 15 journals had articles published within the last 5 years, with a mean number of articles of 33 ± 39 (range, 2 to 159 articles). The mean number of predatory violations according to Cabells' criteria was 6.8 ± 1.4 (range, 3 to 9). Using the DOAJ database, the authors identified a total of 24 plastic surgery-related journals. Compared to potentially predatory journals, journals from the DOAJ were more likely to be indexed in PubMed (0 versus 50 percent, respectively, p0.0001). Time to publication was significantly higher in journals from the DOAJ (17 ± 7 versus 4 ± 1 weeks; p = 0.006). Despite higher article processing charges in the DOAJ group, this difference was not statically significant ($1425 ± $717 versus $1071 ± $1060; p = 0.13).Predatory journals are pervasive in the medical literature and plastic surgery is no exception. Plastic surgeons should practice due diligence when choosing a target journal for their articles. Journals with predatory practices should be distinguished from legitimate open access publication platforms.

Implant-based breast reconstruction infections often require implant explantation. Whereas some plastic surgeons pursue autologous reconstruction following the first implant-based breast reconstruction failure caused by infection, others argue that a second attempt is acceptable.The authors conducted a retrospective study of patients who underwent a second reconstruction attempt with implant-based or free flap breast reconstruction following explantation because of infection between 2006 and 2019. Surgical and patient-reported outcomes were compared between the two groups.A total of 6093 implant-based breast reconstructions were performed during the study period, of which 130 breasts met our inclusion criteria [implant-based, n = 86 (66 percent); free flap, n = 44 (34 percent)]. No significant differences in rates of overall (25 percent versus 36 percent; p = 0.2) or major (20 percent versus 21 percent; p = 0.95) complications were identified between the free flap and implant-based cohorts, respectively. Implant-based breast reconstruction patients were more likely to experience a second infection (27 percent versus 2 percent; p = 0.0007) and reconstruction failure (21 percent versus 5 percent; p = 0.019). Among irradiated patients, reconstruction failure was reported in 44 percent of the implant-based and 7 percent of the free flap cohorts (p = 0.02). Free flap patients reported significantly higher scores for Satisfaction with Breasts (73.7 ± 20.1 versus 48.5 ± 27.9; p = 0.0046).Following implant-based breast reconstruction explantation because of infection, implant-based and free flap breast reconstruction had similar rates of overall and major complications; however, implant-based breast reconstruction had considerably higher rates of infection and reconstructive failures and lower patient-reported scores for Satisfaction with Breasts. Given the high rates of implant-based breast reconstruction failure in patients with prior radiotherapy and infection-based failure, plastic surgeons should strongly consider autologous reconstruction in this patient population.Therapeutic, III.

PURPOSE Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but identification of need is difficult. We sought to develop and test a tool to accurately predict an individual's risk of financial toxicity based on clinical, demographic, and patient-reported data prior to initiation of breast cancer treatment. PATIENTS AND METHODS We surveyed 611 patients undergoing breast cancer therapy at MD Anderson Cancer Center. We collected data using the validated COmprehensive Score for financial Toxicity (COST) patient-reported outcome measure alongside other financial indicators (credit score, income, and insurance status). We also collected clinical and perioperative data. We trained and tested an ensemble of machine learning (ML) algorithms (neural network, regularized linear model, support vector machines, and a classification tree) to predict financial toxicity. Data were randomly partitioned into training and test samples (2:1 ratio). Predictive performance was assessed using area-under-the-receiver-operating-characteristics-curve (AUROC), accuracy, sensitivity, and specificity. RESULTS In our test sample (N = 203), 48 of 203 women (23.6%) reported significant financial burden. The algorithm ensemble performed well to predict financial burden with an AUROC of 0.85, accuracy of 0.82, sensitivity of 0.85, and specificity of 0.81. Key clinical predictors of financial burden from the linear model were neoadjuvant therapy (βregularized, .11) and autologous, rather than implant-based, reconstruction (βregularized, .06). Notably, radiation and clinical tumor stage had no effect on financial burden. CONCLUSION ML models accurately predicted financial toxicity related to breast cancer treatment. These predictions may inform decision making and care planning to avoid financial distress during cancer treatment or enable targeted financial support. Further research is warranted to validate this tool and assess applicability for other types of cancer.

Background Patients with contaminated/dirty-infected defects are at high risk for postoperative complications after abdominal wall reconstruction (AWR). We evaluated outcomes of AWR using acellular dermal matrix (ADM) for mesh reinforcement and identified predictors of hernia recurrence (HR), surgical site occurrences (SSOs), and surgical site infections (SSIs). Study Design We conducted a retrospective cohort study of patients who underwent AWR using ADM, from March 2005 to June 2019. Outcomes were compared between Centers for Disease Control and Prevention (CDC) wound classifications. The primary outcome measure was HR. Secondary outcomes were SSOs and SSIs. Results We identified 725 AWRs using ADM that met the study criteria. Participants had a mean age of 60 ± 11.5 years, mean BMI of 31 ± 7 kg/m2, and mean follow-up time of 42 ± 29 months. Three hundred two patients (41.6%) had clean defects, 322 patients (44.4%) had clean-contaminated defects, and 101 patients (13.9%) had contaminated/dirty-infected defects. Patients with contaminated/dirty-infected defects had an HR rate of 20.8%, SSO rate of 54.5%, and SSI rate of 23.8%. Multivariate logistic regression found that contaminated/dirty-infected defects were independent predictors of SSOs (OR 2.99; 95% CI 1.72–5.18; p Conclusions SSIs and SSOs increase as contamination levels rise, but the risk of HR does not. AWR with ADM provides safe and durable outcomes, even with increasing levels of contamination.

Prepectoral implant-based breast reconstruction (IBR) has recently become the standard of care for many reconstructive surgeons and is often supplemented with coverage using acellular dermal matrix(ADM). However, more clinical data examining the use of ADM in breast reconstruction are needed. The present study compares complications and patient-reported outcomes(PROs) between three different types of ADM used in IBR.We performed a retrospective review of consecutive patients who underwent immediate prepectoral IBR from January 2018 through December 2019. Surgical outcomes and PROs (using the BREAST-Q) were compared between the Alloderm, Surgimend, and Dermacell ADMs.Overall, 557 breasts (383 patients) were included (78.6% Alloderm, 14% Surgimend, and 7.4% Dermacell). Patients in the Dermacell group were older (p=0.001) and more likely to have diabetes mellitus (p=0.001) compared to Alloderm and Surgimend patients. Other patient characteristics were similar between the three groups. The overall complication rate was equivalent between the three ADM groups (Alloderm 27% vs. Surgimend 33% vs. Dermacell 39%; p=0.209). Multivariable frailty models demonstrated that the type of ADM was not significantly associated with overall complications, infection, major complications, or device explantation. BREAST-Q satisfaction with the breast, psychosocial well-being, and sexual well-being were also similar between the three ADM groups (p=0.109, p=0.439, p=0.152, respectively).We found that three of the most commonly used ADMs in the United States have similar surgical outcomes and PROs when used for prepectoral IBR. No significant differences in infection, overall complication, and device removal rates were identified between Alloderm, Surgimend, and Dermacell.

Post-mastectomy breast reconstruction in patients with a history of breast-conserving surgery (BCS) and radiotherapy is challenging with a paucity of literature on the outcomes of different breast reconstructive techniques. We hypothesized that implant-based breast reconstruction (IBR) would be associated with higher complication rates compared to either IBR combined with latissimus dorsi (LD) or free flap breast reconstruction (FFBR).We conducted a retrospective review of patients who underwent mastectomy with a prior history of BCS and radiotherapy between January 2000 and March 2016. Surgical and patient-reported outcomes (BREAST-Q) were compared between IBR vs. IBR/LD vs. FFBR.We identified 9473 patients who underwent BCS and radiotherapy. Ninety-nine patients (105 reconstructions) met our inclusion criteria, 29% (n=30) of whom received IBR, 26% (n=27) IBR/LD, and 46% (n=48) received FFBR. Overall complication rate was not significantly different among the three groups (50% in IBR vs. 41% in IBR/LD vs. 44% in FFBR, p=0.77) while reconstruction failures were significantly lower in the FFBR group (33% in IBR vs. 19% in IBR/LD vs. 0% in FFBR, p0.0001). The time between the receipt of radiotherapy and reconstruction was not a significant predictor of overall complications and reconstruction failure. No significant differences were identified between the three study cohorts in any of the three studied BREAST-Q domains.In patients with prior BCS and radiotherapy, FFBR was associated with lower probability of reconstruction failure compared to IBR but no significant difference in overall and major complication rates. The addition of LD flap to IBR did not translate into lower complication rates but may result in decreased reconstruction failures.

A growing body of evidence supports the efficacy of surgical treatments for lymphedema. This study reports the outcomes of vascularized lymph node transplantation (VLNT) for the treatment of patients with lymphedema compared with maximal conservative treatment alone.Consecutive patients undergoing VLNT to treat primary and secondary lymphedema affecting the upper or lower extremities were included. All patients were optimized preoperatively with conservative therapy. Demographic and treatment information was collected, and outcomes data were electronically captured prospectively; descriptive statistics were performed.There were 134 patients included that had achieved maximal reductions by conservative therapy preoperatively. This series included jejunal mesenteric (n = 25), groin (n = 43), lateral thoracic (n = 31), omental or right gastroepiploic (n = 21), and submental (n = 14) VLN flaps. At 24 months postoperatively, there were significant reductions in limb volume change (mean [SD] 45.7% [8.7%]; p = 0.002) LDex score (mean [SD] 59.8% [8.7%]; p0.001), Lymphedema Life Impact Scale score (mean [SD] 61.6% [5.9]; p0.001), and cellulitis episodes (97.9%; p0.001). At 3 and 6 months postoperatively, limb volume change was significantly greater for the upper than the lower extremity, otherwise outcomes were similar. There were no flap losses and overall outcomes were similar between the different VLN flap types.Treatment of lymphedema using VLNT resulted in progressive, significant reductions in limb volume, bioimpedance spectroscopy measurements of extracellular fluid, and episodes of cellulitis, with improved patient-reported outcomes and limb function measures compared with maximal conservative therapy alone. The complication rate was low and there were no significant outcomes differences between the VLNT types.

Autologous fat grafting (AFG) serves as an effective method to address volume defects, contour irregularities, and asymmetry in both aesthetic and reconstructive procedures. In recent years, there has been growing concern about the potential of cancer recurrence and interference with cancer surveillance in oncologic patients receiving AFG. The adipose tissue contains adipose-derived stem cells (ASCs), a specific type of mesenchymal stem cells, that facilitate secretion of numerous growth factors which in turn stimulate tissue regeneration and angiogenesis. As such, it has been theorized that ASCs may also have the potential to stimulate cancer cell proliferation and growth when used in oncologic patients. Multiple research studies have demonstrated the ability of ACSs to facilitate tumor proliferation in animal models. However, clinical research in oncologic patients has yielded contradictory findings. Although the literature pertaining to oncologic safety in head and neck, as well as sarcoma, cancer patients remains limited, studies demonstrate no increased risk of tumor recurrence in these patient populations receiving AFG. Similarly, both the efficacy and safety of AFG have been well established in breast cancer patients through numerous clinical studies. More recently, preclinical research in animal models has shown that AFG has the potential to facilitate tissue regeneration and improve joint contracture following irradiation. Ultimately, further research is needed to elucidate the safety of AFG in a variety of oncologic patients, as well as explore its use in tissue regeneration, particularly in the setting of radiotherapy. Level of Evidence: 4

SUMMARY Proper management of symptomatic textured implant patients is critical to identify and treat associated oncologic disease. Textured surface breast implants were first introduced more than 50 years ago in an effort to decrease high rates of capsular contracture and implant malposition observed with first-generation smooth surface breast implants. Textured implants were dominant over smooth devices in the United States in the late 1990s, but they fell out of favor for newer-generation smooth implants, while texture remained the dominant selling implants worldwide until recently. A class I device recall by the US Food and Drug Administration in 2019 precipitated a removal of the highest selling implant worldwide, Allergan Biocell, due to a disproportionately increased risk of breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). Operative strategies, such as bacterial control at the time of textured implant insertion, have not been credibly shown to affect or prevent the future development of BIA-ALCL. BIA-ALCL patients require complete surgical excision of their disease, whereas textured implant patients who are otherwise asymptomatic do not require surgical removal. For suspicious cases, diagnostic testing with CD30 immunohistochemistry should be performed before any surgical intervention. Capsules are evaluated with 12 strategic regional biopsies in a standardized approach. If surgeons are revising or exchanging textured implants, they may reasonably consider a total capsulectomy, though this is not advocated by the Food and Drug Administration or national societies, and has not been shown to mitigate future risk of BIA-ALCL. The purpose of this article is to review data on and outcomes for textured surface implants, disease-associated risk, and the management strategy for revisionary surgery and device surveillance.

Background High treatment costs associated with breast cancer are a substantial burden to patients and society. Despite mounting awareness, patient perspectives about the value of cost discussions in breast reconstruction and risk factors for financial distress are unknown. Methods The authors performed a single-institution, cross-sectional survey of all women who underwent breast reconstruction following mastectomy or lumpectomy for breast cancer or risk reduction. Questions were derived from previously published survey items, and the authors leveraged regression analysis to identify patient-level risk factors for major financial distress. Results A total of 647 of 2293 patients returned the survey questionnaires (28.2 percent response rate). From the 647 respondents, 399 (62 percent) underwent breast reconstruction, and of these, 140 (35 percent) reported that total treatment expenses were higher than expected. One hundred twenty-nine breast reconstruction patients (32 percent) paid over $5000 in out-of-pocket costs. Two hundred eighty-four (71 percent) felt that surgeons should explain the estimated out-of-pocket costs when choosing a type of breast reconstruction and 205 (51 percent) believed that a financial consultation should be scheduled with every new cancer diagnosis. However, only 52 patients (13 percent) reported having had cost discussions with the treatment team. The incidence of major financial distress was n = 70 (18 percent), and following regression analysis, higher credit score and annual income were associated with a 66 percent and 69 percent risk reduction, respectively. Conclusions Recipients of breast reconstruction demonstrate unanticipated and unplanned financial strain related to out-of-pocket expenses and believe that cost-consciousness should impact treatment decisions. Lower income and credit score are associated with financial distress. Cost discussions may optimize decision-making in preference sensitive conditions.