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Abstract Following the survival benefit demonstrated in the OlympiA trial, one year of adjuvant olaparib is now recommended for all patients with germline BRCA1/2 pathogenic/likely pathogenic variants (PV) and high-risk, HER2-negative early breast cancer after chemotherapy. However, optimal identification of high-risk patients who may derive benefit from this genomically-directed therapy is debated. In this study, we sought to characterize the real-world proportion of gBRCA1/2 PV carriers eligible for adjuvant olaparib according to the OlympiA criteria, and to compare clinicopathologic characteristics and outcomes between eligible and ineligible patients.

Background: Robotic-assisted total joint arthroplasty (rTJA) has growing interest among patients and surgeons. However, patient interest in and perceptions of rTJA have not been well explored. We sought to investigate the influence of patient demographics on interest in rTJA and patient perceptions regarding rTJA. Methods: Patients presenting for their initial adult reconstruction consultation received an optional anonymous survey prior to seeing the provider. Patient sociodemographic parameters were recorded. Additional questions assessed interest in and perceptions surrounding rTJA. Results were analyzed to determine whether patient factors correlated with survey responses. Results: A total of 360 patients participated. Analysis of responses revealed 77.8% of patients were interested in rTJA. Interest level positively correlated with patient age (Rs = 0.139, P = .010), education level (Rs = 0.168, P = .002), household income (Rs = 0.274, P < .001), and White race (F = 4.157, P = .016). At least 100 patients believed rTJA was easier and more accurate, but more expensive and had a significant learning curve for the surgeon. Over 100 patients believed robots were capable of independently performing most or all of the rTJA operation. Conclusions: Patient interest in rTJA varies between patients. Many patients have an incomplete understanding of rTJA, and orthopaedic surgeons should address patient perceptions during surgical consultation. Level of Evidence: IV, Cross-sectional study.

Inquiline ant social parasites exploit other ant species for their reproductive benefit because they do not possess a worker caste. Due to their relative rarity in nature, the biology and natural history of inquilines are largely unknown. Likewise, not much research exists that details the close relationship between inquilines and their host(s), and how each organism influences the genetic structure of the other. Here, we conducted a comparative population genetics study to assess patterns of genetic structure within and among populations of inquiline Solenopsis daguerrei and its known fire ant hosts, which includes invasive Solenopsis invicta. Using nuclear and mitochondrial markers, we show that four genetically distinct groups of S. daguerrei likely exist, each with different degrees of host association. Consistent with previous inferences of the inquiline lifestyle, we find that inbreeding is common in S. daguerrei, presumably a result of intranidal mating and restricted dispersal. Results from this study, specifically host association patterns, may inform future biological control strategies to mitigate invasive S. invicta populations.

There is an expanding body of literature that describes the application of deep learning and other machine learning and artificial intelligence methods with potential relevance to neuroradiology practice. In this article, we performed a literature review to identify recent developments on the topics of artificial intelligence in neuroradiology, with particular emphasis on large datasets and large-scale algorithm assessments, such as those used in imaging AI competition challenges. Numerous applications relevant to ischemic stroke, intracranial hemorrhage, brain tumors, demyelinating disease, and neurodegenerative/neurocognitive disorders were discussed. The potential applications of these methods to spinal fractures, scoliosis grading, head and neck oncology, and vascular imaging were also reviewed. The AI applications examined perform a variety of tasks, including localization, segmentation, longitudinal monitoring, diagnostic classification, and prognostication. While research on this topic is ongoing, several applications have been cleared for clinical use and have the potential to augment the accuracy or efficiency of neuroradiologists.

Artificial intelligence (AI) uses computer algorithms to process and interpret data as well as perform tasks, while continuously redefining itself. Machine learning, a subset of AI, is based on reverse training in which evaluation and extraction of data occur from exposure to labeled examples. AI is capable of using neural networks to extract more complex, high-level data, even from unlabeled data sets, and better emulate, or even exceed, the human brain. Advances in AI have and will continue to revolutionize medicine, especially the field of radiology. Compared to the field of interventional radiology, AI innovations in the field of diagnostic radiology are more widely understood and used, although still with significant potential and growth on the horizon. Additionally, AI is closely related and often incorporated into the technology and programming of augmented reality, virtual reality, and radiogenomic innovations which have the potential to enhance the efficiency and accuracy of radiological diagnoses and treatment planning. There are many barriers that limit the applications of artificial intelligence applications into the clinical practice and dynamic procedures of interventional radiology. Despite these barriers to implementation, artificial intelligence in IR continues to advance and the continued development of machine learning and deep learning places interventional radiology in a unique position for exponential growth. This review describes the current and possible future applications of artificial intelligence, radiogenomics, and augmented and virtual reality in interventional radiology while also describing the challenges and limitations that must be addressed before these applications can be fully implemented into common clinical practice.

Category: Ankle Arthritis; Ankle; Diabetes Introduction/Purpose: Total ankle arthroplasty (TAA) results in improved patient outcomes and preserved range of motion for patients with end-stage arthritis. Wound complications following these procedures, while rare, can have a significant impact on patient morbidity, particularly when they require return to the operating room and flap coverage. We sought to determine the risk factors associated with the need for flap coverage over TAA, and hypothesized that intraoperative variables such as additional procedures to provide angular correction would play a more important role than patient-specific variables. Methods: We performed a single center retrospective review of primary total ankle arthroplasties from April 2007 - February 2019. Patients demographics and medical comorbidities were collected in addition to concomitant procedures performed at the time of TAA such as tibial osteotomies, removal of hardware, and subtalar fusion. Multivariable, main effects logistic regression models were performed to evaluate the impact of specific concomitant procedures during primary TAA on the rate of subsequent flap coverage with adjustment for age, sex, and medical comorbidities. Results: 2,124 TAA resulted in 29 flaps after an average of 1.1 (range 0-5) surgeries and 89.7 (range 18-591) days after the index arthroplasty. The most common flap was a radial forearm free flap performed in 15 (51.7%) patients. Patients requiring flap coverage were significantly older (p=0.044), were more likely to be diabetic (p=0.029), and were more likely to present to the ED and be readmitted within 90-days of their surgery (p

Abstract Background Australia’s energy future is at the crossroads and the role of renewable sources is in focus. Biomass from sustainably managed forests provide a significant opportunity for electricity and heat generation and production of liquid fuels. Australia has extensive native forests of which a significant proportion are on private land. However, there is limited knowledge on the potential capacity of this resource to contribute to the expansion of a biomass for bioenergy industry. In addition, there are concerns on how to reconcile biomass harvesting with environmental protection. Methods We used regional ecosystem vegetation mapping for Queensland to stratify harvestable forests within the 1.8 m hectares of private native forests present in the Southeast Queensland bioregion in 2014. We used a dataset of 52,620 individual tree measurements from 541 forest inventory plots collected over the last 10 years. Tree biomass was estimated using current biomass allometric equations for Australia. Biomass potentially available from selective sawlog harvesting and silvicultural treatment across the bioregion was calculated and mapped. Results Current sawlog harvesting extracts 41.4% of the standing tree biomass and a biomass for bioenergy harvest would retain on average 36% of felled tree biomass on site for the protection of environmental and fauna habitat values. The estimated area extent of harvestable private native forests in the bioregion in 2013 was 888,000 ha and estimated available biomass for bioenergy in living trees was 13.6 million tonnes (t). The spotted gum (Corymbia citriodora subsp. variegata) forests were the most extensive, covering an area of 379,823 ha and with a biomass for bioenergy yield of 14.2 t∙ha−1 (with approximately 11.2 t∙ha−1 of the biomass harvested from silvicultural thinning and 3 t∙ha−1 recovered from sawlog harvest residual). Conclusions Silvicultural treatment of private native forests in the Southeast Queensland bioregion, has the capacity to supply a large quantity of biomass for bioenergy. The availability of a biomass for bioenergy market, and integration of sawlog harvesting and silvicultural treatment operations, could provide land owners with additional commercial incentive to improve the management of private native forests. This could potentially promote restoration of degraded forests, ecological sustainability and continued provision of wood products.

Introduction. Extremity lipomas and well-differentiated liposarcomas (WDLs) are difficult to distinguish on MR imaging. We sought to evaluate the accuracy of MRI interpretation using MDM2 amplification, via fluorescence in-situ hybridization (FISH), as the gold standard for pathologic diagnosis. Furthermore, we aimed to investigate the utility of a diagnostic formula proposed in the literature. Methods. We retrospectively collected 49 patients with lipomas or WDLs utilizing MDM2 for pathologic diagnosis. Four expert readers interpreted each patient’s MRI independently and provided a diagnosis. Additionally, a formula based on imaging characteristics (i.e. tumor depth, diameter, presence of septa, and internal cystic change) was used to predict the pathologic diagnosis. The accuracy and reliability of imaging-based diagnoses were then analyzed in comparison to the MDM2 pathologic diagnoses. Results. The accuracy of MRI readers was 73.5% (95% CI 61–86%) with substantial interobserver agreement (κ=0.7022). The formula had an accuracy of 71%, which was not significantly different from the readers (p=0.71). The formula and expert observers had similar sensitivity (83% versus 83%) and specificity (64.5% versus 67.7%; p=0.659) for detecting WDLs. Conclusion. The accuracy of both our readers and the formula suggests that MRI remains unreliable for distinguishing between lipoma and WDLs.

This paper, based on theories of ecological perception, embodied motivated cognition, and evolutionary psychology, proposes that pictures elicit evolved biologically imperative responses more quickly and thoroughly than do words. These biologically imperative responses are directly responsible for evolved automatic reactions away from biological threats (e.g. escaping predators, avoiding disease and noxious stimuli) and towards opportunities (e.g. consuming food, approaching mates, finding shelter) in the environment. When elicited, these responses take time to occur and may delay or interfere with other types of behavior. Thus, when environmental information is presented in pictures (which should elicit larger biological responses than words) biological responses should interfere more with higher order tasks like information processing and cognitive decision-making. To test this proposition we designed an experiment in which participants performed speeded categorizations of 60 pairs of matched pleasant and unpleasant environmental opportunities and threats. They categorized the items based on their form (is this a word or a picture?) or based on how the picture made them feel (is this pleasant or unpleasant to you?). If pictures do elicit greater biologically imperative responses than their word counterparts, participants should be able to make form decisions faster than feeling decisions, especially when presented with words rather than pictures and especially when the words and pictures have less biological relevance. This main proposition was supported. Implications for this proposition in terms of communication theory are discussed.

Chronic osteomyelitis involving the distal femur often results in amputation or arthrodesis. This article presents three cases of chronic osteomyelitis treated with a staged approach culminating in endoprosthetic reconstruction. Stage one involved resection of infected bone and placement of an intramedullary nail spanning the bony defect between proximal femur and tibia, with antibiotic cement packed around the nail. Patients were then placed on long-term IV +/− oral antibiotics to clear the infection. A “cooldown” period was then used between stages where patients were off antibiotics and inflammatory markers were monitored for signs of remaining infection. Stage two then involved reconstruction of the distal femur and knee with an endoprosthesis. In the appropriate patient, this treatment strategy offers another option in this challenging population.