Concordance and discordance of GeneXpert MTB/RIF and conventional culture method for diagnosis of Extra-Pulmonary Tuberculosis at a tertiary care hospital in Pakistan.

Objective: To identify concordance and discordance between GeneXpert MTB/RIF assay and gold standard bacteriologic culture for the diagnosis of Mycobacterium tuberculosis (MTB) in Extra-Pulmonary tuberculosis (EPTB) specimens in our region. Methods: This is a retrospective cross-sectional study conducted at the Indus Hospital and Health Network. Data from 1st January, 2020 to 31st December, 2021 was analyzed. A total of 1499 EPTB specimens were included for which GeneXpert was requested along with acid-fast bacteria (AFB) culture from the same specimen. Specimens were processed according to specimen type following standard operating procedures of the laboratory. Fluorescent staining was performed on all specimens along with bacteriologic culture. The GeneXpert MTB/RIF assay was carried out in exact accordance with the manufacturer's instructions. Results: Out of 1499 EPTB specimens, 1370 (91.39%) specimens exhibited concordance between GeneXpert and conventional culture method, while 129 (8.60%) specimens showed discordance. GeneXpert exhibited sensitivity and specificity of 69.4% and 94.3% respectively in comparison to culture. Conclusion: GeneXpert sensitivity for the diagnosis of EPTB varied with the site involved. Lower sensitivity was observed in ascitic and pleural fluids as compared to higher sensitivity observed among urine samples and pus aspirates. However, given the quick turnaround time and ease of use, it is a helpful tool in the diagnosis of EPTB when utilized in the appropriate clinical context. Caution is advised while interpreting negative GeneXpert results in endemic settings and should be interpreted along with other supporting clinical and diagnostic features.

Can a Neutrophil-Lymphocyte Ratio Derived from Preoperative Blood Tests Predict Arteriovenous Fistula Maturation?

BACKGROUND: To evaluate the association between inflammatory markers expressed as neutrophil-lymphocyte ratio (NLR) and process of arteriovenous fistula (AVF) maturation. METHODS: A retrospective review of patients with end-stage renal disease referred for formation of a new AVF in one center. Patients referred to the vascular service in the University Hospital of Limerick for creation of vascular access between 2009 and 2013. The association between NLR, calculated from preoperative blood tests, and functional fistula maturation, as determined by successful use of the AVF for 6 consecutive hemodialysis sessions, was investigated using univariate and logistic regression analyses. A logistic regression analysis was carried out to assess potential influence from other factors related to AVF maturation. Stepwise regression test was performed including the NLR. RESULTS: Overall AVF functional maturation rate in our study was 53.7% (66/123). Patients with matured AVFs had an NLR of 4.850 (1.8-15.7) compared with 3.554 (1.7-15.0); this difference was found to be significant (P = 0.024). Female gender (P = 0.008) and a history of kidney transplant (P = 0.004) were the only independent factors of fistula maturation outcome in a logistic regression model. CONCLUSION: Increased level of NLR was found to be associated with fistula maturation; however, more studies are needed to validate this finding.

Extract and Characterize Hairpin Vortices in Turbulent Flows.

Hairpin vortices are one of the most important vortical structures in turbulent flows. Extracting and characterizing hairpin vortices provides useful insight into many behaviors in turbulent flows. However, hairpin vortices have complex configurations and might be entangled with other vortices, making their extraction difficult. In this work, we introduce a framework to extract and separate hairpin vortices in shear driven turbulent flows for their study. Our method first extracts general vortical regions with a region-growing strategy based on certain vortex criteria (e.g., λ2) and then separates those vortices with the help of progressive extraction of ( λ2) iso-surfaces in a top-down fashion. This leads to a hierarchical tree representing the spatial proximity and merging relation of vortices. After separating individual vortices, their shape and orientation information is extracted. Candidate hairpin vortices are identified based on their shape and orientation information as well as their physical characteristics. An interactive visualization system is developed to aid the exploration, classification, and analysis of hairpin vortices based on their geometric and physical attributes. We also present additional use cases of the proposed system for the analysis and study of general vortices in other types of flows.

Determination of Inducible Clindamycin Resistance and Correlation with Vitek2 Inducible Clindamycin Resistance Test in Staphylococcus aureus Isolated from Clinical Samples.

OBJECTIVE: To compare the performance of Vitek2 with the gold standard D test in terms of inducible clindamycin resistance (ICR) detection. STUDY DESIGN: Descriptive study. Place and Duration of the Study: Indus Hospital and Health Network Karachi, Pakistan, from November 2021 to April 2022. METHODOLOGY: Standard operating procedures of the laboratory were followed for processing of clinical samples. Methicillin-resistant Staphylococcus aureus (MRSA) isolates were included. The isolates from the same patient within two-week time period were excluded. Clinical laboratory standards institute guidelines were followed for performing and interpreting D test. The results of the D test were compared with Vitek2 results for ICR. RESULTS: A total of 313 isolates were MRSA, of which 93 isolates tested positive for ICR on both the D test and Vitek2. Nine isolates were positive for ICR on Vitek2 and negative on the Kirby-Bauer disk diffusion method. One isolate tested positive on the disk method and negative on Vitek2. CONCLUSION: Vitek 2 appeared to give false positive results. Reporting false susceptibility of clindamycin can cause therapeutic failure which can markedly affect the patient's outcome. This discordance needs to be investigated further with a large sample size and stringent observation of D-test results to pick laboratory error. KEY WORDS: Methicillin-resistant Staphylococcus aureus, Inducible clindamycin resistance, D zone, Vitek2.

Enhancing heart disease prediction using a self-attention-based transformer model.

Cardiovascular diseases (CVDs) continue to be the leading cause of more than 17 million mortalities worldwide. The early detection of heart failure with high accuracy is crucial for clinical trials and therapy. Patients will be categorized into various types of heart disease based on characteristics like blood pressure, cholesterol levels, heart rate, and other characteristics. With the use of an automatic system, we can provide early diagnoses for those who are prone to heart failure by analyzing their characteristics. In this work, we deploy a novel self-attention-based transformer model, that combines self-attention mechanisms and transformer networks to predict CVD risk. The self-attention layers capture contextual information and generate representations that effectively model complex patterns in the data. Self-attention mechanisms provide interpretability by giving each component of the input sequence a certain amount of attention weight. This includes adjusting the input and output layers, incorporating more layers, and modifying the attention processes to collect relevant information. This also makes it possible for physicians to comprehend which features of the data contributed to the model's predictions. The proposed model is tested on the Cleveland dataset, a benchmark dataset of the University of California Irvine (UCI) machine learning (ML) repository. Comparing the proposed model to several baseline approaches, we achieved the highest accuracy of 96.51%. Furthermore, the outcomes of our experiments demonstrate that the prediction rate of our model is higher than that of other cutting-edge approaches used for heart disease prediction.

Lattice instability and magnetic phase transitions in strongly correlated MnAs.

Using variable temperature x-ray total scattering in magnetic field, we study the interaction between lattice and magnetic degrees of freedom in MnAs, which loses its ferromagnetic order and hexagonal ('H') lattice symmetry at 318 K to recover the latter and become a true paramagnet when the temperature is increased to 400 K. Our results show that the 318 K transition is accompanied by highly anisotropic displacements of Mn atoms that appear as a lattice degree of freedom bridging the 'H' and orthorhombic phases of MnAs. This is a rare example of a lowering of an average crystal symmetry due to an increased displacive disorder emerging on heating. Our results also show that magnetic and lattice degrees of freedom appear coupled but not necessarily equivalent control variables for triggering phase transitions in strongly correlated systems in general and in particular in MnAs.

Bio-inspired based meta-heuristic approach for predicting the strength of fiber-reinforced based strain hardening cementitious composites.

A recently introduced bendable concrete having hundred times greater strain capacity provides promising results in repair of engineering structures, known as strain hardening cementitious composites (SHHCs). The current research creates new empirical prediction models to assess the mechanical properties of strain-hardening cementitious composites (SHCCs) i.e., compressive strength (CS), first crack tensile stress (TS), and first crack flexural stress (FS), using gene expression programming (GEP). Wide-ranging records were considered with twelve variables i.e., cement percentage by weight (C%), fine aggregate percentage by weight (Fagg%), fly-ash percentage by weight (FA%), Water-to-binder ratio (W/B), super-plasticizer percentage by weight (SP%), fiber amount percentage by weight (Fib%), length to diameter ratio (L/D), fiber tensile strength (FTS), fiber elastic modulus (FEM), environment temperature (ET), and curing time (CT). The performance of the models was deduced using correlation coefficient (R) and slope of regression line. The established models were also assessed using relative root mean square error (RRMSE), Mean absolute error (MAE), Root squared error (RSE), root mean square error (RMSE), objective function (OBF), performance index (PI) and Nash-Sutcliffe efficiency (NSE). The resulting mathematical GP-based equations are easy to understand and are consistent disclosing the originality of GEP model with R in the testing phase equals to 0.8623, 0.9269, and 0.8645 for CS, TS and FS respectively. The PI and OBF are both less than 0.2 and are in line with the literature, showing that the models are free from overfitting. Consequently, all proposed models have high generalization with less error measures. The sensitivity analysis showed that C%, Fagg%, and ET are the most significant variables for all three models developed with sensitiveness index higher than 10 %. The result of the research can assist researchers, practitioners, and designers to assess SHCC and will lead to sustainable, faster, and safer construction from environment-friendly waste management point of view.

Cholera Outbreak 2022 in Karachi: A Report on Serotype and Antibiotic Susceptibility Pattern.

OBJECTIVE: To identify the bacterial agent responsible for the surge of cases of acute diarrhoeal disease in Karachi, Pakistan, and assess the antimicrobial susceptibility pattern of the isolates. STUDY DESIGN: Observational study. PLACE AND DURATION OF STUDY: Department of Microbiology, Indus Hospital & Health Network, Karachi, Pakistan, from 1st March to 31st May 2022. METHODOLOGY: Vibrio cholerae (V. Cholerae) isolates from stool samples received in the laboratory in the months of March, April, and May were identified and antibiotic susceptibility testing was performed by the Kirby-Bauer disk diffusion method. Serology was performed to identify the serotype causing a surge in cases of acute watery diarrhoea. RESULTS: A total of three-hundred and seventy-eight stool samples were received during the study period, out of which seventy-eight were positive for V. cholerae serogroup O1 serotype Ogawa. The isolate tested 100% sensitive for Ciprofloxacin, Tetracycline, Doxycycline, and Azithromycin, while 74% resistance was observed in Trimethoprim/Sulfamethoxazole and 25% resistance in Ampicillin. CONCLUSION: V. cholerae serogroup O1 serotype Ogawa was the causative agent responsible for cholera outbreak in Karachi during the early summer of 2022. Ciprofloxacin, Tetracycline, Doxycycline, and Azithromycin are appropriate antimicrobials for treatment; whereas resistance to Trimethoprim/Sulfamethoxazole, and Ampicillin was higher. KEY WORDS: Vibrio cholerae, Outbreak, Acute diarrhoeal disease.

Advanced Machine Learning Modeling Approach for Prediction of Compressive Strength of FRP Confined Concrete Using Multiphysics Genetic Expression Programming.

The purpose of this article is to demonstrate the potential of gene expression programming (GEP) in anticipating the compressive strength of circular CFRP confined concrete columns. A new GEP model has been developed based on a credible and extensive database of 828 data points to date. Numerous analyses were carried out to evaluate and validate the presented model by comparing them with those presented previously by different researchers along with external validation comparison. In comparison to other artificial intelligence (AI) techniques, such as Artificial Neural Networks (ANN) and the adaptive neuro-fuzzy interface system (ANFIS), only GEP has the capability and robustness to provide output in the form of a simple mathematical relationship that is easy to use. The developed GEP model is also compared with linear and nonlinear regression models to evaluate the performance. Afterwards, a detailed parametric and sensitivity analysis confirms the generalized nature of the newly established model. Sensitivity analysis results indicate the performance of the model by evaluating the relative contribution of explanatory variables involved in development. Moreover, the Taylor diagram is also established to visualize how the proposed model outperformed other existing models in terms of accuracy, efficiency, and being closer to the target. Lastly, the criteria of external validation were also fulfilled by the GEP model much better than other conventional models. These findings show that the presented model effectively forecasts the confined strength of circular concrete columns significantly better than the previously established conventional regression-based models.

Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete.

For the production of geopolymer concrete (GPC), fly-ash (FA) like waste material has been effectively utilized by various researchers. In this paper, the soft computing techniques known as gene expression programming (GEP) are executed to deliver an empirical equation to estimate the compressive strength of GPC made by employing FA. To build a model, a consistent, extensive and reliable data base is compiled through a detailed review of the published research. The compiled data set is comprised of 298 experimental results. The utmost dominant parameters are counted as explanatory variables, in other words, the extra water added as percent FA (), the percentage of plasticizer (), the initial curing temperature (), the age of the specimen (), the curing duration (), the fine aggregate to total aggregate ratio (), the percentage of total aggregate by volume (), the percent SiO2 solids to water ratio () in sodium silicate (Na2SiO3) solution, the NaOH solution molarity (), the activator or alkali to FA ratio (), the sodium oxide (Na2O) to water ratio () for preparing Na2SiO3 solution, and the Na2SiO3 to NaOH ratio (). A GEP empirical equation is proposed to estimate the of GPC made with FA. The accuracy, generalization, and prediction capability of the proposed model was evaluated by performing parametric analysis, applying statistical checks, and then compared with non-linear and linear regression equations.

Diagnostic Performance of Ankle-Brachial Pressure Index in Lower Extremity Arterial Disease.

Introduction Ankle-brachial pressure indices (ABIs) continue to form the basis of diagnostics for lower extremity arterial disease (LEAD). However, there remains a paucity of data to support its accuracy. This study aims to evaluate its diagnostic sensitivity and specificity using established arterial-imaging modalities as a benchmark. Methods In this retrospective study, a regional, prospectively maintained, vascular laboratory database was interrogated to identify referred patients with arterial disease who underwent concomitant assessment with ABI and lower limb arterial duplex ultrasound (DUS). Duplex acted as the reference standard. Those who had peripheral computed tomography angiogram (CTA) within 3 months of initial assessment were included in a subgroup analysis to correlate ABI with CTA. The primary end point was the sensitivity and specificity of ABI compared with DUS as the reference standard. Results Concomitant assessment was performed in 438 limbs (250 patients) over a 27-month period. The ABI was normal (0.9 to 1.4) in 196 limbs (44.9%) and abnormal in the remaining 241 limbs (55.1%). False-positive results occurred in 83 out of 241 limbs (34.4%), and false-negative results occurred in 54 limbs out of 196 (27.5%). True-positive results were 158 out of 241 limbs (65.6%), whereas true-negative results were 142 out of 196 limbs (72.4%). ABI using DUS as a benchmark identified a sensitivity for peripheral artery disease of 72.3% and a specificity of 69.3%. Concomitant CTA imaging was available in 200 limbs. The sensitivity and specificity of ABI correlated with CTA were 65.5 and 68.8%, respectively. Conclusion ABIs have a moderate predictive value in the diagnosis of LEAD. Normal range outcomes cannot be taken to infer the absence of LEAD and, as such, further arterial imaging in the form of DUS or angiography should be strongly considered in those with suspected underlying disease requiring intervention. Further noninvasive tests such as exercise studies or pulse volume waveforms should be considered, if diagnostic uncertainty exists, in those requiring nonoperative intervention and risk factor control.

Forecasting Strength of CFRP Confined Concrete Using Multi Expression Programming.

This study provides the application of a machine learning-based algorithm approach names "Multi Expression Programming" (MEP) to forecast the compressive strength of carbon fiber-reinforced polymer (CFRP) confined concrete. The suggested computational Multiphysics model is based on previously reported experimental results. However, critical parameters comprise both the geometrical and mechanical properties, including the height and diameter of the specimen, the modulus of elasticity of CFRP, unconfined strength of concrete, and CFRP overall layer thickness. A detailed statistical analysis is done to evaluate the model performance. Then the validation of the soft computational model is made by drawing a comparison with experimental results and other external validation criteria. Moreover, the results and predictions of the presented soft computing model are verified by incorporating a parametric analysis, and the reliability of the model is compared with available models in the literature by an experimental versus theoretical comparison. Based on the findings, the valuation and performance of the proposed model is assessed with other strength models provided in the literature using the collated database. Thus the proposed model outperformed other existing models in term of accuracy and predictability. Both parametric and statistical analysis demonstrate that the proposed model is well trained to efficiently forecast strength of CFRP wrapped structural members. The presented study will promote its utilization in rehabilitation and retrofitting and contribute towards sustainable construction material.

Predicting the Ultimate Axial Capacity of Uniaxially Loaded CFST Columns Using Multiphysics Artificial Intelligence.

The object of this research is concrete-filled steel tubes (CFST). The article aimed to develop a prediction Multiphysics model for the circular CFST column by using the Artificial Neural Network (ANN), the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Gene Expression Program (GEP). The database for this study contains 1667 datapoints in which 702 are short CFST columns and 965 are long CFST columns. The input parameters are the geometric dimensions of the structural elements of the column and the mechanical properties of materials. The target parameters are the bearing capacity of columns, which determines their life cycle. A Multiphysics model was developed, and various statistical checks were applied using the three artificial intelligence techniques mentioned above. Parametric and sensitivity analyses were also performed on both short and long GEP models. The overall performance of the GEP model was better than the ANN and ANFIS models, and the prediction values of the GEP model were near actual values. The PI of the predicted Nst by GEP, ANN and ANFIS for training are 0.0416, 0.1423, and 0.1016, respectively, and for Nlg these values are 0.1169, 0.2990 and 0.1542, respectively. Corresponding OF values are 0.2300, 0.1200, and 0.090 for Nst, and 0.1000, 0.2700, and 0.1500 for Nlg. The superiority of the GEP method to the other techniques can be seen from the fact that the GEP technique provides suitable connections based on practical experimental work and does not rely on prior solutions. It is concluded that the GEP model can be used to predict the bearing capacity of circular CFST columns to avoid any laborious and time-consuming experimental work. It is also recommended that further research should be performed on the data to develop a prediction equation using other techniques such as Random Forest Regression and Multi Expression Program.

Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches.

To avoid time-consuming, costly, and laborious experimental tests that require skilled personnel, an effort has been made to formulate the depth of wear of fly-ash concrete using a comparative study of machine learning techniques, namely random forest regression (RFR) and gene expression programming (GEP). A widespread database comprising 216 experimental records was constructed from available research. The database includes depth of wear as a response parameter and nine different explanatory variables, i.e., cement content, fly ash, water content, fine and coarse aggregate, plasticizer, air-entraining agent, age of concrete, and time of testing. The performance of the models was judged via statistical metrics. The GEP model gives better performance with R2 and ρ equals 0.9667 and 0.0501 respectively and meet with the external validation criterion suggested in the previous literature. The k-fold cross-validation also verifies the accurateness of the model by evaluating R2, RSE, MAE, and RMSE. The sensitivity analysis of GEP equation indicated that the time of testing is the influential parameter. The results of this research can help the designers, practitioners, and researchers to quickly estimate the depth of wear of fly-ash concrete thus shortening its ecological susceptibilities that push to sustainable and faster construction from the viewpoint of environmentally friendly waste management.

DEep VEin Lesion OPtimisation (DEVELOP) trial: protocol for a randomised, assessor-blinded feasibility trial of iliac vein intervention for venous leg ulcers.

BACKGROUND: Venous leg ulceration is a widespread, debilitating pathology with high recurrence rates. Conservative treatment using graduated compression dressings may be associated with unacceptable ulcer recurrence rates. Early superficial venous ablation encourages ulcer healing and reduces recurrence. However, many of this cohort display concomitant ilio-caval stenosis, which further contributes to lower limb venous hypertension and ulceration. An approach that combines early superficial venous ablation with early treatment of ilio-caval stenotic disease may significantly improve ulcer healing and recurrence rates. We question whether early iliac vein interrogation with intravascular ultrasound (IVUS), stenting of significant occlusive disease plus superficial venous ablation, in patients with active venous leg ulceration, will produce superior ulcer healing to standard therapy. METHODS: This is a prospective, multi-centre, randomised controlled, feasibility trial recruiting patients with lower limb venous ulceration and saphenous venous incompetence. Patients will be randomised to undergo either truncal ablation and compression therapy or truncal ablation, simultaneous iliac interrogation with intravascular ultrasound and stenting of significant (> 50%) iliac vein lesions plus compression therapy. The primary feasibility outcome will be the rate of eligible patient participation while the primary clinical outcomes will be ulcer healing and procedural safety. Secondary outcomes include time to healing, quality of life and clinical scores, ulcer recurrence rates and rates of post-thrombotic syndrome. Follow-up will be over a 5-year period. This feasibility trial is designed to include 60 patients. Should it be practicable a total of 594 patients would be required to adequately power the trial to definitively address ulcer-healing rates. DISCUSSION: This trial will be the first randomised trial to examine the role iliac interrogation and intervention in conjunction with standard operative therapy in the management of venous ulceration related to superficial truncal venous incompetence. ETHICAL COMMITTEE REFERENCE: C.A. 2111 Galway Clinical Research Ethics Committee REGISTRATION: Clinical Trials.gov registration NCT03640689 , Registered on 21 August 2018.

Does longitudinal or transverse orientation of the ultrasound probe improve cannulation success in minimally invasive venous surgery: A multicentre randomised controlled trial.

OBJECTIVE: This study evaluates the effect of transverse and longitudinal ultrasound transducer orientation on saphenous vein cannulation during endovenous ablation. METHODS: A single-blinded, multicentre, randomised controlled trial was performed in patients undergoing ultrasound-guided venous cannulation for saphenous ablation. The primary outcomes were overall cannulation success and time to successful cannulation. RESULTS: In total, 100 patients were assigned to parallel longitudinal orientation and transverse orientation groups. Cannulation success was 100%. There was no significant variation in time to cannulation detected between the transverse orientation and longitudinal orientation (85 s vs. 71 s, p = 0.314). Longitudinal orientation was associated with significantly fewer needle passes [median 3 (interquartile range 1-5) vs. 2 (interquartile range 1-3), p = 0.026] and less pain (median visual analogue scale score 1 vs. 2.5, p = 0.039) than those in the transverse orientation group. CONCLUSION: This trial has shown that while longitudinal orientation is associated with less procedural pain it has no significant effect on time to target vein cannulation during endovenous ablation.

Predictive parameters of arteriovenous fistula functional maturation in a population of patients with end-stage renal disease.

INTRODUCTION: With increasing numbers of patients diagnosed with ESRD, arteriovenous fistula (AVF) maturation has become a major factor in improving both dialysis related outcomes and quality of life of those patients. Compared to other types of access it has been established that a functional AVF access is the least likely to be associated with thrombosis, infection, hospital admissions, secondary interventions to maintain patency and death. AIM: Study of demographic factors implicated in the functional maturation of arteriovenous fistulas. Also, to explore any possible association between preoperative haematological investigations and functional maturation. METHODS: We performed a retrospective chart review of all patients with ESRD who were referred to the vascular service in the University Hospital of Limerick for creation of vascular access for HD. We included patients with primary AVFs; and excluded those who underwent secondary procedures. RESULTS: Overall AVF functional maturation rate in our study was 53.7% (52/97). Female gender showed significant association with nonmaturation (P = 0.004) and was the only predictor for non-maturation in a logistic regression model (P = 0.011). Patients who had history of renal transplant (P = 0.036), had relatively lower haemoglobin levels (P = 0.01) and were on calcium channel blockers (P = 0.001) showed better functional maturation rates. CONCLUSION: Female gender was found to be associated with functional non-maturation, while a history kidney transplant, calcium channel-blocker agents and low haemoglobin levels were all associated with successful functional maturation. In view of the conflicting evidence in the literature, large prospective multi-centre registry-based studies with well-defined outcomes are needed.

A breast surgeon's paranoia pays off: the importance of keen clinical acumen in a case of postradiotherapy breast angiosarcoma.

A 72-year-old woman underwent left wide local excision and an axillary node sampling in 2005 for a T2, N0, M0 invasive ductal carcinoma followed by adjuvant chemotherapy, radiotherapy and hormonal therapy. In 2011, she developed spontaneous blue breast discolouration. Initial examination revealed global breast firmness, skin thickening and ecchymosis. Despite no evidence of recurrent disease, the patient was scheduled for fortnightly review. This review demonstrated marked worsening discolouration and new nipple areolar complex blood-filled blisters. Despite concurrent antiplatelet therapy as a possible cause, the breast clinician's clinical concern of angiosarcoma led to a skin punch biopsy, revealing only non-specific lymphocytic infiltrate. Interval mammographic assessment demonstrated non-specific architectural distortion. Regardless of these benign findings, a breast MRI was performed demonstrating possible breast angiosarcoma. Ultrasound-guided biopsy demonstrated low-grade breast angiosarcoma. The patient underwent completion mastectomy, for a 150 mm high-grade postradiotherapy angiosarcoma. Annual clinical review and contralateral mammography is planned.