Honey bees infer source location from the dances of returning foragers.

Honeybees (Apis mellifera carnica) communicate the direction and distance to a food source by means of a waggle dance. We ask whether bees recruited by the dance use it only as a flying instruction, with the technical form of a polar vector, or also translate it into a location vector that enables them to set courses directed toward the food source from arbitrary locations within their familiar territory. The flights of recruits captured on exiting the hive and released at distant sites were tracked by radar. The recruits performed first a straight flight in approximately the compass direction indicated by the dance. However, this "vector" portion of their flights and the ensuing tortuous "search" portion were strongly and differentially affected by the release site. Searches were biased toward the true location of the food and away from the location specified by translating the origin for the danced polar vector to the release site. We conclude that by following the dance recruits get two messages, a polar flying instruction (bearing and range from the hive) and a location vector that enables them to approach the source from anywhere in their familiar territory. The dance communication is much richer than thought so far.

Association of stress hyperglycemia ratio with in-hospital new-onset atrial fibrillation and long-term outcomes in patients with acute myocardial infarction.

AIMS: To investigate the predictive value and prognostic impact of stress hyperglycemia ratio (SHR) for new-onset atrial fibrillation (NOAF) complicating acute myocardial infarction (AMI). MATERIALS AND METHODS: This retrospective study included 2145 AMI patients without AF history between February 2014 and March 2018. SHR was calculated using fasting blood glucose (mmol/L)/[1.59*HbA1c (%)-2.59]. The association between SHR and post-MI NOAF was assessed with multivariable logistic regression analyses. The primary outcome was a composite of cardiac death, heart failure hospitalisation, recurrent MI, and ischaemic stroke (MACE). Cox regression-adjusted hazard ratios with 95% confidence intervals (CI) were estimated for MACE. RESULTS: A total of 245 (11.4%) patients developed NOAF. In the multivariable logistic regression analyses, SHR (each 10% increase) was significantly associated with increased risks of NOAF in the whole population (OR: 1.05, 95% CI: 1.01-1.10), particularly in non-diabetic individuals (OR:1.08, 95% CI: 1.01-1.17). During a median follow-up of 2.7 years, 370 (18.5%) MACEs were recorded. The optimal cut-off value of SHR for MACE prediction was 1.119. Patients with both high SHR (≥1.119) and NOAF possessed the highest risk of MACE compared to those with neither high SHR nor NOAF after multivariable adjustment (HR: 2.18, 95% CI: 1.39-3.42), especially for diabetics (HR: 2.63, 95% CI: 1.41-4.91). Similar findings were observed using competing-risk models. CONCLUSIONS: SHR is an independent predictor of post-MI NOAF in non-diabetic individuals. Diabetic patients with both high SHR and NOAF had the highest risk of MACE, suggesting that therapies targeting SHR may be considered in these patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03533543.

Movement during the acquisition of a visual landmark may be necessary for rapid learning in ants.

We conducted laboratory experiments using Japanese carpenter ants (Camponotus japonicus) to investigate whether movement during visual learning can influence the learning performance of ant foragers. We performed three different experiments. In the first experiment, the ants could move freely in a straight maze during the visual learning. The ants in the experiments two and three were fixed to a certain position during the visual learning training. A distinct difference between these two experiments was that the ants in one experiment could perceive an approaching visual stimulus during the training, although they were fixed. After training phases, a Y-maze test was performed. One arm of the Y-maze had a visual stimulus presented to the ants during the training. We found that the ants in the first experiment showed rapid learning and correctly selected the landmark arm. However, the ants in the experiments two and three did not exhibit any preference for the chosen arm. Interestingly, we found differences in the time spent around a certain location in the Y-maze between the experiments two and three. These results suggest that movement during visual learning may influence the rapid learning of ant foragers.

Enhancing long-term survival prediction with two short-term events: Landmarking with a flexible varying coefficient model.

Patients with cardiovascular diseases who experience disease-related short-term events, such as hospitalizations, often exhibit diverse long-term survival outcomes compared to others. In this study, we aim to improve the prediction of long-term survival probability by incorporating two short-term events using a flexible varying coefficient landmark model. Our objective is to predict the long-term survival among patients who survived up to a pre-specified landmark time since the initial admission. Inverse probability weighting estimation equations are formed based on the information of the short-term outcomes before the landmark time. The kernel smoothing method with the use of cross-validation for bandwidth selection is employed to estimate the time-varying coefficients. The predictive performance of the proposed model is evaluated and compared using predictive measures: area under the receiver operating characteristic curve and Brier score. Simulation studies confirm that parameters under the landmark models can be estimated accurately and the predictive performance of the proposed method consistently outperforms existing methods that either do not incorporate or only partially incorporate information from two short-term events. We demonstrate the practical application of our model using a community-based cohort from the Atherosclerosis Risk in Communities (ARIC) study.

Long-term reliability of the phospholamban (PLN) p.(Arg14del) risk model in predicting major ventricular arrhythmia: a landmark study.

AIMS: Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive. Our aim is to evaluate the diagnostic performance of the PLN p.(Arg14del) risk model at 3-year follow-up. METHODS AND RESULTS: We performed a landmark analysis 3 years after presentation and selected only patients with no prior major VA. Data were collected of 268 PLN p.(Arg14del)-positive subjects, aged 43.5 ± 16.3 years, 38.9% male. After the 3 years landmark, subjects had a mean follow-up of 4.0 years (± 3.5 years) and 28 (10%) subjects experienced major VA with an annual event rate of 2.6% [95% confidence interval (CI) 1.6-3.6], defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. The PLN p.(Arg14del) risk score yielded good discrimination in the 3 years landmark cohort with a C-statistic of 0.83 (95% CI 0.79-0.87) and calibration slope of 0.97. CONCLUSION: The PLN p.(Arg14del) risk model has sustained good model performance up to 3 years follow-up in PLN p.(Arg14del)-positive subjects with no history of major VA. It may therefore be used to support decision-making for primary prevention ICD implantation not merely at presentation but also up to at least 3 years of follow-up.

Landmarks, beacons, or panoramic views: What do pigeons attend to for guidance in familiar environments?

Birds and social insects represent excellent systems for understanding visually guided navigation. Both animal groups use surrounding visual cues for homing and foraging. Ants extract sufficient spatial information from panoramic views, which naturally embed all near and far spatial information, for successful homing. Although egocentric panoramic views allow for parsimonious explanations of navigational behaviors, this potential source of spatial information has been mostly neglected during studies of vertebrates. Here we investigate how distinct landmarks, a beacon, and panoramic views influence the reorientation behavior in pigeons (Columba livia). Pigeons were trained to search for a location characterized by a beacon and several distinct landmarks. Transformation tests manipulated aspects of the landmark configuration, allowing for a dissociation among navigational strategies. Quantitative image and path analyses provided support that the panoramic view was used by the pigeons. Although the results from some individuals support the use of beaconing, overall the pigeons relied predominantly on the panoramic view when spatial cues provided conflicting information regarding the goal location. Reorientation based on vector and bearing information derived from distinct landmarks as well as environmental geometry failed to account fully for the results. Thus, the results of our study support that pigeons can use panoramic views for reorientation in familiar environments. Given that the current model for landmark use by pigeons posits the use of different vectors from an object, a global panorama-matching strategy suggests a fundamental change in the theory of how pigeons use surrounding visual cues for localization.

Automatic soft-tissue analysis on orthodontic frontal and lateral facial photographs based on deep learning.

BACKGROUND: To establish the automatic soft-tissue analysis model based on deep learning that performs landmark detection and measurement calculations on orthodontic facial photographs to achieve a more comprehensive quantitative evaluation of soft tissues. METHODS: A total of 578 frontal photographs and 450 lateral photographs of orthodontic patients were collected to construct datasets. All images were manually annotated by two orthodontists with 43 frontal-image landmarks and 17 lateral-image landmarks. Automatic landmark detection models were established, which consisted of a high-resolution network, a feature fusion module based on depthwise separable convolution, and a prediction model based on pixel shuffle. Ten measurements for frontal images and eight measurements for lateral images were defined. Test sets were used to evaluate the model performance, respectively. The mean radial error of landmarks and measurement error were calculated and statistically analysed to evaluate their reliability. RESULTS: The mean radial error was 14.44 ± 17.20 pixels for the landmarks in the frontal images and 13.48 ± 17.12 pixels for the landmarks in the lateral images. There was no statistically significant difference between the model prediction and manual annotation measurements except for the mid facial-lower facial height index. A total of 14 measurements had a high consistency. CONCLUSION: Based on deep learning, we established automatic soft-tissue analysis models for orthodontic facial photographs that can automatically detect 43 frontal-image landmarks and 17 lateral-image landmarks while performing comprehensive soft-tissue measurements. The models can assist orthodontists in efficient and accurate quantitative soft-tissue evaluation for clinical application.

Direct MR arthrography of the hip joint: anterior approach without imaging guidance.

PURPOSE: The purpose of this study is to describe the anterior injection approach, with anatomical landmark guidance, for direct MR arthrography (dMRA) of the hip joint, and to evaluate the effectiveness in joint distension and the security of the technique. MATERIAL AND METHODS: Retrospective review of hip dMRAs was conducted on patients with suspected intra-articular pathology from two MR outpatient centers, performed by two radiologists with 25 and 5 years of experience, respectively. The analysis included assessing the presence of intra-articular contrast material (gadolinium-based solution), the number of injections performed, the degree of joint distension, and the degree of contrast extravasation. A multi-variant analysis was carried out to determine if the procedure success depend on any of the demographic variants or on the radiologist experience. Additionally, the presence of immediate and medium-term post-puncture complications was evaluated. RESULTS: One hundred patients with 104 hip dMRA were included; 60 were men, with mean age of 38 years (16-63 years). Contrast material was successfully introduced intra-articularly in 100% of patients, being necessary a second puncture only in 6% of procedures. The capsular distension was considered optimal for diagnosis in 97% of cases. Different degrees of contrast extravasation were found in 30% of dMRA. There was no statistically significant relationship observed between patient variables and the performance of dMRA, nor did it show any correlation with the experience of the radiologists. No puncture-derived complications were found. CONCLUSION: Hip dMRA through anterior injection guided by anatomical references is an effective and safe alternative for patients with suspected intra-articular pathology.

Direct MR arthrography without image guidance: a practical guide, joint-by-joint.

Direct MR arthrography (dMRA) is a fundamental technique in diagnosing pathology in major peripheral joints, allowing for precise evaluation of intra-articular structures. Although injection guidance is typically performed using imaging techniques such as ultrasound or fluoroscopy, puncture via anatomical landmarks may be useful in certain circumstances where it has been proven to be a safe and effective procedure. This paper describes the indications and injection technique of dMRA, joint by joint, focusing on the different technical details, from the most common locations, like the shoulder or hip, to those with more restricted clinical indications, such as the wrist, knee, elbow, or ankle. The most relevant anatomical landmarks are detailed for each joint, aiding in the intra-articular introduction of diluted contrast, highlighting the most accessible trajectories and structures to avoid when inserting the needle. Additionally, tips are provided to facilitate proper joint distension. With all this information, this paper aims to serve as a suitable reference guide for performing dMRA without image guidance if needed.

Long-term outcomes of 5-year survivors without recurrence after the complete resection of non-small cell lung cancer after lobectomy: a landmark analysis in consideration of competing risks.

PURPOSE: Among non-small cell lung cancers (NSCLC), 5 years is a benchmark in cancer control and treatment, but a certain percentage of cases recur after 5 years. The long-term post-recurrence outcomes remain controversial. To examine the accurate prognostic factors associated with survival and cancer recurrence among 5-year survivors, a landmark analysis that considered competing risks was performed. METHODS: Complete resection of NSCLC was performed in 2482 patients between January 2003 and December 2015. A total of 1431 patients were 5-year survivors without recurrence. A landmark time analysis was applied to the overall survival (OS) and recurrence-free survival (RFS) from 5 years after surgery, and the findings were calculated using the Kaplan-Meier method. The cumulative incidence of cause-specific death and recurrence was estimated using the cumulative incidence function, while carefully considering the competing risks. RESULTS: Postoperative recurrence was detected in 732 patients, of whom 68 (9.3%) had recurrence after 5 years. The median follow-up period was 8.2 years. In the competing risk analysis, the independent poor prognostic factors associated with cause-specific death were age ≥ 75 years, lymph node metastasis and pleural invasion. CONCLUSIONS: Patients requiring a follow-up for > 5 years were aged ≥ 75 years and had either lymph node metastasis or pleural invasion.

Three-Dimensional Multi-Modality Registration for Orthopaedics and Cardiovascular Settings: State-of-the-Art and Clinical Applications.

The multimodal and multidomain registration of medical images have gained increasing recognition in clinical practice as a powerful tool for fusing and leveraging useful information from different imaging techniques and in different medical fields such as cardiology and orthopedics. Image registration could be a challenging process, and it strongly depends on the correct tuning of registration parameters. In this paper, the robustness and accuracy of a landmarks-based approach have been presented for five cardiac multimodal image datasets. The study is based on 3D Slicer software and it is focused on the registration of a computed tomography (CT) and 3D ultrasound time-series of post-operative mitral valve repair. The accuracy of the method, as a function of the number of landmarks used, was performed by analysing root mean square error (RMSE) and fiducial registration error (FRE) metrics. The validation of the number of landmarks resulted in an optimal number of 10 landmarks. The mean RMSE and FRE values were 5.26 ± 3.17 and 2.98 ± 1.68 mm, respectively, showing comparable performances with respect to the literature. The developed registration process was also tested on a CT orthopaedic dataset to assess the possibility of reconstructing the damaged jaw portion for a pre-operative planning setting. Overall, the proposed work shows how 3D Slicer and registration by landmarks can provide a useful environment for multimodal/unimodal registration.

Multitask Learning Strategy with Pseudo-Labeling: Face Recognition, Facial Landmark Detection, and Head Pose Estimation.

Most facial analysis methods perform well in standardized testing but not in real-world testing. The main reason is that training models cannot easily learn various human features and background noise, especially for facial landmark detection and head pose estimation tasks with limited and noisy training datasets. To alleviate the gap between standardized and real-world testing, we propose a pseudo-labeling technique using a face recognition dataset consisting of various people and background noise. The use of our pseudo-labeled training dataset can help to overcome the lack of diversity among the people in the dataset. Our integrated framework is constructed using complementary multitask learning methods to extract robust features for each task. Furthermore, introducing pseudo-labeling and multitask learning improves the face recognition performance by enabling the learning of pose-invariant features. Our method achieves state-of-the-art (SOTA) or near-SOTA performance on the AFLW2000-3D and BIWI datasets for facial landmark detection and head pose estimation, with competitive face verification performance on the IJB-C test dataset for face recognition. We demonstrate this through a novel testing methodology that categorizes cases as soft, medium, and hard based on the pose values of IJB-C. The proposed method achieves stable performance even when the dataset lacks diverse face identifications.

Multi-Sensor-Assisted Low-Cost Indoor Non-Visual Semantic Map Construction and Localization for Modern Vehicles.

With the transformation and development of the automotive industry, low-cost and seamless indoor and outdoor positioning has become a research hotspot for modern vehicles equipped with in-vehicle infotainment systems, Internet of Vehicles, or other intelligent systems (such as Telematics Box, Autopilot, etc.). This paper analyzes modern vehicles in different configurations and proposes a low-cost, versatile indoor non-visual semantic mapping and localization solution based on low-cost sensors. Firstly, the sliding window-based semantic landmark detection method is designed to identify non-visual semantic landmarks (e.g., entrance/exit, ramp entrance/exit, road node). Then, we construct an indoor non-visual semantic map that includes the vehicle trajectory waypoints, non-visual semantic landmarks, and Wi-Fi fingerprints of RSS features. Furthermore, to estimate the position of modern vehicles in the constructed semantic maps, we proposed a graph-optimized localization method based on landmark matching that exploits the correlation between non-visual semantic landmarks. Finally, field experiments are conducted in two shopping mall scenes with different underground parking layouts to verify the proposed non-visual semantic mapping and localization method. The results show that the proposed method achieves a high accuracy of 98.1% in non-visual semantic landmark detection and a low localization error of 1.31 m.

A Deep Learning Model for Markerless Pose Estimation Based on Keypoint Augmentation: What Factors Influence Errors in Biomechanical Applications?

In biomechanics, movement is typically recorded by tracking the trajectories of anatomical landmarks previously marked using passive instrumentation, which entails several inconveniences. To overcome these disadvantages, researchers are exploring different markerless methods, such as pose estimation networks, to capture movement with equivalent accuracy to marker-based photogrammetry. However, pose estimation models usually only provide joint centers, which are incomplete data for calculating joint angles in all anatomical axes. Recently, marker augmentation models based on deep learning have emerged. These models transform pose estimation data into complete anatomical data. Building on this concept, this study presents three marker augmentation models of varying complexity that were compared to a photogrammetry system. The errors in anatomical landmark positions and the derived joint angles were calculated, and a statistical analysis of the errors was performed to identify the factors that most influence their magnitude. The proposed Transformer model improved upon the errors reported in the literature, yielding position errors of less than 1.5 cm for anatomical landmarks and 4.4 degrees for all seven movements evaluated. Anthropometric data did not influence the errors, while anatomical landmarks and movement influenced position errors, and model, rotation axis, and movement influenced joint angle errors.

Faces in Event Streams (FES): An Annotated Face Dataset for Event Cameras.

The use of event-based cameras in computer vision is a growing research direction. However, despite the existing research on face detection using the event camera, a substantial gap persists in the availability of a large dataset featuring annotations for faces and facial landmarks on event streams, thus hampering the development of applications in this direction. In this work, we address this issue by publishing the first large and varied dataset (Faces in Event Streams) with a duration of 689 min for face and facial landmark detection in direct event-based camera outputs. In addition, this article presents 12 models trained on our dataset to predict bounding box and facial landmark coordinates with an mAP50 score of more than 90%. We also performed a demonstration of real-time detection with an event-based camera using our models.

An Audio-Based SLAM for Indoor Environments: A Robotic Mixed Reality Presentation.

In this paper, we present a novel approach referred to as the audio-based virtual landmark-based HoloSLAM. This innovative method leverages a single sound source and microphone arrays to estimate the voice-printed speaker's direction. The system allows an autonomous robot equipped with a single microphone array to navigate within indoor environments, interact with specific sound sources, and simultaneously determine its own location while mapping the environment. The proposed method does not require multiple audio sources in the environment nor sensor fusion to extract pertinent information and make accurate sound source estimations. Furthermore, the approach incorporates Robotic Mixed Reality using Microsoft HoloLens to superimpose landmarks, effectively mitigating the audio landmark-related issues of conventional audio-based landmark SLAM, particularly in situations where audio landmarks cannot be discerned, are limited in number, or are completely missing. The paper also evaluates an active speaker detection method, demonstrating its ability to achieve high accuracy in scenarios where audio data are the sole input. Real-time experiments validate the effectiveness of this method, emphasizing its precision and comprehensive mapping capabilities. The results of these experiments showcase the accuracy and efficiency of the proposed system, surpassing the constraints associated with traditional audio-based SLAM techniques, ultimately leading to a more detailed and precise mapping of the robot's surroundings.

Evolution of the term "epicondyle of the femur": Revisiting the anatomical and surgical literature.

The femoral epicondyle is an anatomical bony landmark essential for surgeons and anatomists, but there are discrepancies between the two fields when using this term. In current orthopedic surgery, it commonly denotes the small bony prominence of the femoral condyle. Given the derivation, "epicondyle" should be a region projecting laterally from the articular surface rather than a point. These discrepancies in usage are found not only between the fields but also in the literature. This article reviews the narrative definition of "epicondyle of the femur" in surgery and the evolution of the term in anatomy. The outcomes of the review suggest a relationship between the differing perceptions of the epicondyle and the evolution of the term. In reports of studies related to the epicondyle, it is strongly recommended that the definition of the word is clearly stated, with an understanding of its evolution.

Long-term impact of type 2 diabetes onset on dementia incidence rate among New Zealanders with impaired glucose tolerance: A tapered-matched landmark analysis over 25 years.

INTRODUCTION: We aimed to investigate the association between the onset of type 2 diabetes (T2D) and dementia incidence rates (IR) in the population with impaired glucose tolerance (IGT) identified in primary care in New Zealand (NZ) over 25 years. METHODS: Tapered matching and landmark analysis (accounting for immortal bias) were used to control for potential effects of known confounders. The association between T2D onset and 5- and 10-year IR of dementia was estimated by weighted Cox models. RESULTS: The onset of T2D was significantly associated with the 10-year IR of dementia, especially in the socioeconomically deprived, those of non-NZ European ethnicity, those currently smoking, and patients with higher metabolic measures. DISCUSSION: Our findings suggest that the onset of T2D is a significant risk factor for dementia in individuals with IGT. Dementia screening and structured diabetes prevention are vital in the population with IGT, particularly those from deprived or ethnic minority backgrounds. HIGHLIGHTS: Increased dementia incidence rate links with T2D onset in people with IGT. Significant incidence varied by ethnicity, socioeconomic status, and health factors. Results emphasize the diabetes manage and socioeconomic factors on dementia risk. Secondary analysis highlights the key role of vascular health in dementia prevention.

Molecular Targeting of the Human Epidermal Growth Factor Receptor-2 (HER2) Genes across Various Cancers.

Human epidermal growth factor receptor 2 (HER2) belongs to the ErbB family, a group of four transmembrane glycoproteins with tyrosine kinase activity, all structurally related to epidermal growth factor receptor (EGFR). These tyrosine kinases are involved in the transmission of cellular signals controlling normal cell growth and differentiation. If this transmission goes awry, it can lead to dysregulated growth of the cell. HER2 specifically can be implicated in the pathogenesis of at least eight malignancies. HER2 positivity quickly became a well-characterized indicator of aggressiveness and poor prognosis, with high rates of disease progression and mortality. After realizing the implication of HER2, it first became investigated as a target for treatment in breast cancer, and later expanded to areas of research in other cancer types. To this day, the most therapeutic advancements of anti-HER2 therapy have been in breast cancer; however, there have been strong advancements made in the incorporation of anti-HER2 therapy in other cancer types as well. This comprehensive review dissects HER2 to its core, incorporating the most up to date information. The topics touched upon are discussed in detail and up to 200 published sources from the most highly recognized journals have been integrated. The importance of knowing about HER2 is exemplified by the groundbreaking advancements that have been made, and the change in treatment plans it has brought to the oncological world in the last twenty years. Since its groundbreaking discovery there have been significant breakthroughs in knowledge regarding the actual receptor, the receptors biology, its mechanism of action, and advancements in tests to detect HER2 and significant strides on how to best incorporate targeted treatment. Due to the success of this field thus far, the review concludes by discussing the future of novel anti-HER2 therapy currently in development that everyone should be aware of.

The distal tibiofibular syndesmosis is a reliable landmark for 3° varus tibial resection in total knee arthroplasty: a radiological evaluation on 1296 cases.

PURPOSE: The purpose of this study was to evaluate the reproducibility and the accuracy of distal tibiofibular syndesmosis (DTFS) as landmark to perform controlled varus tibial resections during total knee arthroplasty (TKA). The hypothesis was that DTFS can be used to perform an accurate 3° varus tibial cut. METHODS: A retrospective analysis on a consecutive series of standard weightbearing full-length anteroposterior views of the lower limbs radiographic images was conducted. For each radiograph, the hip-knee-ankle (HKA) angle, the angle between the tibial mechanical axis and the line connecting the centre of the tibial spines and the DTFS (tibiofibular angle, TFA) and the medial proximal tibial angle (MPTA) were calculated. Each measurement was carried out twice by three independent observers, and intra- and inter-observer measurement reliability were assessed using the intraclass correlation coefficient (ICC) analysis. RESULTS: A total of 1296 lower limbs were analysed from a series of 648 weightbearing full-length anteroposterior radiographs. The ICC were > 90% for all measurements. The mean TFA value was 2.94 ± 0.68 (range 2.38-3.51). No differences were detected comparing the mean TFA value on the right and left limb (p = 0.795) as well as comparing the values in male and female patients (p = 0.691). Linear regression analysis did not find statistically significant correlation between TFA and MPTA, or TFA and HKA angles, respectively. CONCLUSION: The distal tibiofibular syndesmosis is a reliable and easy reproducible radiographic landmark that can be used when planning a 3° varus tibial cut. Future studies are needed to confirm the validity of this method also in clinical settings. LEVEL OF EVIDENCE: IV, retrospective case series.