Standard View Research Articles

Lesser transgressions and loss of standing to blame

AbstractIn the Standard View, a blamee can dismiss another's blaming of her as hypocritical and thus standingless if, and only if, the blamer's violations of the norm he is invoking are as bad as the blamee's. I defend a counterexample to this view showing that blame can be hypocritical and thus standingless when, simultaneously with blaming, the blamer willingly violates, in a minor way, the norm he is invoking. If correct, this has important implications for accounts of what makes hypocritical blame standingless. Hypocritical blame of the sort involved in my counterexample cannot be accommodated by the moral equality account of standing to blame. Nor can existing commitment accounts accommodate it without revising the way we think about standing‐relevant commitment. Hence, this article points to a need for both revising the common view of when blame can be dismissed as hypocritical and rethinking the two standard accounts of that in virtue of which we have or lack standing to blame. Specifically, it points to an interesting way in which standing to blame appears to be time‐relative.

Industrial heritage restoration/renovation projects and their societal impacts: Case of Gasholder Restoration Projects

The refurbishment of industrial heritage structures offers economic benefits and provides future generations with an insight into the industrial history of cities. However, industrial heritage projects possess unique attributes and risks, and the procedures for restoring, renovating, and converting these structures differ from those of other construction projects and their impacts to society. From the view of Social Impact Management, ISO 45001, ISO 14001, ISO/DIS 14001 and similar standards directly related with the sustainability. However, the design and method of construction are also important not only for workers’ safety but also public health and safety. For a holistic view Building Information Modeling provides us to gather information to reduce these concerns. This short communication covers societal impacts of a recently completed project in Germany that titled as Building Information Modeling (BIM) based sustainability, facility management and design for safety of industrial heritage buildings restoration/renovation projects and tries to put forward health and safety risks of Gasholder Restoration Projects to workers as well as to public during the project and after the completion by the aid of on site observations and expert panel discussions.

Angiographic classification of chronic subdural hematoma.

<p>Chronic subdural hematoma (cSDH) is a challenging pathology with high recurrence rate after surgical treatment and may seriously affect the patient&rsquo;s quality of life. Membrane formation with angiogenesis plays an important role in the evolution of the disease, providing a promising target for endovascular therapy. Our goal is to categorize angiographic patterns of chronic subdural hematoma for standardized reporting purposes.</p>. <p>In our retrospective analysis of prospective data collection, we analyzed angiographic properties of all high recurrence risk patients with cSDH, who were treated by embolization in our hospital between February 2019 and June 2020. Altogether 17 patients were included in the analysis.&nbsp;</p>. <p>Based on superselective angiography of the middle meningeal artery (MMA) in the two standard, AP and lateral views, three distinct categories of dural supply were defined: normal vascular pattern (Grade I), cottonwool appearance without enlargement of the MMA branches (Grad II) and strong cottonwool like staining with dilatative remodelling of the MMA branches (Grade III).</p>. <p>The proposed grading system of the angiographic appearance of cSDH, representing the pathophysiological evolution of the disease should be correlated to therapeutic success rates and could be applied in future clinical studies.</p>.

A collinear perspective on the Regge limit

The high energy (Regge) limit provides a playground for understanding all loop structures of scattering amplitudes, and plays an important role in the description of many phenomenologically relevant cross-sections. While well understood in the planar limit, the structure of non-planar corrections introduces many fascinating complexities, for which a general organizing principle is still lacking. We study the structure of multi-reggeon exchanges in the context of the effective field theory for forward scattering, and derive their factorization into collinear operators (impact factors) and soft operators. We derive the structure of the renormalization group consistency equations in the effective theory, showing how the anomalous dimensions of the soft operators are related to those of the collinear operators, allowing us to derive renormalization group equations in the Regge limit purely from a collinear perspective. The rigidity of the consistency equations provides considerable insight into the all orders organization of Regge amplitudes in the effective theory, as well as its relation to other approaches. Along the way we derive a number of technical results that improve the understanding of the effective theory. We illustrate this collinear perspective by re-deriving all the standard BFKL equations for two-Glauber exchange from purely collinear calculations, and we show that this perspective provides a number of conceptual and computational advantages as compared to the standard view from soft or Glauber physics. We anticipate that this formulation in terms of collinear operators will enable a better understanding of the relation between BFKL and DGLAP in gauge theories, and facilitate the analysis of renormalization group evolution equations describing Reggeization beyond next-to-leading order.

Quantifying fetal heart health in gestational diabetes: a new approach with fetal heart quantification technology.

This study aimed to assess the impact of gestational diabetes mellitus (GDM) on fetal heart structure and function using a technique called fetal heart quantification (Fetal HQ), with a focus on mitochondrial dynamics, which employs advanced imaging technology for comprehensive analysis. A total of 180 fetuses with normal heart structures, aged 24-40weeks of gestation, were examined. A 2-3s cine loop in the standard four-chamber oblique view was captured and analyzed using the speckle-tracking technique with Fetal HQ. Various echocardiographic parameters were evaluated, including four-chamber view (4CV), global spherical index (GSI), global longitudinal strain (GLS), 24-segment spherical index (SI), ventricular fractional area change (FAC), cardiac output (CO), and stroke volume (SV). These parameters were compared between the GDM group and the control group during two gestational periods: 24+0 to 28+0 weeks and 28+1 to 40+1 weeks. Statistical analysis was performed using independent samples t-tests and Mann-Whitney U tests to identify significant differences. Twenty fetuses from mothers with GDM and 40 from the control group were recruited at 24+0 to 28+0 weeks. At 28+1 to 40+1 weeks, 40 fetuses from mothers with GDM and 80 from the control group were recruited. The fetal left ventricular global longitudinal function was similar between the GDM and control groups. However, compared to the controls, right ventricular function in the GDM group was lower only at 28+1 to 40+1 weeks. In the GDM group, the global spherical index (GSI) was lower than in the control group at 28+1 to 40+1 weeks (1.175 vs. 1.22; p = 0.001). There were significant decreases in ventricular FAC (38.74% vs. 42.83%; p < 0.0001) and 4CV GLS for the right ventricle (-22.27% vs. -26.31%; p = 0.005) at 28+1 to 40+1 weeks. Our findings suggest that GDM is associated with decreased right ventricular function in the fetal heart, particularly during the later stages of pregnancy (28+1 to 40+1 weeks), compared to fetuses from healthy pregnancies. The Fetal HQ technique represents a valuable tool for evaluating the structure and function of fetal hearts affected by GDM during the advanced stages of pregnancy.

Structural and functional cardiac parameters across occupations: a cross-sectional study in differing work environments

Previous investigations have highlighted notable variations in cardiovascular risk indicators associated with various professional categories. However, only a few studies have examined structural and functional cardiac parameters using echocardiography within distinct occupational groups. Hence, this study endeavored to assess cardiac structural and functional parameters in three additional occupations: firefighters (FFs), police officers (POs), and office workers (OWs). This prospective study encompassed 197 male participants (97 FFs, 54 POs, and 46 OWs) from Germany. All participants underwent 2D and Doppler echocardiography in resting conditions; standard parasternal and apical axis views were employed to evaluate structural (diastolic and systolic) and functional (systolic and diastolic function, and strain) cardiac parameters. All three occupational groups exhibited a tendency towards septal hypertrophy. Notably, OWs exhibited the largest diastolic interventricular septum diameter (IVSd), at 1.33 ± 0.25 cm. IVSd significantly varied between POs and OWs (p = 0.000) and between POs and FFs (p = 0.025). Additionally, during diastole a substantially larger left ventricular posterior wall diameter (LVPWd) was observed in OWs compared to FFs (p = 0.001) and POs (p = 0.013). The left ventricular diastolic cavity diameter (LVIDd) and the left ventricular systolic cavity diameter (LVIDs) were significantly higher in POs than they were in FFs (LVIDd: p = 0.001; LVIDs: p = 0.009), and the LVIDd was notably higher in FFs (p = 0.015) and POs compared to OWs (p = 0.000). FFs exhibited significantly better diastolic function, indicated by higher diastolic peak velocity ratios (MV E/A ratio) and E/E’ ratios, compared to POs (E/A ratio: p = 0.025; E/E’ ratio: p = 0.014). No significant difference in diastolic performance was found between OWs and FFs. Significantly higher E’(lateral) values were noted in POs compared to FFs (p = 0.003) and OWs (p = 0.004). Ejection fraction did not significantly differ among FFs, POs, and OWs (p > 0.6). The left ventricular mass (LV Mass) was notably higher in POs than it was in FFs (p = 0.039) and OWs (p = 0.033). Strain parameter differences were notably improved in two- (p = 0.006) and four-chamber (p = 0.018) views for FFs compared to POs. Concentric remodeling was the predominant change observed in all three occupational groups. Significant differences in the presence of various forms of hypertrophy were observed in FFs, POs, and OWs (exact Fisher test p-values: FFs vs. OWs = 0.021, POs vs. OWs = 0.002). OWs demonstrated notably higher rates of concentric remodeling than FFs did (71.77% vs. 47.9%). This study underscores disparities in both functional and structural parameters in diverse occupational groups. Larger prospective studies are warranted to investigate and delineate differences in structural and functional cardiac parameters across occupational groups, and to discern their associated effects and risks on the cardiovascular health of these distinct professional cohorts.

Remapping revisited: how the hippocampus represents different spaces.

The representation of distinct spaces by hippocampal place cells has been linked to changes in their place fields (the locations in the environment where the place cells discharge strongly), a phenomenon that has been termed 'remapping'. Remapping has been assumed to be accompanied by the reorganization of subsecond cofiring relationships among the place cells, potentially maximizing hippocampal information coding capacity. However, several observations challenge this standard view. For example, place cells exhibit mixed selectivity, encode non-positional variables, can have multiple place fields and exhibit unreliable discharge in fixed environments. Furthermore, recent evidence suggests that, when measured at subsecond timescales, the moment-to-moment cofiring of a pair of cells in one environment is remarkably similar in another environment, despite remapping. Here, I propose that remapping is a misnomer for the changes in place fields across environments and suggest instead that internally organized manifold representations of hippocampal activity are actively registered to different environments to enable navigation, promote memory and organize knowledge.

Re-thinking mathematical connections with theories of difference

ABSTRACT In this theoretical article, we explore the possibility that instead of a mathematical connection arising “in-between” two (or more) pre-existing ideas or objects, which have presumably been known or understood, that connection is itself the motor of understanding. The standard view of connection, in which two existing ideas or concepts are brought together, is based on a philosophy of identity which seeks to establish objects and their properties and then compare them. In contrast, a philosophy of difference sees objects as “becoming” through difference. We explore this new way of conceptualising connection not only because it reflects our commitment to a relational ontology, but because it enables us to better handle the enmeshment of affect in mathematical learning without subordinating it to the cognitive. We draw on illustrative data to show what analysing connections as acts of differencing might look like and how it involves affective, social and technical dimensions.

HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos.

In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essential foundation for diagnosing congenital heart disease. Previous studies have mostly focused on the detection of adult CCs, which may not be applicable to the fetus. In clinical practice, localization of SCCs needs to recognize end-systole (ES) and end-diastole (ED) frames accurately, ensuring that every frame in the cycle is a standard view. Most existing methods are not based on the detection of key anatomical structures, which may not recognize irrelevant views and background frames, results containing non-standard frames, or even it does not work in clinical practice. We propose an end-to-end hybrid neural network based on an object detector to detect SCCs from fetal ultrasound videos efficiently, which consists of 3 modules, namely Anatomical Structure Detection (ASD), Cardiac Cycle Localization (CCL), and Standard Plane Recognition (SPR). Specifically, ASD uses an object detector to identify 9 key anatomical structures, 3 cardiac motion phases, and the corresponding confidence scores from fetal ultrasound videos. On this basis, we propose a joint probability method in the CCL to learn the cardiac motion cycle based on the 3 cardiac motion phases. In SPR, to reduce the impact of structure detection errors on the accuracy of the standard plane recognition, we use XGBoost algorithm to learn the relation knowledge of the detected anatomical structures. We evaluate our method on the test fetal ultrasound video datasets and clinical examination cases and achieve remarkable results. This study may pave the way for clinical practices.

Crowdsourced Assessment of Aesthetic Outcomes of Dorsal Preservation Rhinoplasty

Abstract Goals/Purpose The inherent subjectivity in evaluating aesthetic outcomes presents a unique challenge in assessing rhinoplasty. Crowdsourcing has provided a new metric for objective analysis. The authors designed a study to compare the aesthetic outcomes of dorsal preservation rhinoplasty versus structural rhinoplasty using a reliable and valid crowdsourcing platform. We aim to objectively quantify the relative aesthetic advantages of performing a dorsal preservation technique. Additionally, we aim to demonstrate the efficacy of using crowdsourcing as an efficient and reliable method for evaluating any plastic surgery aesthetic outcome. Methods/Technique This retrospective observational study was approved by the IRB at UCLA. A total of 64 patients who had previously undergone rhinoplasty performed by the senior author were included. All surgeries were performed at the UCLA Ronald Reagan Medical Center. Patients with prior nasal surgery or trauma were excluded. All subjects were photographed using standard rhinoplasty views during the pre-and postoperative visits. Frontal and right profile photographs were then cropped in a standardized fashion (Photos, Version 8.0, Apple Inc.) and used for evaluation. All evaluations and ratings were collected using the HIPPA compliant and encrypted software via a secure online platform (LoveMyDelta, Inc., Philadelphia, PA). All crowd workers were recruited and vetted through this platform, with internal fidelity checks performed. Each crowd worker was shown a profile and frontal view of a patient and asked to score the overall appearance of the nose, the nasal dorsum profile, the symmetry of the dorsal aesthetic lines, and the dorsal contour using a visual analog scale. Scoring was performed using a provided validated visual assessment guide. They were asked whether they believed the subject had undergone rhinoplasty and asked to provide a level of confidence in their guess. Crowdworkers’ responses were aggregated to allow for high-powered intra-rater analysis. Intra-rater reliability and confidence intervals were calculated. Aggregate data from all raters were used to generate an absolute value of aesthetic state for each cohort. A "delta" was then obtained for each value by comparing the preoperative to the postoperative state to obtain a representative value of the improvement after undergoing surgery. Raters were asked if the patient appeared to have had surgery, and each correct and incorrect response was proportionally weighted based on the raters' confidence in their answer. The delta (difference in preoperative to postoperative aesthetic state) for each parameter for the dorsal and non-dorsal preservation cohorts was calculated using non-paired T-tests to determine significance. Results/Complications A total of 64 patients were included for evaluation. The structural rhinoplasty cohort consisted of 34 patients. The dorsal preservation cohort included 30 patients. Both dorsal preservation and non-dorsal preservation rhinoplasty cohorts were associated with improved overall crowdsourced aesthetic outcomes and improved outcomes across all subparameters. Overall, delta (d) improved in both dorsal preservation (0.300, 95% CI +/- 0.047) and structural (0.377, 95% CI +/- 0.055) cohorts. When raters were asked to predict whether a patient had surgery, the correlation coefficient between the confidence in the prediction and that prediction being correct was 0.74 (95% CI +/- 0.47 in the structural group, suggesting that a crowd worker was likely to be correct in identifying whether a patient had structural rhinoplasty. However, the correlation coefficient was -0.0554 (95% CI +/- 0.058) in the dorsal preservation group. This suggests the raters were unable to consistently identify which patients had dorsal preservation rhinoplasty with any confidence. Conclusion In the ongoing challenge to achieve better aesthetic outcomes in plastic surgery, crowdsourcing is a valuable tool for helping to measure these outcomes. We compared the aesthetic outcomes of dorsal preservation rhinoplasty versus structural rhinoplasty using a reliable and valid crowdsourcing platform. We found that significant improvements in overall aesthetic outcomes were achieved with both techniques, while a more natural “unoperated” outcome was achieved when performing a dorsal preservation technique. With this type of study and assessment tool, we helped to demonstrate the efficacy of using crowdsourcing as an efficient and reliable method for evaluating any plastic surgery aesthetic outcome.

Alerting effects require the absence of surprise

Ongoing actions are interrupted for a brief period of time whenever salient and expectancy-discrepant stimuli (surprise stimuli) interfere with the present task set. By contrast, salient stimuli (alerting cues) preceding targets can facilitate behaviour by reducing time to initiate actions. Both phenomena seem to be at odds with each other as actions are either impaired or facilitated. Therefore, in the present study, we asked how surprise and alerting effects interact. In two experiments, participants performed choice reaction tasks without any prior knowledge of the impending alerting cue. After a baseline period of trials without an alerting cue, the alerting cue was presented for the first time. It was found that the initial presentation of the alerting cue significantly slowed down reaction times. However, after just a single trial this impairment went away. This reveals that the beneficial effects of alerting for action presuppose that alerting cues are expected and represented in the top-down task set. As such, the present findings challenge the standard view of phasic alerting as a bottom-up and entirely stimulus-driven phenomenon.

AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning.

In cardiac cine imaging, acquiring high-quality data is challenging and time-consuming due to the artifacts generated by the heart's continuous movement. Volumetric, fully isotropic data acquisition with high temporal resolution is, to date, intractable due to MR physics constraints. To assess whole-heart movement under minimal acquisition time, we propose a deep learning model that reconstructs the volumetric shape of multiple cardiac chambers from a limited number of input slices while simultaneously optimizing the slice acquisition orientation for this task. We mimic the current clinical protocols for cardiac imaging and compare the shape reconstruction quality of standard clinical views and optimized views. In our experiments, we show that the jointly trained model achieves accurate high-resolution multi-chamber shape reconstruction with errors of <13 mm HD95 and Dice scores of >80%, indicating its effectiveness in both simulated cardiac cine MRI and clinical cardiac MRI with a wide range of pathological shape variations.

RL-TEE: Autonomous Probe Guidance for Transesophageal Echocardiography Based on Attention-Augmented Deep Reinforcement Learning

Ultrasound image acquisition in conventional transesophageal echocardiography (TEE) requires complex manual operation of the probe in the esophagus based on the interpretation of ultrasound images and in-depth knowledge of the cardiac anatomy. In this work, we formulate the TEE probe guidance task as a reinforcement learning (RL) problem, and present the first learning-based solution to 3-DOF control of a TEE probe based on the ultrasound image feedback, named RL-TEE, in order to mimic the visual search and navigation strategies of expert echocardiographers. The probe-tissue interaction in TEE is carefully modeled in our framework by considering both the requirements for navigation towards the standard views and compliance in the esophageal environment. Furthermore, we propose a hybrid deep Q-network model that augments a convolutional neural network backbone with self-attention mechanisms to better capture spatial information in ultrasound images to guide navigation decisions. The presented methods are preliminarily validated in a TEE simulation environment built with data from 25 subjects to acquire four standard views of the heart. Our results show that the proposed method can effectively learn to accurately and compliantly guide the probe movement for TEE standard view acquisition tasks and has a good generalization ability to unseen patient data. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation of this paper is to realize 3-DOF movement guidance of a TEE probe to acquire the standard views of the heart based on the real-time images, which can be applied to existing robotic control systems or used to assist novice echocardiographers in TEE examination, thereby relieving operator workload and improving ease of use. This paper suggests a novel approach that uses the deep RL technique to achieve automatic interpretation of TEE images and intelligent guidance of the probe movement. The RL framework is designed to take into account both the navigation efficiency and compliance with the esophageal environment for the targeted intracorporeal application. A hybrid deep Q-network model that augments a convolutional neural network with attention mechanisms is designed to better capture spatial information from ultrasound images to predict the probe movement. The effectiveness of the framework is preliminarily validated in extensive experiments in a simulation environment built with real patient data. The proposed method can be applied in clinical use to provide real-time TEE probe guidance for novice echocardiographers, and can be integrated with a robotic system to fully automate the TEE acquisition, thereby relieving the doctors from tedious manual operation to focus on the diagnosis and treatment.

ImageAssist: A Novel Smartphone Application for Standardized Clinical Photography That Implements and Automates American Society of Plastic Surgery/Plastic Surgery Foundation Photographic Guidelines With Background Deletion.

Standardized medical photography of the face is a vital part of patient documentation, clinical evaluation, and scholarly dissemination. Because digital photography is a mainstay in clinical care, there is a critical need for an easy-to-use mobile device application that could assist users in taking a standardized clinical photograph. ImageAssist was developed to answer this need. The mobile application is integrated into the electronic medical record (EMR); it implements and automates American Society of Plastic Surgery/Plastic Surgery Research Foundation photographic guidelines with background deletion. A team consisting of a craniofacial plastic surgeon and the Health Information Technology product group developed and implemented the pilot application of ImageAssist. The application launches directly from patients' chart in the mobile version of the EMR, EPIC Haiku (Verona, Wisconsin). Standard views of the face (90-degree, oblique left and right, front and basal view) were built into digital templates and are user selected. Red digital frames overlay the patients' face on the screen and turn green once standardized alignment is achieved, prompting the user to capture. The background is then digitally subtracted to a standard blue, and the photograph is not stored on the user's phone. ImageAssist initial beta user group was limited to 13 providers across dermatology, ENT, and plastic surgery. A mix of physicians, advanced practice providers, and nurses was included to pilot the application in the outpatient clinic setting using Image Assist on their smart phone. After using the app, an internal survey was used to gain feedback on the user experience. In the first 2 years of use, 31 users have taken more than 3400 photographs in more than 800 clinical encounters. Since initial release, automated background deletion also has been functional for any anatomic area. ImageAssist is a novel smartphone application that standardizes clinical photography and integrated into the EMR, which could save both time and expense for clinicians seeking to take consistent clinical images. Future steps include continued refinement of current image capture functionality and development of a stand-alone mobile device application.

Selection criteria for facility management practices: residents’ and building/site managers’ perspectives in urban transformation projects

PurposeThe facility management (FM) sector, which is developing rapidly, is making slower progress in Turkey compared to Europe and the USA. This paper aims to research the underlying issues leading to FM practices and offer insights into the implications of FM-related policies, especially for large urban transformation projects.Design/methodology/approachThe study used a mixed-methods research design and collected qualitative data through semi-structured interviews with building/site managers and quantitative data through structured surveys with residents. Forty-nine building/site managers and 660 residents participated in the interview and survey from Turkey’s North Ankara and Dikmen Valley urban transformation projects.FindingsThe FM by residents, performed by the managers selected among homeowners, was preferred to the professional FM in Turkey. Education level, age, homeownership and duration of living in the region were associated with selecting FM practices. Cost also had an important place among the selection criteria, and the standard view from the residents was that professional FM would cause a cost increase. However, interviews with building/site managers in North Ankara and Dikmen Valley Urban Transformation areas revealed that a significant part of the problem resulted from insufficient knowledge and experience in FM.Research limitations/implicationsWithin the scope of the research, two urban transformation projects in Ankara Province were selected, and the survey was limited to the North Ankara Entrance Urban Transformation Project and Dikmen Valley Urban Transformation Project areas. Although there is a need to improve the understanding of FM in all facilities, built environments and collective buildings, collective buildings in urban transformation areas due to several constraints, those other identified areas are postponed for future study. In addition, collective buildings located in transformation areas differ from others in discussing the social dimension and the impact of management.Social implicationsWithin the scope of the research, two urban transformation projects in Ankara Province were selected, and the survey was limited to the North Ankara Entrance Urban Transformation Project and Dikmen Valley Urban Transformation Project areas. Although there is a need to improve the understanding of FM in all facilities, due to several constraints built environments and collective buildings in urban transformation areas, are postponed for future study. In addition, collective buildings located in transformation areas differ from others in discussing the social dimension and the impact of management.Originality/valueThis study evaluates two different FM approaches: FM by residents and professional FM, implemented in Turkey and identifies the criteria for choosing the FM practice. In addition, both building/site managers and residents evaluate different perspectives on FM. This study is unique because it compares different FM practices in Turkey and the criteria for residents to prefer different FM practices.

The effect of real-time EF automatic tool on cardiac ultrasound performance among medical students.

Point-of-care ultrasound (POCUS) is a sensitive, safe, and efficient tool used in many clinical settings and is an essential part of medical education in the United States. Numerous studies present improved diagnostic performances and positive clinical outcomes among POCUS users. However, others stress the degree to which the modality is user-dependent, rendering high-quality POCUS training necessary in medical education. In this study, the authors aimed to investigate the potential of an artificial intelligence (AI) based quality indicator tool as a teaching device for cardiac POCUS performance. The authors integrated the quality indicator tool into the pre-clinical cardiac ultrasound course for 4th-year medical students and analyzed their performances. The analysis included 60 students who were assigned to one of two groups as follows: the intervention group using the AI-based quality indicator tool and the control group. Quality indicator users utilized the tool during both the course and the final test. At the end of the course, the authors tested the standard echocardiographic views, and an experienced clinician blindly graded the recorded clips. Results were analyzed and compared between the groups. The results showed an advantage in quality indictor users' median overall scores (P = 0.002) with a relative risk of 2.3 (95% CI: 1.10, 4.93, P = 0.03) for obtaining correct cardiac views. In addition, quality indicator users also had a statistically significant advantage in the overall image quality in various cardiac views. The AI-based quality indicator improved cardiac ultrasound performances among medical students who were trained with it compared to the control group, even in cardiac views in which the indicator was inactive. Performance scores, as well as image quality, were better in the AI-based group. Such tools can potentially enhance ultrasound training, warranting the expansion of the application to more views and prompting further studies on long-term learning effects.

Automatic multi-view pose estimation in focused cardiac ultrasound

Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator’s experience, resulting in primarily qualitative 2D exams. This study presents a novel framework to automatically estimate the 3D spatial relationship between standard FoCUS views. The proposed framework uses a multi-view U-Net-like fully convolutional neural network to regress line-based heatmaps representing the most likely areas of intersection between input images. The lines that best fit the regressed heatmaps are then extracted, and a system of nonlinear equations based on the intersection between view triplets is created and solved to determine the relative 3D pose between all input images. The feasibility and accuracy of the proposed pipeline were validated using a novel realistic in silico FoCUS dataset, demonstrating promising results. Interestingly, as shown in preliminary experiments, the estimation of the 2D images’ relative poses enables the application of 3D image analysis methods and paves the way for 3D quantitative assessments in FoCUS examinations.

Self-supervised learning for medical image data with anatomy-oriented imaging planes

Self-supervised learning has emerged as a powerful tool for pretraining deep networks on unlabeled data, prior to transfer learning of target tasks with limited annotation. The relevance between the pretraining pretext and target tasks is crucial to the success of transfer learning. Various pretext tasks have been proposed to utilize properties of medical image data (e.g., three dimensionality), which are more relevant to medical image analysis than generic ones for natural images. However, previous work rarely paid attention to data with anatomy-oriented imaging planes, e.g., standard cardiac magnetic resonance imaging views. As these imaging planes are defined according to the anatomy of the imaged organ, pretext tasks effectively exploiting this information can pretrain the networks to gain knowledge on the organ of interest. In this work, we propose two complementary pretext tasks for this group of medical image data based on the spatial relationship of the imaging planes. The first is to learn the relative orientation between the imaging planes and implemented as regressing their intersecting lines. The second exploits parallel imaging planes to regress their relative slice locations within a stack. Both pretext tasks are conceptually straightforward and easy to implement, and can be combined in multitask learning for better representation learning. Thorough experiments on two anatomical structures (heart and knee) and representative target tasks (semantic segmentation and classification) demonstrate that the proposed pretext tasks are effective in pretraining deep networks for remarkably boosted performance on the target tasks, and superior to other recent approaches.

Responding to his Critics: A New Account of Origen's Peri Archon

Abstract: Why did Origen write Peri Archon ? The standard view, often tinged with triumphant hues, envisions him as a "man of the church," embarking upon a bold research agenda while laying waste to his heterodox opponents. But I believe this picture misses the mark. It was really Origen—and not these heretics—who was in the dock. And it was those whom he regarded as his fellow Christians in Alexandria, including his bishop, who made up the prosecution. In this essay I argue that Peri Archon was Origen's response to these in-house critics, who increasingly regarded his views on select issues as heretical, or at least, less than orthodox. This essay has two parts. In the first, I examine Origen's self-portrait in the preface of Peri Archon , demonstrating how he shrewdly maneuvered his project into orthodox waters. In the second, I explain why he adopted this tactic. I spotlight five issues from his earlier writings where he challenged positions adopted by most Christians in his day, including prominent church leaders. These controversial stances surface again in Peri Archon but often in a diplomatic form and always in an orthodox frame. Peri Archon was Origen's apologia to fellow Christians.

Left ventricular function assessment including or excluding trabeculations in left ventricular non-compaction, a preliminary case-control cardiac magnetic resonance study.

Functional assessment of compact myocardium and hypertrabeculations in left ventricular non-compaction (LVNC) is underestimated with regards to the morphological spectrum of disease. We aimed to assess whether measuring concurrently left ventricular (LV) volume, mass and ejection fraction (LVEF) with and without trabeculation inclusion on cine magnetic resonance (cineMR) could help diagnose patients with LVNC by comparison to normal individuals with an excess of myocardial trabeculations. This retrospective single center magnetic resonance imaging study (Bichat University Hospital) of 67 consecutive patients with echocardiographic hypertrabeculations seen at echocardiography between March 2011 and October 2018 included 30 patients with known LVNC and 16 control subjects with simple hypertrabeculations (non-compact/compact (NC/C) ratio between 1.8 and 2.2, trabeculations involving 10% to 17% of the left ventricle) using steady-state free precession (SSFP) cine sequences in the standard views. LV volumes, mass and LVEF were measured with and without trabeculation inclusion using CVI42 software. Follow-up was studied in 20 patients and 14 controls. Functional parameters were compared using Student's paired t-test. Pearson product moment correlation coefficients were calculated. Bland-Altman analysis determined the inter- and intra-reader functional data reproducibility. When excluding the trabeculations (i.e. non-compacted myocardium) from measurements, LVEF was within normal ranges both in patients and controls, while it increased by 9.8%±1.6% in LVNC and decreased by 10.9%±1.4% in controls when trabeculae were included in the endocardial contours (P<0.0001). The overall myocardial mass remained stable according to the diastolic or systolic phase in LVNC whereas it significantly decreased in controls. Depending whether trabeculations were included or not, LVEF measurements were significantly different between patients with LVNC and controls. These distinctive measurements might be used as an adjunctive clinical tool to help confirm the diagnosis of LVNC.