Series Of Images Research Articles

Evolution of Left Ventricular Thrombus on Serial Cardiovascular Magnetic Resonance Imaging.

Current management of left ventricular (LV) thrombus relies on limited, non-contemporary, echocardiography-based studies. Data on LV thrombus evolution and the associated embolic risk are scarce. We aimed to describe the evolution of LV thrombus on serial cardiovascular magnetic resonance imaging (CMR) - the current reference standard for the detection of LV thrombus, and identify correlates of no resolution and the embolic risk associated with resolution status. We conducted a retrospective cohort study of 107 consecutive patients with LV thrombus who had 213 serial CMRs at a median of 255 days after the index CMR. Of these, 97.2% were anticoagulated. At 3 months after detection by CMR, 75% (47/63) had no resolution of LV thrombus; at 6 months, 53% (35/66) had no resolution; and at 12 months, 37% (23/63) had no resolution. Correlates of no resolution at 6 months included a history of myocardial infarction, LV aneurysm, ischemic etiology of cardiomyopathy, and larger thrombus volume. Recurrence of LV thrombus was rare at 5.3%. On survival analysis using the landmark analysis method, embolic events often occurred beyond 6 months, more frequently in patients with unresolved LV thrombus. Our findings challenge previous literature by demonstrating a lower rate of resolution of LV thrombus and substantial embolic risk beyond 6 months associated with unresolved LV thrombus on serial CMR. Our findings advocate for extended anticoagulation, particularly in patients with markers associated with no resolution. These findings have important implications for clinical practice and research into managing patients with LV thrombus.

Gender and Ethnicity Bias of Text-to-Image Generative Artificial Intelligence in Medical Imaging, Part 2: Analysis of DALL-E 3.

Disparity among gender and ethnicity remains an issue across medicine and health science. Only 26%-35% of trainee radiologists are female, despite more than 50% of medical students' being female. Similar gender disparities are evident across the medical imaging professions. Generative artificial intelligence text-to-image production could reinforce or amplify gender biases. Methods: In March 2024, DALL-E 3 was utilized via GPT-4 to generate a series of individual and group images of medical imaging professionals: radiologist, nuclear medicine physician, radiographer, nuclear medicine technologist, medical physicist, radiopharmacist, and medical imaging nurse. Multiple iterations of images were generated using a variety of prompts. Collectively, 120 images were produced for evaluation of 524 characters. All images were independently analyzed by 3 expert reviewers from medical imaging professions for apparent gender and skin tone. Results: Collectively (individual and group images), 57.4% (n = 301) of medical imaging professionals were depicted as male, 42.4% (n = 222) as female, and 91.2% (n = 478) as having a light skin tone. The male gender representation was 65% for radiologists, 62% for nuclear medicine physicians, 52% for radiographers, 56% for nuclear medicine technologists, 62% for medical physicists, 53% for radiopharmacists, and 26% for medical imaging nurses. For all professions, this overrepresents men compared with women. There was no representation of persons with a disability. Conclusion: This evaluation reveals a significant overrepresentation of the male gender associated with generative artificial intelligence text-to-image production using DALL-E 3 across the medical imaging professions. Generated images have a disproportionately high representation of white men, which is not representative of the diversity of the medical imaging professions.

Gender and Ethnicity Bias of Text-to-Image Generative Artificial Intelligence in Medical Imaging, Part 1: Preliminary Evaluation.

Generative artificial intelligence (AI) text-to-image production could reinforce or amplify gender and ethnicity biases. Several text-to-image generative AI tools are used for producing images that represent the medical imaging professions. White male stereotyping and masculine cultures can dissuade women and ethnically divergent people from being drawn into a profession. Methods: In March 2024, DALL-E 3, Firefly 2, Stable Diffusion 2.1, and Midjourney 5.2 were utilized to generate a series of individual and group images of medical imaging professionals: radiologist, nuclear medicine physician, radiographer, and nuclear medicine technologist. Multiple iterations of images were generated using a variety of prompts. Collectively, 184 images were produced for evaluation of 391 characters. All images were independently analyzed by 3 reviewers for apparent gender and skin tone. Results: Collectively (individual and group characters) (n = 391), 60.6% were male and 87.7% were of a light skin tone. DALL-E 3 (65.6%), Midjourney 5.2 (76.7%), and Stable Diffusion 2.1 (56.2%) had a statistically higher representation of men than Firefly 2 (42.9%) (P < 0.0001). With Firefly 2, 70.3% of characters had light skin tones, which was statistically lower (P < 0.0001) than for Stable Diffusion 2.1 (84.8%), Midjourney 5.2 (100%), and DALL-E 3 (94.8%). Overall, image quality metrics were average or better in 87.2% for DALL-E 3 and 86.2% for Midjourney 5.2, whereas 50.9% were inadequate or poor for Firefly 2 and 86.0% for Stable Diffusion 2.1. Conclusion: Generative AI text-to-image generation using DALL-E 3 via GPT-4 has the best overall quality compared with Firefly 2, Midjourney 5.2, and Stable Diffusion 2.1. Nonetheless, DALL-E 3 includes inherent biases associated with gender and ethnicity that demand more critical evaluation.

Blind Recognition of Frame Synchronization Based on Deep Learning.

In this paper, a deep-learning-based frame synchronization blind recognition algorithm is proposed to improve the detection performance in non-cooperative communication systems. Current methods face challenges in accurately detecting frames under high bit error rates (BER). Our approach begins with flat-top interpolation of binary data and converting it into a series of grayscale images, enabling the application of image processing techniques. By incorporating a scaling factor, we generate RGB images. Based on the matching radius, frame length, and frame synchronization code, RGB images with distinct stripe features are classified as positive samples for each category, while the remaining images are classified as negative samples. Finally, the neural network is trained on these sets to classify test data effectively. Simulation results demonstrate that the proposed algorithm achieves a 100% probability in frame recognition when BER is below 0.2. Even with a BER of 0.25, the recognition probability remains above 90%, which exhibits a performance improvement of over 60% compared with traditional algorithms. This work addresses the shortcomings of existing methods under high error conditions, and the idea of converting sequences into RGB images also provides a reliable solution for frame synchronization in challenging communication environments.

3D micromorphological reconstruction and roughness characterization of wood surface based on sequence images

A novel non-contact optical inspection technique is proposed to precisely reconstruct the three-dimensional surface structure of wood and evaluate its roughness. The feasibility of using image fusion techniques to characterize the 3D roughness of wood surfaces is explored by combining high-resolution serial image acquisition techniques with advanced data processing methods. The work focuses on examining various cut surfaces of three distinct wood species: Larch, Catalpa, and Toona sinensis. The proposed 3D roughness parameters are verified using 3D reconstruction and precise measurements. The experimental results demonstrate that the proposed method exhibits strong adaptability in measuring wood surface roughness and achieves a high degree of consistency with the results obtained from traditional digital microscope systems. This study not only validates the possible use of multilayer sequence image fusion technology in measuring wood roughness, but also establishes a solid basis for the creation of 3D assessment criteria for wood surface roughness and associated inspection systems.

Feasibility of thin-slice, low noise images created using multi-kernel synthesis to replace multiple image series in head CT.

SynthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON) is a multi-kernel synthesis method that creates a single series of thin-slice computed tomography (CT) images displaying low noise and high spatial resolution, increasing reader efficiency and minimizing partial volume averaging. To compare the diagnostic performance of a single set of ZIRCON images to two routine clinical image series using conventional CT head and bone reconstruction kernels for diagnosing intracranial findings and fractures in patients with trauma or suspected acute neurologic deficit. In total, 50 patients underwent clinically indicated head CT in the ER (15 normal, 35 abnormal cases). A non-reader neuroradiologist established the reference standard. Three neuroradiologists reviewed two routine clinical series (head and bone kernels) and a single ZIRCON series, detecting intracranial findings or fractures and rating confidence (0-100). Sensitivity, specificity, and jackknife free-response receiver operating characteristic (JAFROC) figure of merit (FOM) were compared (limit of non-inferiority: -0.10). ZIRCON and conventional images demonstrated comparable performance for fractures (sensitivity: 51.5% vs. 54.5%; specificity: 40.2% vs. 34.2%) and intracranial findings (sensitivity: 88.2% vs. 91.4%; specificity: 77.2% vs. 73.7%).The estimated difference of JAFROC FOM demonstrated ZIRCON non-inferiority for acute pathologies overall (0.003 [95% CI=-0.051-0.057]) and fractures (0.048 [95% CI=-0.050-0.145]) but not for intracranial findings alone (-0.024 [95% CI=-0.100-0.052]). Thin-slice, low noise, and high spatial resolution images can be created to display intracranial findings and fractures replacing multiple images series in head CT with similar performance. Future studies in more patients and further algorithmic development are warranted.

Diffuse meningeal melanocytosis – a silent culprit

Abstract Introduction/Objective Diffuse meningeal melanocytosis is a rare melanocytic proliferation that poses significant risk of severe hydrocephalus and mortality among children and young adults. Although the clonal melanocytes do not typically exhibit malignant morphological features, their capability for extensive invasion and malignant-like behavior necessitates tissue biopsy alongside immunohistochemical and molecular testing for definitive diagnosis. Methods/Case Report A 17-year-old male presented with progressive headaches, photophobia, and nausea, initially attributed to migraines. Neuro-opthalmological assessment revealed papilledema, leading to a diagnosis of idiopathic intracranial hypertension. Serial imaging showed fluctuating leptomeningeal enhancement and moderate communicating hydrocephalus without parenchymal lesions. Therapeutic lumbar punctures provided modest symptom improvement; increased opening pressure was observed. Evaluation of seven CSF specimens showed low glucose levels, increased cellularity consisting of bland appearing epithelioid cells of unknown etiology, and increased lymphocytes. Infectious causes were excluded. Due to the indeterminate CSF findings, discussion between the cytopathologist and neuro-opthamologist was crucial to facilitate tissue biopsy to exclude a neoplastic process. Subsequent shunt placement and cerebral cortex biopsy revealed neoplastic cells with sheet-like architecture coating the dura without overt brain invasion. The tumor cells had eosinophilic cytoplasm without pigment and enlarged nuclei with irregular contours, vesicular chromatin, and prominent nucleoli. No high-grade features were seen. Immunohistochemical stains were positive for MART1, HMB45, and PRAME, consistent with a melanocytic lesion. FISH melanoma panel was negative. The final diagnosis was diffuse meningeal melanocytic neoplasm, most consistent with meningeal melanocytosis. The patient received chemotherapy with improved symptoms and stable disease. Results (if a Case Study enter NA) NA Conclusion Diffuse meningeal melanocytosis is a challenging cytologic diagnosis as melanocytes can morphologically mimic lymphocytes and monocytes, and the low cellularity of CSF specimens often results in insufficient cell blocks for ancillary tests. The direct communication of the pathologist with the clinical team to correlate pathology, radiology, and clinical symptoms was essential to ensure the proper management of this patient.

B-FLOWS: Biofouling Focused Learning and Observation for Wide-Area Surveillance in Tidal Stream Turbines

Biofouling, the accumulation of marine organisms on submerged surfaces, presents significant operational challenges across various marine industries. Traditional detection methods are labor intensive and costly, necessitating the development of automated systems for efficient monitoring. The study presented in this paper focuses on detecting biofouling on tidal stream turbine blades using camera-based monitoring. The process begins with dividing the video into a series of images, which are then annotated to identify and select the bounding boxes containing objects to be detected. These annotated images are used to train YOLO version 8 to detect biofouled and clean blades in the images. The proposed approach is evaluated using metrics that demonstrate the superiority of this YOLO version compared to previous ones. To address the issue of misdetection, a data augmentation approach is proposed and tested across different YOLO versions, showing its effectiveness in improving detection quality and robustness.

6714 Bone And Radiologic Findings In Congenital Generalized Lipodystrophy: A Systematic Review

Abstract Disclosure: R.M. Tuska: None. M. Brush: None. A.A. Livinski: None. R.J. Brown: None. Congenital Generalized Lipodystrophy (CGL) is characterized by a near-total loss of subcutaneous adipose tissue, leading to severe metabolic and systemic comorbidities. CGL is most commonly caused by mutations in AGPAT2 (CGL1) and BSCL2 (CGL2) genes. Skeletal abnormalities such as diffuse sclerosis, lytic bone lesions, and high bone mineral density (BMD) have been recognized in many patients with CGL, but the radiologic and clinical features of these bone phenotypes remain ill-defined. The aim of this systematic review was to evaluate the bone manifestations and radiologic findings associated with CGL1 and CGL2. We searched 6 databases: CINAHL Plus, Embase, Global Index Medicus (WHO), PubMed, Scopus, and Web of Science: Core. We screened articles utilizing a dual reviewer process in Covidence. Included publications reported primary bone and radiologic findings in patients with CGL1 or CGL2. Exclusions comprised publications without full text, duplicate publications, those lacking bone measures, and review articles. Two reviewers extracted data using RedCap and assessed risk of bias. 270 records were screened and 37 records reporting 179 cases of CGL were included for data extraction. Among the 79 patients assessed for bone cysts, 49 (62%) exhibited lytic appearing lesions. Of these 49, 14 (29%) patients presented with symptomatic lesions, primarily manifesting as bone pain at the lesion site (n=6), or pathologic fracture at the lesion site (n=9). Bone biopsy (n=7) revealed thin trabeculae and extensive vascular proliferation at the lesion site. Bone marrow biopsies (n=2) and imaging (n=20) revealed normal hematopoietic marrow with a marked reduction in marrow fat. 12 patients underwent serial bone imaging revealing diffuse osteosclerosis and the absence of lytic lesions in early childhood. During adolescence, lytic lesions appeared and progressed throughout the proximal and distal ends of the long bones in the appendicular skeleton sparing the axial skeleton. Markers of bone turnover were within normal limits except for sclerostin, which was elevated in a cohort of 11 patients. High BMD (n= 65), advanced skeletal maturation (n= 49), diffuse osteosclerosis (n=30), scoliosis (n=8), pseudo-osteopoikilosis (n=6), coxa valga (n=5), enlarged epiphyses (n=7), and coarse trabeculae (n=8) were also reported. While leptin replacement therapy improved metabolic parameters in many patients, it did not reverse the high bone mineral density or significantly alter markers of bone turnover. Individuals with CGL exhibit a spectrum of skeletal abnormalities including lytic-appearing lesions, osteosclerosis, high bone mineral density, advanced skeletal maturation, and pseudo-osteopoikilosis. Further long-term follow-up is needed to comprehensively assess the progression of these lesions over the life course and to elucidate the mechanisms contributing to their development. Presentation: 6/2/2024

7762 A Unique Case Of Sepsis-Driven Bilateral Adrenal Hemorrhages In A Patient With HIT

Abstract Disclosure: A. Siddiqui: None. B. Shalit: None. H. Nadeem: None. Z. Khan: None. D. Pinkhasova: None. Introduction: Bilateral adrenal hemorrhages, commonly seen in the setting of sepsis as Waterhouse Friderichsen syndrome, is a rare life-threatening condition. This process is driven by the release of bacterial endotoxins leading to the activation of coagulation, fibrinolysis, and proinflammatory pathways. It is by a similar process that now non-septic hypercoagulable states, including heparin-induced thrombocytopenia (HIT), factor V Leiden and protein C resistance are also being recognized as etiologic for bilateral adrenal hemorrhaging. The following case demonstrates a combination of the two etiologies leading to adrenal insufficiency from bilateral adrenal hemorrhages. Clinical Case: A 48-year-old male presented to the emergency department with right upper quadrant pain, dyspnea, and a low-grade fever. Laboratory results indicated leukocytosis with a predominance of neutrophils. Initial computed tomography imaging revealed a 4 x 3.5 cm right lower lobe multi-loculated lung abscess and multiple right lower lobe segmental/subsegmental pulmonary emboli. The patient was started on a heparin drip and empiric antibiotics. Infectious disease was consulted to help determine the etiology of the lung abscess. Extensive workup including sputum, blood, fungal cultures, and acid-fast bacillus smear testing were negative. The patient improved on routine broad-spectrum antibiotics and was planned to be transitioned to a direct oral anticoagulant until serial imaging revealed incidental bilateral 4 cm adrenal hemorrhages. Endocrinology was emergently consulted; a random cortisol level was drawn and found to be low at 2.7 (3-17 µg/dL) with an elevated Adrenocorticotropic hormone (ACTH) level of 114 (6 - 50 pg/mL) indicative of primary adrenal insufficiency. The patient subsequently became hypotensive and was started on stress-dose steroids. Upon further investigation, the patient was found to be thrombocytopenic, and hematology was involved. Based on his 4T score of 5, concern was raised for HIT and argatroban was initiated. Moreover, the patient was eventually stabilized for discharge with close follow-ups with endocrinology, infectious disease, and hematology as an outpatient. Conclusion: There have been 17 reported cases of bilateral adrenal hemorrhaging in the setting of HIT uniformly presenting with complete hemodynamic collapse. This case serves as even more unique given the added component of sepsis. Both sepsis and HIT respectively have been well established to pose individual risk for developing bilateral adrenal hemorrhages. Hence, we hope to highlight the importance of exploring all potential causes of adrenal insufficiency in the setting of bilateral adrenal hemorrhaging and emphasize the harms of anchoring to a single etiology. Presentation: 6/3/2024

A phenological-knowledge-independent method for automatic paddy rice mapping with time series of polarimetric SAR images

Paddy rice, which sustains more than half of the global population, requires accurate and efficient mapping to ensure food security. Synthetic aperture radar (SAR) has become indispensable in this process due to its remarkable ability to operate effectively in adverse weather conditions and its sensitivity to paddy rice growth. Phenological-knowledge-based (PKB) methods have been commonly employed in conjunction with time series of SAR images for paddy rice mapping, primarily because they eliminate the need for training datasets. However, PKB methods possess inherent limitations, primarily stemming from their reliance on precise phenological information regarding paddy rice growth. This information varies across regions and paddy rice varieties, making it challenging to use PKB methods effectively on a large spatial scale, such as the national or global scale, where collecting comprehensive phenological data becomes impractical. Moreover, variations in farming practices and field conditions can lead to differences in paddy rice growth stages even within the same region. Using a generalized set of phenological knowledge in PKB methods may not be suitable for all paddy fields, potentially resulting in errors in paddy rice extraction. To address the challenges posed by PKB methods, this study proposed an innovative approach known as the phenological-knowledge-independent (PKI) method for mapping paddy rice using time series of Sentinel-1 SAR images. The central innovation of the PKI method lies in its capability to map paddy rice without relying on specific knowledge of paddy rice phenology or the need for a training dataset. This was made possible by the incorporation of three novel metrics: VH and VV normalized maximum temporal changes (NMTC) and VH temporal mean, derived from the distinctions between paddy rice and other land cover types in time series of SAR images. The PKI method was rigorously evaluated across three regions in China, each featuring different paddy rice varieties. Additionally, the PKI method was compared with two prevalent phenological-knowledge-based techniques: the automated paddy rice mapping method using SAR flooding signals (ARM-SARFS) and the manual interpretation of unsupervised clustering results (MI-UCR). The PKI method achieved an average overall accuracy of 97.99%, surpassing the ARM-SARFS, which recorded an accuracy of 89.65% due to errors stemming from phenological disparities among different paddy fields. Furthermore, the PKI method delivered results on par with the MI-UCR, which relied on the fusion of SAR and optical image time series, achieving an accuracy of 97.71%. As demonstrated by these findings, the PKI method proves highly effective in mapping paddy rice across diverse regions, all without the need for phenological knowledge or a training dataset. Consequently, it holds substantial promise for efficiently mapping paddy rice on a large spatial scale. The source code used in this study is available at https://code.earthengine.google.com/f82cf10cad64fa3f971ae99027001a6e.

Construction of New MRI Contrast Agents for Spatiotemporal Visualization of Nitric Oxide in Ischemia/Reperfusion Organs.

Noninvasive and real-time nitric oxide (NO) visualization in vivo is still a challenge. Herein, we constructed a series of NO-responsive magnetic resonance imaging (MRI) contrast agents Gd1b-e by modifying Gd-DO3A using a bis-pyridyl-ethylamine side chain as a signal-amplifying moiety and o-phenylenediamine as a NO-responsive linker. It was found that Gd1b, d, and e can form macromolecular ternary complexes (Gd-Zn2+-HSA) with high longitudinal relaxivity (r1) (12.2-16.2 mM-1 s-1). Once reacting with NO, the o-phenylenediamine linker was hydrolyzed to produce a small molecular Gd complex with sharply decreased r1 (4.7-6.3 mM-1 s-1). Among them, Gd1d with a desirable pharmacokinetic profile (t1/2 = 5.91 h) could clearly distinguish the ischemia-reperfusion (IR) liver with excessive NO in rats. Meanwhile, the temporarily reduced amount of NO in the IR liver and brain by the NO scavenger 2-phenyl-4,4,5,5-tetramethylimidazoline-3-oxide-1-oxyl could enhance the signal of Gd1d, suggesting anticipated NO-responsive property. This research offers a new avenue for insight into the NO spatiotemporal property in multiple IR organs.

Baseline Platelet Count Predicts Infarct Size and Mortality after Acute Myocardial Infarction.

Platelets greatly contribute to cardiovascular diseases. We sought to explore the association of platelet counts with infarct size and outcome in patients presenting with acute ST-segment elevation MI (STEMI) treated with primary percutaneous coronary intervention (PPCI). In this retrospective study, we grouped 1,198 STEMI patients into tertiles (T) based on platelet count on admission: T1 = 102-206 [109 platelets/L] (n = 402), T2 = 207-259 [109 platelets/L] (n = 396), and T3 = 260-921 [109 platelets/L] (n = 400). Primary endpoint was 1-year all-cause mortality. Patients with highest platelet counts on admission showed the greatest area at risk and infarct size: area at risk (median) was 22.0% (interquartile range [IQR]: 12.0-39.8%) in T1, 21.0% (IQR: 11.0-37.1%) in T2, and 26.0% (IQR: 14.9-45.0%) of the left ventricle in T3 (p = 0.003); final infarct sizes after 7 to 14 days were as follows: 10.0% (IQR: 2.0-21.0%) in T1, 9.0% (IQR: 2.0-20.7%) in T2, and 12.0% (IQR: 3.0-27.3%) of the left ventricle in T3 (p = 0.015) as serial imaging revealed. At 1 year, 16 all-cause deaths occurred in T1, 5 in T2, and 22 in T3 (log-rank test, p = 0.006). After adjustment, T1 and T3 were associated with all-cause 1-year mortality (T1: hazard ratio [HR] = 3.40, 95% confidence interval [CI] = 1.23-9.54, p = 0.02; T3: HR = 3.55, 95% CI = 1.23-9.78, p = 0.01) compared with T2. At 5 years, all-cause mortality remained numerically higher in the T1 and T3. In patients with STEMI undergoing PPCI, low and high blood platelet levels on admission were associated with increased long-term mortality (Fig. 1).

Leveraging machine learning and Landsat time series for high-resolution mapping of mining-induced vegetation changes in Ouagadougou, Burkina Faso

Quarries are open pit mines, where construction materials such as granite and clay are extracted from the earth's surface, leading to a major disturbance of vegetation and subsequent degradation of ecosystem services. Assessing mining-associated degradation over time remains a challenge. This paper uses a temporal series of Landsat satellite image extracted from Google Earth Engine (GEE) for monitoring mining effects on land cover around the West African city of Ouagadougou, Burkina Faso. We conducted a binary classification of quarry and non-quarry using Landsat 9 images. To account for varying quarry patterns, we applied the LandTrendr algorithm to analyze images from 1990 to 2022, mapping annual vegetation disturbance and recovery. This generated high-resolution land cover maps with over 90 % accuracy across 257 quarries (38 km²). LandTrendr identified disturbance years with 87 % accuracy and assessed recovery in abandoned quarries. Remote sensing accuracy was validated through fieldwork and analysis of historical aerial photos. Our findings revealed that major disturbances coincided with new quarrying activities, particularly during urban expansion from 2005 to 2019, with NDVI decreasing by 0.3 in active mining areas. Vegetation recovery was observed in 23 % of the abandoned quarries, with NDVI increases by 0.15 within five years post abandonment, particularly in clay quarries. The strongest recovery occurred in given up abandoned from 2015 to 2019, aligned with increased conservation efforts. Our approach offers valuable insights into mining impacts and vegetation resilience in semi-arid environments, informing sustainable urban planning and environmental management in rapidly transforming regions of West Africa.

Dynamic digital image correlation method for rolling convective contact

Digital image correlation (DIC) is an increasingly popular and effective non-contact method for measuring full-field displacements and strains of deformable bodies under load. Current DIC methods applied to bodies undergoing large displacements and rotations require a large measurement area for both the reference (i.e., undeformed) image and the deformed images. This can limit the resulting resolution of the displacement and strain fields. To address this issue, we propose a two-stage dynamic DIC method capable of measuring displacements and strains under material convection with high resolution. During the first stage, the reference image is assembled from smaller, high-resolution images of the undeformed object obtained using a spatially-fixed or moving frame. Following capture, each sub-image is rigidly translated and rotated into its appropriate place, thereby producing a full, high-resolution image of the reference body. In stage two, images of the loaded and deformed body, again obtained using a small camera frame with high resolution, are aligned with matching regions of the undeformed composite image using BRISK feature detection before performing DIC. We demonstrate the method on a contact problem whereby an elastomeric roller travels along a rigid surface. In doing so, we obtain fine-resolution measurements of the state of strain of the region of the roller sidewall in contact with the substrate, even as new material convects through the region of interest. We present these measurements as a series of images and videos capturing strain evolution as the roller transitions from static loads to a fully dynamic steady-state, documenting the effectiveness of the method.

Interpreting the Projected Frontal Area in Front Crawl: Determining the Projected Frontal Area of Each Body Segment.

This study aimed to provide evidence for the interpretation of the projected frontal area (PFA) during front crawl. To achieve this goal, we developed a method for calculating the PFA of each body segment using digital human technology and compared the pressure drag under two calculation conditions: a combination of the PFA with and without accounting for the horizontal velocity of each body segment. Twelve competitive male swimmers performed a 15-meter front crawl at 1.20 m·s-1. The three-dimensional positions of the reflective markers attached to the swimmer's body were recorded using an underwater motion-capture system. Based on the body shape of each swimmer obtained from the photogenic body scanner, individual digital human body models were created with the color of the model's vertices divided into eight body segments. The time series of the volumetric swimming motion was reconstructed using inverse kinematics. The PFA of each body segment was then calculated by the automatic processing of a series of parallel frontal images. The pressure drag index, defined as the value excluding the drag coefficient while simultaneously considering the PFA and the horizontal velocity, was calculated under two conditions: the static condition (accounting for only the PFA of each body segment) and the dynamic condition (accounting for the PFA and horizontal velocity of each body segment). Notably, the pressure drag index was higher under the static condition than under the dynamic condition for the humerus, ulna, and hand segments (p < 0.001). The results obtained using our methodology indicate that the PFA of the upper limb segments overestimates their contribution to pressure drag during front crawl under the static condition.

Incidentally detected noninfectious thoracic aortitis: A clinical approach.

Noninfectious aortitis is occasionally detected incidentally, either on imaging or on histopathologic review after open thoracic aortic surgery. It can present as a clinically asymptomatic, seemingly focal lesion, as diffuse inflammation throughout several aortic segments but sparing the branch vessels, or as a manifestation of a widespread systemic condition. Treatment differs based on etiology, so once identified, all patients with aortitis need a thorough evaluation, laboratory tests, complete large-vessel imaging, and a referral to a vasculitis expert. All patients with aortitis are at high risk of future vascular complications and should be followed with serial clinical evaluations and imaging.

Serial Multiparametric Kidney Magnetic Resonance Imaging in a Prospective Cohort of Patients with AKI

Serial Multiparametric Kidney Magnetic Resonance Imaging in a Prospective Cohort of Patients with AKI

Overview of ADNI MRI.

The magnetic resonance imaging (MRI) Core has been operating since Alzheimer's Disease Neuroimaging Initiative's (ADNI) inception, providing 20 years of data including reliable, multi-platform standardized protocols, carefully curated image data, and quantitative measures provided by expert investigators. The overarching purposes of the MRI Core include: (1) optimizing and standardizing MRI acquisition methods, which have been adopted by many multicenter studies and trials worldwide and (2) providing curated images and numeric summary values from relevant MRI sequences/contrasts to the scientific community. Over time, ADNI MRI has become increasingly complex. To remain technically current, the ADNI MRI protocol has changed substantially over the past two decades. The ADNI 4 protocol contains nine different imaging types (e.g., three dimensional [3D] T1-weighted and fluid-attenuated inversion recovery [FLAIR]). Our view is that the ADNI MRI data are a greatly underutilized resource. The purpose of this paper is to educate the scientific community on ADNI MRI methods and content to promote greater awareness, accessibility, and use. HIGHLIGHTS: The MRI Core provides multi-platform standardized protocols, carefully curated image data, and quantitative analysis by expert groups. The ADNI MRI protocol has undergone major changes over the past two decades to remain technically current. As of April 25, 2024, the following numbers of image series are available: 17,141 3D T1w; 6877 FLAIR; 3140 T2/PD; 6623 GRE; 3237 dMRI; 2846 ASL; 2968 TF-fMRI; and 2861 HighResHippo (see Table 1 for abbreviations). As of April 25, 2024, the following numbers of quantitative analyses are available: FreeSurfer 10,997; BSI 6120; tensor based morphometry (TBM) and TBM-SYN 12,019; WMH 9944; dMRI 1913; ASL 925; TF-fMRI NFQ 2992; and medial temporal subregion volumes 2726 (see Table 4 for abbreviations). ADNI MRI is an underutilized resource that could be more useful to the research community.

Gender Bias in Text-to-Image Generative Artificial Intelligence When Representing Cardiologists

Introduction: While the global medical graduate and student population is approximately 50% female, only 13–15% of cardiologists and 20–27% of training fellows in cardiology are female. The potentially transformative use of text-to-image generative artificial intelligence (AI) could improve promotions and professional perceptions. In particular, DALL-E 3 offers a useful tool for promotion and education, but it could reinforce gender and ethnicity biases. Method: Responding to pre-specified prompts, DALL-E 3 via GPT-4 generated a series of individual and group images of cardiologists. Overall, 44 images were produced, including 32 images that contained individual characters and 12 group images that contained between 7 and 17 characters. All images were independently analysed by three reviewers for the characters’ apparent genders, ages, and skin tones. Results: Among all images combined, 86% (N = 123) of cardiologists were depicted as male. A light skin tone was observed in 93% (N = 133) of cardiologists. The gender distribution was not statistically different from that of actual Australian workforce data (p = 0.7342), but this represents a DALL-E 3 gender bias and the under-representation of females in the cardiology workforce. Conclusions: Gender bias associated with text-to-image generative AI when using DALL-E 3 among cardiologists limits its usefulness for promotion and education in addressing the workforce gender disparities.