Use of Point-of-Care Ultrasound to Diagnose a Ruptured Splenic Hemangioma.

An 89-year-old female presented to the emergency department (ED) with hypotension and altered mental status. The patient had no external signs of trauma or hemorrhage and no abdominal tenderness on examination. The patient remained hypotensive after initial fluid resuscitation, and laboratory testing revealed a significant anemia. Point-of-care ultrasound (POCUS) was used to perform a rapid ultrasound in shock (RUSH) exam in an attempt to uncover the etiology of undifferentiated hypotension. The exam displayed free fluid in the right upper quadrant and the left upper quadrant exam demonstrated a large splenic lesion with mixed echogenicity. Subsequent computed tomography (CT) of the abdomen and pelvis with intravenous contrast suggested a ruptured hemorrhagic splenic cyst, and the patient underwent an emergent splenectomy for hemorrhage control. Operative pathologic examination revealed the cystic lesion to be a splenic hemangioma. This case report highlights the utility of the Rapid Ultrasound for Shock and Hypotension (RUSH) protocol when evaluating patients with undifferentiated nontraumatic shock, and a rare cause of spontaneous intra-abdominal hemorrhage.

A redox switch allows binding of Fe(II) and Fe(III) ions in the cyanobacterial iron-binding protein FutA from Prochlorococcus.

The marine cyanobacterium Prochlorococcus is a main contributor to global photosynthesis, whilst being limited by iron availability. Cyanobacterial genomes generally encode two different types of FutA iron-binding proteins: periplasmic FutA2 ABC transporter subunits bind Fe(III), while cytosolic FutA1 binds Fe(II). Owing to their small size and their economized genome Prochlorococcus ecotypes typically possess a single futA gene. How the encoded FutA protein might bind different Fe oxidation states was previously unknown. Here, we use structural biology techniques at room temperature to probe the dynamic behavior of FutA. Neutron diffraction confirmed four negatively charged tyrosinates, that together with a neutral water molecule coordinate iron in trigonal bipyramidal geometry. Positioning of the positively charged Arg103 side chain in the second coordination shell yields an overall charge-neutral Fe(III) binding state in structures determined by neutron diffraction and serial femtosecond crystallography. Conventional rotation X-ray crystallography using a home source revealed X-ray-induced photoreduction of the iron center with observation of the Fe(II) binding state; here, an additional positioning of the Arg203 side chain in the second coordination shell maintained an overall charge neutral Fe(II) binding site. Dose series using serial synchrotron crystallography and an XFEL X-ray pump-probe approach capture the transition between Fe(III) and Fe(II) states, revealing how Arg203 operates as a switch to accommodate the different iron oxidation states. This switching ability of the Prochlorococcus FutA protein may reflect ecological adaptation by genome streamlining and loss of specialized FutA proteins.

Five historical innovations that have shaped modern orthopaedic surgery.

Throughout history, many innovations have contributed to the development of modern orthopaedic surgery, improving patient outcomes and expanding the range of treatment options available to patients. This article explores five key historical innovations that have shaped modern orthopaedic surgery: X-ray imaging, bone cement, the Thomas splint, the Pneumatic tourniquet and robotic-assisted surgery. We will review the development, impact and significance of each innovation, highlighting their contributions to the field of orthopaedic surgery and their ongoing relevance in contemporary and perioperative practice.

An overview of bone cement: Perioperative considerations, complications, outcomes and future implications.

Polymethyl methacrylate is commonly known as bone cement and is widely used for implant fixation in various orthopaedic arthroplasty and trauma surgery. The first bone cement use in orthopaedics is widely accredited to the famous English surgeon, John Charnley, who in 1958, used it for total hip arthroplasty. Since then, there have been many developments in cementing techniques in arthroplasty surgery. This overview aims to cover the perioperative considerations of bone cement, including cementing techniques, current outcomes and complications such as bone cement implantation syndrome. The overview will additionally consider future developments involving bone cement in orthopaedic arthroplasty.

Should we recommend patellofemoral arthroplasties to patients?

Aims: With up to 40% of patients having patellofemoral joint osteoarthritis (PFJ OA), the two arthroplasty options are to replace solely the patellofemoral joint via patellofemoral arthroplasty (PFA), or the entire knee via total knee arthroplasty (TKA). The aim of this study was to assess postoperative success of second-generation PFAs compared to TKAs for patients treated for PFJ OA using patient-reported outcome measures (PROMs) and domains deemed important by patients following a patient and public involvement meeting. Methods: MEDLINE, EMBASE via OVID, CINAHL, and EBSCO were searched from inception to January 2022. Any study addressing surgical treatment of primary patellofemoral joint OA using second generation PFA and TKA in patients aged above 18 years with follow-up data of 30 days were included. Studies relating to OA secondary to trauma were excluded. ROB-2 and ROBINS-I bias tools were used. Results: A total of nine studies were included, made up of four randomized controlled trials (domain 1) and five cohort studies (domain 2). PROMs and knee function specific scores developed for reporting TKA were unable to detect any difference between PFA and TKA. There was no significant difference in complications between PFA and TKA. PFAs were found to have a better postoperative range of motion. Conclusion: TKA and PFA are both viable options for patients with primary PFJ OA. Over time, we have seen an emphasis on patient satisfaction and better quality of life. Recommending sacrificing healthy medial and lateral compartments to treat patellofemoral joint arthritis should be given further thought.

Host cell-based screening assays for identification of molecules targeting Pseudomonas aeruginosa cyclic di-GMP signaling and biofilm formation.

The rapid emergence of bacterial resistance to antibiotics in current use is occurring worldwide and poses a significant threat to global healthcare systems. Recent research to identify new effective anti-bacterial agents has focused on regulatory pathways as targets for interference. Regulatory mechanisms employing intracellular Bis-(3',5') cyclic di-guanylate (c-di-GMP) as a secondary messenger represent a distinct category of subjects. This molecule, c-di-GMP, is present in nearly all bacterial species and plays a pivotal role in governing various biological processes, encompassing antibiotic resistance, biofilm formation, and virulence. Alteration of the cellular concentrations of the nucleotide through modulation of associated signaling pathways has the potential to reduce biofilm formation or increase susceptibility of the biofilm bacteria to antibiotics. Here, we have developed a screen for compounds that alter c-di-GMP levels in Pseudomonas aeruginosa in co-culture with bronchial epithelial cells. Through the assay of 200 natural compounds, we were able to identify several substances showing promising effects on P. aeruginosa in a host biofilm infection model. Importantly, we detected compounds that inhibit c-di-GMP levels and showed significant influence on biofilm formation and virulence in P. aeruginosa in vitro and in vivo. Consequently, we offer proof-of-concept information regarding swift and practical drug screening assays, suitable for medium- to high-throughput applications, which target the c-di-GMP signaling pathways in this significant Gram-negative pathogen.

Stress Cardiomyopathy Following Thoracostomy Tube Placement and Hemothorax Drainage: A Case Report.

Stress cardiomyopathy (SCM) is a clinical phenomenon presenting symptoms suggestive of acute coronary syndrome and defined by acute, but transient, electrocardiogram (ECG) changes and left ventricular wall motion abnormalities. However, no obstructive coronary lesion is identified on catheterization, and pathognomic echocardiogram findings are typically encountered. Multiple causes have been posited in the literature (e.g., severe stress, anxiety, pain, comorbid illness, trauma). We present the case of a 46-year-old female who presented to the emergency department (ED) for delayed left-sided hemothorax (six weeks following a high-speed motor vehicle collision) and developed an acute SCM following large-bore chest tube placement. To our knowledge, no prior cases have been reported immediately following thoracostomy tube placement and hemothorax drainage in the ED setting. We explore possible mechanistic explanations related to our case, which adds to the existing literature on the subject.

Proof of Concept: Using ChatGPT to Teach Emergency Physicians How to Break Bad News.

Background Breaking bad news is an essential skill for practicing physicians, particularly in the field of emergency medicine (EM). Patient-physician communication teaching has previously relied on standardized patient scenarios and objective structured clinical examination formats. The novel use of artificial intelligence (AI) chatbot technology, such as Chat Generative Pre-trained Transformer (ChatGPT), may provide an alternative role in graduate medical education in this area. As a proof of concept, the author demonstrates how providing detailed prompts to the AI chatbot can facilitate the design of a realistic clinical scenario, enable active roleplay, and deliver effective feedback to physician trainees. Methods ChatGPT-3.5 language model was utilized to assist in the roleplay of breaking bad news. A detailed input prompt was designed to outline rules of play and grading assessment via a standardized scale. User inputs (physician role), chatbot outputs (patient role) and ChatGPT-generated feedback were recorded. Results ChatGPT set up a realistic training scenario on breaking bad news based on the initial prompt. Active roleplay as a patient in an emergency department setting was accomplished, and clear feedback was provided to the user through the application of the Setting up, Perception, Invitation, Knowledge, Emotions with Empathy, and Strategy or Summary (SPIKES) framework for breaking bad news. Conclusion The novel use of AI chatbot technology to assist educators is abundant with potential. ChatGPT was able to design an appropriate scenario, provide a means for simulated patient-physician roleplay, and deliver real-time feedback to the physician user. Future studies are required to expand use to a targeted group of EM physician trainees and provide best practice guidelines for AI use in graduate medical education.

Identification of Potential Antimicrobial Targets of Pseudomonas aeruginosa Biofilms through a Novel Screening Approach.

Pseudomonas aeruginosa is an opportunistic pathogen of considerable medical importance, owing to its pronounced antibiotic tolerance and association with cystic fibrosis and other life-threatening diseases. The aim of this study was to highlight the genes responsible for P. aeruginosa biofilm tolerance to antibiotics and thereby identify potential new targets for the development of drugs against biofilm-related infections. By developing a novel screening approach and utilizing a public P. aeruginosa transposon insertion library, several biofilm-relevant genes were identified. The Pf phage gene (PA0720) and flagellin gene (fliC) conferred biofilm-specific tolerance to gentamicin. Compared with the reference biofilms, the biofilms formed by PA0720 and fliC mutants were completely eliminated with a 4-fold-lower gentamicin concentration. Furthermore, the mreC, pprB, coxC, and PA3785 genes were demonstrated to play major roles in enhancing biofilm tolerance to gentamicin. The analysis of biofilm-relevant genes performed in this study provides important novel insights into the understanding of P. aeruginosa antibiotic tolerance, which will facilitate the detection of antibiotic resistance and the development of antibiofilm strategies against P. aeruginosa. IMPORTANCE Pseudomonas aeruginosa is an opportunistic pathogen of high medical importance and is one of the main pathogens responsible for the mortality of patients with cystic fibrosis. In addition to inherited antibiotic resistance, P. aeruginosa can form biofilms, defined as communities of microorganisms embedded in a self-produced matrix of extracellular polymeric substances adhering to each other and/or to a surface. Biofilms protect bacteria from antibiotic treatments and represent a major reason for antibiotic failure in the treatment of chronic infections caused by cystic fibrosis. Therefore, it is crucial to develop new therapeutic strategies aimed at specifically eradicating biofilms. The aim of this study was to generalize a novel screening method for biofilm research and to identify the possible genes involved in P. aeruginosa biofilm tolerance to antibiotics, both of which could improve the understanding of biofilm-related infections and allow for the identification of relevant therapeutic targets for drug development.

Bactericidal and anti-biofilm effects of uncharged and cationic ultrasound-responsive nitric oxide microbubbles on Pseudomonas aeruginosa biofilms.

Bacterial biofilms are a major and ongoing concern for public health, featuring both inherited genetic resistance traits and a conferred innate tolerance to traditional antibiotic therapies. Consequently, there is a growing need for novel methods of drug delivery, to increase the efficacy of antimicrobial agents. This research evaluated the anti-biofilm and bactericidal effects of ultrasound responsive gas-microbubbles (MBs) of either air or nitric oxide, using an in vitro Pseudomonas aeruginosa biofilm model grown in artificial wound medium. The four lipid-based MB formulations evaluated were room-air MBs (RAMBs) and nitric oxide MBs (NOMBs) with no electrical charge, as well as cationic (+) RAMBs+ and NOMBs+. Two principal treatment conditions were used: i) ultrasound stimulated MBs only, and ii) ultrasound stimulated MBs with a sub-inhibitory concentration (4 µg/mL) of the antibiotic gentamicin. The total treatment time was divided into a 60 second passive MB interaction period prior to 40 second ultrasound exposure; each MB formulation was tested in triplicate. Ultrasound stimulated RAMBs and NOMBs without antibiotic achieved reductions in biofilm biomass of 93.3% and 94.0%, respectively. Their bactericidal efficacy however was limited, with a reduction in culturable cells of 26.9% and 65.3%, respectively. NOMBs with sub-inhibitory antibiotic produced the most significant reduction in biofilm biomass, corresponding to a 99.9% (SD ± 5.21%); and a 99.9% (SD ± 0.07%) (3-log) reduction in culturable bacterial cells. Cationic MBs were initially manufactured to promote binding of MBs to negatively charged biofilms, but these formulations also demonstrated intrinsic bactericidal properties. In the absence of antibiotic, the bactericidal efficacy of RAMB+ and NOMB+ was greater that of uncharged counterparts, reducing culturable cells by 84.7% and 86.1% respectively; increasing to 99.8% when combined with antibiotic. This study thus demonstrates the anti-biofilm and bactericidal utility of ultrasound stimulated MBs, and specifically is the first to demonstrate the efficacy of a NOMB for the dispersal and potentiation of antibiotics against bacterial biofilms in vitro. Importantly the biofilm system and complex growth-medium were selected to recapitulate key morphological features of in vivo biofilms. The results us offer new insight for the development of new clinical treatments, for example, in chronic wounds.

Added value of mass characteristic frequency to 2-D shear wave elastography for differentiation of benign and malignant thyroid nodules.

Mass characteristic frequency (fmass) is a novel shear wave (SW) parameter that represents the ratio of the averaged minimum SW speed within the regions of interest to the largest dimension of the mass. Our study objective was to evaluate if the addition of fmass to conventional 2-D shear wave elastography (SWE) parameters would improve the differentiation of benign from malignant thyroid nodules. Our cohort comprised 107 patients with 113 thyroid nodules, of which 67 (59%) were malignant. Two-dimensional SWE data were obtained using the Supersonic Imagine Aixplorer ultrasound system equipped with a 44- to 15-MHz15-MHz linear array transducer. A receiver operating characteristic curve was generated based on a multivariable logistic regression analysis to evaluate the ability of SWE parameters with/without fmass and with/without clinical factors to discriminate benign from malignant thyroid nodules. The addition of fmass to conventional SW elasticity parameters increased the area under the curve from 0.808 to 0.871 (p = 0.02). The combination of SW elasticity parameters plus fmass plus clinical factors provided the strongest thyroid nodule malignancy probability estimate, with a sensitivity of 93.4% and specificity of 91.1% at the optimal threshold. In summary, fmass can be a valuable addition to conventional 2-D SWE parameters.

Economic significance of biofilms: a multidisciplinary and cross-sectoral challenge.

The increasing awareness of the significance of microbial biofilms across different sectors is continuously revealing new areas of opportunity in the development of innovative technologies in translational research, which can address their detrimental effects, as well as exploit their benefits. Due to the extent of sectors affected by microbial biofilms, capturing their real financial impact has been difficult. This perspective highlights this impact globally, based on figures identified in a recent in-depth market analysis commissioned by the UK's National Biofilms Innovation Centre (NBIC). The outputs from this analysis and the workshops organised by NBIC on its research strategic themes have revealed the breath of opportunities for translational research in microbial biofilms. However, there are still many outstanding scientific and technological challenges which must be addressed in order to catalyse these opportunities. This perspective discusses some of these challenges.

Multi-Excitation Raman Spectroscopy for Label-Free, Strain-Level Characterization of Bacterial Pathogens in Artificial Sputum Media.

The current methods for diagnosis of acute and chronic infections are complex and skill-intensive. For complex clinical biofilm infections, it can take days from collecting and processing a patient's sample to achieving a result. These aspects place a significant burden on healthcare providers, delay treatment, and can lead to adverse patient outcomes. We report the development and application of a novel multi-excitation Raman spectroscopy-based methodology for the label-free and non-invasive detection of microbial pathogens that can be used with unprocessed clinical samples directly and provide rapid data to inform diagnosis by a medical professional. The method relies on the differential excitation of non-resonant and resonant molecular components in bacterial cells to enhance the molecular finger-printing capability to obtain strain-level distinction in bacterial species. Here, we use this strategy to detect and characterize the respiratory pathogens Pseudomonas aeruginosa and Staphylococcus aureus as typical infectious agents associated with cystic fibrosis. Planktonic specimens were analyzed both in isolation and in artificial sputum media. The resonance Raman components, excited at different wavelengths, were characterized as carotenoids and porphyrins. By combining the more informative multi-excitation Raman spectra with multivariate analysis (support vector machine) the accuracy was found to be 99.75% for both species (across all strains), including 100% accuracy for drug-sensitive and drug-resistant S. aureus. The results demonstrate that our methodology based on multi-excitation Raman spectroscopy can underpin the development of a powerful platform for the rapid and reagentless detection of clinical pathogens to support diagnosis by a medical expert, in this case relevant to cystic fibrosis. Such a platform could provide translatable diagnostic solutions in a variety of disease areas and also be utilized for the rapid detection of anti-microbial resistance.

Role of the flagellar hook in the structural development and antibiotic tolerance of Pseudomonas aeruginosa biofilms.

Pseudomonas aeruginosa biofilms exhibit an intrinsic resistance to antibiotics and constitute a considerable clinical threat. In cystic fibrosis, a common feature of biofilms formed by P. aeruginosa in the airway is the occurrence of mutants deficient in flagellar motility. This study investigates the impact of flagellum deletion on the structure and antibiotic tolerance of P. aeruginosa biofilms, and highlights a role for the flagellum in adaptation and cell survival during biofilm development. Mutations in the flagellar hook protein FlgE influence greatly P. aeruginosa biofilm structuring and antibiotic tolerance. Phenotypic analysis of the flgE knockout mutant compared to the wild type (WT) reveal increased fitness under planktonic conditions, reduced initial adhesion but enhanced formation of microcolony aggregates in a microfluidic environment, and decreased expression of genes involved in exopolysaccharide formation. Biofilm cells of the flgE knock-out mutant display enhanced tolerance towards multiple antibiotics, whereas its planktonic cells show similar resistance to the WT. Confocal microscopy of biofilms demonstrates that gentamicin does not affect the viability of cells located in the inner part of the flgE knock-out mutant biofilms due to reduced penetration. These findings suggest that deficiency in flagellar proteins like FlgE in biofilms and in cystic fibrosis infections represent phenotypic and evolutionary adaptations that alter the structure of P. aeruginosa biofilms conferring increased antibiotic tolerance.

Preoperative Factors Affecting the Patient-Reported Outcome Measures following Total Knee Replacement: Socioeconomic Factors and Preoperative OKS Have a Clinically Meaningful Effect.

The Oxford Knee Score (OKS) is a patient-reported outcome questionnaire typically used to assess function and pain in patients undergoing total knee replacement (TKR). However, research is inconclusive as to which preoperative factors are important in explaining variation in outcome following TKR. The operative records of 12,709 patients who underwent primary TKR over a 9-year period were analyzed. The following variables were collected for each patient: age, sex, body mass index (BMI), Index of Multiple Deprivation decile rank, side of operation, diagnosis, the American Society of Anaesthesiologists (ASA) grade, preoperative OKS, EQ-5D index score, EuroQol visual analog scale (EQ-VAS) score, the postoperative OKS at 1 and 2 years. Generalized linear regression models were performed at 1 and 2 years to investigate the effect of the preoperative variables on the postoperative OKS. The effect of age, sex, BMI, Index of Multiple Deprivation decile rank, diagnosis, ASA grade, preoperative OKS, EuroQoL five-dimensional (EQ-5D) index score, and EQ-VAS score were all statistically significant in explaining the variation in OKS at 1 and 2 years postoperatively, with critical level of significance of 0.05 (5%). Being male aged 60 to 69 years of normal BMI, ASA grade I (fit and healthy), living in an affluent area, not reporting preoperative anxiety/depression, were associated with an enhanced mean postoperative OKS at both 1 and 2 years. When adjusted for potential confounding, age of 60-69 years, male sex, normal BMI, lower ASA grade, higher Index of Multiple Deprivation and higher pre-operative EQ-5D, EQ-VAS and OKS were identified as factors that resulted in higher post-operative OKS after primary TKR.

Phylogenetic Analysis with Prediction of Cofactor or Ligand Binding for Pseudomonas aeruginosa PAS and Cache Domains.

PAS domains are omnipresent building blocks of multidomain proteins in all domains of life. Bacteria possess a variety of PAS domains in intracellular proteins and the related Cache domains in periplasmic or extracellular proteins. PAS and Cache domains are predominant in sensory systems, often carry cofactors or bind ligands, and serve as dimerization domains in protein association. To aid our understanding of the wide distribution of these domains, we analyzed the proteome of the opportunistic human pathogen Pseudomonas aeruginosa PAO1 in silico. The ability of this bacterium to survive under different environmental conditions, to switch between planktonic and sessile/biofilm lifestyle, or to evade stresses, notably involves c-di-GMP regulatory proteins or depends on sensory pathways involving multidomain proteins that possess PAS or Cache domains. Maximum likelihood phylogeny was used to group PAS and Cache domains on the basis of amino acid sequence. Conservation of cofactor- or ligand-coordinating amino acids aided by structure-based comparison was used to inform function. The resulting classification presented here includes PAS domains that are candidate binders of carboxylic acids, amino acids, fatty acids, flavin adenine dinucleotide (FAD), 4-hydroxycinnamic acid, and heme. These predictions are put in context to previously described phenotypic data, often generated from deletion mutants. The analysis predicts novel functions for sensory proteins and sheds light on functional diversification in a large set of proteins with similar architecture. IMPORTANCE To adjust to a variety of life conditions, bacteria typically use multidomain proteins, where the modular structure allows functional differentiation. Proteins responding to environmental cues and regulating physiological responses are found in chemotaxis pathways that respond to a wide range of stimuli to affect movement. Environmental cues also regulate intracellular levels of cyclic-di-GMP, a universal bacterial secondary messenger that is a key determinant of bacterial lifestyle and virulence. We study Pseudomonas aeruginosa, an organism known to colonize a broad range of environments that can switch lifestyle between the sessile biofilm and the planktonic swimming form. We have investigated the PAS and Cache domains, of which we identified 101 in 70 Pseudomonas aeruginosa PAO1 proteins, and have grouped these by phylogeny with domains of known structure. The resulting data set integrates sequence analysis and structure prediction to infer ligand or cofactor binding. With this data set, functional predictions for PAS and Cache domain-containing proteins are made.

Comparing deep learning-based automatic segmentation of breast masses to expert interobserver variability in ultrasound imaging.

Deep learning is a powerful tool that became practical in 2008, harnessing the power of Graphic Processing Unites, and has developed rapidly in image, video, and natural language processing. There are ongoing developments in the application of deep learning to medical data for a variety of tasks across multiple imaging modalities. The reliability and repeatability of deep learning techniques are of utmost importance if deep learning can be considered a tool for assisting experts, including physicians, radiologists, and sonographers. Owing to the high costs of labeling data, deep learning models are often evaluated against one expert, and it is unknown if any errors fall within a clinically acceptable range. Ultrasound is a commonly used imaging modality for breast cancer screening processes and for visually estimating risk using the Breast Imaging Reporting and Data System score. This process is highly dependent on the skills and experience of the sonographers and radiologists, thereby leading to interobserver variability and interpretation. For these reasons, we propose an interobserver reliability study comparing the performance of a current top-performing deep learning segmentation model against three experts who manually segmented suspicious breast lesions in clinical ultrasound (US) images. We pretrained the model using a US thyroid segmentation dataset with 455 patients and 50,993 images, and trained the model using a US breast segmentation dataset with 733 patients and 29,884 images. We found a mean Fleiss kappa value of 0.78 for the performance of three experts in breast mass segmentation compared to a mean Fleiss kappa value of 0.79 for the performance of experts and the optimized deep learning model.

Quantitative assessment of ensemble coherency in contrast-free ultrasound microvasculature imaging.

PURPOSE: Contrast-free visualization of microvascular blood flow (MBF) using ultrasound can play a valuable role in diagnosis and detection of diseases. In this study, we demonstrate the importance of quantifying ensemble coherence for robust MBF imaging. We propose a novel approach to quantify ensemble coherence by estimating the local spatiotemporal correlation (LSTC) image, and evaluate its efficacy through simulation and in vivo studies. METHODS: The in vivo patient studies included three volunteers with a suspicious breast tumor, 15 volunteers with a suspicious thyroid tumor, and two healthy volunteers for renal MBF imaging. The breast data displayed negligible prior motion and were used for simulation analysis involving synthetically induced motion, to assess its impact on ensemble coherency and motion artifacts in MBF images. The in vivo thyroid data involved complex physiological motion due to its proximity to the pulsating carotid artery, which was used to assess the in vivo efficacy of the proposed technique. Further, in vivo renal MBF images demonstrated the feasibility of using the proposed ensemble coherence metric for curved array-based MBF imaging involving phase conversion. All ultrasound data were acquired at high imaging frame rates and the tissue signal was suppressed using spatiotemporal clutter filtering. Thyroid tissue motion was estimated using two-dimensional normalized cross correlation-based speckle tracking, which was subsequently used for ensemble motion correction. The coherence of the MBF image was quantified based on Casorati correlation of the Doppler ensemble. RESULTS: The simulation results demonstrated that an increase in ensemble motion corresponded with a decrease in ensemble coherency, which reciprocally degraded the MBF images. Further the data acquired from breast tumors demonstrated higher ensemble coherency than that from thyroid tumors. Motion correction improved the coherence of the thyroid MBF images, which substantially improved its visualization. The proposed coherence metrics were also useful in assessing the ensemble coherence for renal MBF imaging. The results also demonstrated that the proposed coherence metric can be reliably estimated from downsampled ensembles (by up to 90 % ), thus allowing improved computational efficiency for potential applications in real-time MBF imaging. CONCLUSIONS: This pilot study demonstrates the importance of assessing ensemble coherency in contrast-free MBF imaging. The proposed LSTC image quantified coherence of the Doppler ensemble for robust MBF imaging. The results obtained from this pilot study are promising, and warrant further development and in vivo validation.

Automatic Deep Learning Semantic Segmentation of Ultrasound Thyroid Cineclips Using Recurrent Fully Convolutional Networks.

Medical segmentation is an important but challenging task with applications in standardized report generation, remote medicine and reducing medical exam costs by assisting experts. In this paper, we exploit time sequence information using a novel spatio-temporal recurrent deep learning network to automatically segment the thyroid gland in ultrasound cineclips. We train a DeepLabv3+ based convolutional LSTM model in four stages to perform semantic segmentation by exploiting spatial context from ultrasound cineclips. The backbone DeepLabv3+ model is replicated six times and the output layers are replaced with convolutional LSTM layers in an atrous spatial pyramid pooling configuration. Our proposed model achieves mean intersection over union scores of 0.427 for cysts, 0.533 for nodules and 0.739 for thyroid. We demonstrate the potential application of convolutional LSTM models for thyroid ultrasound segmentation.