The Effect of Time Pressure on Motion Economy and Smoothness of Interventional Radiology Trainee Performance in Simulated Central Venous Line Placement.

PURPOSE: To evaluate the effect of being under time pressure on procedural performance using hand motion analysis. MATERIALS AND METHODS: Eight radiology trainees performed central venous access on a phantom while recording video and hand motion data using an electromagnetic motion tracker. Each trainee performed the procedure six times: the first three trials without any prompts (control), while for the next three, they were asked to perform the task as fast as possible (time pressure). Validated hand motion metrics were analyzed, and two blinded and independent evaluators rated procedural performance using a previously validated task-specific global rating scale (GRS). Motion/time ratios and linear mixed-effect methods were used to control for time, and constants for both strategies were compared. RESULTS: Hand motion analysis showed that trainees completed the simulated procedure faster under time pressure (46 ± 18 s vs. 56 ± 27 s, p = 0.008) than during the control strategy. However, when controlling for time, trainees moved their hands 79 more centimeters (p = 0.04), made 15 more translational movements (p = 0.003) and 18 more rotational movements (p = 0.01) when under time pressure compared to at their own pace. CONCLUSION: Although trainees could perform the procedure faster under time pressure, there was a deterioration in hand motion economy and smoothness. This suggests that hand motion metrics offer a more comprehensive assessment of technical performance than time alone.

Analyzing the Evolution of Needle and Ultrasound Probe Manipulation Skills of Interventional Radiology Trainees With Time and Experience.

PURPOSE: To test the hypothesis that hand motion analysis can measure the progression of needle and ultrasound probe manipulation skills of interventional radiology trainees in central venous line placement. MATERIALS AND METHODS: An expert cohort of 6 interventional radiologists and 4 anesthesiologists and a trainee cohort of 6 novice trainees (<50 central lines) and 5 experienced trainees (>50 central lines) performed simulated central venous access. Four novices and 1 experienced trainee repeated the task 1 year later. An electromagnetic motion tracking system tracked the needle hand and ultrasound probe. Path length, translational, and rotational movements were calculated separately for the needle hand and probe sensor. These metrics were used to calculate motion metrics based scores on a scale of 0 to 3 for each sensor. Nonparametric statistics were used, and the data are reported as median ± interquartile range. RESULTS: Comparing novice and experienced trainees, there was a significant difference in probe scores (experienced vs. novice: 1 ± 2 vs. 0 ± 0, P = 0.04) but not in needle-hand scores (1 ± 1.5 vs. 0 ± 1, P = 0.26). Trainees showed a significant increase in probe scores at the 1-year follow-up (baseline vs. follow-up: 0 ± 1 vs. 2.5 ± 1.8, P = 0.003), but no significant difference was observed in the needle manipulation metrics. Experts differed significantly from experienced trainees for all metrics for both sensors (P < 0.05), with the exception of the path length of the probe. CONCLUSIONS: Acquisition of improved dexterity of the probe may occur before improvement in the dexterity with the needle hand for interventional radiology trainees.

Evaluation of Technical Performance of Ultrasound-Guided Procedures through Hand Motion Analysis: An Exploration of Motion Metrics.

PURPOSE: To evaluate the ability of hand motion analysis using conventional and new motion metrics to differentiate between operators of varying levels of experience for central venous access (CVA) and liver biopsy (LB). MATERIALS AND METHODS: In the CVA task, 7 interventional radiologists (experts), 10 senior trainees, and 5 junior trainees performed ultrasound-guided CVA on a standardized manikin; 5 trainees were retested after 1 year. In the LB task, 4 radiologists (experts) and 7 trainees biopsied a lesion on a manikin. Conventional motion metrics (path length and task time), a refined metric (translational movements), and new metrics (rotational sum and rotational movements) were calculated. RESULTS: In the CVA task, experts outperformed trainees on all metrics (P < .02). Senior trainees required fewer rotational movements (P = .02), translational movements (P = .045), and time (P = .001) than junior trainees. Similarly, on 1-year follow-up, trainees had fewer translational (P = .02) and rotational (P = .003) movements with less task time (P = .003). The path length and rotational sum were not different between junior and senior trainees or for trainees on follow-up. Rotational and translational movements had greater area under the curve values (0.91 and 0.86, respectively) than the rotational sum (0.73) and path length (0.61). In the LB task, experts performed the task with a shorter path length (P = .04), fewer translational (P = .04) and rotational (P = .02) movements, and less time (P < .001) relative to the trainees. CONCLUSIONS: Hand motion analysis using translational and rotational movements was better at differentiating levels of experience and improvement with training than the conventional metric of path length.

Allergic Polysensitization Clusters: Newly Recognized Severity Marker in Urban Asthmatic Adults.

INTRODUCTION: While reliable, quantitative in vitro testing for sensitivity to aeroallergens has been available for decades, such information has largely been ignored in clustering analyses of asthma. Our aim is to explore allergic polysensitization as a possible marker of asthma severity and, as such, to be considered as an integral marker in future asthma clustering analyses. METHODS: We constructed a database of sensitizations to the 25 aeroallergens in our geographic area (zone 1, Northeastern US) using the ImmunoCAP® in vitro assay. We used the Scikit-Learn® machine learning library for model-based clustering to identify allergic polysensitization clusters. Clusters were compared for differences in common office-based clinical markers of asthma. RESULTS: The database consisted of 509 patients. Unbiased machine learning identified ten clusters of increasing allergic polysensitization of varying sizes (n = 1-339) characterized by significant increases in mean serum immunoglobulin E (p < 0.001), peripheral blood eosinophil count (p < 0.001), and DLCO (p = 0.02). There was a significant decline in mean age at presentation (p < 0.001), FEV1/FVC (p = 0.01), and FEF25-75 (p = 0.002) with increasing allergic polysensitization. Finally, we identified two divergent paths for the poly-atopic march, one driven by perennial and the other by seasonal allergens. CONCLUSION: This pilot study showed that allergic polysensitization, using readily available qualitative and quantitative in vitro sensitization data, largely ignored in cluster analyses to date, may add further clinical precision in cluster analyses of asthma. We suggest the methods used here can be applied and tested using larger databases and aeroallergens present in diverse geographic regions.

Improving Teamwork Competencies in Human-Machine Teams: Perspectives From Team Science.

In response to calls for research to improve human-machine teaming (HMT), we present a "perspective" paper that explores techniques from computer science that can enhance machine agents for human-machine teams. As part of this paper, we (1) summarize the state of the science on critical team competencies identified for effective HMT, (2) discuss technological gaps preventing machines from fully realizing these competencies, and (3) identify ways that emerging artificial intelligence (AI) capabilities may address these gaps and enhance performance in HMT. We extend beyond extant literature by incorporating recent technologies and techniques and describing their potential for contributing to the advancement of HMT.

Mathematical modeling of mass and energy transport for thermoembolization.

Background: Thermoembolization presents a unique treatment alternative for patients diagnosed with hepatocellular carcinoma. The approach delivers a reagent that undergoes an exothermic chemical reaction and combines the benefits of embolic as well as thermal- and chemical-ablative therapy modalities. The target tissue and vascular bed are subjected to simultaneous hyperthermia, ischemia, and chemical denaturation in a single procedure. To guide optimal delivery, we developed a mathematical model for understanding the competing diffusive and convective effects observed in thermoembolization delivery protocols.Methods: A mixture theory formulation was used to mathematically model thermoembolization as chemically reacting transport of an electrophile, dichloroacetyl chloride (DCACl), within porous living tissue. Mass and energy transport of each relevant constituent are considered. Specifically, DCACl is injected into the vessels and exothermically reacts with water in the blood or tissue to form dichloroacetic acid and hydrochloric acid. Neutralization reactions are assumed instantaneous in this approach. We validated the mathematical model predictions of temperature using MR thermometry of the thermoembolization procedure performed in ex vivo kidney.Results: Mathematical modeling predictions of tissue death were highly dependent on the vascular geometry, injection pressure, and intrinsic amount of exothermic energy released from the chemical species, and were able to recapitulate the temperature distributions observed in MR thermometry.Conclusion: These efforts present a first step toward formalizing a mathematical model for thermoembolization and are promising for providing insight for delivery protocol optimization. While our approach captured the observed experimental temperature measurements, larger-scale experimental validation is needed to prioritize additional model complexity and fidelity.

Temperature mapping of exothermic in situ chemistry: imaging of thermoembolization via MR.

Purpose: MR temperature imaging (MRTI) was employed for visualizing the spatiotemporal evolution of the exotherm of thermoembolization, an investigative transarterial treatment for solid tumors. Materials and methods: Five explanted kidneys were injected with thermoembolic solutions, and monitored by MRTI. In three nonselective experiments, 5 ml of 4 mol/l dichloroacetyl chloride (DCA-Cl) solution in a hydrocarbon vehicle was injected via the main renal artery. For two of these three, MRTI temperature data were compared to fiber optic thermal probes. Another two kidneys received selective injections, treating only portions of the kidneys with 1 ml of 2 mol/l DCA-Cl. MRTI data were acquired and compared to changes in pre- and post-injection CT. Specimens were bisected and photographed for gross pathology 24 h post-procedure. Results: MRTI temperature estimates were within ±1 °C of the probes. In experiments without probes, MRTI measured increases of 30 °C. Some regions had not reached peak temperature by the end of the >18 min acquisition. MRTI indicated the initial heating occurred in the renal cortex, gradually spreading more proximally toward the main renal artery. Gross pathology showed the nonselective injection denatured the entire kidney whereas in the selective injections, only the treated territory was coagulated. Conclusion: The spatiotemporal evolution of thermoembolization was visualized for the first time using noninvasive MRTI, providing unique insight into the thermodynamics of thermoembolization. Précis Thermoembolization is being investigated as a novel transarterial treatment. In order to begin to characterize delivery of this novel treatment modality and aid translation from the laboratory to patients, we employ MR temperature imaging to visualize the spatiotemporal distribution of temperature from thermoembolization in ex vivo tissue.

Evaluation of an automated grid artifact detection system for quality control in digital mammography.

PURPOSE: Grid artifacts occur in digital mammography when synchronization between the grid assembly and generator is not achieved, including when malfunctions occur in the grid assembly or generator subsystems. Such artifacts are not explicitly monitored or evaluated by existing mammography quality control programs. In this study, we developed an automated method for quantifying the presence of grid artifacts in two-dimensional (2D) digital mammography images and assessed its utility as a supplement to existing quality control programs. METHODS: Four digital mammography systems (Hologic Dimensions 3D 5000) were configured to automatically transfer 2D images to a server where the strength of the grid pattern, γmax , was quantified using a template-matching algorithm and stored in amySQL database. This analysis was performed on both American College of Radiology (ACR) phantom and clinical images. Changes in γmax were compared with image quality and service records to establish preliminary action limits for physicist intervention for each type of image. These action limits were applied around selected service events to evaluate their clinical utility. RESULTS: All systems exhibited a gradual increase in γmax in ACR phantom images prior to having identical major components of the generator subsystem replaced, despite the absence of visible gridlines in the images. Retrospective analysis of phantom images suggested that physicists should consider AEC testing when γ max exceeds 0.050 and that clinical image quality may be affected when γ max exceeds 0.060. Eighteen of 19 visible grid artifacts were identified using a threshold γ max value of 0.065 in clinical images. Warning limits that indicate abnormal operation before visible degradation in image quality were also established. These warning limits were 0.046 and 0.041 for the 24 × 29 cm and 18 × 24 cm paddles, respectively. Specific malfunctions in the generator and grid subsystems can be detected by applying these limits. CONCLUSIONS: Automated monitoring of γ max provides useful information about the status of digital mammography units without affecting clinical operations. When used with appropriate action limits, this type of monitoring can help physicists identify specific equipment malfunctions before they would be detected by other quality control tests and before they affect clinical images.

Magnetic resonance and photoacoustic imaging of brain tumor mediated by mesenchymal stem cell labeled with multifunctional nanoparticle introduced via carotid artery injection.

OBJECTIVE: To evaluate the feasibility of visualizing bone marrow-derived human mesenchymal stem cells (MSCs) labeled with a gold-coated magnetic resonance (MR)-active multifunctional nanoparticle and injected via the carotid artery for assessing the extent of MSC homing in glioma-bearing mice. MATERIALS AND METHODS: Nanoparticles containing superparamagnetic iron oxide coated with gold (SPIO@Au) with a diameter of ∼82 nm and maximum absorbance in the near infrared region were synthesized. Bone marrow-derived MSCs conjugated with green fluorescent protein (GFP) were successfully labeled with SPIO@Au at 4 µg ml-1 and injected via the internal carotid artery in six mice bearing orthotopic U87 tumors. Unlabeled MSCs were used as a control. The ability of SPIO@Au-loaded MSCs to be imaged using MR and photoacoustic (PA) imaging at t = 0 h, 2 h, 24 h, and 72 h was assessed using a 7 T Bruker Biospec experimental MR scanner and a Vevo LAZR PA imaging system with a 5 ns laser as the excitation source. Histological analysis of the brain tissue was performed 72 h after MSC injection using GFP fluorescence, Prussian blue staining, and hematoxylin-and-eosin staining. RESULTS: MSCs labeled with SPIO@Au at 4 µg ml-1 did not exhibit cell death or any adverse effects on differentiation or migration. The PA signal in tumors injected with SPIO@Au-loaded MSCs was clearly more enhanced post-injection, as compared with the tumors injected with unlabeled MSCs at t = 72 h. Using the same mice, T2-weighted MR imaging results taken before injection and at t = 2 h, 24 h, and 72 h were consistent with the PA imaging results, showing significant hypointensity of the tumor in the presence of SPIO@Au-loaded MSCs. Histological analysis also showed co-localization of GFP fluorescence and iron, thereby confirming that SPIO@Au-labeled MSCs continue to carry their nanoparticle payloads even at 72 h after injection. CONCLUSIONS: Our results demonstrated the feasibility of tracking carotid artery-injected SPIO@Au-labeled MSCs in vivo via MR and PA imaging.

A heterogeneous tissue model for treatment planning for magnetic resonance-guided laser interstitial thermal therapy.

We evaluated a physics-based model for planning for magnetic resonance-guided laser interstitial thermal therapy for focal brain lesions. Linear superposition of analytical point source solutions to the steady-state Pennes bioheat transfer equation simulates laser-induced heating in brain tissue. The line integral of the photon attenuation from the laser source enables computation of the laser interaction with heterogeneous tissue. Magnetic resonance thermometry data sets (n = 31) were used to calibrate and retrospectively validate the model's thermal ablation prediction accuracy, which was quantified by the Dice similarity coefficient (DSC) between model-predicted and measured ablation regions (T > 57 °C). A Gaussian mixture model was used to identify independent tissue labels on pre-treatment anatomical magnetic resonance images. The tissue-dependent optical attenuation coefficients within these labels were calibrated using an interior point method that maximises DSC agreement with thermometry. The distribution of calibrated tissue properties formed a population model for our patient cohort. Model prediction accuracy was cross-validated using the population mean of the calibrated tissue properties. A homogeneous tissue model was used as a reference control. The median DSC values in cross-validation were 0.829 for the homogeneous model and 0.840 for the heterogeneous model. In cross-validation, the heterogeneous model produced a DSC higher than that produced by the homogeneous model in 23 of the 31 brain lesion ablations. Results of a paired, two-tailed Wilcoxon signed-rank test indicated that the performance improvement of the heterogeneous model over that of the homogeneous model was statistically significant (p < 0.01).

A methodology for thermal dose model parameter development using perioperative MRI.

Post-treatment imaging is the principal method for evaluating thermal lesions following image-guided thermal ablation procedures. While real-time temperature feedback using magnetic resonance temperature imaging (MRTI) is a complementary tool that can be used to optimise lesion size throughout the procedure, a thermal dose model is needed to convert temperature-time histories to estimates of thermal damage. However, existing models rely on empirical parameters derived from laboratory experiments that are not direct indicators of post-treatment radiologic appearance. In this work, we investigate a technique that uses perioperative MR data to find novel thermal dose model parameters that are tailored to the appearance of the thermal lesion on post-treatment contrast-enhanced imaging. Perioperative MR data were analysed for five patients receiving magnetic resonance-guided laser-induced thermal therapy (MRgLITT) for brain metastases. The characteristic enhancing ring was manually segmented on post-treatment T1-weighted imaging and registered into the MRTI geometry. Post-treatment appearance was modelled using a coupled Arrhenius-logistic model and non-linear optimisation techniques were used to find the maximum-likelihood kinetic parameters and dose thresholds that characterise the inner and outer boundary of the enhancing ring. The parameter values and thresholds were consistent with previous investigations, while the average difference between the predicted and segmented boundaries was on the order of one pixel (1 mm). The areas predicted using the optimised model parameters were also within 1 mm of those predicted by clinically utilised dose models. This technique makes clinically acquired data available for investigating new thermal dose model parameters driven by clinically relevant endpoints.

Referenceless magnetic resonance temperature imaging using Gaussian process modeling.

PURPOSE: During magnetic resonance (MR)-guided thermal therapies, water proton resonance frequency shift (PRFS)-based MR temperature imaging can quantitatively monitor tissue temperature changes. It is widely known that the PRFS technique is easily perturbed by tissue motion, tissue susceptibility changes, magnetic field drift, and modality-dependent applicator-induced artifacts. Here, a referenceless Gaussian process modeling (GPM)-based estimation of the PRFS is investigated as a methodology to mitigate unwanted background field changes. The GPM offers a complementary trade-off between data fitting and smoothing and allows prior information to be used. The end result being the GPM provides a full probabilistic prediction and an estimate of the uncertainty. METHODS: GPM was employed to estimate the covariance between the spatial position and MR phase measurements. The mean and variance provided by the statistical model extrapolated background phase values from nonheated neighboring voxels used to train the model. MR phase predictions in the heating ROI are computed using the spatial coordinates as the test input. The method is demonstrated in ex vivo rabbit liver tissue during focused ultrasound heating with manually introduced perturbations (n = 6) and in vivo during laser-induced interstitial thermal therapy to treat the human brain (n = 1) and liver (n = 1). RESULTS: Temperature maps estimated using the GPM referenceless method demonstrated a RMS error of <0.8°C with artifact-induced reference-based MR thermometry during ex vivo heating using focused ultrasound. Nonheated surrounding areas were <0.5°C from the artifact-free MR measurements. The GPM referenceless MR temperature values and thermally damaged regions were within the 95% confidence interval during in vivo laser ablations. CONCLUSIONS: A new approach to estimation for referenceless PRFS temperature imaging is introduced that allows for an accurate probabilistic extrapolation of the background phase. The technique demonstrated reliable temperature estimates in the presence of the background phase changes and was demonstrated useful in the in vivo brain and liver ablation scenarios presented.

Effect of pulse sequence parameter selection on signal strength in positive-contrast MRI markers for MRI-based prostate postimplant assessment.

PURPOSE: For postimplant dosimetric assessment, computed tomography (CT) is commonly used to identify prostate brachytherapy seeds, at the expense of accurate anatomical contouring. Magnetic resonance imaging (MRI) is superior to CT for anatomical delineation, but identification of the negative-contrast seeds is challenging. Positive-contrast MRI markers were proposed to replace spacers to assist seed localization on MRI images. Visualization of these markers under varying scan parameters was investigated. METHODS: To simulate a clinical scenario, a prostate phantom was implanted with 66 markers and 86 seeds, and imaged on a 3.0T MRI scanner using a 3D fast radiofrequency-spoiled gradient recalled echo acquisition with various combinations of scan parameters. Scan parameters, including flip angle, number of excitations, bandwidth, field-of-view, slice thickness, and encoding steps were systematically varied to study their effects on signal, noise, scan time, image resolution, and artifacts. RESULTS: The effects of pulse sequence parameter selection on the marker signal strength and image noise were characterized. The authors also examined the tradeoff between signal-to-noise ratio, scan time, and image artifacts, such as the wraparound artifact, susceptibility artifact, chemical shift artifact, and partial volume averaging artifact. Given reasonable scan time and managable artifacts, the authors recommended scan parameter combinations that can provide robust visualization of the MRI markers. CONCLUSIONS: The recommended MRI pulse sequence protocol allows for consistent visualization of the markers to assist seed localization, potentially enabling MRI-only prostate postimplant dosimetry.

Developmental changes in semantic knowledge organization.

Semantic knowledge is a crucial aspect of higher cognition. Theoretical accounts of semantic knowledge posit that relations between concepts provide organizational structure that converts information known about individual entities into an interconnected network in which concepts can be linked by many types of relations (e.g., taxonomic, thematic). The goal of the current research was to address several methodological shortcomings of prior studies on the development of semantic organization, by using a variant of the spatial arrangement method (SpAM) to collect graded judgments of relatedness for a set of entities that can be cross-classified into either taxonomic or thematic groups. In Experiment 1, we used the cross-classify SpAM (CC-SpAM) to obtain graded relatedness judgments and derive a representation of developmental changes in the organization of semantic knowledge. In Experiment 2, we validated the findings of Experiment 1 by using a more traditional pairwise similarity judgment paradigm. Across both experiments, we found that an early recognition of links between entities that are both taxonomically and thematically related preceded an increasing recognition of links based on a single type of relation. The utility of CC-SpAM for evaluating theoretical accounts of semantic development is discussed.

Estimating nanoparticle optical absorption with magnetic resonance temperature imaging and bioheat transfer simulation.

PURPOSE: Optically activated nanoparticle-mediated heating for thermal therapy applications is an area of intense research. The ability to characterise the spatio-temporal heating potential of these particles for use in modelling under various exposure conditions can aid in the exploration of new approaches for therapy as well as more quantitative prospective approaches to treatment planning. The purpose of this research was to investigate an inverse solution to the heat equation using magnetic resonance temperature imaging (MRTI) feedback, for providing optical characterisation of two types of nanoparticles (gold-silica nanoshells and gold nanorods). METHODS: The optical absorption of homogeneous nanoparticle-agar mixtures was measured during exposure to an 808 nm laser using real-time MRTI. A coupled finite element solution of heat transfer was registered with the data and used to solve the inverse problem. The L2 norm of the difference between the temperature increase in the model and MRTI was minimised using a pattern search algorithm by varying the absorption coefficient of the mixture. RESULTS: Absorption fractions were within 10% of literature values for similar nanoparticles. Comparison of temporal and spatial profiles demonstrated good qualitative agreement between the model and the MRTI. The weighted root mean square error was <1.5 σMRTI and the average Dice similarity coefficient for ΔT = 5 °C isotherms was >0.9 over the measured time interval. CONCLUSION: This research demonstrates the feasibility of using an indirect method for making minimally invasive estimates of nanoparticle absorption that might be expanded to analyse a variety of geometries and particles of interest.