Optimized raw data selection for artifact reduction of breathing controlled four-dimensional sequence scanning.

Background and purpose: Even with most breathing-controlled four-dimensional computed tomography (4DCT) algorithms image artifacts caused by single significant longer breathing still occur, resulting in negative consequences for radiotherapy. Our study presents first phantom examinations of a new optimized raw data selection and binning algorithm, aiming to improve image quality and geometric accuracy without additional dose exposure. Materials and methods: To validate the new approach, phantom measurements were performed to assess geometric accuracy (volume fidelity, root mean square error, Dice coefficient of volume overlap) for one- and three-dimensional tumor motion trajectories with and without considering motion hysteresis effects. Scans without significantly longer breathing cycles served as references. Results: Median volume deviations between optimized approach and reference of at maximum 1% were obtained considering all movements. In comparison, standard reconstruction yielded median deviations of 9%, 21% and 12% for one-dimensional, three-dimensional, and hysteresis motion, respectively. Measurements in one- and three-dimensional directions reached a median Dice coefficient of 0.970 ± 0.013 and 0.975 ± 0.012, respectively, but only 0.918 ± 0.075 for hysteresis motions averaged over all measurements for the optimized selection. However, for the standard reconstruction median Dice coefficients were 0.845 ± 0.200, 0.868 ± 0.205 and 0.915 ± 0.075 for one- and three-dimensional as well as hysteresis motions, respectively. Median root mean square errors for the optimized algorithm were 30 ± 16 HU2 and 120 ± 90 HU2 for three-dimensional and hysteresis motions, compared to 212 ± 145 HU2 and 130 ± 131 HU2 for the standard reconstruction. Conclusions: The algorithm was proven to reduce 4DCT-related artifacts due to missing projection data without further dose exposure. An improvement in radiotherapy treatment planning due to better image quality can be expected.

Development and Validation of a Deep-Learning-Based Algorithm for Detecting and Classifying Metallic Implants in Abdominal and Spinal CT Topograms.

PURPOSE: To develop and validate a deep-learning-based algorithm (DLA) that is designed to segment and classify metallic objects in topograms of abdominal and spinal CT. METHODS: DLA training for implant segmentation and classification was based on a U-net-like architecture with 263 annotated hip implant topograms and 2127 annotated spine implant topograms. The trained DLA was validated with internal and external datasets. Two radiologists independently reviewed the external dataset consisting of 2178 abdomen anteroposterior (AP) topograms and 515 spine AP and lateral topograms, all collected in a consecutive manner. Sensitivity and specificity were calculated per pixel row and per patient. Pairwise intersection over union (IoU) was also calculated between the DLA and the two radiologists. RESULTS: The performance parameters of the DLA were consistently >95% in internal validation per pixel row and per patient. DLA can save 27.4% of reconstruction time on average in patients with metallic implants compared to the existing iMAR. The sensitivity and specificity of the DLA during external validation were greater than 90% for the detection of spine implants on three different topograms and for the detection of hip implants on abdominal AP and spinal AP topograms. The IoU was greater than 0.9 between the DLA and the radiologists. However, the DLA training could not be performed for hip implants on spine lateral topograms. CONCLUSIONS: A prototype DLA to detect metallic implants of the spine and hip on abdominal and spinal CT topograms improves the scan workflow with good performance for both spine and hip implants.

Benchmarking machine learning-based real-time respiratory signal predictors in 4D SBRT.

BACKGROUND: Stereotactic body radiotherapy of thoracic and abdominal tumors has to account for respiratory intrafractional tumor motion. Commonly, an external breathing signal is continuously acquired that serves as a surrogate of the tumor motion and forms the basis of strategies like breathing-guided imaging and gated dose delivery. However, due to inherent system latencies, there exists a temporal lag between the acquired respiratory signal and the system response. Respiratory signal prediction models aim to compensate for the time delays and to improve imaging and dose delivery. PURPOSE: The present study explores and compares six state-of-the-art machine and deep learning-based prediction models, focusing on real-time and real-world applicability. All models and data are provided as open source and data to ensure reproducibility of the results and foster reuse. METHODS: The study was based on 2502 breathing signals ( t t o t a l ≈ 90 $t_{total} \approx 90$  h) acquired during clinical routine, split into independent training (50%), validation (20%), and test sets (30%). Input signal values were sampled from noisy signals, and the target signal values were selected from corresponding denoised signals. A standard linear prediction model (Linear), two state-of-the-art models in general univariate signal prediction (Dlinear, Xgboost), and three deep learning models (Lstm, Trans-Enc, Trans-TSF) were chosen. The prediction performance was evaluated for three different prediction horizons (480, 680, and 920 ms). Moreover, the robustness of the different models when applied to atypical, that is, out-of-distribution (OOD) signals, was analyzed. RESULTS: The Lstm model achieved the lowest normalized root mean square error for all prediction horizons. The prediction errors only slightly increased for longer horizons. However, a substantial spread of the error values across the test signals was observed. Compared to typical, that is, in-distribution test signals, the prediction accuracy of all models decreased when applied to OOD signals. The more complex deep learning models Lstm and Trans-Enc showed the least performance loss, while the performance of simpler models like Linear dropped the most. Except for Trans-Enc, inference times for the different models allowed for real-time application. CONCLUSION: The application of the Lstm model achieved the lowest prediction errors. Simpler prediction filters suffer from limited signal history access, resulting in a drop in performance for OOD signals.

A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems.

OBJECTIVES: The aim of this study was to introduce and evaluate a new metal artifact reduction framework (iMARv2) that addresses the drawbacks (residual artifacts after correction and user preferences for image quality) associated with the current clinically applied iMAR. MATERIALS AND METHODS: A new iMARv2 has been introduced, combining the current iMAR with new modular components to remove residual metal artifacts after image correction. The postcorrection image impression is adjustable with user-selectable strength settings. Phantom scans from an energy-integrating and a photon-counting detector CT were used to assess image quality, including a Gammex phantom and anthropomorphic phantoms. In addition, 36 clinical cases (with metallic implants such as dental fillings, hip replacements, and spinal screws) were reconstructed and evaluated in a blinded and randomized reader study. RESULTS: The Gammex phantom showed lower HU errors compared with the uncorrected image at almost all iMAR and iMARv2 settings evaluated, with only minor differences between iMAR and the different iMARv2 settings. In addition, the anthropomorphic phantoms showed a trend toward lower errors with higher iMARv2 strength settings. On average, the iMARv2 strength 3 performed best of all the clinical reconstructions evaluated, with a significant increase in diagnostic confidence and decrease in artifacts. All hip and dental cases showed a significant increase in diagnostic confidence and decrease in artifact strength, and the improvements from iMARv2 in the dental cases were significant compared with iMAR. There were no significant improvements in the spine. CONCLUSIONS: This work has introduced and evaluated a new method for metal artifact reduction and demonstrated its utility in routine clinical datasets. The greatest improvements were seen in dental fillings, where iMARv2 significantly improved image quality compared with conventional iMAR.

A Multimodal A* Algorithm to Solve the Two-Dimensional Optimization Problem of Accompanying a Person for an Intelligent Wheelchair.

Impaired mobility have far-reaching consequences for handicapped persons and their relatives. Mobile robotic technologies enable intelligent wheelchairs to regain mobility for those affected. Multiple research projects address human aware navigation and the task of following a person for assistive robots. But just a few projects focus on accompanying a person to enable social interaction. Therefore, we present a navigation system for indoor navigation in dynamic and cluttered environments as well as a novel algorithm for accompanying a person.First, we developed an autonomous driving wheelchair for indoor navigation based on the robot operating system (ROS). Thereby, a multi sensor setup using cameras and laser scanner enables localization within a map. People are detected by the same sensors and tracked by a Kalman filter. Afterwards we propose a novel algorithm to achieve a dynamic accompanying behaviour. An attractiveness distribution is introduced to evaluate the possible accompanying positions next to the manually selected target person regarding social interaction. The resulting two-dimensional optimization problem is solved by a novel multimodal extension of the A* algorithm.The proposed intelligent wheelchair is able to navigate in indoor environments and to accompany any person. In addition it allows social interaction while walking to relieve relatives or nursing staff, which otherwise need to push the wheelchair. The aim is to increase participation in everyday life for those affected.

Working from home and management controls.

The Covid-19 pandemic and the corresponding shift toward working from home (WFH) amplifies control problems within organizations and poses severe challenges for management control as employees' tasks are difficult to observe under WFH conditions. We examine the association between WFH and action controls. Based on a survey among employees in a large international corporation, we find that under WFH conditions the organization more intensively uses standardization and planning participation. We also examine the association between WFH and employee outcomes. The findings suggest that WFH is associated with more time employees spend in meetings and a higher job focus. Overall, the study adds to the literature by exploring the association between WFH and the use of management controls in organizations.

Dose reduction in sequence scanning 4D CT imaging through respiratory signal-guided tube current modulation: A feasibility study.

BACKGROUND: Respiratory signal-guided 4D CT sequence scanning such as the recently introduced Intelligent 4D CT (i4DCT) approach reduces image artifacts compared to conventional 4D CT, especially for irregular breathing. i4DCT selects beam-on periods during scanning such that data sufficiency conditions are fulfilled for each couch position. However, covering entire breathing cycles during beam-on periods leads to redundant projection data and unnecessary dose to the patient during long exhalation phases. PURPOSE: We propose and evaluate the feasibility of respiratory signal-guided dose modulation (i.e., temporary reduction of the CT tube current) to reduce the i4DCT imaging dose while maintaining high projection data coverage for image reconstruction. METHODS: The study is designed as an in-silico feasibility study. Dose down- and up-regulation criteria were defined based on the patients' breathing signals and their representative breathing cycle learned before and during scanning. The evaluation (including an analysis of the impact of the dose modulation criteria parameters) was based on 510 clinical 4D CT breathing curves. Dose reduction was determined as the fraction of the downregulated dose delivery time to the overall beam-on time. Furthermore, under the assumption of a 10-phase 4D CT and amplitude-based reconstruction, beam-on periods were considered negatively affected by dose modulation if the downregulation period covered an entire phase-specific amplitude range for a specific breathing phase (i.e., no appropriate reconstruction of the phase image possible for this specific beam-on period). Corresponding phase-specific amplitude bins are subsequently denoted as compromised bins. RESULTS: Dose modulation resulted in a median dose reduction of 10.4% (lower quartile: 7.4%, upper quartile: 13.8%, maximum: 28.6%; all values corresponding to a default parameterization of the dose modulation criteria). Compromised bins were observed in 1.0% of the beam-on periods (72 / 7370 periods) and affected 10.6% of the curves (54/510 curves). The extent of possible dose modulation depends strongly on the individual breathing patterns and is weakly correlated with the median breathing cycle length (Spearman correlation coefficient 0.22, p < 0.001). Moreover, the fraction of beam-on periods with compromised bins is weakly anti-correlated with the patient's median breathing cycle length (Spearman correlation coefficient -0.24; p < 0.001). Among the curves with the 17% longest average breathing cycles, no negatively affected beam-on periods were observed. CONCLUSION: Respiratory signal-guided dose modulation for i4DCT imaging is feasible and promises to significantly reduce the imaging dose with little impact on projection data coverage. However, the impact on image quality remains to be investigated in a follow-up study.

Bilingual resuscitation training does not affect adherence to resuscitation guidelines but reduces leadership skills and overall team performance. An observational study with cross-border German-Polish training.

Aim of study: This study aims to investigate feasibility and quality of a bilingual cardiopulmonary resuscitation training with interprofessional emergency teams from Germany and Poland. Methods: As part of a cross-border European Territorial Cooperation (Interreg-VA) funded project a combined communication and simulation training was organised. Teams of German and Polish emergency medicine personnel jointly practised resuscitation. The course was held in both languages with consecutive translation.Quality of chest compression was assessed using a simulator with feedback application. Learning objectives (quality of cardiopulmonary resuscitation, adherence to guidelines, closed loop communication), and team performance were assessed by an external observer. Coopers Team Emergency Assessment Measure questionnaire was used. Results: Twenty-one scenarios with 17 participants were analysed. In all scenarios, defibrillation and medication were delivered with correct dosage and at the right time. Mean fraction of correct hand position was 85.7% ± 25.7 [95%-CI 74.0; 97.4], mean fraction of compression depth 75.1% ± 21.0 [95%-CI 65.6; 84.7], compression rate 117.7 min-1 ± 7.1 [95%-CI 114.4; 120.9], and chest compression fraction 83.3% ± 3.8 [95%-CI 81.6; 85.0].Quality of cardiopulmonary resuscitation was rated as "fair" to "good", adherence to guidelines as "good", and closed loop communication as "fair". Bilingual teams demonstrated good situational awareness, but lack of leadership and suboptimal overall team performance. Conclusion: Bilingual and interprofessional cross-border resuscitation training in German and Polish tandem teams is feasible. It does not affect quality of technical skills such as high-quality chest compression but does affect performance of non-technical skills (e.g. closed loop communication and leadership).

Zn deficiency disrupts Cu and S homeostasis in Chlamydomonas resulting in over accumulation of Cu and Cysteine.

Growth of Chlamydomonas reinhardtii in zinc (Zn) limited medium leads to disruption of copper (Cu) homeostasis, resulting in up to 40-fold Cu over-accumulation relative to its typical Cu quota. We show that Chlamydomonas controls its Cu quota by balancing Cu import and export, which is disrupted in a Zn deficient cell, thus establishing a mechanistic connection between Cu and Zn homeostasis. Transcriptomics, proteomics and elemental profiling revealed that Zn-limited Chlamydomonas cells up-regulate a subset of genes encoding "first responder" proteins involved in sulfur (S) assimilation and consequently accumulate more intracellular S, which is incorporated into L-cysteine, γ-glutamylcysteine, and homocysteine. Most prominently, in the absence of Zn, free L-cysteine is increased ∼80-fold, corresponding to ∼2.8 × 109 molecules/cell. Interestingly, classic S-containing metal binding ligands like glutathione and phytochelatins do not increase. X-ray fluorescence microscopy showed foci of S accumulation in Zn-limited cells that co-localize with Cu, phosphorus and calcium, consistent with Cu-thiol complexes in the acidocalcisome, the site of Cu(I) accumulation. Notably, cells that have been previously starved for Cu do not accumulate S or Cys, causally connecting cysteine synthesis with Cu accumulation. We suggest that cysteine is an in vivo Cu(I) ligand, perhaps ancestral, that buffers cytosolic Cu.

Predominantly defective CD8+ T cell immunity to SARS-CoV-2 mRNA vaccination in lung transplant recipients.

BACKGROUND: Although mRNA vaccines have overall efficacy preventing morbidity/mortality from SARS-CoV-2 infection, immunocompromised persons remain at risk. Antibodies mostly prevent early symptomatic infection, but cellular immunity, particularly the virus-specific CD8+ T cell response, is protective against disease. Defects in T cell responses to vaccination have not been well characterized in immunocompromised hosts; persons with lung transplantation are particularly vulnerable to vaccine failure with severe illness. METHODS: Comparison groups included persons with lung transplantation and no history of COVID-19 (21 and 19 persons after initial mRNA vaccination and a third booster vaccination respectively), 8 lung transplantation participants recovered from COVID-19, and 22 non-immunocompromised healthy control individuals after initial mRNA vaccination (without history of COVID-19). Anti-spike T cell responses were assayed by stimulating peripheral blood mononuclear cells (PBMCs) with pooled small overlapping peptides spanning the SARS-CoV-2 spike protein, followed by intracellular cytokine staining (ICS) and flow cytometry for release of cytokines in response to stimulation, including negative controls (no peptide stimulation) and positive controls (phorbol myristate acetate [PMA] and ionomycin stimulation). To evaluate for low frequency memory responses, PBMCs were cultured in the presence of the mRNA-1273 vaccine for 14 days before this evaluation. RESULTS: Ionophore stimulation of PBMCs revealed a less inflammatory milieu in terms of interleukin (IL)-2, IL-4, and IL-10 profiling in lung transplantation individuals, reflecting the effect of immunosuppressive treatments. Similar to what we previously reported in healthy vaccinees, spike-specific responses in lung transplantation recipients were undetectable (< 0.01%) when tested 2 weeks after vaccination or later, but were detectable after in vitro culture of PBMCs with mRNA-1273 vaccine to enrich memory T cell responses. This was also seen in COVID-19-recovered lung transplantation recipients. Comparison of their enriched memory responses to controls revealed relatively similar CD4+ T cell memory, but markedly reduced CD8+ T cell memory both after primary vaccination or a booster dose. These responses were not correlated to age or time after transplantation. The vaccine-induced CD4+ and CD8+ responses correlated well in the healthy control group, but poorly in the transplantation groups. CONCLUSIONS: These results reveal a specific defect in CD8+ T cells, which have key roles both in transplanted organ rejection but also antiviral effector responses. Overcoming this defect will require strategies to enhance vaccine immunogenicity in immunocompromised persons.

A nonlinear scaling-based normalized metal artifact reduction to reduce low-frequency artifacts in energy-integrating and photon-counting CT.

BACKGROUND: Metal within the scan plane can cause severe artifacts when reconstructing X-ray computed tomography (CT) scans. Both in clinical use and recent research, normalized metal artifact reduction (NMAR) has established as the reference method for correcting metal artifacts, but NMAR introduces inconsistencies within the sinogram, which can cause additional low-frequency artifacts after image reconstruction. PURPOSE: This paper introduces an extension to NMAR by applying a nonlinear scaling function (NLS-NMAR) to reduce low-frequency artifacts, which get introduced by the reconstruction of interpolation-edge-related sinogram inconsistencies in the normalized sinogram domain. METHODS: After linear interpolation of the metal trace, an NLS function is applied in the prior-normalized sinogram domain to reduce the impact of the interpolation edges during filtered backprojection. After sinogram denormalization and image reconstruction, the low frequencies of the NLS image are combined with different high frequencies to restore anatomic details. An anthropomorphic dental phantom with removable metal inserts was utilized on two different CT systems to quantitatively assess the artifact reduction performance in terms of HU deviations and the root-mean-square-error within relevant regions of interest. Clinical dental examples were assessed to qualitatively demonstrate the problem of the interpolation-related blooming as well as to demonstrate the performance of the NLS function to reduce respective artifacts. To quantitatively prove HU consistency, HU values were assessed in central ROIs in the clinical cases. In addition, single clinical cases of a hip replacement and pedicle screws in the spine are shown to demonstrate the method's results in other body regions. RESULTS: The NLS-NMAR can minimize the effect of interpolation-related sinogram inconsistencies and thus reduce resulting hyperdense blooming artifacts. In the phantom results, the reconstructions with the NLS-NMAR-corrected low frequencies demonstrate the lowest error. In the qualitative assessment of the clinical data, the NLS-NMAR shows a tremendous enhancement in image quality, also performing best within all assessed images series. CONCLUSION: The NLS-NMAR provides a small yet effective extension to conventional NMAR by reducing low-frequency hyperdense metal trace-interpolation-related artifacts in computed tomography.

Iterative Metal Artifact Reduction in Head and Neck CT Facilitates Tumor Visualization of Oral and Oropharyngeal Cancer Obscured by Artifacts From Dental Hardware.

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate the diagnostic utility of iterative metal artifact reduction (iMAR) in computed tomography (CT)-imaging of oral and oropharyngeal cancers when obscured by dental hardware artifacts and to determine the most appropriate iMAR settings for this purpose. MATERIALS AND METHODS: The study retrospectively enrolled 27 patients (8 female, 19 male; mean age 64±12.7years) with histologically confirmed oral or oropharyngeal cancer obscured by dental artifacts in contrast-enhanced CT. Raw CT data were reconstructed with ascending iMAR strengths (levels 1/2/3/4/5) and one reconstruction without iMAR (level 0). For subjective analysis, two blinded radiologists rated tumor visualization and artifact severity on a five-point Likert scale. For objective analysis, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index (AI) were determined. RESULTS: iMAR reconstructions improved the subjective image quality of tumor edge and contrast, and the objective parameters of tumor SNR and CNR, reaching their optimum at iMAR levels 4 and 5 (P<.001). AI decreased with iMAR reconstructions reaching its minimum at iMAR level 5 (P<.001). Tumor detection rates increased 2.4-fold with iMAR 5, 2.1-fold with iMAR 4, and 1.9-fold with iMAR 3 compared to reconstructions without iMAR. Disadvantages such as algorithm-induced artifacts increased significantly with higher iMAR strengths (P<.05), reaching a maximum with iMAR 5. CONCLUSION: iMAR significantly improves CT imaging of oral and oropharyngeal cancers, as confirmed by both subjective and objective measures, with best results at highest iMAR strengths.

Cysteine: an ancestral Cu binding ligand in green algae?

Growth of Chlamydomonas reinhardtii in zinc (Zn) limited medium leads to disruption of copper (Cu) homeostasis, resulting in up to 40-fold Cu over-accumulation relative to its typical Cu quota. We show that Chlamydomonas controls its Cu quota by balancing Cu import and export, which is disrupted in a Zn deficient cell, thus establishing a mechanistic connection between Cu and Zn homeostasis. Transcriptomics, proteomics and elemental profiling revealed that Zn-limited Chlamydomonas cells up-regulate a subset of genes encoding "first responder" proteins involved in sulfur (S) assimilation and consequently accumulate more intracellular S, which is incorporated into L-cysteine, γ-glutamylcysteine and homocysteine. Most prominently, in the absence of Zn, free L-cysteine is increased ~80-fold, corresponding to ~ 2.8 × 10 9 molecules/cell. Interestingly, classic S-containing metal binding ligands like glutathione and phytochelatins do not increase. X-ray fluorescence microscopy showed foci of S accumulation in Zn-limited cells that co-localize with Cu, phosphorus and calcium, consistent with Cu-thiol complexes in the acidocalcisome, the site of Cu(I) accumulation. Notably, cells that have been previously starved for Cu do not accumulate S or Cys, causally connecting cysteine synthesis with Cu accumulation. We suggest that cysteine is an in vivo Cu(I) ligand, perhaps ancestral, that buffers cytosolic Cu.

Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT.

PURPOSE: 4D CT imaging is an integral part of 4D radiotherapy workflows. However, 4D CT data often contain motion artifacts that mitigate treatment planning. Recently, breathing-adapted 4D CT (i4DCT) was introduced into clinical practice, promising artifact reduction in in-silico and phantom studies. Here, we present an image quality comparison study, pooling clinical patient data from two centers: a new i4DCT and a conventional spiral 4D CT patient cohort. METHODS: The i4DCT cohort comprises 129 and the conventional spiral 4D CT cohort 417 4D CT data sets of lung and liver tumor patients. All data were acquired for treatment planning. The study consists of three parts: illustration of image quality in selected patients of the two cohorts with similar breathing patterns; an image quality expert rater study; and automated analysis of the artifact frequency. RESULTS: Image data of the patients with similar breathing patterns underline artifact reduction by i4DCT compared to conventional spiral 4D CT. Based on a subgroup of 50 patients with irregular breathing patterns, the rater study reveals a fraction of almost artifact-free scans of 89% for i4DCT and only 25% for conventional 4D CT; the quantitative analysis indicated a reduction of artifact frequency by 31% for i4DCT. CONCLUSION: The results demonstrate 4D CT image quality improvement for patients with irregular breathing patterns by breathing-adapted 4D CT in this first corresponding clinical data image quality comparison study.

[Early Psychiatric Patient Registration and the Case of Wuerttemberg]. / Das "Kataster für württembergische Psychiatriepatienten" und der Beginn der systematischen Patientenerfassung in der Psychiatrie.

This article provides both an analysis of the impact of medical statistics on psychiatric research as well as biographical information on one of its central protagonists, Württemberg medical doctor Wilhelm Weinberg. Against the background of the assumption of genetic inheritance of mental illnesses, a paradigm shift took place in the sense of a further development of so-called statistics for the insane. In addition to innovative diagnostics and nosology of the Kraepelin school, the study of human genetics was expected to become a promising step towards the predictability of mental illnesses. In particular, psychiatrist and racial hygienist Ernst Rüdin did thus integrate Weinberg's research findings. Weinberg became the founding figure of a central patient register in Wuerttemberg. During National Socialism, however, usage of this register shifted from being an instrument for research to one of establishing a hereditary biological inventory.

Persistent memory despite rapid contraction of circulating T Cell responses to SARS-CoV-2 mRNA vaccination.

Introduction: While antibodies raised by SARS-CoV-2 mRNA vaccines have had compromised efficacy to prevent breakthrough infections due to both limited durability and spike sequence variation, the vaccines have remained highly protective against severe illness. This protection is mediated through cellular immunity, particularly CD8+ T cells, and lasts at least a few months. Although several studies have documented rapidly waning levels of vaccine-elicited antibodies, the kinetics of T cell responses have not been well defined. Methods: Interferon (IFN)-γ enzyme-linked immunosorbent spot (ELISpot) assay and intracellular cytokine staining (ICS) were utilized to assess cellular immune responses (in isolated CD8+ T cells or whole peripheral blood mononuclear cells, PBMCs) to pooled peptides spanning spike. ELISA was performed to quantitate serum antibodies against the spike receptor binding domain (RBD). Results: In two persons receiving primary vaccination, tightly serially evaluated frequencies of anti-spike CD8+ T cells using ELISpot assays revealed strikingly short-lived responses, peaking after about 10 days and becoming undetectable by about 20 days after each dose. This pattern was also observed in cross-sectional analyses of persons after the first and second doses during primary vaccination with mRNA vaccines. In contrast, cross-sectional analysis of COVID-19-recovered persons using the same assay showed persisting responses in most persons through 45 days after symptom onset. Cross-sectional analysis using IFN-γ ICS of PBMCs from persons 13 to 235 days after mRNA vaccination also demonstrated undetectable CD8+ T cells against spike soon after vaccination, and extended the observation to include CD4+ T cells. However, ICS analyses of the same PBMCs after culturing with the mRNA-1273 vaccine in vitro showed CD4+ and CD8+ T cell responses that were readily detectable in most persons out to 235 days after vaccination. Discussion: Overall, we find that detection of spike-targeted responses from mRNA vaccines using typical IFN-γ assays is remarkably transient, which may be a function of the mRNA vaccine platform and an intrinsic property of the spike protein as an immune target. However, robust memory, as demonstrated by capacity for rapid expansion of T cells responding to spike, is maintained at least several months after vaccination. This is consistent with the clinical observation of vaccine protection from severe illness lasting months. The level of such memory responsiveness required for clinical protection remains to be defined.

Localized Induction Heating of Cu-Sn Layers for Rapid Solid-Liquid Interdiffusion Bonding Based on Miniaturized Coils.

Considering the demand for low temperature bonding in 3D integration and packaging of microelectronic or micromechanical components, this paper presents the development and application of an innovative inductive heating system using micro coils for rapid Cu-Sn solid-liquid interdiffusion (SLID) bonding at chip-level. The design and optimization of the micro coil as well as the analysis of the heating process were carried out by means of finite element method (FEM). The micro coil is a composite material of an aluminum nitride (AlN) carrier substrate and embedded metallic coil conductors. The conductive coil geometry is generated by electroplating of 500 µm thick copper into the AlN carrier. By using the aforementioned micro coil for inductive Cu-Sn SLID bonding, a complete transformation into the thermodynamic stable ε-phase Cu3Sn with an average shear strength of 45.1 N/mm2 could be achieved in 130 s by applying a bond pressure of 3 MPa. In comparison to conventional bonding methods using conduction-based global heating, the presented inductive bonding approach is characterized by combining very high heating rates of about 180 K/s as well as localized heating and efficient cooling of the bond structures. In future, the technology will open new opportunities in the field of wafer-level bonding.

In vivo assessment of tissue-specific radiological parameters with intra- and inter-patient variation using dual-energy computed tomography.

PURPOSE/OBJECTIVE: Experimental in vivo determination of radiological tissue parameters of organs in the head and pelvis within a large patient cohort, expanding on the current standard human tissue database summarized in ICRU46. MATERIAL/METHODS: Relative electron density (RED), effective atomic number (EAN) and stopping-power ratio (SPR) were obtained from clinical dual-energy CT scans using a clinically validated DirectSPR implementation and organ segmentations of 107 brain-tumor (brain, brainstem, spinal cord, chiasm, optical nerve, lens) and 120 pelvic cancer patients (prostate, kidney, liver, bladder). The impact of contamination by surrounding tissues on the tissue parameters was reduced with a dedicated contour adaption routine. Tissue parameters were characterized regarding the cohort mean value as well as the variation within each patient (2σintra) and between patients (2σinter). For the brain, age-dependent differences were determined. RESULTS: For 10 organs, including 4 structures not listed in ICRU46, the mean RED, EAN and SPR as well as their respective intra- and inter-patient variation were determined. SPR intra-patient variation was higher than 1.3% (1.3-4.6%) in all organs and always exceeded the inter-patient variation of the organ mean SPR (0.6-2.1%). For the brain, a significant SPR variation between pediatric and non-pediatric patients was determined. CONCLUSION: Radiological tissue parameters in the head and pelvis were characterized in vivo for a large patient cohort using dual-energy CT. This reassesses parts of the current standard database defined in ICRU46, furthermore complementing the data described in literature by smaller substructures in the brain as well as by the quantification of organ-specific inter- and intra-patient variation.

Nonlinearly scaled prior image-controlled frequency split for high-frequency metal artifact reduction in computed tomography.

PURPOSE: This paper introduces a new approach for the dedicated reduction of high-frequency metal artifacts, which applies a nonlinear scaling (NLS) transfer function on the high-frequency projection domain to reduce artifacts, while preserving edge information and anatomic detail by incorporating prior image information. METHODS: An NLS function is applied to suppress high-frequency streak artifacts, but to restrict the correction to metal projections only, scaling is performed in the sinogram domain. Anatomic information should be preserved and is excluded from scaling by incorporating a prior image from tissue classification. The corrected high-frequency sinogram is reconstructed and combined with the low-frequency component of a normalized metal artifact reduction (NMAR) image. Scans of different anthropomorphic phantoms were acquired (unilateral hip, bilateral hip, dental implants, and embolization coil). Multiple regions of interest (ROIs) were drawn around the metal implants and hounsfield unit (HU) deviations were analyzed. Clinical data sets including single image slices of dental fillings, a bilateral hip implant, spinal fixation screws, and an aneurysm coil were reconstructed and assessed. RESULTS: The prior image-controlled NLS can remove streak artifacts while preserving anatomic detail within the bone and soft tissue. The qualitative analysis of clinical cases showed a tremendous enhancement within dental fillings and neuro coils, and a significant enhancement within spinal screws or hip implants. The phantom scan measurements support this observation. In all phantom setups, the NLS-corrected result showed lowest HU derivation and the best visualization of the data. CONCLUSIONS: The prior image-controlled NLS provides a method to reduce high-frequency streaks in metal-corrupted computed tomography (CT) data.