Inflammation-Triggered Enlargement of Choroid Plexus in Subacute COVID-19 Patients with Neurological Symptoms.

OBJECTIVE: To investigate whether choroid plexus volumes in subacute coronavirus disease 2019 (COVID-19) patients with neurological symptoms could indicate inflammatory activation or barrier dysfunction and assess their association with clinical data. METHODS: Choroid plexus volumes were measured in 28 subacute COVID-19 patients via cerebral magnetic resonance imaging (MRI), compared with those in infection-triggered non-COVID-19 encephalopathy patients (n = 25), asymptomatic individuals after COVID-19 (n = 21), and healthy controls (n = 21). Associations with inflammatory serum markers (peak counts of leukocytes, C-reactive protein [CRP], interleukin 6), an MRI-based marker of barrier dysfunction (CSF volume fraction [V-CSF]), and clinical parameters like olfactory performance and cognitive scores (Montreal Cognitive Assessment) were investigated. RESULTS: COVID-19 patients showed significantly larger choroid plexus volumes than control groups (p < 0.001, η2 = 0.172). These volumes correlated significantly with peak leukocyte levels (p = 0.001, Pearson's r = 0.621) and V-CSF (p = 0.009, Spearman's rho = 0.534), but neither with CRP nor interleukin 6. No significant correlations were found with clinical parameters. INTERPRETATION: In patients with subacute COVID-19, choroid plexus volume is a marker of central nervous system inflammation and barrier dysfunction in the presence of neurologic symptoms. The absence of plexus enlargement in infection-triggered non-COVID-19 encephalopathy suggests a specific severe acute respiratory syndrome coronavirus 2 effect. This study also documents an increase in choroid plexus volume for the first time as a parainfectious event. ANN NEUROL 2024.

Cryo-EM structure of the fully assembled Elongator complex.

Transfer RNA (tRNA) molecules are essential to decode messenger RNA codons during protein synthesis. All known tRNAs are heavily modified at multiple positions through post-transcriptional addition of chemical groups. Modifications in the tRNA anticodons are directly influencing ribosome decoding and dynamics during translation elongation and are crucial for maintaining proteome integrity. In eukaryotes, wobble uridines are modified by Elongator, a large and highly conserved macromolecular complex. Elongator consists of two subcomplexes, namely Elp123 containing the enzymatically active Elp3 subunit and the associated Elp456 hetero-hexamer. The structure of the fully assembled complex and the function of the Elp456 subcomplex have remained elusive. Here, we show the cryo-electron microscopy structure of yeast Elongator at an overall resolution of 4.3 Å. We validate the obtained structure by complementary mutational analyses in vitro and in vivo. In addition, we determined various structures of the murine Elongator complex, including the fully assembled mouse Elongator complex at 5.9 Å resolution. Our results confirm the structural conservation of Elongator and its intermediates among eukaryotes. Furthermore, we complement our analyses with the biochemical characterization of the assembled human Elongator. Our results provide the molecular basis for the assembly of Elongator and its tRNA modification activity in eukaryotes.

The multi-subunit Elongator complex mediates the addition of a carboxymethyl group to wobble uridines in eukaryotic tRNAs. This tRNA modification is crucial to preserve the integrity of cellular proteomes and to protects us against severe neurodegenerative diseases. Elongator is organized in two distinct modules (i) the larger Elp123 subcomplex that binds and modifies the suitable tRNA substrate and (ii) the smaller Elp456 subcomplex that assists the release of the modified tRNA. The presented cryo-EM structures of Elongator show that the assemblies are very dynamic and undergo conformational rearrangements at consecutive steps of the process. Last but not least, the study provides a detailed reaction scheme and shows that the architecture of Elongator is highly conserved from yeast to mammals.

Cerebellar, Not Nigrostriatal Degeneration Impairs Dexterity in Multiple System Atrophy.

BACKGROUND: Multiple system atrophy (MSA) clinically manifests with either predominant nigrostriatal or cerebellopontine degeneration. This corresponds to two different phenotypes, one with predominant Parkinson's symptoms (MSA-P [multiple system atrophy-parkinsonian subtype]) and one with predominant cerebellar deficits (MSA-C [multiple system atrophy-cerebellar subtype]). Both nigrostriatal and cerebellar degeneration can lead to impaired dexterity, which is a frequent cause of disability in MSA. OBJECTIVE: The aim was to disentangle the contribution of nigrostriatal and cerebellar degeneration to impaired dexterity in both subtypes of MSA. METHODS: We thus investigated nigrostriatal and cerebellopontine integrity using diffusion microstructure imaging in 47 patients with MSA-P and 17 patients with MSA-C compared to 31 healthy controls (HC). Dexterity was assessed using the 9-Hole Peg Board (9HPB) performance. RESULTS: Nigrostriatal degeneration, represented by the loss of cells and neurites, leading to a larger free-fluid compartment, was present in MSA-P and MSA-C when compared to HCs. Whereas no intergroup differences were observed between the MSAs in the substantia nigra, MSA-P showed more pronounced putaminal degeneration than MSA-C. In contrast, a cerebellopontine axonal degeneration was observed in MSA-P and MSA-C, with stronger effects in MSA-C. Interestingly, the degeneration of cerebellopontine fibers is associated with impaired dexterity in both subtypes, whereas no association was observed with nigrostriatal degeneration. CONCLUSION: Cerebellar dysfunction contributes to impaired dexterity not only in MSA-C but also in MSA-P and may be a promising biomarker for disease staging. In contrast, no significant association was observed with nigrostriatal dysfunction. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Ultra-high-resolution photon-counting detector CT in evaluating coronary stent patency: a comparison to invasive coronary angiography.

OBJECTIVES: To determine the diagnostic accuracy of ultra-high-resolution photon-counting detector CT angiography (UHR PCD-CTA) for evaluating coronary stent patency compared to invasive coronary angiography (ICA). METHODS: Consecutive, clinically referred patients with prior coronary stent implantation were prospectively enrolled between August 2022 and March 2023 and underwent UHR PCD-CTA (collimation, 120 × 0.2 mm). Two radiologists independently analyzed image quality of the in-stent lumen using a 5-point Likert scale, ranging from 1 ("excellent") to 5 ("non-diagnostic"), and assessed all coronary stents for the presence of in-stent stenosis (≥ 50% lumen narrowing). The diagnostic accuracy of UHR PCD-CTA was determined, with ICA serving as the standard of reference. RESULTS: A total of 44 coronary stents in 18 participants (mean age, 83 years ± 6 [standard deviation]; 12 women) were included in the analysis. In 3/44 stents, both readers described image quality as non-diagnostic, whereas reader 2 noted a fourth stent to have non-diagnostic image quality. In comparison to ICA, UHR PCD-CTA demonstrated a sensitivity, specificity, and accuracy of 100% (95% CI [confidence interval] 47.8, 100), 92.3% (95% CI 79.1, 98.4), and 93.2% (95% CI 81.3, 98.6) for reader 1 and 100% (95% CI 47.8, 100), 87.2% (95% CI 72.6, 95.7), and 88.6% (95% CI 75.4, 96.2) for reader 2, respectively. Both readers observed a 100% negative predictive value (36/36 stents and 34/34 stents). Stent patency inter-reader agreement was 90.1%, corresponding to a substantial Cohen's kappa value of 0.72. CONCLUSIONS: UHR PCD-CTA enables non-invasive assessment of coronary stent patency with high image quality and diagnostic accuracy. CLINICAL RELEVANCE STATEMENT: Ultra-high-resolution photon-counting detector CT angiography represents a reliable and non-invasive method for assessing coronary stent patency. Its high negative predictive value makes it a promising alternative over invasive coronary angiography for the rule-out of in-stent stenosis. KEY POINTS: • CT-based evaluation of coronary stent patency is limited by stent-induced artifacts and spatial resolution. • Ultra-high-resolution photon-counting detector CT accurately evaluates coronary stent patency compared to invasive coronary angiography. • Photon-counting detector CT represents a promising method for the non-invasive rule-out of in-stent stenosis.

Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset.

PURPOSE: In cases of acute intracerebral hemorrhage (ICH) volume estimation is of prognostic and therapeutic value following minimally invasive surgery (MIS). The ABC/2 method is widely used, but suffers from inaccuracies and is time consuming. Supervised machine learning using convolutional neural networks (CNN), trained on large datasets, is suitable for segmentation tasks in medical imaging. Our objective was to develop a CNN based machine learning model for the segmentation of ICH and of the drain and volumetry of ICH following MIS of acute supratentorial ICH on a relatively small dataset. METHODS: Ninety two scans were assigned to training (n = 29 scans), validation (n = 4 scans) and testing (n = 59 scans) datasets. The mean age (SD) was 70 (± 13.56) years. Male patients were 36. A hierarchical, patch-based CNN for segmentation of ICH and drain was trained. Volume of ICH was calculated from the segmentation mask. RESULTS: The best performing model achieved a Dice similarity coefficient of 0.86 and 0.91 for the ICH and drain respectively. Automated ICH volumetry yielded high agreement with ground truth (Intraclass correlation coefficient = 0.94 [95% CI: 0.91, 0.97]). Average difference in the ICH volume was 1.33 mL. CONCLUSION: Using a relatively small dataset, originating from different CT-scanners and with heterogeneous voxel dimensions, we applied a patch-based CNN framework and successfully developed a machine learning model, which accurately segments the intracerebral hemorrhage (ICH) and the drains. This provides automated and accurate volumetry of the bleeding in acute ICH treated with minimally invasive surgery.

Impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion in patients with suspected stroke.

PURPOSE: CT perfusion of the brain is a powerful tool in stroke imaging, though the radiation dose is rather high. Several strategies for dose reduction have been proposed, including increasing the intervals between the dynamic scans. We determined the impact of temporal resolution on perfusion metrics, therapy decision, and radiation dose reduction in brain CT perfusion from a large dataset of patients with suspected stroke. METHODS: We retrospectively included 3555 perfusion scans from our clinical routine dataset. All cases were processed using the perfusion software VEOcore with a standard sampling of 1.5 s, as well as simulated reduced temporal resolution of 3.0, 4.5, and 6.0 s by leaving out respective time points. The resulting perfusion maps and calculated volumes of infarct core and mismatch were compared quantitatively. Finally, hypothetical decisions for mechanical thrombectomy following the DEFUSE-3 criteria were compared. RESULTS: The agreement between calculated volumes for core (ICC = 0.99, 0.99, and 0.98) and hypoperfusion (ICC = 0.99, 0.99, and 0.97) was excellent for all temporal sampling schemes. Of the 1226 cases with vascular occlusion, 14 (1%) for 3.0 s sampling, 23 (2%) for 4.5 s sampling, and 63 (5%) for 6.0 s sampling would have been treated differently if the DEFUSE-3 criteria had been applied. Reduction of temporal resolution to 3.0 s, 4.5 s, and 6.0 s reduced the radiation dose by a factor of 2, 3, or 4. CONCLUSION: Reducing the temporal sampling of brain perfusion CT has only a minor impact on image quality and treatment decision, but significantly reduces the radiation dose to that of standard non-contrast CT.

Value of virtual non-contrast images to identify uncomplicated cystic renal lesions: photon-counting detector CT vs. dual-energy integrating detector CT.

PURPOSE: To investigate the value of photon-counting detector CT (PCD-CT) derived virtual non-contrast (VNC) reconstructions to identify renal cysts in comparison with conventional dual-energy integrating detector (DE EID) CT-derived VNC reconstructions. MATERIAL AND METHODS: We prospectively enrolled consecutive patients with simple renal cysts (Bosniak classification-Version 2019, density ≤ 20 HU and/or enhancement ≤ 20 HU) who underwent multiphase (non-contrast, arterial, portal venous phase) PCD-CT and for whom non-contrast and portal venous phase DE EID-CT was available. Subsequently, VNC reconstructions were calculated for all contrast phases and density as well as contrast enhancement within the cysts were measured and compared. MRI and/or ultrasound served as reference standards for lesion classification. RESULTS: 19 patients (1 cyst per patient; age 69.5 ± 10.7 years; 17 [89.5%] male) were included. Density measurements on PCD-CT non-contrast and VNC reconstructions (arterial and portal venous phase) revealed no significant effect on HU values (p = 0.301). In contrast, a significant difference between non-contrast vs. VNC images was found for DE EID-CT (p = 0.02). For PCD-CT, enhancement for VNC reconstructions was < 20 HU for all evaluated cysts. DE EID-CT measurements revealed an enhancement of > 20 HU in five lesions (26.3%) using the VNC reconstructions, which was not seen with the non-contrast images. CONCLUSION: PCD-CT-derived VNC images allow for reliable and accurate characterization of simple cystic renal lesions similar to non-contrast scans whereas VNC images calculated from DE EID-CT resulted in substantial false characterization. Thus, PCD-CT-derived VNC images may substitute for non-contrast images and reduce radiation dose and follow-up imaging.

Photon-counting detector computed tomography for metal artifact reduction: a comparative study of different artifact reduction techniques in patients with orthopedic implants.

PURPOSE: Artifacts caused by metallic implants remain a challenge in computed tomography (CT). We investigated the impact of photon-counting detector computed tomography (PCD-CT) for artifact reduction in patients with orthopedic implants with respect to image quality and diagnostic confidence using different artifact reduction approaches. MATERIAL AND METHODS: In this prospective study, consecutive patients with orthopedic implants underwent PCD-CT imaging of the implant area. Four series were reconstructed for each patient (clinical standard reconstruction [PCD-CTStd], monoenergetic images at 140 keV [PCD-CT140keV], iterative metal artifact reduction (iMAR) corrected [PCD-CTiMAR], combination of iMAR and 140 keV monoenergetic [PCD-CT140keV+iMAR]). Subsequently, three radiologists evaluated the reconstructions in a random and blinded manner for image quality, artifact severity, anatomy delineation (adjacent and distant), and diagnostic confidence using a 5-point Likert scale (5 = excellent). In addition, the coefficient of variation [CV] and the relative quantitative artifact reduction potential were obtained as objective measures. RESULTS: We enrolled 39 patients with a mean age of 67.3 ± 13.2 years (51%; n = 20 male) and a mean BMI of 26.1 ± 4 kg/m2. All image quality measures and diagnostic confidence were significantly higher for the iMAR vs. non-iMAR reconstructions (all p < 0.001). No significant effect of the different artifact reduction approaches on CV was observed (p = 0.26). The quantitative analysis indicated the most effective artifact reduction for the iMAR reconstructions, which was higher than PCD-CT140keV (p < 0.001). CONCLUSION: PCD-CT allows for effective metal artifact reduction in patients with orthopedic implants, resulting in superior image quality and diagnostic confidence with the potential to improve patient management and clinical decision making.

A Context-based Chatbot Surpasses Trained Radiologists and Generic ChatGPT in Following the ACR Appropriateness Guidelines.

Background Radiological imaging guidelines are crucial for accurate diagnosis and optimal patient care as they result in standardized decisions and thus reduce inappropriate imaging studies. Purpose In the present study, we investigated the potential to support clinical decision-making using an interactive chatbot designed to provide personalized imaging recommendations from American College of Radiology (ACR) appropriateness criteria documents using semantic similarity processing. Methods We utilized 209 ACR appropriateness criteria documents as specialized knowledge base and employed LlamaIndex, a framework that allows to connect large language models with external data, and the ChatGPT 3.5-Turbo to create an appropriateness criteria contexted chatbot (accGPT). Fifty clinical case files were used to compare the accGPT's performance against general radiologists at varying experience levels and to generic ChatGPT 3.5 and 4.0. Results All chatbots reached at least human performance level. For the 50 case files, the accGPT performed best in providing correct recommendations that were "usually appropriate" according to the ACR criteria and also did provide the highest proportion of consistently correct answers in comparison with generic chatbots and radiologists. Further, the chatbots provided substantial time and cost savings, with an average decision time of 5 minutes and a cost of 0.19 € for all cases, compared to 50 minutes and 29.99 € for radiologists (both p < 0.01). Conclusion ChatGPT-based algorithms have the potential to substantially improve the decision-making for clinical imaging studies in accordance with ACR guidelines. Specifically, a context-based algorithm performed superior to its generic counterpart, demonstrating the value of tailoring AI solutions to specific healthcare applications.

Accuracy of Ultrahigh-Resolution Photon-counting CT for Detecting Coronary Artery Disease in a High-Risk Population.

Background Recently introduced photon-counting CT may improve noninvasive assessment of patients with high risk for coronary artery disease (CAD). Purpose To determine the diagnostic accuracy of ultrahigh-resolution (UHR) coronary CT angiography (CCTA) in the detection of CAD compared with the reference standard of invasive coronary angiography (ICA). Materials and Methods In this prospective study, participants with severe aortic valve stenosis and clinically indicated CT for transcatheter aortic valve replacement planning were consecutively enrolled from August 2022 to February 2023. All participants were examined with a dual-source photon-counting CT scanner using a retrospective electrocardiography-gated contrast-enhanced UHR scanning protocol (tube voltage, 120 or 140 kV; collimation, 120 × 0.2 mm; 100 mL of iopromid; no spectral information). Subjects underwent ICA as part of their clinical routine. A consensus assessment of image quality (five-point Likert scale: 1 = excellent [absence of artifacts], 5 = nondiagnostic [severe artifacts]) and a blinded independent reading for the presence of CAD (stenosis ≥50%) were performed. UHR CCTA was compared with ICA using area under the receiver operating characteristic curve (AUC). Results Among 68 participants (mean age, 81 years ± 7 [SD]; 32 male, 36 female), the prevalence of CAD and prior stent placement was 35% and 22%, respectively. The overall image quality was excellent (median score, 1.5 [IQR, 1.3-2.0]). The AUC of UHR CCTA in the detection of CAD was 0.93 per participant (95% CI: 0.86, 0.99), 0.94 per vessel (95% CI: 0.91, 0.98), and 0.92 per segment (95% CI: 0.87, 0.97). Sensitivity, specificity, and accuracy, respectively, were 96%, 84%, and 88% per participant (n = 68); 89%, 91%, and 91% per vessel (n = 204); and 77%, 95%, and 95% per segment (n = 965). Conclusion UHR photon-counting CCTA provided high diagnostic accuracy in the detection of CAD in a high-risk population, including subjects with severe coronary calcification or prior stent placement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Williams and Newby in this issue.

Application of diffusion microstructure imaging in musculoskeletal radiology - translation from head to shoulders.

OBJECTIVES: Quantitative MRI techniques, such as diffusion microstructure imaging (DMI), are increasingly applied for advanced tissue characterization. We determined its value in rotator cuff (RC) muscle imaging by studying the association of DMI parameters to isometric strength and fat fraction (FF). METHODS: Healthy individuals prospectively underwent 3T-MRI of the shoulder using DMI and chemical shift encoding-based water-fat imaging. RC muscles were segmented and quantitative MRI metrics (V-ISO, free fluid; V-intra, compartment inside of muscle fibers; V-extra, compartment outside of muscle fibers, and FF) were extracted. Isometric shoulder strength was quantified using specific clinical tests. Sex-related differences were assessed with Student's t. Association of DMI-metrics, FF, and strength was tested. A factorial two-way ANOVA was performed to compare the main effects of sex and external/internal strength-ratio and their interaction effects on quantitative imaging parameters ratios of infraspinatus/subscapularis. RESULTS: Among 22 participants (mean age: 26.7 ± 3.1 years, 50% female, mean BMI: 22.6 ± 1.9 kg/m2), FF of the individual RC muscles did not correlate with strength or DMI parameters (all p > 0.05). Subjects with higher V-intra (r = 0.57 to 0.87, p < 0.01) and lower V-ISO (r = -0.6 to -0.88, p < 0.01) had higher internal and external rotation strength. Moreover, V-intra was higher and V-ISO was lower in all RC muscles in males compared to female subjects (all p < 0.01). There was a sex-independent association of external/internal strength-ratio with the ratio of V-extra of infraspinatus/subscapularis (p = 0.02). CONCLUSIONS: Quantitative DMI parameters may provide incremental information about muscular function and microstructure in young athletes and may serve as a potential biomarker. KEY POINTS: • Diffusion microstructure imaging was successfully applied to non-invasively assess the microstructure of rotator cuff muscles in healthy volunteers. • Sex-related differences in the microstructural composition of the rotator cuff were observed. • Muscular microstructural metrics correlated with rotator cuff strength and may serve as an imaging biomarker of muscular integrity and function.

Deep learning segmentation results in precise delineation of the putamen in multiple system atrophy.

OBJECTIVES: The precise segmentation of atrophic structures remains challenging in neurodegenerative diseases. We determined the performance of a Deep Neural Patchwork (DNP) in comparison to established segmentation algorithms regarding the ability to delineate the putamen in multiple system atrophy (MSA), Parkinson's disease (PD), and healthy controls. METHODS: We retrospectively included patients with MSA and PD as well as healthy controls. A DNP was trained on manual segmentations of the putamen as ground truth. For this, the cohort was randomly split into a training (N = 131) and test set (N = 120). The DNP's performance was compared with putaminal segmentations as derived by Automatic Anatomic Labelling, Freesurfer and Fastsurfer. For validation, we assessed the diagnostic accuracy of the resulting segmentations in the delineation of MSA vs. PD and healthy controls. RESULTS: A total of 251 subjects (61 patients with MSA, 158 patients with PD, and 32 healthy controls; mean age of 61.5 ± 8.8 years) were included. Compared to the dice-coefficient of the DNP (0.96), we noted significantly weaker performance for AAL3 (0.72; p < .001), Freesurfer (0.82; p < .001), and Fastsurfer (0.84, p < .001). This was corroborated by the superior diagnostic performance of MSA vs. PD and HC of the DNP (AUC 0.93) versus the AUC of 0.88 for AAL3 (p = 0.02), 0.86 for Freesurfer (p = 0.048), and 0.85 for Fastsurfer (p = 0.04). CONCLUSION: By utilization of a DNP, accurate segmentations of the putamen can be obtained even if substantial atrophy is present. This allows for more precise extraction of imaging parameters or shape features from the putamen in relevant patient cohorts. CLINICAL RELEVANCE STATEMENT: Deep learning-based segmentation of the putamen was superior to currently available algorithms and is beneficial for the diagnosis of multiple system atrophy. KEY POINTS: • A Deep Neural Patchwork precisely delineates the putamen and performs equal to human labeling in multiple system atrophy, even when pronounced putaminal volume loss is present. • The Deep Neural Patchwork-based segmentation was more capable to differentiate between multiple system atrophy and Parkinson's disease than the AAL3 atlas, Freesurfer, or Fastsurfer.

Impact of different metal artifact reduction techniques in photon-counting computed tomography head and neck scans in patients with dental hardware.

OBJECTIVES: Metal artifacts remain a challenge in computed tomography. We investigated the potential of photon-counting computed tomography (PCD-CT) for metal artifact reduction using an iterative metal artifact reduction (iMAR) algorithm alone and in combination with high keV monoenergetic images (140 keV) in patients with dental hardware. MATERIAL AND METHODS: Consecutive patients with dental implants were prospectively included in this study and received PCD-CT imaging of the craniofacial area. Four series were reconstructed (standard [PCD-CTstd], monoenergetic at 140 keV [PCD-CT140keV], iMAR corrected [PCD-CTiMAR], combination of iMAR and 140 keV monoenergetic [PCD-CTiMAR+140keV]). All reconstructions were assessed qualitatively by four radiologists (independent and blinded reading on a 5-point Likert scale [5 = excellent; no artifact]) regarding overall image quality, artifact severity, and delineation of adjacent and distant anatomy. To assess signal homogeneity and evaluate the magnitude of artifact reduction, we performed quantitative measures of coefficient of variation (CV) and a region of interest (ROI)-based relative change in artifact reduction [PCD-CT/PCD-CTstd]. RESULTS: We enrolled 48 patients (mean age 66.5 ± 11.2 years, 50% (n = 24) males; mean BMI 25.2 ± 4.7 kg/m2; mean CTDIvol 6.2 ± 6 mGy). We found improved overall image quality, reduced artifacts and superior delineation of both adjacent and distant anatomy for the iMAR vs. non-iMAR reconstructions (all p < 0.001). No significant effect of the different artifact reduction approaches on CV was observed (p = 0.42). The ROI-based analysis indicated the most effective artifact reduction for the iMAR reconstructions, which was significantly higher compared to PCD-CT140keV (p < 0.001). CONCLUSION: PCD-CT offers highly effective approaches for metal artifact reduction with the potential to overcome current diagnostic challenges in patients with dental implants. CLINICAL RELEVANCE STATEMENT: Metallic artifacts pose a significant challenge in CT imaging, potentially leading to missed findings. Our study shows that PCD-CT with iMAR post-processing reduces artifacts, improves image quality, and can possibly reveal pathologies previously obscured by artifacts, without additional dose application. KEY POINTS: • Photon-counting detector CT (PCD-CT) offers highly effective approaches for metal artifact reduction in patients with dental fillings/implants. • Iterative metal artifact reduction (iMAR) is superior to high keV monoenergetic reconstructions at 140 keV for artifact reduction and provides higher image quality. • Signal homogeneity of the reconstructed images is not affected by the different artifact reduction techniques.

Photon-Counting Computed Tomography (PC-CT) of the spine: impact on diagnostic confidence and radiation dose.

OBJECTIVES: Computed tomography (CT) is employed to evaluate surgical outcome after spinal interventions. Here, we investigate the potential of multispectral photon-counting computed tomography (PC-CT) on image quality, diagnostic confidence, and radiation dose compared to an energy-integrating CT (EID-CT). METHODS: In this prospective study, 32 patients underwent PC-CT of the spine. Data was reconstructed in two ways: (1) standard bone kernel with 65-keV (PC-CTstd) and (2) 130-keV monoenergetic images (PC-CT130 keV). Prior EID-CT was available for 17 patients; for the remaining 15, an age-, sex-, and body mass index-matched EID-CT cohort was identified. Image quality (5-point Likert scales on overall, sharpness, artifacts, noise, diagnostic confidence) of PC-CTstd and EID-CT was assessed by four radiologists independently. If metallic implants were present (n = 10), PC-CTstd and PC-CT130 keV images were again assessed by 5-point Likert scales by the same radiologists. Hounsfield units (HU) were measured within metallic artifact and compared between PC-CTstd and PC-CT130 keV. Finally, the radiation dose (CTDIvol) was evaluated. RESULTS: Sharpness was rated significantly higher (p = 0.009) and noise significantly lower (p < 0.001) in PC-CTstd vs. EID-CT. In the subset of patients with metallic implants, reading scores for PC-CT130 keV revealed superior ratings vs. PC-CTstd for image quality, artifacts, noise, and diagnostic confidence (all p < 0.001) accompanied by a significant increase of HU values within the artifact (p < 0.001). Radiation dose was significantly lower for PC-CT vs. EID-CT (mean CTDIvol: 8.83 vs. 15.7 mGy; p < 0.001). CONCLUSIONS: PC-CT of the spine with high-kiloelectronvolt reconstructions provides sharper images, higher diagnostic confidence, and lower radiation dose in patients with metallic implants. KEY POINTS: • Compared to energy-integrating CT, photon-counting CT of the spine had significantly higher sharpness and lower image noise while radiation dose was reduced by 45%. • In patients with metallic implants, virtual monochromatic photon-counting images at 130 keV were superior to standard reconstruction at 65 keV in terms of image quality, artifacts, noise, and diagnostic confidence.

Widespread white matter oedema in subacute COVID-19 patients with neurological symptoms.

While neuropathological examinations in patients who died from COVID-19 revealed inflammatory changes in cerebral white matter, cerebral MRI frequently fails to detect abnormalities even in the presence of neurological symptoms. Application of multi-compartment diffusion microstructure imaging (DMI), that detects even small volume shifts between the compartments (intra-axonal, extra-axonal and free water/CSF) of a white matter model, is a promising approach to overcome this discrepancy. In this monocentric prospective study, a cohort of 20 COVID-19 inpatients (57.3 ± 17.1 years) with neurological symptoms (e.g. delirium, cranial nerve palsies) and cognitive impairments measured by the Montreal Cognitive Assessment (MoCA test; 22.4 ± 4.9; 70% below the cut-off value <26/30 points) underwent DMI in the subacute stage of the disease (29.3 ± 14.8 days after positive PCR). A comparison of whole-brain white matter DMI parameters with a matched healthy control group (n = 35) revealed a volume shift from the intra- and extra-axonal space into the free water fraction (V-CSF). This widespread COVID-related V-CSF increase affected the entire supratentorial white matter with maxima in frontal and parietal regions. Streamline-wise comparisons between COVID-19 patients and controls further revealed a network of most affected white matter fibres connecting widespread cortical regions in all cerebral lobes. The magnitude of these white matter changes (V-CSF) was associated with cognitive impairment measured by the MoCA test (r = -0.64, P = 0.006) but not with olfactory performance (r = 0.29, P = 0.12). Furthermore, a non-significant trend for an association between V-CSF and interleukin-6 emerged (r = 0.48, P = 0.068), a prominent marker of the COVID-19 related inflammatory response. In 14/20 patients who also received cerebral 18F-FDG PET, V-CSF increase was associated with the expression of the previously defined COVID-19-related metabolic spatial covariance pattern (r = 0.57; P = 0.039). In addition, the frontoparietal-dominant pattern of neocortical glucose hypometabolism matched well to the frontal and parietal focus of V-CSF increase. In summary, DMI in subacute COVID-19 patients revealed widespread volume shifts compatible with vasogenic oedema, affecting various supratentorial white matter tracts. These changes were associated with cognitive impairment and COVID-19 related changes in 18F-FDG PET imaging.

Diffusion microstructure imaging in progressive supranuclear palsy: reduced axonal volumes in the superior cerebellar peduncles, dentato-rubro-thalamic tracts, ventromedial thalami, and frontomesial white matter.

Differentiating between Parkinson's disease (PD) and atypical Parkinson syndromes such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and corticobasal degeneration is challenging. Diffusion microstructure imaging (DMI) was analyzed in patients with clinically suspected atypical Parkinson syndromes and healthy controls. In an exploration cohort, the spatial distribution of PSP-related changes of DMI parameters were evaluated in a voxel-wise analysis and a region-of-interest (ROI)-based approach was established. The diagnostic performance was subsequently tested in an independent validation cohort. In the exploration cohort, 53 PSP patients were compared to a pooled comparison group of 19 patients with PD, 26 patients with MSA, 7 patients with corticobasal syndrome, and 25 healthy controls. PSP patients showed widespread axonal loss in the superior cerebellar peduncles, the dentato-rubro-thalamic tracts, the thalami and the frontal white matter (each P < 0.001). In the validation cohort consisting of 12 patients with PSP vs. 13 patients with other movement disorders, the accuracy of this ROI-based approach for identifying the PSP was highest in the thalamus and the frontal white matter (accuracy 0.96 each). This DMI approach can identify PSP patients on an individual level in a collective with suspected atypical Parkinson syndromes and allows further insight on microstructural alterations in vivo.

Cognitive impairment and altered cerebral glucose metabolism in the subacute stage of COVID-19.

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, neurological symptoms increasingly moved into the focus of interest. In this prospective cohort study, we assessed neurological and cognitive symptoms in hospitalized coronavirus disease-19 (COVID-19) patients and aimed to determine their neuronal correlates. Patients with reverse transcription-PCR-confirmed COVID-19 infection who required inpatient treatment primarily because of non-neurological complications were screened between 20 April 2020 and 12 May 2020. Patients (age > 18 years) were included in our cohort when presenting with at least one new neurological symptom (defined as impaired gustation and/or olfaction, performance < 26 points on a Montreal Cognitive Assessment and/or pathological findings on clinical neurological examination). Patients with ≥2 new symptoms were eligible for further diagnostics using comprehensive neuropsychological tests, cerebral MRI and 18fluorodeoxyglucose (FDG) PET as soon as infectivity was no longer present. Exclusion criteria were: premorbid diagnosis of cognitive impairment, neurodegenerative diseases or intensive care unit treatment. Of 41 COVID-19 inpatients screened, 29 patients (65.2 ± 14.4 years; 38% female) in the subacute stage of disease were included in the register. Most frequently, gustation and olfaction were disturbed in 29/29 and 25/29 patients, respectively. Montreal Cognitive Assessment performance was impaired in 18/26 patients (mean score 21.8/30) with emphasis on frontoparietal cognitive functions. This was confirmed by detailed neuropsychological testing in 15 patients. 18FDG PET revealed pathological results in 10/15 patients with predominant frontoparietal hypometabolism. This pattern was confirmed by comparison with a control sample using voxel-wise principal components analysis, which showed a high correlation (R2 = 0.62) with the Montreal Cognitive Assessment performance. Post-mortem examination of one patient revealed white matter microglia activation but no signs of neuroinflammation. Neocortical dysfunction accompanied by cognitive decline was detected in a relevant fraction of patients with subacute COVID-19 initially requiring inpatient treatment. This is of major rehabilitative and socioeconomic relevance.

3D X-ray based visualization of directional deep brain stimulation lead orientation.

Knowing the orientation of directional deep brain stimulation electrodes enables imaging-based adjustment of the stimulation settings. A rotational X-ray based examination was developed to determine the electrodes orientation. By identifying the patient´s 0° axis and the electrode´s rotation using the "iron sights"-sign, the exact orientation of the electrode in relation to the ACPC-line is given. The presented imaging approach offers a reliable diagnostic tool for visualization of the implanted DBS electrode orientation in clinical routine.

Pre-arrayed Pan-AAV Peptide Display Libraries for Rapid Single-Round Screening.

Display of short peptides on the surface of adeno-associated viruses (AAVs) is a powerful technology for the generation of gene therapy vectors with altered cell specificities and/or transduction efficiencies. Following its extensive prior use in the best characterized AAV serotype 2 (AAV2), recent reports also indicate the potential of other AAV isolates as scaffolds for peptide display. In this study, we systematically explored the respective capacities of 13 different AAV capsid variants to tolerate 27 peptides inserted on the surface followed by production of reporter-encoding vectors. Single-round screening in pre-arrayed 96-well plates permitted rapid and simple identification of superior vectors in >90 cell types, including T cells and primary cells. Notably, vector performance depended not only on the combination of capsid, peptide, and cell type, but also on the position of the inserted peptide and the nature of flanking residues. For optimal data availability and accessibility, all results were assembled in a searchable online database offering multiple output styles. Finally, we established a reverse-transduction pipeline based on vector pre-spotting in 96- or 384-well plates that facilitates high-throughput library panning. Our comprehensive illustration of the vast potential of alternative AAV capsids for peptide display should accelerate their in vivo screening and application as unique gene therapy vectors.

Deep brain stimulation electrodes may rotate after implantation-an animal study.

Directional deep brain stimulation (dDBS) electrodes allow to steer the electrical field in a specific direction. When implanted with torque, they may rotate for a certain time after implantation. The aim of this study was to evaluate whether and to which degree leads rotate in the first 24 h after implantation using a sheep brain model. dDBS electrodes were implanted in 14 sheep heads and 3D rotational fluoroscopy (3D-RF) scans were acquired to visualize the orientation of the electrode leads. Electrode leads were clockwise rotated just above the burr holes (180° n = 6, 360° n = 6, 2 controls) and 3D-RF scans were again acquired after 3, 6, 13, 17, and 24 h, respectively. One hundred eighty degree rotated electrodes showed an initial rotation of 83.5° (range: 35.4°-128.3°) and a rotation of 114.0° (range: 57°-162°) after 24 h. With 360° torsion, mean initial rotation was 201° (range: 3.3°-321.4°) and mean rotation after 24 h 215.7° (range 31.9°-334.7°), respectively. Direct postoperative imaging may not be accurate for determining the rotation of dDBS electrodes if torque is present.