Citations

Abstract Objectives To assess quantitative and qualitative image characteristics in phantoms and patients using a simultaneous ultra-high resolution (UHR) and multi-energy (ME) dual-source cardiac scan mode in a photon counting detector (PCD) CT scanner. Methods UHR-ME cardiac scans were performed to determine the spatial resolution and multi-energy performance. UHR reconstructions were completed to measure transverse and axial spatial resolution in terms of modulation transfer function (MTF) and slice sensitivity profile (SSP). Virtual monoenergetic images (VMIs), virtual non-contrast (VNC) images, and iodine concentration images were created using moderately sharp reconstruction kernels to assess ME performance. With IRB approval, coronary CT angiograms were acquired in 19 patients using the UHR-ME mode, from which iodine contrast-to-noise ratio (CNR) was measured. Various ME post-processing tasks were performed to show the utility of the spectral capabilities. Results VMIs showed a mean CT number error of 6.0%, while iodine accuracy was 0.71 mg/cc (root-mean-square-error). Spatial resolution matched well with a standard UHR mode. Patient images showed a trend of higher CNR at lower keV, while higher keV images showed decreased calcium blooming. ME techniques to separate iodine and calcium were used successfully. Conclusions The combination of UHR-ME cardiac mode retains UHR image quality while providing flexibility for ME post-processing. Advances in knowledge Cardiac UHR-ME PCD-CT scanning offers simultaneous UHR and ME imaging without loss of spatial or temporal resolution or quantitative accuracy.

Abstract Background With progressive accumulation of knowledge on SARS-CoV-2 infection clinical management, treatment guidelines recommended several options including remdesivir, a broad-spectrum antiviral. Given the evolving nature of coronavirus disease 2019, capturing the totality of scientific evidence from clinical trials and observational studies is critical to inform clinical decision making. We conducted a systematic literature review with meta-analysis to summarize the effectiveness of remdesivir among hospitalized adults. Methods We systematically searched MEDLINE, Embase and Cochrane Library databases for interventional and observational studies examining remdesivir efficacy. A rigorous double-reviewer approach was used for source identification, screening, data extraction and risk of bias assessment. A hierarchical random-effects model meta-analysis was used, with subgroup analyses for randomized controlled trials (RCTs) and real-world (RW) studies. Results From January 2019 to December 2023 >18 000 sources were screened, and 122 unique studies were identified, reporting on 25 174 participants in RCTs and 1 279 859 in RW studies. Remdesivir significantly increased survival in the overall population (odds ratio, 0.69 [95% confidence interval, .55–.86]; P = .001] across SARS-CoV-2 variants and disease severity levels: no supplemental oxygen (0.81 [.75–.88]), low-flow oxygen (0.71 [.64–.79]), high-flow oxygen (0.87 [.83–.91]), and invasive mechanical ventilation (0.78 [.68–.90]). Rehospitalization risk was significantly reduced in patients receiving remdesivir (odds ratio, 0.72 [95% confidence interval, .64–.81]). Conclusions Our comprehensive systematic literature review, capturing the totality of evidence, showed a significant survival benefit among patients hospitalized for SARS-CoV-2 infection and receiving remdesivir, across all disease severity levels. To assure that healthcare providers are aware of and deploy evidence-based optimal care, recommendations should rely on both RCT and RW data.

Abstract Background Accurate low‐dose CT simulation is required to efficiently assess reconstruction and dose reduction techniques. Projection domain noise insertion requires proprietary information from manufacturers. Analytic image domain noise insertion methods are successful for linear reconstruction algorithms, however extending them to non‐linear algorithms remains challenging. Emerging, deep‐learning‐based image domain noise insertion methods have potential, but few approaches have explicitly incorporated physics information and a texture‐synthesis model to guide the generation of locally and globally correlated noise texture. Purpose We proposed a p hysics‐informed model‐based gener a tive neura l network for simulating scann e r‐ and algori t hm‐specific low‐dose C T e xams (PALETTE). It is expected to provide an alternative to projection domain noise insertion methods in the absence of manufacturers’ proprietary information and tools. Methods PALETTE integrated a physics‐based noise prior generation process, a Noise2Noisier sub‐network, and a noise texture synthesis sub‐network. The Noise2Noisier sub‐network provided a bias prior, which, combined with the noise prior, served as the inputs to noise texture synthesis sub‐network. Explicit regularizations in spatial and frequency domains were developed to account for noise spatial correlation and frequency characteristics. For proof‐of‐concept, PALETTE was trained and validated for a commercial iterative reconstruction algorithm (SAFIRE, Siemens Healthineers), using the paired routine and 25% dose images from CT phantoms (lateral size 30–40 cm; three training and four testing phantoms) and open‐access patient cases (10 training and 20 testing cases). In phantom validation, noise power spectra (NPS) were compared in water background and tissue‐mimicking inserts, using peak frequency and mean‐absolute‐error (MAE). In patient case evaluation, visual inspection and quantitative assessment were conducted on axial, coronal, and sagittal planes. Local and global noise texture were visually inspected in low‐dose CT images and the difference images between routine and low dose. Noise levels in liver and fat were measured. Local and global 2D Fourier magnitude spectra of the difference images and the corresponding radial mean profiles were used to assess similarity in noise frequency components within tissues and entire field‐of‐view, using spectral correlation mapper (SCM) and spectral angle mapper (SAM). Several baseline neural network models (e.g., GAN) were included in the evaluation. Statistical significance was tested using a t ‐test for related samples. Results PALETTE‐derived NPS showed accurate noise peak frequency (PALETTE/reference: water 1.40/1.40 lp/cm; inserts 1.7/1.7lp/cm) and small MAE (≤0.65 HU 2 cm 2 ). PALETTE created anatomy‐dependent noise texture, showing realistic local and global granularity and streaks. No statistically significant difference was observed in noise levels ( p > 0.05). Noise range was comparable across 3D image volume (PALETTE / reference):liver – [18.0, 53.4] / [19.3, 50.0] HU; fat – [11.7, 42.4] / [12.1, 41.3] HU. Percent absolute difference of local noise was small (mean ± standard deviation): liver 4.1%±3.1%, fat 4.6%±3.1%. Noise frequency distribution was close to the reference (mean per case): SCM ≥ 0.92, SAM ≤ 0.22. Additionally, PALETTE outperformed all baseline models in visual inspection and quantitative comparison. Conclusion PALETTE can provide high‐quality image domain noise insertion for simulating accurate low‐dose CT images created with a commercial non‐linear reconstruction algorithm.

Abstract Background Multi‐energy CT (MECT) enables quantification of material concentrations by measuring linear attenuation coefficient line integrals with multiple x‐ray spectra. Photon counting detector (PCD)‐CT utilizes a detector‐based approach for MECT that can suffer from substantial spectral overlap, resulting in amplified material quantification noise. Dual‐source dual‐kV approaches for MECT are currently utilized in some energy‐integrating detector (EID)‐CT systems and can potentially be utilized with PCD‐CT for improved spectral separation. Purpose To evaluate the iodine quantification performance of a novel dual‐source (DS)‐PCD‐CT scan mode and compare to single‐source (SS)‐PCD‐CT and DS‐EID‐CT. Materials and Methods A 30 cm × 40 cm solid water phantom with four iodine inserts (2, 5, 10, and 15 mg/mL) was scanned with the three spectral modalities: SS‐PCD‐CT with two energy thresholds, DS‐PCD‐CT (90/Sn150 kV), and DS‐EID‐CT (90/Sn150 kV). For each modality, full‐dose (12 mGy) and half‐dose scans were acquired, and images were reconstructed with filtered back‐projection using a quantitative (Qr40) kernel. When scanning in a DS configuration, the total radiation dose budget is split between two detectors, increasing the strength of a signal‐dependent filter compared to a SS acquisition. To account for this effect, the modulation transfer function (MTF) for each modality was measured from a 0.05 mm tungsten wire. A linear spatial filter was applied to the SS images to match their MTF to that of the DS images. The resulting high‐ and low‐energy images were input into an image‐domain least squares material decomposition algorithm with iodine and water as the two basis materials. Iodine quantification accuracy and noise measured from the iodine basis images were used as figures of merit, and t‐tests used to compare between modalities. Results The 10% MTF cutoffs were 0.56, 0.57, 0.60, and 0.57 lp/mm for DS‐EID‐CT, DS‐PCD‐CT, SS‐PCD‐CT, and SS‐PCD‐CT after MTF‐matching, respectively, with the SS‐PCD‐CT MTF cutoff dropping to 0.58 lp/mm at half‐dose. Without accounting for the signal‐dependent filter by matching the MTFs, the noise in iodine material basis images from SS‐PCD‐CT was 10% higher than that of DS‐EID‐CT. After matching the MTFs, the noise in the SS‐PCD‐CT iodine image was 9%–22% lower than that of the DS‐EID‐CT. The lowest iodine image noise was from the DS‐PCD‐CT, which was 39%–41% lower than the DS‐EID‐CT. The DS‐PCD‐CT noise magnitude was significantly different from the other modalities. Mean iodine quantification accuracy across all measured concentrations was within 5% for all modalities at full dose, but was only below 5% for the DS‐PCD‐CT at half‐dose. Conclusions SS‐PCD‐CT with two energy thresholds outperformed DS‐EID‐CT in terms of image noise in iodine basis images when spatial resolution was matched. DS‐PCD‐CT gave the lowest noise due to the combination of PCD technology and improved spectral separation from the different x‐ray spectra.

AbstractBackgroundPhoton counting X‐ray detectors (PCDs) provide better spatial resolution than energy integrating X‐ray detectors, but even higher resolution is desired in some applications. Certain charge sharing compensation techniques such as coincidence counting preferentially detect photons that arrive at the boundary between pixels, and this could be used for subpixel localization of incident photons and enhanced spatial resolution.PurposeTo estimate improvements to spatial resolution and detective quantum efficiency that are possible when using coincidence counting for high‐resolution, non‐spectral imaging.MethodsThe modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) were estimated using numerical simulations of a two‐dimensional parallel‐beam CT system. Coincidence counters were modeled either geometrically or with Monte Carlo simulations. The geometric model consisted of narrow coincidence counters that interlaced with wider ordinary pixels, and showed that using standard filtered backprojection decreases low‐frequency DQE, but that a frequency weighting technique could be used to restore DQE. The Monte Carlo simulations were used to estimate the possible improvements that could be expected from real systems. The pixel pitch was 0.25 mm and the source apertures considered were 0, 0.125, and 0.5 mm. A numerical stent phantom was also used to illustrate possible improvements.ResultsAssuming a 0.125 mm source aperture and the Monte Carlo model, the limiting MTF (at 10%) increased from 20 to 40 lp/cm using coincidence counters. This can be explained by the increased sampling (and higher Nyquist limit) possible from coincidence counters. In the geometric model, coincidence counters are compared to conventional double sampling techniques such as in‐plane flying focal spot, and the MTF at 38 lp/cm increased from 5% to 53%. Without the frequency weighting technique, low‐frequency DQE was reduced by about 20%, but these losses are recovered with frequency weighting. Improvements are much more modest with the 0.25 mm source aperture because the system becomes source‐limited.ConclusionsCoincidence counting could be used to increase spatial resolution in PCDs. The increases in system resolution could be large if a high‐resolution X‐ray source were available.

Abstract Primary testicular diffuse large B-cell lymphoma (PT-DLBCL) is a rare and aggressive lymphoma with molecular heterogeneity not well characterize. In this study, we performed next-generation sequencing analysis for a large number of DNA and RNA samples from patients with PT-DLBCL. DNA sequencing analysis identified ≥ 3 chromosomes with copy number variations (CNVs) and microsatellite instability as prognostic biomarkers, rather than MYD88 mutations and genetic subtypes. Remarkably, targeted RNA-seq analysis in 195 patients revealed that TP53 mutations with a ≥ 40% variant allele frequency had significantly adverse prognostic impact, and that a 150-gene expression signature subdivided PT-DLBCL into two distinct clusters, termed as testicular lymphoma tumor (TLT) and microenvironment (ME) subtypes. The TLT subtype featured upregulation of genes involved in B-cell receptor signaling, cell cycle, DNA damage and repair, higher frequencies of CNVs and MYD88 mutations, elder ages, larger tumor sizes, and significantly poorer survival. Genomic microRNA profiling analysis identified significantly differentially expressed microRNAs between 113 PT-DLBCL and 180 systemic DLBCL patients, and further subdivided the PT-DLBCL cohort by microRNA signatures. The subcohort with upregulation of 16 microRNAs associated with PT-DLBCL and testicular tissue expression had significantly better survival. This study revealed characteristic genetic, gene expression, and microRNA profiles and heterogeneity in PT-DLBCL.

Introduction: Primary diffuse large B-cell lymphoma (DLBCL) of the central nervous system (CNS), traditionally referred to as primary CNS lymphoma (PCNSL), is a rare type of primary large B-cell lymphoma of immune-privileged sites with significantly poorer prognosis than systemic DLBCL. Genetic profiles of PCNSL were widely studied, whereas the tumor microenvironment has not been well characterized. Patients and Methods: A series of molecular analyses were performed using DLBCL FFPE tissues collected by the International Lymphoma Consortium. First, multiplex fluorescent immunohistochemistry (mfIHC) using antibodies for CD20, PAX5, CD3, CD4, CD8, FOXP3, CD45RO, CD68, CD56, PD-1, PD-L1, PD-L2, and CTLA-4 was performed on PCNSL tissues from 121 immunocompetent patients and de novo systemic DLBCL tissues from 405 patients. Digital quantification results for 405 patients with EBV-negative systemic DLBCL or primary testicular (PT) DLBCL have been reported previously. The preliminary mfIHC results of PCNSL will be presented. Second, mfIHC for multiple B cell biomarkers, CD3, CD4, CD8, CD68, CD163, CD11c, and CD31 were performed for 10 PCNSL validation cases, 24 PT-DLBCL and 451 systemic DLBCL tissues (unpublished). Third, RNA samples were extracted and sequenced for the targeted 1408 cancer-associated genes, successfully in 142 PCNSL cases, including 102 cases evaluated by either of these two mfIHC panels and additional 40 PCNSL cases, Results: First, in the first large mfIHC cohort, PCNSLs compared with de novo systemic nodal or extranodal DLBCL had significantly higher mean/median CD56+ cell densities whereas lower T cell densities (consistent with the immune privilege), as well as lower CD45RO+, PD-1+, and FOXP3+ percentages in T cells whereas higher CD4¯CD8¯ double-negative percentages in T cells. Prognostic analysis in the PCNSL cohort showed that high CD56+ cell densities and high CD45RO+CD8+ T cell densities were associated with significantly poorer and better patient survival, respectively, which are opposite to their prognostic effects in systemic DLBCL as previously reported. Twelve patients had very high PD-L1 expression in B cells and significantly poorer survival in the PCNSL cohort. Second, as validation, the 10 PCNSL cases in the second mfIHC study showed significantly less T cells than systemic DLBCL and PT-DLBCL cases, and low CD8 T cell densities and having low percentage of CD8 T cells adjacent to tumor cells were associated with significantly poorer survival. Immunofluorescence landscapeand spatial analysisrevealed significant differences in immune privilege between PCNSL and PT-DLBCL. Third, gene expression profiling analysis by targeted RNA-seq identified 282 significantly differentially expressed genes between PCNSL and systemic DLBCL, referred to as the PCNSL signature. Unsupervised clustering analysis divided the PCNSL cohort into two clusters, which had no significant difference in MYD88 mutation frequencies analyzed at the mRNA level. Importantly, the cluster with higher expression of many neural glial genes in the PCNSL signature had significantly poorer survival, which remained significant in multivariate analysis adjusting for clinical factors and/or treatments, two PCNSL subcohorts (as training and validation cohorts), and methotrexate-treated patients. NCAM1 (Neural Cell Adhesion Molecule 1, encoding CD56) was among the upregulated PCNSL signature genes, explaining the poorer prognosis associated with higher CD56+ cell densities in PCNSL by the mfIHC analysis. Summary: Our studies represent the largest immunophenotypic and gene expression profiling studies currently in PCNSL, a rare type of primary DLBCL of immune-privileged sites. Multiplex immunofluorescence revealed the immune landscape in PCNSL in comparison with systemic and testicular DLBCL, and identified prognostic immune biomarkers. Targeted RNA-seq identified a PCNSL gene signature enriched with neuronal-glial genes and showing significant prognostic effect in PCNSL. These novel findings in the PCNSL microenvironment warrant further studies.

AbstractBackgroundCochlear implants (CIs) are used to rehabilitate moderate to profound sensorineural hearing loss and stimulate the auditory system via a multichannel electrode array positioned in the scala tympani. Imaging evaluation of CIs is substantially degraded by metallic artifacts. Photon‐counting detector (PCD)‐CT has the potential to minimize such artifacts, though this has not been convincingly established in prior studies. This study compared the visualization of CI electrodes on PCD‐CT to conventional energy integrating detector (EID)‐CT.Materials and MethodsFive patients with CIs were prospectively recruited to undergo temporal bone imaging on both EID‐CT and PCD‐CT scanners yielding 2D and 3D Volume Rendering Technique (VRT) images. Three nonblinded neuroradiologists reviewed 2D and 3D VRT images for the ability to resolve CI electrode leads using a Likert scale. The average Likert scores of PCD‐CT versus EID‐CT were calculated for each reader for both 2D and 3D VRT images. (Likert scores 1–5 based on inferior to superior rating of PCD‐CT compared to EID‐CT). Inter‐rater agreement was assessed using Krippendorff's alpha with ordinal weights. ResultsFive patients underwent temporal bone CT for CI array evaluation. As evidenced by 5‐point Likert scales that were independently used by the three reviewers, this study demonstrated superior resolution of CI electrode array using PCD‐CT as compared to EID‐CT with an average score of 4.2 ± 0.8 for 2D images and 4.9 ± 0.4 for 3D VRT images.ConclusionsPCD‐CT is superior to EID‐CT in the visualization of CI electrodes, particularly in 3D VRT imaging.

Tumor-educated platelets (TEPs) are a potential method of liquid biopsy for the diagnosis and monitoring of cancer. However, the mechanism underlying tumor education of platelets is not known, and transcripts associated with TEPs are often not tumor-associated transcripts. We demonstrated that direct tumor transfer of transcripts to circulating platelets is an unlikely source of the TEP signal. We used CDSeq, a latent Dirichlet allocation algorithm, to deconvolute the TEP signal in blood samples from patients with glioblastoma. We demonstrated that a substantial proportion of transcripts in the platelet transcriptome are derived from nonplatelet cells, and the use of this algorithm allows the removal of contaminant transcripts. Furthermore, we used the results of this algorithm to demonstrate that TEPs represent a subset of more activated platelets, which also contain transcripts normally associated with nonplatelet inflammatory cells, suggesting that these inflammatory cells, possibly in the tumor microenvironment, transfer transcripts to platelets that are then found in circulation. Our analysis suggests a useful and efficient method of processing TEP transcriptomic data to enable the isolation of a unique TEP signal associated with specific tumors.

AbstractBackground and PurposeTo compare the performance of the photon‐counting detector (PCD)‐CT against a cutting‐edge energy‐integrated detector (EID)‐CT to visualize different segments of the chorda tympani nerve.Materials and MethodsAn IRB‐approved protocol prospectively enrolled patients for temporal bone CT on both EID‐CT and PCD‐CT scanners. Fellowship‐trained neuroradiologists compared visualization of chorda tympani segments on each scanner using a 5‐point Likert scale (1 indicating EID is far superior to PCD, 3 indicating they are equivalent, and 5 indicating PCD is far superior to EID). Scores were averaged across segments and tested using a one‐sample Wilcoxon signed‐rank test with a one‐sided alternative hypothesis.ResultsForty temporal bones were evaluated. Average Likert scores for visualization of chorda tympani segments‐chorda tympani canal/proximal segment, middle ear/posterior tympanic segment, and petrotympanic fissure/distal segment‐ on the PCD compared to EID scanner were 4.2 (SD = 0.4), 4.4 (0.5), and 4 (0.0), respectively. The anterior tympanic segment of the chorda tympani was not well visualized on either platform or therefore not scored. PCD compared to the EID scanner had better overall performance (Median = 4.2, 95% CI: [4.1, 5.0], p‐value < .001).ConclusionPCD‐CT improves visualization of the petrous and intratympanic chorda tympani nerve segments, chorda tympani canaliculus, and petrotympanic fissure compared to comparable EID‐CT examinations. The improved visualization of the chorda tympani is important for the characterization of middle ear pathology involving this structure and presurgical planning to determine the size of the facial recess for cochlear implantation and to estimate the risk of nerve injury.