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Rapidity and transverse momentum dependence of inclusive J/ψ production in pp collisions at √s=7 TeV
(2011)
The ALICE experiment at the LHC has studied inclusive J/ψ production at central and forward rapidities in pp collisions at √s=7 TeV. In this Letter, we report on the first results obtained detecting the J/ψ through the dilepton decay into e+e− and μ+μ− pairs in the rapidity ranges |y|<0.9 and 2.5<y<4, respectively, and with acceptance down to zero pT. In the dielectron channel the analysis was carried out on a data sample corresponding to an integrated luminosity Lint=5.6 nb−1 and the number of signal events is NJ/ψ=352±32(stat.)±28(syst.); the corresponding figures in the dimuon channel are Lint=15.6 nb−1 and NJ/ψ=1924±77(stat.)±144(syst.). The measured production cross sections are σJ/ψ(|y|<0.9)=10.7±1.0(stat.)±1.6(syst.)−2.3+1.6(syst.pol.)μb and σJ/ψ(2.5<y<4)=6.31±0.25(stat.)±0.76(syst.)−1.96+0.95(syst.pol.)μb. The differential cross sections, in transverse momentum and rapidity, of the J/ψ were also measured.
The change in allele frequencies within a population over time represents a fundamental process of evolution. By monitoring allele frequencies, we can analyze the effects of natural selection and genetic drift on populations. To efficiently track time-resolved genetic change, large experimental or wild populations can be sequenced as pools of individuals sampled over time using high-throughput genome sequencing (called the Evolve & Resequence approach, E&R). Here, we present a set of experiments using hundreds of natural genotypes of the model plant Arabidopsis thaliana to showcase the power of this approach to study rapid evolution at large scale. First, we validate that sequencing DNA directly extracted from pools of flowers from multiple plants -- organs that are relatively consistent in size and easy to sample -- produces comparable results to other, more expensive state-of-the-art approaches such as sampling and sequencing of individual leaves. Sequencing pools of flowers from 25-50 individuals at ∼40X coverage recovers genome-wide frequencies in diverse populations with accuracy r > 0.95. Secondly, to enable analyses of evolutionary adaptation using E&R approaches of plants in highly replicated environments, we provide open source tools that streamline sequencing data curation and calculate various population genetic statistics two orders of magnitude faster than current software. To directly demonstrate the usefulness of our method, we conducted a two-year outdoor evolution experiment with A. thaliana to show signals of rapid evolution in multiple genomic regions. We demonstrate how these laboratory and computational Pool-seq-based methods can be scaled to study hundreds of populations across many climates.
Background: Polytrauma and respiratory tract damage after thoracic trauma cause about 25% of mortality among severely injured patients. Thoracic trauma can lead to the development of severe lung complications such as acute respiratory distress syndrome, and is, therefore, of great interest for monitoring in intensive care units (ICU). In recent years, club cell protein (CC)16 with its antioxidant properties has proven to be a potential outcome-related marker. In this study, we evaluated whether CC16 constitutes as a marker of lung damage in a porcine polytrauma model.
Methods: In a 72 h ICU polytrauma pig model (thoracic trauma, tibial fracture, hemorrhagic shock, liver laceration), blood plasma samples (0, 3, 9, 24, 48, 72 h), BAL samples (72 h) and lung tissue (72 h) were collected. The trauma group (PT) was compared to a sham group. CC16 as a possible biomarker for lung injury in this model, and IL-8 concentrations as known indicator for ongoing inflammation during trauma were determined by ELISA. Histological analysis of ZO-1 and determination of total protein content were used to show barrier disruption and edema formation in lung tissue from the trauma group.
Results: Systemic CC16 levels were significantly increased early after polytrauma compared vs. sham. After 72 h, CC16 concentration was significantly increased in lung tissue as well as in BAL in PT vs. sham. Similarly, IL-8 and total protein content in BAL were significantly increased in PT vs. sham. Evaluation of ZO-1 staining showed significantly lower signal intensity for polytrauma.
Conclusion: The data confirm for the first time in a larger animal polytrauma model that lung damage was indicated by systemic and/or local CC16 response. Thus, early plasma and late BAL CC16 levels might be suitable to be used as markers of lung injury in this polytrauma model.
Background: Polytrauma and respiratory tract damage after thoracic trauma cause about 25% of mortality among severely injured patients. Thoracic trauma can lead to the development of severe lung complications such as acute respiratory distress syndrome, and is, therefore, of great interest for monitoring in intensive care units (ICU). In recent years, club cell protein (CC)16 with its antioxidant properties has proven to be a potential outcome-related marker. In this study, we evaluated whether CC16 constitutes as a marker of lung damage in a porcine polytrauma model.
Methods: In a 72 h ICU polytrauma pig model (thoracic trauma, tibial fracture, hemorrhagic shock, liver laceration), blood plasma samples (0, 3, 9, 24, 48, 72 h), BAL samples (72 h) and lung tissue (72 h) were collected. The trauma group (PT) was compared to a sham group. CC16 as a possible biomarker for lung injury in this model, and IL-8 concentrations as known indicator for ongoing inflammation during trauma were determined by ELISA. Histological analysis of ZO-1 and determination of total protein content were used to show barrier disruption and edema formation in lung tissue from the trauma group.
Results: Systemic CC16 levels were significantly increased early after polytrauma compared vs. sham. After 72 h, CC16 concentration was significantly increased in lung tissue as well as in BAL in PT vs. sham. Similarly, IL-8 and total protein content in BAL were significantly increased in PT vs. sham. Evaluation of ZO-1 staining showed significantly lower signal intensity for polytrauma.
Conclusion: The data confirm for the first time in a larger animal polytrauma model that lung damage was indicated by systemic and/or local CC16 response. Thus, early plasma and late BAL CC16 levels might be suitable to be used as markers of lung injury in this polytrauma model.
Background: Atypical EGFR mutations occur in 10%-30% of non-small-cell lung cancer (NSCLC) patients with EGFR mutations and their sensitivity to classical epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKI) is highly heterogeneous. Patients harboring one group of uncommon, recurrent EGFR mutations (G719X, S768I, L861Q) respond to EGFR-TKI. Exon 20 insertions are mostly insensitive to EGFR-TKI but display sensitivity to exon 20 inhibitors. Clinical outcome data of patients with very rare point and compound mutations upon systemic treatments are still sparse to date.
Patients and methods: In this retrospective, multicenter study of the national Network Genomic Medicine (nNGM) in Germany, 856 NSCLC cases with atypical EGFR mutations including co-occurring mutations were reported from 12 centers. Clinical follow-up data after treatment with different EGFR-TKIs, chemotherapy and immune checkpoint inhibitors were available from 260 patients. Response to treatment was analyzed in three major groups: (i) uncommon mutations (G719X, S7681, L861Q and combinations), (ii) exon 20 insertions and (iii) very rare EGFR mutations (very rare single point mutations, compound mutations, exon 18 deletions, exon 19 insertions).
Results: Our study comprises the largest thus far reported real-world cohort of very rare EGFR single point and compound mutations treated with different systemic treatments. We validated higher efficacy of EGFR-TKI in comparison to chemotherapy in group 1 (uncommon), while most exon 20 insertions (group 2) were not EGFR-TKI responsive. In addition, we found TKI sensitivity of very rare point mutations (group 3) and of complex EGFR mutations containing exon 19 deletions or L858R mutations independent of the combination partner. Notably, treatment responses in group 3 (very rare) were highly heterogeneous. Co-occurring TP53 mutations exerted a non-significant trend for a detrimental effect on outcome in EGFR-TKI-treated patients in groups 2 and 3 but not in group 1.
Conclusions: Based on our findings, we propose a novel nNGM classification of atypical EGFR mutations.
The Gleason grading system remains the most powerful prognostic predictor for patients with prostate cancer since the 1960s. Its application requires highly-trained pathologists, is tedious and yet suffers from limited inter-pathologist reproducibility, especially for the intermediate Gleason score 7. Automated annotation procedures constitute a viable solution to remedy these limitations. In this study, we present a deep learning approach for automated Gleason grading of prostate cancer tissue microarrays with Hematoxylin and Eosin (H&E) staining. Our system was trained using detailed Gleason annotations on a discovery cohort of 641 patients and was then evaluated on an independent test cohort of 245 patients annotated by two pathologists. On the test cohort, the inter-annotator agreements between the model and each pathologist, quantified via Cohen’s quadratic kappa statistic, were 0.75 and 0.71 respectively, comparable with the inter-pathologist agreement (kappa = 0.71). Furthermore, the model’s Gleason score assignments achieved pathology expert-level stratification of patients into prognostically distinct groups, on the basis of disease-specific survival data available for the test cohort. Overall, our study shows promising results regarding the applicability of deep learning-based solutions towards more objective and reproducible prostate cancer grading, especially for cases with heterogeneous Gleason patterns.
Formalin‐fixed, paraffin‐embedded (FFPE ), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here, we developed a pressure cycling technology (PCT )‐SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PC a) and diffuse large B‐cell lymphoma (DLBCL ) samples. We show that the proteome patterns of FFPE PC a tissue samples and their analogous fresh‐frozen (FF ) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PC a tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between 1 and 15 years in a biobank and show a high degree of the proteome pattern similarity between two types of histological regions in small FFPE samples, that is, punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of a certain degree of biological variations. Applying the method to two independent DLBCL cohorts, we identified myeloperoxidase, a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PC a and DLBCL have been discovered.
Impaired alveolar formation and maintenance are features of many pulmonary diseases that are associated with significant morbidity and mortality. In a forward genetic screen for modulators of mouse lung development, we identified the non-muscle myosin II heavy chain gene, Myh10. Myh10 mutant pups exhibit cyanosis and respiratory distress, and die shortly after birth from differentiation defects in alveolar epithelium and mesenchyme. From omics analyses and follow up studies, we find decreased Thrombospondin expression accompanied with increased matrix metalloproteinase activity in both mutant lungs and cultured mutant fibroblasts, as well as disrupted extracellular matrix (ECM) remodeling. Loss of Myh10 specifically in mesenchymal cells results in ECM deposition defects and alveolar simplification. Notably, MYH10 expression is downregulated in the lung of emphysema patients. Altogether, our findings reveal critical roles for Myh10 in alveologenesis at least in part via the regulation of ECM remodeling, which may contribute to the pathogenesis of emphysema.
he first measurements of the invariant differential cross sections of inclusive π0 and η meson production at mid-rapidity in proton–proton collisions at s=0.9 TeV and s=7 TeV are reported. The π0 measurement covers the ranges 0.4<pT<7 GeV/c and 0.3<pT<25 GeV/c for these two energies, respectively. The production of η mesons was measured at s=√7 TeV in the range 0.4<pT<15 GeV/c. Next-to-Leading Order perturbative QCD calculations, which are consistent with the π0 spectrum at s=0.9 TeV, overestimate those of π0 and η mesons at s=√7 TeV, but agree with the measured η/π0 ratio at s=√7 TeV.
The ALICE Collaboration has measured inclusive J/ψ production in pp collisions at a center-of-mass energy √s=2.76 TeV at the LHC. The results presented in this Letter refer to the rapidity ranges |y|<0.9 and 2.5<y<4 and have been obtained by measuring the electron and muon pair decay channels, respectively. The integrated luminosities for the two channels are Linte=1.1 nb−1 and Lintμ=19.9 nb−1, and the corresponding signal statistics are NJ/ψe+e−=59±14 and NJ/ψμ+μ−=1364±53. We present dσJ/ψ/dy for the two rapidity regions under study and, for the forward-y range, d2σJ/ψ/dydpt in the transverse momentum domain 0<pt<8 GeV/c. The results are compared with previously published results at s=7 TeV and with theoretical calculations.
The ALICE experiment has measured low-mass dimuon production in pp collisions at √s=7 TeV in the dimuon rapidity region 2.5<y<4. The observed dimuon mass spectrum is described as a superposition of resonance decays (η,ρ,ω,η′,ϕ) into muons and semi-leptonic decays of charmed mesons. The measured production cross sections for ω and ϕ are σω(1<pt<5 GeV/c,2.5<y<4)=5.28±0.54(stat)±0.49(syst) mb and σϕ(1<pt<5 GeV/c,2.5<y<4)=0.940±0.084(stat)±0.076(syst) mb. The differential cross sections d2σ/dydpt are extracted as a function of pt for ω and ϕ. The ratio between the ρ and ω cross section is obtained. Results for the ϕ are compared with other measurements at the same energy and with predictions by models.
Heavy flavour decay muon production at forward rapidity in proton–proton collisions at √s=7 TeV
(2012)
The production of muons from heavy flavour decays is measured at forward rapidity in proton–proton collisions at √s=7 TeV collected with the ALICE experiment at the LHC. The analysis is carried out on a data sample corresponding to an integrated luminosity Lint=16.5 nb−1. The transverse momentum and rapidity differential production cross sections of muons from heavy flavour decays are measured in the rapidity range 2.5<y<4, over the transverse momentum range 2<pt<12 GeV/c. The results are compared to predictions based on perturbative QCD calculations.
Harmonic decomposition of two particle angular correlations in Pb–Pb collisions at √sNN=2.76 TeV
(2012)
Angular correlations between unidentified charged trigger (t) and associated (a) particles are measured by the ALICE experiment in Pb–Pb collisions at √sNN=2.76 TeV for transverse momenta 0.25<pTt,a<15 GeV/c, where pTt>pTa. The shapes of the pair correlation distributions are studied in a variety of collision centrality classes between 0 and 50% of the total hadronic cross section for particles in the pseudorapidity interval |η|<1.0. Distributions in relative azimuth Δϕ≡ϕt−ϕa are analyzed for |Δη|≡|ηt−ηa|>0.8, and are referred to as “long-range correlations”. Fourier components VnΔ≡〈cos(nΔϕ)〉 are extracted from the long-range azimuthal correlation functions. If particle pairs are correlated to one another through their individual correlation to a common symmetry plane, then the pair anisotropy VnΔ(pTt,pTa) is fully described in terms of single-particle anisotropies vn(pT) as VnΔ(pTt,pTa)=vn(pTt)vn(pTa). This expectation is tested for 1⩽n⩽5 by applying a global fit of all VnΔ(pTt,pTa) to obtain the best values vn{GF}(pT). It is found that for 2⩽n⩽5, the fit agrees well with data up to pTa∼3–4 GeV/c, with a trend of increasing deviation as pTt and pTa are increased or as collisions become more peripheral. This suggests that no pair correlation harmonic can be described over the full 0.25<pT<15 GeV/c range using a single vn(pT) curve; such a description is however approximately possible for 2⩽n⩽5 when pTa<4 GeV/c. For the n=1 harmonic, however, a single v1(pT) curve is not obtained even within the reduced range pTa<4 GeV/c.
The ALICE Collaboration reports the measurement of the relative J/ψ yield as a function of charged particle pseudorapidity density dNch/dη in pp collisions at √s=7 TeV at the LHC. J/ψ particles are detected for pt>0, in the rapidity interval |y|<0.9 via decay into e+e−, and in the interval 2.5<y<4.0 via decay into μ+μ− pairs. An approximately linear increase of the J/ψ yields normalized to their event average (dNJ/ψ/dy)/〈dNJ/ψ/dy〉 with (dNch/dη)/〈dNch/dη〉 is observed in both rapidity ranges, where dNch/dη is measured within |η|<1 and pt>0. In the highest multiplicity interval with 〈dNch/dη(bin)〉=24.1, corresponding to four times the minimum bias multiplicity density, an enhancement relative to the minimum bias J/ψ yield by a factor of about 5 at 2.5<y<4 (8 at |y|<0.9) is observed.
Der Vorstand der Deutschen Gesellschaft für Epileptologie und die Kommission „Epilepsie und Synkopen“ der Deutschen Gesellschaft für Neurologie haben die aktuelle Datenlage zur Impfung zur Vorbeugung der Corona-Virus-Krankheit 2019 (COVID-19) sowie zur Impfpriorisierung bei Menschen mit Epilepsie gesichtet, diese zusammengefasst und geben die unten genannten Empfehlungen ab.
Introduction and Objective: Identifying patients that benefit from cisplatin-based adjuvant chemotherapy is a major issue in the management of muscle-invasive bladder cancer (MIBC). The purpose of this study is to correlate “luminal” and “basal” type protein expression with histological subtypes, to investigate the prognostic impact on survival after adjuvant chemotherapy and to define molecular consensus subtypes of “double negative” patients (i.e., without expression of CK5/6 or GATA3).
Materials and Methods: We performed immunohistochemical (IHC) analysis of CK5/6 and GATA3 for surrogate molecular subtyping in 181 MIBC samples. The mRNA expression profiles for molecular consensus classification were determined in CK5/6 and GATA3 (double) negative cases using a transcriptome panel with 19.398 mRNA targets (HTG Molecular Diagnostics). Data of 110 patients undergoing radical cystectomy were available for survival analysis.
Results: The expression of CK5/6 correlated with squamous histological subtype (96%) and expression of GATA3 was associated with micropapillary histology (100%). In the multivariate Cox-regression model, patients receiving adjuvant chemotherapy had a significant survival benefit (hazard ratio [HR]: 0.19 95% confidence interval [CI]: 0.1–0.4, p < 0.001) and double-negative cases had decreased OS (HR: 4.07; 95% CI: 1.5–10.9, p = 0.005). Double negative cases were classified as NE-like (30%), stroma-rich (30%), and Ba/Sq (40%) consensus molecular subtypes and displaying different histological subtypes.
Background and Aims: The prevalence of hepatitis C virus (HCV) antibodies in Germany has been estimated to be in the range of 0.4–0.63%. Screening for HCV is recommended in patients with elevated ALT levels or significant risk factors for HCV transmission only. However, 15–30% of patients report no risk factors and ALT levels can be normal in up to 20–30% of patients with chronic HCV infection. The aim of this study was to assess the HCV seroprevalence in patients visiting two tertiary care emergency departments in Berlin and Frankfurt, respectively.
Methods: Between May 2008 and March 2010, a total of 28,809 consecutive patients were screened for the presence of anti-HCV antibodies. Anti-HCV positive sera were subsequently tested for HCV-RNA.
Results: The overall HCV seroprevalence was 2.6% (95% CI: 2.4–2.8; 2.4% in Berlin and 3.5% in Frankfurt). HCV-RNA was detectable in 68% of anti-HCV positive cases. Thus, the prevalence of chronic HCV infection in the overall study population was 1.6% (95% CI 1.5–1.8). The most commonly reported risk factor was former/current injection drug use (IDU; 31.2%) and those with IDU as the main risk factor were significantly younger than patients without IDU (p<0.001) and the male-to-female ratio was 72% (121 vs. 46 patients; p<0.001). Finally, 18.8% of contacted HCV-RNA positive patients had not been diagnosed previously.
Conclusions: The HCV seroprevalence was more than four times higher compared to current estimates and almost one fifth of contacted HCV-RNA positive patients had not been diagnosed previously.
There is a need for diagnostic biomarkers of epilepsy and status epilepticus to support clinical examination, electroencephalography and neuroimaging. Extracellular microRNAs may be potentially ideal biomarkers since some are expressed uniquely within specific brain regions and cell types. Cerebrospinal fluid offers a source of microRNA biomarkers with the advantage of being in close contact with the target tissue and sites of pathology. Here we profiled microRNA levels in cerebrospinal fluid from patients with temporal lobe epilepsy or status epilepticus, and compared findings to matched controls. Differential expression of 20 microRNAs was detected between patient groups and controls. A validation phase included an expanded cohort and samples from patients with other neurological diseases. This identified lower levels of miR-19b in temporal lobe epilepsy compared to controls, status epilepticus and other neurological diseases. Levels of miR-451a were higher in status epilepticus compared to other groups whereas miR-21-5p differed in status epilepticus compared to temporal lobe epilepsy but not to other neurological diseases. Targets of these microRNAs include proteins regulating neuronal death, tissue remodelling, gliosis and inflammation. The present study indicates cerebrospinal fluid contains microRNAs that can support differential diagnosis of temporal lobe epilepsy and status epilepticus from other neurological and non-neurological diseases.
The Board of Directors of the German Society of Epileptology and the committee on epilepsy and syncope of the German Society of Neurology have reviewed the current data on vaccination to prevent coronavirus disease 2019 (COVID-19) and vaccination prioritization in people with epilepsy and provide a summary and recommendations.
The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form.
BACKGROUND AND PURPOSE: We evaluated cerebral white and gray matter changes in patients with iRLS in order to shed light on the pathophysiology of this disease.
METHODS: Twelve patients with iRLS were compared to 12 age- and sex-matched controls using whole-head diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) techniques. Evaluation of the DTI scans included the voxelwise analysis of the fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD).
RESULTS: Diffusion tensor imaging revealed areas of altered FA in subcortical white matter bilaterally, mainly in temporal regions as well as in the right internal capsule, the pons, and the right cerebellum. These changes overlapped with changes in RD. Voxel-based morphometry did not reveal any gray matter alterations.
CONCLUSIONS: We showed altered diffusion properties in several white matter regions in patients with iRLS. White matter changes could mainly be attributed to changes in RD, a parameter thought to reflect altered myelination. Areas with altered white matter microstructure included areas in the internal capsule which include the corticospinal tract to the lower limbs, thereby supporting studies that suggest changes in sensorimotor pathways associated with RLS.
Highlights
• Piriform cortex and amgydala can be separated based on their distinct structural connectivity.
• Similar to histological findings, the connectivity of the piriform cortex suggests posterior frontal and temporal subregions.
• Subregions of the piriform cortex have distinct connectivity profiles.
• Anterior PC extended into ventrotemporal PC posteriorly, which has not been described before, requiring further investigation.
• All parcellations were made publicly available.
Abstract
The anatomy of the human piriform cortex (PC) is poorly understood. We used a bimodal connectivity-based-parcellation approach to investigate subregions of the PC and its connectional differentiation from the amygdala.
One hundred (55 % female) genetically unrelated subjects from the Human Connectome Project were included. A region of interest (ROI) was delineated bilaterally covering PC and amygdala, and functional and structural connectivity of this ROI with the whole gray matter was computed. Spectral clustering was performed to obtain bilateral parcellations at granularities of k = 2–10 clusters and combined bimodal parcellations were computed. Validity of parcellations was assessed via their mean individual-to-group similarity per adjusted rand index (ARI).
Individual-to-group similarity was higher than chance in both modalities and in all clustering solutions. The amygdala was clearly distinguished from PC in structural parcellations, and olfactory amygdala was connectionally more similar to amygdala than to PC. At higher granularities, an anterior and ventrotemporal and a posterior frontal cluster emerged within PC, as well as an additional temporal cluster at their boundary. Functional parcellations also showed a frontal piriform cluster, and similar temporal clusters were observed with less consistency. Results from bimodal parcellations were similar to the structural parcellations. Consistent results were obtained in a validation cohort.
Distinction of the human PC from the amygdala, including its olfactory subregions, is possible based on its structural connectivity alone. The canonical fronto-temporal boundary within PC was reproduced in both modalities and with consistency. All obtained parcellations are freely available.
Highlights:
• Assessment of body composition parameters in a large cohort of patients with HCC undergoing TACE.
• Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition.
• Skeletal muscle volume and related parameters were independent prognostic factors in patients with HCC undergoing TACE.
Background & Aims: Body composition assessment (BCA) parameters have recently been identified as relevant prognostic factors for patients with hepatocellular carcinoma (HCC). Herein, we aimed to investigate the role of BCA parameters for prognosis prediction in patients with HCC undergoing transarterial chemoembolization (TACE).
Methods: This retrospective multicenter study included a total of 754 treatment-naïve patients with HCC who underwent TACE at six tertiary care centers between 2010–2020. Fully automated artificial intelligence-based quantitative 3D volumetry of abdominal cavity tissue composition was performed to assess skeletal muscle volume (SM), total adipose tissue (TAT), intra- and intermuscular adipose tissue, visceral adipose tissue, and subcutaneous adipose tissue (SAT) on pre-intervention computed tomography scans. BCA parameters were normalized to the slice number of the abdominal cavity. We assessed the influence of BCA parameters on median overall survival and performed multivariate analysis including established estimates of survival.
Results: Univariate survival analysis revealed that impaired median overall survival was predicted by low SM (p <0.001), high TAT volume (p = 0.013), and high SAT volume (p = 0.006). In multivariate survival analysis, SM remained an independent prognostic factor (p = 0.039), while TAT and SAT volumes no longer showed predictive ability. This predictive role of SM was confirmed in a subgroup analysis of patients with BCLC stage B.
Conclusions: SM is an independent prognostic factor for survival prediction. Thus, the integration of SM into novel scoring systems could potentially improve survival prediction and clinical decision-making. Fully automated approaches are needed to foster the implementation of this imaging biomarker into daily routine.
Impact and implications: Body composition assessment parameters, especially skeletal muscle volume, have been identified as relevant prognostic factors for many diseases and treatments. In this study, skeletal muscle volume has been identified as an independent prognostic factor for patients with hepatocellular carcinoma undergoing transarterial chemoembolization. Therefore, skeletal muscle volume as a metaparameter could play a role as an opportunistic biomarker in holistic patient assessment and be integrated into decision support systems. Workflow integration with artificial intelligence is essential for automated, quantitative body composition assessment, enabling broad availability in multidisciplinary case discussions.