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  • 1
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    A new calibration method for charm jet identification validated with proton-proton collision events at √s = 13 TeV
    IOP Publishing ; 2022
    In:  Journal of Instrumentation Vol. 17, No. 03 ( 2022-03-01), p. P03014-
    Details
    In: Journal of Instrumentation, IOP Publishing, Vol. 17, No. 03 ( 2022-03-01), p. P03014-
    Abstract: Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.
    Type of Medium: Online Resource
    ISSN: 1748-0221
    URL: Article
    DOI: 10.1088/1748-0221/17/03/P03014
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
    detail.hit.zdb_id: 2235672-1
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  • 2
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    NIMG-83. MULTIMODAL PET/MRI RADIOMICS AND CLINICAL PARAMETERS FOR OVERALL SURVIVAL PREDICTION IN PATIENTS WITH IDH WILDTYPE GLIOBLASTOMA
    Oxford University Press (OUP) ; 2022
    In:  Neuro-Oncology Vol. 24, No. Supplement_7 ( 2022-11-14), p. vii184-vii184
    Details
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 24, No. Supplement_7 ( 2022-11-14), p. vii184-vii184
    Abstract: Currently, most radiomics studies on survival prediction in brain tumor patients are based on MRI only. The goal of our study was to evaluate multimodal radiomics derived from amino acid PET/MRI and clinical parameters for survival prediction in patients with newly diagnosed IDH wildtype glioblastoma. METHODS Sixty-three patients with newly diagnosed IDH wildtype glioblastoma were evaluated retrospectively. At initial diagnosis, all patients underwent structural MRI and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET. Tumor volumes were automatically segmented using a deep learning-based tool followed by visual inspection. Predefined and deep radiomics features were extracted from both imaging modalities. Feature repeatability analyses and feature selection were performed to avoid overfitting. Cox regression models for overall survival were built from clinical parameters such as age or the extent of resection, radiomics features, and combinations thereof, and finally validated using 5-fold cross-validation. Further evaluation of the model in an external test dataset is ongoing. RESULTS The median overall survival was 12 months (range, 0-64 months). Higher age and larger FET PET tumor volumes were significantly correlated with shorter overall survival (age, r=-0.39, p & lt; 0.001; volume, r=-0.31, p & lt; 0.05). Models solely based on predefined FET PET or MRI radiomics features showed a similar mean concordance index (C-index) as the model based on clinical parameters (C-indices, 0.68±0.04; 0.64±0.03; and 0.69±0.08, respectively). Multimodal radiomics based on predefined and deep features yielded improved C-indices of 0.75±0.06 and 0.72±0.09, respectively. A model based on multimodal radiomics and clinical parameters achieved the best prognostic performance (C-index, 0.80±0.04). CONCLUSION Our results suggest an added clinical value of multimodal FET PET/MRI radiomics with clinical parameters for the non-invasive survival prediction in patients with IDH wildtype glioblastoma.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    URL: Article
    DOI: 10.1093/neuonc/noac209.701
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2094060-9
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  • 3
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    Use of advanced neuroimaging and artificial intelligence in meningiomas
    Wiley ; 2022
    In:  Brain Pathology Vol. 32, No. 2 ( 2022-03)
    Details
    In: Brain Pathology, Wiley, Vol. 32, No. 2 ( 2022-03)
    Abstract: Anatomical cross‐sectional imaging methods such as contrast‐enhanced MRI and CT are the standard for the delineation, treatment planning, and follow‐up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non‐invasively provide detailed insights into the molecular and metabolic features of meningiomas. These techniques are usually based on MRI, e.g., perfusion‐weighted imaging, diffusion‐weighted imaging, MR spectroscopy, and positron emission tomography. Furthermore, artificial intelligence methods such as radiomics offer the potential to extract quantitative imaging features from routinely acquired anatomical MRI and CT scans and advanced imaging techniques. This allows the linking of imaging phenotypes to meningioma characteristics, e.g., the molecular‐genetic profile. Here, we review several diagnostic applications and future directions of these advanced neuroimaging techniques, including radiomics in preclinical models and patients with meningioma.
    Type of Medium: Online Resource
    ISSN: 1015-6305 , 1750-3639
    URL: Issue
    URL: Article
    DOI: 10.1111/bpa.v32.2
    DOI: 10.1111/bpa.13015
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2029927-8
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  • 4
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    Evaluation of FET PET Radiomics Feature Repeatability in Glioma Patients
    MDPI AG ; 2021
    In:  Cancers Vol. 13, No. 4 ( 2021-02-05), p. 647-
    Details
    In: Cancers, MDPI AG, Vol. 13, No. 4 ( 2021-02-05), p. 647-
    Abstract: Amino acid PET using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine (FET) has attracted considerable interest in neurooncology. Furthermore, initial studies suggested the additional diagnostic value of FET PET radiomics in brain tumor patient management. However, the conclusiveness of radiomics models strongly depends on feature generalizability. We here evaluated the repeatability of feature-based FET PET radiomics. A test–retest analysis based on equivalent but statistically independent subsamples of FET PET images was performed in 50 newly diagnosed and histomolecularly characterized glioma patients. A total of 1,302 radiomics features were calculated from semi-automatically segmented tumor volumes-of-interest (VOIs). Furthermore, to investigate the influence of the spatial resolution of PET on repeatability, spherical VOIs of different sizes were positioned in the tumor and healthy brain tissue. Feature repeatability was assessed by calculating the intraclass correlation coefficient (ICC). To further investigate the influence of the isocitrate dehydrogenase (IDH) genotype on feature repeatability, a hierarchical cluster analysis was performed. For tumor VOIs, 73% of first-order features and 71% of features extracted from the gray level co-occurrence matrix showed high repeatability (ICC 95% confidence interval, 0.91–1.00). In the largest spherical tumor VOIs, 67% of features showed high repeatability, significantly decreasing towards smaller VOIs. The IDH genotype did not affect feature repeatability. Based on 297 repeatable features, two clusters were identified separating patients with IDH-wildtype glioma from those with an IDH mutation. Our results suggest that robust features can be obtained from routinely acquired FET PET scans, which are valuable for further standardization of radiomics analyses in neurooncology.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers13040647
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2527080-1
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  • 5
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    Oligo(cis-1,4-isoprene) aldehyde-oxidizing dehydrogenases of the rubber-degrading bacterium Gordonia polyisoprenivorans VH2
    Springer Science and Business Media LLC ; 2017
    In:  Applied Microbiology and Biotechnology Vol. 101, No. 21 ( 2017-11), p. 7945-7960
    Details
    In: Applied Microbiology and Biotechnology, Springer Science and Business Media LLC, Vol. 101, No. 21 ( 2017-11), p. 7945-7960
    Type of Medium: Online Resource
    ISSN: 0175-7598 , 1432-0614
    URL: Article
    DOI: 10.1007/s00253-017-8508-x
    RVK:
    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 1464336-4
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  • 6
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    Combinations of single-top-quark production cross-section measurements and |fLVVtb| determinations at $$ \sqrt{s} $$ = 7 and 8 TeV with the ATLAS and CMS experiments
    Springer Science and Business Media LLC ; 2019
    In:  Journal of High Energy Physics Vol. 2019, No. 5 ( 2019-05)
    Details
    In: Journal of High Energy Physics, Springer Science and Business Media LLC, Vol. 2019, No. 5 ( 2019-05)
    Abstract: This paper presents the combinations of single-top-quark production cross-section measurements by the ATLAS and CMS Collaborations, using data from LHC proton-proton collisions at $$ \sqrt{s} $$ s = 7 and 8 TeV corresponding to integrated luminosities of 1.17 to 5.1 fb −1 at $$ \sqrt{s} $$ s = 7 TeV and 12.2 to 20.3 fb −1 at $$ \sqrt{s} $$ s = 8 TeV. These combinations are performed per centre-of-mass energy and for each production mode: t -channel, tW , and s -channel. The combined t -channel cross-sections are 67.5 ± 5.7 pb and 87.7 ± 5.8 pb at $$ \sqrt{s} $$ s = 7 and 8 TeV respectively. The combined tW cross-sections are 16.3 ± 4.1 pb and 23.1 ± 3.6 pb at $$ \sqrt{s} $$ s = 7 and 8 TeV respectively. For the s -channel cross-section, the combination yields 4.9 ± 1.4 pb at $$ \sqrt{s} $$ s = 8 TeV. The square of the magnitude of the CKM matrix element V tb multiplied by a form factor f LV is determined for each production mode and centre-of-mass energy, using the ratio of the measured cross-section to its theoretical prediction. It is assumed that the top-quark-related CKM matrix elements obey the relation | V td |, | V ts | ≪ | V tb |. All the | f LV V tb | 2 determinations, extracted from individual ratios at $$ \sqrt{s} $$ s = 7 and 8 TeV, are combined, resulting in | f LV V tb | = 1.02 ± 0.04 (meas.) ± 0.02 (theo.). All combined measurements are consistent with their corresponding Standard Model predictions.
    Type of Medium: Online Resource
    ISSN: 1029-8479
    URL: Article
    DOI: 10.1007/JHEP05(2019)088
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2027350-2
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  • 7
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    Combination of inclusive top-quark pair production cross-section measurements using ATLAS and CMS data at $$ \sqrt{s} $$ = 7 and 8 TeV
    Springer Science and Business Media LLC ; 2023
    In:  Journal of High Energy Physics Vol. 2023, No. 7 ( 2023-07-27)
    Details
    In: Journal of High Energy Physics, Springer Science and Business Media LLC, Vol. 2023, No. 7 ( 2023-07-27)
    Abstract: A combination of measurements of the inclusive top-quark pair production cross-section performed by ATLAS and CMS in proton–proton collisions at centre-of-mass energies of 7 and 8 TeV at the LHC is presented. The cross-sections are obtained using top-quark pair decays with an opposite-charge electron–muon pair in the final state and with data corresponding to an integrated luminosity of about 5 fb − 1 at $$ \sqrt{s} $$ s = 7 TeV and about 20 fb − 1 at $$ \sqrt{s} $$ s = 8 TeV for each experiment. The combined cross-sections are determined to be 178 . 5 ± 4 . 7 pb at $$ \sqrt{s} $$ s = 7 TeV and $$ {243.3}_{-5.9}^{+6.0} $$ 243.3 − 5.9 + 6.0 pb at $$ \sqrt{s} $$ s = 8 TeV with a correlation of 0.41, using a reference top-quark mass value of 172.5 GeV. The ratio of the combined cross-sections is determined to be R 8 / 7 = 1 . 363 ± 0 . 032. The combined measured cross-sections and their ratio agree well with theory calculations using several parton distribution function (PDF) sets. The values of the top-quark pole mass (with the strong coupling fixed at 0.118) and the strong coupling (with the top-quark pole mass fixed at 172.5 GeV) are extracted from the combined results by fitting a next-to-next-to-leading-order plus next-to-next-to-leading-log QCD prediction to the measurements. Using a version of the NNPDF3.1 PDF set containing no top-quark measurements, the results obtained are $$ {m}_t^{\textrm{pole}}={173.4}_{-2.0}^{+1.8} $$ m t pole = 173.4 − 2.0 + 1.8 GeV and $$ {\alpha}_{\textrm{s}}\left({m}_Z\right)={0.1170}_{-0.0018}^{+0.0021} $$ α s m Z = 0.1170 − 0.0018 + 0.0021 .
    Type of Medium: Online Resource
    ISSN: 1029-8479
    URL: Article
    DOI: 10.1007/JHEP07(2023)213
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2027350-2
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  • 8
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    Combination of the W boson polarization measurements in top quark decays using ATLAS and CMS data at $$ \sqrt{s} $$ = 8 TeV
    Springer Science and Business Media LLC ; 2020
    In:  Journal of High Energy Physics Vol. 2020, No. 8 ( 2020-08)
    Details
    In: Journal of High Energy Physics, Springer Science and Business Media LLC, Vol. 2020, No. 8 ( 2020-08)
    Abstract: The combination of measurements of the W boson polarization in top quark decays performed by the ATLAS and CMS collaborations is presented. The measurements are based on proton-proton collision data produced at the LHC at a centre-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of about 20 fb − 1 for each experiment. The measurements used events containing one lepton and having different jet multiplicities in the final state. The results are quoted as fractions of W bosons with longitudinal ( F 0 ), left-handed ( F L ), or right-handed ( F R ) polarizations. The resulting combined measurements of the polarization fractions are F 0 = 0 . 693 ± 0 . 014 and F L = 0 . 315 ± 0 . 011. The fraction F R is calculated from the unitarity constraint to be F R = − 0 . 008 ± 0 . 007. These results are in agreement with the standard model predictions at next-to-next-to-leading order in perturbative quantum chromodynamics and represent an improvement in precision of 25 (29)% for F 0 ( F L ) with respect to the most precise single measurement. A limit on anomalous right-handed vector ( V R ), and left- and right-handed tensor ( g L , g R ) tWb couplings is set while fixing all others to their standard model values. The allowed regions are [ − 0 . 11 , 0 . 16] for V R , [ − 0 . 08 , 0 . 05] for g L , and [ − 0 . 04 , 0 . 02] for g R , at 95% confidence level. Limits on the corresponding Wilson coefficients are also derived.
    Type of Medium: Online Resource
    ISSN: 1029-8479
    URL: Article
    DOI: 10.1007/JHEP08(2020)051
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2027350-2
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  • 9
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    Radiomics for the non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to non-small cell lung cancer 
    Springer Science and Business Media LLC ; 2023
    In:  Journal of Neuro-Oncology Vol. 163, No. 3 ( 2023-07), p. 597-605
    Details
    In: Journal of Neuro-Oncology, Springer Science and Business Media LLC, Vol. 163, No. 3 ( 2023-07), p. 597-605
    Abstract: The expression level of the programmed cell death ligand 1 (PD-L1) appears to be a predictor for response to immunotherapy using checkpoint inhibitors in patients with non-small cell lung cancer (NSCLC). As differences in terms of PD-L1 expression levels in the extracranial primary tumor and the brain metastases may occur, a reliable method for the non-invasive assessment of the intracranial PD-L1 expression is, therefore of clinical value. Here, we evaluated the potential of radiomics for a non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to NSCLC. Patients and methods Fifty-three NSCLC patients with brain metastases from two academic neuro-oncological centers (group 1, n = 36 patients; group 2, n = 17 patients) underwent tumor resection with a subsequent immunohistochemical evaluation of the PD-L1 expression. Brain metastases were manually segmented on preoperative T1-weighted contrast-enhanced MRI. Group 1 was used for model training and validation, group 2 for model testing. After image pre-processing and radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. The radiomics model was trained and validated using random stratified cross-validation. Finally, the best-performing radiomics model was applied to the test data. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analyses. Results An intracranial PD-L1 expression (i.e., staining of at least 1% or more of tumor cells) was present in 18 of 36 patients (50%) in group 1, and 7 of 17 patients (41%) in group 2. Univariate analysis identified the contrast-enhancing tumor volume as a significant predictor for PD-L1 expression (area under the ROC curve (AUC), 0.77). A random forest classifier using a four-parameter radiomics signature, including tumor volume, yielded an AUC of 0.83 ± 0.18 in the training data (group 1), and an AUC of 0.84 in the external test data (group 2). Conclusion The developed radiomics classifiers allows for a non-invasive assessment of the intracranial PD-L1 expression in patients with brain metastases secondary to NSCLC with high accuracy.
    Type of Medium: Online Resource
    ISSN: 0167-594X , 1573-7373
    URL: Article
    DOI: 10.1007/s11060-023-04367-7
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2007293-4
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  • 10
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    Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression
    Springer Science and Business Media LLC ; 2022
    In:  Journal of Neuro-Oncology Vol. 159, No. 3 ( 2022-09), p. 519-529
    Details
    In: Journal of Neuro-Oncology, Springer Science and Business Media LLC, Vol. 159, No. 3 ( 2022-09), p. 519-529
    Abstract: To investigate the potential of radiomics applied to static clinical PET data using the tracer O-(2-[ 18 F]fluoroethyl)- l -tyrosine (FET) to differentiate treatment-related changes (TRC) from tumor progression (TP) in patients with gliomas. Patients and Methods One hundred fifty-one (151) patients with histologically confirmed gliomas and post-therapeutic progressive MRI findings according to the response assessment in neuro-oncology criteria underwent a dynamic amino acid PET scan using the tracer O-(2-[ 18 F]fluoroethyl)- l -tyrosine (FET). Thereof, 124 patients were investigated on a stand-alone PET scanner (data used for model development and validation), and 27 patients on a hybrid PET/MRI scanner (data used for model testing). Mean and maximum tumor to brain ratios (TBR mean , TBR max ) were calculated using the PET data from 20 to 40 min after tracer injection. Logistic regression models were evaluated for the FET PET parameters TBR mean , TBR max , and for radiomics features of the tumor areas as well as combinations thereof to differentiate between TP and TRC. The best performing models in the validation dataset were finally applied to the test dataset. The diagnostic performance was assessed by receiver operating characteristic analysis. Results Thirty-seven patients (25%) were diagnosed with TRC, and 114 (75%) with TP. The logistic regression model comprising the conventional FET PET parameters TBR mean and TBR max resulted in an AUC of 0.78 in both the validation (sensitivity, 64%; specificity, 80%) and the test dataset (sensitivity, 64%; specificity, 80%). The model combining the conventional FET PET parameters and two radiomics features yielded the best diagnostic performance in the validation dataset (AUC, 0.92; sensitivity, 91%; specificity, 80%) and demonstrated its generalizability in the independent test dataset (AUC, 0.85; sensitivity, 81%; specificity, 70%). Conclusion The developed radiomics classifier allows the differentiation between TRC and TP in pretreated gliomas based on routinely acquired static FET PET scans with a high diagnostic accuracy.
    Type of Medium: Online Resource
    ISSN: 0167-594X , 1573-7373
    URL: Article
    DOI: 10.1007/s11060-022-04089-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2007293-4
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