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  1. AU=Charters Pia F P AU=Charters Pia F P
  2. AU="Adumuah, Naa N"
  3. AU="Rodrigues, Jonathan Carl Luis"
  4. AU=Seidel Bastian M
  5. AU="Duan Weimin"
  6. AU=Ioanas M
  7. AU="Nancy Zambon"
  8. AU="Kumawat, Sunita"
  9. AU=Bogliacino Francesco
  10. AU="Setter, Peter"
  11. AU=Shikata Chihiro
  12. AU="Jordan P. Metcalf"
  13. AU=Peri?i? Nanut Milica AU=Peri?i? Nanut Milica
  14. AU="Pramod, Ganapathiraju"
  15. AU="Fu, Chu-Jun"
  16. AU="Nejad, Harry G."
  17. AU="Zhang, Q E"
  18. AU="Oppenheim, Madeline"

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  1. Artikel ; Online: Subacute combined degeneration of the cord secondary to nitrous oxide misuse: No laughing matter.

    Charters, Pia F P / Morrison, Hamish Duncan / Witherick, Jonathan / King, Susan

    BJR case reports

    2021  Band 7, Heft 3, Seite(n) 20200179

    Abstract: Nitrous oxide ( ... ...

    Abstract Nitrous oxide (N
    Sprache Englisch
    Erscheinungsdatum 2021-02-05
    Erscheinungsland England
    Dokumenttyp Case Reports
    ISSN 2055-7159
    ISSN (online) 2055-7159
    DOI 10.1259/bjrcr.20200179
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: 18

    Charters, Pia F P / Little, David / Rodrigues, Jonathan C L / Graham, Richard N / Redman, Stewart L

    BJR case reports

    2020  Band 6, Heft 3, Seite(n) 20200091

    Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the infectious disease COVID-19, was declared a global pandemic in March 2020. As radiology departments ... ...

    Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the infectious disease COVID-19, was declared a global pandemic in March 2020. As radiology departments recommence
    Schlagwörter covid19
    Sprache Englisch
    Erscheinungsdatum 2020-06-26
    Erscheinungsland England
    Dokumenttyp Case Reports
    ISSN 2055-7159
    ISSN (online) 2055-7159
    DOI 10.1259/bjrcr.20200091
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Artificial intelligence can detect left ventricular dilatation on contrast-enhanced thoracic computer tomography relative to cardiac magnetic resonance imaging.

    Asif, Ashar / Charters, Pia F P / Thompson, Charlotte A S / Komber, Hend M E I / Hudson, Benjamin J / Rodrigues, Jonathan Carl Luis

    The British journal of radiology

    2022  Band 95, Heft 1138, Seite(n) 20210852

    Abstract: Objectives: To assess the diagnostic accuracy of an automated algorithm to detect left ventricular (LV) dilatation on non-ECG gated CT, using cardiac magnetic resonance (CMR) as reference standard.: Methods: Consecutive patients with contrast- ... ...

    Abstract Objectives: To assess the diagnostic accuracy of an automated algorithm to detect left ventricular (LV) dilatation on non-ECG gated CT, using cardiac magnetic resonance (CMR) as reference standard.
    Methods: Consecutive patients with contrast-enhanced CT thorax and CMR within 31 days (2016-2020) were analysed (
    Results: Automated diameter analysis was feasible in 92% of cases (77/84; 45 men, age 61 ± 14 years, mean CT to CMR interval 10 ± 8 days). Relative to CMR as a reference standard, 45% had LV dilatation. In males, an automated LV diameter measurement of ≥55.5 mm was ≥90% specific for CMR-defined LV dilatation (positive predictive value (PPV) 85.7%, negative predictive value (NPV) 61.2%, accuracy 68.9%). In females, an LV diameter of ≥49.7 mm was ≥90% specific for CMR-defined LV dilatation (PPV 66.7%, NPV 73.1%, accuracy 71.9%). AI CT volumetry data did not significantly improve AUC performance.
    Conclusion: Fully automated AI-derived analysis LV dilatation on routine unselected non-gated contrast-enhanced CT thorax studies is feasible. We have defined thresholds for the detection of LV dilatation on CT relative to CMR, which could be used to routinely screen for dilated cardiomyopathy at the time of CT.
    Advances in knowledge: We show, for the first time, that a fully-automated AI-derived analysis of maximal LV chamber axial diameter on non-ECG-gated thoracic CT is feasible in unselected real-world cases and that the derived measures can predict LV dilatation relative to cardiac magnetic resonance imaging, the non-invasive reference standard for determining cardiac chamber size. We have derived sex-specific cut-off values to screen for LV dilatation on routine contrast-enhanced thoracic CT. Future work should validate these thresholds and determine if technology can alter clinical outcomes in a cost-effective manner.
    Mesh-Begriff(e) Aged ; Artificial Intelligence ; Computers ; Dilatation ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Reproducibility of Results ; Stroke Volume ; Tomography, X-Ray Computed/methods
    Sprache Englisch
    Erscheinungsdatum 2022-03-18
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2982-8
    ISSN 1748-880X ; 0007-1285
    ISSN (online) 1748-880X
    ISSN 0007-1285
    DOI 10.1259/bjr.20210852
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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