Your browser doesn't support javascript.
Submillisievert chest CT in patients with COVID-19 - experiences of a German Level-I center.
Hamper, Christina M; Fleckenstein, Florian Nima; Büttner, Laura; Hamm, Bernd; Thieme, Nadine; Thiess, Hans-Martin; Scholz, Oriane; Döllinger, Felix; Böning, Georg.
  • Hamper CM; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Fleckenstein FN; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Büttner L; Berlin Institute of Health (BIH), Anna-Louisa-Karsch 2, 10178 Berlin, Germany.
  • Hamm B; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Thieme N; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Thiess HM; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Scholz O; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Döllinger F; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Böning G; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
Eur J Radiol Open ; 7: 100283, 2020.
Article in English | MEDLINE | ID: covidwho-898807
ABSTRACT

PURPOSE:

Computed tomography (CT) is used for initial diagnosis and therapy monitoring of patients with coronavirus disease 2019 (COVID-19). As patients of all ages are affected, radiation dose is a concern. While follow-up CT examinations lead to high cumulative radiation doses, the ALARA principle states that the applied dose should be as low as possible while maintaining adequate image quality. The aim of this study was to evaluate parameter settings for two commonly used CT scanners to ensure sufficient image quality/diagnostic confidence at a submillisievert dose. MATERIALS AND

METHODS:

We retrospectively analyzed 36 proven COVID-19 cases examined on two different scanners. Image quality was evaluated objectively as signal-to-noise ratio (SNR)/contrast-to-noise ratio (CNR) measurement and subjectively by two experienced, independent readers using 3-point Likert scales. CT dose index volume (CTDIvol) and dose-length product (DLP) were extracted from dose reports, and effective dose was calculated.

RESULTS:

With the tested parameter settings we achieved effective doses below 1 mSv (median 0.5 mSv, IQR 0.2 mSv, range 0.3-0.9 mSv) in all 36 patients. Thirty-four patients had typical COVID-19 findings. Both readers were confident regarding the typical COVID-19 CT-characteristics in all cases (3 ± 0). Objective image quality parameters were SNRnormal lung 17.0 ± 5.9, CNRGGO/normal lung 7.5 ± 5.0, and CNRconsolidation/normal lung 15.3 ± 6.1.

CONCLUSION:

With the tested parameters, we achieved applied doses in the submillisievert range, on two different CT scanners without sacrificing diagnostic confidence regarding COVID-19 findings.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Prognostic study / Qualitative research Language: English Journal: Eur J Radiol Open Year: 2020 Document Type: Article Affiliation country: J.ejro.2020.100283

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Prognostic study / Qualitative research Language: English Journal: Eur J Radiol Open Year: 2020 Document Type: Article Affiliation country: J.ejro.2020.100283