Open AccessSoftware-based noise reduction in cranial magnetic resonance imaging: Influence on image quality
Author(s) -
Philipp Fuelkell,
Soenke Langner,
Nele Friedrich,
MarieLuise Kromrey,
Christoph Georg Radosa,
Ivan Platzek,
Birger Mensel,
JensPeter Kühn
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0206196
Subject(s) - fluid attenuated inversion recovery , magnetic resonance imaging , image quality , white matter , nuclear medicine , sound level meter , medicine , sound pressure , physics , nuclear magnetic resonance , radiology , artificial intelligence , acoustics , computer science , noise level , image (mathematics)
Objectives To investigate acoustic noise reduction, image quality and white matter lesion detection rates of cranial magnetic resonance imaging (MRI) scans acquired with and without sequence-based acoustic noise reduction software. Material and methods Thirty-one patients, including 18 men and 13 women, with a mean age of 58.3±14.5 years underwent cranial MRI. A fluid-attenuated inversion recovery (FLAIR) sequence was acquired with and without acoustic noise reduction using the Quiet Suite (QS) software (Siemens Healthcare). During data acquisition, peak sound pressure levels were measured with a sound level meter (Testo, Typ 815). In addition, two observers assessed subjective image quality for both sequences using a five-point scale (1 very good—5 inadequate). Signal-to-noise ratio (SNR) was measured for both sequences in the following regions: white matter, gray matter, and cerebrospinal fluid. Furthermore, lesion detection rates in white matter pathologies were evaluated by two observers for both sequences. Acoustic noise, image quality including SNR and white matter lesion detection rates were compared using the Mann-Whitney-U-test. Results Peak sound pressure levels were slightly but significantly reduced using QS, P ≤0.017. Effective sound pressure, measured in Pascal, was decreased by 19.7%. There was no significant difference in subjective image quality between FLAIR sequences acquired without/with QS: observer 1: 2.03/2.07, P = 0.730; observer 2: 1.98/2.10, P = 0.362. In addition, SNR was significantly increased in white matter, P ≤0.001, and gray matter, P = 0.006, using QS. The lesion detection rates did not decline utilizing QS: observer 1: P = 0.944 observer 2: P = 0.952. Conclusions Sequence-based noise reduction software such as QS can significantly reduce peak sound pressure levels, without a loss of subjective image quality and increase SNR at constant lesion detection rates.