Local diagnostic reference levels for digital mammography: Two hospitals study in northwest, Nigeria.
Compressed breast thickness
DRLs
Mean glandular dose
Optimisation
digital mammography
Journal
Journal of medical imaging and radiation sciences
ISSN: 1876-7982
Titre abrégé: J Med Imaging Radiat Sci
Pays: United States
ID NLM: 101469694
Informations de publication
Date de publication:
09 2021
09 2021
Historique:
received:
07
01
2021
revised:
20
03
2021
accepted:
29
03
2021
pubmed:
27
4
2021
medline:
3
11
2021
entrez:
26
4
2021
Statut:
ppublish
Résumé
Mammography involves the use of low energy X-rays to image the breast tissue. Although low dose radiation is used, the use of ionising radiation implies the risk of inducing breast cancer. Thus, the study established local DRLs for digital mammography for in-house dose optimisation. This was a retrospective study that had a total of 240 women that presented for mammography at the two tertiary institutions located in the Northwest region of Nigeria. Patient demographic information including compressed breast thickness (CBT), which is the breast tissue thickness across the imaging plate, and mean glandular dose (MGD) were recorded. Data were analysed based on descriptive and inferential statistics using SPSS statistical software. The DRLs based on MGD and CBT were established and compared with the relevant data in the literature. Local DRLs based on MGD and CBT were established at the 75th percentile (craniocaudal (CC): 1.50 mGy; 57 mm; mediolateral (MLO): 1.60 mGy; 63 mm) and 95th percentile (CC: 3.74 mGy; 69 mm; MLO: 3.61 mGy; 76 mm). The MGD based on manual exposure was significantly (p < 0.005) higher compared to the automatic optimisation parameter (AOP) mode which suggests the need to continuously adhere to the use of AOP mode for in-house dose optimisation. The study established local DRLs for the digital mammography systems at the 75th and 95th percentiles which compared well with the values established in the literature. Manual selection of parameters should only be employed where there are legitimate indications as it is associated with high exposure. Also, manual selection of parameters should be based on preset tables as a function of compressed breast thickness.
Sections du résumé
BACKGROUND
Mammography involves the use of low energy X-rays to image the breast tissue. Although low dose radiation is used, the use of ionising radiation implies the risk of inducing breast cancer. Thus, the study established local DRLs for digital mammography for in-house dose optimisation.
METHODS
This was a retrospective study that had a total of 240 women that presented for mammography at the two tertiary institutions located in the Northwest region of Nigeria. Patient demographic information including compressed breast thickness (CBT), which is the breast tissue thickness across the imaging plate, and mean glandular dose (MGD) were recorded. Data were analysed based on descriptive and inferential statistics using SPSS statistical software. The DRLs based on MGD and CBT were established and compared with the relevant data in the literature.
RESULTS
Local DRLs based on MGD and CBT were established at the 75th percentile (craniocaudal (CC): 1.50 mGy; 57 mm; mediolateral (MLO): 1.60 mGy; 63 mm) and 95th percentile (CC: 3.74 mGy; 69 mm; MLO: 3.61 mGy; 76 mm). The MGD based on manual exposure was significantly (p < 0.005) higher compared to the automatic optimisation parameter (AOP) mode which suggests the need to continuously adhere to the use of AOP mode for in-house dose optimisation.
CONCLUSION
The study established local DRLs for the digital mammography systems at the 75th and 95th percentiles which compared well with the values established in the literature. Manual selection of parameters should only be employed where there are legitimate indications as it is associated with high exposure. Also, manual selection of parameters should be based on preset tables as a function of compressed breast thickness.
Identifiants
pubmed: 33896746
pii: S1939-8654(21)00075-8
doi: 10.1016/j.jmir.2021.03.035
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
435-442Informations de copyright
Copyright © 2021. Published by Elsevier Inc.