Literature DB >> 30645158

Frequency and Diagnostic Implications of Image Artifacts by Eye-Lens Shielding in Head CT.

Stefan A Schmidt1, Teresa Gruenke1, Meinrad Beer1, Arthur P Wunderlich2.   

Abstract

OBJECTIVE: The eye lens is one of the most radiosensitive organs, and medical radiation is one of the main causes of cataracts. To protect the lens during head CT examinations, protectors have been developed; however, they can lead to image artifacts, which is a major disadvantage of their use. This study retrospectively evaluates the frequency and extent of artifacts caused by these protectors related to three anatomic regions (eye, brain, and bone) and their dependence on protector positioning.
MATERIALS AND METHODS: Datasets from 261 consecutive head CT examinations obtained during 3.5 months of routine clinical imaging were assessed. Diagnostic quality of the images was evaluated by objective measuring and subjective scoring on a 5-point Likert scale. Furthermore, the position of the lens protector in correlation to the eye lens and the intensity and frequency of artifacts were analyzed.
RESULTS: Only 4.6% of all analyzed examinations were completely free from artifacts; 95.4% showed artifacts at least in the orbital cavity. Although the brain was affected in 27.8% of cases, in only 5.8% of cases was there a risk of misinterpretation, such as suspected intracranial bleeding. In 24.9% of cases, the lens was not properly covered by the protector. A too cranial position of the protector was identified as the main risk factor for cerebral artifacts.
CONCLUSION: Eye shielding for brain CT examinations often leads to artifacts. However, in only a small percentage of cases do these artifacts affect tissue depiction in regions beyond the eye (i.e., brain or bones). Correct positioning is mandatory to minimize artifacts.

Entities:  

Keywords:  cranial CT; dose reduction; eye lens protection

Year:  2019        PMID: 30645158     DOI: 10.2214/AJR.18.19929

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  1 in total

1.  Lens Identification to Prevent Radiation-Induced Cataracts Using Convolutional Neural Networks.

Authors:  Ross Filice
Journal:  J Digit Imaging       Date:  2019-08       Impact factor: 4.056

  1 in total

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