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the claim

Radiation exposure can be accurately derived from DICOM metadata files

the verdict
SUPPORTED
the evidence backs this
Recorded sources
5 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that radiation exposure can be accurately derived from DICOM metadata files?

Yes. Multiple studies demonstrate that patient radiation exposure and dose metrics can be reliably and accurately derived from DICOM metadata files.

Verdict: SUPPORTED · 5 sources for, 0 against · Last checked

The analysis

The retrieved papers consistently show that DICOM headers and metadata contain the necessary technical parameters (such as kVp, mAs, and dose descriptors) to accurately track, estimate, and calculate patient radiation exposure in clinical imaging. There are no papers refuting this claim.

Evidence for · 5
Radiation exposure of computed tomography imaging for the assessment of acute stroke
2020
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Zensen, S., Guberina, N., Opitz, M., Köhrmann, M., Deuschl, C., Forsting, M., Wetter, A., & Bos, D. (2020). Radiation exposure of computed tomography imaging for the assessment of acute stroke. doi.org. https://doi.org/10.1007/s00234-020-02548-z

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More for · 4
AUTOMATIC BRAIN DOSE ESTIMATION IN COMPUTED TOMOGRAPHY USING PATIENT DICOM IMAGES
2020
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Gharbi, S., Labidi, S., & Mars, M. (2020). AUTOMATIC BRAIN DOSE ESTIMATION IN COMPUTED TOMOGRAPHY USING PATIENT DICOM IMAGES. doi.org. https://doi.org/10.1093/rpd/ncaa006

Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool
2015
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Brady, S. L. & Kaufman, R. A. (2015). Estimating pediatric entrance skin dose from digital radiography examination using DICOM metadata: A quality assurance tool. doi.org. https://doi.org/10.1118/1.4918324

Machine learning‐based estimation of patient body weight from radiation dose metrics in computed tomography
2024
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Ichikawa, H., Ichikawa, S., & Sawane, Y. (2024). Machine learning‐based estimation of patient body weight from radiation dose metrics in computed tomography. doi.org. https://doi.org/10.1002/acm2.14467

Audit of data from examination image headers collected for quality assurance in the ECOG-ACRIN EA1151 tomosynthesis mammographic imaging screening trial (TMIST).
2023
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AK, M., GE, M., JG, M., E, P., SZ, S., O, A., & MJ, Y. (2023). Audit of data from examination image headers collected for quality assurance in the ECOG-ACRIN EA1151 tomosynthesis mammographic imaging screening trial (TMIST).. doi.org. https://doi.org/10.1002/mp.16772

What does the evidence say?

The retrieved papers consistently show that DICOM headers and metadata contain the necessary technical parameters (such as kVp, mAs, and dose descriptors) to accurately track, estimate, and calculate patient radiation exposure in clinical imaging. There are no papers refuting this claim.

Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 8504 Aug 2026
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