The British journal of radiology · 2023
RRIMS: Radiation Risk In Mammography Screening - model evaluation.
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Hooshmand Sahand, Reed Warren M, Suleiman Mo'ayyad E, Brennan Patrick C
Аннотация
OBJECTIVE: The Radiation Risk In Mammography Screening (RRIMS) model was introduced as a novel tool to help females accurately calculate their lifetime mean glandular dose (MGD) and estimate their population-level risk of radiation-induced breast cancer incidence and mortality.
METHODS: The model's accuracy was evaluated by comparing the received MGD of 317 women who had undergone a total of 733 visits across one to four rounds of screening. This was achieved by comparing the RRIMS predicted dose values with the same examination dose calculated manually by hand. Qualitative and quantitative statistical analyses were performed to assess the percentage difference (% diff) or agreement between the two values.
RESULTS: Qualitative statistical analysis using the Bland-Altman plots demonstrated a statistically significant bias for the % diff between the manually calculated and RRIMS predicted dose values, where the mean (bias) was -2.02% with an upper and lower limit of agreement of 40.24% and -44.27%, respectively. Quantitative statistical analysis revealed an intraclass correlation coefficient (ICC, 3,1) of 0.64 (p-value < 0.001) and a Kendall's W of 0.83 (p-value < 0.001).
CONCLUSION: The results indicate a statistically significant and reasonably good level of agreement between the manually calculated vs RRIMS predicted dose values. This work was focused on one of the major mammography equipment manufacturers that is Hologic, however there is potential for a multivendor applicability study of this model with future iterations. This will further improve upon this innovative dose and risk prediction tool that can empower healthcare professionals when making informed decisions and enhance patient care.
ADVANCES IN KNOWLEDGE: This paper assesses the precision of the dose and risk model that our team has previously established. The results bring us one step closer to providing females and clinicians with a useful tool that can help explain and contextualise the benefits and risks associated with screening mammography.
METHODS: The model's accuracy was evaluated by comparing the received MGD of 317 women who had undergone a total of 733 visits across one to four rounds of screening. This was achieved by comparing the RRIMS predicted dose values with the same examination dose calculated manually by hand. Qualitative and quantitative statistical analyses were performed to assess the percentage difference (% diff) or agreement between the two values.
RESULTS: Qualitative statistical analysis using the Bland-Altman plots demonstrated a statistically significant bias for the % diff between the manually calculated and RRIMS predicted dose values, where the mean (bias) was -2.02% with an upper and lower limit of agreement of 40.24% and -44.27%, respectively. Quantitative statistical analysis revealed an intraclass correlation coefficient (ICC, 3,1) of 0.64 (p-value < 0.001) and a Kendall's W of 0.83 (p-value < 0.001).
CONCLUSION: The results indicate a statistically significant and reasonably good level of agreement between the manually calculated vs RRIMS predicted dose values. This work was focused on one of the major mammography equipment manufacturers that is Hologic, however there is potential for a multivendor applicability study of this model with future iterations. This will further improve upon this innovative dose and risk prediction tool that can empower healthcare professionals when making informed decisions and enhance patient care.
ADVANCES IN KNOWLEDGE: This paper assesses the precision of the dose and risk model that our team has previously established. The results bring us one step closer to providing females and clinicians with a useful tool that can help explain and contextualise the benefits and risks associated with screening mammography.