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A Novel Shorthand Approach to Knee Bone Age Using MRI: A Validation and Reliability Study. | LitMetric

AI Article Synopsis

  • The study developed a shorthand algorithm for determining bone age using knee MRIs, aiming to increase efficiency and reduce the costs and risks associated with traditional radiographic methods.
  • It involved adolescent patients who had both knee MRIs and hand radiographs, with results showing a strong correlation between the shorthand algorithm's predictions and conventional hand bone age assessments, regardless of the raters' experience levels.
  • The algorithm proved to be reliable, with good interrater agreement, suggesting that it can be effectively utilized by medical students, residents, and attending physicians in clinical settings.

Article Abstract

Background: Bone-age determination remains a difficult process. An atlas for bone age has been created from knee-ossification patterns on magnetic resonance imaging (MRI), thereby avoiding the need for radiographs and associated costs, radiation exposure, and clinical inefficiency. Shorthand methods for bone age can be less time-consuming and require less extensive training as compared with conventional methods.

Purpose: To create and validate a novel shorthand algorithm for bone age based on knee MRIs that could correlate with conventional hand bone age and demonstrate reliability across medical trainees.

Study Design: Cohort study (diagnosis); Level of evidence, 2.

Methods: Included in this study were adolescent patients who underwent both knee MRI and hand bone age radiographs within 90 days between 2009 and 2018. A stepwise algorithm for predicting bone age using knee MRI was developed separately for male and female patients, and 7 raters at varying levels of training used the algorithm to determine the bone age for each MRI. The shorthand algorithm was validated using Spearman rho ( ) to correlate each rater's predicted MRI bone age with the recorded Greulich and Pyle (G&P) hand bone age. Interrater and intrarater reliability were also calculated using intraclass correlation coefficients (ICCs).

Results: A total of 38 patients (44.7% female) underwent imaging at a mean age of 12.8 years (range, 9.3-15.7 years). Shorthand knee MRI bone age scores were strongly correlated with G&P hand bone age ( = 0.83; < .001). The shorthand algorithm was a valid predictor of G&P hand bone age regardless of level of training, as medical students ( = 0.75), residents ( = 0.81), and attending physicians ( = 0.84) performed similarly. The interrater reliability of our shorthand algorithm was 0.81 (95% CI, 0.73-0.88), indicating good to excellent interobserver agreement. Respondents also demonstrated consistency, with 6 of 7 raters demonstrating excellent intrarater reliability (median ICC, 0.86 [range, 0.68-0.96]).

Conclusion: This shorthand algorithm is a consistent, reliable, and valid way to determine skeletal maturity using knee MRI in patients aged 9 to 16 years and can be utilized across different levels of orthopaedic and radiographic expertise. This method is readily applicable in a clinical setting and may reduce the need for routine hand bone age radiographs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8361531PMC
http://dx.doi.org/10.1177/23259671211021582DOI Listing

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