Reply:
======

* O. Foesleitner
* K.-H. Nenning
* T. Traub-Weidinger
* M. Feucht
* S. Bonelli
* T. Czech
* C. Dorfer
* D. Prayer
* G. Kasprian

We would like to comment on the letter to the Editor regarding our article on corticospinal tract asymmetries in unilateral polymicrogyria.1 We thank Drs Jalalvandi and Naderi for their interest in our work and appreciate the opportunity to respond to their remarks.

In most radiologic studies, the κ value is commonly used to assess interrater reliability. However, as emphasized by the authors and initially shown by Byrt et al,2 it has important weaknesses due to bias and prevalence issues. Byrt et al recommended using the bias and the prevalence indices to address these shortcomings. In addition to several other observations, we documented a high concordance in detecting the presence or absence of corticospinal tract asymmetry in cases of unilateral polymicrogyria by 2 independent observers (9/10 consistent ratings, Table). The low bias (0.22) and prevalence (0.11) indices support the validity of our κ values. If, however, one wanted to use the prevalence-adjusted bias-adjusted κ,2 in our case reaching 0.78, interrater agreement would still show a substantial strength of agreement.2,3 Because the issues mentioned above do not apply to our sample, we opted for the classic κ value.

View this table:
[Table1](http://www.ajnr.org/content/39/11/E124/T1)

Assessment of the corticospinal tract asymmetry by raters A and Ba

In conclusion, we support the call of the letter for caution when using the κ coefficient. However, the issue of neither prevalence nor bias is relevant for our study. Thus, our results allow the conclusion of reliable visual assessment of corticospinal tract asymmetry in unilateral polymicrogyria involving the motor cortex based on T1-weighted and color-coded diffusion tensor imaging maps at the level of the midbrain.

## References

1.  1. Foesleitner O, Nenning KH, Traub-Weidinger T, et al. Assessing corticospinal tract asymmetry in unilateral polymicrogyria. AJNR Am J Neuroradiol 2018;39:1530–35 doi:10.3174/ajnr.A5715 pmid:29954815
    
    [Abstract/FREE Full Text](http://www.ajnr.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NDoiYWpuciI7czo1OiJyZXNpZCI7czo5OiIzOS84LzE1MzAiO3M6NDoiYXRvbSI7czoyMToiL2FqbnIvMzkvMTEvRTEyNC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30=) 

2.  2. Byrt T, Bishop J, Carlin JB. Bias, prevalence and kappa. J Clin Epidemiol 1993;46:423–29 doi:10.1016/0895-4356(93)90018-V pmid:8501467
    
    [CrossRef](http://www.ajnr.org/lookup/external-ref?access_num=10.1016/0895-4356(93)90018-V&link_type=DOI) 
    
    [PubMed](http://www.ajnr.org/lookup/external-ref?access_num=8501467&link_type=MED&atom=%2Fajnr%2F39%2F11%2FE124.atom) 
    
    [Web of Science](http://www.ajnr.org/lookup/external-ref?access_num=A1993LG76300002&link_type=ISI) 

3.  3. Sim J, Wright CC. The kappa statistic in reliability studies: use, interpretation, and sample size requirements. Phys Ther 2005;85:257–68 pmid:15733050
    
    [Abstract/FREE Full Text](http://www.ajnr.org/lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6OToicHRqb3VybmFsIjtzOjU6InJlc2lkIjtzOjg6Ijg1LzMvMjU3IjtzOjQ6ImF0b20iO3M6MjE6Ii9ham5yLzM5LzExL0UxMjQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9) 

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