Ho-ho-ho! Gather around, my dear friends, as I tell you a fascinating tale from the land of medical marvels, where the elves—ah, I mean scientists—are tirelessly working to bring joy and health to all. This story unfolds in a place not so far from the North Pole, where the challenge of evaluating bone changes in chronic kidney diseases (CKD) has puzzled many. But fear not, for the spirit of innovation has led to a breakthrough, much like finding the perfect toy for a hard-to-please child on Christmas Eve.

In this tale, our heroes embarked on a journey with 75 patients blessed with stage 1 CKD (CKD1) and another 75 navigating the stormy seas of stage 5 CKD (CKD5). Their sleigh? None other than the chest CT radiomics method, guided by the bright nose of 3D Slicer software, lighting the way through the dense fog of medical uncertainty. These brave souls ventured to compare the radiomics features of bone between CKD1 and CKD5 cases, discovering not one, not two, but forty radiomics features that differed significantly (P <0.05), much like distinguishing between reindeers with shiny noses and those without.

But what’s a Christmas story without a bit of magic? Using the enchanting spells of maximum correlation minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO), our heroes selected five features to establish a prediction model as carefully as I choose the best cookies left out for me on Christmas Eve. This model, my dear friends, was as reliable as my reindeer on a foggy night, with the area under the receiver operating characteristic curve shining bright at 0.903 and 0.854 for the training and validation cohorts, respectively, in determining CKD1 and CKD5.

So, as we wrap up this tale with a bow, let us rejoice in the knowledge that chest CT radiomics is indeed a feasible sleigh for evaluating bone changes caused by CKD, bringing hope and joy to many, much like a well-delivered present on Christmas morning. Ho-ho-ho! Merry Christmas and a healthy New Year to all!