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Non-small-cell lung cancer ( NSCLC ) has significant pathological, genetic and cellular heterogeneity, so the prognosis of patients varies greatly.
NSCLC
In this regard, radioomics technology that uses high-dimensional quantitative features extracted from imaging data is a good choice.
Recently, a study published in European Radiology used different CT slice thickness to evaluate the prognosis of NSCLC patients, and explored whether CT slice thickness will affect the performance of the radiomic prognostic model of NSCLC patients.
This study included 311 patients who underwent NSCLC surgical resection between May 2014 and December 2015, and the CT images of each patient with 1, 3, and 5 mm slice thicknesses were evaluated.
On the corresponding layer thickness data set, the c index of the development set Rad1, Rad3 and Rad5 predicted DFS are 0.
Table 1 In the development set, three radioomics models with different layer thicknesses are used to predict the performance of DFS.
Table 2 In the validation set, three radioomics models with different layer thicknesses are used to predict the performance of DFS.
CT layer thickness has no significant impact on the performance of the radiomic model for predicting DFS in patients with non-small cell lung cancer.
Original source:
Original source:Sohee Park,Sang Min Lee,Seonok Kim,et al.
Sohee Park,Sang Min Lee,Seonok Kim,et al.
Performance of radiomics models for survival prediction in non-small-cell lung cancer: influence of CT slice thickness.
DOI: org/10.
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