Background
Although histological examination is the standard method for assessing genetic status, the development of a noninvasive method, which can display the heterogeneity of the whole tumor to supplement genotype analysis, might be important for personalized treatment strategies.
Purpose
To evaluate the potential role of diffusion kurtosis imaging (DKI)‐derived parameters using histogram analysis derived from whole‐tumor volumes for prediction of the status of KRAS mutations in patients with rectal adenocarcinoma.
Study Type
Retrospective.
Subjects
In all, 148 consecutive patients with histologically confirmed rectal adenocarcinoma who were treated at our institution.
Sequence
DKI was performed with a 3.0 T MRI system using a single‐shot echo‐planar imaging sequence with b values of 0, 700, 1400, and 2100 sec/mm2.
Assessment
D, K, and apparent diffusion coefficient (ADC) values were measured using whole‐tumor volume histogram analysis and were compared between different KRAS mutations status.
Statistical Tests
Student's t‐test or Mann–Whitney U‐test, and receiver operating characteristic (ROC) curves were used for statistical analysis.
Results
All the percentile metrics of ADC and D values were significantly lower in the mutated group than those in the wildtype group (all P < 0.05), except for the minimum value of ADC and D (both P > 0.05), while K‐related percentile metrics were higher in the mutated group compared with those in the wildtype group (all P < 0.05). Regarding the comparison of the diagnostic performance of all the histogram metrics, K75th showed the highest AUC value of 0.871, and the corresponding values for sensitivity, specificity, positive predictive value, and negative predictive value were 81.43%, 78.21%, 77.03%, and 82.43%, respectively.
Data Conclusion
DKI metrics with whole‐tumor volume histogram analysis is associated with KRAS mutations, and thus may be useful for predicting the KRAS status of rectal cancers for guiding targeted therapy.
Level of Evidence: 3
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2019.
from #Head and Neck by Sfakianakis via simeraentaxei on Inoreader http://bit.ly/2AKsGGp
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