Tumor density is associated with response to endobronchial ultrasound-guided transbronchial needle injection of cisplatin.

ABSTRACT:

Background

Endobronchial ultrasound-guided transbronchial needle injection of cisplatin (EBUS-TBNI cisplatin) is a therapeutic option for patients with recurrent lung cancer. However, the tumor characteristics that influence the distribution of the agent following intratumoral delivery remain largely unknown.

Methods

We performed a retrospective evaluation of EBUS-TBNI cisplatin cases performed at two centers. Semi-automated tumor segmentation from CT scans was performed while blinded to the outcome of response. Twenty-four algorithmic radiomics features from two categories, Morphology (i.e., shape, volume) and Intensity (i.e., density), were extracted, and feature selection performed via least absolute shrinkage and selection operator (LASSO) regression. Models were constructed from clinicoepidemiologic variables and selected radiomics features and evaluated using the likelihood ratio chi-square assessment and Akaike's information criterion (AIC).

Results

Thirty-eight patients with available imaging data were analyzed. Based on RECIST criteria, 27 of 38 treated sites demonstrated complete or partial remission (71%). The top three features identified by LASSO regression were variance, energy, and kurtosis. All three are measures of intensity, a surrogate for tumor density. Two logistic regression models with the outcome of response were created, each with the top 3 categorical features: (I) an Intensity model including variance, energy, and kurtosis, and (II) a Morphology model including surface-to-volume ratio, spherical disproportion, and maximum 3-dimensional (3D) diameter. Only the Intensity model met criteria for significance (P=0.024), and it resulted in a lower AIC and higher pseudo R square value vs. the Morphology model.

Conclusions

Measures of tumor density are more highly associated with response to EBUS-TBNI cisplatin than measures of morphology.

SUBMITTER: Kinsey CM 

PROVIDER: S-EPMC7578514 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature