Diffusion Tensor Imaging Can Discriminate the Primary Cell Type of Intracranial Metastases for Patients with Lung Cancer

Abstract

Histopathological differentiation of primary lung cancer is clinically important. We aimed to investigate whether diffusion tensor imaging (DTI) parameters of metastatic brain lesions could predict the histopathological types of the primary lung cancer. Methods: In total, 53 patients with 98 solid metastatic brain lesions of lung cancer were included. Lung tumors were subgrouped as non-small cell carcinoma (NSCLC) (n = 34) and small cell carcinoma (SCLC) (n = 19). Apparent diffusion coefficient (ADC) and Fractional anisotropy (FA) values were calculated from solid enhanced part of the brain metastases. The association between FA and ADC values and histopathological subtype of the primary tumor was investigated. Results: The mean ADC and FA values obtained from the solid part of the brain metastases of SCLC were significantly lower than the NSCLC metastases (P < 0.001 and P = 0.003, respectively). ROC curve analysis showed diagnostic performance for mean ADC values (AUC=0.

Imaging in translational cancer research

“…Because water diffusion in biological tissue is often anisotropic, and not isotropic, i.e., equal in all directions, the concept of a diffusion tensor captures and quantifies this (fractional) anisotropy, thus enabling investigation of preferred tracts of diffusion, e.g., along neuronal fibers in brain tissue or peripheral nerves 66 , 67 . Although used primarily in neuro-oncology 68 , this method has also been shown to be beneficial in determining the histological grade of oral carcinoma 69 ; discriminating between small-cell lung cancer and non-small cell lung cancer brain metastases 70 ; correlating with Gleason scores in prostate cancer 71 ; or predicting parametrial infiltration in cervical cancer 72 .…”