Introduction: Non-invasive methods that can characterize a tumor's molecular features could enhance treatment management. Recently, researchers have investigated tumor heterogeneity on imaging to assess how grainy or coarse a tumor seems to be in the search for oncologic prognostic markers and mechanisms. Quantitative computed tomography (CT) based texture analysis (qCTTA) has been used to derive tumor heterogeneity information, and the appearance of the tumors has been shown to relate to patient outcome in esophageal, colorectal, lung and head and neck cancer and treatment response in metastatic renal cell cancer. Furthermore histological assessment has demonstrated an association between qCTTA and hypoxia and angiogenesis in lung cancer and very recently qCTTA in combination with CT blood-flow and PET glucose-uptake identified an imaging signature for K-ras mutation status in colorectal cancer. In this study, we examined the predictive potential of tumoral qCTTA to differentiate K-ras mutant and K-ras wildtype tumors and its prognostic potential using non-contrast CT imaging in non-small cell lung cancer (NSCLC).

Methods: Formalin-fixed, paraffin-embedded (FFPE) lung tumor tissues from patients with stage I and II NSCLC, diagnosed between 2001 and 2007 and undergoing definitive surgical resection were obtained. Tumor DNA was extracted and analyzed on the LungCarta Panel that interrogates 213 somatic mutations in 26 oncogenes and/or tumor suppressor genes. Cases with a K-ras mutation or pan-wildtype for all 26 oncogenes and tumor suppressor genes were selected for imaging analysis. Baseline pre-treatment non-contrast CT images that were performed as part of standard of care were retrieved for qCTTA. qCTTA was applied to regions of interest in the primary tumor and comprised an image filtration-histogram technique; where the filtration technique enhanced features of different sizes based on the spatial scale filter (SSF) value varying from fine (2mm in radius), medium (3-5mm in radius) and coarse (6mm in radius) followed by quantification of the histogram parameters – kurtosis (a measure of peakedness and tailedness) and skewness (a measure of asymmetry of the histogram). Non-parametric Mann Whitney test assessed the ability of the qCTTA, clinical and patient characteristics to differentiate between K-ras mutation from pan-wildtype whereas Kaplan-Meier survival analysis assessed the ability of these markers including K-ras mutation to predict survival.

Results: 48 cases were identified and qCTTA was applied to pre-treatment non-contrast CT. The median age was 70.4 years (range 45.1-85.1), 29 were men, and 46 had a smoking history. There were 33 adenocarcinomas, 10 squamous cell carcinomas, and 5 other NSCLC. Stages IA, IB, IIA, and IIB were 16, 21, 6, and 5; respectively. At least 33 patients did not receive adjuvant chemotherapy. There were 27 cases with K-ras mutation and 21 cases that were pan-wildtype. As of the last follow-up, 18 had confirmed disease relapse, including 5 with brain metastasis, and 22 were deceased. The median disease-free survival (DFS) was 39.7 months and median overall survival (OS) was 45.0 months. Positive skewness (p=0.031) and lower kurtosis (p=0.009) were significantly associated with the presence of a K-ras mutation (n=27 vs. 21 pan-wildtype). Kurtosis was a significant predictor of OS (p=0.009) and DFS (p=0.04) with a lower kurtosis value linked with poorer survival. As expected, patients with disease relapse and older age had significantly inferior OS and DFS, whereas adenocarcinomas (n=30) had inferior DFS vs. non-adenocarcinomas (n=14)(p=0.031). In line with other published data in early-stage NSCLC, K-ras was not associated with OS or DFS.

Conclusions: The outcomes in this dataset are in sync with published poor clinical prognostic features in early-stage NSCLC. Lower kurtosis (which may reflect increased number of highlighted features and intensity variation in highlighted features) and positive skewness (which may reflect bright highlighted features surrounded by darker background or lower density areas) are significantly associated with K-ras mutations. These features may suggest more tumoral necrosis and these may be due to the hostile microenvironment within a K-ras driven tumor. A qCTTA feature such as lower kurtosis is prognostic for poorer OS and DFS. Non-invasive qCTTA can differentiate the presence of K-ras mutation from pan-wildtype NSCLC and is associated with patient survival.

Citation Format: Glen J. Weiss, Balaji Ganeshan, Kenneth A. Miles, David A. Campbell, Philip Y. Cheung, Samuel Frank, Ronald L. Korn. Noninvasive image texture analysis differentiates K-ras mutation from pan-wildtype NSCLC and is prognostic. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr A34.