Can CT measures of tumour heterogeneity stratify risk for nodal metastasis in patients with non-small cell lung cancer?

Abstract

CTTA in NSCLC is related to nodal status in patients without distant metastases and has the potential to inform selection of investigative strategies for the assessment of mediastinal malignancy.

Radiomics predicts survival of patients with advanced non‑small cell lung cancer undergoing PD‑1 blockade using Nivolumab

“…The GLCM-entropy, specifically measures the randomness of gray-level voxel pairs, and has been significantly associated, as above, with a worse prognosis in other works (19,27,30).…”

“…In our analysis, a higher histogram entropy was associated with worse outcome. Several reports suggest that this parameter reflects the aggressiveness of the disease as associated to a rapid growth and invasiveness (27,30,52).…”

“…In recent years, numerous studies have examined the potential clinical utility of radiomics features calculated from computed tomography (CT) images of NSCLC, correlated with tumor histology (24)(25)(26), staging (27), patient prognosis (19,(28)(29)(30) and genetic mutations (31)(32)(33).…”

Radiologist Engagement as a Potential Barrier to the Clinical Translation of Quantitative Imaging for the Assessment of Tumor Heterogeneity

“…The quantitative imaging method for assessing tumor heterogeneity adopted in this study was CT texture analysis (CTTA) which has been shown to be related to risk of mediastinal metastasis and overall prognosis for patients with Non-Small Cell Lung Cancer (NSCLC). The reasons for this selection were: a) the high incidence of NSCLC, b) the established role of CT in the clinical management of patients with this tumour, including routine presentation of imaging findings at the MDT meeting, c) the ability to extract heterogeneity information from images currently acquired in routine clinical practice, thereby avoiding the need for additional imaging procedures, and d) increasing research evidence for the prognostic value of CTTA in this patient population [6][7][8][9][10][11]. CTTA parameters were derived using TexRAD software (Feedback, Cambridge, UK) which implements the filtration-histogram method [15].…”

“…For lesions known to be malignant, imaging measures of heterogeneity can potentially provide correlates for biological features such as gene mutations when tissue-based assays are contra-indicated or have failed [4][5][6][7]. Heterogeneity measures may also be useful in providing an indicate of tumor aggression as illustrated by the association of heterogeneity within CT images of primary lung cancers with the likelihood of mediastinal metastases [8] and overall prognosis [6,7,[9][10][11]. Heterogeneity imaging can also potentially provide an indication of likely response to treatment.…”