Details

Autor(en) / Beteiligte

• Hermans, B.C.M.
• Sanduleanu, S.
• Derks, J.L.
• Woodruff, H.
• Hillen, L.M.
• Casale, R.
• Hoesein, F. Mohamed
• de Jong, E.
• Berge, D.M.H.J. ten
• Speel, E.J.M.
• Lambin, P.
• Gietema, H.A.
• Dingemans, A-M.C.

Titel

Exploring imaging features of molecular subtypes of large cell neuroendocrine carcinoma (LCNEC)

Ist Teil von

• Lung cancer (Amsterdam, Netherlands), 2020-10, Vol.148, p.94-99

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2020

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• •LCNEC has radiological characteristics of both SCLC and NSCLC.•LCNEC can be classified in molecular SCLC-like and NSCLC-like subtypes.•Molecular LCNEC subtypes could not be identified based on radiological imaging.•Most LCNEC are molecular SCLC-like, but have a radiological NSCLC-like appearance.•These results highlight LCNEC as a unique tumor entity. Radiological characteristics and radiomics signatures can aid in differentiation between small cell lung carcinoma (SCLC) and non-small cell lung carcinoma (NSCLC). We investigated whether molecular subtypes of large cell neuroendocrine carcinoma (LCNEC), i.e. SCLC-like (with pRb loss) vs. NSCLC-like (with pRb expression), can be distinguished by imaging based on (1) imaging interpretation, (2) semantic features, and/or (3) a radiomics signature, designed to differentiate between SCLC and NSCLC. Pulmonary oncologists and chest radiologists assessed chest CT-scans of 44 LCNEC patients for ‘small cell-like’ or ‘non-small cell-like’ appearance. The radiologists also scored semantic features of 50 LCNEC scans. Finally, a radiomics signature was trained on a dataset containing 48 SCLC and 76 NSCLC scans and validated on an external set of 58 SCLC and 40 NSCLC scans. This signature was applied on scans of 28 SCLC-like and 8 NSCLC-like LCNEC patients. Pulmonary oncologists and radiologists were unable to differentiate between molecular subtypes of LCNEC and no significant differences in semantic features were found. The area under the receiver operating characteristics curve of the radiomics signature in the validation set (SCLC vs. NSCLC) was 0.84 (95% confidence interval (CI) 0.77-0.92) and 0.58 (95% CI 0.29-0.86) in the LCNEC dataset (SCLC-like vs. NSCLC-like). LCNEC appears to have radiological characteristics of both SCLC and NSCLC, irrespective of pRb loss, compatible with the SCLC-like subtype. Imaging interpretation, semantic features and our radiomics signature designed to differentiate between SCLC and NSCLC were unable to separate molecular LCNEC subtypes, which underscores that LCNEC is a unique disease.