Lung cancer histologic types distribution infographic presenting major histologies and their relative frequencies. The chart is a non-imaging visualization with labeled segments. It shows adenocarcinoma as the most common histology (~38%), followed by squamous cell carcinoma (~20%), small cell carcinoma (~14%), large cell carcinoma (~3%), and other types (~25%). This representation highlights epidemiology: adenocarcinoma is more frequent in women and never-smokers and tends to arise in peripheral airways, whereas squamous and small cell carcinomas originate in proximal airways and show strong smoking associations. Mixed histologies occur in about 10% of cases (e.g., adenocarcinoma with squamous cell). In never-smokers, adenocarcinoma frequently harbors EGFR mutations, while KRAS mutations are more linked to smoking history; TP53 mutations are more common in smoking-related cancers. Clinical relevance includes informing diagnostic workups, guiding biopsy targeting, and shaping research into histology-specific biology and molecular profiles. This image serves educational, epidemiologic, and research contexts in pathology, oncology, pulmonology, and medical education, and supports discussions about tumor heterogeneity, histology-driven therapy implications, and population-based cancer statistics.

This diagnostic imaging set presents axial thoracic CT scans illustrating three types of lung cancer: Small Cell Lung Cancer (SCLC), Adenocarcinoma, and Squamous Cell Carcinoma. The content is organized into three comparative rows: 'Original' scans, 'Gold Standard' manual segmentations, and automated segmentation results ('Our method'). The SCLC image displays an irregular, large area of increased density in the upper right lung field, consistent with a consolidated mass. The adenocarcinoma scan reveals a more localized, peripheral rounded nodule in the left lung parenchyma. The squamous cell carcinoma scan shows a central lesion with significant soft tissue density near the mediastinum. The 'Gold Standard' row utilizes a red dotted contour to delineate the lung parenchyma boundaries, including the identified pathological regions. This comparison highlights the capability of deep learning algorithms in Lung Parenchyma Segmentation (LPS), specifically the extraction of texture features and nodule morphology for differential diagnosis between SCLC and Non-Small Cell Lung Cancer (NSCLC) subtypes in clinical oncology.

Digital whole-slide histopathology image of a peripherally located lung squamous cell carcinoma captured on a hematoxylin and eosin stained section. The specimen represents peripheral parenchyma with a bronchogenic carcinoma infiltrating the lung periphery. On low- and high-power inspection, nests and irregular clusters of polygonal tumor cells extend from the capsule into adjacent stroma. Tumor cells exhibit eosinophilic cytoplasm, distinct cell borders, and prominent nuclei with coarse chromatin; intercellular bridges may be visible, and occasional keratinization features can be present in well-differentiated foci. The surrounding lung parenchyma shows desmoplastic stromal response and inflammatory infiltrate. The lesion demonstrates peripheral localization, an infiltrative growth pattern, and disruption of normal alveolar architecture. The image supports a histopathologic diagnosis of squamous cell carcinoma due to squamous differentiation, keratinization in places, and intercellular keratin bridges; such morphology is typical in smokers with bronchogenic carcinoma. Clinically, this histology correlates with a smoking history and indicates a solid, non-small cell lung cancer variant with squamous lineage. This image would be valuable for educational purposes, pathology review, differential diagnosis with adenocarcinoma or large cell carcinoma, and in teaching about tumor-stroma interactions in peripheral lung cancers. Correlation with clinical history enhances interpretive accuracy and guides multidisciplinary care in treatment planning.

This composite educational graphic illustrates the differential response of lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) to anti-VEGFR therapies (Sunitinib and DC101) using preclinical mouse models. The data is presented in four panels (A-D). Panels A and B focus on ADC, featuring waterfall plots and line graphs of tumor diameter change. Representative transverse respiratory-gated micro-CT images of the thoracic cavity show ADC lesions (white arrows and high-magnification insets) at pre-treatment and post-treatment stages. In the control group, micro-CT shows visible lesion enlargement, while the Sunitinib-treated group exhibits stabilization of lesion size, corroborated by the flat line plot and waterfall bars below the 20% progression threshold. Panels C and D focus on SCC. Waterfall plots and line graphs depict tumor area change. Micro-CT images demonstrate diffuse tumor masses (outlined by dotted lines). In both control and Sunitinib-treated SCC groups, post-treatment images show significant expansion of the tumor-occupied area, indicating primary resistance to anti-VEGFR2 treatment. This highlights the clinical concept of histology-dependent therapy response in non-small cell lung cancer subtypes.

This histopathology slide depicts lung tumor tissue examined by light microscopy following hematoxylin and eosin staining. The specimen is derived from pulmonary parenchyma in a region containing tumor cells. The architecture shows a hybrid neoplasm composed of mucin-producing cells arranged in gland-like clusters and adenomatoid glands intermingled with nests of squamous cells, characterized by dense eosinophilic cytoplasm and rounded to polygonal nuclei. Mucinous cells exhibit bluish cytoplasm and intracytoplasmic mucin; squamous cells display keratinization features and abundant eosinophilic cytoplasm; together they confirm a combined histology with two distinct subtypes. The background stroma contains desmoplastic reaction and inflammatory infiltrate in places. This pattern is typical of adenosquamous carcinoma of the lung, observed in roughly 10% of lung cancers, where prognosis and therapeutic decisions hinge on the more aggressive component. Clinically, such tumors portend a poorer prognosis than pure adenocarcinoma or pure squamous cell carcinoma and may influence choices between surgical resection and systemic therapy. Immunophenotypic profiling (TTF-1 and Napsin A positivity for glandular components; p40/p63 positivity for squamous components) can assist subtyping. Recognize that combined histology carries implications for staging, prognosis, and potential targeted regimens; differential considerations include pure adenocarcinoma with mucin production, pure squamous cell carcinoma, or small cell variants.

Multi-modal chest imaging comparison of two primary lung cancer types: Adenocarcinoma (Case 1) and Squamous Cell Carcinoma (Case 2). The 4x2 grid displays axial sections across four modalities: (a) Computed Tomography (CT), (b) Diffusion-Weighted Imaging (DWI), (c) Apparent Diffusion Coefficient (ADC) maps, and (d) T2-Weighted Imaging (T2WI). In Case 1, the adenocarcinoma presents as a focal nodule in the right lung field with hyperintensity on DWI and corresponding hypointensity on the ADC map (1.39 x 10^-3 mm^2/s), indicating restricted diffusion. In Case 2, the squamous cell carcinoma is located in the left posterior lung periphery, demonstrating stronger signal suppression on the ADC map (1.04 x 10^-3 mm^2/s) compared to Case 1. T2WI reveals heterogeneous internal architecture for the adenocarcinoma and a more homogeneous appearance for the squamous cell carcinoma. This comparative imaging set illustrates the diagnostic utility of combining structural (CT) and functional (DWI/ADC) MRI sequences to characterize pulmonary nodules and differentiate histological subtypes based on diffusion restriction and T2 contrast ratios.