Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-aided detection (CAD) systems are not routinely used by radiologists for pulmonary nodule detection in clinical practice despite their potential benefits. Maximum intensity projection (MIP) images improve the detection of pulmonary nodules in radiological evaluation with computed tomography (CT) scans. Inspired by the clinical methodology of radiologists, we aim to explore the feasibility of applying MIP images to improve the effectiveness of automatic lung nodule detection using convolutional neural networks (CNNs). We propose a CNN-based approach that takes MIP images of different slab thicknesses (5 mm, 10 mm, 15 mm) and 1 mm axial section slices as input. Such an approach augments the two-dimensional (2-D) CT slice images with more representative spatial information that helps discriminate nodules from vessels through their morphologies. Our proposed method achieves sensitivity of 92.7% with 1 false positive per scan and sensitivity of 94.2% with 2 false positives per scan for lung nodule detection on 888 scans in the LIDC-IDRI dataset. The use of thick MIP images helps the detection of small pulmonary nodules (3 mm-10 mm) and results in fewer false positives. Experimental results show that utilizing MIP images can increase the sensitivity and lower the number of false positives, which demonstrates the effectiveness and significance of the proposed MIP-based CNNs framework for automatic pulmonary nodule detection in CT scans. The proposed method also shows the potential that CNNs could gain benefits for nodule detection by combining the clinical procedure.
The overexpression of human telomerase reverse transcriptase (hTERT) has been associated with the proliferation and migration of colorectal cancer (CRC) cells. We investigated the roles of KRT23 and hTERT in promoting CRC cell proliferation and migration. We verified the relationship between KRT23 and hTERT in CRC using streptavidin-agarose pulldown and chromatin immunoprecipitation (ChIP) assays. One hundred and fifty-four human CRC specimens were analyzed using immunohistochemistry. The roles of KRT23 and hTERT in cell growth and migration were studied using siRNA and lentiviruses in vivo and in vitro. Western blot and wound scratch analyses were used to determine the signaling pathway for KRT23-mediated activation of CRC growth and migration. Telomerase activity was measured by using the TeloTAGGG Telomerase PCR ELISA PLUS Kit. We identified KRT23 as a new hTERT promoter-binding protein. Patients with high KRT23 and hTERT expression had markedly shorter overall survival. Overexpression of KRT23 upregulated the expression of hTERT protein, hTERT promoter-driven luciferase and telomerase activity in CRC. Conversely, inhibition of KRT23 by a KRT23-specific siRNA repressed the endogenous hTERT protein, the expression of hTERT promoter-driven luciferase and telomerase activity. Overexpression of KRT23 also promoted CRC proliferation and migration. By contrast, KRT23 inhibition significantly inhibited tumor cell growth in vitro and in vivo. KRT23 promoted cancer stem cell properties and increased the expression of CD133 and CD44. These results demonstrate that KRT23 is an important cellular factor that promotes CRC growth by activating hTERT expression and that KRT23 is a potential novel therapeutic target for CRC.
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