Technology in cancer research & treatment
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Technol. Cancer Res. Treat. · Jan 2018
ReviewRadiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer.
Routine follow-up visits and radiographic imaging are required for outcome evaluation and tumor recurrence monitoring. Yet more personalized surveillance is required in order to sufficiently address the nature of heterogeneity in nonsmall cell lung cancer and possible recurrences upon completion of treatment. Radiomics, an emerging noninvasive technology using medical imaging analysis and data mining methodology, has been adopted to the area of cancer diagnostics in recent years. ⋯ This review summarized the application of radiomics in response assessments in radiotherapy and chemotherapy for non-small cell lung cancer, including image acquisition/reconstruction, region of interest definition/segmentation, feature extraction, and feature selection and classification. The literature search for references of this article includes PubMed peer-reviewed publications over the last 10 years on the topics of radiomics, textural features, radiotherapy, chemotherapy, lung cancer, and response assessment. Summary tables of radiomics in response assessment and treatment outcome prediction in radiation oncology have been developed based on the comprehensive review of the literature.
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Technol. Cancer Res. Treat. · Jan 2018
Accelerated Hypofractionated Radiotherapy Versus Stereotactic Body Radiotherapy for the Treatment of Stage I Nonsmall Cell Lung Cancer-A Single Institution Experience With Long-Term Follow-Up.
Although stereotactic body radiation therapy is one of the standard treatments for stage I nonsmall cell lung cancer, in the case of central tumors it carries the risk of severe adverse events for serial organs. Accelerated hypofractionated radiotherapy is considered a reasonable alternative to treat central tumors. We have been treating central tumors with accelerated hypofractionated radiotherapy using a 75 Gy/25 fr/5 weeks regimen, and we compared the results with those of stereotactic body radiation therapy using 48 Gy/4 fr/1 week. ⋯ Accelerated hypofractionated radiotherapy with a 75 Gy/25 fr/5 weeks regimen is promising in that it can obtain similar local control and survival results to stereotactic body radiation therapy, and it can control both central and peripheral tumors without any serial organ toxicities. Based on these results, prospective multicenter trials are worth conducting, especially for ultracentral tumors.
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Technol. Cancer Res. Treat. · Jan 2018
Nicotine Induces Progressive Properties of Lung Adenocarcinoma A549 Cells by Inhibiting Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Expression and Plasma Membrane Localization.
Lung cancer remains one of the most common cancer-related deaths worldwide. The cigarette smoking is a risk factor for lung cancer development. Interestingly, the cystic fibrosis transmembrane conductance regulator encoded by CFTR gene, an ATP-binding cassette transporter-class ion channel that conducts chloride and bicarbonate anions across membrane of epithelial cells, has recently been suggested to play a role in the development and progression of many types of cancer. ⋯ Remarkably, an overexpression of cystic fibrosis transmembrane conductance regulator significantly inhibited the progressive potency of A549 cells, including capacity of cell migration and invasion and clonogenicity, along with a decreased expression of cell proliferative markers Ki67, p63, and proliferating cell nuclear antigen, and cancer stem cell marker CD133, stem cell pluripotency-related transcription factors octamer-binding transcription factor ¾, and sex-determining region Y-box 2, regardless of the presence of nicotine. In contrast, opposite effects were observed in A549 cells that the cystic fibrosis transmembrane conductance regulator was knockdown by short hairpin RNA to cystic fibrosis transmembrane conductance regulator. This study thus suggests that cystic fibrosis transmembrane conductance regulator may play a tumor suppressor role in lung cancer cells, which may be a novel therapeutic target warranted for further investigation.
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Technol. Cancer Res. Treat. · Jan 2018
A Generalized Deep Learning-Based Diagnostic System for Early Diagnosis of Various Types of Pulmonary Nodules.
A novel framework for the classification of lung nodules using computed tomography scans is proposed in this article. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the following 2 groups of features: (1) appearance features modeled using the higher order Markov Gibbs random field model that has the ability to describe the spatial inhomogeneities inside the lung nodule and (2) geometric features that describe the shape geometry of the lung nodules. The novelty of this article is to accurately model the appearance of the detected lung nodules using a new developed seventh-order Markov Gibbs random field model that has the ability to model the existing spatial inhomogeneities for both small and large detected lung nodules, in addition to the integration with the extracted geometric features. ⋯ To evaluate the proposed framework, we used the publicly available data from the Lung Image Database Consortium. We used a total of 727 nodules that were collected from 467 patients. The proposed system demonstrates the promise to be a valuable tool for the detection of lung cancer evidenced by achieving a nodule classification accuracy of 91.20%.