NSCLC tumor shrinkage prediction using quantitative image features
Highlights • Lung tumors shrink during radiotherapy, with much variation between patients. • Pre-treatment CT images can be used to predict tumor shrinkage after treatment. • Potential uses include identifying patients who will benefit from adaptive radiation therapy.
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| Veröffentlicht in: | Computerized medical imaging and graphics 2016-04, Vol.49, p.29-36 |
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| container_title | Computerized medical imaging and graphics |
| container_volume | 49 |
| creator | Hunter, Luke A Chen, Yi Pei Zhang, Lifei Matney, Jason E Choi, Haesun Kry, Stephen F Martel, Mary K Stingo, Francesco Liao, Zhongxing Gomez, Daniel Yang, Jinzhong Court, Laurence E |
| description | Highlights • Lung tumors shrink during radiotherapy, with much variation between patients. • Pre-treatment CT images can be used to predict tumor shrinkage after treatment. • Potential uses include identifying patients who will benefit from adaptive radiation therapy. |
| doi_str_mv | 10.1016/j.compmedimag.2015.11.004 |
| format | Article |
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| language | eng |
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| subjects | Algorithms Carcinoma, Non-Small-Cell Lung - diagnostic imaging Carcinoma, Non-Small-Cell Lung - radiotherapy Feature extraction Humans Internal Medicine Lung Neoplasms - diagnostic imaging Lung Neoplasms - radiotherapy Mathematical models Medical services NSCLC Other Patients Pattern Recognition, Automated - methods prediction Pretreatment Prognosis Quantitative image feature Radiographic Image Interpretation, Computer-Assisted - methods Radiotherapy, Image-Guided - methods Reproducibility of Results Sensitivity and Specificity Shrinkage Subtraction Technique texture Tomography, X-Ray Computed - methods Treatment Outcome Tumor Burden tumor shrinkage Tumors |
| title | NSCLC tumor shrinkage prediction using quantitative image features |
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