Multi-level analysis of spatio-temporal features in non-mass enhancing breast tumors
| Autor: | Diego P. Morales, Katja Pinker-Domenig, Marc B. I. Lobbes, Anke Meyer-Bäse, Encarnacin Castillo, Amirhessam Tahmassebi, Dat Tien Ngo, Antonio García |
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| Rok vydání: | 2018 |
| Předmět: |
Treatment response
Computer science Multi level analysis Kinetic information 020206 networking & telecommunications Enhancement pattern 02 engineering and technology Computational biology medicine.disease Breast cancer Computer-aided diagnosis Early prediction 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Cytotoxic Therapy |
| Zdroj: | Smart Biomedical and Physiological Sensor Technology XV. |
| DOI: | 10.1117/12.2304928 |
| Popis: | Diagnostically challenging breast tumors and Non-Mass-Enhancing (NME) lesions are often characterized by spatial and temporal heterogeneity, thus difficult to detect and classify. Differently from mass enhancing tumors they have an atypical temporal enhancement behavior that does not enable a straight-forward lesion classification into benign or malignant. The poorly defined margins do not support a concise shape description thus impacting morphological characterizations. A multi-level analysis strategy capturing the features of Non-Mass- Like-Enhancing (NMLEs) is shown to be superior to other methods relying only on morphological and kinetic information. In addition to this, the NMLE features such as NMLE distribution types and NMLE enhancement pattern, can be employed in radomics analysis to make robust models in the early prediction of the response to neo-adjuvant chemotherapy in breast cancer. Therefore, this could predict treatment response early in therapy to identify women who do not benefit from cytotoxic therapy. |
| Databáze: | OpenAIRE |
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