Projects / Programmes
Quantitative image analysis of non-small cell lung cancer: estimation of biological potential and treatment planning based on DNA ploidy and nuclear texture features
Code |
Science |
Field |
Subfield |
3.04.00 |
Medical sciences |
Oncology |
|
Code |
Science |
Field |
B200 |
Biomedical sciences |
Cytology, oncology, cancerology |
B520 |
Biomedical sciences |
General pathology, pathological anatomy |
non-small cel lung cancer, image cytometry, DNA ploidy, nuclear texture features, prognosis
Researchers (10)
Organisations (2)
Abstract
Lung cancer is the most common cancer in men and causes most of cancer related deaths,. In women, lung cancer is the second most common cause of death from cancer. In spite of aggresive treatment, the long-term survival of lung cancer patients is less than 10%. At present, there are no efficient and reliable screening tests for the detection of early lung cancer. The possibilities to decrease mortality from lung cancer are limited to a more effective treatment, adapted to the individual patient. Additional objective prognostic factors are needed for a better treatment planning. Image cytometric DNA ploidy and nuclear texture features provide an objective analysis of cell nucleus and a more accurate biological potential of a tumor can be estimated.
In the proposed study, we are planning to analyze if DNA ploidy and nuclear texture features could be used for 1. objective evaluation of stage of the disease and tumor differentiation, 2. identification of patients in Stage I and II, who would need adjuvant chemotherapy after racdical resection of tumor to be cured, 3. to identify patients in Stage IIIA with resectable lung cancer with better prognosis, who would benefit from post-operative chemotherapy.
We expect that image cytometric analysis, including DNA ploidy and nuclear texture features, of non-small cell lung cancers will provide new information about biological potential of tumors, which would enable more rational treatment planning and consequently better survival.