CLINICAL STUDY IN ACCELERATED HYPERFRACTIONATED IRRADIATION IN THE TREATMENT OF LOCAL ADVANCED NON-SMALL CELL LUNG CANCER

Objective To evaluate the effect of accelerated hyperfractionated irradiation (AHFJ) and conventional fractionated irradiation (CFI) for local advanced non- small cell lung cancer (NSCLC). Methods The patients of AI-IFJ group were irradiated to large-field target volume by a daily fraction of 2Gy, and small-field target volume by a daily fraction of 1Gy with more than 6h interval. The total dose of large-field target volume was SOGy/25Fx/SW and of small-field target volume was 7SGy/SOFx/5W. The patients in CFI group were irradiated by a daily fraction of 2Gy to the total dose of 66Gy/33Fx/6. 6W. After 3 months of radiotherapy, the tumor response rates of complete recovery (CR), partial recovery (PR), and no change (NC) and 1- and 2- year survival rate in the two groups were observed. Results The tumor response rates of CR,PR,NC in AHFI group and CFI group were 22.9%(8/35), 60.0%(21/35), 17.1%(6/35) and 11.4% (4/35), 51.4% (18/35), 37.2% (13/35) respectively (P>0. 05). All patients were followed up 2 years or more. The 1- and 2- year survival rates in AHFI group and CFI group were 62.9% (22/35), 31 .4% (11/35) and 42.9% (15/35) , 17.1% (6/35) respectively (P< 0.05). The incidences of esophagitis and pneumonitis in AHFI group and CFI group were 34.3% (12/35), 22. 9% (8/35) and 40.0% (14/35), 17.1% (6/35)(P>0. 05). Conclusion In comparison with CFI, AHFI may increase 1- and 2- year sur-vival rate after treatment of local advanced non-small cell lung cancer, while the radio-reactions, either early or late, did not increase significantly.

Using wavelet multi-resolution nature to accelerate the identification of fractional order system

Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method.