ABSTRACT
Lung cancer remains to have the highest morbidity and mortality rates in China among known malignant tumors. Novel drugs and regimens have been sought because of the limited efficiency of traditional chemotherapy and radiotherapy in lung cancer treatment. In the last 20 years, rapid developments in molecular targeted therapy and immunotherapy have increased clinical efficacy and benefitted patients with cancer. Treatments for lung cancer are the most rapidly developed among treatments for solid tumors, pioneering tumor precision medicine. This manuscript reviews the evolution and development of targeted therapy and immunotherapy and discusses existing problems and future directions in the precision therapy of lung cancer.
ABSTRACT
Magnetic resonance spectroscopy has many important applications in bio-engineering while acquiring high dimensional spectroscopy is usually time consuming. Non-uniformly sampling can speed up the data acquisition but the missing data points have to be restored with proper signal models. In this work, a specific two dimensional (2D) magnetic resonance signal, in which the first dimension lies in frequency domain while the second dimension lies in time domain, is reconstructed with a proposed low rank Hankel-matrix method. This method explores two general properties: 1) the rank of a structured matrix, converted from a 2D exponential signal, is equal to the number of 2D spectral peaks; 2) this rank is small if the spectrum is sparse. Results on real magnetic resonance spectroscopy show that proposed method outperforms the state-of-compressed sensing method on recovering low-intensity spectral peaks.
