High Time-domain FNIRS And Application On Pulmonary Disease

With the increase of factors such as air pollution,smoking,inhalation of dust and harmful gases,lung disease problems are becoming more and more serious.After the end of the COVID-19 pandemic,many people experienced lung damage,which has made the detection of lung diseases more urgent.Currently,non-invasive techniques such as CT,X-ray,and MRI are mainly used for screening lung diseases,but these methods are timeconsuming and costly,and are not suitable for most people.In recent years,the rapidly developing near-infrared spectroscopy technology has been widely applied in life sciences,among which f NIRS technology has shown promising applications.Therefore,Thesis proposes to apply high-temporal-resolution f NIRS technology to the study of lung disease.We use MCVM software for lung photon transmission simulation,and based on the simulation results,guide the design of TD-f NIRS system for the lungs,providing theoretical reference for the system.The aim is to provide a convenient and non-invasive optical detection method for lung disease detection through this research.In Thesis,we first analyze the current commonly used lung disease detection techniques,their principles,advantages,and disadvantages.Then we introduce in detail the basic principles of the f NIRS technology adopted in Thesis,and summarize its application history and current status.Next,based on the Monte Carlo principle,Thesis focuses on discussing the lung photon transmission.After introducing the history and basic idea of Monte Carlo,we elaborate on the principle of photon transmission,as well as the regularity of photon motion in simulation.Finally,a lung template and a pulmonary embolism model were established using Visible Chinese.We then analyzed the simulation results and optimized the source-detector distance for the lungs.The penetration depth of photons from the skin to the lungs was found to be 32 ～ 36 mm,with 6 ～ 8.4 mm occurring in the lungs.The distribution of the optical flux and the change in its intensity in the lungs indicated that photons could reach the lungs from the light source.The SSD values of the five lung lobes ranged from 0.0235%to 0.0368%,while the average photon absorption in the lungs was about 9%.The photon absorption of each lobe was different,reflecting the different photon migration paths of the five lobes.In addition,based on some parameters,we optimized the source-detector distance for the lungs and found that 2.7 ～ 2.9 cm is the optimal source-detector distance for the lungs,but the optimal distance for the upper lobe of the right lung is 3.3 ～ 3.5 cm.Subsequently,Thesis introduces the design and algorithm of the TD-f NIRS system,implements the construction of the system,and conducts a preliminary experiment to demonstrate the feasibility of non-invasive near-infrared detection of the lungs.We first provide the ideas behind the TD-f NIRS system design,including the light source,detector,data collection,and processing.Then we explain in detail the algorithm used by the system.Afterward,we specifically introduce the equipment used to build the system,focusing on the collection process and parameter settings.Three performance test experiments were conducted on the completed TD-f NIRS: drop ink experiment,depth experiment and cuff experiment,which verified its good performance.In order to verify the lung simulation results,we recruited 14 healthy volunteers to conduct preliminary f NIRS experiments on the lungs,which proved that non-invasive near-infrared detection of the lungs is feasible.Finally,we summarize the work of the entire paper,describe the innovative points of the paper,and propose research prospects for this topic,analyzing the areas for improvement and presenting preliminary solutions to these issues.