研究目的
To investigate the use of a green aiming beam for stone autofluorescence and reflection measurements to increase the safety of laser lithotripsy by preventing damage to soft tissue and medical devices.
研究成果
Autofluorescence induced by a green aiming beam can be exploited for stone detection in laser lithotripsy, and reflection measurements can provide additional information on fiber condition and position. Implementing these safety features can assist in avoiding tissue perforation and damage to medical devices.
研究不足
The study did not include cystine and uric acid stones due to their rarity and non‐interventional treatment preference, respectively. The method's effectiveness with severely damaged fibers and in non‐contact mode requires further investigation.
1:Experimental Design and Method Selection
An external fiber‐fiber‐coupling‐box was set up for pulsed holmium laser radiation containing a green diode laser module and optics and detectors for measuring the reflected light and fluorescence. Measurements were done via a lock‐in technique.
2:Sample Selection and Data Sources
More than 20 human calculi samples and porcine calix in vitro were used. Measurements were recorded with the fiber positioned on tissue, stone, or in/on medical equipment.
3:List of Experimental Equipment and Materials
Holmium laser (Auriga QI; StarMedTec), green diode laser module (Flexpoint FP‐D‐520‐5M‐C‐F/Flexpoint FP‐D‐520‐3M‐C‐F‐1MHz; BLAU Optoelektronik), lock‐in amplifiers (SR810 and SR830; Stanford Research Systems, eLockIn204/2; Anfatec Instruments), photodetectors (PDA36A‐EC; Thorlabs).
4:Experimental Procedures and Operational Workflow
The fiber was brought in contact with the specimen, and autofluorescence signals were recorded. Reflection and fluorescence signals were recorded with varying distances between fiber tip and sample and during ongoing lithotripsy procedures.
5:Data Analysis Methods
Lock‐in amplifier signals were analyzed, and data were digitized via a high‐speed analog‐to‐digital converter. Software was written for automatic data storage and analysis.
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