Important Parameters of NIR-II Imaging in the Early Diagnosis of Lower Extremity Peripheral Artery Disease

Overview

Lower extremity peripheral artery disease (PAD) is a growing global health problem. New ways have been explored to diagnose PAD in recent years, such as the second near-infrared region (NIR-II, 900-1,880 nm wavelengths) imaging. In this study, NIR-II imaging was performed on patients with type 2 diabetes without PAD, and time-intensity curves were generated according to the imaging results, and specific parameters on the curves were analyzed. The key parameters for the diagnosis of lower limb artery plaque were obtained by comparing the parameters of patients with and without plaque. Patients will be followed up six months and one year after the first NIR-II imaging. The patient will undergo Duplex ultrasound (DUS), NIR-II imaging and laboratory examination. With DUS results as the reference standard, patients diagnosed with PAD for the first time during follow-up were focused on, and the parameter range of the first NIR-II imaging was statistically analyzed, so as to obtain the diagnostic threshold for early diagnosis of PAD.

1. The registry procedures and quality assurance: the study recruited patients diagnosed with type 2 diabetes from the Department of Endocrinology at the Second Hospital of Shanxi Medical University. If the patient meets the inclusion criteria and agrees to be enrolled, a written informed consent will be signed. The imaging process is completed by a uniform standard, and all imaging operations are performed by the same operator. The operator has been formally trained and the procedure and results are checked by another professional NIR imaging engineer. 2. Imaging process: The imaging device used was Full Spectrum Opening in Vivo Fluorescence Imaging System (DPM-IVFM-NIR-OF, Beijing Digital Precision Medicine Technology Co., Ltd., China). Firstly, participants were asked if they had a history of indocyanine green (ICG) or iodine allergy. If there was no relevant allergy history, an ICG skin test was performed on each participant. The skin test reagent was the ICG solution (Dandong Yichuang Pharmaceutical, China) with a concentration of 0.005mg/mL (diluted with sterile water for injection) . The test reagent (0.1 ml) was injected subcutaneously into the inner forearm and the subject was observed for 20 min. If there was no allergic reaction, an indent needle was placed in the basilic vein of patients. The NIR imaging was conducted in a room without natural light. Before the examination, the subject rested for at least 15 min in a supine position with both knee joints bent 90 degrees and both feet put together, and then step horizontally on the black background board on the examination bed. In NIR-II imaging, the selected filter was 1000 nm long-pass. The power of the 808nm wavelength laser emitter was adjusted to 10000mW with the aperture size adjusted to 2.0 and the exposure time set to 100 ms. The laser emitter was fixed at 20cm vertical to the dorsal foot, and the NIR-II camera was fixed at 40cm vertical to the dorsal foot. ICG solution (2.5 mg/mL, diluted with sterile water for injection) was administered intravenously via an indignant needle. The dose of ICG injected was determined according to body weight: 0.1mg/Kg. The time for intravenous injection of ICG solution was 5 seconds. The intensity of fluorescence signal on both the dorsal feet was recorded within 5 minutes after ICG solution was injected. The dorsal pedis region from the transverse tarsus joint to the distal metatarsal bone was selected as the region of interest (ROI). The ROI was analyzed using the built-in analysis software External Data processing to generate a time-intensity curve. 3. Plan for missing data: missing data will be excluded from analysis. 4. Methods to summarize the data: NIR-II parameters extracted from time-intensity curves for all patients were recorded in the same excell table. In addition, baseline information (such as age, gender, height, weight, etc.) and clinical characteristics (such as years of diabetes, hypertension, hyperlipidemia, etc.) of all patients were recorded in this table. 5. Statistical analysis: In this study, SPSS 26.0 software and R 4.2.0 software were used to conduct in-depth statistical research. When processing measurement data, the Kolmogorov-Smirnov test was first used to verify whether the data followed the normal distribution. Data with a normal distribution was represented by x±s, while data with a skewed distribution was represented by M (Q1, Q3). For comparison between groups, the independent sample test or the Mann-Whitney U test were selected. For classified data, χ2 test or Fisher exact probability method was chosen for further investigation. A significance level of P \< 0.05 means that the difference was statistically significant.