title: Infrared thermal imaging as a novel evaluation method for deep vein thrombosis in lower limbs.
abstract: OBJECTIVE
  Early detection of deep vein thrombosis (DVT) is critical to prevent clinical pulmonary thromboembolism. However, most conventional methods for diagnosing DVT are functionally limited and complicated. The aim of this study was to evaluate the value of infrared-thermal-imaging (IRTI), a novel imaging detection or screening technique, in diagnosis of DVT in animal models.
  
  
  METHODS
  DVT model of femoral veins was established in nine New Zealand rabbits. The right hind femoral vein was embolized and the contralateral one served as a nonembolized control. Measurements of IRTI, compression ultrasonography (CPUS), and angiography under ultrasonic observation (AGUO) were performed at three time points: T1 (baseline, 10 min prior to surgery), T2 (2 h after thrombin injection), and T3 (48 h postoperatively). Qualitative pseudocolor analysis and quantitative temperature analysis were performed based on mean area temperature (Tav) and mean curvilinear temperature (Tca) of the region of interest as shown in IRTI. Temperature differences (TD) in Tav (TD(Tav)) and Tca (TD(Tca)) between the DVT and control sides were computed. Comparative statistical analysis was carried out by paired t-test and repeated measure, while multiple comparisons were performed by using Greenhouse-Geisser and Bonferroni approach. Values of P < 0.05 and P < 0.01 were considered statistically significant and highly significant.
  
  
  RESULTS
  Modeling of DVT was successful in all rabbits, as confirmed by CPUS and AGUO and immediately detected by IRTI. IRTI qualitative analysis of pseudocolor revealed that the bilateral temperatures were apparently asymmetrical and that there were abnormally high temperature zones on the DVT side where thrombosis formed. The results of paired t-test of Tav and Tca between DVT side and control sides did not reveal statistical difference at T1 (Tav: P = 0.817; Tca: P = 0.983) yet showed statistical differences at both T2 (Tav: P = 0.023; Tca: P = 0.021) and T3 (Tav: P = 0.016; Tca: P = 0.028). Results of repeated measure and multiple comparisons of TD(Tav) and TD(Tca) were highly different and significant differences across the T2 (TD(Tav): P = 0.009; TD(Tav): P = 0.03) and T3 (TD(Tav): P = 0.015; TD(Tav): P = 0.021).
  
  
  CONCLUSIONS
  IRTI temperature quantitative analysis may help further detection of DVT. Additionally, IRTI could serve as a novel detection and screening tool for DVT due to its convenience, rapid response, and high sensitivity.
authors.affiliation: The First Affiliated Hospital of Guangzhou Medical College, Guangzhou, China.
authors.forename: Fangge
authors.initials: F
authors.lastname: Deng
authors.forename: Qing
authors.initials: Q
authors.lastname: Tang
authors.forename: Yujiang
authors.initials: Y
authors.lastname: Zheng
authors.forename: Guangqiao
authors.initials: G
authors.lastname: Zeng
authors.forename: Nanshan
authors.initials: N
authors.lastname: Zhong
mesh_terms: D000465:Algorithms; D000818:Animals; D001831:Body Temperature; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007259:Infrared Rays; D011817:Rabbits; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013817:Thermography / Q000379:methods*; D020246:Venous Thrombosis / Q000175:diagnosis* / Q000503:physiopathology*