• Shunichi Sato, Mutsuo Yamazaki, Daizoh Saitoh, Hitoshi Tsuda, Yoshiaki Okada, Minoru Obara, and Hiroshi Ashida.
• Division of Biomedical Information Sciences, National Defense Medical College Research Institute, National Defense Medical College, Tokorozawa, Japan. shunsato@ndmc.ac.jp
• J Trauma. 2005 Dec 1; 59 (6): 1450-5; discussion 1455-6.

BackgroundAccurate burn depth assessment is important for determining the appropriate treatment plan for severe burn patients. However, conventional methods of diagnoses, such as visual observation and pinprick test, are often inaccurate. We previously proposed a new method for burn diagnosis in which photoacoustic signals originating from the blood in healthy tissue under the injured tissue are measured. In this study, we investigated the validity of this method by an experiment using rat scald burn models.MethodsSuperficial dermal burns (SDBs), deep dermal burns (DDBs), and deep burns (DBs) were made in the dorsal skin of rats by using a Walker-Mason template. Wounds were irradiated with low-energy, 550-nm, nanosecond pulsed light, and photoacoustic signals induced were measured with a piezoelectric film as a function of postburn time. Measurement in normal skin as a control was also performed. Temporal profiles of the photoacoustic signals were converted into depth profiles using sound velocity of tissue, and for each profile, a peak showing highest signal intensity was selected. For this peak, the depth at which the signal rose (signal rise depth) and the depth that gave a peak value (signal peak depth) were recorded. Statistical analysis was performed to clarify the difference in depth information of signals between burn groups.ResultsDepth profiles of photoacoustic signals showed unique features depending on the degree of burn; pronounced peaks shifted to deeper tissue as the burn severity increased. This indicates that the zone of stasis formed due to injuries can be monitored. There were significant differences in both the signal rise depth and the peak depth between the control and SDB groups, SDB and DDB groups, and DDB and DB groups (p < 0.001).ConclusionSDBs, DDBs, and DBs can be differentiated by photoacoustic signals, suggesting that the method proposed is useful for diagnosing burn injuries.

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