Y Kagaya1, N Ohura2, H Suga2, H Eto2, A Takushima2, K Harii2. 1. Department of Plastic and Reconstructive Surgery, Kyorin University School of Medicine, Japan. Electronic address: mkagayakson@yahoo.co.jp. 2. Department of Plastic and Reconstructive Surgery, Kyorin University School of Medicine, Japan.
Abstract
OBJECTIVES: The "tissue oxygen saturation (StO2) foot-mapping" method was developed using a non-invasive near-infrared tissue oximeter monitor to classify the foot regions as ischemic and non-ischemic areas. The purpose of this study was to evaluate StO2 foot-mapping as a reliable method to detect ischemic areas in the feet of patients with critical limb ischemia (CLI), and to compare the results with assessments from the angiosome model. METHODS: The foot areas of 20 CLI patients and 20 healthy controls were classified into four regions: (1) 0 ≤ StO2 < 30%, (2) 30 ≤ StO2 < 50%, (3) 50 ≤ StO2 < 70%, and (4) 70 ≤ StO2 ≤ 100% to perform StO2 foot-mapping. Each area occupancy rate was compared between the two groups, and the threshold StO2 value for detecting ischemia was set. Next, the locations of ulcers (in 16 patients) were compared to the predicted ischemic regions by the StO2 foot-mapping and by the angiosome model and angiography. RESULTS: In regions (1) and (2) (StO2 < 50%), the area occupancy rate was significantly higher in the CLI group and almost zero in the control group, so that the threshold StO2 value for detecting ischemia was set at 50%. The locations of ulcers were compatible with StO2 foot-mapping in 87.5% of the cases (14/16), while they were compatible with the assessment from the angiosome model in 68.8% of the cases (11/16). CONCLUSIONS: This study suggests that StO2 foot-mapping can successfully and non-invasively detect ischemic areas in the peripheral tissue of the foot, and also more appropriately than the assessment provided by the angiosome model. StO2 foot-mapping can be used to evaluate the real angiosome: the real distribution of the peripheral tissue perfusion in the CLI patient's foot, which is determined by the peripheral microvascular blood flow, rather than the main arterial blood flow.
OBJECTIVES: The "tissue oxygen saturation (StO2) foot-mapping" method was developed using a non-invasive near-infrared tissue oximeter monitor to classify the foot regions as ischemic and non-ischemic areas. The purpose of this study was to evaluate StO2 foot-mapping as a reliable method to detect ischemic areas in the feet of patients with critical limb ischemia (CLI), and to compare the results with assessments from the angiosome model. METHODS: The foot areas of 20 CLI patients and 20 healthy controls were classified into four regions: (1) 0 ≤ StO2 < 30%, (2) 30 ≤ StO2 < 50%, (3) 50 ≤ StO2 < 70%, and (4) 70 ≤ StO2 ≤ 100% to perform StO2 foot-mapping. Each area occupancy rate was compared between the two groups, and the threshold StO2 value for detecting ischemia was set. Next, the locations of ulcers (in 16 patients) were compared to the predicted ischemic regions by the StO2 foot-mapping and by the angiosome model and angiography. RESULTS: In regions (1) and (2) (StO2 < 50%), the area occupancy rate was significantly higher in the CLI group and almost zero in the control group, so that the threshold StO2 value for detecting ischemia was set at 50%. The locations of ulcers were compatible with StO2 foot-mapping in 87.5% of the cases (14/16), while they were compatible with the assessment from the angiosome model in 68.8% of the cases (11/16). CONCLUSIONS: This study suggests that StO2 foot-mapping can successfully and non-invasively detect ischemic areas in the peripheral tissue of the foot, and also more appropriately than the assessment provided by the angiosome model. StO2 foot-mapping can be used to evaluate the real angiosome: the real distribution of the peripheral tissue perfusion in the CLI patient's foot, which is determined by the peripheral microvascular blood flow, rather than the main arterial blood flow.
Authors: Jie Zheng; David Muccigrosso; Xiaodong Zhang; Hongyu An; Andrew R Coggan; Bashir Adil; Charles F Hildebolt; Chandu Vemuri; Patrick Geraghty; Mary K Hastings; Michael J Mueller Journal: J Magn Reson Imaging Date: 2016-03-10 Impact factor: 4.813
Authors: Masoud Edalati; Mary K Hastings; David Muccigrosso; Christopher J Sorensen; Charles Hildebolt; Mohamed A Zayed; Michael J Mueller; Jie Zheng Journal: J Magn Reson Imaging Date: 2018-11-16 Impact factor: 4.813