Reply: Intraoperative Near-infrared Spectroscopy Can Predict Skin Flap Necrosis

Many thanks to the reviewers for their comments.1 Like most science, the devil is in the details, and we acknowledge that there may be differences in semantics. Nonetheless, the main findings from our study remain relevant in the utility of novel imaging modalities to assess tissue viability. The differentiation between near-infrared spectroscopy (NIRS) and near-infrared imaging is semantic in nature. The definition of spectroscopy is the measurement and interpretation of electromagnetic spectra. As SnapshotNIR is emitting and then measuring reflected near-infrared light spectra, it falls under this purview of spectroscopy. The depth of near-infrared light penetration is wavelength-dependent, or in some contact-based applications, dependent on the distance between the emitted signal to the sensor receiving the signal. As such, light penetration depth cannot be tied so specifically to imaging versus spectroscopy. Furthermore, the contact versus noncontact nature is not a defining feature of spectroscopy. Indeed, some of the earliest applications of NIRS came from the agriculture industry to assess properties of crops in a noncontact way.2 As such, although SnapshotNIR is a noncontinuous and noncontact assessment of tissue oxygenation, this does not make it any less of a spectroscopy device. We would argue that near-infrared imaging may be a subset of NIRS devices, and the 2 are not mutually exclusive. Many of the other peer-reviewed publications using the same technology have preferentially used the term NIRS.3–6 Additionally, there are reports using near-infrared imaging and NIRS interchangeably which calls into question what the critical distinction is between these 2 terms.7 We also appreciate the feedback regarding the distinction of measuring perfusion verses measuring oxygenation. The NIRS device used provides a direct measure of oxygenated hemoglobin. Although this is not a direct measure of perfusion, it is a very good surrogate measure of perfusion and metabolism, especially in the clinical cases presented in this study. Although oxygenation and perfusion are linked (through the Fick equation), they are different. Oxygen consumption (V̇O2) by tissue is directly tied to the tissue blood flow (Q̇tissue) and the arteriovenous difference in oxygen content, as demonstrated in the following formula: V˙O2tissue=Q˙tissue×(CaO2−CvO2) Assuming standard surgical conditions (normal respiratory function and minimal arterial-venous differences in partial pressure of oxygen and hemoglobin) a patient’s arterial saturation will be ~98%, causing measurements of tissue oxygen saturation (StO2) to be almost exclusively contingent on changes in venous blood volume and venous oxygen saturation. As such, this equation can be adapted to the following: V˙O2tissue=Q˙tissue×(98%−StO2)%Volv As SnapshotNIR provides us spatial resolution of both control tissue and tissue at risk within a single set of images, we can be relatively confident that metabolism is conserved in like tissue, and so, changes in StO2 are reflective of changes in blood flow. Importantly, we are not measuring StO2 on areas where we feel it likely that perfusion and oxygen consumption have been decoupled (diffusion limitation or mitochondrial dysfunction). Furthermore, SnapshotNIR provides relative intensities of total hemoglobin, which is a surrogate measure of how much blood volume is within a particular area (data not presented in our work). Although they are not true measures of perfusion, they are implicit markers of blood flow and are likely not affected in our particular application. DISCLOSURE The author has no financial interest to declare in relation to the content of this article.