2.1.

Subject Eligibility, Inclusion, and Exclusion Criteria

Eligibility criteria for this study included male and female patients between 12 and 30 years underage undergoing elective arthroscopic knee surgery under general anesthesia at Boston Children’s Hospital. Exclusion criteria included inability to cooperate or understand the nature of the study, structural or genetic disorders that affect typical brain structure and function, significant medical disease, smoking history, inability to obtain reliable fNIRS measures in initial signal test, or inability to maintain head stillness for 200 continuous seconds. This protocol was approved by Boston Children’s Hospital’s institutional review board, and all participants and legal guardians assented/consented to participation in this study. This study conformed to the Declaration of Helsinki for experiments in patients related to pain.

2.2.

Subjects

Study personnel gathered data from 24 patients (ages 12 to 25 years) who underwent arthroscopic knee surgery under general anesthesia; however, five patients were excluded from analysis; one patient had unsaved data, one patient withdrew due to medical emergency, and three patients had incomplete pre- and/or postsurgical data. Table 1 provides demographic and clinical data for the 19 patients. Eleven patients (58%) received regional anesthesia prior to surgical incision (age $17.6\pm 3.59$, six females) received regional anesthesia (nerve block; NB), while eight patients (age $18.9\pm 2.80$, five females) did not (non-NB). This decision to perform a nerve block was made by the anesthesiology team, without any predetermined factors.

Table 1

Demographic and clinical data. Abbreviations: M, male; F, female; R, right knee; L, left knee; Y, nerve block placed; N, nerve block not placed; ACL, anterior cruciate ligament; IT, Iliotibial band; OCD, osteochondritis dissecans.

2.3.

Anesthetic Technique

All patients underwent general anesthesia according to routine practice. Anesthetic data for each patient are shown in Table S1 in the Supplementary Material. Drug dosages are presented here as median [range]. Briefly, all patients were premedicated with 2-mg midazolam IV and propofol (median 200 mg [150 to 300 mg]) used for induction of anesthesia in 18 patients (95%). In one patient (#13), the induction dose of propofol was not recorded. Fentanyl (median 100 g [100 to 250 mg]) was administered as part of the induction in all but one patient who was given sufentanil (#2). Anesthesia was maintained with an inhalational agent, predominantly sevoflurane, and supplemented with a propofol infusion in 12 patients (47%). The airway was managed with a laryngeal mask airway and spontaneous ventilation; neuromuscular blockade was not employed. For intraoperative analgesia, hydromorphone (median 0.6 mg [0.3 to 1.6 mg]) was the opioid of choice and acetaminophen (650 mg IV) was administered intraoperatively to all but one patient. Ketorolac (median 30 mg [18 to 30 mg]) and diazepam (median 2.5 mg [2.5 to 7.5 mg]) were each administered to approximately half the patients. The acetaminophen, ketorolac, and diazepam were generally given toward the end of the surgery. Antiemetic prophylaxis included ondansetron (4 mg) in all but one patient (#17), dexamethasone (median 4 [4 to 8] mg) in all but three patients (#s 1, 3, 16), and a scopolamine patch (1.5 mg) was applied in two patients (#s 6, 13).

An adductor canal peripheral nerve block with ropivacaine (0.2% or 0.35%) was performed under ultrasound guidance on the ipsilateral limb in 11 (58%) patients. Nerve block was administered based on the clinical team’s recommendation following standard clinical evaluation and the patient’s consent. Details for the regional anesthesia are presented in Table S1 in the Supplementary Material. A catheter for infusion of local anesthetic was placed in one patient (#17) but the infusion was only started 6 h postoperatively. In one patient, a lateral femoral cutaneous nerve block was added to the adductor canal block. Dexmedetomidine and clonidine were added to the ropivacaine in one (#7) and two (#s 5, 9) patients, respectively.

Local anesthetic (0.25% bupivacaine with 1:200,000 epinephrine) was injected by the surgeon in 16 patients (84%), either immediately prior to incision ($n=9$) or at the end of surgery ($n=7$). Of the 11 patients that received a peripheral nerve block, local anesthetic was injected by the surgeon in 10 cases either with incision ($n=8$) or at the end of surgery ($n=2$). For patients that did not receive a nerve block ($n=8$), local anesthetic was injected by the surgeon at the end of the procedure in six patients.

2.4.

Surgical Procedure

Surgical procedures were performed according to standard practice and are shown in Table 1.^56,57 Each subject laid flat in the supine position for the entire duration of the study. Surgical technique involved skin incision and dissection of cutaneous tissue to create portals for insertion of arthroscopes and related instruments, shaving of torn ligamentous tissue, cutting of hamstring, iliotibial band, and/or patellar bone for autografts, drilling, and suturing of surgical incisions. We chose to define “skin incisions” as the painful events, i.e., P1 and P2. As with any surgical procedure (injections, scraping, nerve block applications), other processes may be painful. Notwithstanding this decision, we believe that fNIRS will be able to detect any painful procedure. A verbal rating scale (VRS) was used to evaluate pain intensity (0 being no pain; 10 being the worst pain imaginable) in each patient just prior to surgery, shortly after arrival in the post-anesthesia care unit (PACU) and just prior to discharge from the PACU.

2.5.

Data (fNIRS) Acquisition

Data were collected using a multichannel fNIRS system at 690 and 830 nm wavelengths and 25 Hz sampling frequency (TechEn Inc., Milford, Massachusetts, CW7 System). The changes in hemoglobin concentration of oxygenated (${\mathrm{HbO}}_2$), deoxygenated (HbR), and total hemoglobin (HbT) within the cortical areas were measured based on the modified Beer–Lambert law. We have previously described techniques of using fNIRS for measuring of pain/nociception under anesthesia.²² A similar approach was taken here. A custom probe with nine sources and 14 long-separation detectors (placed $\sim 3\mathrm{cm}$ from the source) and nine short-separation detectors (placed 0.8 cm from the source)⁵⁸ were used (see Fig. 1). This probe was designed using an EEG cap with a 10–20 layout to include 24 channels covering the bilateral PreFC and the bilateral somatosensory cortices [see Fig. 2(b)]. We specifically evaluated six brain ROIs: the PreFC consisting of three ROIs: (1) the medial polar frontal cortex (mPFC), (2) lateral polar-frontal cortex (lPFC), (3) lateral pre-frontal cortex (lateral Pre-FC) and the bilateral somatosensory cortex (S1) also made up of three ROIs: (4) superior S1, (5) medial S1, and (6) inferior S1.

Fig. 1

fNIRS node map. The nine sources marked in yellow are detected by the 14 regular detectors in purple and the nine short-source detectors in blue. Black arrows represent the 3 cm between the sources and the long-separation detectors while the red arrows show the 0.8 cm between the sources and the short-separation detectors. The 24 connections between the sources and the detectors are the channels that feedback the concentrations of oxygenated (${\mathrm{HbO}}_2$), deoxygenated (HbR), and total (HbT) hemoglobin to the end user. The front 12 PreFC channels are separated into the lateral (silver), pre-lateral (blue), and medial (yellow) groups while the back 12 somatosensory cortex (S1) is split into the superior (red), central (orange), and inferior (green) S1 groups.

Fig. 2

fNIRS timeline. Each patient has one of their knees operated on [as shown in (a)⁵⁹]. Using the fNIRS cap in (b), concentration readings are obtained from the 24 nodes attached to the head. These nodes observe four concentrations in the six ROIs shown in (c) (a, superior S1; b, central S1; c, inferior S1; d, lateral frontal cortex; e, lateral polar frontal cortex; f, mPFC). As the opposite cortex is observed and since the right knee is operated on, we look at the 12 channels in the left cortex (7 to 12 in the frontal PreFC and 19 to 24 in the rear in Fig. 1). ${\mathrm{HbO}}_2$ and HbR are recorded for 25-min after surgery starts [see (d) for the average oxyhemoglobin of the six relevant filtered channels for PreFC and S1, with the standard error represented each side of the error bars]. An incision was performed at the start of the section of time marked in black and continued through the black bar’s duration. A sliding window of 10 s in 1 s increments was then calculated for the minute after the incision. This period of time is then examined for trends in the patient (no nerve block was administered to this patient). When all the patient data have been collected, the average oxygenated hemoglobin of the patients who did receive nerve block and those who did not were calculated and plotted along with a running error bar over time as shown in (e).

Prior to entering the operating room, the probe-containing cap was securely placed on patients’ heads. The optodes were secured using custom designed washers to maintain contact (see Fig. S1 in the Supplementary Material). A smaller EEG cap with the same probe layout was used for pediatric patients as needed. Data quality and optode positions were confirmed with a 10-min baseline scan in the preoperative setting. There were two steps of quality control, one during data acquisition and one during postprocessing. After setup and before the beginning of the scan, the channels were visually inspected. Good contact between the scalp and the optode was confirmed by (1) acceptable power intensity (as indicated by CW7 software) and (2) a visible heart rate in all the channels, including short-separation channels. After which, the fNIRS data were continuously collected, beginning at anesthetic induction, and concluding following final suturing at the end of surgery. During this period, one research personnel was responsible for monitoring fNIRS data acquisition quality, while another was responsible for noting the time and type of surgical procedures; for instance, the initial incision was noted as “incision,” arthroscopic scraping was noted as “scraping,”and so on. A summary of fNIRS signal acquisition and data analysis for a single patient is shown in Fig. 2.

2.6.

Preprocessing

Raw signals and their power spectrum were visually inspected using Homer2 toolbox. If at least two out of the four channels within a cortical region (lateral PreFC, medial PreFC, and somatosensory cortex) exhibited a visible heart rate component in the raw time series and a discernible peak at the cardiac frequency range of the power spectrum, that region qualified as “good” data. If the raw time series exhibited a heart rate component, but the data were noisy, it was classified as “average” data. If the raw time series did not show a visible heart rate, the data were too noisy, and the power spectrum did not show a discernable heart rate component, then that data were considered “poor” data. This classification was performed for every subject. Subjects with at least two cortical regions with “average” or more data were included in the next steps of the analysis. Raw fNIRS time series data were then preprocessed using scripts written by our group in the MATLAB R2018b platform. The raw fNIRS signal was converted to optical density and corrected for head-motion using a wavelet-based algorithm.⁶⁰ Motion-corrected fNIRS data were then bandpass filtered at 0.01 to 0.3 Hz and converted to concentration data using the hmrOD2conc function in the Homer2 toolbox.^61–63 A linear temporal regression of the hemoglobin (${\mathrm{HbO}}_2$, HbR, and HbT) time series of each cortical channel was performed using the nearest short-separation (physiological) channel recording as a nuisance regressor.²³ The time series of long-separation channels was the dependent variable, and the time series of the nearest short-separation channels was the independent variable/regressor, as shown in Eq. (1):

This was performed for every long-separation channel ($n=24$). The residual hemoglobin time series from temporal regression was then fitted using a third-order polynomial to remove nonlinear drifts. Lastly, the data were corrected for linear drifts and converted to microMolar ($\mu \mathrm{M}$) units.

2.7.

Data Analysis

After preprocessing, the time series for ${\mathrm{HbO}}_2$, HbR, and HbT of the 12 channels on the hemisphere contralateral and the 12 channels on the ipsilateral hemisphere to the operated-on knee were retrieved (see Fig. 1 for diagram of channels). The ${\mathrm{HbO}}_2$ time series of these adjacent channels in each cortex were averaged within the contralateral and ipsilateral ROIs to form a single time series for the six different ROIs in every patient (see Fig. 2 for an illustration of this process for a single patient).

2.8.

Rolling Average Concentration Change

Concentration changes in these six ROIs were investigated at three different time points: no procedure (P0; i.e., no surgival interventions during this time), first incision (P1), and last incision (P2). P0 was defined as the 60-s intraoperative epoch in which patients did not receive any procedure. This metric was individually determined for each patient by selecting the longest possible lapse of time between any procedure (minimim 2 min; maximum 9 min; average 4.5 min). This was because there was not enough duration before any kind of surgical intervention was made. P1 was defined as the 60-s epoch following the first incision, and P2 was defined as the 60-s epoch following the last incision. All epochs were normalized to the mean at the time of observation. A timeline of the surgical procedures including the P0, P1, and P2 events in each patient is shown in Fig. 3.

Fig. 3

Timeline for surgical events during anesthesia. Presurgical pain scores for each patient were ranked on a 0 to 10 VRS scale (0 being no pain; 10 being worst pain imaginable). After presurgery, NB patients are marked with a Y and non-NB patients are marked with an N. The first incision, representing the first instance of pain in the patient (P1), occurs in the minute marked with the black diamond. The 60 s that are furthest away from an event (painful or nonpainful) are marked with a magenta diamond (P0) and the last incision is marked with a green diamond (P2). Other procedures which are painful in nature happen within the minute increments marked with red circles, while nonpainful procedures are marked with blue circles. Surgery lasted between 25 and 65 min for each patient. Another VRS pain score was taken in the recovery room postsurgery, and a final score after being discharged from the PACU.

Next, a standardized 10-s sliding window with 1-s increments was calculated for the 60 s during P0, P1, and P2. The area for the absolute standardized rolling average curves was computed for the six ROIs in each patient using the trapz function in MATLAB. A mixed ANOVA approach was utilized to protect against type I errors due to multiple comparisons. This helps to identify significant differences in the area under the curve measure of P0, P1, and P2 procedures in NB versus non-NB groups. Statistically significant effects were obtained at the significance level of $p<0.05$. A Benjamini–Hochberg false-discovery rate (FDR) correction for multiple comparison problems (at $\alpha =0.05$) was also utilized (PMID 28740688).

2.9.

Functional Correlation

Between the 15 unique ROI–ROI connections for a given epoch, we calculated Pearson’s $r$ correlation coefficient for P0, P1, and P2 conditions. These average changes in correlation over time were grouped into the PreFC, S1, and PreFC/S1 regions (by averaging all channels within the contralateral hemisphere) for NB and non-NB patients. This was computed using a sliding window correlation approach (see Fig. 7 for an example of this). A mixed ANOVA approach was used to identify significant differences in the functional correlation measures and dynamic functional correlation measures of P0, P1, and P2 procedures in NB versus non-NB groups and over time. Any statistically significant effects were recorded at significance level of $p<0.05$ with a Benjamini–Hocberg FDR correction for multiple comparison problem (at $\alpha =0.05$).

3.1.

Pain Events With and Without Nerve Blockade: Dynamic Hemoglobin Concentration and Correlation Values

The values of $\mathrm{\Delta }[{\mathrm{HbO}}_2]$, $\mathrm{\Delta }[\mathrm{HbR}]$, and $\mathrm{\Delta }[\mathrm{HbT}]$ on the contralateral and ipsilateral sides of the brain corresponding with affected knee showed significant relations between NB and non-NB groups, and between the pain events P1 and P2, and the control period P0. Between the 18 combinations of hemoglobin concentration, observed periods of time (P0, P1 or P2), proximity to the knee and the six ROIs, we observed the following traits indicative of the presence of nerve block and the presence of pain. Below we note the three major findings.

3.1.1.

Large contralateral $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ increases following a painful event in non-NB patient group

The time series graph in Fig. 4 shows the average contralateral $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ and its standard error over the six ROIs. (The median figure is shown in Fig. S2 in the Supplementary Material.) No significant relationships are observed in the PreFC ROIs during any event, with all $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ concentration levels staying within $\pm \mathrm{\Delta }0.2\mathrm{mM}$ of the baseline. The most notable finding in concentration difference is the poststimulus increase in non-NB patients. This reaches an average amplitude peak of $+\mathrm{\Delta }0.41$ mM after around 20 s in P1 and a $\ge 30\mathrm{s}$ epoch after P2 (this peak becomes the new baseline in InfS1 while this signal declines to the baseline in CentS1 and SupS1). Conversely, for patients without a nerve block, an overall decrease in $[{\mathrm{HbO}}_2]$ was observed within the first 5 s in inferior S1. The changes in $[{\mathrm{HbO}}_2]$ observed in S1 were not seen in data obtained in the absence of painful procedures. This shows a repeatable measure to detect the presence of a pain event for patients without a nerve block (and potentially with one).

Fig. 4

Mean concentration over time. Rolling averages and standard errors for the standardized contralateral oxygenated hemoglobin concentration ($\mathrm{\Delta }[{\mathrm{HbO}}_2]$) are observed for six relevant ROIs; lateral polar frontal cortex (lateral FC), lateral Pre-FC, medial Pre-FC, inferior S1, medial S1, and polar S1. These are recorded for the minute where no procedure occurs (P0), the minute after the first recorded incision takes place (P1), and the minute after the last recorded incision takes place (P2). Average concentrations of patients who were given nerve block (NB) are in red and patients not given nerve block (non-NB) are in blue. Correlations are taken every 10 s at the points marked in magenta and are shown in Fig. 7.

3.1.2.

Areas between $\mathrm{\Delta }[{\mathrm{HbO}}_2]$, $\mathrm{\Delta }[\mathrm{HbR}]$, and $\mathrm{\Delta }[\mathrm{HbT}]$ and the x axis in some contralateral S1 ROIs are statistically significant between NB and non-NB groups

Absolute areas between contralateral and ipsilateral $\mathrm{\Delta }[{\mathrm{HbO}}_2]$, $\mathrm{\Delta }[\mathrm{HbR}]$, and $\mathrm{\Delta }[\mathrm{HbT}]$ and the $x$ axis are on average four times larger for S1 ROIs than PreFC ROIs and twice as large for NB groups than non-NB groups (see Fig. 5 for a visual representation of contralateral $\mathrm{\Delta }[{\mathrm{HbO}}_2]$). Across the 18 observed combinations in Table S2 in the Supplementary Material, there are 10 relations between the NB and non-NB groups that are statistically significant under a mixed model ANOVA approach. Of these, eight of these are in the contralateral S1 region. Notably, all three observed time periods (P0, P1, and P2) are significant for contralateral $\mathrm{\Delta }[\mathrm{HbR}]$ in central S1. The result for contralateral P1 $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ and $\mathrm{\Delta }[\mathrm{HbR}]$ is also shown to be statistically significant after FDR at $\alpha =0.05$.

Fig. 5

Bar chart of area under standardized curves for 12 channels. The average area captured between the $X$ axis baseline and the NB and non-NB curves (see Fig. 4) for each of the six ROIs is shown for P0, P1, and P2. The labels on each bar in magenta show the total area captured with the error bar representing the standard error of the group. The two magenta lines show the total mean for the PreFC and S1, respectively, for their six areas captured by the curve. A two sampled $t$-test was conducted between the nerve and non-nerve blocks for $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ (see Table S3 in the Supplementary Material). Numbers in black show that the null hypothesis has been accepted such that both vectors come from normal distributions with equals means while numbers in red show the nerve block and non-nerve block vectors reject the null hypothesis. Bars marked with a (*) are statistically significant after FDR correction at $\alpha =0.05$.

These significances provide crucial information for showing the presence of a nerve block within the patient based on the findings thus far, especially early on into surgery observing contralateral P1 CL $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ and $\mathrm{\Delta }[\mathrm{HbR}]$. Finally, a strong repeatability measure is observed in the non-NB groups for pain procedures in ipsilateral $\mathrm{\Delta }[\mathrm{HbR}]$ for the superior S1 ROI (underlined in Table S2 in the Supplementary Material).^64–66 These concentrations are shown to be consistent across patients during pain events, and a moderate resemblance during the recorded nonpain event P0. Differences between absolute areas under the curve for contra- and ipsilateral ROIs for P1 and P2 in non-NB are shown in Fig. 6.

Fig. 6

Activated versus inactivated areas under the curve for P1 and P2. Activation on the contralateral slide is compared against the inactivation on the ipsilateral side. These area between the curve and the $x$ axis for non-NB patients are compared between the P1 and P2 periods. The area for the activated side was smaller than the inactivated side except for changes in deoxyhemoglobin in inferior S1 during P2.

3.1.3.

There are three significant differences between NB and non-NB groups and one significant difference over time that are repeated over contralateral and ipsilateral $\mathrm{\Delta }[{\mathrm{HbO}}_2]$

Correlation analyses were performed to determine if interactions between ROIs could provide further insights to the cortical hemodynamic response to pain procedures. Correlations between ROIs were shown to be robustly positive in PreFC regions, weakly positive in S1 and very weakly negative in the PreFC/S1 overlap. Figure 7 shows the average changes in correlation over 10-s intervals for the PreFC and S1 regions, their overlap PreFC/S1, and across all correlations for $\mathrm{\Delta }[{\mathrm{HbO}}_2]$. This graph shows four relations that are statistically significant ($p<0.05$), with (a) and (b) remaining statistically significant after FDR. (a) The effects of time in the PreFC/S1 overlap during P2. (b) The correlations between NB and non-NB groups in the PreFC/S1 overlap during P2. (c) The correlations between NB and non-NB groups in the PreFC/S1 overlap during P1. (d) The correlations between NB and non-NB groups in the total of all correlations during P1.

Fig. 7

Average correlation over time. The average standardized correlations of $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ for all channels within PreFC, S1, between PreFC/S1 and their totals were calculated using a 10-s window incremented by 1 s. Only the correlation measures at 10-s windows (0,10,20,30,40,50) are shown by the magenta lines in Fig. 4 along with standard error of mean. Regions with significant effects of time on $\mathrm{\Delta }[{\mathrm{HbO}}_2]$ are indicated the $x$ axis label “time (s)” is highlighted in red and in blue if it remains significant after FDR, with significant effects of NB-time interaction indicated using the $y$ axis label “change ($r$).”

Table S3 in the Supplementary Material shows that observations (a) to (d) is repeated across the ipsilateral side for $\mathrm{\Delta }[{\mathrm{HbO}}_2]$; however, while only (b) is significant after FDR ($\alpha =0.05$) at on the contralateral side, (b) to (d) are also significant on the ipsilateral side in this way. (b) and (c) show a repeated measure between NB and non-NB groups that is not present during the control period P0 that holds for all pain events to the patients.

4.1.

fNIRS Signal Changes to an Incisional Procedure

We obtained continuous bilateral recordings from three brain regions in patients under general anesthesia: S1, mPFC and LPFC as shown in Sec. 3. We interpret the results from these recordings as: (1) fNIRS can measure a surgical incision event—the cortical response occurs within 5 s of the incision, clearly within the time-domain of fNIRS response;⁶⁹ (2) even with a regional nerve block (although not evaluated for efficacy due to administration after patients were unconscious), fNIRS measurements of changes in $[{\mathrm{HbO}}_2]$ are still observed, albeit opposite to those observed without a nerve block (discussed below), suggesting that a painful event can be temporally evaluated; and (3) the measure is repeatable even in the context of apparent differences in assumed fentanyl plasma concentrations.

Taken together, we have deduced a number of indicators (fNIRS response time) locked with incision presumed to activate nociceptor fibers with an incision. This is dependent on measures of $[{\mathrm{HbO}}_2]$ determined during the surgical procedure. As such, using fNIRS, it may be possible to provide a signal for pain/nociception over the course of the surgical procedure.

4.2.

fNIRS Measures of the Response to Surgical Trauma: Is this Nociception/Pain?

Here, we discuss three aspects of why we consider our fNIRS measures to likely be measures of pain/nociception. We are careful to use the term “pain” here, since it normally refers to conscious perception (see definition by the International Association for the Study of Pain).⁷⁰ We are confident that we are measuring nociception, since (1) the fNIRS signals are observed and temporally associated with the incision; (2) the brain regions are associated directly and indirectly, including higher order, with the processing of nociception; (3) the use of opioid analgesics (i.e., fentanyl) diminishes the fNIRS signal, which is presumably a result of activation of the nociceptive pathways. The nerve blocks may also contribute to this understanding.

Tissue damage activates nociceptors via direct damage to pain fibers.⁷¹ Once initiated, inflammatory processes promote ongoing pain via activation of primary afferent neurons and may produce peripheral sensitization (enhancement of signal transmission to painful or nonpainful stimuli).⁷² Such changes may induce central sensitization because of the ongoing afferent barrage from the initial damage or subsequent tissue damage.⁷³ To date, few studies have shown that attempts at complete neural blockade of afferent pathways can be accomplished to prevent central sensitization. This is relevant for a number of reasons, including the ideas that central sensitization may lead to increased postoperative pain,⁷⁴ which may potentially be the initial harbinger of pain chronification.⁷⁵

As noted above, nociceptive activation of the central nervous system may occur with deep general anesthesia—although clinical responses may not be detected —and nociceptive activation persists under general anesthesia in healthy volunteers in the brain⁶⁷ and spinal cord.⁶⁶ Unless there is a complete, successful nerve block, nociceptive afferent information will reach the cortical regions of the brain⁷⁶—as is evidenced from our group’s findings, using fNIRS, that cortical activity is present under general anesthesia in patients undergoing cardiac ablation.²² Such data are corroborated by findings in anesthetized rats, using anesthetic agents, such as propofol,⁷⁷ and in patients under propofol sedation for colonoscopy.²⁴

4.3.

Are the Areas (S1, mPFC, lPFC, and Lateral Pre-FC) Used in our fNIRS Signal Measures Involved in Pain/Nociceptive Processing?

The primary somatosensory cortex is well defined to be involved following primary nociceptive activation in animal and human studies.^78,79 Usually, the activation is somatotopically organized based on the human homunculus^80,81 but may be altered by nerve blockade^82,83 or ischemic anesthesia.⁸⁴ The PreFC has a major role in pain processing,⁸⁵ and we have previously summarized the role of the polar frontal cortex in pain processing.²⁹ The lateral frontal cortex included the ventral- and dorsolateral prefrontal cortex has also been documented to be activated following painful stimuli.⁸⁶ Taken together, while some of these regions may have more direct involvement in nociceptive pathways, they are nonetheless all involved through functional connectivity as part of the pain connectome.⁸⁷

Opioids are potent analgesics for acute pain⁸⁸ and are frequently administered as part of the anesthesia protocol because inhalational anesthetics are not potent analgesics.^89,90 In our patient group, the opioid fentanyl (50, 100, or $150\mu \mathrm{g}$), which acts on $\mu$-opioid receptors, was administered intravenously at the beginning of the anesthetic procedure ($n=17$), and in some cases ($n=6$), repeated. Using the intravenous route, the time to maximum concentration is around 5 min, with the analgesic effect being delayed by around 2.5 min and lasting, on average, over 2 h.^87,91 One dose of intravenous $100\mu \mathrm{g}$ fentanyl has an equivalent analgesic effect of 10 mg of intravenous morphine. Our prior work has indicated a dose-dependent effect of oral morphine (10 mg) to a painful stimulus.³¹ While opioids may produce their analgesic effects by peripheral and central mechanisms, complete blockade at clinical doses used in the anesthetic regimen may not be possible, although fentanyl⁷³ and remifentanil,⁹² for example, suppress brain activation as measured by positron emission tomography with $1.5\mu \mathrm{g}/\mathrm{kg}$ in healthy volunteers and EEG measures in rats.⁹³

We observed an increase in the fNIRS response at the last incision. We suggest that there are two mechanisms that may be at play: (1) hyperalgesia induced by the incision as noted above due to inflammatory activation and also repetitive nociceptive barrages occurring as a result of the surgical repair; and (2) fentanyl produces rapid onset of hyperalgesic priming at both peripheral and central nociceptors as a result of prolongation of inflammatory-induced hyperalgesia.⁹⁴ There was also a change in the fNIRS signal between nerve block and non-nerve block groups, which is one conundrum related to an analgesic effect. We expected the nerve block group to have less of a cortical response and also a decreased pain score in the early postoperative period versus the non-nerve block group (see Fig. 8). While we do not have a clear answer, there are a number of possibilities, including: (1) altered functional changes in interhemispheric communication: reports of alteration or distortion in responses in S1 may be a result of an increase in inhibitory interneuron activity for transcallosal pathways causing inappropriate functional responses in the ipsilateral hemisphere (see Ref. 96); (2) alterations in tactile inputs: the nerve block may have a differential effect on pain (C and Ad fibers) versus touch and proprioceptive inputs (AB fibers) (see Ref. 97). Given that the nerve block was administered to some patients while under anesthesia, there was no way to evaluate the efficacy during the anesthetic period.⁹⁸ In line with this, sensory inputs may be present from other portions of the knee not involved in the nerve block’s targeted coverage; and (3) rewiring: neural blockade may cause rapid rewiring of S1 synaptic connections, as shown in prior fMRI studies in neuropathic pain patients,⁹⁹ surgical disruption of nerves,¹⁰⁰ or following local anesthetic blockade in noninjured animals.^101,102 Local hyperexcitability of S1 and to frontal areas may result from rapid alteration of dendritic spines resulting from altered sensory input.¹⁰³

Fig. 8

Pain scores. Patients are asked to self-report pain levels on a VRS scale of 0 to 10 (0 being no pain felt; 10 being worst pain imaginable) at three times during their visit: presurgery, postsurgery, and after discharge from the PACU. Patients are separated into NB and non-NB groups, and the average of each group is shown on top of each color-coded line on the left-hand side. Differences in scores pre- to post-surgery ranged from no change noticed in patients 2, 3, and 16, to a pain score increase of 6 observed in patients 1, 5, 7, 8, 18, and 19. The mean of the change in pain scores pre- to postsurgery was 3.53 with a standard error of 2.7 showing that in the average surgical window of 51 min, a large increase in pain is felt, increasing cases of “no pain” (VRS 0) to “mild pain” (VRS 1-3), and “mild pain” to “moderate pain” (VRS 4-6).⁹⁵

4.4.

Perioperative Pain Scores and Pain Algorithms

There are a few salient issues related to pain in this paper that deserve further investigation. The first is the ability to measure pain/nociceptive events as discussed above, and the second relates to the efficacy of the nerve block. Based on postsurgical self-reported VRS pain scores in the PACU (see Fig. 8), there are no differences in pain scores based on this small population (see caveats). In addition, there is no “blockade” of fNIRS activation with nerve block, as would be expected. As such, intraoperative monitoring of nociception, no matter what the anesthetic procedure is, would seem like a valuable asset in the surgical setting to provide information on inhibition of pain/nociception as measured by fNIRS. The third issue relates to the development of real-time measures: in addition to intraoperative notification of pain/nociceptive signals (and appropriate, timely analgesia or maintenance thereof), this approach may also provide a cumulative “pain load” that could be measured by applying algorithms to provide such a measure. Pain load may be a critical measure for predicting postoperative pain and, potentially, pain chronification.

The changes to hemoglobin concentrations as a response to pain can be measured in real time as a way to detect when the patient is feeling pain during surgery. From a series of repeatable results, an algorithm can be trained to receive previous time series values and foresee how the patient will respond to painful stimuli. Machine learning techniques practice on previous patient data where times of incision can be recorded.¹⁰⁴ From here, the predictions can be made based on how patients with similar hemoglobin concentration levels have responded to pain.

4.5.

Caveats

There are a number of caveats that need to be considered.