2.1.

Participants and Experimental Design

A total of 15 participants (9 males and 6 females; $20.9\pm 3.8\mathrm{year}$, $65.7\pm 10.4\mathrm{kg}$, $168.6\pm 7.3\mathrm{cm}$) were recruited for the study. Participants were nonsmokers, who were not involved in any athletic or programmed physical activities for the previous six months, had no history of asthma, cardiopulmonary, or musculoskeletal disease, and were not currently taking any medications or sports supplements. Training and testing took place in the Human Performance Laboratory of the Institute for Clinical and Translational Science (ICTS) at the University of California, Irvine. Participants provided written informed consent before their involvement in the study. Following consent, two of three exercise protocols (see exercise training below) were randomly assigned to each participant with one protocol being applied to the left leg and a second, different protocol applied to the right leg using a block-randomization schedule. Participants attended two to three preliminary sessions to be familiarized with the testing and training equipment. Following familiarization, testing measurements were performed during a baseline session before exercise training began and a post-training session following 5 weeks of exercise training. Each testing session included body composition assessed by DXA and DOSI. In addition to these assessments, muscular strength was determined using a one-repetition maximum (1RM) model. The study protocol was approved in advance by the Institutional Review Board of the University of California, Irvine.

2.2.

Exercise Training

RT occurred over a 5-week period with participants training 3 days/week for total of 15 training sessions. This study utilized three exercise training protocols: (1) low-intensity at 20% 1RM (LIT), (2) high-intensity exercise at 70% 1RM (HIT), and (3) low-intensity exercise at 20% 1RM with blood-flow restriction ($\mathrm{LIT}+\mathrm{BFR}$). Exercise training occurred unilaterally on a 45-deg angle hack squat machine (HF-4357, Hoist Fitness, San Diego, California). Participant foot placement was determined by centering the metatarsophalangeal articulation for the sagittal plane and the medial side of the shoe for the frontal plane on the equipment foot plate. During each session, the right leg was trained first followed by the left leg. Each repetition started with the ankle in a dorsiflexed position. Participants were encouraged to plantar flex under maximal effort with a controlled descent back to the initial dorsiflexed position for 1.5 s controlled with a metronome. Under the protocol with BFR, an automated blood pressure cuff (Hokanson, Inc., Bellevue, Washington) was placed proximal to the knee joint during training. The cuff was inflated to $1.3\times$ systolic blood pressure before the commencement of exercise. Following the training session, participants consumed 20 g of high-quality whey protein supplement (Optimum Nutrition, Downers Grove, Illinois) in 200 mL of water.

2.3.

1-Repetition Maximum Strength Testing

Participants were positioned on the exercise equipment and instructed by study personnel to perform exercises at maximal exertion utilizing the technique described above. A repetition was considered successful if the weight was lifted to at least 80% of the maximum distance obtained during an unloaded repetition. Following a successful repetition, participants rested at least 1.5 min before weight was incrementally increased in association with guidelines set forth by the National Strength and Conditioning Association.²⁵ Incremental increases were repeated until a participant was unable to perform a successful repetition. The highest load lifted for a successful repetition was noted as the participant’s 1RM.

2.4.

Dual Energy X-Ray Absorptiometry Measurements

DXA measurements were performed at baseline and post-training with a Hologic Discovery A DXA system using Apex 3.3 software (Hologic, Marlborough, Massachusetts). Participants lay supine on a padded table with all metal objects removed. Participants were raster scanned from head to foot and then the lower leg region was defined superiorly by tibiofemoral joint and inferiorly by the talocrural joint. To more directly compare DOSI and DXA values, bone mineral content was excluded from the DXA data and only soft-tissue parameters were analyzed. Specifically, soft tissue is comprised of FM and residual LM. In addition to FM and LM, the fraction of the soft tissue that is LM is defined in this study as lean mass fraction (LMF).

2.5.

Diffuse Optical Spectroscopic Imaging Measurements

The technical details of DOSI have been described previously.²⁰ Briefly, DOSI combines FDPM and broadband spectroscopy to obtain absorption and scattering coefficients across a broad range of wavelengths (650 to 1000 nm). This allows for precise quantitation of tissue concentrations of the major absorbers in this range of wavelengths. The system used in this study has been described previously but a brief overview will be provided here.¹⁴ The FDPM system utilizes three intensity-modulated, near-infrared laser diodes (690, 785, and 835 nm) and an avalanche photodiode detector to collect diffusely reflected light in the form of photon density waves. The broadband NIRS system utilizes a broadband quartz tungsten halogen source and a spectrometer for light collection. All light sources are fiber-coupled into a handheld probe that contains the avalanche photodiode and another optical fiber coupled to a spectrometer. Fiber placement in the probe allows for coregistered FDPM and broadband NIRS measurements with a source–detector separation that is fixed at 28 mm.

DOSI measurements were performed at baseline and post-training. Post-training DOSI assessments were performed at least 65 h ($80\pm 13\mathrm{h}$) following the final exercise session for all participants. Participants were positioned prone on a padded table and grids of 48 points each were drawn over both calves (Fig. 1). The grids consisted of six rows and eight columns, each separated by 2.5 cm ($\sim 220{\mathrm{cm}}^2$ total area). Three broadband DOSI scans were performed ($\sim 3\mathrm{s}/\mathrm{scan}$) at each grid point and tissue chromophore concentrations were averaged from the sequential scans. The chromophores analyzed in this study consisted of oxygenated hemo+myoglobin (${\mathrm{HbMbO}}_2$), deoxygenated hemo+myoglobin (HbMbR), water content (water), lipid content (lipid), and then the following derived parameters: total hemo+myoglobin ($\mathrm{THbMb}={\mathrm{HbMbO}}_2+\mathrm{HbMbR}$) and oxygen saturation (${\mathrm{StO}}_2={\mathrm{HbMbO}}_2/\mathrm{THbMb}$).

Fig. 1

The photo on the left shows a sample participant with the DOSI grid-points on the lower legs. Eight columns and six rows covered each leg, with each point being spaced 2.5 cm from the next point. DOSI THbMb results are shown in a grid image in the middle. On the right, an interpolated DOSI image is formed by using cubic spline interpolation between points. Contrast from medial and lateral muscle head groups can be seen in the lower left and right regions of the grid, respectively. THbMb, total-hemo/myoglobin; DOSI, diffuse optical spectroscopic imaging.

Prior to analysis, a medial region of interest (RoI) from the DOSI grid was selected. This RoI selection was performed for two reasons: (1) to help account for potential grid-shifting due to manual scanning error during data collection and (2) to allow for detailed analysis on a highly reproducible region, which was most likely sampling gastrocnemius muscle tissue (contained higher levels of THbMb than the surrounding tissue). Medial RoIs were determined using a thresholding criterion that has been used previously to identify and track tumors in breast cancer.²³ We are using the method in this study to track the medial head of the gastrocnemius and we defined a THbMb threshold as

2.6.

DOSI Surface Rendering

The 3-D surface geometry of a sample participant was acquired using a Microsoft Kinect for Windows V1 (Microsoft, Washington) and the Kinect Fusion SDK. The Kinect also acquires an image of the surface, which is textured onto the 3-D geometry using open source software Point Cloud Library.²⁶ The textured 3-D mesh is rendered and the measurement points are selected. The optical data, measurement locations, and 3-D mesh are imported into MATLAB to generate a 3-D interpolated topographic map. A similar process was used in our previous studies of weight loss and breast cancer chemotherapy monitoring to create 3-D renderings of DOSI data from abdomen and breast tissue.^14,23 Not all participants were available for scanning with the Kinect system, so the initial 3-D surface geometry from a representative volunteer was used to generate 3-D surface images with DOSI data from all participants. This surface rendering was only utilized to help visualize each participant’s data and did not affect the results from this study. The method is included solely to explain how to repeat the exact visualization we have shown in this study.

2.7.

Statistical Analysis

Throughout this study, we employed the Holm–Bonferroni correction when testing multiple hypotheses and our significance level was defined as $\alpha =0.05$. All statistical tests were performed with R (R Foundation for Statistical Computing, Vienna, Austria.)

Wilcoxon signed-rank tests were performed to test for changes in repeatedly measured parameters. For DXA, we tested for changes in lower leg LM, FM, and LMF, and for DOSI, we tested for changes in ${\mathrm{HbMbO}}_2$, HbMbR, THbMb, ${\mathrm{StO}}_2$, water, and lipid.

Pearson product–moment correlation coefficients were calculated for all six pairs of DOSI parameters and DXA LMF. Coefficients were calculated separately for parameters measured at baseline and post-training. Since repeated observations were performed on each participant (data were collected for both legs), there was a possibility that repeated observations would enhance the significance of our correlation tests. To address this issue, mean values between the two legs were calculated for DOSI and DXA parameters before correlation tests were performed so only one data point per person is included in correlation tests.²⁷ This method allows for a more accurate description of correlations between participants when there are repeated measures for each individual participant.²⁷ It should be emphasized that this process was more conservative than simply treating all legs as independent contributors to the correlation tests.

3.1.

Participant Demographics and Strength Training

The cohort of participants involved a combination of nine male and six female participants ranging in age from 18 to 33 years. All 15 of these participants were assessed with DXA and performed all strength testing and training. Among the 30 legs from the 15 total participants, 9 legs were assigned to LIT, 10 to HIT, and 11 to LIT + BFR. Three participants were not able to contribute to the DOSI results due to system malfunction, so the DOSI data are composed of 12 participants (8 male, 4 female). A faulty electronic component needed repair in the DOSI instrument and participants were unavailable when attempting to reschedule after repair. For the three participants with missing DOSI data, strength data were used in the 1RM comparison between training regimens, but these participants are not included when comparing DXA, DOSI, and 1RM results in the correlation tests.

Participants did not experience significant body weight changes over the course of the study, measuring $67.0\pm 2.0\mathrm{kg}$ at baseline and $66.9\pm 2.1\mathrm{kg}$ post-training. While all three training regimens resulted in significantly increased 1RM, there was no statistical difference in 1RM gains when comparing regimens. When all regimens were pooled together, the entire cohort showed a significant increase in 1RM with a $62\pm 9\%$ change over average baseline values of $70.7\pm 4.9\mathrm{kg}$ ($\mathrm{\Delta }1\mathrm{RM}=41.5\pm 6.2\mathrm{kg}$, $p=1.9\times {10}^{-5}$). All participants experienced 1RM gains in both legs except for one participant whose 1RM did not change in her right leg. Since no statistical difference was detected in 1RM between separate training regimens, we did not break the participants into subcohorts for DOSI and DXA analysis. In addition, we did not observe an association between baseline 1RM and the magnitude of 1RM change.

3.2.

DOSI Images and Surface Rendering

Recovered DOSI images were generated for all parameters and data were rendered on a 3-D surface geometry from a sample participant (Fig. 2). Spatial heterogeneities were present in all images and likely reveal the location of the medial and lateral heads of the gastrocnemius. The images demonstrate changes that take place between baseline [Figs. 2(a) and 2(b)] and post-training [Figs. 2(e) and 2(f)], and show that specific regions of the gastrocnemius present greater changes than elsewhere. For the participant’s data shown in these images, absorption and reduced scattering coefficients were in the range of 0.010 to $0.055{\mathrm{mm}}^{-1}$ and 0.4 to $0.8{\mathrm{mm}}^{-1}$, respectively, depending on measurement position and wavelength [Figs. 2(a), 2(d), 2(g), and 2(h)]. The large range in optical properties was expected as each participant was scanned over a total area of $\sim 220{\mathrm{cm}}^2$.

Fig. 2

This figure shows sample THbMb DOSI images, THbMb surface renderings, and optical properties for a participant’s right leg. (a) Baseline DOSI THbMb map with the approximate medial RoI marked. (b) Baseline DOSI THbMb surface rendering. (c) Mean ($\pm \mathrm{std}$ dev) absorption coefficients across the medial RoI and across the entire calf. (d) Mean ($\pm \mathrm{std}$ dev) reduced scattering coefficients across the medial RoI and across the entire calf. (e–h) The corresponding figures 5-week post-training. Color bars show concentration of THbMb in $\mu \mathrm{M}$. THbMb, total-hemo+myoglobin; DOSI, diffuse optical spectroscopic imaging.

3.3.

Correlation Tests

At baseline, significant correlations were found between several DOSI parameters and DXA-derived LMF (Fig. 3). LMF was positively correlated with ${\mathrm{HbMbO}}_2$ ($p=2.0\times {10}^{-4}$, $R=0.87$), HbMbR ($p=1.2\times {10}^3$, $R=0.82$), water ($p=1.4\times {10}^{-5}$, $R=0.93$), and THbMb ($p=2.1\times {10}^{-4}$, $R=0.87$) and negatively correlated with lipid ($p=1.6\times {10}^{-5}$, $R=-0.93$).

Fig. 3

These plots show DOSI parameters plotted against LMF from DXA at baseline and post-training. (a) ${\mathrm{HbMbO}}_2$, (b) HbMbR, (c) water, (d) lipid, (e) THbMb, and (f) ${\mathrm{StO}}_2$. Each data point represents a single leg, so 24 points comprise each plot. Significant correlations were detected between all DOSI parameters shown here and LMF except in (f) where ${\mathrm{StO}}_2$ versus LMF did not meet our significance criteria. LMF, lean mass fraction; ${\mathrm{HbMbO}}_2$, oxy-hemo/myoglobin; HbMbR, deoxy-hemo/myoglobin; THbMb, total-hemo/myoglobin; ${\mathrm{StO}}_2$, tissue HbMb saturation; DXA, dual-energy x-ray absorptiometry; DOSI, diffuse optical spectroscopic imaging.

After training, the same correlations were found between DOSI parameters and LMF (Fig. 3). LMF was positively correlated with ${\mathrm{HbMbO}}_2$ ($p=8.7\times {10}^{-5}$, $R=0.89$), HbMbR ($p=0.0027$, $R=0.78$), water ($p=4.2\times {10}^{-6}$, $R=0.94$), and THbMb ($p=0.0002$, $R=0.87$) and negatively correlated with lipid ($p=0.0035$, $R=-0.77$).

At both time points, ${\mathrm{StO}}_2$ was not statistically associated with LMF ($p=0.034$ and 0.0216, $R=0.61$ and 0.65), but it is likely that this result would become statistically significant with more participants.

3.4.

DXA and DOSI Changes with Training

The only significant DXA change with training was a $2\pm 1\%$ increase in LM over average baseline values of $2010.7\pm 85.6\mathrm{g}$ ($\mathrm{\Delta }\mathrm{LM}=36.4\pm 12.4\mathrm{g}$, $p=0.01641$). Of the 30 legs assessed by DXA, 19 showed gains in LM. After training, DOSI data from the medial RoI showed significant increases in ${\mathrm{HbMbO}}_2$ and THbMb, with a $6\pm 2\%$ increase over average baseline values of $57.5\pm 3.5\mu \mathrm{M}$ ($\mathrm{\Delta }{\mathrm{HbMbO}}_2=3.4\pm 1.0\mu \mathrm{M}$, $p=0.00314$) and a $6\pm 1\%$ increase over average baseline values of $82.6\pm 4.4\mu \mathrm{M}$ ($\mathrm{\Delta }\mathrm{THbMb}=4.9\pm 1.1\mu \mathrm{M}$, $p=0.00024$), respectively. Of the 24 legs assessed by DOSI, 18 showed increases in ${\mathrm{HbMbO}}_2$ and 20 showed increases in THbMb. The other DOSI parameters—HbMbR, water, lipid, and ${\mathrm{StO}}_2$—did not change significantly with training. In all cases, no association was detected between baseline parameters and the magnitude of change after training (Fig. 4). In addition, as a secondary set of tests, we evaluated whether the magnitude of DOSI parameter changes was associated with the magnitude of strength change due to training. We did not detect any significant correlations in these secondary tests.

Fig. 4

These figures show changes in (a) 1RM, (b) lean mass, (c) [THbMb], and (d) [${\mathrm{HbMbO}}_2$] that accompanied 5 weeks of RT plotted against baseline values. All four parameters showed significant increases (results in text). Each data point represents a single leg from this study, while the dotted line represents the mean change across the entire cohort. The magnitude of change was not associated with baseline values. 1RM, 1-rep-maximum; THbMb, total-hemo/myoglobin; ${\mathrm{HbMbO}}_2$, oxy-hemo/myoglobin.