Muscular disorders (MDs) are a large heterogeneous group of diseases characterized by progressive weakening and degeneration of skeletal muscle tissue. Many forms of congenital MDs are now known to arise from identified single-gene defects. Molecular diagnosis can clarify medical decisions as to the course of treatment, long-term prognosis, and genetic counseling. Still other MDs are associated only secondarily with the onset of disease elsewhere in the patient, e.g., cachexia in cancer, atrophy due to injury or neuropathy, or sarcopenia of aging. For both genetic and nongenetic MDs, monitoring the course of disease and judging the success of treatment are most often approached through methods that are either low-resolution or invasive, without assessing the integrity of muscle fibers directly. Much attention is focused on the prospect of monitoring disease through microarray gene-expression profiling. However, a recent effort to differentiate expression patterns of early and advanced human Duchenne Muscular Dystrophy showed a remarkable constancy in expression profiles, even as disease worsened over many years.1 Several different imaging modalities, such as quantitative computed tomography, dual energy X-ray absorptiometry, and magnetic resonance imaging, provide information about the geometry, mass, and tissue composition of bone and muscle.2 These noninvasive techniques are suitable for rough quantitative measurements of tissue degradation/repair. However, low spatial resolution prevents these methods from probing the microscopic features and molecular structure of skeletal muscle.
Sarcomeres of striated muscle produce the force that is ultimately responsible for contractile function. Expression and catalysis of sarcomeric proteins are well documented to respond to neuromuscular activity or disease,3, 4, 5, 6, 7 making the sarcomere pattern a prime candidate for a visible indicator of myofiber integrity.8, 9, 10 In fact, some published evidence correlates muscular dystrophy with changes in the sarcomere pattern of biopsy samples.8, 11 However, quantitative microscopic assessment of muscle sarcomere damage has never been adopted as a routine diagnostic tool. The absence of appropriately specific, objective, and automated imaging techniques has been the major limitation for the development of such approaches. Traditional histochemical staining to reveal striations (e.g., eosin or Alizarin blue) lacks molecular specificity, as it also labels additional nonsarcomeric intracellular structures and organelles. Laser diffraction has been used to measure a globally averaged sarcomere length in muscle tissue, and has even been applied to live measurement of muscle extension during orthopedic surgery,12, 13, 14, 15 but it does not allow for a micron-by-micron analysis of the contractile lattice within tissue. Observation of sarcomere pattern by either electron, immunofluorescence, or polarization microscopy has very limited applicability in the clinic: none of these imaging techniques can be used to image directly within thick-muscle biopsy samples, and obtaining statistically reliable data requires analysis of hundreds of histological sections. Moreover, no robust means for quantifying the differences between sarcomere patterns in healthy and diseased muscle—to yield objective scores of muscle fiber structure—has been described for any of these techniques.
We present a novel approach to the problem of quantitative diagnostic muscle imaging, by combining a deep-sectioning, high-resolution optical imaging technique with mathematical and statistical analysis of the resulting intrinsic contrast images from muscle tissue. The myosin thick filaments of sarcomeres produce second-harmonic generation (SHG) when excited by a focused ultrafast-pulsed infrared laser, and the synchronized alignment of repeating sarcomeric A-bands in adjacent myofibrils yields a pattern of high-contrast striation within normal muscle fibers that is striking in its regularity of period and orientation. 16, 17, 18, 19, 20, 21, 22 Furthermore, the method yields three-dimensional stacks comprising relatively large volumes of intact tissue, since the deep-sectioning power of SHG imaging allows image acquisition at a submicron resolution up to into a specimen.
Here, we have assessed the potential of monitoring the progression of muscular disease by quantitative analysis of sarcomere striation patterns in SHG images from muscle samples. By applying the Helmholtz equation for wavenumber to collections of SHG images from groups of individuals, we correlated the distribution of lengths of sarcomeres to the severity of disease, comparing mouse or human muscle suffering atrophic, dystrophic, or sarcopenic decline to matched control specimens. Our data show that quantitative SHG imaging of sarcomeric myosin provides robust discrimination between muscle of healthy animals and those with even mild forms of MDs. Because SHG optics can be adapted by miniaturization for real-time in vivo imaging,23, 24, 25, 26 this method should become valuable for minimally invasive monitoring of muscle structure during medical treatment.
Quantification and Classification of Striation Patterns in SHG Images of Muscle
We used the SHG microscope to capture digital image volumes from skeletal muscle tissue from a range of normal and diseased sources. In healthy myofibers, bands of sarcomeric SHG are straight and evenly spaced, with each band lying virtually orthogonal to the long axis (axis of contraction) of the cell. Damaged cells display a range of visible deviations from this norm, sometimes localized to subdomains within a giant myofiber: hypercontraction or hyperextension of striation spacing; misorientation, skewing, or contortion of bands; diminution or complete loss of SHG intensity (Fig. 1 ). An individual region of contractile apparatus can be found to display any one or a combination of these defects. To measure these changes and to assign criteria for scoring normal and abnormal structure, we applied the Helmholtz equation for wavenumber to calculate the local striation spacing and angle of orientation, thus creating new image maps for each of these metrics, in addition to the primary map of SHG intensity [Figs. 2a and 2b ; see Section 4 for details of the algorithm]. The deep optical sectioning power of the SHG microscope produced multislice image stacks that typically comprised more than of tissue. Thus, the fine spatial resolution of this sarcomere pattern quantitation (SPQ) algorithm allowed automatic assessment, by three distinct numerical criteria, of each of the tens of thousands of sarcomeres within the group of muscle fibers that were sampled by a single image volume. Unfortunately, the nonlinear dependence of measured SHG intensity upon sample thickness deterred us from assigning reliable abnormal/normal cut-off levels to make diagnostic distinctions based on image brightness. However, by reference to the literature on the physiology and ultrastructure of mammalian sarcomeres, and by empirical fitting to control images, we defined thresholds for scoring of abnormal sarcomere length ( or , a range characteristic of normal needle biopsy samples27) and striation angle ( or ). These threshold measurments were independent of specimen-depth effects on image intensity, and they excluded consideration of any region lacking SHG pattern, therefore focusing entirely on myosin-containing structure within myofiber cells. Acquiring these objective SPQ measurements permitted detailed statistical analysis of the effects of specific MDs upon the structure of sarcomeres throughout the imaged volume.
Correlation of Sarcomere Pattern Scores with Damage Due to MDs in Mice
We tested the applicability of the SPQ scoring algorithm to detecting and quantifying disease in muscle. We imaged specimens of gastrocnemius muscle by SHG, comparing SHG image sets from control mice against SHG image data acquired from mice with each of three established models of muscular disorders: disuse-induced atrophy, hereditary muscular dystrophy, and aging (see descriptions of disease models in Section 4). The selected models each incur a characteristic range of damage within the full spectrum of phenotypic severity, allowing us to rate the sensitivity of SHG image analysis in detecting injury. Efforts to combine binary thresholds for both SPQ criteria (length and angle) to measure the abundance of normal versus abnormal sarcomeres provided rather reliable differentiation between healthy and diseased muscle samples (data not shown). However, we found that a detailed analysis focusing specifically on the distribution of sarcomere lengths within specimens produced even better distinctions. A consistent negative correlation between the severity of a disease and the mean sarcomere length was revealed for all disorder models we tested [Fig. 2d]. While sarcomere lengths spanned from in biopsies of healthy muscles, both mild and severe forms of MDs showed a noticeable reduction in the range of sarcomere lengths and an increased fraction of hypercontracted sarcomeres with lengths below [Figs. 2c and 2d].
To employ these differences in sarcomere length as a diagnostic marker, we extracted three distinct characteristics of the distribution of sarcomere lengths for each sample volume: the overall mean length (ML), the fraction of all sarcomeres that were not hypercontracted below in length (FNH), and the mean length of the fraction of sarcomeres that were not hypercontracted (MNHL). Clear discrimination between healthy and disordered muscle could be achieved using either ML or FNH alone when control mice were compared to double mutants, which lack functional dystrophin and utrophin proteins and develop a severe form of Duchenne-like dystrophy [Fig. 2d].28, 29 Similarly, ML showed a significant difference between controls and animals subjected to atrophy by hindlimb suspension (HLS) [Fig. 2d], a protocol that decreased femur bone mineral density by an average of 12% and muscle fiber size by 13% (see Fig. 3 ). Consistent, but not statistically significant, alteration of sarcomere pattern relative to controls was detected in biopsies affected by other milder muscular disorders (mice with single mutations lacking only dystrophin, wild-type mice recovering from atrophy, or wild-type mice of advanced age). These milder forms of disease also displayed a broader range of FNH scores among the acquired image volumes, suggesting a mixture of normal and abnormal sarcomere pattern throughout the tissue of these animals.
To more carefully test the diagnostic efficacy of SPQ scores, we performed receiver operating characteristic (ROC) analysis—both nonparametric and using multivariate logistic regression—to assess the specificity and sensitivity of SPQ measures in distinguishing groups by a clinically relevant statistical test (Table 1 ).30, 31, 32 As expected, evaluation of muscle damage based on a single sarcomere pattern parameter (FNH or MNHL) was sufficient to reliably detect severe MDs, such as dystrophy in mutants and muscle atrophy in hindlimb-suspended mice [ROC areas under the curve (AUC) , with 95% confidence for both FNH and MNHL in both comparisons; Table 1], at late stages when other signs of disease were clearly observed. Yet the diagnostic power of either of these parameters alone was not sufficient for clear discrimination of any moderate or mild form of MD from control samples (ROC AUC , 95% confidence for all cases; Table 1).
Discrimination of control and diseased mouse muscle by SPQ measurements. Receiver operating characteristic area-under-the-curve (ROC AUC) values are shown in bold face for comparisons among control, mild, and severe disorders. Confidence intervals for each of these calculated values were derived by 1000-fold bootstrap resampling with replacement. The 95% confidence interval for the ROC AUC of each comparison is shown in parentheses under the measured ROC AUC value.
Remarkably, however, bivariate logistic regression combining both FNH and MNHL substantially improved the impact of SPQ scoring and allowed us in several cases to efficiently discriminate intermediate forms of MDs from either control samples or severely affected individuals. For example, in a test for the subtle changes brought on by aging, we achieved quite effective differentiation of -old mouse muscle from -old specimens (ROC AUC 0.866, 95% confidence 0.786; Table 1). This contrast was detected despite our finding of no significant difference in either agility or the percentage of fat-free body mass between breed-matched animals of these approximate age groups (Fig. 4 ) and the absence of any visibly recognizable alterations of sarcomere pattern. Even more strikingly, both (mild) and (severe) dystrophic animals were absolutely discriminated from wild-type controls by a logistic regression model combining all three measures of sarcomere length distribution (ROC AUC 1.000, 95% confidence 1.000; Table 1). The definitiveness of this result stands out, especially with regard to , because the pathology of mice is known to be subtle in the early weeks of life.29, 33, 34, 35
To examine the applicability of SPQ scoring in monitoring muscle healing after damage, we analyzed the alteration of sarcomere pattern associated with reloading of HLS-atrophied muscles. Two days of recovery did not change the cross-sectional diameter of muscle fibers in the gastocnemius (Fig. 3), and has been shown in the literature to yield no improvement in either muscle mass or bone mineral density in adult C57BL6 mice (Ref. 36 and our own unpublished data). Nonetheless, we found a clear improvement of muscle SPQ values within hindlimb-reloaded muscle tissue imaged by SHG. In fact, recuperation of pattern within just two days of reloading was sufficient to reliably segregate recovering animals from the fully atrophic (ROC AUC 0.866, 95% confidence 0.799 in the trivariate regression model), and recovering limbs were actually more accurately discerned from HLS-atrophy specimens than from controls (Table 1). This result is remarkable, for it reveals both the speed of contractile adaptation to newly regained mobility and the sensitivity of SHG/SPQ to the early onset of musculoskeletal remodeling during physiological recovery from disease.
SPQ of Changes in Human Aging
To consider whether these methods were also applicable in human muscle, and to ask if SPQ would correlate with functional performance, we recruited groups of unrelated young adult and elderly volunteers who underwent tests of physical performance and provided a needle biopsy of the quadriceps muscle, vastus lateralis. We acquired SHG images and calculated SPQ values from each of the biopsies. As was seen for mice, SPQ appeared to efficiently resolve specimens from the young and old groups, even by univariate analysis of individual scores [ROC AUC values , , ; see Fig. 5b ]. Small sample sizes for this study led to decreased lower bounds for confidence in ROC analysis of any of these individual scores. However, we found for human specimens that bivariate and trivariate logistic regression (combining FNH, MNHL, and/or ML) substantially improved the impact of SPQ scoring, to quite closely parallel the results seen for aging in mice [Fig. 5c].
Three major conclusions arise from these studies that should impact the future of high-resolution imaging in the assessment of striated muscle disease. First, striation pattern is generally indicative of a broad range of muscle disease. Second, these changes in striation pattern can be quantified automatically to yield statistically powerful measures of muscle health. Third, endogenous SHG offers a means to extract these quantifiable patterns as high-contrast images from muscle tissue in its native state or in vivo.
The periodic structure of contractile machinery lies at the core of muscle function, and this assembly depends upon continual signaling, gene regulation, and biomechanical feedback. We found that three different disorders leading to loss of muscle performance were detectable by SPQ analysis, and quantifiable in their progression, even though none of their etiologies involves a primary molecular defect within the contractile apparatus. Thus, other deficits in muscle homeostasis or function will likely be amenable to SPQ, including neuropathies and cachexia secondary to cancer.3, 37, 38 The SPQ algorithm automatically extracts multiple measured variables from the striation pattern and allows one to transition from raw image to statistical analysis between subjects in a way that can be completely independent of operator judgment or bias. In this study, we analyzed the correlation of a number of SPQ variables (and combinations thereof) with muscle disease. From our current experience, sarcomere length gives the most robust quantification of progression from healthy to mild to severe disease. Why all three disorders studied manifest hypercontraction of sarcomeres is not certain, although dystrophin/utrophin deficiency is known to disrupt myofibril interaction with the cell cortex and to accelerate leakage of calcium into myofibers,39, 40, 41 and it is possible that similar effects are wrought by atrophy and sarcopenia. Nevertheless, this relatively subtle change in banding pattern was the most informative distinction between healthy and compromised muscle, apparently more sensitive than measurements of myofiber or tissue morphology or overt disruptions of the contractile lattice. It is known that muscles change their fiber-type composition in response to some of the disease conditions that we have observed here,42, 43, 44, 45, 46, 47 and such changes might possibly affect our measurements. However, we have examined the sarcomere pattern in muscles with varying proportions of different fiber types, as well as in mice where fiber types are marked by contrasting fluorescent reporter genes, and have not noted any distinctions between the striation patterns of different muscle fiber types (data not shown). We believe, based on these observations, that changes in fiber type probably do not alter the sarcomere length distributions that we have measured. Whatever may be the cause of the sarcomere-shortening effect that we have detected, a relationship between sarcomere length and contraction strength has been well documented,48, 49, 50 suggesting that the loss of performance in muscular disorders may be linked to such structural changes within the cells.
Many mathematical approaches can be applied to texture and pattern analysis in images. The Helmholtz equation works especially well in the context of sarcomeric banding, because the pattern so closely approximates a sine wave in one direction and is uniform in the orthogonal direction. Our analysis method specifically seeks such patterns and identifies the direction and period of the sine wave. In this instance, Helmholtz analysis is more effective than other methods, such as Fourier and wavelet analysis, that decompose the pattern into a sum of waves of predetermined spatial frequencies and orientations, none of which may exactly match the pattern of the image. Already, we have found that Helmholtz approximation yields greater than a 10-fold improvement in pattern-detection sensitivity over an application of 2D wavelet analysis that we have used previously51 (data not shown). Interestingly, efforts at combining measures of sarcomere length with both the angle and SHG intensity of individual striations in a multivariate treatment of the image pattern [an approach designed to capitalize on all of the variables portrayed in Fig. 2a] failed under ROC analysis to equal the power of the approach to SPQ that we have employed here: multivariate logistic regression focused on specific regions of the distribution of sarcomere length alone.
Further improvements upon the performance achieved in this study are still likely, through continued refinement of SPQ algorithms. For example, we have attempted to differentiate muscle biopsies from adult human volunteers diagnosed as normal versus intermediate-frail by Fried’s criteria for frailty.52 Unfortunately, SPQ analyses have not yielded a notable discrimination between two groups of these classes (five and six patients in each group; ROC AUCs: , , ). Similarly, we have not achieved high-quality ROC distinctions between pairs of several of the MD states that we have analyzed: e.g., vs. (ROC AUCs: , , ), or HLS vs. -old mice (ROC AUCs: , , ). Beyond the elementary level of analysis that we have explored in this paper, more diagnostic potential should result from spatial-distribution analysis of abnormal regions throughout the volume of tissue,53 possibly allowing distinction among different etiologies of disease.
Our assessment of the Helmholtz approach also defines some criteria for the design of imaging systems used for capturing sarcomere pattern. As discussed in Section 4, the image magnification and signal-to-noise ratio in our current images approach the lower limits at which this analysis works efficiently. Reducing image noise could allow for some decrease in magnification, and therefore measurement of more sarcomeres per image. Alternatively, lower noise at the current magnification could allow more detailed analysis of subpopulations of hypercontracted sarcomeres.
While SPQ can be applied to any imaging regime that highlights sarcomere striations, the advantages of SHG contrast make it an especially strong choice for future diagnostic muscle imaging.19 Reports from several labs have used precise morphometric, polarization anisotropy, biochemical, and genetic methods to show that SHG arises from the myosin thick filaments of sarcomeres.16, 18, 19, 20, 21, 22 Intrinsic SHG from myosin harmonophores can be elicited and imaged in living tissue without dyes, and the deep sectioning of SHG imaging yields the equivalent of hundreds of serial histological sections within each spatially unified image volume of tissue. In our work, and in principle within a pathology laboratory, SHG imaging can be done immediately following biopsy collection, and pattern analysis is completed the same day. With a continuation of recent advances in microendoscopy, employing SHG-compatible GRIN lens technology,23, 24, 25, 26 imaging of sarcomere patterns will likely become possible in the tissue of live patients without removing biopsies. Streamlining of automated SPQ algorithms should then allow real-time quantification of myocyte health in the clinic and provide a rapid and unbiased tool for assessing diagnosis and prognosis in a wide range of muscular and myocardial disorders.
Animal Models of Atrophy, Dystrophy, and Sarcopenia
Muscle atrophy was induced in -old C57BL6 mice by a course of HLS, as described in the following section. HLS in both mice and rats has been shown to result in substantial atrophy of both muscle and bone within the hind legs during this time span. Returning animals to walking on all fours induces a recovery of muscle force, mass, and fiber size, as well as bone mass recovery, at a rate that is comparable to or slower than the initial rate of atrophy. 42, 43, 44, 54, 55, 56, 57, 58 Mice of the genotype lack functional dystrophin protein and show continual necrosis and regeneration of muscle fibers starting at about of age and extending throughout the full course of life.33, 34, 35, 39 Yet animals show normal muscle strength through much of life and can achieve close to 80% of the life spans of controls.60, 61 In contrast, mice, which lack both dystrophin and the paralogous protein utrophin, display much more rapid incidence of muscle fiber damage and have a maximum lifespan of .29 Sarcopenia, the progressive loss of muscle mass and strength with aging, has been found to affect animals across many phyla. To evaluate the effectiveness of SHG imaging in recognizing sarcopenic changes in the mouse, we examined muscle from mice at mid-adulthood ( old) and at an advanced age close to the average lifespan of the wild type.60 All animal protocols were approved by the Animal Care and Use Committee of the University of Connecticut Health Center (UCHC), Farmington, CT.
Hindlimb suspension (HLS) protocol
Cages for hindlimb suspension (HLS) of mice were constructed based on the standard HLS cage design for unloading hindlimbs of rats.62, 63 In addition to miniaturizing components, modifications included suspending the mice from a lightweight roller ball carriage, comprising two spherical polymer balls rolling on twin rails, that allowed the suspended mice to walk freely around in the rat-sized wire bottom cages.
Six-month-old C57B1/6 females were used. Mice were moved into HLS cages (one mouse per cage) two days before suspension and tails were taped one day before suspension to allow mice to become acclimated to tape. Mice were suspended for . Control mice, and those released from HLS for recovery, resided in normal mouse cages. During this protocol, all mice were housed in a room in which the ambient temperature was maintained at . Mice had free access to regular food and water. Body weights and behavior were monitored daily during suspension. Mice of three different groups were sacrificed for imaging of muscle from the gastrocnemius of each hind leg: control ( mice, 14 muscle samples, 119 image stacks analyzed); mice suspended for and sacrificed without return to normal walking (“HLS;” mice, 12 muscle samples, 89 image stacks analyzed); and mice suspended for and then released for of normal walking (“reload;” mice, 10 muscle samples, 66 image stacks analyzed).
Breeding of dystrophic mouse models, and
Founders for the dystrophy model breeding breeding colony were kindly provided by Dr. Melissa Spencer (UCLA). Initial crosses of donated females were mated to males ordered from the Jackson Laboratory (Bar Harbor, ME) and rederivation of embryos was carried out by staff of the Center for Laboratory Animal Care and the Gene Targeting and Transgenic Facility at UConn Health Center. Genotypes of progeny were determined in each litter by PCR and/or sequencing.28, 29, 59 Five-week-old mice, both male and female, of three different genotypes were sacrificed for imaging of muscle from the gasrocnemius of each hind leg: wild-type C57Bl/6 ( mice, 12 muscle samples, 128 image stacks analyzed); single-mutant ( mice, 16 muscle samples, 101 image stacks analyzed); and double-mutant ( mice, 14 muscle samples, 42 image stacks analyzed).
Adult and aged mice
For aging studies, 10- and -old C57BL6 males raised at Harlan, Inc. (Indianapolis, IN) were purchased through the National Institute on Aging. The animals were received and housed for acclimatization before each imaging experiment. Animals of two groups were sacrificed for imaging of muscle from the gastrocnemius of each hind leg: -old C57Bl/6 ( mice, 10 muscle samples, 89 image stacks analyzed); and -old C57Bl/6 ( mice, 20 muscle samples, 192 image stacks analyzed).
Mouse muscle samples
Mice were sacrificed by narcosis, and lower hindlimbs were removed and skinned for dissection. Small specimens of muscle were dissected from the gastrocnemius using the cutting blade of a skeletal muscle biopsy needle (Popper & Sons Inc.) and briefly washed in ice-cold phosphate buffered saline (Invitrogen). Adipose and connective tissue were removed by scalpel under a dissecting microscope, and trimmed samples were stored in optical clearing buffer containing 50% glycerol at until imaging. Optical clearing yields more than a two-fold increase in SHG image contrast for deep optical sections in muscle tissue and substantially diminishes SHG from collagen fibrils within muscle. Previous work has shown virtually no effect of glycerol upon myosin assembly, enzymatic activity, or sarcomere pattern.51, 64, 65, 66, 67
Human patient biopsy samples
Fifteen patient volunteers were recruited for muscle biopsy. Four young (age ) and 11 elderly subjects (age and older; average age ) were free of physical disabilities, metastatic cancer, and medication known to affect muscle health. The skin and subcutaneous layer surrounding the biopsy area were anesthetized with 1% lidocaine (Elkins-Sinn, Cherry Hill, NJ), a small incision was made, and a deep-muscle biopsy was taken from the lateral portion of the vastus lateralis ( above the knee) using a Bergström cannula biopsy needle (Depuy Orthopedics, Warsaw, IN) with suction. The tissue sample was immediately trimmed of any visible fat or connective tissue and mounted on the microscope slide in cold sterile saline solution. SHG imaging began within of sampling. The numbers of image stacks collected from the young and elderly groups were 22 and 39, respectively. The protocol for this study was approved by the Institutional Review Board of the University of Connecticut Health Center (UCHC), Farmington, CT.
SHG microscope setup and imaging conditions
All SHG experiments used a nonlinear optical imaging system described previously:18 an Olympus BX61WI upright microscope equipped with a FluoView 300 (Olympus USA) scanning head and Mira 900 Ti-sapphire laser pumped by a , Verdi (Coherent). The laser was tuned at , and average power at the sample plane was adjusted to , depending on the sample thickness. A long working-distance 40X, 0.8 N.A. water immersion objective lens and a 0.9 N.A. dry condenser (Olympus USA) were used for excitation and forward-propagating signal collection, respectively. The SHG signal was reflected with a hard reflector (TLM2; bandwidth ; CVI Laser), isolated from the laser fundamental and any fluorescence by a bandpass filter ( FWHM, CVI Laser), and detected by a photon-counting photomultiplier module (Hamamatsu 7421, Bridgewater, NJ). Three-dimensional stacks containing up to 150 optical sections at increments were acquired at slow scan speed ( image; ) with a resolution of .
Sarcomere pattern quantification (SPQ)
Computed analysis of sarcomere pattern was performed on SHG image stacks using a custom-designed plug-in collection within the Java-based program ImageJ (http://rsb.info.nih.gov/ij). This MuscleTone package quantifies the tonal component of sarcomere pattern by using the 2D Helmholtz equation to estimate the square of the wavenumber on a pixel-by-pixel basis according to , where is the pixel intensity. The mean and the variance of the estimate for the wavelength (i.e., sarcomere length), , are computed over a small neighborhood of each pixel. If the variance falls below a threshold, then the sarcomere length for that pixel is taken as the mean wavelength. MuscleTone computes image maps of the following parameters for the neighborhood of every pixel of the raw image: average pixel intensity, sarcomere length, and striation angle (angle between A-bands and the long axis of the myofiber, assumed to be 90° for the ideal case). The striation angle is estimated by averaging from over the pixel neighborhoods. Images were processed in three spatial frequency bands spanning a range of expected wavelengths between 4 and . The radius of the averaging neighborhood for each band was taken as 125% of the upper wavelength limit of that band (up to ). The results for the various bands were combined by selecting the band giving the smallest standard deviation of the computed wavelength for each pixel. The maximum standard deviations allowed for assigning a nonzero score were and 50° for and , respectively. The accuracy of this algorithm and its sensitivity to noise were tested with computer-generated chirped sinusoidal patterns convolved with a level of random noise similar to that in our SHG images, and reliable measurements were obtained for sarcomere lengths of . This range encompasses the majority of sarcomeres in normal muscle samples.51 Sarcomere length distributions were extracted from the generated maps with the ImageJ histogram tool.
In order to further streamline use of the MuscleTone algorithm on images randomly oriented in the -plane, the following method was used to automatically determine the angle perpendicular to the long axis of muscle fibers within the sample. A Gaussian filter with a radius equal to the upper wavelength limit was applied to each slice of the stack. The filtered image was thresholded, using ImageJ’s auto-threshold function to set the limits for the conversion to a binary intensity scale. Finally, the Find Edges filter of ImageJ was applied, and a Radon transform calculation was used to find the angle in the -plane with the largest variance along a projection. All sarcomere lengths and striation angles were then determined, as described above, relative to this cross-fiber axis, .
ROC Analysis and Bootstrapped Estimation of Error
The receiver operating characteristic curve compares the sensitivity and specificity of a classifier system as the threshold for discrimination is varied, indicating the true-positive and false-positive rates for classification of members of two distinct groups.30, 31, 32 A test with no power in distinguishing between two groups yields a value of 0.5 for the area under the ROC curve (AUC), while a perfect classifier yields 1.0 for the ROC AUC. We calculated ROC curves and AUC values for primary data using STATA and Microsoft Excel. For estimation of error from our relatively small samples (and taking into account dependencies between image volumes from the same animal/patient, leg, or biopsy), we generated 1,000 model data sets for each class of specimen by bootstrap selection of data points with replacement, using custom-written C++ code. Logistic regression models were generated and ROC curve errors were calculated from the bootstrapped data sets using STATA.
Mouse mobility performance testing
These studies were studies were conducted using a Rotamex RotaRod instrument from Columbus Instruments (Columbus, OH). The testing protocol was designed in order to reliably diagnose the presence of declines in mobility and endurance in mice. Following a brief warm-up session (a linear acceleration from performed over ), each animal underwent five consecutive increasingly challenging trials, each lasting . Trial 1 began at and accelerated to , trials 2–3 began at and accelerated to , while trials 4–5 began at and accelerated to . Testing sessions were standardized in terms of time of day, room, and study investigator. Results were analyzed using a repeated-measures ANOVA, allowing for the examination of both between-group effects and within-subject effects. A full model allowed for a simultaneous examination of between-group and within-subject effects.
Body composition and bone mineral density of mice
Body composition was determined using peripheral dual-energy X-ray absorptiometry (pDXA; PIXImus II; GE-Lunar Corp., Madison, WI). Prior to each series of scans, a tissue calibration scan was performed using the manufacturer’s provided phantom. Mice were anesthetized using 2.5% Isoflurane (IsoFlo; Abbott Laboratories, North Chicago, IL) mixed with oxygen for a period of , including induction and scanning. The mice were then placed in the prone position on a specimen tray and scanned. The head was excluded from total body scans. Information was provided on fat, lean body mass, and bone mineral density involving total body, as well as femoral diaphysis. HLS mice were measured initially after taping the tails, but before suspension, and again at the end of the period of hindlimb suspension.
We thank Melissa Spencer for providing founder mice and George Keech and the staff of the Center for Laboratory Animal Care for assistance in establishing the mouse colony, and to John Crabbe for advice on rotarod experiments. Sierra Root helped with SHG imaging, Ariel Isaacson and Vaibhav Juneja assisted with work on image-pattern analysis, and Ion Moraru and Jeffrey Dutton helped with data storage and management. This study was supported by grants from the American Heart Association (S.V.P.), the National Science Foundation and Ellison Medical Foundation (W.A.M.), NIBIB (EB001842 to P.J.C. and W.A.M.), NIAMS (AR47673 to C.P.), the TRIHPA endowment and General Clinical Research Center program (MO1-RR06192 to C.J.), the Travelers Chair in Geriatrics and Gerontology and NIA (AR54713 to G.A.K.), and the American Federation for Aging Research (B.Z.).