Video analysis of standing — an alternative footprint analysis to assess functional loss following injury to the rat sciatic nerve

Video analysis of standing — an alternative footprint analysis to assess functional loss following injury to the rat sciatic nerve

Journal of Neuroscience Methods 102 (2000) 109 – 116 www.elsevier.com/locate/jneumeth Video analysis of standing — an alternative footprint analysis ...

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Journal of Neuroscience Methods 102 (2000) 109 – 116 www.elsevier.com/locate/jneumeth

Video analysis of standing — an alternative footprint analysis to assess functional loss following injury to the rat sciatic nerve Marijan Bervar * Department for Plastic and Reconstructi6e Surgery, Maribor General Hospital, Ljubljanska ul. 5, Maribor 2000, Slo6enia Received 7 February 2000; received in revised form 7 July 2000; accepted 7 July 2000

Abstract The rat sciatic nerve is a well-established animal model for the study of recovery from peripheral nerve injuries. Footprint analysis is the most widely used non-invasive method of measuring functional recovery after injury in this model. We describe a new alternative video analysis of standing (or static footprint video analysis) to assess functional loss following injury to the rat sciatic nerve, during animal standing or periodic rest on a flat transparent surface. We found good correlation between video recording during standing and dynamic ink track footprint parameter measurements for both 1 – 5 and injured 2 – 4 toe spreads only. Reproducibility for these three parameters was also better using the video method. Uninjured 2 – 4 toe spread by video showed a poor correlation and similar reproducibility as compared with ink. However, both print length parameters measured by video had poorer correlation and greater variability, particularly the print length factor (PLF) was weakly correlated with that determined by ink. Contribution of the footprint factors on the estimated functional loss has also changed in conditions during standing. It was most prominent for the 1–5 toe spread factor (TSF), near marginal for the 2 – 4 or intermediary toe spread factor (ITF), and weak, statistically insignificant for the PLF. Thus, the introduction of a new functional loss index, or so-called static sciatic index (SSI), and its estimating formula was mandatory. Moreover, using a simple ratio of injured/uninjured 1 – 5 video toe spread as a substitute for the SSI, we could achieve considerable simplification of the method without any significant loss of accuracy. Our video analysis of standing is technically easier to perform than the corresponding footprint video analysis during walking, but still preserves all advantages of video versus conventional ink track method, i.e. there are few non-measurable footprints, better repeatability, high accuracy and more precise quantification of the degree of functional loss after sciatic nerve injury in the rat. © 2000 Elsevier Science B.V. All rights reserved. Keywords: Peripheral nerve; Nerve injury; Nerve regeneration; Functional recovery

1. Introduction Characteristic gait changes occur after unilateral sciatic nerve injury in rats. Gradual disappearance of these changes in time reflects nerve regeneration and functional recovery. The degree of functional loss (or recovery) can be quantified by the method known as footprint analysis (DeMedinaceli et al., 1982). The method is simple, non-invasive and has been shown to measure a combination of motor and sensory recovery. It can be used repeatedly to measure functional recovery over time in the same animal.

* Corresponding author. Tel.: +386-2-3211000; fax: + 386-23312393.

Since its introduction, it has been modified several times. The latest modification (Bain et al., 1989) showed that there are only three parameters of the rat hind limb footprints with significant correlation to the degree of functional loss, the print length, the 1–5 and the 2–4 (intermediary) toe spread. The print length and 1–5 toe spread depend on contributions from both tibial and peroneal divisions of the sciatic nerve. The 2–4 toe spread is dependent on the tibial division alone. By comparing these parameters from prints of the injured and uninjured hind limb, one can express the degree of functional loss by a sciatic functional index (SFI) for total sciatic nerve lesions, or by a tibial functional index (TFI) and peroneal functional index (PFI) for selective lesions of the particular nerve division.

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Fig. 1. Frequent animal rest pose in the glass-bottomed box.

Several different techniques have been developed to obtain appropriate rat hind limb footprints. DeMedinaceli et al. (1982) used ink for staining the feet and allowed the animal to walk in a proper walkway across white paper. Others used water on the feet and a special moisture-sensitive paper (Lowden et al., 1988), or thickened developer and a radiographic film in a darkened walkway (Bain et al., 1989). Introduction of the video imaging technique to record the footprints was a con-

siderable advancement in this field (Lin et al., 1992). It allowed digital analysis of the video images and better repeatability. It significantly diminished the number of useless footprints and minimised printing errors in comparison with previous methods. Correlation of the footprint parameters determined by video and ink technique was good, except for the print length parameter. Consequently, the calculation of the SFI by video was no longer appropriate (Walker et al., 1994). The authors recommended that a simple ratio of injured/uninjured hind foot, 1–5 toe spread as measured by video, might be a more reliable and repeatable measure of functional loss after sciatic nerve injury. Our long-term observations of the rat hind limb footprints on the video images after different kinds of sciatic nerve injuries convinced us that characteristic and visually very similar changes of footprint parameters in time appear not only in dynamic (during walking), but also in static conditions (during standing or periodic animal rest on the same surface). We, therefore, decided to examine whether it was possible to assess the functional loss and recovery after sciatic nerve injury in rat by technically more easily performed static measurements. We also wanted to determine if this alternative video footprint analysis was as accurate and repeatable as the dynamic ink footprint analysis.

Fig. 2. Video equipment set-up.

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2. Materials and methods

2.1. Animals Twenty-four adult male white Wistar A rats weighing 250–350 g were used. All the animals were housed in beta-chip-lined cages, two animals per cage, and were allowed normal cage activities under standard laboratory conditions. The animals were fed Knapka’s rat chow and water ad libitum.

2.2. Surgical procedure Under intraperitoneal anaesthesia (Ketamine 9 mg/ 100 g, Rompun 1.25 mg/100 g, Atropine 0.025 mg/100 g body weight), we exposed the sciatic nerve unilaterally through a biceps muscle splitting incision in the posterior thigh. After nerve mobilisation, two types of e injuries were performed, i.e. a crush injury (axonotmesis, n= 12) and a transection injury (neurotmesis, n= 12). The level of injury was as low as possible, in general, just above the terminal nerve ramification. Crush lesions were performed using special modified pliers to prevent cutting when applied for 10 s. Transection lesions were performed using straight microsurgical scissors, and immediate epifascicular epineural coaptation was done with 10/0 prolene sutures under magnification. Opposite leg and sciatic nerve were not operated upon and served as a control. Fig. 3. View from below. Without any additional contrasting, the pale skin discoloured areas at the points of the hind feet contact with the transparent glass surface are clearly visible. Note the differences of the foot posture and the particular footprint parameters between uninjured right and injured left hind limb.

2.3. Functional assessment Functional recovery after the sciatic nerve injury was assessed serially using video recording of the plantar aspect of the animal hind feet during occasional rest periods in a glass-bottomed box measuring 25×16×9 cm (Fig. 1). For recording, we used a JVC VHS HQ video camera, model GR-45, connected to the colour

Table 1 Regression analysis of ink versus video measurements of particular footprint parameters and calculated ratios Parameter measured

Degrees of freedom (df)

Correlation coefficient (R)a

Standard error (S.E.)

Significance level (P-value)

1–5 Toe spread (TS) Uninjured hind foot Injured hind foot Calculated ratiob

198 198 198

0.6761 0.9690 0.9407

4.4825 3.1060 0.0913

PB0.0001 PB0.0001 PB0.0001

2–4 Toe spread (IT) Uninjured hind foot Injured hind foot Calculated ratiob

198 198 198

0.3530 0.9584 0.8246

3.9173 1.4327 0.1175

PB0.0001 PB0.0001 PB0.0001

Print length (PL) Uninjured hind foot Injured hind foot Calculated ratiob

198 198 198

−0.4893 −0.2698 −0.0571

6.0281 9.8573 0.0796

PB0.0001 P =0.0001 P =0.4223

a b

N= 200 pairs of measurements. Critical value of the correlation coefficient, R(198,0.01) =0.1818. Calculated ratio = (injured−uninjured)/uninjured hind foot, or TSF, ITF and PLF, respectively.

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Table 2 Reproducibility of footprint parameters (same animal, same day)a Parameter measured

Degrees of freedom (df, 1.2)

Average coefficient of variation in % (video)b

Average coefficient of variation in % (ink)

Most repeatable technique (P-value)

1–5 Toe spread (TS) Uninjured hind foot Injured hind foot

1.398 1.398

5.8 9.1

6.7 12.0

Video (P= 0.0015) Video (P=0.0001)

2–4 Toe spread (IT) Uninjured hind foot Injured hind foot

1.398 1.398

8.6 10.9

9.5 12.5

None (P =0.0337) Video (P=0.0047)

Print length (PL) Uninjured hind foot Injured hind foot

1.398 1.398

3.7 4.2

2.8 2.9

a b

Ink (PB0.0001) Ink (PB0.0001)

ANOVA. N= 200 animal days. Coefficient of variation = S.D./mean in %.

Table 3 Evaluation of influence of particular footprint factors PLF, TSF and ITF on functional loss SFI by regression t a-statistics Multiple linear regression statistics: N = 200, R= 0.9380, Rsquare =0.8798, S.E. =9.8218, F=478.5671, PB0.0001 Determined footprint factor

Degrees of freedom (df)

Regression statistics (t b)

Significance level (P-value)

PLF TSF ITF

196 196 196

0.964 12.080 2.745

P =0.3362 PB0.0001 P =0.0066

a b

Critical value, t(196,0.01) = 2.601. t =bi/S.E. (bi), where bi and S.E. (bi) are regression coefficients and their estimated S.E., respectively.

TV set as a monitor via commercial video cassette recorder with super-still advance playback mode (National NV-L15EN). The video camera was placed underneath the transparent bottom of the box at a distance of 20 cm from the objective lens, set at focal length of 9 mm. No additional contrasting was necessary, except for two 100 W sources for oblique lighting on both sides of the video camera (Fig. 2). Under such conditions, the positions of the toes and the sole pale skin discoloured areas, caused by spontaneous body weight pressure, were clearly visible in most instances in the footprints during the video tape playback in super-still mode (Fig. 3). The distance between the tip of the third toe and the most posterior margin of the sole discoloured area was defined as the print length parameter on the video images. All video recordings were performed under similar conditions concerning time, light, animal’s biorhythm and human activity patterns. We paid special attention to minimise any unnecessary stress to the animals in order to avoid its possible effects on the postural muscle tone. A tested animal was put into the box gently

and freely, and was left there at least 5 min to adapt to a new environment before recording. During the recording itself, any further mechanical, acoustic or visual irritation, including observer’s movements and manipulations, was avoided as much as possible. The recordings were taken only by day in a darkened room with artificial light coming solely from below. The other animals waited for testing in the next-door room under normal conditions. A single recording of each animal lasted approximately 60 s. Video assessment of the hind footprints was obtained twice preoperatively and on post-injury days 1, 7, 14, 17, 21, 24, 28, 35 and 42 for crush injuries, and on post-injury-days 1, 21, 45, 75, 105, 135 and 165 for transection injuries. On the same days, after an appropriate delay providing time for animal’s rest from previous video testing, assessment of the hind footprints was obtained by applying a quick-drying non-toxic water-soluble ink to both hind feet and allowing the animal to walk freely down the 54× 8.5× 22 cm walled walkway, leaving tracks on the underlying paper.

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The parameters of print length, 1 – 5 toe spread and 2 – 4 toe spread of four injured and four uninjured hind footprints, were measured manually by a pair of compasses and a ruler from both the video recordings and the ink tracks of each animal on each assessment day. The measurements from these four footprints were averaged to determine the parameter values, their standard deviations and coefficients of variation for that day. Ratios of (injured – uninjured)/uninjured hind feet parameters (or factors — print length factor (PLF), 1 – 5 toe spread factor (TSF) and intermediary toe spread factor (ITF)) were determined by both static video and dynamic ink track method. The latter was used for assessment of the functional loss by SFI, as described by Bain et al. (1989). All measurements were made by a single observer who had previously obtained a normal Z score on the self-evaluation test (Brown et al., 1989).

2.4. Statistical analysis The statistical analysis was performed in four steps. First, we assessed the correlation between particular footprint parameters and their calculated ratios or footprint factors. Regression analysis was performed pair-

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ing the values determined by dynamic ink track and static video methods. Precision between the two methods was compared using coefficients of variation (S.D./mean) for each individual animal, on injured and uninjured feet. These coefficients were analysed by an ANOVA to examine between animal and across recovery time variability. Second, for all the animals during the observation time, we evaluated the influence of particular factors, PLF, TSF and ITF, determined by the static video method on estimated functional loss SFI, determined by the dynamic ink track method. Multiple linear regression analysis was performed and all factors, whose contribution assessed by regression t-statistics was not significant, have been excluded from further analysis. Thirdly, we found the appropriate formula to assess a functional loss in static conditions. We changed the term SFI to static sciatic index (SSI) with only formal intention to distinguish between functional losses determined in static and those in dynamic conditions. Multiple linear regression analysis was performed utilising 96 video assessments, 48 accomplished preoperatively, where functional loss SSI as dependent variable was defined as 0, and 48 accomplished postoperatively (post-injury days 1, 7 for crush injuries; post-injury

Fig. 4. Comparison of the recovery patterns determined by the video 1 – 5 toe spread, the static video and the ink track method after a sciatic nerve transection injury. Note: error bars represent inter-animal variation (S.D.) in response to the injury.

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Fig. 5. Comparison of the recovery patterns determined by the video 1 – 5 toe spread, the static video and the ink track method after a sciatic nerve crush injury. Note: error bars represent inter-animal variation (S.D.) in response to the injury. Table 4 Regression analysis of static video vs. dynamic ink track method (intra-animal)a Method

Static video vs. ink track Video 1–5 toe spread vs. ink track Static video vs. video 1–5 toe spread a

Degrees of freedom (df) 198 198 198

Correlation coefficient (R)

Standard error (S.E.) Significance level (P-value)

0.9378 0.9343 0.9968

9.7983 10.0457 2.1444

PB0.0001 PB0.0001 PB0.0001

N= 200 pairs of estimations. Critical value of the correlation coefficient, R(198,0.01) =0.1818.

days 1, 21 for transection injuries), where functional loss SSI as dependent variable was defined as −100. Only those video footprint parameters whose contribution to the regression was previously confirmed (see step two) were utilised as independent variables. Finally, we assessed the correlation and accuracy of the static video methods to reproduce the same results of functional loss, as were obtained by the dynamic ink track method. Calculated values for functional loss on each animal on each day were paired and regression analysis was performed. All data were computerised and statistically analysed with the SPSS program. An alpha value of 0.01 was used as an index of statistical significance (two tailed P 5 0.01).

3. Results Using the video technique in static conditions, we were able to collect four complete paired footprints on each animal on all 240 animal days (48 preoperatively and 192 postoperatively). Using the ink track method, 40 of 240 animal days of footprint collection had fewer than four complete paired prints per day. The principal reasons were smeared prints, incomplete toe separation, rotation postures of the paralysed feet and toe contractures. These observations were excluded. The results of intra-animal regression analysis of particular footprint parameters and their calculated ratios (factors) determined in dynamic and static conditions are given in Table 1. There was a good correlation

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between dynamic ink track and static video measurements for both 1– 5 toe spreads and injured 2–4 toe spread. However, uninjured 2 – 4 toe spread and both print length parameters had poorer correlation. The parameter ratios also demonstrated good correlation between the two methods, except for the PLF. The results of the reproducibility analysis are presented in Table 2. There was better reproducibility (significantly smaller coefficients of variation) of both injured and uninjured 1 – 5 toe and injured 2 –4 toe spreads using static video rather than dynamic ink track method. Uninjured 2 – 4 toe spread by video had similar values, as compared with ink. However, there was greater variability of both foot print lengths, as measured by static video than with ink track method. The results of evaluation of the influence of particular factors, PLF, TSF and ITF, determined by static video method on functional loss SFI determined by dynamic ink track method are presented in Table 3. This analysis clearly showed that foot print factors determined by the static video method have different influences on the functional loss SFI, compared with those determined in dynamic conditions. Namely in dynamic conditions, all three factors have statistically significant predictable power (Bain et al., 1989), in contrast to static conditions, where the TSF factor (P B 0.0001) is the most prominent, the ITF factor (P =0.0066) is near marginal, and the PLF factor (P = 0.3362) is weak and statistically insignificant. This factor might be excluded from further procedure. Therefore, it seemed appropriate to introduce a new term, SSI and develop a new formula for assessment of functional loss after sciatic nerve injury in the rat, using only TSF and ITF factors determined by the static video method as independent variables and defined functional loss (0 preoperatively, − 100 postoperatively) as a dependent variable. Multiple linear regression analysis was performed and necessary coefficients were determined, giving the following formula, SSI =108.44 TSF+31.85 ITF −5.49

(1)

The F value of this equation was 563.357, significant at the P B0.0001 level. Moreover, at the first approximation, the ITF factor with near marginal influence on the regression can be neglected and further simplification of a formula achieved. A simple ratio of injured/uninjured hind foot video 1–5 toe spread in %, can be used (Walker et al., 1994). Recovery patterns over time determined by the three methods for the two types of sciatic nerve injuries in the rat are shown in Figs. 4 and 5.

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The results of intra-animal regression analysis to assess the correlation and accuracy of the static video methods to reproduce the same results of functional loss, as were obtained by the dynamic ink track method, are given in Table 4. The regression analysis showed that correlation between the static video methods and dynamic ink track method is very high. The estimated accuracy was not considerably reduced, even if we simplified the procedure by using simple ratio of injured/uninjured video 1–5 hind foot toe spread as a substitute for the SSI.

4. Discussion The toes and the heel position as reflected on the footprints of rats during standing is determined mainly by two opposing forces, body weight and postural muscle tone during standing. The recovery of muscle tone after nerve injury is a constituent part of integral nerve and muscle functional recovery. Thus, theoretically it is not surprising to expect a good correlation between the static and dynamic footprint parameters during the recovery period after peripheral nerve injury. Indeed, we found a good correlation between static and dynamic measurements for injured and uninjured 1–5 toe spread parameters and injured 2–4 toe spread parameter. The correlation for uninjured 2 –4 toe spread parameter was not so good. However, repeatability of the toe spread measurements was always better under static conditions. In contrast, the static injured and uninjured print length parameter measurements displayed poor correlation and lesser repeatability, as compared with dynamic measurements. The position of the toes and the heel on the video recordings were evaluated during standing and this probably involves different neurophysiological mechanism from those effective during walking. The position during standing is mainly dependent upon postural muscle tone while the toe and the heel position during walking depends upon dynamic changes in muscle activity. This might very well be the cause for the poor correlation between the dynamic ink track method and the present static method in regard to the print length parameter. Moreover, determining the most posterior point of the heel contact with the transparent surface is perhaps the most difficult part of the video analysis and is subject to observer’s misinterpretation and unwilling measuring errors. Excessive variability and poor correlation were the main reasons for discarding the PLF from the formula, estimating motor function loss or recovery by the video recording method during standing. Given that our static method measures a specific aspect of sciatic nerve function, it is important to realise that stressful manipulation of the animal during the

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testing might interfere with postural muscle tone and thus influence the toe and the heel position. Standing on a glass plate with intense light coming from below might be some kind of a stress for rats compared to ink smeared under the feet which precedes the recording of footprints for the walking track analysis. The potential users of the static video method should pay attention to this by providing sufficient time between placing the animal in the testing box and the recording, and allowing sufficient rest between the static video and the dynamic ink track procedure. In addition, all other alerting stimuli from the environment should be kept to a minimum. On the other hand, our observations confirmed the fact that the 1–5 toe spread is the most useful parameter for measuring functional recovery after a sciatic nerve injury. It is dependent on anatomic contributions from both the peroneal and tibial divisions of the sciatic nerve (Bain et al., 1989) and, therefore, closely follows the sciatic functional recovery as a whole. This parameter also demonstrates the greatest deviation from the normal of all studied parameters allowing measurement of smaller changes after injury and during recovery. As such, this parameter has the greatest ‘weight’ in all proposed formulas and can be used alone in the form of simple ratio of injured/uninjured hind foot video 1–5 toe spread expressed in % to assess functional loss by the video recording method during standing. We demonstrated that the recovery patterns determined over time by the static and dynamic methods for two types of sciatic nerve injury (crush or transection plus suture) in the rats were generally similar as far as the beginning and the plateau of functional recovery were concerned. Correlation between the video recording method during standing and dynamic ink track method was very good, so the accuracy of assessment of functional loss by these two methods is comparable. Even if we simplify the estimating procedure by using a simple ratio of injured/uninjured video 1 – 5 hind foot toe spread as a substitute for the SSI, accuracy of the assessment does not change considerably. Although our static video footprint analysis requires more expensive technical equipment, we think it has significant advantages in comparison to conventional ink track method, i.e. there are few non-measurable footprints, it displays better repeatability and, therefore, higher accuracy and more precise quantification of the degree of functional loss and recovery after sciatic nerve injury in the rat. Similar conclusions, regarding the usefulness of the footprint video analysis during walking for assessing sciatic nerve functional loss and recovery, were pre-

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sented in the literature (Walker et al., 1994). However, our static footprint video analysis is technically easier to perform than the corresponding dynamic one. No additional contrasting is necessary. Owing to static conditions, the video camera is placed closely to the object of observation which enables better visibility, better discrimination of the toes and more precise estimation of the footprint parameters, except for the print length (see above). Taking into account all necessary precautions during testing, as mentioned above, the static footprint video is a reliable method for quantification of functional loss and recovery after sciatic nerve injury in the rat. It is suitable for studies of different procedures applied to ameliorate the restitution of motor function after peripheral nerve injury.

Acknowledgements The author would like to thank Professor Janez Sketelj, of Institute for Pathophysiology, Ljubljana Medical Faculty, SLO, for his critical review and helpful comment regarding the manuscript; Professor Nada S& abec, of Deprtment of English and American Studies, Maribor Faculty of Education, SLO, for proof reading of the text; Professor Damjan Miklavcˇicˇ, of Laboratory for Biocybernetics, Ljubljana Electrotechnic Faculty, SLO; and Professor Betty F. Sisken, of Center for Biomedical Engineering, University of Kentucky College of Medicine, USA for their unselfish help, advice and encouragement.

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