ArticlePDF Available

3 Dimensional photonic scans for measuring body volume and muscle mass in the standing horse

PLOS
PLOS One
Authors:

Abstract and Figures

Reasons for performing study Although muscle mass strongly influences performance, there is currently no effective means to measure the 3-dimensional muscle mass of horses. We evaluated a 3-dimensional (3D) scanning methodology for its ability to quantify torso and hindquarter volumes as a proxy for regional muscle mass in horses. Objectives Determine the repeatability of 3D scanning volume (V) measurements and their correlation to body weight, estimated body volume and muscle/fat ultrasound (US) depth. Methods Handheld 3D photonic scans were performed on 16 Quarter Horses of known body weight 56 days apart (n = 32 scans) with each scan performed in duplicate (n = 32 replicates). Tail head fat, gluteal and longissimus dorsi muscle depths were measured using US. Processed scans were cropped to isolate hindquarter (above hock, caudal to tuber coxae) and torso (hindquarter plus dorsal thoracolumbar region) segments and algorithms used to calculate V. Torso and hindquarter volume were correlated with body weight and US using Pearson’s correlation and with estimated torso volume (50% body weight / body density) with Bland-Altman analysis. Results Scans took 2 min with < 3.5% error for duplicate scans. Torso volume (R = 0.90, P< 0.001) and hindquarter volume (R = 0.82, P< 0.001) strongly correlated with body weight and estimated BV (R = 0.91) with low bias. Torso volume moderately correlated to mean muscle US depth (R = 0.4, P< 0.05) and tail head fat (R = 0.42, P< 0.01). Mean muscle US depth moderately correlated to body weight (R = 0.50, P< 0.01). Main limitations 3D Scans determine body volume not muscle volume. Conclusions The hand-held 3D scan provided a rapid repeatable assessment of torso and hindquarter volume strongly correlated to body weight and estimated volume. Superimposition of regional scans and volume measures could provide a practical means to follow muscle development when tail head fat depth remain constant.
This content is subject to copyright.
RESEARCH ARTICLE
3 Dimensional photonic scans for measuring
body volume and muscle mass in the
standing horse
Stephanie J. ValbergID
1
*, Amanda K. Borer Matsui
1
, Anna M. Firshman
2
,
Lauren Bookbinder
1
, Scott A. Katzman
3
, Carrie J. Finno
4
1McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, Michigan State
University, East Lansing, MI, United States of America, 2Department of Veterinary Population Medicine,
College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States of America,
3Department of Surgical and Radiological Sciences, University of California Davis, Davis, CA, United States
of America, 4Department of Population Health and Reproduction, University of California Davis, Davis, CA,
United States of America
*valbergs@cvm.msu.edu
Abstract
Reasons for performing study
Although muscle mass strongly influences performance, there is currently no effective
means to measure the 3-dimensional muscle mass of horses. We evaluated a 3-dimen-
sional (3D) scanning methodology for its ability to quantify torso and hindquarter volumes as
a proxy for regional muscle mass in horses.
Objectives
Determine the repeatability of 3D scanning volume (V) measurements and their correlation
to body weight, estimated body volume and muscle/fat ultrasound (US) depth.
Methods
Handheld 3D photonic scans were performed on 16 Quarter Horses of known body weight
56 days apart (n = 32 scans) with each scan performed in duplicate (n = 32 replicates). Tail
head fat, gluteal and longissimus dorsi muscle depths were measured using US. Processed
scans were cropped to isolate hindquarter (above hock, caudal to tuber coxae) and torso
(hindquarter plus dorsal thoracolumbar region) segments and algorithms used to calculate
V. Torso and hindquarter volume were correlated with body weight and US using Pearson’s
correlation and with estimated torso volume (50% body weight / body density) with Bland-
Altman analysis.
Results
Scans took 2 min with <3.5% error for duplicate scans. Torso volume (R = 0.90, P<0.001)
and hindquarter volume (R = 0.82, P<0.001) strongly correlated with body weight and esti-
mated BV (R = 0.91) with low bias. Torso volume moderately correlated to mean muscle US
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 1 / 12
a1111111111
a1111111111
a1111111111
a1111111111
a1111111111
OPEN ACCESS
Citation: Valberg SJ, Borer Matsui AK, Firshman
AM, Bookbinder L, Katzman SA, Finno CJ (2020) 3
Dimensional photonic scans for measuring body
volume and muscle mass in the standing horse.
PLoS ONE 15(2): e0229656. https://doi.org/
10.1371/journal.pone.0229656
Editor: Lisa M. Katz, University College Dublin,
School of Veterinary Medicine, IRELAND
Received: September 18, 2019
Accepted: February 12, 2020
Published: February 27, 2020
Copyright: ©2020 Valberg et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: Endowment of the Mary Anne McPhail
Dressage Chair in Equine Sports Medicine (SJV),
Michigan State University, Freeman Fund for
Equine Research, Michigan State University (SJV)
and University of California Center for Equine
Health (CJF). The funders had no role in study
design, data collection and analysis, decision to
publish, or preparation of the manuscript.
depth (R = 0.4, P<0.05) and tail head fat (R = 0.42, P<0.01). Mean muscle US depth mod-
erately correlated to body weight (R = 0.50, P<0.01).
Main limitations
3D Scans determine body volume not muscle volume.
Conclusions
The hand-held 3D scan provided a rapid repeatable assessment of torso and hindquarter
volume strongly correlated to body weight and estimated volume. Superimposition of
regional scans and volume measures could provide a practical means to follow muscle
development when tail head fat depth remain constant.
Introduction
The volume (V) of the locomotor muscles in terms of number of fibers and their architectural
arrangements exert a profound influence on performance by impacting the power generated
by muscle at varying velocities of shortening [1;2]. In particular, the large proximal pelvic
muscles generate much of the force required for equine athletic performance [1]. Athletic
horses are reported to have greater muscle mass (53–57%) when compared to other horses
(42%) and a larger portion of their overall muscle weight endowed in the propulsive locomotor
muscles of the hindlimb region [3]. Development of specific muscle groups is colloquially
known to be characteristic of specific equine performance types, however, there are few if any
scientific reports documenting gross development of muscle groups critical for particular
equine disciplines (Pub Med and Google Scholar search 01/09/2018)[1].
The paucity of information related to muscle mass and body V in horses is related to the
technical difficulties in measuring these parameters [1;2]. There has been no readily available
mechanism to quantify 3D muscle mass in horses and to follow the changes that occur as
horses progress through training. Conventionally, photographs, body condition scoring and
ultrasonography (US) have been used to as a proxy to assess muscle mass in research studies of
horses [2;4;5]. The subjectivity of body condition scoring and the limited number of muscles
that can be assessed in 2 dimensions with US impede the accurate measurement of muscle
development in the entire body [2;5;6]. Magnetic resonance imaging (MRI) is capable of pro-
viding a 3D assessment of muscle mass, however, it is has not yet been used to report body V
or muscle mass in horses and is neither readily available, nor affordable for routine follow up
[7].
The need for accurate measurements of human body shape and body dimensions for retail
and commercial purposes has resulted in the development of digitized optical methods to gen-
erate 3D photonic images of an individual [811]. Commercial scans use numerous stationary
lasers within a booth to provide 3D body contours of people within a 20 second period [8;11].
Working toward our long term goal of devising a rapid means to accurately assess body V and
muscle development in the horse, we adapted a handheld infrared photonic scanner to pro-
duce a 3D image of a horse [12]. The handheld Optical Structure Sensor Scanner projected a
speckled pattern of invisible infrared light and captured distortions in the projection as a 3D
mesh. Post scan processing algorithms were used to transform the mesh into a solid body
where volumes could be measured.
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 2 / 12
Competing interests: The authors have declared
that no competing interests exist.
We hypothesized that the 3D photonic scan would be highly repeatable and provide a good
correlate to body V in horses. The purpose of the present study was to assess the repeatability
of the developed 3D scanning technique and to determine how well volumetric measures
reflected body weight as well as muscle and fat mass assessed using US. To more specifically
assess muscle V important for propulsion, cropping of scans was performed to isolate regions
such as the hindquarter above the hock and the torso (dorsal thoracolumbar region
+ hindquarter).
Materials and methods
Validation of volume assessment
In order to determine that the 3D scanner accurately assesses volume, two boxes of known
volume (0.0571 m
3
and 0.0213 m
3
) were stacked askew on top of each other to form a more
complex structure and the volume of the combined box structure assessed using the 3 D scan-
ner (S1 Fig). The scanning was repeated 4 times and the percent error calculated for each
assessment.
Horses
Sixteen unfit horses of Quarter Horse-related breeds, 10 mares, 6 geldings, with a mean age of
12.1 ±2.7 years housed at a University facility on dry lots were used in the present study. Body
condition scores (1–9) ranged from 4 to 7 with a mean (SD) of 5.6 ±0.9. Body weights (BW)
were obtained at the time of each body scan. To increase the number of technical scan repli-
cates, the scanning process was repeated on the same 16 horses 56 days apart as part of an
ongoing nutritional study. The research was approved by IACUC at the University of Califor-
nia, Davis and Michigan State University in compliance with the US National Research Coun-
cil’s Guide for the Care and Use of Laboratory Animals, the US Public Health Service’s Policy
on Humane Care and Use of Laboratory Animals, and Guide for the Care and Use of Labora-
tory Animals. The individuals assisting with the research in this manuscript have given written
informed consent (as outlined in PLOS consent form) to publish their images.
Scanning
Procedure
Horses were groomed, the tail was wrapped and 6 cm pieces of white tape partially folded in
half were affixed to the skin at the highest point on the tuber coxae and over the dorsal spinous
process of the most caudal sacral vertebra. A lunging surcingle was fitted into the natural girth
groove to define the cranial margin of the torso (Fig 1A). Xylazine hydrochloride (0.3–0.4 mg/
kg IV) was administered to any horses that were reluctant to stand still. Horses were positioned
so that both forelimbs were square, both hindlimbs were square and all four limbs were placed
naturally underneath the body fully weight bearing. Duplicate scans were performed within
minutes of each other with horses standing in the same squared position. During positioning,
horses were facing one corner diagonally in a 3.7m x 3.7 m stall (Fig 1B). Two mounting blocks
0.45 m in width were placed equidistant between the fore and hindlimbs approximately 1.5–2
m from the horse on the left and right sides (Fig 1A).
An Occipital Structure Sensor (ST01, Occipital, Inc., Boulder, CO) was attached to an iPad
Air 2 (Model A1566, Apple, Cupertino CA) running the Structure application (Structure v1.9,
Occipital Inc, Boulder CO)
2
(Fig 1A). The iPad was then linked via a wireless router (Linksys
E2500, Irvine CA)
3
to a laptop (Dell Precision 7520, 7520, Intel
1
Corei7-7920HQ CPU @
3.10 Gz, 64 GB RAM, Dell, Round Rock, TX,) sitting outside the stall running the scanning
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 3 / 12
program (Skanect Pro v1.9 (Win64, Occipital, San Francisco, CA). The scan was started with
the operator holding the iPad with attached scanner slightly above chest height beginning at
the left front of the horse and progressing caudally at a steady smooth pace (Fig 1B,S1 Video).
The procedure included stepping up and down on the mounting block to scan the dorsal left
torso (Fig 1A), moving from left to right sides behind the horse (Fig 1B), stepping up and
down the mounting block on the right side and finishing at the right shoulder (S1 Video).
Whenever possible while scanning, one of the two mounting blocks or set of hooves were kept
in the scan to facilitate tracking (Fig 1B). Each scan took approximately 2 min. Scans were
stopped, discarded and repeated if the scan lost tracking, if the horse moved during the scan-
ning process or if the left and right halves of the surcingle did not align perfectly over the back
in the scan. On every occasion that a scan was performed, a second scan was obtained to assess
accuracy. The second scan was performed within 15 min of the first complete scan with the
horse again placed in a squared stance with hindlimbs directly underneath the horse. Hind-
quarter and torso V for each horse were comprised of the mean of both scans.
Post-processing of scans
Object files for each scan were exported from Skanect and imported into the Meshmixer pro-
gram (Meshmixer, Version 3.3.15, Autodesk, Inc., San Francisco, CA). The horse’s body was
then isolated in each scan by cropping the handler, walls, mounting block and ground off the
mesh. The horse’s body was then cropped to isolate the ‘torso’. The torso was delineated crani-
ally by the surcingle, and ventrally by a plane drawn parallel to the floor from the junction of
Fig 1. 3D scanning process. A. Positioning of the horse for obtaining a 3D scan using an iPad with occipital structure sensor scanner and surcingle with anatomic
markers. B. Diagonal position of the horse for scanning in a stall and screen view of the scanning image.
https://doi.org/10.1371/journal.pone.0229656.g001
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 4 / 12
the flank and stifle to the surcingle. Cropping of the lower abdomen minimized the volume in
the region of the large colon. The torso included the HQ which was cropped above the point of
the hock with the tail removed if necessary, to assess the full semimembranosus/tendinosus
area (Fig 2A and 2B,S2 Video). The hindquarter sector was isolated by cropping the torso at
markers placed on the highest point of the tuber coxae. The width of the mounting block in
duplicate scans was evaluated as a control object.
Ultrasonography
Horses were restrained in stocks and US was performed by one experienced ultrasonographer
(AMF) using a TeraVet 3000 Ultrasound machine (Teratech Corp, Burlington MA). US was
performed one the same day as scanning was performed. Standard skin preparation consisted
of clipping the hair, cleaning with alcohol and application of US gel.
T18 and L3 lumbar muscles
Left and right lumbar muscles at the level of the 18
th
thoracic vertebrae were found by palpat-
ing the curvature of the 18
th
rib craniodorsally to the point at which it could be palpated con-
necting to the spinal column. Left and right lumbar muscles (longissimus dorsi/ cranial
gluteus medius) at the level of the 3
rd
lumbar vertebra were found by following a line that ran
directly vertical towards midline from the caudal most aspect of the 18
th
rib. For both of these
locations a 5cm square of hair was clipped at the level of T18 and L3, the center of which was
10 cm from the dorsal midline (in the iliocostal muscle groove) (Fig 2C).
A curvilinear probe (Terason 5C2A-Vet Convex 5.0–2.0 MHz) was oriented transversely
following the skin curvature and 3 separate images were captured that depicted the skin sur-
face, longissimus dorsi and margin of the rib or transverse process. Because little subcutaneous
fat was evident, muscle depths were measured from skin surface to the bone margin.
Middle gluteal
The middle gluteal muscle depth was measured on left and right sides at a location equidistant
between the dorsal most aspect of the tuber sacrale and the dorsal most aspect of the tuber
coxae (Fig 2D). A 5 cm square of hair was clipped at the midpoint of this line. The curvilinear
probe was oriented transversely and muscle depth was measured in three separate images
from the skin surface to the fascial plane that separates the gluteal medius’ superficial and deep
(gluteus accessorius) compartments (Fig 2D).
Fat pad
Subcutaneous adipose tissue was measured at a site 5 cm to the left and right of the root of the
tail. A linear 6-MHz probe (Terason 12L5-Vet) was oriented transversely and fat depth was
measured from the skin surface to the ventral limit of the subcutaneous adipose tissue.
Statistical analysis
Scan V and US measurements were tested for normality using D’Agostino & Pearson omnibus
normality test and found to be normally distributed. Mean and standard deviations of scan V,
BW and US depths were calculated. Percent error was calculated for torso V and hindquarter
V by dividing the difference in volume between scan 1 and scan 2 by scan 1 and multiplying
by 100. The coefficient of variations for US measurements were calculated from the 3 measure-
ments of US depth taken for each horse at each site. Pearson’s Correlation coefficients were
calculated to assess relationships among BW, torso V, hindquarter V and US depths. Bland
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 5 / 12
Altman plots were analyzed to compare 3D scan V for torso with estimated V for the torso.
Estimated torso V was calculated as (BW/ (body density X 0.5)), based on the fact that torso V
was approximately ½of the horse’s body V in our preliminary scans of the entire horse. The
value used for body density was approximated from previous lean human and horse references
(1010 kg/m
3
) [2;13;14]. Statistical analyses were performed using GraphPad Prism 7.0
(Graphpad Software, La Jolla, CA).Results with P <0.05 were reported as statistically
significant.
Fig 2. Torso and hindquarter volume cropping and processing of ultrasound images. A. Regions of the body that were cropped (black lines) in order to obtain the torso
volume measurement. The torso was defined as the area caudal to the surcingle above a horizontal plane drawn parallel to the floor from the skin fold at the juncture of the
stifle and flank and included the hindquarters above the point of the hock. B. The 3D image of the body scan of the torso of the horse in A. C. The 3 areas utilized for US
imaging including T18, L3 over the longissimus muscle and middle gluteal muscle. D. US image of the middle gluteal muscle where muscle depth was measured for the
superficial compartment. Arrow indicates fascia separating superficial and deep middle gluteal compartments.
https://doi.org/10.1371/journal.pone.0229656.g002
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 6 / 12
Results
Validation of volume assessment
The known volume of the stacked boxes was 0.07834 m
3
. The mean volume for 4 repeated 3D
scans of the boxes was 0.07667 ±0.0004 m
3
. The mean percent error was 2.1 ±0.56%.
Volume and percent error
Mean torso V was 0.2777 ±0.0229 m
3
and mean estimated torso V was 0.2690 ±0.0241 m
3
.
The mean difference between duplicates was low at 0.0075 ±0.0099 m
3
(CI 0.0051–0.0123)
with little estimated bias indicated by Bland Altman analysis (Fig 3A). There was a high degree
of correlation between torso V and estimated torso V (R = 0.91) (Fig 3B). The error between
scans was low at 3.0 ±2.1% for torso V and 3.5 ±3.3% for hindquarter V. Duplicate measure-
ments of the width of the control object in the scan had an error of 2.6 ±1.9%.
Correlation to body weight
There was a strong positive correlation between torso V and BW (R = 0.91, P<0.0001) as well
as hindquarter V and BW (R = 0.88, P<0.0001) (BW range 450 to 640 kg) (Fig 3C and 3D).
The mean of T18, L3 and gluteal muscle US depth was moderately positively correlated to BW
(R = 0.50, P = 0.004) (Fig 4A). Tail head fat depth was not correlated to body weight (R = 0.18,
P = 0.3).
Scanning volume versus ultrasound depth
The coefficient of variation for US depth at each site ranged from 1.73 to 3.45%, with the low-
est variation found for L3 and gluteal muscle (Table 1). Torso V (R = 0.40, P = 0.02) and hind-
quarter V (R = 0.51, P = 0.002) showed a moderate positive correlation to the mean of T18, L3
and gluteal muscle US depth (Fig 4B and 4C). Gluteal muscle depth had stronger positive cor-
relations to torso V and hindquarter V (Fig 4D and 4E) than T18 (R = 0.12, P = 0.1, hindquar-
ter V, R = 0.30, P = 0.5 Torso V) or L3 muscle depths. Torso V, but not hindquarter V
(R = 0.13, P = 0.5), was moderately correlated to tail head fat (Fig 4F).
Discussion
The present study determined that the hand-held 3D scanning methodology provided a rapid
method to measure torso and hindquarter V in horses with a high degree of repeatability. The
<3.5% error between duplicate scans was similar to errors reported for more expensive sta-
tionary laser 3D scanning used in human studies.[8;11] Scans took approximately 2 min to
perform with horses standing still. The initial challenge in performing scans was to ensure that
the scan maintained tracking throughout. Utilizing a steady pace for movement of the hand-
held scanner around the horse, ensuring objects such as paired hooves or mounting blocks
were always in the scan and using a surcingle to ensure that left and right sides perfectly
aligned were all useful adaptations to ensure high quality scans.
Validation of a new method of measurement requires comparison to the gold standard. In
the case of equine body V, however, there are no previous technologies that have accurately
assessed body V in the horse to the best of our knowledge. In humans, the ‘gold standard’ for
assessing body volume is hydrostatic weighing, which is impractical for horses as it requires
immersion in a water tank.[9;10] Other methods to assess muscle and fat body composition in
humans include dual energy X-ray absorption (DEXA), air displacement, bio-electrical imped-
ance analysis and MRI, however, validated data for these techniques is not available for horses
for comparison.[2;10]
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 7 / 12
In order to determine if our 3D scan V measurements reasonably reflected actual body V,
we first scanned a structure (boxes) of known volume and found the scan provided an accurate
volume assessment with 2% error. Next, we compared measured torso V to a best estimate of
body V calculated as BW divided by body density. Fat tissue (0.90) is less dense than bone,
muscle tissue (1.1 to 1.3) and water (1.0).[15] We utilized an estimated body density from
human studies of 1010 kg/m
3
and preliminary data that showed our torso V represented
approximately 50% of the entire horse’s body V (Fig 2).[13;14] Very small mean differences
between measured torso V and estimated BV were found with mean values differing
by <3.1%. A strong correlation was found between torso V and estimated torso V (R = 0.91).
A Bland Altman analysis demonstrated that the limit of agreement between methods was nar-
row and without bias. In addition, there was a strong positive correlation (R = 0.91) between
BW and both torso V and hindquarter V. Thus, to the best of our abilities, we were able to con-
firm that the handheld 3D infrared scan appears to provide an accurate measure of body V in
horses.
Fig 3. Accuracy of 3D scanning to assess body volume. A. Bland Altman plot comparing the differences between torso V and average of estimated torso
volume (V) with 95% confidence intervals depicted by red dashed lines. Only two of 32 V measures were outside of the 95% confidence limits. B.
Correlation of 3D scan torso V with estimated torso V (R = 0.91). C. Positive correlation of 3D scan torso volume with body weight. D. Positive correlation
of 3D scan hindquarter volume with body weight. �� P<0.001.
https://doi.org/10.1371/journal.pone.0229656.g003
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 8 / 12
As our long term goal is to use 3D Scanning to follow muscle development, we compared
US assessment of muscle mass with BW and body V calculations. Mean values for US assess-
ment of combined lumbar and middle gluteal muscles were moderately correlated to torso V
(accounting for only 16% of variability) and hindquarter V (25% of variability). Mean US
depth was not as strongly correlated to BW (accounting for 25% of the variability) as torso V
(83% of variability) or hindquarter V (77% of variability). This was not an unexpected finding
since US only provides two dimensions of muscle size at a limited site. The advantage of 3D
scanning would appear to be the ability to rapidly capture the full dimension of muscle bulk
compared to US. The advantage of US measurement, however, is that it direct measures skele-
tal muscle depth and excludes subcutaneous fat, bone mass, lung volume, gastrointestinal fill
and potentially hydration status that are incorporated into measures of body V.[2;5;10]
In the present study, 3D scans were cropped in order to focus on the propulsive hindlimb
muscles. The lower abdomen, limbs below the hock, forelimb, head and neck of the horse were
removed from measurements. The stifle fold was used as a readily identifiable plane to crop
Fig 4. Correlation and Pearson’s correlation coefficients. A. Mean US measures of two sites in lumbar muscle and one site over the middle gluteal muscle
compared to body weight. B. Mean US values for the three muscle depths compared to torso V. C. Mean US values for the three muscle depths compared to
hindquarter (HQ) V. D. Positive correlation of middle gluteal ultrasound depth with torso V. E. Positive correlation of middle gluteal ultrasound depth with
HQ V. F. Positive correlation of tail head fat to torso V. P<0.05, �� P<0.01, ��P<0.001.
https://doi.org/10.1371/journal.pone.0229656.g004
Table 1. Mean (SD) ultrasound depths at the sites; T18 and L3 of the left (L) and right (R) longissimus muscles, the middle gluteal muscle and the tail head (fat).
T18 L3 Gluteal Tail head
L R L R L R L R
Depth (cm) 7.59 ±1.13 7.90 ±1.20 9.37 ±1.53 9.63 ±1.27 9.57 ±1.33 9.67 ±1.26 1.70 ±0.56 1.79 ±0.60
CV (%) 3.35 ±2.10 3.24 ±1.98 1.75 ±1.02 1.87 ±1.0 1.73 ±1.01 2.18 ±1.47 3.45 ±2.29 2.83 ±1.89
The coefficient of variation (CV) expressed as a percent was calculated as the SD for 3 measurements at each site divided by the mean depth.
https://doi.org/10.1371/journal.pone.0229656.t001
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 9 / 12
the lower abdomen to minimize the impact of gastrointestinal volume. To further remove an
impact of large intestinal volume, more of the abdomen could be cropped, however, this
would require highly standardized affixed markers to avoid potential variability. Using the
cropping methods in the present study, torso V and hindquarter V were significantly corre-
lated to muscle US depth. Importantly however, the impact of subcutaneous fat on torso V was
readily evident based on significant correlation of torso V to US tail head fat depth.
Fat occupies a disproportionate volume compare to muscle due to its lower density. At
higher body condition scores, body fat deposition increases exponentially, equally distributed
between internal and external sites.[2;6] Both intermuscular and subcutaneous fat deposits
are more strongly correlated to total fat deposits than intraabdominal fat.[6] Thus, compari-
sons of 3D scans for muscle development in an individual horse over time must include a mea-
sure of body fat to ensure that changes in V are not a result of increased fat deposition. We
utilized the tail head region to assess fat depth because there was little observable subcutaneous
fat deposited in the longissimus and gluteal muscles regions evaluated with US. This site had
low coefficient of variation. Other studies have measured B mode fat depth at a site 5 cm lateral
from the midline at the center of the pelvic bone with reported correlation coefficients between
actual and ultrasound-measured rump fat thickness ranging from R
2
= 0.90 to 0.96. [16;17]
The specific site of measurement of fat on the hindquarter should be clearly described as it is
unclear from Westervelt what the center of the pelvic bone specifically represents.[16]
The results of the present study suggest that 3D scanning V could be of great benefit in
assessing athletic horses and are supported by a recent study of 3D scanning used to assess
rowing performance in humans.[18] Overall, studies of rowers found that absolute, rather
than proportional measurements, and 2D and 3D rather than 1D measurements were the best
predictors of rowing ergometry performance, with whole body V and surface area, standing
height, mass and leg length being the strongest individual predictors. In addition, the study
found that scanning was time-efficient and noninvasive, enhancing participation and provid-
ing a historical record of each athlete at a particular point in time that could be reexamined in
the future without the athlete present.[18] All of these are features that would be of value in
assessing equine athletes.
To be clear, the scanning technique used in the present study assesses volume and is not a
direct measure of muscle mass. US depth can be used as a proxy for the mass of specific mus-
cles.[5] US depth, however, was not strongly correlated to hindquarter V and US has the disad-
vantages of variability of measurements between different individuals, time required to US
numerous muscles and the potential need to clip horses.[5] In contrast, a 2 min scan is highly
repeatable, quick and encompasses the entire superficial muscle contour. One could argue that
because body weight was strongly correlated to estimated body volume, body weight could be
used rather than a body scan to estimate volume. An estimated body volume, however, would
not provide a means to assess changes in the volume of specific body regions with training. In
contrast, a scan could be further divided into sectors, such as left versus right hindquarters,
which would provide more specific indications of regional muscle development. Thus, while
US and body weight are currently useful proxies for assessing muscle development, 3 dimen-
sional scanning has the potential to provide additional information on regional muscle
development.
In conclusion, the handheld Occipital Structure Sensor Scanner and post-processing algo-
rithms provided a rapid accurate means to assess body V in horses that was highly propor-
tional to BW. Results suggest it would be feasible to utilize this technology to follow muscle
development of an individual horse over time using cropped scans provided that control mea-
sures are taken to ensure changes in V do not reflect changes in fat deposition, hydration sta-
tus, large intestinal fill, hydration or posture.
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 10 / 12
Supporting information
S1 Fig. Image from the scan of the two boxes used to validate the 3D scanner’s ability to
accurately assess volume.
(TIF)
S1 File. Previous utilization of the scanning technique to assess body volume in the horse.
(PDF)
S1 Video. The procedure for performing a 3D photonic scan. The process begins at the
horse’s right shoulder and finishing at the horse’s left shoulder.
(MP4)
S2 Video. Video depicting the 3D scanned image of the torso from many different angles
after processing and cropping.
(MP4)
Acknowledgments
We are grateful for the technical assistance of Janel Peterson, Erin Burns, Anna Dahlgren and
Brittni Ming-Whitfield.
Author Contributions
Conceptualization: Stephanie J. Valberg, Amanda K. Borer Matsui.
Data curation: Stephanie J. Valberg.
Formal analysis: Amanda K. Borer Matsui.
Funding acquisition: Stephanie J. Valberg.
Investigation: Stephanie J. Valberg, Amanda K. Borer Matsui, Lauren Bookbinder, Scott A.
Katzman, Carrie J. Finno.
Methodology: Stephanie J. Valberg, Amanda K. Borer Matsui, Anna M. Firshman, Lauren
Bookbinder, Scott A. Katzman, Carrie J. Finno.
Project administration: Stephanie J. Valberg, Carrie J. Finno.
Resources: Stephanie J. Valberg.
Supervision: Stephanie J. Valberg, Carrie J. Finno.
Validation: Stephanie J. Valberg, Amanda K. Borer Matsui, Anna M. Firshman.
Writing original draft: Stephanie J. Valberg.
Writing review & editing: Stephanie J. Valberg, Anna M. Firshman, Lauren Bookbinder,
Scott A. Katzman, Carrie J. Finno.
References
1. Payne R.C., Hutchinson J.R., Robilliard J.J., Smith N.C. and Wilson A.M. (2005) Functional specialisa-
tion of pelvic limb anatomy in horses (Equus caballus). J Anat 206, 557–574. https://doi.org/10.1111/j.
1469-7580.2005.00420.x PMID: 15960766
2. Kearns C.F., McKeever K.H. and Abe T. (2002) Overview of horse body composition and muscle archi-
tecture: implications for performance. Vet J 164, 224–234. https://doi.org/10.1053/tvjl.2001.0702
PMID: 12505395
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 11 / 12
3. Gunn, H.M. (1987) Muscle bone and fat proportions and the muscle distribution of Thoroughbreds and
other horses. In: Equine Exercise Physiology 2 Proceedings of the Second International Conference on
Equine Exercise Physiology, Ed: J.R.a.R. Gillespie, N.E., ICEEP, Davis, CA. pp 253–264.
4. Graham-Thiers P.M. and Kronfeld D.S. (2005) Amino acid supplementation improves muscle mass in
aged and young horses. J Anim Sci 83, 2783–2788. https://doi.org/10.2527/2005.83122783x PMID:
16282616
5. Lindner A., Signorini R., Vassallo J., Tomatis F., Flores F.M., Gagliano et al. (2010) Reproducibility and
Repeatability of Equine Muscle Thickness Measurements with Ultrasound. J Equine Vet Sci 30, 635–
640.
6. Dugdale A.H.A., Curtis G.C., Harris P.A. and Mc Argo C. (2011) Assessment of body fat in the pony:
Part I. Relationships between the anatomical distribution of adipose tissue, body composition and body
condition. Equine Veterinary Journal 43, 552–561. https://doi.org/10.1111/j.2042-3306.2010.00330.x
PMID: 21496091
7. Karlsson A., Rosander J., Romu T., Tallberg J., Gronqvist A., Borga M. et al. (2015) Automatic and
quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body
water-fat MRI. J Magn Reson Imaging 41, 1558–1569. https://doi.org/10.1002/jmri.24726 PMID:
25111561
8. Pandis P. and Bull A.M.J. (2017) A low-cost three-dimensional laser surface scanning approach for
defining body segment parameters. P I Mech Eng H 231, 1064–1068.
9. Adler C., Steinbrecher A., Jaeschke L., Mahler A., Boschmann M., Jeran S. et al. (2017) Validity and
reliability of total body volume and relative body fat mass from a 3-dimensional photonic body surface
scanner. Plos One 12.
10. Lee S.Y. and Gallagher D. (2008) Assessment methods in human body composition. Curr Opin Clin
Nutr 11, 566–572.
11. Wells J.C.K., Ruto A. and Treleaven P. (2008) Whole-body three-dimensional photonic scanning: a
new technique for obesity research and clinical practice. Int J Obesity 32, 232–238.
12. Valberg S.J.B., A.K. (2018) Assessment of equine muscle mass by 3-dimensional scanning. Compara-
tive Exercise Physiology 14, S25.
13. Jackson A.S. and Pollock M.L. (1978) Generalized Equations for Predicting Body Density of Men. Brit J
Nutr 40, 497–504. https://doi.org/10.1079/bjn19780152 PMID: 718832
14. Jackson A., Pollock M. and Ward A. (1978) Generalized Equations for Prediction of Body-Composition
in Women. Med Sci Sport Exer 10, 47–47.
15. Brozek J., Grande F., Anderson J.T. and Keys A. (1963) Densitometric Analysis of Body Composition:
Revision of Some Quantitative Assumptions. Ann N Y Acad Sci 110, 113–140. https://doi.org/10.1111/
j.1749-6632.1963.tb17079.x PMID: 14062375
16. Westervelt R.G., Stouffer J.R., Hintz H.F. and Schryver H.F. (1976) Estimating Fatness in Horses and
Ponies. J Anim Sci 43, 781–785.
17. Kane R.A.F., M.;PArrett, D.;Lawrence, L.M. (1987) Estimating fatness in horses. In: Proceedings of the
10th Equine Nutrition and Physiology Symposium, Fort Collins CO. pp 127–131.
18. Schranz N., Tomkinson G., Olds T., Petkov J. and Hahn A.G. (2012) Is three-dimensional anthropomet-
ric analysis as good as traditional anthropometric analysis in predicting junior rowing performance? J
Sport Sci 30, 1241–1248.
Three dimensional body scanning
PLOS ONE | https://doi.org/10.1371/journal.pone.0229656 February 27, 2020 12 / 12
... Over the past decade, three-dimensional (3-D) body scanning has been used widely to obtain anthropometric measurements in humans (Lu et al., 2010). Similarly, we have utilised an infrared 3-D photonic scanner in horses to assess muscle volume as a proxy for muscle mass (Valberg et al., 2020). This scanning technique provided a rapid repeatable assessment of torso and HQV and was found to strongly correlate with body weight and estimated body volume (Valberg et al., 2020). ...
... Similarly, we have utilised an infrared 3-D photonic scanner in horses to assess muscle volume as a proxy for muscle mass (Valberg et al., 2020). This scanning technique provided a rapid repeatable assessment of torso and HQV and was found to strongly correlate with body weight and estimated body volume (Valberg et al., 2020). Factors that create variability in 3-D scans have been investigated and controlled in human studies (Lu et al., 2010). ...
... Environment, hardware and software errors can be controlled with standardised settings and system calibration and improved measurement extraction software (Bradtmiller and Gross, 1999;Daanen and van de Water, 1998). Such variables have also been controlled in the 3-D scanning assessment of body volume in horses (Valberg et al., 2020). Two further sources of potential error identified in humans that have not been evaluated in horses include use of manual landmarking and the impact of body posture (Dekker, 2000;Lu and Wang, 2008). ...
Article
Well-developed musculature is important for performance yet difficult to quantify. Recently, we validated infrared 3-dimensional (3-D) photonic scanning as an accurate measure of body volume and proxy for regional muscle mass in horses. Our current objective was to determine the impact of body position on measures of lumbar (LV) and hindquarter (HQV) volume. Anatomic markers were placed on 8 horses, positioned at: (1) four hooves square, (2) neck turned ~25°, (3) head raised mean 17 cm, (4) one hind hoof (HH) forward 14±5 cm, (5) a front and contralateral HH ~15 cm all offset, (6) one HH resting. A handheld Occipital Structure Sensor photonic scanner, iPad, Skanect and Materialise 3-Matic programs captured LV and HQV. Measured LV and HQV for whole, same and opposite-side with altered head positions and whole LV and HQV with altered HH positions were compared to volume standing square using repeated measures ANOVA. The volumes of the opposite-side or same-side with altered HH positions were compared to the corresponding side when square using a paired t test with multiple test correction (P<0.017). Head elevated negatively impacted measured left LV (-10% difference, P=0.1) compared to square, however, differences were not significant. Head turned did not impact measured LV. Resting HH significantly increased measured whole (18%, P=0.04) and same-side LV (49%, P=0.001) versus square but not the opposite-side LV. One HH forward (whole 16%, P=0.02; same-side 19%, P=0.01) or all offset (whole 14%, P=0.002; same-side 27%, P=0.0001) significantly increased measured whole or same-side LV versus square. Measured HQV was not impacted by head elevated or limb position but was 2% higher on the opposite-side of the turned head (P=0.01). We conclude that alterations in body position have minimal impact on measured HQV, whereas accurate assessment of LV requires horses stand squarely.
... Three-dimensional (3D) light-scanning as a method of data collection is new in its application for horses but has been suggested to be reliable for measuring equine trunk and limb volumes (Johnson and Symons, 2020;Valberg et al., 2020) and could potentially be used to record the dorsal profile of horses. Although unable to collect data on individual muscle dimensions, like the FCR, it may be useful to objectively measure total epaxial muscle cross section area in an efficient and non-invasive manner. ...
... The reliability of the FCR to record thoracic region profile size has been tested at three levels of this spinal region (Greve and Dyson, 2013;Mackechnie-Guire et al., 2018) however 3D light-scanning has only been tested for whole body and limb volume in horses (Johnson and Symons, 2020;Valberg et al., 2020). To further explore the potential use of 3D light scanning in horses, the aim of this study was to investigate reliability of repeated measurements of the thoracic region morphology and symmetry with 3D light-scanning. ...
... The export settings were: format: STL; colours: per-vertex; number of faces: 22,130; scale: metres; colour space: sRGB. Stl files were imported into Meshmixer (V3.5.474, 2017, Autodesk Inc, San Rafael, CA, USA) (Valberg et al., 2020) and edited to remove any background and areas not of interest (e.g. lower leg, head and mid-neck). ...
Article
Equine epaxial muscle size, thoracolumbar profile and symmetry in horses is of clinical interest due to relationships with pain and pathology. Flexible-curve rulers have previously been used to gather reliable, objective measures of thoracic profile, however, 3D light-scanning offers a potential non-contact alternative method to estimate cross sectional area (CSA) of the region. 3D light-scans of the thoracic epaxial region were taken from ten endurance horses (7 geldings, 3 mares; 8±2 years). Total CSA of the combined epaxial musculature, using computer software, was calculated at scapula and T18 levels (depth: 15 cm). Intra and inter-rater (n=3) reliability of CSA measurements was assessed using Friedman’s analyses and post-hoc Wilcoxon rank tests (three repeated measures). Intraclass correlation estimates (ICC ± 95% confidence intervals (CI)) were calculated (mean-rating, absolute-agreement, 2-way mixedeffects model). Paired t-tests assessed differences between right and left areas. No significant differences existed for transverse plane-cuts (scapula, T18 P>0.05) between light-scans. Right and left areas were significantly different at the withers (P=0.012) with the left side larger in 70% of scans, but no significant differences were found between sides at T18. No differences existed for different plane-cuts of the same horse (P=0.53; ICC: 0.76; CIs: 0.43-0.92). While reliability was reduced between all raters (P=0.02; ICC: 0.70; CIs: 0.56-0.82), no significant differences occurred between two different assessors experienced in using the software (P=0.88; ICC: 0.90; CIs: 0.82-0.95). Intra-rater reliability for assessing thoracic profile and inter-rater reliability ICC values with experienced analysts was interpreted as good/excellent. The results suggest 3D light-scanning is an objective, non-invasive method to record size and symmetry of the epaxial region in horses and warrants validity testing against current measurement methods such as the flexible-curve ruler.
... Además de estimar la grasa corporal usando UTR, la evaluación muscular también es relevante en caballos deportivos, ya que, en este tipo de equinos, el rendimiento atlético depende de su potencia muscular (Payne et al. 2005); mediante esta técnica, se puede medir el área muscular, a nivel del lomo y el espesor del glúteo medio. Estas medidas son importantes, ya que los caballos deportivos tienen una mayor masa muscular, que va de 53-57 % en comparación con otros caballos, que es 42 % (Valberg et al. 2020). El desarrollo de grupos musculares específicos es reconocido en ciertos tipos de disciplinas deportivas equinas, como el salto y el adiestramiento (Payne et al. 2005). ...
Article
Full-text available
Existen varias metodologías para determinar la condición corporal del caballo deportivo, siendo unas más objetivas que otras; sin embargo, la escala de condición corporal es la más usada para estimar las reservas corporales de animales en actividad atlética. El objetivo del estudio fue estimar, por métodos no invasivos, el espesor de grasa subcutánea y desarrollo muscular de caballos deportivos, de una academia de Cundinamarca y calcular algunos índices que definen la composición corporal. Se escogieron 29 caballos adultos (9 hembras, 20 machos), de cuatro tipos raciales; caballo deporte colombiano, criollo, polo argentino, Pura sangre inglés. Para evaluar la grasa subcutánea se usó el puntaje de condición corporal (PCC) escala Henneke, el ultrasonido en tiempo real UTR, midiendo espesor de grasa dorsal y de cadera. La musculatura se determinó usando UTR a nivel dorsal, midiendo el ojo del lomo y el glúteo medio. Se tomaron pesos y medidas morfométricas: altura de cruz, longitud corporal, perímetro torácico. Con estas medidas corporales o ecográficas se calcularon índices de desempeño o composición corporal: índice corporal (IC), índice de carga al paso-1 y al trote-2 (IC1 y IC2), % de grasa corporal (%GC), Índice de masa corporal (IMC), relación perímetro torácico–altura cruz (PT:AC), índice muscular (IM) e índice musculoesquelético (IME). Los índices de carga y de composición corporal indicaron diferencias entre tipos raciales (p<0,05). Entre índices de engrasamiento se presentaron correlaciones altas con PCC (EGD 0,78 y IMC 0,99). Algunos índices (IC1, IC2) serían indicadores indirectos de la relación fin-bienestar en los animales.
... depth cameras, especially iPads [8], [9], with applications ranging from veterinary [10], [11] and forestry [12], [13] to reconstruction of buildings [14] and heritage documentation [15]. This serves as a motivation for new techniques that can bridge EOT and mobile AR, as EOT algorithms are already designed to deal with noisy measurements in environments with low computational resources. ...
Conference Paper
Full-text available
Augmented reality (AR) in mobile devices (such as smartphones and tablets) is becoming more popular each day, and because of this many newer devices are starting to ship with embedded depth sensors. This presents a great opportunity for the field of extended object tracking, whose algorithms are well-suited for dealing with varying measurement quality while requiring little CPU usage. In this paper, we present an application in the field of robotics, based on the idea of reconstructing the dynamic state of a robot (joint positions and velocities) simply by observing it with an AR device, and using only the robot specification (its URDF file) as prior knowledge, without requiring a connection to the robot’s control system. This can allow the mobile device to identify where a robot is, or viceversa, without requiring markers such as QR codes. Additionally, this can serve as a stepping stone for more sophisticated assistance systems that can interact with the robot without requiring any access to its internals, which could otherwise make it difficult to deploy the AR app in sensitive systems. Using the iPad Pro 2020 as an example device, we examine the challenges involved in processing mobile depth images, how to develop a robust shape model and the corresponding estimator, and how the app can ask the user to help in its initialization using AR. We will also provide an evaluation with real data that shows how the proposed system can track a moving robot robustly even if measurement quality is reduced significantly. (PDF) Robot Joint Tracking With Mobile Depth Cameras for Augmented Reality Applications. Available from: https://www.researchgate.net/publication/362937250_Robot_Joint_Tracking_With_Mobile_Depth_Cameras_for_Augmented_Reality_Applications [accessed Sep 22 2022].
Article
Full-text available
Simple Summary Increased incidence of obesity in our equine population has clear negative impacts on equine health, such as increasing the risk of equine metabolic syndrome and laminitis. Excessive adipose tissue likely also has negative impacts on exercise performance, due to a combined inflammatory response and the effects of excessive weight carriage on work effort and limb health. This review explores research conducted in these areas. Abstract There is ample research describing the increased risk of health concerns associated with equine obesity, including insulin dysregulation and laminitis. For athletes, the negative effect of weight carriage is well documented in racing thoroughbreds (i.e., handicapping with weight) and rider weight has been shown to impact the workload of ridden horses and to some degree their gait and movement. In many groups of competitive and athletic horses and ponies, obesity is still relatively common. Therefore, these animals not only are at risk of metabolic disease, but also must perform at a higher workload due to the weight of their adipose tissue. Excess body weight has been documented to affect gait quality, cause heat stress and is expected to hasten the incidence of arthritis development. Meanwhile, many equine event judges appear to favor the look of adiposity in competitive animals. This potentially rewards horses and ponies that are at higher risk of disease and reinforces the owner’s decisions to keep their animals fat. This is a welfare concern for these animals and is of grave concern for the equine industry.
Article
Loss of skeletal muscle mass likely compromises performance and welfare in horses and thus routine monitoring would be valuable. Currently available methods to assess muscle mass require expert knowledge and are often expensive. To provide a simple method, a muscle atrophy scoring system (MASS) was created and tested by three evaluators (raters) in 38 horses of varying age, breed, and health status. Inter-rater agreement on atrophy scores was in the good-to-excellent range for ratings of the neck (ICC= 0.62), back (ICC= 0.62) and hind (ICC= 0.76) regions but was poor for the abdominal region (ICC= 0.29). Due to this low agreement, the abdominal region was excluded from further analysis. Associations between muscle atrophy scores and age, pituitary pars intermedia dysfunction (PPID) status, and body composition indicators, including weight and estimated fat-free mass (FFM), were examined. Weight was inversely associated with neck, back and hind muscle atrophy scores (β= -0.008, β= -0.008, β= -0.009, respectively; all P<0.001), but estimated FFM was not associated with muscle atrophy scores at any region (P>0.05). Age was positively related to neck (β= 0.030, P<0.01), back (β= 0.037, P<0.001) and hind (β= 0.040, P<0.001) muscle atrophy scores. PPID-positive horses (n=4) had higher muscle atrophy scores than PPID-negative horses (n=23), even after adjusting for age (P<0.05). This data suggests that neck, back and hind region evaluations by individual raters likely have acceptable reliability. In addition, these findings support further evaluation of the potential benefits of the MASS to identify and monitor muscle atrophy in horses.
Article
Full-text available
Background A subset of horses deficient in alpha‐tocopherol (α‐TP) develop muscle atrophy and vitamin E‐responsive myopathy (VEM) characterized by mitochondrial alterations in the sacrocaudalis dorsalis medialis muscle (SC). Objectives To quantify muscle histopathologic abnormalities in subclinical α‐TP deficient horses before and after α‐TP supplementation and compare with retrospective (r)VEM cases. Animals Prospective study; 16 healthy α‐TP‐deficient Quarter Horses. Retrospective study; 10 retrospective vitamin E‐responsive myopathy (rVEM) cases . Methods Blood, SC, and gluteus medius (GM) biopsy specimens were obtained before (day 0) and 56 days after 5000 IU/450 kg horse/day PO water dispersible liquid α‐TP (n = 8) or control (n = 8). Muscle fiber morphology and mitochondrial alterations were compared in samples from days 0 and 56 and in rVEM cases. Results Mitochondrial alterations more common than our reference range (<2.5% affected fibers) were present in 3/8 control and 4/8 treatment horses on day 0 in SC but not in GM (mean, 2.2; range, 0%‐10% of fibers). Supplementation with α‐TP for 56 days did not change the percentage of fibers with mitochondrial alterations or anguloid atrophy, or fiber size in GM or SC. Clinical rVEM horses had significantly more mitochondrial alterations (rVEM SC, 13% ± 7%; GM, 3% ± 2%) and anguloid atrophy compared to subclinical day 0 horses. Conclusions and Clinical Importance Clinically normal α‐TP‐deficient horses can have mitochondrial alterations in the SC that are less severe than in atrophied VEM cases and do not resolve after 56 days of α‐TP supplementation. Preventing α‐TP deficiency may be of long‐term importance for mitochondrial viability.
Article
Full-text available
Body segment parameters are used in many different applications in ergonomics as well as in dynamic modelling of the musculoskeletal system. Body segment parameters can be defined using different methods, including techniques that involve time-consuming manual measurements of the human body, used in conjunction with models or equations. In this study, a scanning technique for measuring subject-specific body segment parameters in an easy, fast, accurate and low-cost way was developed and validated. The scanner can obtain the body segment parameters in a single scanning operation, which takes between 8 and 10 s. The results obtained with the system show a standard deviation of 2.5% in volumetric measurements of the upper limb of a mannequin and 3.1% difference between scanning volume and actual volume. Finally, the maximum mean error for the moment of inertia by scanning a standard-sized homogeneous object was 2.2%. This study shows that a low-cost system can provide quick and accurate subject-specific body segment parameter estimates.
Article
Full-text available
Objective Three-dimensional photonic body surface scanners (3DPS) feature a tool to estimate total body volume (BV) from 3D images of the human body, from which the relative body fat mass (%BF) can be calculated. However, information on validity and reliability of these measurements for application in epidemiological studies is limited. Methods Validity was assessed among 32 participants (men, 50%) aged 20–58 years. BV and %BF were assessed using a 3DPS (VitusSmart XXL) and air displacement plethysmography (ADP) with a BOD POD® device using equations by Siri and Brozek. Three scans were obtained per participant (standard, relaxed, exhaled scan). Validity was evaluated based on the agreement of 3DPS with ADP using Bland Altman plots, correlation analysis and Wilcoxon signed ranks test for paired samples. Reliability was investigated in a separate sample of 18 participants (men, 67%) aged 25–66 years using intraclass correlation coefficients (ICC) based on two repeated 3DPS measurements four weeks apart. Results Mean BV and %BF were higher using 3DPS compared to ADP, (3DPS-ADP BV difference 1.1 ± 0.9 L, p<0.01; %BF difference 7.0 ± 5.6, p<0.01), yet the disagreement was not associated with gender, age or body mass index (BMI). Reliability was excellent for 3DPS BV (ICC, 0.998) and good for 3DPS %BF (ICC, 0.982). Results were similar for the standard scan and the relaxed scan but somewhat weaker for the exhaled scan. Conclusions Although BV and %BF are higher than ADP measurements, our data indicate good validity and reliability for an application of 3DPS in epidemiological studies.
Article
Full-text available
With the use of three-dimensional whole body scanning technology, this study compared the 'traditional' anthropometric model [one-dimensional (1D) measurements] to a 'new' model [1D, two-dimensional (2D), and three-dimensional (3D) measurements] to determine: (1) which model predicted more of the variance in self-reported best 2000-m ergometry rowing performance; and (2) what were the best anthropometric predictors of ergometry performance, for junior rowers competing at the 2007 and 2008 Australian Rowing Championships. Each rower (257 females, 16.3 ± 1.4 years and 243 males, 16.6 ± 1.5 years) completed a performance and demographic questionnaire, had their mass, standing and sitting height physically measured and were landmarked and scanned using the Vitus Smart® 3D whole body scanner. Absolute and proportional anthropometric measurements were extracted from the scan files. Partial least squares regression analysis, with anthropometric measurements and age as predictor variables and self-reported best 2000-m ergometer time as the response variable, was used to first compare the two models and then to determine the best performance predictors. The variance explained by each model was similar for both male [76.1% (new) vs. 73.5% (traditional)] and female [72.3% (new) vs. 68.6% (traditional)] rowers. Overall, absolute rather than proportional measurements, and 2D and 3D rather than 1D measurements, were the best predictors of rowing ergometry performance, with whole body volume and surface area, standing height, mass and leg length the strongest individual predictors.
Article
Full-text available
1. Skinfold thickness, body circumferences and body density were measured in samples of 308 and ninety-five adult men ranging in age from 18 to 61 years. 2. Using the sample of 308 men, multiple regression equations were calculated to estimate body density using either the quadratic or log form of the sum of skinfolds, in combination with age, waist and forearm circumference. 3. The multiple correlations for the equations exceeded 0.90 with standard errors of approximately ±0.0073 g/ml. 4. The regression equations were cross validated on the second sample of ninety-five men. The correlations between predicted and laboratory-determined body density exceeded 0.90 with standard errors of approximately 0.0077 g/ml. 5. The regression equations were shown to be valid for adult men varying in age and fatness.
Article
PurposeTo develop and demonstrate a rapid whole-body magnetic resonance imaging (MRI) method for automatic quantification of total and regional skeletal muscle volume.Materials and Methods The method was based on a multi-atlas segmentation of intensity corrected water–fat separated image volumes. Automatic lean muscle tissue segmentations were achieved by nonrigid registration of atlas datasets with 10 different manually segmented muscle groups. Ten subjects scanned at 1.5 T and 3.0 T were used as atlases, initial validation and optimization. Further validation used 11 subjects scanned at 3.0 T. The automated and manual segmentations were compared using intraclass correlation, true positive volume fractions, and delta volumes.ResultsFor the 1.5 T datasets, the intraclass correlation, true positive volume fractions (mean ± standard deviation, SD), and delta volumes (mean ± SD) were 0.99, 0.91 ± 0.02, −0.10 ± 0.70L (whole body), 0.99, 0.93 ± 0.02, 0.01 ± 0.07L (left anterior thigh), and 0.98, 0.80 ± 0.07, −0.08 ± 0.15L (left abdomen). The corresponding values at 3.0 T were 0.97, 0.92 ± 0.03, −0.17 ± 1.37L (whole body), 0.99, 0.93 ± 0.03, 0.03 ± 0.08L (left anterior thigh), and 0.89, 0.90 ± 0.04, −0.03 ± 0.42L (left abdomen). The validation datasets showed similar results.Conclusion The method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution. J. Magn. Reson. Imaging 2014. © 2014 Wiley Periodicals, Inc.
Article
SUMMARY The relationship of ultrasonic measurements to actual fat cover, the value of such measure- ments for the prediction of total body fat, and the effect of exercise and level of diet intake on fat cover were studied in horses and ponies in four trials. In trial 1 eight ponies were allowed feed ad libitum and seven ponies were fed a limited amount of the same diet for 4�89 months. Ultrasonic rump fat thickness was highly correlated (r = .85), with actual rump fat thickness. The ponies fed ad libitum had greater live weights and rib and rump fat thickness than ponies fed restricted amounts. Twelve horses were evaluated by ultrasound for fat thickness over the shoulder, rib and rump after 0, 30 and 90 days of exercise in the second trial. Shoulder fat and rump fat decreased after 30 days, although rib fat and body weight did not change. In a third experiment, eight horses were evaluated for fat thickness by ultrasound, then slaughtered and analyzed for chemically ex- tractable fat. Rump and shoulder fat were correlated with extractable fat, (r = .93 and r = .71, respectively). The relationship between rump fat determined ultrasonically (X, cm) and extractable fat (Y, %) was described by the equation: Y = 8.64 + 4.70 X (r 2 -- .86).
Article
This study examined the reproducibility and repeatability of muscle thickness (MT) measurements with ultrasound for the following muscles: extensor carpi radialis, extensor digitorum longus (both flexed and extended), gluteus medius, longissimus lumborum, semitendinosus, and supraspinatus. Three examiners measured thickness of these muscles in five Thoroughbreds on 3 consecutive days. The day of measurement did not have any effect on the mean MT value of the muscles examined (P > .05). The left longissimus lumborum muscle was the only muscle for which the second measurement varied from the first and third (P < .05). The examiners had an effect on the mean coefficient of variation (CV) of the thickness of the flexed left extensor carpi radialis and flexed left extensor digitorum longus. The daily measurements varied more in the case of one of the examiners. Mean CVs higher or close to 10% were reported for both sides of the flexed extensor digitorum longus and for the supraspinatus muscles. The lowest CV was calculated for the longissimus lumborum and the extended semitendinosus (<5%). The largest disagreements between the examiners were observed for both sides of the flexed extensor digitorum longus and the supraspinatus (>10%–<20%). The best agreement was measured for the extended extensor carpi radialis and the longissimus lumborum (>3%–<7%). The results showed that for some muscles, it was difficult to locate the exact anatomical site for taking the MT measurements. To reduce CV, it was suggested that only one examiner should take all the measurements and the whole procedure must be such that it is as comfortable as possible for this particular examiner.
Article
Evaluation of equine body fat content is important for nutritional and clinical purposes. However, our understanding of total body fat and its regional distribution in the body is sparse. Currently, body fat evaluation relies on the subjective assessment of body condition score (BCS), which has never been validated against 'gold standard' chemical analysis or dissection measurements in ponies. To define the relationships between subjective (BCS), objective (morphometric) indices of body fat and 'gold standard' measurements of actual body composition. BCS and morphometry offer valid, noninvasive methods for determination of body fat in equids. Methods: Seven mature (mean ± s.e. 13 ± 3 years, 212 ± 14 kg, BCS 1.25-7/9), Welsh Mountain pony mares, destined for euthanasia (for nonresearch purposes), were used. For all ponies, body mass (BM), BCS and various morphometric measurements were recorded. Following euthanasia, all ponies were systematically dissected. Discrete white adipose tissue (WAT) depots were independently described. Gross, body chemical composition was determined by proximate analyses. Total somatic soft tissues increased linearly (r(2) = 1.00), whereas body WAT content (1-26% live BM) increased exponentially (r(2) = 0.96), with BCS. WAT was equally distributed between internal and external sites in all animals irrespective of BCS. Nuchal fat was a poor predictor of total WAT (r(2) = 0.66). Periorbital WAT did not alter with BCS (r(2) = 0.01). Heart girth:withers height and ultrasonic retroperitoneal fat depth were closely associated with total, chemically-extracted lipid which comprised 1-29% live BM (r(2) = 0.91 and 0.88, respectively). The exponential relationship between BCS and total body WAT/lipid suggests that BCS is unlikely to be a sensitive index of body fat for animals in moderate-obese states. Morphometric measurements (body girths and retroperitonel fat depth) may be useful to augment subjective BCS systems.
Article
The present study reviews the most recently developed and commonly used methods for the determination of human body composition in vivo with relevance for nutritional assessment. Body composition measurement methods are continuously being perfected with the most commonly used methods being bioelectrical impedance analysis, dilution techniques, air displacement plethysmography, dual energy X-ray absorptiometry, and MRI or magnetic resonance spectroscopy. Recent developments include three-dimensional photonic scanning and quantitative magnetic resonance. Collectively, these techniques allow for the measurement of fat, fat-free mass, bone mineral content, total body water, extracellular water, total adipose tissue and its subdepots (visceral, subcutaneous, and intermuscular), skeletal muscle, select organs, and ectopic fat depots. There is an ongoing need to perfect methods that provide information beyond mass and structure (static measures) to kinetic measures that yield information on metabolic and biological functions. On the basis of the wide range of measurable properties, analytical methods and known body composition models, clinicians and scientists can quantify a number of body components and with longitudinal assessment, can track changes in health and disease with implications for understanding efficacy of nutritional and clinical interventions, diagnosis, prevention, and treatment in clinical settings. With the greater need to understand precursors of health risk beginning in childhood, a gap exists in appropriate in-vivo measurement methods beginning at birth.