Digital anthropometric volumes: Toward the development and validation of a universal software.

PURPOSE: Anthropometry is a method for quantifying body size and shape often used to derive body composition and health risk prediction models. Recent technology advancements led to development of three-dimensional (3D) optical scanners that can overcome most of the limitations associated with manual anthropometric data collection. However, each of the currently available devices offers proprietary measurements that do not match conventional anthropometric definitions. The aim of the current study was to develop and then evaluate the precision and accuracy of new "universal" 3D optical analysis software that calculates digital anthropometric volumes using identical standard landmarks across scanners. METHODS: Dual-energy x-ray absorptiometry (DXA) and air displacement plethysmography (ADP) total body and regional volume and fat mass reference measurements and 3D optical scans from two proprietary devices were collected from 356 participants to evaluate the robustness of total body and regional volume and fat mass measurements calculated by the developed software. Linear regression modeling with threefold cross validation was used to evaluate total body and regional fat masses from 3D scans. RESULTS: Total body and regional volumes measured by DXA and ADP had strong associations with corresponding estimates from the commercial 3D optical scanners coupled with the universal software (e.g., R2  = 0.98 for Styku and R2  = 1.00 for SS20, for both DXA and ADP comparisons). Regional body volumes also had strong correlation between DXA and the 3DO scanners (e.g., for arm, leg and trunk, respective R2 s of 0.75, 0.86, and 0.97 for Styku and 0.79, 0.89, and 0.98 for SS20). Similarly, there were strong associations between DXA- measured total body and regional fat mass and 3D optical estimates calculated by the universal software (e.g., for total body, arm, leg and trunk, respective R2 s of 0.86, 0.72, 0.77, and 0.88 for Styku and 0.84, 0.76, 0.78, and 0.85 for SS20). Absolute differences in volumes and fat mass between the reference methods and the universal software values revealed underlying proprietary scanner differences that can be improved when designing future devices. CONCLUSIONS: The current study suggests that, when compared against values calculated using DXA and ADP, the universal software was able to measure total and regional body volumes reliably from scans obtained by two different scanners. The universal software, with future refinements, combined with potential optical scanner design improvements, creates new opportunities for developing large multicenter anthropometric databases with uniformly defined body dimensions that can be used for modeling health risks. CLINICAL TRIAL REGISTRATION ID: Shape Up! Adults Study, NCT0363785.

Digital anthropometry for body circumference measurements: Toward the development of universal three-dimensional optical system analysis software.

BACKGROUND/OBJECTIVE: Digital anthropometric (DA) assessments are increasingly being administered with three-dimensional (3D) optical devices in clinical settings that manage patients with obesity and related metabolic disorders. However, anatomic measurement sites are not standardized across manufacturers, precluding use of published reference values and pooling of data across research centers. SUBJECTS/METHODS: This study aimed to develop universal 3D analysis software by applying novel programming strategies capable of producing device-independent DA estimates that agree with conventional anthropometric (CA) measurements made at well-defined anatomic sites. A series of technical issues related to proprietary methods of 3D geometrical reconstruction and image analysis were addressed in developing major software components. To evaluate software accuracy, comparisons were made to CA circumference measurements made with a flexible tape at eleven standard anatomic sites in up to 35 adults scanned with three different commercial 3D optical devices. RESULTS: Overall, group mean CA and DA values across the three systems were in good agreement, with ∼2 cm systematic differences; CA and DA estimates were highly correlated (all p-values <0.01); root-mean square errors were low (0.51-3.27 cm); and CA-DA bias tended to be small, but significant depending on anatomic site and device. CONCLUSIONS: Availability of this software, with future refinements, has the potential to facilitate clinical applications and creation of large pooled uniform anthropometric databases.

Fully Automated Pipeline for Body Composition Estimation from 3D Optical Scans using Principal Component Analysis: A Shape Up Study.

The increasing prevalence and adaptability of 3D optical scan (3DO) technology has invoked many recent studies which use 3DO scanning as a convenient and inexpensive means for predicting body composition and health risks. The Shape Up studies seek a device-agnostic solution for body composition estimation based on principal component analysis (PCA). This paper reports a progress made on Shape Up's previous work which served as a criterion analysis for PCA-based body composition and health risk prediction. This study presents proof-of-concept for a novel automated landmark detection step that allows for a fully automated PCA-based approach to body composition estimation that facilitates a practical device-agnostic PCA-based solution to body composition estimation from 3DO scans. Our results show that replacing expensive and time-consuming manual point placement with the proposed automated landmarks will not diminish the quality of body composition estimates allowing for a more practical pipeline that can be used in real-world settings.

Hole Filling in 3D Scans for Digital Anthropometric Applications.

Anthropometric measurements have been used to assess an individual's body composition, disease risk, and nutritional status. Three-dimensional (3D) optical devices can rapidly acquire body surface scans in the form of a triangular mesh which can then be used to obtain anthropometric measurements such as body volume, limb lengths, and circumferences; however, the meshes provided by some scanners may include missing data patches known as holes. These need to be repaired in order to obtain correct landmark detection and automatic calculation of anthropometric measurements-especially body volume. In this study, we present ScReAM (Scan Reconstruction for Anthropometric Measurements) which is a fully automated geometrical 3D reconstruction approach to find and fill these holes. We compare ScReAM with Alias and MeshFix which are well-known software used for triangular meshing. Evaluations are derived from a sample size of 47 subjects that were scanned by two different 3D optical scanners. Our results validate the accuracy of ScReAM for reconstructing a mesh for volume calculation.

A framework for detecting glaucomatous progression in the optic nerve head of an eye using proper orthogonal decomposition.

Glaucoma is the second leading cause of blindness worldwide. Often, the optic nerve head (ONH) glaucomatous damage and ONH changes occur prior to visual field loss and are observable in vivo. Thus, digital image analysis is a promising choice for detecting the onset and/or progression of glaucoma. In this paper, we present a new framework for detecting glaucomatous changes in the ONH of an eye using the method of proper orthogonal decomposition (POD). A baseline topograph subspace was constructed for each eye to describe the structure of the ONH of the eye at a reference/baseline condition using POD. Any glaucomatous changes in the ONH of the eye present during a follow-up exam were estimated by comparing the follow-up ONH topography with its baseline topograph subspace representation. Image correspondence measures of L1-norm and L2 -norm, correlation, and image Euclidean distance (IMED) were used to quantify the ONH changes. An ONH topographic library built from the Louisiana State University Experimental Glaucoma study was used to evaluate the performance of the proposed method. The area under the receiver operating characteristic curves (AUCs) was used to compare the diagnostic performance of the POD-induced parameters with the parameters of the topographic change analysis (TCA) method. The IMED and L2-norm parameters in the POD framework provided the highest AUC of 0.94 at 10 degrees field of imaging and 0.91 at 15 degrees field of imaging compared to the TCA parameters with an AUC of 0.86 and 0.88, respectively. The proposed POD framework captures the instrument measurement variability and inherent structure variability and shows promise for improving our ability to detect glaucomatous change over time in glaucoma management.

Differential effects of plantar desensitization on locomotion dynamics.

Reduced plantar sensation secondary to chronic diffuse polyneuropathy (PN) is believed to reduce locomotor stability, especially when walking at non-preferred speeds. However, the contribution of plantar sensation to the maintenance of locomotor stability is not entirely clear. The purpose of this study was to examine the effects of acute loss of plantar sensation on the stability-related kinematic properties of walking at different speeds. Lower-extremity joint kinematics were acquired as healthy young adults walked on a treadmill at their preferred walking speed (PWS) and three predetermined speeds (0.8, 1.0, and 1.2m/s) under both normal and desensitized conditions. Desensitization of the foot soles was induced by ice-exposure, and plantar pressure sensation was assessed by a 5.07 monofilament. The average magnitude of stride duration variability (SDvar) and lower-extremity joint angle variability (JTvar), as well as short- and long-term "finite-time" Lyapunov exponents (lambda(ST)(*), lambda(LT)(*)) associated with lower-extremity joint angles were computed. Ice-induced plantar desensitization led to increased lambda(ST)(*) ( approximately 40%) and lambda(LT)(*) (approximately 8%) values but did not affect SDvar or JTvar. Higher treadmill speed led to greater lambda(ST)(*) and lambda(LT)(*) values, but the speed effects were not influenced by plantar desensitization.While acute loss of plantar sensation does not appear to influence the magnitude of spatial or temporal variability, it did attenuate the state-space trajectory divergence caused by stride-to-stride variability (i.e., lambda(ST)( *) and lambda(LT)(*)). However, as opposed to walking at PWS, otherwise healthy locomotor systems do not appear to place increased reliance on plantar sensation when walking at non-preferred treadmill speeds.

Faster walking speeds increase local instability among people with peripheral neuropathy.

Individuals with peripheral neuropathy (PN) may compensate for decreased somatosensation by reducing walking speed. Predisposition to falls may therefore arise from an inability to adapt to challenging walking speeds. The purpose of this study was to examine the effects of PN on the magnitude of variability and local instability on walking at different speeds. Twelve individuals with PN and 12 controls completed a 6-min walk test to determine fast walking speed (FWS). Sagittal plane hip, knee, and ankle joint angles were then calculated during 3 min of treadmill walking at 100%, 80%, and 60% FWS. The magnitudes of stride duration variability (SDvar), joint angle variability (JTvar), and both short- and long-term Lyapunov exponents (used to estimate local instability) were calculated. The PN group walked slower than the control group (p<.001). With groups combined, walking faster led to increased local instability and increased variability (p<.001). The PN group exhibited increased variability (SDvar, p=.02; JTvar, p=.01) over all speeds, and exaggerated local instability (p<.05) when walking at the fastest speed. PN leads to increased walking variability and local instability, particularly when walking at challenging speeds. These results are important to consider in future patient education and rehabilitation programs.

Real-time restoration of white-light confocal microscope optical sections.

Confocal microscopes (CM) are routinely used for building 3-D images of microscopic structures. Nonideal imaging conditions in a white-light CM introduce additive noise and blur. The optical section images need to be restored prior to quantitative analysis. We present an adaptive noise filtering technique using Karhunen-Loéve expansion (KLE) by the method of snapshots and a ringing metric to quantify the ringing artifacts introduced in the images restored at various iterations of iterative Lucy-Richardson deconvolution algorithm. The KLE provides a set of basis functions that comprise the optimal linear basis for an ensemble of empirical observations. We show that most of the noise in the scene can be removed by reconstructing the images using the KLE basis vector with the largest eigenvalue. The prefiltering scheme presented is faster and does not require prior knowledge about image noise. Optical sections processed using the KLE prefilter can be restored using a simple inverse restoration algorithm; thus, the methodology is suitable for real-time image restoration applications. The KLE image prefilter outperforms the temporal-average prefilter in restoring CM optical sections. The ringing metric developed uses simple binary morphological operations to quantify the ringing artifacts and confirms with the visual observation of ringing artifacts in the restored images.