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Apex 3

Manufactured by Hologic
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Sourced in United States, United Kingdom

The APEX 3.1 software is a laboratory information management system (LIMS) designed to streamline workflow and data management in clinical laboratories. It provides a centralized platform for managing sample information, test results, and laboratory operations. The software offers features such as sample tracking, test ordering, and reporting capabilities to help laboratories enhance efficiency and ensure data integrity.

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Lab products found in correlation

Qdr 4500 discovery dxa scanner, by Hologic (2 mentions) Discovery a dxa system, by Hologic (2 mentions) Qdr 4500a dxa machine, by Hologic (2 mentions) Apex software version 4, by Hologic (2 mentions) Discovery a, by Hologic (1 mentions) Leicester height measure, by Seca (1 mentions) Calibrated digital scale, by Seca (1 mentions) Qdr 4500a dxa, by Hologic (1 mentions) Discovery model a densitometer, by Hologic (1 mentions) Discovery instrument, by Hologic (1 mentions) Delphi densitometer, by Hologic (1 mentions) Qdr 4500a, by Hologic (1 mentions) Matlab v7.11.0.584 r2010b, by MathWorks (1 mentions)

18 protocols using apex 3

1

Femoral Geometric Measures from DXA

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Linear geometric measures were derived from hip DXA images using the Hip Structure Analysis program (Hologic Apex 3.0 software). The geometric measures used in this study included the hip axis length (HAL, cm), the narrow neck width (NNW, cm), and the neck-shaft angle (NSA, degree). The HAL is the linear distance from the base of the greater trochanter to the edge of the pelvic inlet. The NNW is the narrowest distance across the femoral neck. The NSA is the angle between derived axes of neck and shaft. The HAL is calculated by the system from the lateral bone map edge of the greater trochanter to the edge of the pelvic inlet or to the Global ROI edge, whichever point is intersected first. Therefore, a strict protocol was followed for positioning the Global ROI edge in the same point of the edge of the pelvic inlet.
Zymbal V., Baptista F., Letuchy E.M., Janz K.F, & Levy S.M. (2019). Mediating Effect of Muscle on the Relationship of Physical Activity and Bone. Medicine and science in sports and exercise, 51(1), 202-210.
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2

Body Composition and Blood Pressure Measurement

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Whole-body scans were obtained using a Hologic Discovery A instrument with APEX 3.0 software (Hologic, Bedford, MA). To encourage compliance, a sheet with appropriate pictures was laid on the couch, and to help reduce movement artefact, the children were shown a suitable DVD. The total radiation doses for the scan was 4.7 μSv. From this scan sex- and age-adjusted estimates of percent body fat and trunk fat (kg) were obtained. During the assessment, the child’s height (using a Leicester height measure, Seca) and weight (using calibrated digital scales, Seca) were also measured. At the clinic visit, a single measurement of seated blood pressure was obtained using a Dinamap monitor. The five outcome variables investigated were BMI, trunk fat, per cent body fat and systolic (SBP) and diastolic blood pressure (DBP).
Norris T., Crozier S.R., Cameron N., Godfrey K.M., Inskip H, & Johnson W. (2020). Fetal growth does not modify the relationship of infant weight gain with childhood adiposity and blood pressure in the Southampton women’s survey. Annals of Human Biology, 47(2), 150-158.
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3

Measurement of Femoral Bone Geometry

Cited 1 time
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At approximately age 19 years old, trained research staff conducted DXA scans for all participants using the Hologic QDR 4500A DXA (Delphi upgrade) with software V.12.3 in the fan-beam mode, as described previously (4 (link)). Briefly, software-specific Global Regions of Interest (ROI) were used to designate the general boundaries of the hip images. The operator reviewed, edited, and confirmed the bone within the ROI box to ensure appropriate bone-edge detection. The DXA measure used in this study was aBMD (g/cm2) at the total hip. Structural geometry was estimated from hip DXA images using the Hip Structure Analysis program (Hologic Apex 3.0 software). This program is based on the principle first described by Martin and Burr that the mass in a pixel value (g/cm2 of hydroxyapatite) can be converted to linear thickness (cm) by dividing it by the effective mineral density of a fully mineralized bone (31 (link)). A line of pixels traversing the bone axis is thus a projection of the surface area of a bone in cross-section and can yield some of its geometry (2 (link)). Specifically, the Hologic software program located the narrowest point of the femoral neck, where bone cross-sectional area (CSA, cm2) and cross-sectional moment of inertia (cm4) for bending in the image plane were calculated, from which femoral neck section modulus (FN Z, cm3) was derived.
Ward R.C., Janz K.F., Letuchy E.M., Peterson C, & Levy S.M. (2019). Contribution of High School Sport Participation to Young Adult Bone Strength. Medicine and science in sports and exercise, 51(5), 1064-1072.
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4

Spinal BMD and Demographic Factors

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The outcome variables are the spinal BMD (total spinal BMD, L1-L4BMD) measured by dual-energy X-ray absorptiometry on the Hologic Discovery model A densitometer (Hologic, Inc., Bedford, Massachusetts). All scans were analyzed using Hologic APEX3.0 software. Covariates include demographic data, such as age, gender, race, education level, marital status, body mass index (BMI, kg/m2), C-reactive protein (CRP, mmol/L), serum total calcium concentration (Ca, mmol/L), phosphorus (P, mmol/L), total cholesterol (TC, mmol/L), alkaline phosphatase (ALP, U/L), aspartate aminotransferase (AST, U/L), alanine aminotransferase (ALT, U/L), smoking status, alcohol consumption, hypertension, diabetes. Covariates were collected through family interviews, physical examination, laboratory measurements, and questionnaires. For more details on data collection, visit https://wwwn.cdc.gov/nchs/nhanes/ContinuousNhanes/Default.aspx?BeginYear=2007 and https://wwwn.cdc.gov/nchs/nhanes/ContinuousNhanes/Default.aspx?BeginYear=2009.
Gu P., Pu B., Chen B., Zheng X., Zeng Z, & Luo W. (2023). Effects of vitamin D deficiency on blood lipids and bone metabolism: a large cross-sectional study. Journal of Orthopaedic Surgery and Research, 18, 20.
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5

Whole-Body DXA Scans in Pediatric Cohort

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At birth (n 102) and 4 years of age (n42–46) a whole-body DXA scan was obtained using a Hologic Discovery
instrument (Hologic, Inc.) in paediatric scan mode (Apex 3.1 software), yielding
fat mass, lean mass and bone mineral content. The CV for body composition
analysis with the DXA instrument was 1·4–1·9 %.
Cleal J.K., Day P.E., Simner C.L., Barton S.J., Mahon P.A., Inskip H.M., Godfrey K.M., Hanson M.A., Cooper C., Lewis R.M, & Harvey N.C. (2015). Placental amino acid transport may be regulated by maternal vitamin D and vitamin D-binding protein: results from the Southampton Women's Survey. The British Journal of Nutrition, 113(12), 1903-1910.
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6

Comprehensive Body Composition Assessment in Allogeneic HSCT

Cited 2 times
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Whole body DXA scans were obtained in alloHSCT, matched controls and healthy reference participants with a Hologic Delphi densitometer (Bedford, Massachusetts).(7 (link)) Outcomes included whole body fat mass (WB-FM, kg) and lean mass (WB-LM, kg) excluding the head, and Leg-LM (kg) as a measure of skeletal muscle. DXA trunk visceral (VAT) and subcutaneous adipose tissue (SAT) area (cm2) in alloHSCT and matched controls were quantified in a 5 cm region at the L4 level (Hologic APEX 3.1 software) with VAT coefficient of variation reported at 2.3%.(26 (link),27 )
Mostoufi-Moab S., Magland J., Isaacoff E.J., Sun W., Rajapakse C.S., Zemel B., Wehrli F., Shekdar K., Baker J., Long J, & Leonard M.B. (2015). Adverse Fat Depots and Marrow Adiposity Are Associated with Skeletal Deficits and Insulin Resistance in Long-Term Survivors of Pediatric Hematopoietic Stem Cell Transplantation. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research, 30(9), 1657-1666.
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7

Body Composition Measurements Using DXA

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Measures of body composition were obtained at the CRFs using a QDR 4500 Discovery DXA scanner (Hologic Inc, Bedford, MA, USA) whilst the individuals were in a supine position. The measures of body composition used in these analyses were whole body, android and gynoid fat mass and whole body lean mass defined as total mass minus fat and bone mass. For all measures, mass from the head was excluded and measures were converted to kg. All scans were reviewed and centrally analysed by a single operator using APEX 3.1 software (Hologic Inc., Bedford, MA, USA), with use of a the European Spine Phantom at the start and end of the study to ensure cross-calibration between scanners [26 , 27 ]. Fat mass index (kg/m2) and lean mass index (kg/m2) were calculated by dividing the measures by height2. Fat-to-lean mass ratio and android-to-gynoid fat mass ratio were derived.
The anthropometric measures of height, weight, and waist circumference were measured by the nurses using standard protocols at ages 60–64 years at both CRFs and home visits and at 69 years at the home visits. BMI (defined as weight (kg)/height(m)2) was calculated.
Bridger Staatz C, & Hardy R. (2019). Number of children and body composition in later life among men and women: Results from a British birth cohort study. PLoS ONE, 14(5), e0209529.
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8

Body Composition Measurement in Older Adults

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Waist and hip circumferences were measured at ages 60–64 and waist-hip ratio was defined as (waist circumference (cm)/ hip circumference (cm)×100%. Body composition was measured using a QDR 4500 Discovery DXA scanner (Hologic Inc, Bedford, MA, USA) at age 60–64 in the CRF; to optimise precision, scans were reviewed and centrally analysed (in Manchester) by a single operator (JA) using APEX 3.1 software (Hologic Inc., Bedford, MA, USA)[23 (link)]. Measures of fat (whole body, android and gynoid) and lean mass (whole body and appendicular) were obtained and converted into kilograms. Fat/lean ratio was derived and multiplied by 100.
Cao Y., Hardy R, & Wulaningsih W. (2019). Associations of medical conditions, lifestyle and unintentional weight loss in early old age: The 1946 British Birth Cohort. PLoS ONE, 14(4), e0211952.
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9

DXA-Based Body Composition Assessment

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Whole body (excluding head because of hair weaves) composition was assessed by dual x-ray absorptiometry (DXA) using standard techniques. All scans were conducted by a qualified technician on a Hologic QDR 4500 A machine when participants were 21+ years old to estimate bone mineral content (BMC), fat-free mass (FFM), fat mass (FM), abdominal visceral adipose tissue (VAT), and abdominal subcutaneous adipose tissue (SAT). Fat-free soft tissue mass (FFSTM) was calculated as the difference between FFM and BMC, while the fat mass index (FMI) and fat-free soft tissue mass index (FFMI) were calculated by dividing FM (kg) and FFSTM (kg) by the square of height (m 2 ), respectively. These scans were analysed using Hologic APEX 3.1 software [21] . A spine phantom was used for daily calibration, and coefficients of variation during the course of the study were less than 1% for total FM and FFSTM respectively. DXA-determined VAT and SAT were computed as described previously [21] . SAT was estimated by summing the subcutaneous fat measured from the DXA image on each side of the abdominal cavity, and subcutaneous fat overlying the abdominal cavity which was determined by modelling [21] . DXA-VAT was estimated by subtracting SAT from the total abdominal fat determined by DXA [21] .
Nyati L.H., Pettifor J.M., Ong K.K, & Norris S.A. (2023). The association between the timing, intensity and magnitude of adolescent growth and body composition in early adulthood. European journal of clinical nutrition.
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10

DXA Measurements for Body Composition

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DXA measurements were performed using a Hologic Discovery A DXA system with Apex 3.3 software (Hologic, Marlborough, Massachusetts, United States). Prior to scanning, participants removed all metal objects and lay supine on a padded table. Using the standard approach with DXA, a three-component model was utilized to quantify fat mass, lean soft tissue mass, and bone mineral content for each participant,22 (link) and these parameters were converted to fat percentage (fat%), lean soft tissue percentage (LST%), and bone (bone%), respectively, by dividing by total body mass, and the related equations are Total body mass=Fat mass+Lean soft tissue mass+Bone mass, Fat%=Fat massFat mass+Lean soft tissue mass+Bone mass, LST%=Lean soft tissue massFat mass+Lean soft tissue mass+Bone mass, and Bone%=Bone massFat mass+Lean soft tissue mass+Bone mass.
Only fat% and LST% were further analyzed in this study, as we did not expect DOSI to be sensitive to bone mineral content given the locations of our measurements and the probable penetration depths of NIR light.
Warren R.V., Bar-Yoseph R., Hill B., Reilly D., Chiu A., Radom-Aizik S., Cooper D.M, & Tromberg B.J. (2022). Diffuse optical spectroscopic method for tissue and body composition assessment. Journal of Biomedical Optics, 27(6), 065002.
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