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Matlab v13

Manufactured by MathWorks

MATLAB v13.0 is a software application for numerical computing and visualization. It provides a programming environment for algorithm development, data analysis, and visualization. MATLAB offers a wide range of mathematical functions, tools, and libraries for various scientific and engineering applications.

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Lab products found in correlation

4 protocols using matlab v13

1

Automated Morphomic Measurements in CT Scans

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Analytic morphomic measurements were performed in a semi-automated manner on collected CT scans using proprietary algorithms programmed in MATLABv13.0 (MathWorks, Natick, MA) according to established methods.28 (link) Briefly, the spinal column vertebral levels were mapped and then cross-sectional area of the left and right psoas muscles at the inferior aspect of the fourth lumbar vertebrae were summed to give the total psoas area. This was then adjusted for fatty infiltration of the muscle using density, measured in Hounsfield units, to yield lean psoas area (LPA).29 (link)
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2

Measuring Trunk Muscle Size via CT Scans

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As a measure of trunk muscle size, we calculated the total psoas area (TPA) from preoperative CT scans. We have previously described methods used to measure TPA.(7 (link), 26 (link)) Briefly, vertebral levels were identified on each patient’s CT scan to be used as anatomical landmarks. Using the transverse image at the L4 vertebral level, the left and right psoas muscles were outlined and the total area was calculated in centimeters. All image processing was performed using semi-automated algorithms programmed in MATLAB v13.0 (MathWorks, Natick, Mass). The population distribution of TPA in mm2 is depicted for males and females in Figure 2A and 2B, respectively. In order to analyze the TPA as a measure of sarcopenia in this study, we normalized the cross section by gender (because men have larger psoas muscles so naturally the cross-section is also larger for the same degree of sarcopenia). Therefore, we expressed our units of TPA in standard deviation units, for each patient’s psoas muscle size compared to the mean within their own gender (Figure 2C). This additional calculation also obviated the need to additionally control for gender.
Last, we also expressed TPA in tertiles in order to more easily display the results in terms of patients with small, medium, and large psoas muscle size.
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3

Quantifying Abdominal Visceral Fat and Total Psoas Area

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CT scans were processed using semi-automated algorithms programmed into MATLAB v13.0 (MathWorks; Natick, MA). After identifying individual vertebral levels on each patient’s CT scan, the deep fascia was traced at each level, as shown in Figure 1. Using automated methods, each pixel within the area encompassed by the fascia was sampled for its radiologic density (in Hounsfield Units [HU]). Those pixels which were sampled to be in the density range of fat were designated as abdominal visceral fat, and the sum of the pixels were termed the visceral fat area. The visceral fat area from T12 through L4 was averaged for each patient and served as the primary exposure variable for this study. Additionally, total psoas area (TPA) was measured as described in our previous work.(9 (link)–12 (link)) Briefly, the cross-sectional areas of the left and right psoas muscles at the level of L4 were measured.
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BP Data Pre-processing Workflow

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We applied the following data pre-processing steps to BP data using custom written software (MATLAB® v13.0, The MathWorks Inc., Natick, MA, 2000): a) artefact rejection; b) 10-second moving average filtering; and c) feature extraction, as described in detail previously (18) (link).
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