TY - JOUR
T1 - CAS3D
T2 - 3D quantitative morphometry on Second Harmonic Generation image volumes from single skeletal muscle fibers
AU - Schneidereit, Dominik
AU - Bauer, Julian
AU - Mnuskina, Sofia
AU - Nübler, Stefanie
AU - Cacciani, Nicola
AU - Mühlberg, Alexander
AU - Kreiss, Lucas
AU - Ritter, Paul
AU - Schürmann, Sebastian
AU - Larsson, Lars
AU - Friedrich, Oliver
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/8
Y1 - 2024/8
N2 - The CAS3D image processing method intuitively applies a combination of Fourier space and real space 3D analysis algorithms to volumetric images of single skeletal muscle fiber Myosin II Second Harmonic Generation (SHG) XYZ image data. Our developed tool automatically quantifies the myofibrillar orientation in muscle samples by determining the cosine angle sum of intensity gradients in 3D (CAS3D) while determining the mean sarcomere length (SL) and sample orientation. The expected CAS3D values could be reproduced from ideal artificial data sets. Applied random noise in artificial images lowers the detected CAS3D value, and for noise levels below 20%, the correlation can be approximated by a linear function with a slope of −0.006 CAS3D/noise%. The deviations in SL and orientation detection were determined on ideal and noisy artificial data sets and were statistically indistinguishable from 0 (null hypothesis t-test P > 0.1). The software was applied to a previously published data set of single skeletal muscle fiber volumetric SHG image data from a rat intensive care unit (ICU) model of ventilator-induced diaphragm dysfunction (VIDD) with treatment regimens involving the small anti-inflammatory molecules BGP-15, vamorolone, or prednisolone. Our method reliably reproduced the results of the previous work and improved the standard deviation of the cosine angle sum detection in all sample groups from a mean of 0.03 to 0.008. This improvement is achieved by applying analysis algorithms to the whole volumetric images in 3D in contrast to the previously common method of slice-wise XY analysis.
AB - The CAS3D image processing method intuitively applies a combination of Fourier space and real space 3D analysis algorithms to volumetric images of single skeletal muscle fiber Myosin II Second Harmonic Generation (SHG) XYZ image data. Our developed tool automatically quantifies the myofibrillar orientation in muscle samples by determining the cosine angle sum of intensity gradients in 3D (CAS3D) while determining the mean sarcomere length (SL) and sample orientation. The expected CAS3D values could be reproduced from ideal artificial data sets. Applied random noise in artificial images lowers the detected CAS3D value, and for noise levels below 20%, the correlation can be approximated by a linear function with a slope of −0.006 CAS3D/noise%. The deviations in SL and orientation detection were determined on ideal and noisy artificial data sets and were statistically indistinguishable from 0 (null hypothesis t-test P > 0.1). The software was applied to a previously published data set of single skeletal muscle fiber volumetric SHG image data from a rat intensive care unit (ICU) model of ventilator-induced diaphragm dysfunction (VIDD) with treatment regimens involving the small anti-inflammatory molecules BGP-15, vamorolone, or prednisolone. Our method reliably reproduced the results of the previous work and improved the standard deviation of the cosine angle sum detection in all sample groups from a mean of 0.03 to 0.008. This improvement is achieved by applying analysis algorithms to the whole volumetric images in 3D in contrast to the previously common method of slice-wise XY analysis.
KW - 3D image analysis
KW - Quantitative morphometry
KW - Second harmonic generation
KW - Skeletal muscle
KW - Software automation
UR - https://www.scopus.com/pages/publications/85196732781
UR - https://res.slu.se/id/publ/aa7a74c2-2866-425a-a1bb-36e93b7c1067
U2 - 10.1016/j.compbiomed.2024.108618
DO - 10.1016/j.compbiomed.2024.108618
M3 - Journal article
C2 - 38925088
AN - SCOPUS:85196732781
SN - 0010-4825
VL - 178
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
M1 - 108618
ER -