Amira avizo software

Resin-embedded tissue blocks were trimmed, mounted on SEM stubs, and then coated with a 5 nm platinum layer using a Q150T-ES sputter coater (Quorum Technologies, UK) before FIB-SEM volume imaging. Data was acquired using Scios Dual beam microscope (FIB-SEM) (Thermo Fischer Scientific). Electron beam imaging was acquired at 2 kV, 0.1 nA current, 1.9 × 1.9 nm pixel spacing, 7 mm working distance, 10 µs acquisition time, and 3072 × 2048 resolution using a T1 detector. SEM images were acquired every 20 nm. The working voltage of gallium ion beam was set at 30 kV, and 0.5 nA current was used for FIB milling. The specimens were imaged at 5 × 5 µm block face and 5 µm depth. FIB milling and SEM imaging were automated using the Auto Slice and View software (v4.1.1.1582, Thermo Fischer Scientific). SEM volume images were aligned and reconstructed using ImageJ (v. 1.8.0_172, NIH) with linear stack alignment, with SIFT and MultiStackRegistration plugins^{77 ,78} . Analysis and segmentation of SEM volume images were done using Amira-Avizo software (v2020.3.1, Thermo Fisher Scientific).

The distal muscle volumes were evaluated by manual segmentation of muscle regions of interest (ROIs) using the Amira-Avizo Software (V6; Thermo Scientific, Waltham, MA, United States). ROIs included the four heads of the quadriceps femoris (vastus medialis, vastus lateralis, vastus intermedius, rectus femoris), the hamstrings (biceps femoris, semimembranosus, semitendinosus), gracilis and sartorius muscles. The segmented muscle volume spanned a distal thigh section of 87.7 ± 2.8 mm (18 ± 0.57 slices) and was standardized relative to the patients’ femur length, defined as distance between the top of the greater trochanter and the lower border of the lateral femoral condyle. This ensured that a comparable muscle volume was analysed in each patient, regardless of body size or leg length. Intramuscular fat content of the muscle ROIs was quantified on the four most superior contiguous axial CT-slices of the investigated thigh region with the software Image J (V1.51; U.S. National Institutes of Health, Bethesda, MD, United States). A voxel-based analysis of muscle density was performed using predefined Hounsfield unit (HU) threshold values to differentiate intramuscular fat (−190 to −30 HU) and skeletal muscle tissue (−29 to 150 HU) (Aubrey et al., 2014 (link)).

OPT images with viral signal and autofluorescence signal were reconstructed in DICOM format using NRecon software (v.1.7.0.4, Bruker) followed by their conversion into NifTi using PMOD VIEW tool (v.4.2, PMOD Technologies Inc., Switzerland) or the dcm2nii tool in MRIcron software for OPT and MR images, respectively. Coregistration and normalization of OPT with the OCUM MRI template was performed using the toolbox SPMmouse in SPM8. All transformation matrices were calculated using individual tissue autofluorescence from OPT images and applied to the corresponding viral OPT images²¹ . The accuracy of all transformations were assessed visually by two individual readers in the check registration tool of SPM8. Fusion images of viral OPT signal were created for each individual brain using its own MRI and with the OCUM template²¹  using the PMOD VIEW tool or Amira-Avizo software (v6.3.0, Thermo Fisher Scientific) for 3D renderings. Finally, brain areas with viral signal were identified according to the OCUM atlas²¹ .