Mice were imaged at 5 min, 24 h, 48 h and 72 h p.i. A group of mice imaged at 72 h p.i. was used for the 72 h p.i. time of biodistributions. Mice were maintained under general anaesthesia with a mixture of 2% isoflurane and 5% air for the duration of the acquisition. Image acquisition was performed with the IRIS PET-CT imager (Iris, Inviscan, Strasbourg France) using a 10-min static whole-body acquisition mode combined with a 20-s CT acquisition (energy window of 250-750 keV and FOV size of 90 mm). The CT acquisition parameters were 80 kV, 0.9 mA, 576 projections and 160 µm voxel size. Filtered back-projection algorithm with beam hardening and ring artefact correction was used. PET images were reconstructed with the 3D Ordered Subsets Expectation Maximization (3D-OSEM-MC,) algorithm, 8 subsets, 8 iterations with correction of decay, random and dead-time. PET and CT were converted into DICOM format and processed with OsiriX Medical Imaging software (version 11.0.1, Pixmeo, Bernex, Switzerland).
Osirix medical imaging software
Manufactured by Pixmeo
Sourced in Switzerland
OsiriX Medical Imaging Software is a powerful digital imaging and communication in medicine (DICOM) viewer designed for radiological images. It allows healthcare professionals to view, process, and analyze medical images from various imaging modalities, including CT, MRI, PET, and ultrasound. The software provides a comprehensive set of tools for visualization, manipulation, and interpretation of medical images, enabling efficient diagnosis and treatment planning.
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Lab products found in correlation
8 protocols using osirix medical imaging software
1
Multimodal Imaging of Mouse Biodistribution
2
Carotid Siphon Calcification Grading Protocol
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Imaging studies were performed with a Philips Brilliance 64 CT scanner (Philips Medical Systems, Eindhoven, the Netherlands). Slice thickness was 3 mm with no gap between slices. CT digital images were viewed using the Osirix Medical Imaging software (Pixmeo, Geneva, Switzerland) with the bone windows setting to grade carotid siphon calcifications. As detailed elsewhere,13 (link)
Grade 1 was defined as the absence or near-absence of calcification, Grade 2 as tiny scattered calcifications, Grade 3 as thick interrupted or thin confluent calcifications, and Grade 4 as thick contiguous calcifications. Individuals were further classified into those with low (Grades 1 and 2) and high (Grades 3 and 4) calcium content in carotid siphons. All scans were read by an experienced neurologist and a neuroradiologist. Kappa coefficients for inter-rater agreements were .81 for the presence of high calcium content in carotid siphons, and discrepancies were resolved by consensus.14 (link)
Grade 1 was defined as the absence or near-absence of calcification, Grade 2 as tiny scattered calcifications, Grade 3 as thick interrupted or thin confluent calcifications, and Grade 4 as thick contiguous calcifications. Individuals were further classified into those with low (Grades 1 and 2) and high (Grades 3 and 4) calcium content in carotid siphons. All scans were read by an experienced neurologist and a neuroradiologist. Kappa coefficients for inter-rater agreements were .81 for the presence of high calcium content in carotid siphons, and discrepancies were resolved by consensus.14 (link)
3
Tumor Volume Measurement on CT
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Regions of interest were outlined over the entire area of visible tumours on post-contrast CT scans (2 mm thin sections) by a radiologist (FS) using the OsiriX medical imaging software (Pixmeo SARL, Switzerland). Tumour volume was calculated by multiplying the area of tumour outlined on each CT image by the slice thickness.
4
Multimodal Imaging Analysis of Craniocervical Junction
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Image analysis included both CT and MR images. We used OsiriX Medical Imaging Software (Pixmeo SARL, Bernex, Switzerland) to analyze CT images for the NASs and TFAs. For MR image analysis, each evaluator used imaging software available to them and included determination of whether SM or fourth ventricle dilatation was present. In the instance of SM, we also measured the maximum transverse width of the syrinx. Furthermore, we measured lateral ventricular volumes and the severity of neural parenchymal deviation at the CCJ (caused by dorsal spinal cord compression and medullary elevation) as detailed below. Evaluators were, in all image evaluations, blinded to each other's findings and to other imaging modality (CT/MRI) analysis results.
5
Quantifying Lymph Node Drainage via SPECT/CT Imaging
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OsiriX medical imaging software (Pixmeo, Geneva, Switzerland) was used to measure total pixel values [15 (link)]. Measurements of the injection site and SNs were performed on the SPECT component of the SPECT/CT scan using a 3D region-growing tool with calculation of the pixel values. Besides the injection site, and the SN(s), the rest activity (higher-echelon nodes, spillage) was calculated. All calculated pixel values were combined resulting in the total pixel value on SPECT/CT.
Liver uptake as a result of shunting during the tracer administration was not taken into account because it could not be accurately determined in all patients; in the head-and-neck and penile cancer patients, the liver was not present in the field of view when performing lymphoscintigraphy and SPECT/CT imaging, and in the prostate cancer patients the liver was only partly present in the field of view.
Based on the measured total pixel values in the SPECT scan the percentage of drainage of the injected dose to an individual SN was calculated using the following formula:
Liver uptake as a result of shunting during the tracer administration was not taken into account because it could not be accurately determined in all patients; in the head-and-neck and penile cancer patients, the liver was not present in the field of view when performing lymphoscintigraphy and SPECT/CT imaging, and in the prostate cancer patients the liver was only partly present in the field of view.
Based on the measured total pixel values in the SPECT scan the percentage of drainage of the injected dose to an individual SN was calculated using the following formula:
6
Blinded Evaluation of Craniocervical Abnormalities
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Two board‐certified neurologists (C. Rusbridge, T.S. Jokinen), blinded to the presence or absence of CM/SM‐related clinical signs, independently evaluated the MR images for CM, SM, or other abnormalities that could cause similar clinical signs or affect cerebrospinal fluid flow. OsiriX Medical Imaging Software (Pixmeo SARL, Bernex, Switzerland) was used for analysis of the CT images of all included dogs for presence, number, location, and area of the PFs at dorsal, lateral, and caudal CSs. Two board‐certified neurologists (A.‐M. Kiviranta and T.S. Jokinen) independently evaluated the anonymized CT images and were hence unaware of any dogs' clinical status.
7
Cranial Suture Fontanelle Analysis
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OsiriX Medical Imaging Software (Pixmeo SARL, Bernex, Switzerland) served for analysis of the CT images of all included dogs for presence, number, and location of the PFs, and the fontanelle areas at dorsal, lateral, and caudal cranial sutures. Additionally, the total fontanelle area was calculated using the closed polygon tool of the software.
8
Multiparametric MRI Tumor Analysis
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The DCE-MRI parameter maps (K trans , K ep , V e , V p , Wash-in, Peak enhancement, and Wash-out) were fused with the T2-weighted axial images by use of OsiriX Medical Imaging Software (Pixmeo, Bernex, Switzerland). Volumes of Interest (VOIs) including the whole tumor volume were generated by a single reader (MHM, blinded to clinical and pathological data, 3 years of experience with rectal cancer MRI) who drew free hand regions of interests (ROI) around all visible tumor based on the anatomical T2-weighted images on each consecutive slice with visible tumor (i.e., intermediate signal intensity mass). ROIs were transferred to the various fusion maps. Any high-signal areas (indicating necrosis) were also included in the ROIs. On the restaging MRIs hypointense areas within the tumor bed (indicating fibrosis) were also included in the ROIs. A representative example of the delineation is shown in Fig. 1.
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