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Syngo multimodality workplace software

Manufactured by Siemens
Sourced in Germany

Syngo Multimodality Workplace software is a medical imaging software platform developed by Siemens. It provides a unified interface for viewing and analyzing images from various imaging modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET).

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5 protocols using syngo multimodality workplace software

1

Dual-Source CT Imaging of Pancreas

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Participants were imaged on a 64-slice dual-source CT scanner (Siemens Somatom Definition DS, Erlangen, Germany) after allergy testing of the contrast agent and fasting for 12 hours. After a plain scan was completed, a 2-mL/kg dose of nonionic iodinated contrast medium (Iodixanol; Yangtze River Pharmaceutical, Taizhou, China) was injected through a 16- or 18-gauge catheter into an antecubital vein at a flow rate of 5 mL/s. This was followed by a chaser bolus of 40 mL of saline solution. Images were obtained separately in the arterial phase (the delay time was determined by bolus-tracking software, generally at 20 to 25 s after injection, according to the time of abdominal aortic enhancement), portal venous phase (45 s after the first acquisition), and delayed phase (120 s after the first acquisition). The scanning parameters were as follows: collimation, 128 rows × 0.6 mm; section thickness, 5 mm; 120 kVp; and effective tube current-time charge, 200 mA. Coronal reconstructions were performed with a section thickness of 2 mm. Additionally, thin sections measuring 1 mm were obtained, and the acquired images were transferred to a workstation (Syngo Multimodality Workplace software; Siemens) to create high-resolution curved planar reformatted images of the pancreas.
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2

Standardized 18F-FDG PET/CT Imaging Protocol

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The baseline 18F-FDG PET/CT studies performed at our institution were
acquired with the protocol described below. All of the baseline scans were
performed within the last 30 days prior to percutaneous ablation.
Patients were required to fast for 6 h prior to the injection of
18F-FDG, in order to achieve a blood glucose level below 140 mg/dL.
All patients received 18F-FDG at a dose of 7.77 MBq/kg (0.21 mCi/kg)
while resting in a dark, quiet room.
Whole-body PET/CT scans were acquired 60 min after 18F-FDG injection.
The images were acquired on a high-resolution imaging platform (Biograph
TruePoint; Siemens Medical Solutions, Knoxville, TN, USA) with lutetium
oxyorthosilicate crystal detectors, 16-slice CT detectors, and a spatial
resolution of 4.2 mm. The image post-processing was performed with Syngo
MultiModality Workplace software (Siemens Medical Solutions). The PET images
were acquired after the CT images (5 min per bed position). Images were
submitted to iterative reconstruction in the axial, coronal, and sagittal
planes, CT being used for attenuation correction. The maximum SUV
(SUVmax), was calculated for each lesion. Two experienced nuclear
medicine physicians and a radiologist analyzed the images. Discordant findings
were reviewed by a third experienced nuclear medicine physician.
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3

Zirconium-89 PET/CT Imaging in Macaques

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PET/CT imaging of male crab-eating macaque (Charles River) was performed with a Siemens Biograph64 mCT PET/CT system. PET images were acquired at 1, 24, 72, 144, 216, and 384 h after intravenous injection (IV) of 10 mg of 2.50 mCi (92.5 MBq) [89Zr]hu11B6. Whole body acquisitions consisting of six bed positions covering from the crown of the animal’s head to mid-tibia. The head and feet were scanned with 4 min per bed, while the beds over the pelvic region were scanned with 14 min per bed, for a total imaging time (including gaps between scans) of about 44 min. Animals were maintained under 2% isoflurane/oxygen anesthesia during the scanning. Data was exported in raw format and the rigid body (3 degrees of freedom) co-registration between PET and CT data was performed in Amira 5.3.3 (FEI). Amira and FIJI were used to produce the majority of the figures in the manuscript. Siemens Syngo MultiModality Workplace software (version VE40A) was used to analyze and quantify [89Zr]hu11B6 uptake on PET images.
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4

Quantifying Visceral Adiposity from CT Scans

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Patients undergoing multi-row spiral CT (Siemens products) were instructed to hold their breath during the scan. The scanning range was from the diaphragm to the pelvic floor, which was reconstructed using the B30f algorithm. We measured the umbilical fat and skeletal muscle areas on the available CT scan images. The edges of skeletal muscle and adipose tissue at this layer were manually delineated on a GE ADW 4.6 workstation using the syngo MultiModality Workplace software (Siemens Healthineers AG, Forchheim, Germany). The CT values for skeletal muscle and adipose tissue were set at -29 to 150 HU and -150 to -50 HU, respectively; the software calculated the area of each part within the set range (18 (link)). According to the Japan Society for the Study of Obesity and widely accepted clinical criteria, the threshold for visceral adiposity measured at the umbilical level on CT images is 100 cm2. Patients with umbilical level VFA ≥ 100 cm2 were considered to have high-VFA, whereas those with VFA < 100 cm2 were considered to have low-VFA (Figure 1).
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5

Sarcopenia Prevalence in Gastric Cancer

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Sarcopenia was defined as low muscle mass, strength, and/or physical performance. Previous studies have shown that lumbar triplane skeletal muscle index (L3 SMI) on CT is the gold standard for estimating muscle quality (25 (link)). After professional training, imaging physicians identified and measured the muscle area of the L3 plane and divided it by the height squared (m2) to obtain the skeletal muscle index of L3 SMI (cm2/m2) on the syngo Multimodality Workplace software (Siemens Medical Solutions, Forchheim, Germany).
Studies have shown that the median prevalence of sarcopenia in patients with gastric cancer is approximately 35.7% (14 (link)). Therefore, in this study, we used a median of 35.7% for grouping. In all the medical records collected,  ≤ 35.7% of both sexes were classified as the sarcopenia group and >35.7% as the non-sarcopenia group. A data collection flowchart is presented in Figure 1.
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