3D-CT scans were obtained by two types of the 16 channel CT scanning equipment (GE ULTRA 16, GE Healthcare, Milwaukee, WI, USA; Siemens Somatom Sensation 16, Siemens, Erlangen, Germany). The slice intervals were at 0.6 mm and 0.62 mm, while the angle was at 0.1° with the precision of 0.1 mm in length. The tomographic images were reconstructed using Advantage Windows 4.1 of the GE Medical System to obtain 3D transparent images. In order to investigate the cross-sectional areas and short width of the safe zones along different angles, we used the oblique sagittal images on multiplanar reformation images that consisted of the axial, sagittal, coronal, and oblique sagittal images in the same screen (Fig. 1 ). The oblique sagittal images could be simultaneously generated after choosing the points and cross section on the axial image, and their cross sections were shown perpendicular to the sliced plane.
Somatom sensation 16
Manufactured by Siemens
Sourced in Germany, United States, Japan, Netherlands
The Somatom Sensation 16 is a 16-slice computed tomography (CT) scanner manufactured by Siemens. It is designed to capture high-quality images of the human body. The Somatom Sensation 16 utilizes advanced technology to provide efficient and reliable imaging solutions for healthcare professionals.
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Lab products found in correlation
Somatom definition flash, by Siemens (25 mentions)
Somatom sensation 64, by Siemens (23 mentions)
Somatom definition as, by Siemens (19 mentions)
Lightspeed vct, by GE Healthcare (16 mentions)
Brilliance 64, by Philips (10 mentions)
Ultravist, by Bayer (10 mentions)
Somatom definition edge, by Siemens (9 mentions)
Aquilion 64, by Toshiba (8 mentions)
Brilliance ict 256, by Philips (7 mentions)
Discovery ct750 hd, by GE Healthcare (6 mentions)
Care dose 4d, by Siemens (5 mentions)
Somatom force, by Siemens (5 mentions)
Ge discovery ct750 hd, by GE Healthcare (5 mentions)
Ultravist 370, by Bayer (5 mentions)
Centricity 2, by GE Healthcare (4 mentions)
Somatom definition, by Siemens (4 mentions)
Definition flash, by Siemens (4 mentions)
Volume wizard diagnostic station, by Siemens (4 mentions)
Brilliance 16, by Philips (4 mentions)
Ultravist 300, by Bayer (4 mentions)
222 protocols using somatom sensation 16
1
3D-CT Scan Reconstruction and Analysis
2
Abdominal CT Imaging Protocol
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All CT scans were acquired using multi-slice CT equipment (Philips Brilliance 64, Philips Medical Systems, Best, The Netherlands; Siemens Somatom Sensation 16 or Somatom Definition Flash, Siemens Healthcare, Erlangen, Germany). PVP images of the liver/abdomen were obtained with a tube voltage of 100-120 kVp. The contrast medium (Ultravist 300 mgI/ml; Iopromide, Bayer Healthcare, Berlin, Germany) was prewarmed to 37 °C (99°F) and administered intravenously as a bolus injection of 110 ml at a rate of 3.5 ml/s, followed by a saline flush of 40 ml. The scan delay for the PVP was set at 70 s. Images were reconstructed in transverse plane using iterative reconstruction (Siemens Somatom Definition Flash) or filtered backprojection (Philips Brilliance 64/Siemens Somatom Sensation 16) with a soft tissue filter. Slice thickness was 3 or 5 mm.
3
Magnetic Microbubble for MR Imaging
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The diagnostic potential of magnetic microbubble was investigated through in vitro MR imaging using 0.3 Tesla MRI machine SIEMENS SOMATOM Sensation 16. Agar phantom was made containing falcons of plain microbubbles and magnetic microbubbles with different Fe concentrations. For comparison with control Gadovist at high concentration was used to get negative contrast effect on T2. Samples were imaged using head-coil and spin-echo sequences to acquire T1 & T2 weighted images. T1 images were taken with TR = 519 ms and TE = 11 ms while for T2 images, TR was 8190 ms and TE = 117 ms for T2 weighted images, slice thickness 6 mm, and FS 0.19. The MR images intensities were calculated by using micro DICOM viewer.
4
Quantifying Coronary Artery Calcification from LDCT
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MILD trial baseline LDCT images were acquired on a 16–detector row CT scanner (Somatom Sensation 16; Siemens Medical Solutions, Forchheim, Germany), while BioMILD trial baseline LDCTs were acquired on a second-generation dual-source CT scanner (Somatom Definition Flash, Siemens Medical Solutions, Forchheim, Germany). Details on LDCT acquisition and imaging interpretation have been reported elsewhere [25 (link),26 (link)].
LDCT images were transferred to a dedicated graphic station (Alienware Area 51 R6 equipped with Dual NVIDIA GeForce RTX 2080 ◦C graphics), and CAC was automatically evaluated using commercially available AI-based software (AVIEW, Coreline Soft, Seoul, Korea). CAC was assessed based on the Agatston score and stratified as follows: 0, 1–10, 11–100, 101–400, and > 400 [22 (link),23 ,27 (link),28 ].
LDCT images were transferred to a dedicated graphic station (Alienware Area 51 R6 equipped with Dual NVIDIA GeForce RTX 2080 ◦C graphics), and CAC was automatically evaluated using commercially available AI-based software (AVIEW, Coreline Soft, Seoul, Korea). CAC was assessed based on the Agatston score and stratified as follows: 0, 1–10, 11–100, 101–400, and > 400 [22 (link),23 ,27 (link),28 ].
5
Murine Lewis Lung Carcinoma Imaging
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Mouse Lewis lung carcinoma cell line (LLC) was purchased from Shanghai Cell Bank of Chinese Academy of Sciences. The MPE mouse model (C57BL/6J, six-week-old, male; Model Animal Research Center of Nanjing University) has been previously described (18 (link), 20 (link)) ( Figure S1 ) . Mice were reportedly administered with an intrathoracic injection of 200μg anti-PD1 mAb (InVivoMab anti-mouse PD-1 (CD279), Bioxcell)/0.9% normal saline on the 7th and 14th day of the model. We then injected 50 μL anti-CD8 mAb (4 mg/kg, InVivoPlus anti-mouse CD8A, Bioxcell) intraperitoneally multiple times to achieve CD8 depletion. The fixed mouse tissues were successively scanned using a CT machine (Siemens Somatom Sensation 16).
6
Preoperative Orbital Imaging Protocols
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Data from the preoperative orbital imaging examinations were retrospectively analyzed. Of the 91 included patients, 73 underwent CT scans, 43 underwent MRI scans, and 25 underwent both CT and MRI scans.
The CT scans were performed using various scanners (GE Medical Systems, GE Lightspeed VCT, GE Discovery CT750 HD, GE OPTIMA CT660, Siemens Somatom Sensation 16, Siemens Somatom Definition AS, Siemens Somatom Definition Edge, Siemens Somatom Definition Flash) with multidetector capabilities ranging from 16 to 128 channels. The techniques and parameters varied depending on the system used; however, most examinations were performed using a 128-channel CT scanner (Somatom Definition Flash; Siemens Medical Solutions). The detailed CT imaging protocols are described in theSupplement .
The MRI scans were performed using various 3T MRI scanners (Magnetom Skyra, Siemens; Achieva, Philips Medical Systems; Ingenia CX, Philips Medical Systems) with a 16- or 64-channel head and neck coil. However, most examinations were performed with a 3T MRI scanner (Magnetom Skyra, Siemens) with a 64-channel head and neck coil. The MRI protocol for head and neck tumors consisted of axial and coronal T1- and T2-weighted turbo spin-echo sequences with diffusion-weighted imaging and dynamic contrast-enhanced (DCE)-MRI. The detailed MRI protocols are described in theSupplement .
The CT scans were performed using various scanners (GE Medical Systems, GE Lightspeed VCT, GE Discovery CT750 HD, GE OPTIMA CT660, Siemens Somatom Sensation 16, Siemens Somatom Definition AS, Siemens Somatom Definition Edge, Siemens Somatom Definition Flash) with multidetector capabilities ranging from 16 to 128 channels. The techniques and parameters varied depending on the system used; however, most examinations were performed using a 128-channel CT scanner (Somatom Definition Flash; Siemens Medical Solutions). The detailed CT imaging protocols are described in the
The MRI scans were performed using various 3T MRI scanners (Magnetom Skyra, Siemens; Achieva, Philips Medical Systems; Ingenia CX, Philips Medical Systems) with a 16- or 64-channel head and neck coil. However, most examinations were performed with a 3T MRI scanner (Magnetom Skyra, Siemens) with a 64-channel head and neck coil. The MRI protocol for head and neck tumors consisted of axial and coronal T1- and T2-weighted turbo spin-echo sequences with diffusion-weighted imaging and dynamic contrast-enhanced (DCE)-MRI. The detailed MRI protocols are described in the
7
Evaluating Lung Nodule Detection Method
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In the present study, we evaluated our proposed method using chest CT scans from Wonkwang University Hospital (WKUH). For the clinical data, we collected chest CT digital imaging and communications in medicine (DICOM) images of 84 anonymous subjects, including 42 subjects with juxta-pleural nodules. Each scan included 150 to 215 image frames, and there were 16,873 images in total. Among the images, 314 included juxta-pleural nodules. The images were acquired at WKUH using a multiple detector computed tomography (MDCT) scanner (Somatom Sensation 16, Siemens, Erlangen, Germany; X-ray tube voltage: 100–120 kV; tube current: 80–328 mA; pixel length: 0.56–0.79 mm). The thickness of each slice was 5.0 mm. The WKUH Institutional Review Board approved the collection and analysis of the imaging data. To evaluate the performance of the model, “gold standard” lung contours were obtained from six trained radiologists. Initially, four trained radiologists drew the contours, and another two trained radiologists confirmed them.
8
3D Modeling of Piglet Anatomy
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CT analyses of the piglets were performed using a SOMATOM Sensation 16 CT scanner (Siemens AG, Munich, Germany). Piglets were subjected to CT after death. Each specimen was placed in a prone position, and noncontrast CT scans of sections 0.625-mm thick were obtained from vertical axial tomographs acquired at 0.625-mm intervals. Scan settings were 120 kVp, 400 mA, and a tube rotation time of 0.5 s. The grey-scale threshold was set to 75 to separate bone from the surrounding tissue using an adaptive threshold method. Three-dimensional (3D) models of the whole body were based on the 0.625-mm thick CT scan slices generated using Advantage Workstation 4.5 software (GE Healthcare, Waukesha, WI, USA).
9
Body Composition Assessment by DXA and CT
10
Robotic-Assisted Facet Joint Punctures
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In this phantom model study, we performed 40 facet joint punctures, 20 using a robotic targeting system and 20 using a freehand procedure, controlled by stepwise CT-scans. The primary endpoint of the study was the time required from planning the CT scan to the correct intra-articular placement of the 21-gauge puncture needle. Secondary endpoints were the accuracy of the needle placement, measured as axial and sagittal deviation, and the number of required needle adjustments.
Prior to the acquisition of a lateral topogram (Somatom Sensation 16, Siemens Healthcare, Forchheim, Germany), the phantom model (Siemens Healthcare, Forchheim, Germany) was immobilized in a vacuum fixation system (iSYS Medizintechnik GmbH, Kitzbühl, Austria). Segment and side of the punctured facet joints were randomized but identical for robotic navigated approach and freehand approach. An experienced interventional radiologist (more than 200 facet joint punctures per year) carried out the procedures. Time requirements, number of corrections, and needle deviation were documented in an Excel spreadsheet.
Prior to the acquisition of a lateral topogram (Somatom Sensation 16, Siemens Healthcare, Forchheim, Germany), the phantom model (Siemens Healthcare, Forchheim, Germany) was immobilized in a vacuum fixation system (iSYS Medizintechnik GmbH, Kitzbühl, Austria). Segment and side of the punctured facet joints were randomized but identical for robotic navigated approach and freehand approach. An experienced interventional radiologist (more than 200 facet joint punctures per year) carried out the procedures. Time requirements, number of corrections, and needle deviation were documented in an Excel spreadsheet.
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