Synapse vincent

Manufactured by Fujifilm

Sourced in Japan

SYNAPSE VINCENT is a high-performance medical imaging platform designed for use in healthcare facilities. It provides integrated solutions for the storage, management, and distribution of digital medical images and patient data. The core function of SYNAPSE VINCENT is to enable efficient and secure access to medical imaging information across various departments and locations.

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Lab products found in correlation

Aquilion 64, by Toshiba (3 mentions) Discovery ct750 hd, by GE Healthcare (3 mentions) Revolution ct, by GE Healthcare (2 mentions) Lightspeed vct, by GE Healthcare (2 mentions) Somatom definition as, by Siemens (1 mentions) Aquilion one, by Canon (1 mentions) Aquilion 32, by Toshiba (1 mentions) Omnipaque 300 mgi ml, by Daiichi Sankyo (1 mentions) Iqon spectral ct, by Philips (1 mentions) Aze virtual place, by Canon (1 mentions) Brightview, by Philips (1 mentions) T k k 5101 grip d, by Takei Scientific Instruments (1 mentions) Signa architect, by GE Healthcare (1 mentions) Aquilion precision, by Toshiba (1 mentions) Ingenia, by Philips (1 mentions) Eeg 1200, by Nihon Kohden (1 mentions) 16 slice multidetector row ct scanner, by Hitachi (1 mentions) Synapse vincent software, by Fujifilm (1 mentions) Aquilion 64, by Canon (1 mentions) Magnetom avantosq 1.5 t b 19, by Siemens (1 mentions)

Close spelling variants of this product

Synapse (45 citations) SYNAPSE VINCENT software (31 citations) Volume Analyzer SYNAPSE VINCENT (17 citations) SYNAPSE VINCENT software program (5 citations) Synapse Vincent System (5 citations) Synapse Vincent Ver. 3 and Ver. 5 (3 citations) SYNAPSE VINCENT image analysis system (3 citations) Volume Analyzer Synapse Vincent 3D image analysis system (3 citations) Synapse Vincent 3D workstation (2 citations) Synapse Vincent ver.4 (2 citations)

137 protocols using synapse vincent

3D Volumetry for Drained Liver Volume Calculation

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We developed a novel method to calculate DLV (3D volumetry) using a 3D volume analyzer (The Synapse Vincent; Fujifilm). This method comprised the following steps: (1) transfer of CT images (axial view) to the 3D imaging system; (2) manual tracing of bile duct using CT images (Fig. 1a); (3) 3D reconstruction of bile duct and liver parenchyma (Fig. 1b); and (4) calculation of DLV by the biliary stents according to the 3D distribution of bile ducts (Fig. 1c). At least 2 gastroenterologists specialized in the bile ducts calculated DLV by using this method.
Fig. 1

Three-dimensional (3D) volumetry for calculating drained liver volume. We used a 3D volume analyzer (The Synapse Vincent; Fujifilm) to calculate the drained liver volume. (a) Manual tracing of bile duct using CT images. (b) Three-dimensional reconstruction of the bile duct and liver parenchyma. (c) Calculation of DLV according to the 3D distribution of bile duct and Bismuth classification. The stent is inserted into the anterior hepatic duct. Each DLV is calculated as the volume of the yellow area in Bismuth classifications IIIa (c1) and IIIb (c2)

Imagawa N., Fukasawa M., Takano S., Kawakami S., Fukasawa Y., Hasegawa H., Kuratomi N., Harai S., Shimamura N., Yoshimura D., Kobayashi S., Yoshida T., Sato M., Suzuki Y, & Enomoto N. (2024). A Novel Method of Calculating the Drained Liver Volume Using a 3D Volume Analyzer for Biliary Drainage of Unresectable Malignant Hilar Biliary Obstruction. Digestive Diseases and Sciences, 69(3), 969-977.

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Cross-Sectional CT Imaging of Muscle Parameters

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For SMA or PA, a single axial image corresponding to the L3 vertebral body was selected and measured for each CT scan. Cross-sectional CT measurement of the SMA and PA within predefined validated boundaries of −29 to +150 Hounsfield units were measured by software (Synapse Vincent; Fujifilm Medical, Tokyo, Japan). SMA consisting of the abdominal muscles, psoas muscles, and para spinal muscles was demarcated. Selected PA only included the psoas muscle area (right and left). All recipients also underwent 3D-CT. Psoas major volume in the lesion by 3D-CT was measured using image recognition software (Synapse Vincent; Fujifilm Medical, Tokyo, Japan).

Matsubara Y., Nakamura K., Matsuoka H., Ogawa C, & Masuyama H. (2019). Pre-treatment psoas major volume is a predictor of poor prognosis for patients with epithelial ovarian cancer. Molecular and Clinical Oncology, 11(4), 376-382.

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Measuring Lung Capacity with CT Imaging

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Segmentation of pneumonia and the total lung capacity on CT (TLC_ct) were calculated on full-inspiratory CT using a SYNAPSE VINCENT volume analyzer (Fujifilm Medical, Tokyo, Japan),25 (link) and the predicted TLC_ct% was calculated based on the predicted values.26 (link) Representative images of the TLC_ct are shown in online supplemental figure 2.

Otake S., Shiraishi Y., Chubachi S., Tanabe N., Maetani T., Asakura T., Namkoong H., Shimada T., Azekawa S., Nakagawara K., Tanaka H., Fukushima T., Watase M., Terai H., Sasaki M., Ueda S., Kato Y., Harada N., Suzuki S., Yoshida S., Tateno H., Yamada Y., Jinzaki M., Hirai T., Okada Y., Koike R., Ishii M., Hasegawa N., Kimura A., Imoto S., Miyano S., Ogawa S., Kanai T, & Fukunaga K. (2024). Lung volume measurement using chest CT in COVID-19 patients: a cohort study in Japan. BMJ Open Respiratory Research, 11(1), e002234.

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Postoperative Bleeding Quantification

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Postoperative bleeding in CT scan images with 5 mm in thickness taken at postoperative day (POD) 1 was analyzed by a three-dimensional system volume analyzer, SYNAPSE VINCENT (Fujifilm, Tokyo, Japan), and the volume of the bleeding was calculated. In these images, subdural hemorrhage or hemorrhage in the excised cavity, which was the target for hemostasis of FLOSEAL, was evaluated. Extradural hemorrhage, where FLOSEAL is not adapted, was excluded from this measurement.

Kamamoto D., Kanazawa T., Ishihara E., Yanagisawa K., Tomita H., Ueda R., Jinzaki M., Yoshida K, & Toda M. (2020). Efficacy of a topical gelatin-thrombin hemostatic matrix, FLOSEAL®, in intracranial tumor resection. Surgical Neurology International, 11, 16.

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Lung Volume Loss Evaluation in Upright Chest X-Rays

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Lung volume loss was evaluated by measuring uVLL, lVLL, and tVLL in the right lung on chest X-rays taken in the upright position and at maximum inspiration (Fig. 2A–C). The data were adjusted for body height [VLLs (mm/m) = unadjusted VLLs (mm)/body height (m)]. The l/u VLL ratio was also calculated. The right (instead of the left) lung was evaluated to eliminate the possible effect of cardiac shadow. VLLs were evaluated by two independent investigators and the results are expressed as a mean of the two estimates. The extent of the reticular pattern, honeycombing, and GGO on chest CT images were semi-quantitatively evaluated as follows: grade 0 (0%), grade 1 (< 25%), grade 2 (25–50%), grade 3 (50–75%), and grade 4 (> 75%)^{29 (link)}. The definitions of reticular pattern, honeycombing, and GGO were according to the Fleishner Society criteria^{30 (link)}. The %LAA on chest CT images was calculated using image-analyzing software (SYNAPSE VINCENT; Fuji Film, Tokyo, Japan).

Karayama M., Aoshima Y., Yasui H., Hozumi H., Suzuki Y., Furuhashi K., Fujisawa T., Enomoto N., Nakamura Y., Inui N, & Suda T. (2021). Simple method for detecting idiopathic interstitial pneumonias by measuring vertical lung length on chest X-ray. Scientific Reports, 11, 7669.

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Tumor Size Measurement by CT Imaging

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The solid diameter was measured using thin-section CT images at 1-mm collimation or a 0.1 mm thick image of SYNAPSE VINCENT (FUJIFILM Corporation, Tokyo, Japan). The radiologic measurement of the tumor size, the single largest dimension measured, was performed using electronic calipers on thin-sections CT. For the maximum diameter, coronal and sagittal section measurements were used in addition to the CT cross section. Thoracic surgeons remeasured the tumor and invasion size at the pre-operative conference with reference to the CT report double-checked by two radiologists. We measured the maximum diameter of the tumor including a ground glass opacity (GGO) and a solid part only in the lung window.

Funai K., Kawase A., Mizuno K., Koyama S, & Shiiya N. (2020). 8th Edition Tumor, Node, and Metastasis T-Stage Prognosis Discrepancies: Solid Component Diameter Predicts Prognosis Better than Invasive Component Diameter. Cancers, 12(6), 1577.

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3D Liver Vasculature Visualization and Analysis

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The conditions of contrast‐enhanced CT were as follows. After a series of scans without a contrast agent, 630 mg/kg of nonionic iodine was administered via the antecubital vein at 30 sec with a power injector. Then scanning was performed in the early arterial, late arterial, and portal phases (25, 35, and 60 sec after contrast injection, respectively). In all phases, the slice thickness was 0.625 mm. The MDCT datasets were transferred to a workstation for 3D image analysis using software (Synapse Vincent; Fujifilm, Tokyo, Japan). The liver parenchyma was semiautomatically extracted from consecutive MDCT images. Three‐dimensional, volume‐rendered images of the portal vein and hepatic vein were generated from the late arterial or portal phase data using the automatic algorithm of the software. Three‐dimensional images of the portal vein, hepatic vein, and liver parenchyma were reconstructed individually and then overlapped to create integrated 3D images. The vascular perfusion area of the tertiary branch of the right anterior portal vein was calculated using software, and the ramification pattern of the right anterior portal vein was evaluated.

Ishii N., Harimoto N., Kogure K., Araki K., Hagiwara K., Tsukagoshi M., Igarashi T., Watanabe A., Kubo N, & Shirabe K. (2022). Study on the portal ramification pattern of the right anterior sector of the liver and a unique medial branch (PV8c) of the right anterior portal vein. Annals of Gastroenterological Surgery, 6(5), 679-687.

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Visual Scoring of Epileptic Zone Boundary

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The observers also evaluated the boundary of the lesion using a 4-point visual score. We used the modified Paldino et al method [9 (link)]. The various scores were defined as follows:

Score 4: clear detection of EZ in terms of both laterality and border

Score 3: clear detection of EZ laterality, but a border that was a little obscure

Score 2: possible detection of EZ laterality and an unclear border

Score 1: poor quality for detection of EZ laterality and border

The observers were able to easily adjust the window level and window width, as well as the degree of transparency using the workstation (SYNAPSE VINCENT; Fujifilm Medical).

Kikuchi K., Togao O., Yamashita K., Momosaka D., Nakayama T., Kitamura Y., Kikuchi Y., Baba S., Sagiyama K., Ishimatsu K., Kamei R., Mukae N., Iihara K., Suzuki S.O., Iwaki T, & Hiwatashi A. (2020). Diagnostic accuracy for the epileptogenic zone detection in focal epilepsy could be higher in FDG-PET/MRI than in FDG-PET/CT. European Radiology, 31(5), 2915-2922.

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Evaluating Skeletal Muscle Mass and Quality Using CT Scans

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Skeletal muscle mass was evaluated using the skeletal muscle mass index (SMI) on CT scans. The SMI was calculated as follows: The sum of the cross-sectional area of skeletal muscles at the level of the third lumbar vertebra (L3) was measured by a radiological technologist using a region of interest (ROI) precisely traced with the use of commercially available image analysis software (volume analyzer SYNAPSE VINCENT, Fujifilm Medical Co., Ltd.), and this value was divided by height squared (cm²/m²) (4 (link)). To evaluate the yearly change in SMI, ΔSMI/year (%) was calculated as follows: ΔSMI/year (%) = [(SMI on the second CT-SMI on the initial CT)/SMI on the initial CT x100/interval between CT (day)/365] (19 (link)). CT was typically conducted in patients with CLD every 6-12 months according to the guidelines of the Japan Society of Hepatology (20 ).
Muscle quality was examined as IMAC at the L3 level. As previously described, IMAC was calculated by dividing the CT attenuation value of the multifidus muscles by that of the subcutaneous fat (21 (link)). To evaluate the yearly change in IMAC, ΔIMAC/year was calculated as follows: ΔIMAC/year = [IMAC on the second CT-IMAC on the initial CT]/[interval between CT (day)/365].

Ohashi K., Ishikawa T., Hoshii A., Hokari T., Suzuki M., Noguchi H., Hirosawa H., Koyama F., Kobayashi M., Hirosawa S., Sugiyama K., Mitobe Y, & Yoshida T. (2020). Effect of levocarnitine administration in patients with chronic liver disease. Experimental and Therapeutic Medicine, 20(5), 94.

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Preoperative Imaging of Pulmonary Vasculature

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All patients were examined preoperatively using 64-slices/rotation computed tomography (SOMATOM Definition AS +; Siemens Healthineers AG, Erlangen, Germany). We used the 3-dimensional image analysis system, Synapse Vincent (Fujifilm Co, Tokyo, Japan), to create 3-dimensional models of the pulmonary blood vessels and bronchia, and identify the dominant blood vessels and regional bronchi in the target area for reference.

Misaki N., Tatakawa K., Chang S.S., Go T, & Yokomise H. (2020). Constant-rate intravenous infusion of indocyanine green leading to high fluorescence intensity in infrared thoracoscopic segmentectomy. JTCVS Techniques, 3, 319-324.

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