Synapse 3d

Manufactured by Fujifilm

Sourced in Japan, United States

Synapse 3D is a software solution developed by Fujifilm for medical image visualization and analysis. It provides healthcare professionals with tools to view, manipulate, and analyze three-dimensional medical images, such as those obtained from CT, MRI, and PET scans. The software is designed to enhance diagnostic capabilities and support clinical decision-making.

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Lab products found in correlation

Matlab, by MathWorks (2 mentions) Objet500 connex3, by Stratasys (1 mentions) Synapse pacs, by Fujifilm (1 mentions) Magnetom skyra, by Siemens (1 mentions) Signa excite hdxt 3.0 t mr scanner, by GE Healthcare (1 mentions) Leonardo console, by Siemens (1 mentions)

14 protocols using synapse 3d

3D Printed Patient-Specific Kidney Model

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From the DICOM data of patient’s MDCT, kidney structures of interest (tumor, healthy parenchyma, arterial tree, renal vein, collecting system) were extracted using an image recognition algorithm (Synapse 3D, Fujifilm, Tokyo, Japan) and transferred into STL format. Using this STL file, a 3D printed model was created on the OBJET 500 Connex 3 (Stratasys, Eden Prairie, MN, USA) with the assistance of a 3D printing manufacturing company (Fasotec, Makuhari, Chiba, Japan).
The color-segmented 3D model was manufactured by the combination of three different types of photopolymer materials (opaque magenta, opaque yellow and transparent clear material) with 16 μ thickness of each layer under solidification by UV.
As displayed in Figs. 1, 2 and 3, the arterial tree was represented in opaque magenta, the collecting system in opaque yellow and mixing magenta and yellow resulted in opaque orange for tumor display. The renal parenchyma and the renal vein were kept translucent to achieve the best visualization of the relationships between the tumor, the collecting system and the arterial branches.

Bernhard J.C., Isotani S., Matsugasumi T., Duddalwar V., Hung A.J., Suer E., Baco E., Satkunasivam R., Djaladat H., Metcalfe C., Hu B., Wong K., Park D., Nguyen M., Hwang D., Bazargani S.T., de Castro Abreu A.L., Aron M., Ukimura O, & Gill I.S. (2015). Personalized 3D printed model of kidney and tumor anatomy: a useful tool for patient education. World journal of urology, 34(3), 337-345.

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Airway Morphometry Measurements from CT

Cited 2 times

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This study aims to measure three parameters of the airways: airway length(in mm), AWT(in mm), and ALA(in mm²). Specifically, we assessed the length of seven major airway sites, which include the trachea, right main bronchus(RMB), right superior lobe bronchus(RSLB), right middle lobe bronchus(RMLB), left main bronchus(LMB), left superior lobe bronchus(LSLB), and left inferior lobe bronchus(LILB). Following our established guidelines for dividing the central airway (Figure S2) [15 (link)], we measured the AWT and ALA at seven specific locations, including zones I to III and V to VIII (midpoint position of each zone) within the central airway. Additionally, we quantified the SCA (in degrees).
Airway parameters were measured in the study through 3D reconstruction of the airway tree from CT images using SYNAPSE 3D, an image analysis software developed by Fujifilm Medical Co., Ltd, Tokyo, Japan (Figure 1) [16 (link), 17 (link)]. The airway centreline was constructed using the minimum spanning tree generated by SYNAPSE 3D. The airway length was measured directly or indirectly (Figure 1B, Table S1). Additionally, the inner and outer contours of the seven selected airway locations were extracted using the graph cut method to calculate AWT and ALA (Figure 1A). The SCA was determined by measuring the airway centreline angles of the right and left main bronchus (Figure 1A).

Liu Y., Teng J., Mei J., Chen C., Xu Q.Q., Zhou C., Deng K.L, & Wang H.W. (2024). Analysis of airway structural parameters in Han Chinese adults: a prospective cross-sectional study. Annals of Medicine, 56(1), 2316258.

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Analysis of Game-Used Baseballs

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The game-used baseballs were scanned utilizing
a 320 detector row Toshiba Aquilion One scanner (Canon Medical Systems,
CA). The baseballs were placed on the scanner gantry, with two different
scans performed. On the first scan, single-game-used baseballs from
2014/pre-ASG 2015 to 2017 were placed next to each other. On the second
scan, four-game-used baseballs from 2014/pre-ASG 2015 and four-game-used
baseballs from 2017 were placed next to each other. Measurement of
the density of the internal components of the baseballs was performed
by evaluating the Hounsfield units. These measurements were conducted
on the Synapse Picture Archive and Communication System (PACS) (Fujifilm
Medical Systems, Japan). Regions of interest were placed on the different
layers of the baseball components, with particular interest on the
Hounsfield units in the different layers of the baseball pill. A visual
“heat map” of the 2014/pre-ASG 2015 and 2017 baseballs,
based on the internal radiodensity as measured by Hounsfield units,
was created by processing the CT data on Synapse 3D (Fujifilm Medical
Systems, Stamford, CT).

Beals N., Zhang L., Law M., Hwang D., Acharya J, & Basu S. (2019). Physicochemical Investigation into Major League Baseballs in the Era of Unprecedented Rise in Home Runs. ACS Omega, 4(23), 20109-20117.

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Fetal Organ Volumetric Analysis Pipeline

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The imaging software used was Synapse PACS and Synapse 3D (FUJIFILM Medical Systems Lexington, MA, US). Lung volumes were calculated on the T2 HASTE sequences, selecting the best image quality plane without motion-induced artifacts [22 (link)]. Liver volumes were calculated on T1 VIBE sequences [23 (link)]. A pediatric radiologist with 15 years of experience in fetal MRI performed the manual segmentation of lung and liver volumes. In each slice, left and right lung and liver areas were determined separately by tracing freehand regions of interest (ROIs), excluding the pulmonary hila and mediastinal structures. The areas were automatically added to obtain the entire organ volume, multiplied by the sum of slice thickness and intergap by the software.
The DICOM files were then anonymized, converted to the NIFTI format for easier manipulation, and fed to the segmentation pipeline.

Conte L., Amodeo I., De Nunzio G., Raffaeli G., Borzani I., Persico N., Griggio A., Como G., Cascio D., Colnaghi M., Mosca F, & Cavallaro G. (2024). Congenital diaphragmatic hernia: automatic lung and liver MRI segmentation with nnU-Net, reproducibility of pyradiomics features, and a machine learning application for the classification of liver herniation. European Journal of Pediatrics, 183(5), 2285-2300.

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MRI-based Brain Compartment Volumetry

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All MRI examinations were performed with a 64-channel 3-T MRI system (MAGNETOM Skyra, Siemens AG, Munich, Germany). Volumetric data were delivered to a 3D workstation (SYNAPSE 3D; Fujifilm Medical Systems, Tokyo, Japan), and semi-automatically segmented into intracranial space, ventricles, and subarachnoid spaces. The subarachnoid spaces were segmented into the following three components: convexity subarachnoid space, Sylvian fissure and basal cistern and posterior fossa. Both, the mean volumes and volume ratios (in percentages), which were calculated as the measured volumes divided by the intracranial volume, were analyzed to eliminate the effect of head size.

Yamada S., Ishikawa M, & Yamamoto K. (2017). Fluid Distribution Pattern in Adult-Onset Congenital, Idiopathic, and Secondary Normal-Pressure Hydrocephalus: Implications for Clinical Care. Frontiers in Neurology, 8, 583.

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Fetal Lung Volume Measurement Protocol

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For each patient, lung volumes were calculated on the T2 HASTE sequences. We chose the axial, coronal, or sagittal plane corresponding to the best image quality, covering the whole thorax on a single acquisition and without motion-induced artifacts. On each section, left and right lung areas were independently determined using freehand region of interest (ROI) on Synapse 3D (FUJIFILM Medical Systems USA, Inc.). The main vessels of the pulmonary hila and mediastinal structures were excluded. The areas were automatically added and multiplied for the slice thickness and intergap by the software to obtain the entire volume of each lung. Left and right lung volumes were added to obtain the total fetal lung volume (TFLV) of each fetus ( gure 2). The TFLV was then expressed as a percentage of the mean normal value expected for gestational age (O/E TFLV %), as previously determined by Rypens et al. (13) .

Amodeo I., Amodeo I., Borzani I., Corsani G., Pesenti N., Raffaeli G., Macchini F., Condò V., Persico N., Ghirardello S., Colnaghi M., Mosca F, & Cavallaro G. (2022). Fetal MRI mediastinal shift angle and respiratory and cardiovascular pharmacological support in newborns with congenital diaphragmatic hernia. European journal of pediatrics, 181(1).

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Texture Analysis of Phantom Imaging

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The manual volumes of interest (VOIs) were drawn using image‐rendering software (Synapse 3D, Fujifilm, Stamford CT) across the entire volume of each of the six texture patterns. A few regions of the phantom had air bubbles due to the manufacturing process, and care was taken to exclude these regions when the analysis was performed. Custom MATLAB (Mathworks, Natick, MA, USA) code was used to extract voxel data corresponding to the VOI. Two‐dimensional CTTA was conducted on the orientation that provided the largest diameter in the axial, coronal, or sagittal dimension. Three‐dimensional CTTA was conducted on the whole VOI.

Varghese B.A., Hwang D., Cen S.Y., Lei X., Levy J., Desai B., Goodenough D.J, & Duddalwar V.A. (2021). Identification of robust and reproducible CT‐texture metrics using a customized 3D‐printed texture phantom. Journal of Applied Clinical Medical Physics, 22(2), 98-107.

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Quantitative Assessment of Lung Emphysema

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We performed a quantitative assessment of lung emphysematous changes with densitometry in images reconstructed with the smooth (b31f Siemens) kernel. For such a purpose, we used the Pulmo (Siemens, Healthcare) software in the Florence cohort and the SYNAPSE 3D (Fujifilm) software in the Pisa cohort, according to an established procedure [17 (link)]. The presence of emphysematous changes was defined using the 6.0% threshold of the relative area of the lung with density values below 950 Hounsfield units (RA950) [18 (link)] normalized to the lung volume at acquisition. Subjects with emphysematous changes were then arbitrarily divided into those with mild (6% ≤ RA950 ≤ 9%) and those with moderate-severe (RA950 > 9%) emphysema.

Mascalchi M., Romei C., Marzi C., Diciotti S., Picozzi G., Pistelli F., Zappa M., Paci E., Carozzi F., Gorini G., Falaschi F., Deliperi A.L., Camiciottoli G., Carrozzi L, & Puliti D. (2023). Pulmonary emphysema and coronary artery calcifications at baseline LDCT and long-term mortality in smokers and former smokers of the ITALUNG screening trial. European Radiology, 33(5), 3115-3123.

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MRI-Based Quantification of Liver Fat

Cited 2 times

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MRI was used to measure the proportion of fat in liver, expressed as liver fat content (LFC), as well as visceral fat volume. Validity of MRI to quantify liver fat has been established in previous studies.^{18 (link),19 (link)} Approximately 50 5mm axial slices were obtained from the top of the liver to the pelvis using a series of 10–15 second breath holds on a GE Signa EXCITE HDxt 3.0T MR scanner. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) was used to delineate visceral fat depots and quantify organ fat.^{20 (link),21 (link)}Image post-processing for fat analysis and quantification was performed using Synapse 3D (Fujifilm, Stamford, CT). Fat fraction maps were used as the base images for segmentation. For each scan, three volumes were manually segmented - total body volume (excluded noisy outer body voxels), abdominal cavity volume, and whole liver volume. Visceral fat volume was created from the abdominal cavity volume. A ≥50% fat fraction threshold was applied on a per-voxel basis to all fat volumes to remove lean tissue. The visceral fat volume was further manually segmented to remove intramuscular and digestive tract fat. The liver volume was eroded by two pixels to generate a region of interest completely within the body of the liver. The average fat fraction within liver volume was reported as LFC.

Xiang A.H., Martinez M.P., Trigo E., Utzschneider K.M., Cree-Green M., Arslanian S., Ehrmann D.A., Caprio S., Mohamed P.H., Hwang D.H., Katkhouda N., Nayak K.S, & Buchanan T.A. (2021). Liver Fat Reduction after Gastric Banding and Associations with Changes in Insulin Sensitivity and β-cell Function. Obesity (Silver Spring, Md.), 29(7), 1155-1163.

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3D CTTA of Phantom ROIs

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The ROI delineation was performed using a manual segmentation technique. Three spherical ROIs were segmented in 3D using image‐rendering software (Synapse 3D, Fujifilm, Stamford CT). Some images of the phantom had air bubbles created as a result of the construction process, care was taken to exclude these regions when the analysis was performed.
Custom MATLAB (Mathworks, Natick, MA, USA) code was used to extract voxel data corresponding to the ROI. Two‐dimensional CTTA was conducted on the orientation that provided the largest diameter in the axial, coronal, or sagittal dimension. Three‐dimensional CTTA was conducted on the whole ROI volume. We used a 20‐bin gray‐level quantization. The slice thickness varied between 2 and 3 mm.

Varghese B.A., Hwang D., Cen S.Y., Levy J., Liu D., Lau C., Rivas M., Desai B., Goodenough D.J, & Duddalwar V.A. (2019). Reliability of CT‐based texture features: Phantom study. Journal of Applied Clinical Medical Physics, 20(8), 155-163.

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