A Novel Multi-Planar Fusion System for PET/CT Images

2013 ◽  
Vol 373-375 ◽  
pp. 608-612
Author(s):  
Zhen Wei Li ◽  
Xiao Li Yang ◽  
Wei Dong Song
Keyword(s):  
Ct Images ◽  
Fusion System ◽  
Color Processing ◽  
Pet Ct ◽  
Dicom Header ◽  
Stable Performance ◽  
Malignant Lesions ◽  
Pseudo Color ◽  
Ct Slices ◽  
Ct Volume

Objective To propose a PET/CT multi-planar fusion system based on PACS. Methods Firstly, the system got PET and CT slices and relevant DICOM header information from PACS workstation, preprocessed them and formed CT volume and PET volume, and then displayed the axial, coronal and sagittal planes of the two volumes by MPR. Afterwards, the results of MPR were enhanced by pseudo color processing, then were fused with the MRP results of CT correspondingly. Finally, the SUVs of PET images and the CT value of CT images were calculated according to the parameters obtained from the DICOM header, and were displayed in the lower right corner of the current sub window. Results This system can be integrated into PACS workstation expediently, can reconstruct each volume, either MPR or MIP, stably and effectively, and can fuse PET images with CT images in different planes. The resource consumption of the system is reasonable and the SUVs calculated were accurate and reliable. Conclusion The system is easy to use and has stable performance, which is helpful in the clinical diagnosis of malignant lesions as an auxiliary tool.

Automated classification of benign and malignant lesions in 18F-NaF PET/CT images using machine learning

2018 ◽  
Vol 63 (22) ◽  
pp. 225019 ◽  
Author(s):  
Timothy Perk ◽  
Tyler Bradshaw ◽  
Song Chen ◽  
Hyung-jun Im ◽  
Steve Cho ◽  
...  
Keyword(s):  
Machine Learning ◽  
Ct Images ◽  
Automated Classification ◽  
Pet Ct ◽  
Malignant Lesions

Retrospective interactive rigid fusion of 18F-FDG-PET and CT

2006 ◽  
Vol 45 (02) ◽  
pp. 88-95 ◽  
Author(s):  
A. Nömayr ◽  
H. Greess ◽  
E. Fiedler ◽  
G. Platsch ◽  
B. Schuler-Thurner ◽  
...  
Keyword(s):  
Malignant Melanoma ◽  
Image Fusion ◽  
Fdg Pet ◽  
False Negative ◽  
Spiral Ct ◽  
Ct Images ◽  
Pet Ct ◽  
Malignant Lesions ◽  
Ct Data

Summary Aim: This study investigates whether interactive rigid fusion of routine PET and CT data improves localization, detection and characterization of lesions compared to separate reading. For this purpose, routine PET and CT scans of patients with metastases from malignant melanoma were used. Patients, methods: In 34 patients with histologically confirmed malignant melanoma, FDG-PET and spiral CT were performed using clinical standard protocols. For all of these patients, gold standard was available. Clinical and radiological follow-up identified 82 lesions as definitely pathological. Two board-certified nuclear medicine physicians and two board-certified radiologists analyzed PET and CT images independently from each other. For each patient up to 32 anatomical regions (24 lymph node regions, 8 extranodular regions) were systematically classified. Discordant areas were interactively analyzed in manually and rigidly registered images using a commercially available fusion tool. No side-by-side reading was performed. Results: Image fusion disclosed that the evaluation of the PET images alone led to a mislocalization in 26 of 91 focally FDG enhancing lesions. The overall sensitivities of PET, CT, and image fusion were 85, 88, and 94%, respectively; the overall specificities of PET, CT and image fusion were 98, 95 and 100%, respectively. Image fusion exhibited statistically significant higher specificity values as compared with CT. Ten definitely malignant sites were false-negative in CT, but could be detected by PET. On the other hand, twelve metastases were false-negative in PET, but could be detected by CT. These included two lesions, which had a clear correlate on the PET image when the fused images were evaluated. On the whole, registration of the PET and CT images yielded additional diagnostic information in 44% of the definitely malignant lesions. Conclusion: Retrospective image fusion of independently obtained PET and CT data is particularly valuable in exactly localizing foci of abnormal FDG uptake and improves the detection of metastases of malignant melanoma.

scholarly journals Textural Features of Pretreatment 18F-FDG PET/CT Images: Prognostic Significance in Patients with Advanced T-Stage Oropharyngeal Squamous Cell Carcinoma

2013 ◽  
Vol 54 (10) ◽  
pp. 1703-1709 ◽  
Author(s):  
N.-M. Cheng ◽  
Y.-H. Dean Fang ◽  
J. Tung-Chieh Chang ◽  
C.-G. Huang ◽  
D.-L. Tsan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Fdg Pet ◽  
Prognostic Significance ◽  
Ct Images ◽  
Textural Features ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct

[68Ga]Ga-FAPI and [18F]FDG PET/CT images in a patient with juvenile polymyositis

2021 ◽  
Author(s):  
Jieling Zheng ◽  
Huaning Chen ◽  
Kaixian Lin ◽  
Shaobo Yao ◽  
Weibing Miao
Keyword(s):  
Fdg Pet ◽  
Ct Images ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct

scholarly journals Increased [18F]FMISO accumulation under hypoxia by multidrug-resistant protein 1 inhibitors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoichi Shimizu ◽  
Yukihiro Nakai ◽  
Hiroyuki Watanabe ◽  
Shimpei Iikuni ◽  
Masahiro Ono ◽  
...  
Keyword(s):  
Cyclosporine A ◽  
Pet Imaging ◽  
Multidrug Resistant ◽  
Ct Images ◽  
Pet Scan ◽  
Reduced Form ◽  
Pet Ct ◽  
Fadu Cells ◽  
Hypoxic State

Abstract Background [18F]Fluoromisonidazole ([18F]FMISO) is a PET imaging probe widely used for the detection of hypoxia. We previously reported that [18F]FMISO is metabolized to the glutathione conjugate of the reduced form in hypoxic cells. In addition, we found that the [18F]FMISO uptake level varied depending on the cellular glutathione conjugation and excretion ability such as enzyme activity of glutathione-S-transferase and expression levels of multidrug resistance-associated protein 1 (MRP1, an efflux transporter), in addition to the cellular hypoxic state. In this study, we evaluated whether MRP1 activity affected [18F]FMISO PET imaging. Methods FaDu human pharyngeal squamous cell carcinoma cells were pretreated with MRP1 inhibitors (cyclosporine A, lapatinib, or MK-571) for 1 h, incubated with [18F]FMISO for 4 h under hypoxia, and their radioactivity was then measured. FaDu tumor-bearing mice were intravenously injected with [18F]FMISO, and PET/CT images were acquired at 4 h post-injection (1st PET scan). Two days later, the same mice were pretreated with MRP1 inhibitors (cyclosporine A, lapatinib, or MK-571) for 1 h, and PET/CT images were acquired (2nd PET scan). Results FaDu cells pretreated with MRP1 inhibitors exhibited significantly higher radioactivity than those without inhibitor treatment (cyclosporine A: 6.91 ± 0.27, lapatinib: 10.03 ± 0.47, MK-571: 10.15 ± 0.44%dose/mg protein, p < 0.01). In the in vivo PET study, the SUVmean ratio in tumors [calculated as after treatment (2nd PET scan)/before treatment of MRP1 inhibitors (1st PET scan)] of the mice treated with MRP1 inhibitors was significantly higher than those of control mice (cyclosporine A: 2.6 ± 0.7, lapatinib: 2.2 ± 0.7, MK-571: 2.2 ± 0.7, control: 1.2 ± 0.2, p < 0.05). Conclusion In this study, we revealed that MRP1 inhibitors increase [18F]FMISO accumulation in hypoxic cells. This suggests that [18F]FMISO-PET imaging is affected by MRP1 inhibitors independent of the hypoxic state.

scholarly journals Impact of the Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Michał Wyrzykowski ◽  
Natalia Siminiak ◽  
Maciej Kaźmierczak ◽  
Marek Ruchała ◽  
Rafał Czepczyński
Keyword(s):  
Reconstruction Algorithm ◽  
Ct Images ◽  
Pet Ct

scholarly journals Automated quantification of baseline imaging PET metrics on FDG PET/CT images of pediatric Hodgkin lymphoma patients

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Amy J. Weisman ◽  
Jihyun Kim ◽  
Inki Lee ◽  
Kathleen M. McCarten ◽  
Sandy Kessel ◽  
...  
Keyword(s):  
Hodgkin Lymphoma ◽  
Correlation Coefficient ◽  
Pet Imaging ◽  
Fdg Pet ◽  
Relative Difference ◽  
Ct Images ◽  
Imaging Features ◽  
Pediatric Hodgkin Lymphoma ◽  
Pet Ct ◽  
Fdg Pet Ct

Abstract Purpose For pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma. Methods 18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson’s correlation coefficient and relative percent differences were calculated between automated and physician-extracted features. Results Median Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78–0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson’s correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of − 4.3% (− 10.0–5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of − 0.4% (− 5.2–7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6–4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR − 7.5–40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically. Conclusions An automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.

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