AAR‐LN‐DQ: Automatic anatomy recognition based disease quantification in thoracic lymph node zones via FDG PET/CT images without Nodal Delineation

2020 ◽  
Vol 47 (8) ◽  
pp. 3467-3484
Author(s):  
Guoping Xu ◽  
Jayaram K. Udupa ◽  
Yubing Tong ◽  
Dewey Odhner ◽  
Hanqiang Cao ◽  
...  
Keyword(s):  
Lymph Node ◽  
Fdg Pet ◽  
Ct Images ◽  
Pet Ct ◽  
Thoracic Lymph Node ◽  
Fdg Pet Ct ◽  
Disease Quantification

Diagnostic performance of 18F-FDG PET/CT, ultrasonography and MRI

2014 ◽  
Vol 53 (03) ◽  
pp. 89-94 ◽  
Author(s):  
D. H. Lee ◽  
J.-K Yoon ◽  
S. J. Lee ◽  
T. H. Kim ◽  
D. K. Kang ◽  
...  
Keyword(s):  
Lymph Node ◽  
Fdg Pet ◽  
Axillary Lymph Node ◽  
Diagnostic Performance ◽  
Axillary Lymph ◽  
Diagnostic Ability ◽  
Node Metastasis ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct

SummaryThe aim of this study was to evaluate the diagnostic abilities of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) compared with those of ultrasonography and magnetic resonance imaging (MRI) for axillary lymph node staging in breast cancer patients. Patients, methods: Pre- operative 18F-FDG PET/non-contrast CT, ultrasonography and MRI were performed in 215 women with breast cancer. Axillary lymph node dissection was performed in all patients and the diagnostic performance of each modality was evaluated using histopathologic assessments as the reference standard. ROC curves were compared to evaluate the diagnostic ability of several imaging modalities (i. e., ultrasonography, MRI and 18F-FDG PET/CT). Results: In total, 132 patients (61.4%) had axillary lymph node metastasis. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for the detection of axillary lymph node metastasis were 72.3%, 77.3%, 66.7%, 81.6%, 75.3% for ultrasonography, 67.5%, 78.0%, 65.9%, 79.2%, 74.0% for MRI, and 62.7%, 88.6%, 77.6%, 79.1%, 78.6% for 18F-FDG PET/CT, respectively. There was no significant difference in diagnostic ability among the imaging modalities (i.e., ultrasonography, MRI and 18F-FDG PET/CT). The diagnostic ability of 18F-FDG PET/CT was significantly improved by combination with MRI (p = 0.0002) or ultrasonography (p < 0.0001). The combination of 18F-FDG PET/CT with ultrasonography had a similar diagnostic ability to that of all three modalities combined (18F-FDG PET/CT+ultraso- nography+MRI, p = 0.05). Conclusion: The diagnostic performance of 18F-FDG PET/CT for detection of axillary node metastasis was not significantly different from that of ultrasonography or MRI in breast cancer patients. Combining 18F-FDG PET/CT with ultrasonography or MRI could improve the diagnostic performance compared to 18F-FDG PET/CT alone.

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 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.

18F-FDG PET/CT of Internal Mammary Lymph Node Hepatocellular Carcinoma Metastases

2018 ◽  
Vol 43 (12) ◽  
pp. e482-e483
Author(s):  
Raja Senthil ◽  
H Ramesh ◽  
Arun Visakh R. ◽  
Thara Pratap ◽  
Pushpa Mahadevan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Lymph Node ◽  
Fdg Pet ◽  
Internal Mammary Lymph Node ◽  
Pet Ct ◽  
Internal Mammary ◽  
18F Fdg ◽  
Fdg Pet Ct

Additional Prone 18F-FDG PET/CT Acquisition to Improve the Visualization of the Primary Tumor and Regional Lymph Node Metastases in Stage II/III Breast Cancer

2016 ◽  
Vol 41 (4) ◽  
pp. e181-e186 ◽  
Author(s):  
Suzana Cipriano Teixeira ◽  
Bas B. Koolen ◽  
Wouter V. Vogel ◽  
Jelle Wesseling ◽  
Marcel P. M. Stokkel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastases ◽  
Primary Tumor ◽  
Fdg Pet ◽  
Regional Lymph Node ◽  
Pet Ct ◽  
Node Metastases ◽  
18F Fdg ◽  
Fdg Pet Ct

scholarly journals Erratum to: Advantages of FDG-PET/CT over CT alone in the preoperative assessment of lymph node metastasis in patients with esophageal cancer

Surgery Today ◽  
2015 ◽  
Vol 45 (4) ◽  
pp. 478-478
Author(s):  
Ryuichi Karashima ◽  
Masayuki Watanabe ◽  
Yu Imamura ◽  
Satoshi Ida ◽  
Yoshifumi Baba ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Fdg Pet ◽  
Preoperative Assessment ◽  
Node Metastasis ◽  
Pet Ct ◽  
Fdg Pet Ct
Sign in / Sign up

Export Citation Format

Share Document