Random correction method for positron emission mammography using delayed coincidence data

2012 ◽  
Author(s):  
Liji Cao ◽  
Ricardo Bugalho ◽  
Catarina Ortigao ◽  
Joao Varela ◽  
Jorg Peter
Keyword(s):  
Correction Method ◽  
Positron Emission Mammography ◽  
Positron Emission ◽  
Coincidence Data

Positron emission mammography in the diagnosis of breast cancer

2016 ◽  
Vol 55 (01) ◽  
pp. 15-20 ◽  
Author(s):  
J. Farahati ◽  
A. G. Müller ◽  
E. Gillman ◽  
M. Hentschel ◽  
F. H. H. Müller
Keyword(s):  
Breast Cancer ◽  
High Specificity ◽  
Diagnostic Value ◽  
Glandular Tissue ◽  
Breast Cancer Patients ◽  
Malignant Tumours ◽  
Benign Lesions ◽  
Interventional Study ◽  
Positron Emission Mammography ◽  
Positron Emission

SummaryAim: To evaluate the diagnostic value (sensitivity, specificity) of positron emission mammography (PEM) in a single site non-interventional study using the maximum PEM uptake value (PUVmax). Patients, methods: In a singlesite, non-interventional study, 108 patients (107 women, 1 man) with a total of 151 suspected lesions were scanned with a PEM Flex Solo II (Naviscan) at 90 min p.i. with 3.5 MBq 18F-FDG per kg of body weight. In this ROI(region of interest)-based analysis, maximum PEM uptake value (PUV) was determined in lesions, tumours (PUVmaxtumour), benign lesions (PUVmaxnormal breast) and also in healthy tissues on the contralateral side (PUVmaxcontralateral breast). These values were compared and contrasted. In addition, the ratios of PUVmaxtumour / PUVmaxcontralateral breast and PUVmaxnormal breast / PUVmaxcontralateral breast were compared. The image data were interpreted independently by two experienced nuclear medicine physicians and compared with histology in cases of suspected carcinoma. Results: Based on a criteria of PUV>1.9, 31 out of 151 lesions in the patient cohort were found to be malignant (21%). A mean PUVmaxtumour of 3.78 ± 2.47 was identified in malignant tumours, while a mean PUVmaxnormal breast of 1.17 ± 0.37 was reported in the glandular tissue of the healthy breast, with the difference being statistically significant (p < 0.001). Similarly, the mean ratio between tumour and healthy glandular tissue in breast cancer patients (3.15 ± 1.58) was found to be significantly higher than the ratio for benign lesions (1.17 ± 0.41, p < 0.001). Conclusion: PEM is capable of differentiating breast tumours from benign lesions with 100% sensitivity along with a high specificity of 96%, when a threshold of PUVmax >1.9 is applied.

scholarly journals Accurate Transmission-Less Attenuation Correction Method for Amyloid-β Brain PET Using Deep Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1836
Author(s):  
Bo-Hye Choi ◽  
Donghwi Hwang ◽  
Seung-Kwan Kang ◽  
Kyeong-Yun Kim ◽  
Hongyoon Choi ◽  
...  
Keyword(s):  
Neural Network ◽  
Attenuation Correction ◽  
Complex Structure ◽  
Scatter Correction ◽  
Amyloid Β ◽  
Correction Method ◽  
Percentage Error ◽  
Similarity Coefficients ◽  
Brain Pet ◽  
Positron Emission

The lack of physically measured attenuation maps (μ-maps) for attenuation and scatter correction is an important technical challenge in brain-dedicated stand-alone positron emission tomography (PET) scanners. The accuracy of the calculated attenuation correction is limited by the nonuniformity of tissue composition due to pathologic conditions and the complex structure of facial bones. The aim of this study is to develop an accurate transmission-less attenuation correction method for amyloid-β (Aβ) brain PET studies. We investigated the validity of a deep convolutional neural network trained to produce a CT-derived μ-map (μ-CT) from simultaneously reconstructed activity and attenuation maps using the MLAA (maximum likelihood reconstruction of activity and attenuation) algorithm for Aβ brain PET. The performance of three different structures of U-net models (2D, 2.5D, and 3D) were compared. The U-net models generated less noisy and more uniform μ-maps than MLAA μ-maps. Among the three different U-net models, the patch-based 3D U-net model reduced noise and cross-talk artifacts more effectively. The Dice similarity coefficients between the μ-map generated using 3D U-net and μ-CT in bone and air segments were 0.83 and 0.67. All three U-net models showed better voxel-wise correlation of the μ-maps compared to MLAA. The patch-based 3D U-net model was the best. While the uptake value of MLAA yielded a high percentage error of 20% or more, the uptake value of 3D U-nets yielded the lowest percentage error within 5%. The proposed deep learning approach that requires no transmission data, anatomic image, or atlas/template for PET attenuation correction remarkably enhanced the quantitative accuracy of the simultaneously estimated MLAA μ-maps from Aβ brain PET.

scholarly journals Clinical practice guidelines for high-resolution breast PET, 2019 edition

2021 ◽  
Vol 35 (3) ◽  
pp. 406-414
Author(s):  
Yoko Satoh ◽  
Masami Kawamoto ◽  
Kazunori Kubota ◽  
Koji Murakami ◽  
Makoto Hosono ◽  
...  
Keyword(s):  
High Resolution ◽  
Practice Guidelines ◽  
Breast Imaging ◽  
Japanese Society ◽  
Insurance Coverage ◽  
Whole Body ◽  
Positron Emission Mammography ◽  
Dedicated Breast Pet ◽  
Positron Emission ◽  
Different Types

AbstractBreast positron emission tomography (PET) has had insurance coverage when performed with conventional whole-body PET in Japan since 2013. Together with whole-body PET, accurate examination of breast cancer and diagnosis of metastatic disease are possible, and are expected to contribute significantly to its treatment planning. To facilitate a safer, smoother, and more appropriate examination, the Japanese Society of Nuclear Medicine published the first edition of practice guidelines for high-resolution breast PET in 2013. Subsequently, new types of breast PET have been developed and their clinical usefulness clarified. Therefore, the guidelines for breast PET were revised in 2019. This article updates readers as to what is new in the second edition. This edition supports two different types of breast PET depending on the placement of the detector: the opposite-type (positron emission mammography; PEM) and the ring-shaped type (dedicated breast PET; dbPET), providing an overview of these scanners and appropriate imaging methods, their clinical applications, and future prospects. The name “dedicated breast PET” from the first edition is widely used to refer to ring-shaped type breast PET. In this edition, “breast PET” has been defined as a term that refers to both opposite- and ring-shaped devices. Up-to-date breast PET practice guidelines would help provide useful information for evidence-based breast imaging.

The potential role of positron emission mammography for detection of breast cancer. A phantom study

2000 ◽  
Vol 27 (8) ◽  
pp. 1943-1954 ◽  
Author(s):  
Raymond R. Raylman ◽  
Stan Majewski ◽  
Randy Wojcik ◽  
Andrew G. Weisenberger ◽  
Brian Kross ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Potential Role ◽  
Phantom Study ◽  
Positron Emission Mammography ◽  
Positron Emission
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