| 1. |
- Ly, John, et al.
(författare)
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Post-reconstruction enhancement of [18F]FDG PET images with a convolutional neural network
- 2021
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Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The aim of the study was to develop and test an artificial intelligence (AI)-based method to improve the quality of [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) images. Methods: A convolutional neural network (CNN) was trained by using pairs of excellent (acquisition time of 6 min/bed position) and standard (acquisition time of 1.5 min/bed position) or sub-standard (acquisition time of 1 min/bed position) images from 72 patients. A test group of 25 patients was used to validate the CNN qualitatively and quantitatively with 5 different image sets per patient: 4 min/bed position, 1.5 min/bed position with and without CNN, and 1 min/bed position with and without CNN. Results: Difference in hotspot maximum or peak standardized uptake value between the standard 1.5 min and 1.5 min CNN images fell short of significance. Coefficient of variation, the noise level, was lower in the CNN-enhanced images compared with standard 1 min and 1.5 min images. Physicians ranked the 1.5 min CNN and the 4 min images highest regarding image quality (noise and contrast) and the standard 1 min images lowest. Conclusions: AI can enhance [18F]FDG-PET images to reduce noise and increase contrast compared with standard images whilst keeping SUVmax/peak stability. There were significant differences in scoring between the 1.5 min and 1.5 min CNN image sets in all comparisons, the latter had higher scores in noise and contrast. Furthermore, difference in SUVmax and SUVpeak fell short of significance for that pair. The improved image quality can potentially be used either to provide better images to the nuclear medicine physicians or to reduce acquisition time/administered activity.
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| 2. |
- Ly, John, et al.
(författare)
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The use of a proposed updated EARL harmonization of 18F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations
- 2019
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Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: The Deauville score (DS) is a clinical tool, based on the comparison between lesion and reference organ uptake of 18F-fluorodeoxyglucose (FDG), used to stratify patients with lymphoma into categories reflecting their disease status. With a plethora of positron emission tomography with computed tomography (PET-CT) hard- and software algorithms, standard uptake value (SUV) in lesions and reference organs may differ which affects DS classification and therefore medical treatment. The EANM Research Ltd. (EARL) harmonization program from the European Association of Nuclear Medicine (EANM) partly mitigates this issue, but local preferences are common in clinical practice. We have investigated the discordance in DS calculated from patients with lymphoma referred for 18F-FDG PET-CT reconstructed with three different algorithms: the newly introduced block-sequential regularization expectation-maximization algorithm commercially sold as Q. Clear (QC, GE Healthcare, Milwaukee, WI, USA), compliant with the newly proposed updated EARL recommendations, and two settings compliant with the current EARL recommendations (EARLlower and EARLupper, representing the lower and upper limit of the EARL recommendations). Methods: Fifty-two patients with non-Hodgkin and Hodgkin lymphoma were included (18 females and 34 males). Segmentation of mediastinal blood pool and liver were semi-automatically performed, whereas segmentation of lesions was done manually. From these segmentations, SUVmax and SUVpeak were obtained and DS calculated. Results: There was a significant difference in DS between the QC algorithm and EARLlower/EARLupper (p < 0.0001 for both) but not between EARLlower and EARLupper (p = 0.102) when SUVmax was used. For SUVpeak, there was a significant difference between QC and EARLlower (p = 0.001), but not for QC vs EARLupper (p = 0.071) or EARLlower vs EARLupper (p = 0.102). Five non-responders (DS 4–5) for QC were classified as responders (DS 1–3) when EARLlower/EARLupper was used, both when SUVmax and SUVpeak were investigated. Conclusion: Using the proposed updated EARL recommendations compared with the current recommendations will significantly change DS classification. In select cases, the discordance would affect the choice of medical treatment. Specifically, the current EARL recommendations were more often prone to classify patients as responders.
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| 3. |
- Minarik, David, et al.
(författare)
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Perfusion vector-a new method to quantify myocardial perfusion scintigraphy images: a simulation study with validation in patients.
- 2015
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Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- The interpretation of myocardial perfusion scintigraphy (MPS) largely relies on visual assessment by the physician of the localization and extent of a perfusion defect. The aim of this study was to introduce the concept of the perfusion vector as a new objective quantitative method for further assisting the visual interpretation and to test the concept using simulated MPS images as well as patients.
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| 4. |
- Reza, Mariana, et al.
(författare)
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Bone Scan Index as a prognostic imaging biomarker during androgen deprivation therapy.
- 2014
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Ingår i: EJNMMI Research. - : Springer Science and Business Media LLC. - 2191-219X. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- Bone Scan Index (BSI) is a quantitative measurement of tumour burden in the skeleton calculated from bone scan images. When analysed at the time of diagnosis, it has been shown to provide prognostic information on survival in men with metastatic prostate cancer (PCa). In this study, we evaluated the prognostic value of BSI during androgen deprivation therapy (ADT).
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