研究目的
To evaluate the effect of using smaller pixels (~2 mm) on general oncologic lesion-detection performance in PET imaging compared to the commonly used ~4 mm pixels.
研究成果
Reconstructing with smaller pixel sizes (~2 mm) significantly improves lesion-detection performance in PET imaging, offering greater improvement than PSF modeling and roughly half the benefit of using TOF. The primary drawback is increased reconstruction time and data storage requirements.
研究不足
The study used phantom data which may not fully represent the variability encountered in clinical practice. The CNPW observer is a model numerical observer that does not fully match human observer performance.
1:Experimental Design and Method Selection:
The study used experimental phantom data from the Utah PET Lesion Detection Database, modeling whole-body FDG PET cancer imaging. Images were reconstructed with 2.036 mm and 4.073 mm pixels using OSEM with and without PSF modeling and TOF. Detection performance was assessed using the CNPW numerical observer with LROC analysis.
2:036 mm and 073 mm pixels using OSEM with and without PSF modeling and TOF. Detection performance was assessed using the CNPW numerical observer with LROC analysis.
Sample Selection and Data Sources:
2. Sample Selection and Data Sources: The data comprised 24 scans over 4 days on a Biograph mCT TOF PET/CT scanner, with up to 23 lesions distributed throughout the phantom each day.
3:List of Experimental Equipment and Materials:
Biograph mCT TOF PET/CT scanner, Utah PET Lesion Detection Database.
4:Experimental Procedures and Operational Workflow:
Images were reconstructed with different pixel sizes and algorithms. Detection performance was assessed using numerical and human observers.
5:Data Analysis Methods:
Lesion-detection performance was quantified using PLOC and ALROC metrics. Statistical significance was assessed using bootstrap estimates and Tukey HSD tests.
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