Evaluation of a model-based attenuation correction method on whole-body 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging.
Hitoshi KuboAyaka NemotoNaoyuki UkonHiroshi ItoPublished in: Radiological physics and technology (2021)
The bone cannot be evaluated using magnetic resonance attenuation correction (MRAC) with the Dixon sequence. To solve this issue, the present study aimed to evaluate model-based AC for whole-body 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) by creating bone segmentation. We analyzed and evaluated the data of 31 consecutive patients. The Biograph mMR (Siemens Healthcare) was used for clinical whole-body 18F-FDG PET/MRI with the conventional MRAC method, and OSIRIX MD software was used to analyze the images. After the examination, the new model-based post-processing MRAC was applied to create μ-maps with bone segmentation, and retrospective PET reconstruction was performed using this μ-map. The bone structures of all patients created using model-based MRAC were visually evaluated. Standard uptake values (SUVs) at 11 anatomical positions in PET images, corrected using the μ-map with and without bone segmentation, were measured and compared. The model-based post-processing MRAC was run for all patients, without errors. Visual evaluation revealed that the model-based post-processing MRAC exhibited poor results for six patients. Furthermore, it exhibited an increasing trend of SUV in the brain compared to the conventional method. Locations other than the brain indicated a similar or decreasing trend. The two methods showed a good linear correlation for all patients. However, patients aged < 20 years exhibited a different trend from those aged ≥ 20 years. We should exercise caution when applying this model-based MRAC for younger patients.
Keyphrases
- positron emission tomography
- end stage renal disease
- magnetic resonance imaging
- computed tomography
- healthcare
- magnetic resonance
- ejection fraction
- chronic kidney disease
- pet ct
- prognostic factors
- deep learning
- type diabetes
- multiple sclerosis
- adipose tissue
- physical activity
- contrast enhanced
- patient reported outcomes
- insulin resistance
- blood glucose
- postmenopausal women
- high intensity
- subarachnoid hemorrhage
- brain injury
- bone loss
- adverse drug
- data analysis