Abstract
This study was performed to prospectively investigate the impact of image fusion in resolving discrepant findings between fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI) or X-ray computed tomography (CT) in patients with gynaecological cancers. Discrepant findings were defined as lesions where the difference between the FDG-PET and MRI/CT images was assigned a value of at least 2 on a 5-point probability scale. The FDG-PET and MRI/CT images were taken within 1 month of each other. Image fusion between FDG-PET and CT was performed by automatic registration between the two images. During an 18-month period, 34 malignant lesions and seven benign lesions from 32 patients who had undergone either surgical excision or a CT-guided histopathological investigation were included for analysis. Among these cases, image fusion was most frequently required to determine the nature and/or the extent of abdominal and pelvic lesions (28/41, 68%), especially as regards peritoneal seeding (8/41, 20%). Image fusion was most useful in providing better localisation for biopsy (16/41, 39%) and in discriminating between lesions with pathological versus physiological FDG uptake (12/41, 29%). Image fusion changed the original diagnosis based on MRI/ CT alone in 9/41 lesions (22%), and the original diagnosis based on FDG-PET alone in 5/41 lesions (12%). It led to alteration of treatment planning (surgery or radiotherapy) in seven of the 32 patients (22%). In patients with gynaecological cancers, the technique of image fusion is helpful in discriminating the nature of FDG-avid lesions, in effectively localising lesions for CT-guided biopsy and in providing better surgical or radiotherapy planning.
| Original language | English |
|---|---|
| Pages (from-to) | 1674-1683 |
| Number of pages | 10 |
| Journal | European Journal of Nuclear Medicine and Molecular Imaging |
| Volume | 30 |
| Issue number | 12 |
| DOIs | |
| State | Published - 12 2003 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Genital neoplasms
- Image fusion
- Magnetic resonance imaging
- Positron emission tomography
- X-ray computed tomography
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