Abstract
Purpose: To compare the diagnostic accuracy of positron emission tomography (PET) and integrated PET/CT and to evaluate the performance of software fusion for staging of non-small cell lung cancer (NSCLC). Methods: Thirty-six patients (17 men and 19 women) with NSCLC underwent staging with integrated PET/CT followed by mediastinal lymph node dissection and tumor resection. Twenty-five of the 36 patients (69%) underwent separate CT studies for software fusion of images. Two blinded reviewers analyzed in consensus all PET images, and an experienced radiologist was added to assess integrated and software-fused PET/CT images. Histopathologic findings served as "gold standard" for determining the diagnostic accuracy of all modalities. Results: Reviewers examining PET and integrated PET/CT classified T stage accurately in 67% (20 of 30 patients) and 97% (29 of 30 patients), respectively (p < 0.05). Overall, interpretations based on PET staged 57% (17 of 30 patients) correctly, overstaged 6 patients (20%), and understaged 7 patients (23%). Interpretations based on integrated PET/CT correctly staged 83% (25 of 30 patients), overstaged 3 patients (10%), and understaged 2 patients (7%). The overall staging accuracy of integrated PET/CT was significantly higher than that of PET (p < 0.05). Automatic software fusion of separately obtained PET and CT studies was successful in 68% of the patients but failed in 32%. In successful software fusion cases, the results of software fusion with regards to T stage and N stage were not different from integrated PET/CT. Conclusions: Integrated PET/CT compared with PET alone was associated with 26% points-greater overall diagnostic accuracy (p = 0.01). The software fusion method failed to provide acceptable coregistration in > 30% of the patients.
| Original language | English |
|---|---|
| Pages (from-to) | 2289-2297 |
| Number of pages | 9 |
| Journal | Chest |
| Volume | 128 |
| Issue number | 4 |
| DOIs | |
| State | Published - Oct 2005 |
| 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
- CT
- Dual-modality imaging
- Fusion imaging
- Non-small cell lung cancer
- Positron emission tomography
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