Abstract
Purpose: To prospectively compare the capabilities for TNM classification and assessment of clinical stage and operability among whole-body magnetic resonance (MR) imaging, coregistered positron emission tomographic (PET)/MR imaging with and without MR signal intensity (SI) assessment, and integrated fluorine 18 fluorodeoxyglucose (FDG) PET/computed tomography (CT) in non-small cell lung cancer (NSCLC) patients. Materials and Methods: The institutional review board approved this study, and written informed consent was obtained from each patient. One hundred forty consecutive NSCLC patients (75 men, 65 women; mean age, 72 years) prospectively underwent whole-body MR imaging, FDG PET/CT, conventional radiologic examinations, and surgical, pathologic, and/or follow-up examinations. All factors and clinical stage and operability were then visually assessed. All PET/MR examinations were assessed with and without SI assessment. One examination used anatomic, metabolic, and relaxation-time information, and the other used only anatomic and metabolic information. κ statistics were used for assessment of all factors and clinical stages with final diagnoses. McNemar test was used to compare the capability of all methods to assess operability. Results: Agreements of assessment of every factor (κ = 0.63-0.97) and clinical stage (κ = 0.65-0.90) were substantial or almost perfect. Regarding capability to assess operability, accuracy of whole-body MR imaging and PET/MR imaging with SI assessment (97.1% [136 of 140]) was significantly higher than that of MR/PET without SI assessment and integrated FDG PET/CT (85.0% [119 of 140]; P < .001). Conclusion: Accuracies of whole-body MR imaging and PET/MR imaging with SI assessment are superior to PET/MR without SI assessment and PET/CT for identification of TNM factor, clinical stage, and operability evaluation of NSCLC patients.
| Original language | English |
|---|---|
| Pages (from-to) | 849-861 |
| Number of pages | 13 |
| Journal | Radiology |
| Volume | 275 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 01-06-2015 |
| 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
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging
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