Objective: This work assessed the usefulness of fully three-dimensional ordered subset expectation maximization (3D-OSEM) algorithm for lymph node (LN) metastases from lung cancer. 3D-OSEM images were evaluated by comparing them with those reconstructed by conventional algorithms, such as conventional OSEM algorithm (2D-OSEM) for 2D acquisition and Fourier rebinning plus conventional OSEM algorithm (FORE + OSEM) for 3D acquisition.
Materials and methods: In a phantom study, the contrast ratio, the image noise and the signal-to-noise ratio (SNR) were calculated, and the detectability and the image quality of these images were visually evaluated. In a clinical study, 14 patients suffering from lung cancer with LN metastases were evaluated. The image quality and the malignancy, and the detectability were visually evaluated.
Results: The contrast ratio was significantly improved using 3D-OSEM as compared with FORE + OSEM, and it was similar to 2D-OSEM. The image noise and SNR in 3D-OSEM images were significantly improved compared with those by other algorithms (p < 0.001). In the visual assessment, the image quality was significantly improved in 3D-OSEM images compared with those by 2D-OSEM and FORE + OSEM (p < 0.001, p = 0.001, respectively). In the clinical study, the image quality and the detectability of LN metastases were improved in 3D-OSEM images compared with those by FORE + OSEM (p < 0.001, p = 0.006, respectively), and image quality and detectability were similar to those of 2D-OSEM images.
Conclusions: 3D-OSEM algorithm successfully improved the diagnostic accuracy of LN metastases in 3D-PET tests.