Effect of Reconstruction Parameters in High-Definition PET/CT on Assessment of Lymph Node Metastases in Head and Neck Squamous Cell Carcinoma

Therapy outcome and overall survival in patients with head and neck squamous cell carcinoma (HNSCC) is influenced by precise localization of the primary tumor and detection of lymph node metastasis involvement at the time of initial diagnosis. Only accurate preoperative staging can improve primary tumor response and avoid early locoregional recurrence with lymph node metastases. The purpose of this study was the optimization of reconstruction parameters in high-definition PET/CT for the improved diagnostic assessment of lymph node metastases. Methods: In the experimental study, image contrast and signal-to-noise ratio were evaluated using a Jaszczak phantom. In the clinical study, 54 patients underwent head and neck imaging on a PET/CT scanner. Diagnostic findings were correlated with postoperative histopathology. For the 54 patients, 123 lymph nodes were evaluated on PET and histologically correlated with the neck dissection specimen. Forty-one lymph nodes were benign, and 82 findings were confirmed as being malignant. Both experimental and clinical studies were reconstructed into a 200 x 200 matrix using a 3-dimensional iterative reconstruction algorithm (ordered-subset expectation maximization [OSEM], 3 iterative steps, 24 subsets). Postfiltering with a 3-dimensional gaussian filter was applied. To study the effect of smoothing filter strength on the diagnostic accuracy of lymph node metastasis detection, 3 different cutoffs-1, 3, and 6 mm in full width at half maximum-were used to perform reconstructions. Results: Phantom studies showed that images reconstructed with 3-mm gaussian postfiltering gained a higher image quality and signal-to-noise ratio. Overall sensitivities for correctly diagnosed lymph nodes were best in 3-mm postfiltered images. Best results for true-positive lymph node findings were achieved with 3-mm postfiltering. With 1-mm postfiltering, accurate lesion detection was not improved, because increasing sensitivity (95% true-positive) correlated with decreasing specificity (12% false-positive). Conclusion: For lymph node assessment on a high-resolution PET/CT scanner, we consider the OSEM algorithm with 3 iterations and 24 subsets, combined with 3-dimensional 3-mm gaussian postfiltering, to be optimal. The continuous application of presently established PET protocols in patients with HNSCC will prove whether current acquisition and reconstruction methods are valuable and should be maintained.