Optimization of a dedicated protocol using a small-voxel PSF reconstruction for head-and-neck ¹⁸FDG PET/CT imaging in differentiated thyroid cancer

¹⁸FDG PET/CT is crucial before neck surgery for nodal recurrence localization in iodine-refractory differentiated or poorly differentiated thyroid cancer (DTC/PDTC). A dedicated head-and-neck (HN) acquisition performed with a thin matrix and point-spread-function (PSF) modelling in addition to the whole-body PET study has been shown to improve the detection of small cancer deposits. Different protocols have been reported with various acquisition times of HN PET/CT. We aimed to compare two reconstruction algorithms for disease detection and to determine the optimal acquisition time per bed position using the Siemens Biograph6 with extended field-of-view.

Twenty-one consecutive and unselected patients with DTC/PDTC underwent HN PET/CT acquisition using list-mode. PET data were reconstructed, mimicking five different acquisition times per bed position from 2 to 10 min. Each PET data set was reconstructed using 3D-ordered subset expectation maximisation (3D-OSEM) or iterative reconstruction with PSF modelling with no post filtering (PSF_allpass). These reconstructions resulted in 210 anonymized datasets that were randomly reviewed to assess ¹⁸FDG uptake in cervical lymph nodes or in the thyroid bed using a 5-point scale. Noise level, maximal standard uptake values (SUVmax), tumour/background ratios (TBRs) and dimensions of the corresponding lesion on the CT scan were recorded. In surgical patients, the largest tumoral size of each lymph node metastasis was measured by a pathologist.

The 120 HN PET studies of the 12 patients with at least 1 ¹⁸FDG focus scored malignant formed the study group. Noise level significantly decreased between 2 and 4 min for both 3D-OSEM and PSF_allpass reconstructions (p < 0.01). TBRs were similar for all the acquisition times for both 3D-OSEM and PSF_allpass reconstructions (p = 0.25 and 0.44, respectively). The detection rate of malignant foci significantly improved from 2 to 10 min for PSF_allpass reconstruction (20/26 to 26/26; p = 0.01) but not for 3D-OSEM (15/26 to 19/26; p = 0.26). For each of the five acquisition times, PSF_allpass detected more malignant foci than 3D-OSEM (p < 0.01). In the seven surgical patients, PSF_allpass evidenced smaller malignant lymph nodes than 3D-OSEM at 8 and 10 min. At 10 min, the mean size of the lymph node metastases neither detected with PSF_allpass nor 3D-OSEM was 3 ± 0.6 mm vs 5.8 ± 1.1 mm for those detected with PSF_allpass only and 10.9 ± 3.3 for those detected with both reconstructions (p < 0.001).

PSF_allpass HN PET improves lesion detectability as compared with 3D-OSEM HN PET. PSF_allpass with an acquisition time between 8 and 10 min provides the best performance for tumour detection.