This article provides an overview of the use of ¹⁸F-FDG PET/CT in various clinical scenarios of head–neck squamous cell carcinoma, ranging from initial staging to treatment-response assessment, and post-therapy follow-up, with a focus on the current evidence, debated issues, and innovative applications. Methodological aspects and the most frequent pitfalls in head–neck imaging interpretation are described. In the initial work-up, ¹⁸F-FDG PET/CT is recommended in patients with metastatic cervical lymphadenectomy and occult primary tumor; moreover, it is a well-established imaging tool for detecting cervical nodal involvement, distant metastases, and synchronous primary tumors. Various ¹⁸F-FDG pre-treatment parameters show prognostic value in terms of disease progression and overall survival. In this scenario, an emerging role is played by radiomics and machine learning. For radiation-treatment planning, ¹⁸F-FDG PET/CT provides an accurate delineation of target volumes and treatment adaptation. Due to its high negative predictive value, ¹⁸F-FDG PET/CT, performed at least 12 weeks after the completion of chemoradiotherapy, can prevent unnecessary neck dissections. In addition to radiomics and machine learning, emerging applications include PET/MRI, which combines the high soft-tissue contrast of MRI with the metabolic information of PET, and the use of PET radiopharmaceuticals other than ¹⁸F-FDG, which can answer specific clinical needs.

Aim: The aim of this study is to assess whether there are some correlations between radiomics and baseline clinical-biological data of prostate cancer (PC) patients using Fluorine-18 Fluoroethylcholine (¹⁸F-FECh) PET/CT. Methods: Digital rectal examination results (DRE), Prostate-Specific Antigen (PSA) serum levels, and bioptical-Gleason Score (GS) were retrospectively collected in newly diagnosed PC patients and considered as outcomes of PC. Thereafter, Volumes of interest (VOI) encompassing the prostate of each patient were drawn to extract conventional and radiomic PET features. Radiomic bivariate models were set up using the most statistically relevant features and then trained/tested with a cross-fold validation test. The best bivariate models were expressed by mean and standard deviation to the normal area under the receiver operating characteristic curves (mAUC, sdAUC). Results: Semiquantitative and radiomic analyses were performed on 67 consecutive patients. tSUVmean and tSkewness were significant DRE predictors at univariate analysis (OR 1.52 [1.01; 2.29], p = 0.047; OR 0.21 [0.07; 0.65], p = 0.007, respectively); moreover, tKurtosis was an independent DRE predictor at multivariate analysis (OR 0.64 [0.42; 0.96], p = 0.03) Among the most relevant bivariate models, szm_2.5D.z.entr + cm.clust.tend was a predictor of PSA levels (mAUC 0.83 ± 0.19); stat.kurt + stat.entropy predicted DRE (mAUC 0.79 ± 0.10); cm.info.corr.1 + szm_2.5D.szhge predicted GS (mAUC 0.78 ± 0.16). Conclusions: tSUVmean, tSkewness, and tKurtosis were predictors of DRE results only, while none of the PET parameters predicted PSA or GS significantly; ¹⁸F-FECh PET/CT radiomic models should be tested in larger cohort studies of newly diagnosed PC patients.

(1) Background: In ⁹⁰Y-TARE treatments, lung-absorbed doses should be calculated according to the manufacturer’s instructions, using the MIRD-scheme. This scheme is derived from the assumption that ⁹⁰Y-microspheres deliver the dose in a water-equivalent medium. Since the density of the lungs is quite different from that of the liver, the absorbed dose to the lungs could vary considerably, especially at the liver/lungs interface. The aim of this work is to compare the dosimetric results obtained by two dedicated software packages implementing a water-equivalent dose calculation and a Monte Carlo (MC) simulation, respectively. (2) Methods: An anthropomorphic IEC phantom and a retrospective selection of 24 patients with a diagnosis of HCC were taken into account. In the phantom study, starting from a ⁹⁰Y-PET/CT acquisition, the liver cavity was manually fixed with a uniform activity concentration on PET series, while the lung compartment was manually expanded on a CT series to simulate a realistic situation in which the liver and lungs are adjacent. These steps were performed by using MIM ⁹⁰Y SurePlan. Then, a first simulation was carried out with only the liver cavity filled, while a second one was carried out, in which the lung compartment was also manually fixed with a uniform activity concentration corresponding to 10% lung shunt fraction. MIM ⁹⁰Y SurePlan was used to obtain Voxel S-Value (VSV) approach dose values; instead, Torch was used to obtain MC approach dose values for both the phantom and the patients. (3) Results: In the phantom study, the percentage mean dose differences (∆D%) between VSV and MC in the first and second simulation, respectively were found to be 1.2 and 0.5% (absolute dose variation, ∆D, of 0.7 and 0.3 Gy) for the liver, −56 and 70% (∆D of −0.3 and −16.2 Gy) for the lungs, and −48 and −60% (∆D of −4.3 and −16.5 Gy) for the Liver/Lungs Edge region. The patient study reports similar results with ∆D% between VSV and MC of 7.0%, 4.1% and 6.7% for the whole liver, healthy liver, and tumor, respectively, while the result was −61.2% for the left lung and −61.1% for both the right lung and lungs. (4) Conclusion: Both VSV and MC allowed accurate radiation dose estimation with small differences (50%) were observed for air-equivalent regions in the phantom simulation and the patient study.