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Purpose: PET-derived metabolic tumor volume (MTV) and total lesion glycolysis of the primary tumor are known to be prognostic of clinical outcome in head and neck cancer (HNC). Including evaluation of lymph node metastases can further increase the prognostic value of PET but accurate manual delineation and classification of all lesions is time-consuming and prone to interobserver variability. Our goal, therefore, was development and evaluation of an automated tool for MTV delineation/classification of primary tumor and lymph node metastases in PET/CT investigations of HNC patients., Methods: Automated lesion delineation was performed with a residual 3D U-Net convolutional neural network (CNN) incorporating a multi-head self-attention block. 698 [Formula: see text]F]FDG PET/CT scans from 3 different sites and 5 public databases were used for network training and testing. An external dataset of 181 [Formula: see text]F]FDG PET/CT scans from 2 additional sites was employed to assess the generalizability of the network. In these data, primary tumor and lymph node (LN) metastases were interactively delineated and labeled by two experienced physicians. Performance of the trained network models was assessed by 5-fold cross-validation in the main dataset and by pooling results from the 5 developed models in the external dataset. The Dice similarity coefficient (DSC) for individual delineation tasks and the primary tumor/metastasis classification accuracy were used as evaluation metrics. Additionally, a survival analysis using univariate Cox regression was performed comparing achieved group separation for manual and automated delineation, respectively., Results: In the cross-validation experiment, delineation of all malignant lesions with the trained U-Net models achieves DSC of 0.885, 0.805, and 0.870 for primary tumor, LN metastases, and the union of both, respectively. In external testing, the DSC reaches 0.850, 0.724, and 0.823 for primary tumor, LN metastases, and the union of both, respectively. The voxel classification accuracy was 98.0% and 97.9% in cross-validation and external data, respectively. Univariate Cox analysis in the cross-validation and the external testing reveals that manually and automatically derived total MTVs are both highly prognostic with respect to overall survival, yielding essentially identical hazard ratios (HR) ([Formula: see text]; [Formula: see text] vs. [Formula: see text]; [Formula: see text] in cross-validation and [Formula: see text]; [Formula: see text] vs. [Formula: see text]; [Formula: see text] in external testing)., Conclusion: To the best of our knowledge, this work presents the first CNN model for successful MTV delineation and lesion classification in HNC. In the vast majority of patients, the network performs satisfactory delineation and classification of primary tumor and lymph node metastases and only rarely requires more than minimal manual correction. It is thus able to massively facilitate study data evaluation in large patient groups and also does have clear potential for supervised clinical application., (© 2023. The Author(s).)

Objective: Several genetic analyses have identified tumor diversity not only among tumors from different patients (intertumor heterogeneity) but also within individual tumors (intratumor heterogeneity). The aim of this study was to analyze the intratumor heterogeneity and other biological parameters based on in vivo distribution in triple-tracer positron emission tomography with computed tomography (PET/CT) study in patients with newly diagnosed head and neck (H&N) cancer., Methods: Thirty-six patients with newly diagnosed H&N cancer were included in the study. Institutional Bioethical Committee approved the study protocol and informed consent was received from every participant. All patients underwent series of 3 PET/CT scans with [ 18 F]Fluorodeoxyglucose ( 18 F-FDG-PET), [ 18 F]Fluorothymidine ( 18 F-FLT-PET), and [ 18 F]Fluoromisonidazole ( 18 F-FMISO-PET) before treatment. Scans were performed on separate days, within a timeframe of 2 weeks. Several PET/CT parameters grading tumor biology including maximum standardized uptake value (SUV max ), total lesion glycolysis (TLG), its equivalent (total hypoxic lesion [TLH] and total proliferative lesion [TLP]), and heterogeneity (area under the curve-cumulative SUV histogram) for the primary tumor were compared., Results: All patients showed increased uptake of 18 F-FDG in primary tumor, ranging from 2.29 to 14.89 SUV max . Respectively, SUV max values for 18 F-FLT ranged from 0.93 to 16.11 and for 18 F-FMISO 0.36-4.07. Based on 3-year follow-up, we divided patients in terms of survival forecasts (first with good prognosis and second with worse). Higher values of TLG/TLP/TLH and SUV max were observed in the second group in all 3 tracers (for 18 F-FDG: 167.40 vs 100.32, 11.15 vs 8.95; for 18 F-FLT: 116.61 vs 60.67, 7.09 vs 5.47; for 18 F-FMISO: 37.34 vs 22.30, 1.70 vs 1.61 respectively). Statistically significant differences were shown in SUV max in 18 F-FDG and 18 F-FLT ( P <0.034, P <0.034, respectively; in TLG, P =0.05; TLP, P =0.04; and TLH, P =0.05)., Conclusion: Our preliminary results suggest worse prognosis in patients with higher heterogeneity values of primary tumor in proliferation and hypoxia images and combination of metabolic and volumetric parameters in TLG and its equivalent and heterogeneity of primary tumor seems to be a prognostic factor.

Objective: The aim of the study was to assess the feasibility of multitracer positron emission tomography (PET) imaging before and during chemoradiation and to evaluate the predictive value of image-based factors for outcome in locally advanced head and neck cancers treated with chemoradiation., Methods: In the week prior to the treatment [ 18 F]-2-flu-2-deoxy-D-glucose (FDG), [ 18 F]-3'-flu-3'deoxythymidine (FLT) and [ 18 F]-flumisonidazole (FMISO) imaging was performed. FLT scans were repeated at 14 and 28 Gy and FMISO at 36 Gy. Overall survival, disease-free survival and local control were correlated with subvolume parameters, and with tumour-to-muscle ratio for FMISO. For every tracer, total metabolic tumour volume was calculated., Results: 33 patients were included. No correlation was found between pre-treatment maximum standardised uptake value for FDG, FLT, FMISO and outcomes. Tumour volume measured on initial CT scans and initial FLT volume correlated with disease-free survivall ( p = 0.007 and 0.04 respectively). FDG and FLT metabolic tumour volumes correlated significantly with local control ( p = 0.005 and 0.02 respectively). In multivariate Cox analysis only individual initial TMRmax correlated with overall survival., Conclusion: PET/CT imaging is a promising tool. However, various aspects of image analysis need further clinical validation in larger multicentre study employing uniform imaging protocol and standardisation, especially for hypoxia tracer., Advances in Knowledge: Monitoring of biological features of the tumour using multitracer PET modality seems to be a feasible option in daily clinical practice.Evaluation of hypoxic subvolumes is more patient dependent; thus, exploration of individual parameters of hypoxia is needed. tumour-to-muscle ratio seems to be the most promising so far.

Objective: The aim of this study was to differentiate between benign and malignant head and neck lymph nodes by sequential imaging., Subjects and Methods: The total of 56 retrospectively analysed patients with suspected or histopathologically confirmed head and neck malignancy (nasopharyngeal cancers mainly; 28 patients), before any treatment, underwent sequential fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) examinations for staging purposes. Remaining 28 patients with physiologic and histopathologically confirmed inflammatory (of non-specified origin) lymph nodes were included into this analysis. Patients underwent sequential PET/CT scans 60 and 90min post injection (p.i.) of the 18 F-FDG. Semi-quantitative analysis of metabolic activity within lymph nodes was based on the standardized uptake value (SUV) evaluation. To compare the metabolic activity fluctuation over time, the retention index (RI) was used. For SUV value and RI cut-off evaluation, the receiver operating characteristic (ROC) analysis was performed., Results: The SUVmax value at 60min p.i. of physiologic, inflammatory and malignant (metastatic) lymph nodes were 1.09±0.33, 2.36±0.60 and 6.31±2.74, respectively. The SUVmax value at 90min p.i. were: 1.01±0.32, 2.48±0.61, and 7.17±2.91, respectively, and there was statistically significant difference between physiologic and inflammatory and physiologic and the metastatic lymph nodes (P<0.001). The values of early and delayed SUVmax were significantly different between physiologic and inflammatory and physiologic and metastatic lymph nodes (P<0.001). The SUVmax, SUVmean values at 60 and at 90min p.i. between malignant and inflammatory lymph nodes were statistically insignificant (P=0.33). The RI at 60 and at 90min p.i. was: -6%±16% for physiologic, 6%±14% for inflammatory and 15%±13% for the metastatic lymph nodes. The SUVmax changes over time (the RI) were statistically significant for physiologic and metastatic and physiologic and inflammatory lymph nodes (P<0.001) and significant between malignant and inflammatory lymph nodes (P=0.02)., Conclusion: Sequential delayed 18 F-FDG PET/CT examinations may increase specificity of this scan and provide information for the differentiation benign and malignant lymph nodes in the cases of head and neck cancer.