68Ga-labeled fibroblast activation protein inhibitor (FAPI) PET/CT for locally advanced or recurrent pancreatic cancer staging and restaging after chemoradiotherapy.

Purpose: 68Ga-labeled fibroblast activation protein inhibitor (FAPI) is a novel PET tracer with great potential for staging pancreatic cancer. Data on locally advanced or recurrent disease is sparse, especially on tracer uptake before and after high dose chemoradiotherapy (CRT). The aim of this study was to evaluate [68Ga]Ga-FAPI-46 PET/CT staging in this setting. Methods: Twenty-seven patients with locally recurrent or locally advanced pancreatic adenocarcinoma (LRPAC n = 15, LAPAC n = 12) in stable disease or partial remission after chemotherapy underwent FAPI PET/CT and received consolidation CRT in stage M0 with follow-up FAPI PET/CT every three months until systemic progression. Quantitative PET parameters SUVmax, SUVmean, FAPI-derived tumor volume and total lesion FAPI-uptake were measured in baseline and follow-up PET/CT scans. Contrast-enhanced CT (ceCT) and PET/CT data were evaluated blinded and staged according to TNM classification. Results: FAPI PET/CT modified staging compared to ceCT alone in 23 of 27 patients in baseline, resulting in major treatment alterations in 52% of all patients (30%: target volume adjustment due to N downstaging, 15%: switch to palliative systemic chemotherapy only due to diffuse metastases, 7%: abortion of radiotherapy due to other reasons). Regarding follow-up scans, major treatment alterations after performing FAPI PET/CT were noted in eleven of 24 follow-up scans (46%) with switch to systemic chemotherapy or best supportive care due to M upstaging and ablative radiotherapy of distant lymph node and oligometastasis. Unexpectedly, in more than 90 % of the follow-up scans, radiotherapy did not induce local fibrosis related FAPI uptake. During the first follow-up, all quantitative PET metrics decreased, and irradiated lesions showed significantly lower FAPI uptake in locally controlled disease (SUVmax p = 0.047, SUVmean p = 0.0092) compared to local failure. Conclusion: Compared to ceCT, FAPI PET/CT led to major therapeutic alterations in patients with LRPAC and LAPAC prior to and after radiotherapy, which might help identify patients benefiting from adjustments in every treatment stage. FAPI PET/CT should be considered a useful diagnostic tool in LRPAC or LAPAC before and after CRT.

Value of [18F]FDG PET/CT parameters of the primary tumor in assessing overall survival in NSCLC patients with cN1-cN3 lymph nodes involvement.

Background: The aim of this retrospective study was to assess the value of 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT parameters in cN1-cN3 non-small cell lung cancer (NSCLC) patients. Materials and methods: 59 consecutive patients (35 M, 24 F) with NSCLC who underwent pretreatment [18F]FDG PET/CT were enrolled to this study. Several primary tumor PET parameters, including the maximum and mean standardized uptake value (SUVmax and SUVmean), the metabolic active tumor volume (MTV) and the total lesion glycolysis (TLG = MTVxSUVmean), were extracted and analysed. Overall survival was defined as time from primary diagnosis to death or the last info. Results: In the whole analysed group 44 patients underwent curative treatment, while 15, because of the severity of the disease, were classified for palliative treatment. Univariate Cox analysis of clinical and metric PET parameters revealed that MTV was a significant prognostic factor for OS (p = 0.024), while TLG and curative treatment showed a trend for significance (p < 0.1). In multivariate Cox regression (MTV and curative treatment) MTV remained a significant factor (p = 0.047). Conclusions: Metabolic tumor volume of the primary tumor was the only independent prognostic factor for cN1-cN3 NSCLC patients.

Quantitative PSMA-PET parameters in localized prostate cancer: prognostic and potential predictive value.

BACKGROUND: PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA. METHODS: This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC). RESULTS: 67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients. CONCLUSION: Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential. Trial registration Due to the retrospective nature of this research, no registration was carried out.

Deep learning based bilateral filtering for edge-preserving denoising of respiratory-gated PET.

BACKGROUND: Residual image noise is substantial in positron emission tomography (PET) and one of the factors limiting lesion detection, quantification, and overall image quality. Thus, improving noise reduction remains of considerable interest. This is especially true for respiratory-gated PET investigations. The only broadly used approach for noise reduction in PET imaging has been the application of low-pass filters, usually Gaussians, which however leads to loss of spatial resolution and increased partial volume effects affecting detectability of small lesions and quantitative data evaluation. The bilateral filter (BF) - a locally adaptive image filter - allows to reduce image noise while preserving well defined object edges but manual optimization of the filter parameters for a given PET scan can be tedious and time-consuming, hampering its clinical use. In this work we have investigated to what extent a suitable deep learning based approach can resolve this issue by training a suitable network with the target of reproducing the results of manually adjusted case-specific bilateral filtering. METHODS: Altogether, 69 respiratory-gated clinical PET/CT scans with three different tracers ( [ 18 F ] FDG, [ 18 F ] L-DOPA, [ 68 Ga ] DOTATATE) were used for the present investigation. Prior to data processing, the gated data sets were split, resulting in a total of 552 single-gate image volumes. For each of these image volumes, four 3D ROIs were delineated: one ROI for image noise assessment and three ROIs for focal uptake (e.g. tumor lesions) measurements at different target/background contrast levels. An automated procedure was used to perform a brute force search of the two-dimensional BF parameter space for each data set to identify the "optimal" filter parameters to generate user-approved ground truth input data consisting of pairs of original and optimally BF filtered images. For reproducing the optimal BF filtering, we employed a modified 3D U-Net CNN incorporating residual learning principle. The network training and evaluation was performed using a 5-fold cross-validation scheme. The influence of filtering on lesion SUV quantification and image noise level was assessed by calculating absolute and fractional differences between the CNN, manual BF, or original (STD) data sets in the previously defined ROIs. RESULTS: The automated procedure used for filter parameter determination chose adequate filter parameters for the majority of the data sets with only 19 patient data sets requiring manual tuning. Evaluation of the focal uptake ROIs revealed that CNN as well as BF based filtering essentially maintain the focal SUV max values of the unfiltered images with a low mean ± SD difference of δ SUV max CNN , STD = (-3.9 ± 5.2)% and δ SUV max BF , STD = (-4.4 ± 5.3)%. Regarding relative performance of CNN versus BF, both methods lead to very similar SUV max values in the vast majority of cases with an overall average difference of δ SUV max CNN , BF = (0.5 ± 4.8)%. Evaluation of the noise properties showed that CNN filtering mostly satisfactorily reproduces the noise level and characteristics of BF with δ Noise CNN , BF = (5.6 ± 10.5)%. No significant tracer dependent differences between CNN and BF were observed. CONCLUSIONS: Our results show that a neural network based denoising can reproduce the results of a case by case optimized BF in a fully automated way. Apart from rare cases it led to images of practically identical quality regarding noise level, edge preservation, and signal recovery. We believe such a network might proof especially useful in the context of improved motion correction of respiratory-gated PET studies but could also help to establish BF-equivalent edge-preserving CNN filtering in clinical PET since it obviates time consuming manual BF parameter tuning.

Combination of tumor asphericity and an extracellular matrix-related prognostic gene signature in non-small cell lung cancer patients.

One important aim of precision oncology is a personalized treatment of patients. This can be achieved by various biomarkers, especially imaging parameters and gene expression signatures are commonly used. So far, combination approaches are sparse. The aim of the study was to independently validate the prognostic value of the novel positron emission tomography (PET) parameter tumor asphericity (ASP) in non small cell lung cancer (NSCLC) patients and to investigate associations between published gene expression profiles and ASP. This was a retrospective evaluation of PET imaging and gene expression data from three public databases and two institutional datasets. The whole cohort comprised 253 NSCLC patients, all treated with curative intent surgery. Clinical parameters, standard PET parameters and ASP were evaluated in all patients. Additional gene expression data were available for 120 patients. Univariate Cox regression and Kaplan-Meier analysis was performed for the primary endpoint progression-free survival (PFS) and additional endpoints. Furthermore, multivariate cox regression testing was performed including clinically significant parameters, ASP, and the extracellular matrix-related prognostic gene signature (EPPI). In the whole cohort, a significant association with PFS was observed for ASP (p < 0.001) and EPPI (p = 0.012). Upon multivariate testing, EPPI remained significantly associated with PFS (p = 0.018) in the subgroup of patients with additional gene expression data, while ASP was significantly associated with PFS in the whole cohort (p = 0.012). In stage II patients, ASP was significantly associated with PFS (p = 0.009), and a previously published cutoff value for ASP (19.5%) was successfully validated (p = 0.008). In patients with additional gene expression data, EPPI showed a significant association with PFS, too (p = 0.033). The exploratory combination of ASP and EPPI showed that the combinatory approach has potential to further improve patient stratification compared to the use of only one parameter. We report the first successful validation of EPPI and ASP in stage II NSCLC patients. The combination of both parameters seems to be a very promising approach for improvement of risk stratification in a group of patients with urgent need for a more personalized treatment approach.

18F-FDG PET/CT-derived total lesion glycolysis predicts abscess formation in patients with surgically confirmed infective endocarditis: Results of a retrospective study at a tertiary center.

BACKGROUND: Abnormal activity of 18F-FDG PET/CT is a major Duke criterion in the diagnostic work-up of infective prosthetic valve endocarditis (IE). We hypothesized that quantitative lesion assessment by 18F-FDG PET/CT-derived standard maximum uptake ratio (SURmax), metabolic volume (MV), and total lesion glycolysis (TLG) might be useful in distinct subgroups of IE patients (e.g. IE-related abscess formation). METHODS: All patients (n = 27) hospitalized in our tertiary IE referral medical center from January 2014 to October 2018 with preoperatively performed 18F-FDG PET/CT and surgically confirmed IE were included into this retrospective analysis. RESULTS: Patients with surgically confirmed abscess formation (n = 10) had significantly increased MV (by ~ fivefold) and TLG (by ~ sevenfold) as compared to patients without abscess (n = 17). Receiver operation characteristics (ROC) analyses demonstrated that TLG (calculated as MV × SURmean, i.e. TLG (SUR)) had the most favorable area under the ROC curve (0.841 [CI 0.659 to 1.000]) in predicting IE-related abscess formation. This resulted in a sensitivity of 80% and a specificity of 88% at a cut-off value of 14.14 mL for TLG (SUR). CONCLUSION: We suggest that 18F-FDG PET/CT-derived quantitative assessment of TLG (SUR) may provide a novel diagnostic tool in predicting endocarditis-associated abscess formation.

Asphericity derived from [18F]FDG PET as a new prognostic parameter in cervical cancer patients.

The objective of this study was to assess the prognostic value of asphericity (ASP) and standardized uptake ratio (SUR) in cervical cancer patients. Retrospective analysis was performed on a group of 508 (aged 55 ± 12 years) previously untreated cervical cancer patients. All patients underwent a pretreatment [18F]FDG PET/CT study to assess the severity of the disease. The metabolic tumor volume (MTV) of the cervical cancer was delineated with an adaptive threshold method. For the resulting ROIs the maximum standardized uptake value (SUVmax) was measured. In addition, ASP and SUR were determined as previously described. Univariate Cox regression and Kaplan-Meier analysis with respect to event free survival (EFS), overall survival (OS), freedom from distant metastasis (FFDM) and locoregional control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed. In the survival analysis, MTV and ASP were shown to be prognostic factors for all investigated endpoints. Tumor metabolism quantified with the SUVmax was not prognostic for any of the endpoints (p > 0.2). The SUR did not reach statistical significance either (p = 0.1, 0.25, 0.066, 0.053, respectively). In the multivariate analysis, the ASP remained a significant factor for EFS and LRC, while MTV was a significant factor for FFDM, indicating their independent prognostic value for the respective endpoints. The alternative parameter ASP has the potential to improve the prognostic value of [18F]FDG PET/CT for event-free survival and locoregional control in radically treated cervical cancer patients.

A convolutional neural network with self-attention for fully automated metabolic tumor volume delineation of head and neck cancer in [Formula: see text]F]FDG PET/CT.

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.

Development of a Neurotensin-Derived 68Ga-Labeled PET Ligand with High In Vivo Stability for Imaging of NTS1 Receptor-Expressing Tumors.

Overexpression of the neurotensin receptor type 1 (NTS1R), a peptide receptor located at the plasma membrane, has been reported for a variety of malignant tumors. Thus, targeting the NTS1R with 18F- or 68Ga-labeled ligands is considered a straightforward approach towards in vivo imaging of NTS1R-expressing tumors via positron emission tomography (PET). The development of suitable peptidic NTS1R PET ligands derived from neurotensin is challenging due to proteolytic degradation. In this study, we prepared a series of NTS1R PET ligands based on the C-terminal fragment of neurotensin (NT(8-13), Arg8-Arg9-Pro10-Tyr11-Ile12-Leu13) by attachment of the chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) via an Nω-carbamoylated arginine side chain. Insertion of Ga3+ in the DOTA chelator gave potential PET ligands that were evaluated concerning NTS1R affinity (range of Ki values: 1.2-21 nM) and plasma stability. Four candidates were labeled with 68Ga3+ and used for biodistribution studies in HT-29 tumor-bearing mice. [68Ga]UR-LS130 ([68Ga]56), containing an N-terminal methyl group and a ß,ß-dimethylated tyrosine instead of Tyr11, showed the highest in vivo stability and afforded a tumor-to-muscle ratio of 16 at 45 min p.i. Likewise, dynamic PET scans enabled a clear tumor visualization. The accumulation of [68Ga]56 in the tumor was NTS1R-mediated, as proven by blocking studies.

Comparison of image quality and spatial resolution between 18F, 68Ga, and 64Cu phantom measurements using a digital Biograph Vision PET/CT.

BACKGROUND: PET nuclides can have a considerable influence on the spatial resolution and image quality of PET/CT scans, which can influence diagnostics in oncology, for example. The individual impact of the positron energy of 18F, 68Ga, and 64Cu on spatial resolution and image quality was compared for PET/CT scans acquired using a clinical, digital scanner. METHODS: A Jaszczak phantom and a NEMA PET body phantom were filled with 18F-FDG, 68Ga-HCl, or 64Cu-HCl, and PET/CT scans were performed on a Siemens Biograph Vision. Acquired images were analyzed regarding spatial resolution and image quality (recovery coefficients (RC), coefficient of variation within the background, contrast recovery coefficient (CRC), contrast-noise ratio (CNR), and relative count error in the lung insert). Data were compared between scans with different nuclides. RESULTS: We found that image quality was comparable between 18F-FDG and 64Cu-HCl PET/CT measurements featuring similar maximal endpoint energies of the positrons. In comparison, RC, CRC, and CNR were degraded in 68Ga-HCl data despite similar count rates. In particular, the two smallest spheres of 10 mm and 13 mm diameter revealed lower RC, CRC, and CNR values. The spatial resolution was similar between 18F-FDG and 64Cu-HCl but up to 18% and 23% worse compared with PET/CT images of the NEMA PET body phantom filled with 68Ga-HCl. CONCLUSIONS: The positron energy of the PET nuclide influences the spatial resolution and image quality of a digital PET/CT scan. The image quality and spatial resolution of 68Ga-HCl PET/CT images were worse than those of 18F-FDG or 64Cu-HCl despite similar count rates.

18F-Fluorodeoxyglucose Positron Emission Tomography of Head and Neck Cancer: Location and HPV Specific Parameters for Potential Treatment Individualization.

Purpose: 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is utilized for staging and treatment planning of head and neck squamous cell carcinomas (HNSCC). Some older publications on the prognostic relevance showed inconclusive results, most probably due to small study sizes. This study evaluates the prognostic and potentially predictive value of FDG-PET in a large multi-center analysis. Methods: Original analysis of individual FDG-PET and patient data from 16 international centers (8 institutional datasets, 8 public repositories) with 1104 patients. All patients received curative intent radiotherapy/chemoradiation (CRT) and pre-treatment FDG-PET imaging. Primary tumors were semi-automatically delineated for calculation of SUVmax, SUVmean, metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Cox regression analyses were performed for event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM). Results: FDG-PET parameters were associated with patient outcome in the whole cohort regarding clinical endpoints (EFS, OS, LRC, FFDM), in uni- and multivariate Cox regression analyses. Several previously published cut-off values were successfully validated. Subgroup analyses identified tumor- and human papillomavirus (HPV) specific parameters. In HPV positive oropharynx cancer (OPC) SUVmax was well suited to identify patients with excellent LRC for organ preservation. Patients with SUVmax of 14 or less were unlikely to develop loco-regional recurrence after definitive CRT. In contrast FDG PET parameters deliver only limited prognostic information in laryngeal cancer. Conclusion: FDG-PET parameters bear considerable prognostic value in HNSCC and potential predictive value in subgroups of patients, especially regarding treatment de-intensification and organ-preservation. The potential predictive value needs further validation in appropriate control groups. Further research on advanced imaging approaches including radiomics or artificial intelligence methods should implement the identified cut-off values as benchmark routine imaging parameters.

Correlation Between Quantitative PSMA PET Parameters and Clinical Risk Factors in Non-Metastatic Primary Prostate Cancer Patients.

Background: PSMA PET is frequently used for staging of prostate cancer patients. Furthermore, there is increasing interest to use PET information for personalized local treatment approaches in surgery and radiotherapy, especially for focal treatment strategies. However, it is not well established which quantitative imaging parameters show highest correlation with clinical and histological tumor aggressiveness. Methods: This is a retrospective analysis of 135 consecutive patients with non-metastatic prostate cancer and PSMA PET before any treatment. Clinical risk parameters (PSA values, Gleason score and D'Amico risk group) were correlated with quantitative PET parameters maximum standardized uptake value (SUVmax), mean SUV (SUVmean), tumor asphericity (ASP) and PSMA tumor volume (PSMA-TV). Results: Most of the investigated imaging parameters were highly correlated with each other (correlation coefficients between 0.20 and 0.95). A low to moderate, however significant, correlation of imaging parameters with PSA values (0.19 to 0.45) and with Gleason scores (0.17 to 0.31) was observed for all parameters except ASP which did not show a significant correlation with Gleason score. Receiver operating characteristics for the detection of D'Amico high-risk patients showed poor to fair sensitivity and specificity for all investigated quantitative PSMA PET parameters (Areas under the curve (AUC) between 0.63 and 0.73). Comparison of AUC between quantitative PET parameters by DeLong test showed significant superiority of SUVmax compared to SUVmean for the detection of high-risk patients. None of the investigated imaging parameters significantly outperformed SUVmax. Conclusion: Our data confirm prior publications with lower number of patients that reported moderate correlations of PSMA PET parameters with clinical risk factors. With the important limitation that Gleason scores were only biopsy-derived in this study, there is no indication that the investigated additional parameters deliver superior information compared to SUVmax.

Influences on PET Quantification and Interpretation.

Various factors have been identified that influence quantitative accuracy and image interpretation in positron emission tomography (PET). Through the continuous introduction of new PET technology-both imaging hardware and reconstruction software-into clinical care, we now find ourselves in a transition period in which traditional and new technologies coexist. The effects on the clinical value of PET imaging and its interpretation in routine clinical practice require careful reevaluation. In this review, we provide a comprehensive summary of important factors influencing quantification and interpretation with a focus on recent developments in PET technology. Finally, we discuss the relationship between quantitative accuracy and subjective image interpretation.

Prognostic Value of Pretherapeutic Primary Tumor MTV from [18F]FDG PET in Radically Treated Cervical Cancer Patients.

The aim of this study was to assess the usefulness of pretherapeutic primary tumor metabolic tumor volume (MTV) in the prognosis of radically treated cervical cancer patients. Retrospective, single-centre analysis was performed on a group of 508 cervical cancer patients. All patients underwent a pretreatment [18F]FDG PET/CT study for the assessment of the disease stage. Several PET-derived parameters-namely, maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), total lesion glycolysis (TLG) and MTV, as well as the clinical parameters, were analysed in terms of the overall survival (OS), event-free survival (EFS), locoregional control (LRC) and freedom from distant metastases (FFDM). Hyperthermia and brachytherapy were prognostic for EFS, OS, and LRC.FIGO stage > II showed a significant effect on EFS, OS, and FFDM. Moreover, hysterectomy was prognostic for OS and histology was prognostic for FFDM. From the PET-derived parameters only MTV of the primary tumor had a significant influence on OS (cutoff point: >12.7 mL, HR: 2.8, 1.75-4.48 95% CI, p < 0.001), LRC (cutoff point: >13.7 mL, HR 2.82, 1.42-5.61 95% CI, p = 0.003), EFS (cutoff point: >10.4 mL, HR: 2.57, 1.67-3.97 95% CI, p < 0.001) and FFDM (cutoff point: >10.4 mL, HR: 5.04, 1.82-13.99 95% CI, p = 0.002). Pretreatment MTV from the primary tumor is the only independent prognostic parameter in OS, LRC, EFS, and FFDM in radically treated cervical cancer patients and should be used in clinical practice in assessing prognosis in these patients.

A convolutional neural network for fully automated blood SUV determination to facilitate SUR computation in oncological FDG-PET.

PURPOSE: The standardized uptake value (SUV) is widely used for quantitative evaluation in oncological FDG-PET but has well-known shortcomings as a measure of the tumor's glucose consumption. The standard uptake ratio (SUR) of tumor SUV and arterial blood SUV (BSUV) possesses an increased prognostic value but requires image-based BSUV determination, typically in the aortic lumen. However, accurate manual ROI delineation requires care and imposes an additional workload, which makes the SUR approach less attractive for clinical routine. The goal of the present work was the development of a fully automated method for BSUV determination in whole-body PET/CT. METHODS: Automatic delineation of the aortic lumen was performed with a convolutional neural network (CNN), using the U-Net architecture. A total of 946 FDG PET/CT scans from several sites were used for network training (N = 366) and testing (N = 580). For all scans, the aortic lumen was manually delineated, avoiding areas affected by motion-induced attenuation artifacts or potential spillover from adjacent FDG-avid regions. Performance of the network was assessed using the fractional deviations of automatically and manually derived BSUVs in the test data. RESULTS: The trained U-Net yields BSUVs in close agreement with those obtained from manual delineation. Comparison of manually and automatically derived BSUVs shows excellent concordance: the mean relative BSUV difference was (mean ± SD) = (- 0.5 ± 2.2)% with a 95% confidence interval of [- 5.1,3.8]% and a total range of [- 10.0, 12.0]%. For four test cases, the derived ROIs were unusable (< 1 ml). CONCLUSION: CNNs are capable of performing robust automatic image-based BSUV determination. Integrating automatic BSUV derivation into PET data processing workflows will significantly facilitate SUR computation without increasing the workload in the clinical setting.

Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies.

BACKGROUND: Asphericity (ASP) of the primary tumor's metabolic tumor volume (MTV) in FDG-PET/CT is independently predictive for survival in patients with non-small cell lung cancer (NSCLC). However, comparability between PET systems may be limited. Therefore, reproducibility of ASP was evaluated at varying image reconstruction and acquisition times to assess feasibility of ASP assessment in multicenter studies. METHODS: This is a retrospective study of 50 patients with NSCLC (female 20; median age 69 years) undergoing pretherapeutic FDG-PET/CT (median 3.7 MBq/kg; 180 s/bed position). Reconstruction used OSEM with TOF4/16 (iterations 4; subsets 16; in-plane filter 2.0, 6.4 or 9.5 mm), TOF4/8 (4 it; 8 ss; filter 2.0/6.0/9.5 mm), PSF + TOF2/17 (2 it; 17 ss; filter 2.0/7.0/10.0 mm) or Bayesian-penalized likelihood (Q.Clear; beta, 600/1750/4000). Resulting reconstructed spatial resolution (FWHM) was determined from hot sphere inserts of a NEMA IEC phantom. Data with approx. 5-mm FWHM were retrospectively smoothed to achieve 7-mm FWHM. List mode data were rebinned for acquisition times of 120/90/60 s. Threshold-based delineation of primary tumor MTV was followed by evaluation of relative ASP/SUVmax/MTV differences between datasets and resulting proportions of discordantly classified cases. RESULTS: Reconstructed resolution for narrow/medium/wide in-plane filter (or low/medium/high beta) was approx. 5/7/9 mm FWHM. Comparing different pairs of reconstructed resolution between TOF4/8, PSF + TOF2/17, Q.Clear and the reference algorithm TOF4/16, ASP differences was lowest at FWHM of 7 versus 7 mm. Proportions of discordant cases (ASP > 19.5% vs. ≤ 19.5%) were also lowest at 7 mm (TOF4/8, 2%; PSF + TOF2/17, 4%; Q.Clear, 10%). Smoothing of 5-mm data to 7-mm FWHM significantly reduced discordant cases (TOF4/8, 38% reduced to 2%; PSF + TOF2/17, 12% to 4%; Q.Clear, 10% to 6%), resulting in proportions comparable to original 7-mm data. Shorter acquisition time only increased proportions of discordant cases at < 90 s. CONCLUSIONS: ASP differences were mainly determined by reconstructed spatial resolution, and multicenter studies should aim at comparable FWHM (e.g., 7 mm; determined by in-plane filter width). This reduces discordant cases (high vs. low ASP) to an acceptable proportion for TOF and PSF + TOF of < 5% (Q.Clear: 10%). Data with better resolution (i.e., lower FWHM) could be retrospectively smoothed to the desired FWHM, resulting in a comparable number of discordant cases.

A FDG-PET radiomics signature detects esophageal squamous cell carcinoma patients who do not benefit from chemoradiation.

Detection of patients with esophageal squamous cell carcinoma (ESCC) who do not benefit from standard chemoradiation (CRT) is an important medical need. Radiomics using 18-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a promising approach. In this retrospective study of 184 patients with locally advanced ESCC. 152 patients from one center were grouped into a training cohort (n = 100) and an internal validation cohort (n = 52). External validation was performed with 32 patients treated at a second center. Primary endpoint was disease-free survival (DFS), secondary endpoints were overall survival (OS) and local control (LC). FDG-PET radiomics features were selected by Lasso-Cox regression analyses and a separate radiomics signature was calculated for each endpoint. In the training cohort radiomics signatures containing up to four PET derived features were able to identify non-responders in regard of all endpoints (DFS p < 0.001, LC p = 0.003, OS p = 0.001). After successful internal validation of the cutoff values generated by the training cohort for DFS (p = 0.025) and OS (p = 0.002), external validation using these cutoffs was successful for DFS (p = 0.002) but not for the other investigated endpoints. These results suggest that pre-treatment FDG-PET features may be useful to detect patients who do not respond to CRT and could benefit from alternative treatment.

Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients.

PURPOSE: [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) parameters have shown prognostic value in nasopharyngeal carcinomas (NPC), mostly in monocenter studies. The aim of this study was to assess the prognostic impact of standard and novel PET parameters in a multicenter cohort of patients. METHODS: The established PET parameters metabolic tumor volume (MTV), total lesion glycolysis (TLG) and maximal standardized uptake value (SUVmax) as well as the novel parameter tumor asphericity (ASP) were evaluated in a retrospective multicenter cohort of 114 NPC patients with FDG-PET staging, treated with (chemo)radiation at 8 international institutions. Uni- and multivariable Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), event-free survival (EFS), distant metastases-free survival (FFDM), and locoregional control (LRC) was performed for clinical and PET parameters. RESULTS: When analyzing metric PET parameters, ASP showed a significant association with EFS (p = 0.035) and a trend for OS (p = 0.058). MTV was significantly associated with EFS (p = 0.026), OS (p = 0.008) and LRC (p = 0.012) and TLG with LRC (p = 0.019). TLG and MTV showed a very high correlation (Spearman's rho = 0.95), therefore TLG was subesequently not further analysed. Optimal cutoff values for defining high and low risk groups were determined by maximization of the p-value in univariate Cox regression considering all possible cutoff values. Generation of stable cutoff values was feasible for MTV (p<0.001), ASP (p = 0.023) and combination of both (MTV+ASP = occurrence of one or both risk factors, p<0.001) for OS and for MTV regarding the endpoints OS (p<0.001) and LRC (p<0.001). In multivariable Cox (age >55 years + one binarized PET parameter), MTV >11.1ml (hazard ratio (HR): 3.57, p<0.001) and ASP > 14.4% (HR: 3.2, p = 0.031) remained prognostic for OS. MTV additionally remained prognostic for LRC (HR: 4.86 p<0.001) and EFS (HR: 2.51 p = 0.004). Bootstrapping analyses showed that a combination of high MTV and ASP improved prognostic value for OS compared to each single variable significantly (p = 0.005 and p = 0.04, respectively). When using the cohort from China (n = 57 patients) for establishment of prognostic parameters and all other patients for validation (n = 57 patients), MTV could be successfully validated as prognostic parameter regarding OS, EFS and LRC (all p-values <0.05 for both cohorts). CONCLUSIONS: In this analysis, PET parameters were associated with outcome of NPC patients. MTV showed a robust association with OS, EFS and LRC. Our data suggest that combination of MTV and ASP may potentially further improve the risk stratification of NPC patients.

Individual patient data meta-analysis of FMISO and FAZA hypoxia PET scans from head and neck cancer patients undergoing definitive radio-chemotherapy.

BACKGROUND AND PURPOSE: Tumor hypoxia plays an important role in head and neck squamous cell carcinomas (HNSCC). Various positron emission tomography (PET) tracers promise non-invasive assessment of tumor hypoxia. So far, the applicability of hypoxia PET is hampered by monocentric imaging trials with few patients. MATERIALS AND METHODS: Multicenter individual patient data based meta-analysis of the original PET data from four prospective imaging trials was performed. All patients had localized disease and were treated with curatively intended radio(-chemo)therapy. Hypoxia PET imaging was performed with 18F-Fluoromisonidazole (FMISO, 102 patients) or 18F-Fluoroazomycin-arabinoside (FAZA, 51 patients). Impact of hypoxia PET parameters on loco-regional control (LRC) and overall survival (OS) was analyzed by uni- and multivariable Cox regression. RESULTS: Baseline characteristics between participating centers differed significantly, especially regarding T stage (p < 0.001), tumor volume (p < 0.001) and p16 status (p = 0.009). The commonly used hypoxia parameters, maximal tumor-to-muscle ratio (TMRmax) and hypoxic volume with 1.6 threshold (HV1.6), showed a strong association with LRC (p = 0.001) and OS (p < 0.001). These findings were irrespective of the radiotracer and the same cut-off values could be applied for FMISO and FAZA (TMRmax > 2.0 or HV1.6 > 1.5 ml). The effect size of TMRmax was similar for subgroups of patients defined by radiotracer, p16 status and FDG-PET parameters for LRC and OS, respectively. CONCLUSION: PET measured hypoxia is robust and has a strong impact on LRC and OS in HNSCC. The most commonly investigated tracers FMISO and FAZA can probably be used equivalently in multicenter trials. Optimal strategies to improve the dismal outcome of hypoxic tumors remain elusive.

Combined tumor plus nontumor interim FDG-PET parameters are prognostic for response to chemoradiation in squamous cell esophageal cancer.

We have investigated the prognostic value of two novel interim 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) parameters in patients undergoing chemoradiation (CRT) for esophageal squamous cell carcinoma (ESCC): one tumor parameter (maximal standardized uptake ratio rSUR) and one normal tissue parameter (change of FDG uptake within irradiated nontumor-affected esophagus ∆SUVNTO ). PET data of 134 European and Chinese patients were analyzed. Parameter establishment was based on 36 patients undergoing preoperative CRT plus surgery, validation was performed in 98 patients receiving definitive CRT. Patients received PET imaging prior and during fourth week of CRT. Clinical parameters, baseline PET parameters, and interim PET parameters (rSUR and ∆SUVNTO ) were analyzed and compared to event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM). Combining rSUR and ∆SUVNTO revealed a strong prognostic impact on EFS, OS, LRC and FFDM in patients undergoing preoperative CRT. In the definitive CRT cohort, univariate analysis with respect to EFS revealed several staging plus both previously established interim PET parameters as significant prognostic factors. Multivariate analyses revealed only rSUR and ∆SUVNTO as independent prognostic factors (p = 0.003, p = 0.008). Combination of these parameters with the cutoff established in preoperative CRT revealed excellent discrimination of patients with a long or short EFS (73% vs. 17% at 2 years, respectively) and significantly discriminated all other endpoints (OS, p < 0.001; LRC, p < 0.001; FFDM, p = 0.02), even in subgroups. Combined use of interim FDG-PET derived parameters ∆SUVNTO and rSUR seems to have predictive potential, allowing to select responders for definitive CRT and omission of surgery.