Dual time-point [18F]FDG PET imaging for quantification of metabolic uptake rate: Evaluation of a simple, clinically feasible method.

PURPOSE: We aimed to investigate whether a clinically feasible dual time-point (DTP) approach can accurately estimate the metabolic uptake rate constant (Ki) and to explore reliable acquisition times through simulations and clinical assessment considering patient comfort and quantification accuracy. METHODS: We simulated uptake kinetics in different tumors for four sets of DTP PET images within the routine clinical static acquisition at 60-min post-injection (p.i.). We determined Ki for a total of 81 lesions. Ki quantification from full dynamic PET data (Patlak-Ki) and Ki from DTP (DTP-Ki) were compared. In addition, we scaled a population-based input function (PBIFscl) with the image-derived blood pool activity sampled at different time points to assess the best scaling time-point for Ki quantifications in the simulation data. RESULTS: In the simulation study, Ki estimated using DTP via (30,60-min), (30,90-min), (60,90-min), and (60,120-min) samples showed strong correlations (r ≥ 0.944, P < 0.0001) with the true value of Ki. The DTP results with the PBIFscl at 60-min time-point in (30,60-min), (60,90-min), and (60,120-min) were linearly related to the true Ki with a slope of 1.037, 1.008, 1.013 and intercept of -6 × 10-4, 2 × 10-5, 5 × 10-5, respectively. In a clinical study, strong correlations (r ≥ 0.833, P < 0.0001) were observed between Patlak-Ki and DTP-Ki. The Patlak-derived mean values of Ki, tumor-to-background-ratio, signal-to-noise-ratio, and contrast-to-noise-ratio were linearly correlated with the DTP method. CONCLUSIONS: Besides calculating the retention index as a commonly used quantification parameter inDTP imaging,our DTP method can accurately estimate Ki.

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.

Radiomics predictive modeling from dual-time-point FDG PET Ki parametric maps: application to chemotherapy response in lymphoma.

BACKGROUND: To investigate the use of dynamic radiomics features derived from dual-time-point (DTP-feature) [18F]FDG PET metabolic uptake rate Ki parametric maps to develop a predictive model for response to chemotherapy in lymphoma patients. METHODS: We analyzed 126 lesions from 45 lymphoma patients (responding n = 75 and non-responding n = 51) treated with chemotherapy from two different centers. Static and DTP radiomics features were extracted from baseline static PET images and DTP Ki parametric maps. Spearman's rank correlations were calculated between static and DTP features to identify features with potential additional information. We first employed univariate analysis to determine correlations between individual features, and subsequently utilized multivariate analysis to derive predictive models utilizing DTP and static radiomics features before and after ComBat harmonization. For multivariate modeling, we utilized both the minimum redundancy maximum relevance feature selection technique and the XGBoost classifier. To evaluate our model, we partitioned the patient datasets into training/validation and testing sets using an 80/20% split. Different metrics for classification including area under the curve (AUC), sensitivity (SEN), specificity (SPE), and accuracy (ACC) were reported in test sets. RESULTS: Via Spearman's rank correlations, there was negligible to moderate correlation between 32 out of 65 DTP features and some static features (ρ < 0.7); all the other 33 features showed high correlations (ρ ≥ 0.7). In univariate modeling, no significant difference between AUC of DTP and static features was observed. GLRLM_RLNU from static features demonstrated a strong correlation (AUC = 0.75, p value = 0.0001, q value = 0.0007) with therapy response. The most predictive DTP features were GLCM_Energy, GLCM_Entropy, and Uniformity, each with AUC = 0.73, p value = 0.0001, and q value < 0.0005. In multivariate analysis, the mean ranges of AUCs increased following harmonization. Use of harmonization plus combining DTP and static features was shown to provide significantly improved predictions (AUC = 0.97 ± 0.02, accuracy = 0.89 ± 0.05, sensitivity = 0.92 ± 0.09, and specificity = 0.88 ± 0.05). All models depicted significant performance in terms of AUC, ACC, SEN, and SPE (p < 0.05, Mann-Whitney test). CONCLUSIONS: Our results demonstrate significant value in harmonization of radiomics features as well as combining DTP and static radiomics models for predicting response to chemotherapy in lymphoma patients.

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.

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.

"Clickable" Albumin Binders for Modulating the Tumor Uptake of Targeted Radiopharmaceuticals.

The intentional binding of radioligands to albumin gains increasing attention in the context of radiopharmaceutical cancer therapy as it can lead to an enhanced radioactivity uptake into the tumor lesions and, thus, to a potentially improved therapeutic outcome. However, the influence of the radioligand's albumin-binding affinity on the time profile of tumor uptake has been only partly addressed so far. Based on the previously identified Nε-4-(4-iodophenyl)butanoyl-lysine scaffold, we designed "clickable" lysine-derived albumin binders (cLABs) and determined their dissociation constants toward albumin by novel assay methods. Structure-activity relationships were derived, and selected cLABs were applied for the modification of the somatostatin receptor subtype 2 ligand (Tyr3)octreotate. These novel conjugates were radiolabeled with copper-64 and subjected to a detailed in vitro and in vivo radiopharmacological characterization. Overall, the results of this study provide an incentive for further investigations of albumin binders for applications in endoradionuclide therapies.

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.

Final Results of the Prospective Biomarker Trial PETra: [11C]-MET-Accumulation in Postoperative PET/MRI Predicts Outcome after Radiochemotherapy in Glioblastoma.

PURPOSE: This prospective trial investigates the association of time to recurrence (TTR) in glioblastoma with [11C]methionine (MET) tracer uptake before postoperative radiochemotherapy (RCT) aiming to guide radiotherapy boost regions. EXPERIMENTAL DESIGN: Between 2013 and 2016, 102 patients with glioblastoma were recruited. RCT was performed with concurrent and adjuvant temozolomide to a total dose of 60 Gy. Tumor residues in postresection PET and MRI were together defined as gross tumor volumes for radiotherapy treatment planning. [11C]methionine (MET)-PET/MRI was performed before RCT and at each follow-up. RESULTS: The primary hypothesis of a longer TTR for patients without increased tracer accumulation in postoperative MET-PET was confirmed in 89 patients. With 18.9 months (95% confidence interval, 9.3-28.5 months), median TTR was significantly (P < 0.001) longer for patients without (n = 29, 32.6%) as compared with 6.3 months (3.6-8.9) for patients with MET accumulation (n = 60, 67.4%) in pre-RCT PET. Although MRI often did not detect all PET-positive regions, an unfavorable impact of residual tumor in postsurgical MRI (n = 38, 42.7%) on TTR was observed [4.6 (4.2-5.1) vs. 15.5 months (6.0-24.9), P < 0.001]. Significant multivariable predictors for TTR were MRI positivity, PET-positive volume, and O6-methylguanine DNA methyltransferase (MGMT) hypermethylation. CONCLUSIONS: Postsurgical amino acid PET has prognostic value for TTR after RCT in glioblastoma. Because of the added value of the metabolic beyond the pure structural information, it should complement MRI in radiotherapy planning if available with reasonable effort, at least in the context of maximal therapy. Furthermore, the spatial correlation of regions of recurrence with PET-positive volumes could provide a bioimaging basis for further trials, for example, testing local radiation dose escalation.

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.

Short-duration dynamic FDG PET imaging: Optimization and clinical application.

PURPOSE: We aimed to investigate whether short dynamic PET imaging started at injection, complemented with routine clinical acquisition at 60-min post-injection (static), can achieve reliable kinetic analysis. METHODS: Dynamic and static 18F-2-fluoro-2-deoxy-D-glucose (FDG) PET data were generated using realistic simulations to assess uncertainties due to statistical noise as well as bias. Following image reconstructions, kinetic parameters obtained from a 2-tissue-compartmental model (2TCM) were estimated, making use of the static image, and the time duration of dynamic PET data were incrementally shortened. We also investigated, in the first 2-min, different frame sampling rates, towards optimized dynamic PET imaging. Kinetic parameters from shortened dynamic datasets were additionally estimated for 9 patients (15 scans) with liver metastases of colorectal cancer, and were compared with those derived from full dynamic imaging using correlation and Passing-Bablok regression analyses. RESULTS: The results showed that by reduction of dynamic scan times from 60-min to as short as 5-min, while using static data at 60-min post-injection, bias and variability stayed comparable in estimated kinetic parameters. Early frame samplings of 5, 24 and 30 s yielded highest biases compared to other schemes. An early frame sampling of 10 s generally kept both bias and variability to a minimum. In clinical studies, strong correlation (r ≥ 0.97, P < 0.0001) existed between all kinetic parameters in full vs. shortened scan protocols. CONCLUSIONS: Shortened 5-min dynamic scan, sampled as 12 × 10 + 6 × 30 s, followed by 3-min static image at 60-min post-injection, enables accurate and robust estimation of 2TCM parameters, while enabling generation of SUV estimates.

Dose dependent cerebellar atrophy in glioma patients after radio(chemo)therapy.

BACKGROUND AND PURPOSE: Radiotherapy is a standard treatment option for high-grade gliomas. Brain atrophy has previously been associated with radiotherapy. The goal of this study was to investigate dose dependent cerebellar atrophy using prospective, longitudinal MR data from adult glioma patients who received radiotherapy. MATERIALS AND METHODS: Cerebellar volumes were measured using T1-weighted MR images from 91 glioma patients before radiotherapy (N = 91) and from longitudinal follow-ups acquired in three monthly intervals (N = 349). Relative cerebellar volumes were calculated as ratios to the corresponding baseline values. Univariate mixed effects models were used to determine factors that were significantly associated with relative cerebellar volumes. These factors were subsequently included as fixed effects in a final multivariate linear mixed effects model. RESULTS: In multivariate analysis, cerebellar volume decreased significantly as a function of time (p < 0.001), time × dose (p < 0.001) and patient age (p = 0.007). Considering a 55 year patient receiving a mean cerebellar dose of 0 Gy (10 Gy), the linear mixed effects model predicts a relative cerebellar volume loss of 0.4% (2.0%) after 1 year and 0.7% (3.6%) after 2 years. Compared to patients treated with photons, the cerebellar dose was significantly lower in patients treated with proton therapy (p < 0.001, r = 0.62). CONCLUSION: Cerebellar volume decreased significantly and irreversibly after radiotherapy as function of time and mean cerebellar dose. Further work is now needed to correlate these results with cognitive function and motor performance.

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.

Olfactory dysfunction correlates with putaminal dopamine turnover in early de novo Parkinson's disease.

Although olfactory dysfunction is one of the most well-established prodromal symptoms in Parkinson's disease (PD), its correlation with clinical disease progression or dopaminergic dysfunction still remains unclear. We here evaluated the association of striatal dopamine metabolism and olfactory function in a homogenous cohort of 30 patients with early untreated de novo PD. Striatal dopamine metabolism was assessed by the extended 18Fluorodopa PET scanning protocol to measure 18Fluorodopa uptake (Kocc) and the effective dopamine distribution volume ratio (EDVR) as the inverse of dopamine turnover. Olfactory function was estimated by the "Sniffin' Sticks" test including odor threshold (T), discrimination (D) and identification (I) assessment. We detected moderate correlations of the EDVR in the posterior putamen with the TDI composite score (r = 0.412; p = 0.024; Pearson's correlation test) and the odor identification score (r = 0.444; p = 0.014). These correlations were confirmed by multivariate regression analyses using age, sex, symptom duration and disease severity as measured by UPDRSIII motor score as candidate covariates. No other associations were observed between olfaction measures and Kocc and EDVR in all striatal regions. Together, olfactory dysfunction in early PD is not correlated with striatal 18Fluorodopa uptake as a measure for dopaminergic degeneration, but with putaminal dopamine turnover as a marker for dopaminergic presynaptic compensatory processes in early PD. These results should be treated as hypothesis generating and require confirmation by larger multicenter studies.

Putaminal Dopamine Turnover in de novo Parkinson's Disease Predicts Later Neuropsychiatric Fluctuations but Not Other Major Health Outcomes.

BACKGROUND AND OBJECTIVE: To investigate the predictive value of striatal dopamine turnover in patients with de novo Parkinson's disease (PD) for later occurrence of major non-motor health outcomes. METHODS: This retrospective, observer-blinded cohort study followed up 29 patients with de novo PD for a median of 10.7 years, who completed 18Fluorodopa PET imaging to measure striatal effective distribution volume ratio (EDVR, inverse of dopamine turnover) prior to antiparkinsonian treatment. Outcomes were assessed with a battery of non-motor, health-related quality-of-life and non-motor fluctuation (WOQ-19) measures and survival. RESULTS: During follow-up, 52% of patients developed wearing-off, 43% neuropsychiatric fluctuations, 35% sensory fluctuations, 32% dementia, 46% depression, 30% psychosis, and PD-related mortality was 26%. Patients with wearing-off and neuropsychiatric fluctuations showed significantly lower baseline EDVR (higher dopamine turnover) in the putamen but not in the caudate nucleus than those without these fluctuations. Consistently, baseline EDVR in the putamen predicted development of wearing-off and neuropsychiatric fluctuations with a lower risk with higher EDVR (lower dopamine turnover), whereas EDVR in caudate nucleus did not correlate with these fluctuations. No relationships were observed between baseline PET measures and the presence of other major health outcomes including survival. CONCLUSIONS: Lower putaminal dopamine turnover in de novo PD is associated with reduced risk for later neuropsychiatric fluctuations comprising a disease-intrinsic predisposing factor for their development, similar as reported for levodopa-induced motor complications. Striatal (putaminal/caudate) dopamine turnover is not predictive for other long-term major health outcomes. These results should be treated as hypothesis generating and require confirmation.

Confirmation of the prognostic value of pretherapeutic tumor SUR and MTV in patients with esophageal squamous cell carcinoma.

PURPOSE: The prognosis for patients with inoperable esophageal carcinoma is still poor and the reliability of individual therapy outcome prediction based on clinical parameters is not convincing. In a recent publication, we were able to show that PET can provide independent prognostic information in such a patient group and that the tumor-to-blood standard uptake ratio (SUR) can improve the prognostic value of tracer uptake values. The present investigation addresses the question of whether the distinctly improved prognostic value of SUR can be confirmed in a similar patient group that was examined and treated at a different site. METHODS: 18F-FDG PET/CT was performed in 147 consecutive patients (115 male, 32 female, mean age: 62 years) with newly diagnosed esophageal squamous cell carcinoma prior to definitive radiochemotherapy. In the PET images, the metabolic active volume (MTV) of the primary tumor was delineated with an adaptive threshold method. For the resulting ROIs, SUVmax and total lesion glycolysis (TLG = MTV × SUVmean) were computed. The blood SUV was determined by manually delineating the aorta in the low-dose CT. SUR values were computed as ratio of tumor SUV and blood SUV. Univariate Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), distant-metastases-free survival (DM), and locoregional control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed. RESULTS: Univariate Cox regression revealed MTV, TLG, and SURmax as significant prognostic factors for OS. MTV as well as TLG were significant prognostic factors for LRC while SURmax showed only a trend for significance. None of the PET parameters was prognostic for DM. In univariate analysis, SUVmax was not prognostic for any of the investigated clinical endpoints. In multivariate analysis (T-stage, N-stage, MTV, and SURmax), MTV was an independent prognostic factor for OS and showed a trend for significance for LRC. SURmax was not an independent predictor for OS or LRC. When including the PET parameters separately in multivariate analysis, MTV as well as SURmax were prognostic factors for OS indicating that SURmax is independent from the clinical parameters but not from MTV. In addition, MTV was an independent prognostic factor for LRC in this separate analysis. CONCLUSIONS: Our study revealed a clearly improved prognostic value of tumor SUR compared to tumor SUV and confirms our previously published findings regarding OS. Furthermore, SUR delivers prognostic information beyond that provided by the clinical parameters alone, but does not add prognostic information beyond that provided by MTV in this patient group. Therefore, our results suggest that pretherapeutic MTV is the parameter of choice for PET-based risk stratification in the considered setting but further investigations are necessary to demonstrate that this suggestion is correct.

Time efficient scatter correction for time-of-flight PET: the immediate scatter approximation.

Utilization of time-of-flight (TOF) information allows us to improve image quality and convergence rate in iterative PET image reconstruction. In order to obtain quantitatively correct images accurate scatter correction (SC) is required that accounts for the non-uniform distribution of scatter events over the TOF bins. However, existing simplified TOF-SC algorithms frequently exhibit limited accuracy while the currently accepted reference method-the TOF extension of the single scatter simulation approach (TOF-SSS)-is computationally demanding and can substantially slow down the reconstruction. In this paper we propose and evaluate a new accelerated TOF-SC algorithm in order to improve this situation. The key idea of the algorithm is the use of an immediate scatter approximation (ISA) for scatter time distribution calculation which speeds up estimation of the required TOF scatter by a factor of up to five in comparison to TOF-SSS. The proposed approach was evaluated in dedicated phantom measurements providing challenging high activity contrast conditions as well as in representative clinical patient data sets. Our results show that ISA is a viable alternative to TOF-SSS. The reconstructed images are in excellent quantitative agreement with those obtained with TOF-SSS while overall reconstruction time can be reduced by a factor of two in whole-body studies, even when using a listmode reconstruction not optimized for speed.