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.

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.

Interobserver variability of image-derived arterial blood SUV in whole-body FDG PET.

BACKGROUND: Today, the standardized uptake value (SUV) is essentially the only means for quantitative evaluation of static [18F-]fluorodeoxyglucose (FDG) positron emission tomography (PET) investigations. However, the SUV approach has several well-known shortcomings which adversely affect the reliability of the SUV as a surrogate of the metabolic rate of glucose consumption. The standard uptake ratio (SUR), i.e., the uptake time-corrected ratio of tumor SUV to image-derived arterial blood SUV, has been shown in the first clinical studies to overcome most of these shortcomings, to decrease test-retest variability, and to increase the prognostic value in comparison to SUV. However, it is unclear, to what extent the SUR approach is vulnerable to observer variability of the additionally required blood SUV (BSUV) determination. The goal of the present work was the investigation of the interobserver variability of image-derived BSUV. METHODS: FDG PET/CT scans from 83 patients (72 male, 11 female) with non-small cell lung cancer (N = 46) or head and neck cancer (N = 37) were included. BSUV was determined by 8 individuals, each applying a dedicated delineation tool for the BSUV determination in the aorta. Two of the observers applied two further tools. Altogether, five different delineation tools were used. With each used tool, delineation was performed for the whole patient group, resulting in 12 distinct observations per patient. Intersubject variability of BSUV determination was assessed using the fractional deviations for the individual patients from the patient group average and was quantified as standard deviation (SD is), 95% confidence interval, and range. Interobserver variability of BSUV determination was assessed using the fractional deviations of the individual observers from the observer-average for the considered patient and quantified as standard deviations (SD p, SD d) or root mean square (RMS), 95% confidence interval, and range in each patient, each observer, and the pooled data respectively. RESULTS: Interobserver variability in the pooled data amounts to RMS = 2.8% and is much smaller than the intersubject variability of BSUV (SD is= 16%). Averaged over the whole patient group, deviations of individual observers from the observer average are very small and fall in the range [ - 0.96, 1.05]%. However, interobserver variability partly differs distinctly for different patients, covering a range of [0.7, 7.4]% in the investigated patient group. CONCLUSION: The present investigation demonstrates that the image-based manual determination of BSUV in the aorta is sufficiently reproducible across different observers and delineation tools which is a prerequisite for accurate SUR determination. This finding is in line with the already demonstrated superior prognostic value of SUR in comparison to SUV in the first clinical studies.

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.

Monitoring scanner calibration using the image-derived arterial blood SUV in whole-body FDG-PET.

BACKGROUND: The current de facto standard for quantification of tumor metabolism in oncological whole-body PET is the standardized uptake value (SUV) approach. SUV determination requires accurate scanner calibration. Residual inaccuracies of the calibration lead to biased SUV values. Especially, this can adversely affect multicenter trials where it is difficult to ensure reliable cross-calibration across participating sites. The goal of the present work was the evaluation of a new method for monitoring scanner calibration utilizing the image-derived arterial blood SUV (BSUV) averaged over a sufficiently large number of whole-body FDG-PET investigations. Data of 681 patients from three sites which underwent routine 18F-FDG PET/CT or PET/MR were retrospectively analyzed. BSUV was determined in the descending aorta using a three-dimensional ROI concentric to the aorta's centerline. The ROI was delineated in the CT or MRI images and transferred to the PET images. A minimum ROI volume of 5 mL and a concentric safety margin to the aortic wall was observed. Mean BSUV, standard deviation (SD), and standard error of the mean (SE) were computed for three groups of patients at each site, investigated 2 years apart, respectively, with group sizes between 53 and 100 patients. Differences of mean BSUV between the individual groups and sites were determined. RESULTS: SD (SE) of BSUV in the different groups ranged from 14.3 to 20.7% (1.7 to 2.8%). Differences of mean BSUV between intra-site groups were small (1.1-6.3%). Only one out of nine of these differences reached statistical significance. Inter-site differences were distinctly larger (12.6-25.1%) and highly significant (P<0.001). CONCLUSIONS: Image-based determination of the group-averaged blood SUV in modestly large groups of whole-body FDG-PET investigations is a viable approach for ensuring consistent scanner calibration over time and across different sites. We propose this approach as a quality control and cross-calibration tool augmenting established phantom-based procedures.

Photon vs. proton radiochemotherapy: Effects on brain tissue volume and perfusion.

BACKGROUND AND PURPOSE: To compare the structural and hemodynamic changes of healthy brain tissue in the cerebral hemisphere contralateral to the tumor following photon and proton radiochemotherapy. MATERIALS AND METHODS: Sixty-seven patients (54.9 ±14.0 years) diagnosed with glioblastoma undergoing adjuvant photon (n = 47) or proton (n = 19) radiochemotherapy with temozolomide after tumor resection underwent T1-weighted and arterial spin labeling MRI. Changes in volume and perfusion before and 3 to 6 months after were compared between therapies. RESULTS: A decrease in gray matter (GM) (-2.2%, P<0.001) and white matter (WM) (-1.2%, P<0.001) volume was observed in photon-therapy patients compared to the pre-radiotherapy baseline. In contrast, for the proton-therapy group, no significant differences in GM (0.3%, P = 0.64) or WM (-0.4%, P = 0.58) volume were observed. GM volume decreased with 0.9% per 10 Gy dose increase (P<0.001) and differed between the radiation modalities (P<0.001). Perfusion decreased in photon-therapy patients (-10.1%, P = 0.002), whereas the decrease in proton-therapy patients, while comparable in magnitude, did not reach statistical significance (-9.1%, P = 0.12). There was no correlation between perfusion decrease and either dose (P = 0.64) or radiation modality (P = 0.94). CONCLUSIONS: Our results show that the tissue volume decrease depends on radiation dose delivered to the healthy hemisphere and differs between treatment modalities. In contrast, the decrease in perfusion was comparable for both irradiation modalities. We conclude that proton therapy may reduce brain-volume loss when compared to photon therapy.

FDG PET/MR in initial staging of sarcoma: Initial experience and comparison with conventional imaging.

OBJECTIVE: To assess the feasibility of positron emission tomography/magnetic resonance imaging (PET/MR) with 18F-fluordeoxyglucose (FDG) for initial staging of sarcoma. MATERIALS AND METHODS: Twenty-nine patients with sarcoma were included in this study. Weighted kappa (κ) was used to assess the agreement between PET/MR and conventional imaging (CT and MR). The accuracy of PET/MR and conventional imaging for distant metastases was compared using receiver operating characteristic (ROC) analysis. RESULTS: T and M stage were identical for PET/MR and conventional modalities in all patients (κ=1). N stage was identical for 28/29 patients (κ=0.65). CONCLUSIONS: FDG PET/MR shows excellent agreement with the currently preferred imaging methods (CT and MR) in initial staging of sarcoma.

Early and late effects of radiochemotherapy on cerebral blood flow in glioblastoma patients measured with non-invasive perfusion MRI.

BACKGROUND AND PURPOSE: To provide a systematic measure of changes of brain perfusion in healthy tissue following a fractionated radiotherapy of brain tumors. MATERIALS AND METHODS: Perfusion was assessed before and after radiochemotherapy using arterial spin labeling in a group of 24 patients (mean age 54.3 ± 14.1 years) with glioblastoma multiforme. Mean relative perfusion change in gray matter in the hemisphere contralateral to the tumor was obtained for the whole hemisphere and also for six regions created by thresholding the individual dose maps at 10 Gy steps. RESULTS: A significant decrease of perfusion of -9.8 ± 20.9% (p=0.032) compared to the pre-treatment baseline was observed 3 months after the end of radiotherapy. The decrease was more pronounced for high-dose regions above 50 Gy (-16.8 ± 21.0%, p=0.0014) than for low-dose regions below 10 Gy (-2.3 ± 20.0%, p=0.54). No further significant decrease compared to the post-treatment baseline was observed 6 months (-0.4 ± 18.4%, p=0.94) and 9 months (2.0 ± 15.4%, p=0.74) after the end of radiotherapy. CONCLUSIONS: Perfusion decreased significantly during the course of radiochemotherapy. The decrease was higher in regions receiving a higher dose of radiation. This suggests that the perfusion decrease is at least partly caused by radiotherapy. Our results suggest that the detrimental effects of radiochemotherapy on perfusion occur early rather than later.

Correction of quantification errors in pelvic and spinal lesions caused by ignoring higher photon attenuation of bone in [18F]NaF PET/MR.

PURPOSE: MR-based attenuation correction (MRAC) in routine clinical whole-body positron emission tomography and magnetic resonance imaging (PET/MRI) is based on tissue type segmentation. Due to lack of MR signal in cortical bone and the varying signal of spongeous bone, standard whole-body segmentation-based MRAC ignores the higher attenuation of bone compared to the one of soft tissue (MRACnobone). The authors aim to quantify and reduce the bias introduced by MRACnobone in the standard uptake value (SUV) of spinal and pelvic lesions in 20 PET/MRI examinations with [18F]NaF. METHODS: The authors reconstructed 20 PET/MR [18F]NaF patient data sets acquired with a Philips Ingenuity TF PET/MRI. The PET raw data were reconstructed with two different attenuation images. First, the authors used the vendor-provided MRAC algorithm that ignores the higher attenuation of bone to reconstruct PETnobone. Second, the authors used a threshold-based algorithm developed in their group to automatically segment bone structures in the [18F]NaF PET images. Subsequently, an attenuation coefficient of 0.11 cm(-1) was assigned to the segmented bone regions in the MRI-based attenuation image (MRACbone) which was used to reconstruct PETbone. The automatic bone segmentation algorithm was validated in six PET/CT [18F]NaF examinations. Relative SUVmean and SUVmax differences between PETbone and PETnobone of 8 pelvic and 41 spinal lesions, and of other regions such as lung, liver, and bladder, were calculated. By varying the assigned bone attenuation coefficient from 0.11 to 0.13 cm(-1), the authors investigated its influence on the reconstructed SUVs of the lesions. RESULTS: The comparison of [18F]NaF-based and CT-based bone segmentation in the six PET/CT patients showed a Dice similarity of 0.7 with a true positive rate of 0.72 and a false discovery rate of 0.33. The [18F]NaF-based bone segmentation worked well in the pelvis and spine. However, it showed artifacts in the skull and in the extremities. The analysis of the 20 [18F]NaF PET/MRI examinations revealed relative SUVmax differences between PETnobone and PETbone of (-8.8%±2.7%, p=0.01) and (-8.1%±1.9%, p=2.4×10(-8)) in pelvic and spinal lesions, respectively. A maximum SUVmax underestimation of -13.7% was found in lesion in the third cervical spine. The averaged SUVmean differences in volumes of interests in lung, liver, and bladder were below 3%. The average SUVmax differences in pelvic and spinal lesions increased from -9% to -18% and -8% to -17%, respectively, when increasing the assigned bone attenuation coefficient from 0.11 to 0.13 cm(-1). CONCLUSIONS: The developed automatic [18F]NaF PET-based bone segmentation allows to include higher bone attenuation in whole-body MRAC and thus improves quantification accuracy for pelvic and spinal lesions in [18F]NaF PET/MRI examinations. In nonbone structures (e.g., lung, liver, and bladder), MRACnobone yields clinically acceptable accuracy.

Evaluation of in vivo quantification accuracy of the Ingenuity-TF PET/MR.

PURPOSE: The quantitative accuracy of standardized uptake values (SUVs) and tracer kinetic uptake parameters in patient investigations strongly depends on accurate determination of regional activity concentrations in positron emission tomography (PET) data. This determination rests on the assumption that the given scanner calibration is valid in vivo. In a previous study, we introduced a method to test this assumption. This method allows to identify discrepancies in quantitative accuracy in vivo by comparison of activity concentrations of urine samples measured in a well-counter with activity concentrations extracted from PET images of the bladder. In the present study, we have applied this method to the Philips Ingenuity-TF PET/MR since at the present stage, absolute quantitative accuracy of combined PET/MR systems is still under investigation. METHODS: Twenty one clinical whole-body F18-FDG scans were included in this study. The bladder region was imaged as the last bed position and urine samples were collected afterward. PET images were reconstructed including MR-based attenuation correction with and without truncation compensation and 3D regions-of-interest (ROIs) of the bladder were delineated by three observers. To exclude partial volume effects, ROIs were concentrically shrunk by 8-10 mm. Then, activity concentrations were determined in the PET images for the bladder and for the urine by measuring the samples in a calibrated well-counter. In addition, linearity measurements of SUV vs singles rate and measurements of the stability of the coincidence rate of "true" events of the PET/MR system were performed over a period of 4 months. RESULTS: The measured in vivo activity concentrations were significantly lower in PET/MR than in the well-counter with a ratio of the former to the latter of 0.756 ± 0.060 (mean ± std. dev.), a range of 0.604-0.858, and a P value of 3.9 ⋅ 10(-14). While the stability measurements of the coincidence rate of "true" events showed no relevant deviation over time, the linearity scans revealed a systematic error of 8%-11% (avg. 9%) for the range of singles rates present in the bladder scans. After correcting for this systematic bias caused by shortcomings of the manufacturers calibration procedure, the PET to well-counter ratio increased to 0.832 ± 0.064 (0.668 -0.941), P = 1.1 ⋅ 10(-10). After compensating for truncation of the upper extremities in the MR-based attenuation maps, the ratio further improved to 0.871 ± 0.069 (0.693-0.992), P = 3.9 ⋅ 10(-8). CONCLUSIONS: Our results show that the Philips PET/MR underestimates activity concentrations in the bladder by 17%, which is 7 percentage points (pp.) larger than in the previously investigated PET and PET/CT systems. We attribute this increased underestimation to remaining limitations of the MR-based attenuation correction. Our results suggest that only a 2 pp. larger underestimation of activity concentrations compared to PET/CT can be observed if compensation of attenuation truncation of the upper extremities is applied. Thus, quantification accuracy of the Philips Ingenuity-TF PET/MR can be considered acceptable for clinical purposes given the ±10% error margin in the EANM guidelines. The comparison of PET images from the bladder region with urine samples has proven a useful method. It might be interesting for evaluation and comparison of the in vivo quantitative accuracy of PET, PET/CT, and especially PET/MR systems from different manufacturers or in multicenter trials.

On the relation between Kaiser-Bessel blob and tube of response based modelling of the system matrix in iterative PET image reconstruction.

We investigate the question of how the blob approach is related to tube of response based modelling of the system matrix. In our model, the tube of response (TOR) is approximated as a cylinder with constant density (TOR-CD) and the cubic voxels are replaced by spheres. Here we investigate a modification of the TOR model that makes it effectively equivalent to the blob model, which models the intersection of lines of response (LORs) with radially variant basis functions ('blobs') replacing the cubic voxels. Implications of the achieved equivalence regarding the necessity of final resampling in blob-based reconstructions are considered. We extended TOR-CD to a variable density tube model (TOR-VD) that yields a weighting function (defining all system matrix elements) which is essentially identical to that of the blob model. The variable density of TOR-VD was modelled by a Gaussian and a Kaiser-Bessel function, respectively. The free parameters of both model functions were determined by fitting the corresponding weighting function to the weighting function of the blob model. TOR-CD and the best-fitting TOR-VD were compared to the blob model with a final resampling step (BLOB-RS) and without resampling (BLOB-NRS) in phantom studies. For three different contrast ratios and two different voxel sizes, resolution noise curves were generated. TOR-VD and BLOB-NRS lead to nearly identical images for all investigated contrast ratios and voxel sizes. Both models showed strong Gibbs artefacts at 4 mm voxel size, while at 2 mm voxel size there were no Gibbs artefacts visible. The spatial resolution was similar to the resolution with TOR-CD in all cases. The resampling step removed most of the Gibbs artefacts and reduced the noise level but also degraded the spatial resolution substantially. We conclude that the blob model can be considered just as a special case of a TOR-based reconstruction. The latter approach provides a more natural description of the detection process and allows for modifications that are not readily representable within the blob framework.

FDG PET/MR for the assessment of lymph node involvement in lymphoma: initial results and role of diffusion-weighted MR.

RATIONALE AND OBJECTIVES: The purpose of this study was to evaluate the sensitivity and specificity of positron emission tomography/magnetic resonance imaging (PET/MR) with 18F-fluorodeoxyglucose (FDG) for nodal involvement in malignant lymphoma. MATERIALS AND METHODS: Twenty-seven patients with malignant lymphoma (16 men and 11 women; mean age, 45 years) were included in this retrospective study. The patients underwent FDG PET/MR after intravenous injection of FDG (176-357 MBq FDG, 282 MBq on average). Follow-up imaging and histology served as the standard of reference. RESULTS: One-hundred and twenty-seven (18.1%) of 702 lymph node stations were rated as having lymphoma involvement based on the standard of reference. One-hundred and twenty-four (17.7%) of 702 lymph node stations were rated as positive by FDG PET/MR. The sensitivity and specificity of FDG PET/MR for lymph node station involvement were 93.8% and 99.4%. CONCLUSIONS: FDG PET/MR is feasible for lymphoma staging and has a high sensitivity and specificity for nodal involvement in lymphoma. Comparison with PET/CT is necessary to determine whether FDG PET/MR can replace PET/CT for lymphoma staging.

Correction of scan time dependence of standard uptake values in oncological PET.

BACKGROUND: Standard uptake values (SUV) as well as tumor-to-blood standard uptake ratios (SUR) measured with [ 18F-]fluorodeoxyglucose (FDG) PET are time dependent. This poses a serious problem for reliable quantification since variability of scan start time relative to the time of injection is a persistent issue in clinical oncological Positron emission tomography (PET). In this work, we present a method for scan time correction of, both, SUR and SUV. METHODS: Assuming irreversible FDG kinetics, SUR is linearly correlated to Km (the metabolic rate of FDG), where the slope only depends on the shape of the arterial input function (AIF) and on scan time. Considering the approximately invariant shape of the AIF, this slope (the 'Patlak time') is an investigation independent function of scan time. This fact can be used to map SUR and SUV values from different investigations to a common time point for quantitative comparison. Additionally, it turns out that modelling the invariant AIF shape by an inverse power law is possible which further simplifies the correction procedure. The procedure was evaluated in 15 fully dynamic investigations of liver metastases from colorectal cancer and 10 dual time point (DTP) measurements. From each dynamic study, three 'static scans' at T=20,35,and 55 min post injection (p.i.) were created, where the last scan defined the reference time point to which the uptake values measured in the other two were corrected. The corrected uptake values were then compared to those actually measured at the reference time. For the DTP studies, the first scan (acquired at (78.1 ± 15.9) min p.i.) served as the reference, and the uptake values from the second scan (acquired (39.2 ± 9.9) min later) were corrected accordingly and compared to the reference. RESULTS: For the dynamic data, the observed difference between uncorrected values and values at reference time was (-52±4.5)% at T=20 min and (-31±3.7)% at T=35 min for SUR and (-30±6.6)% at T=20 min and (-16±4)% at T=35 min for SUV. After correction, the difference was reduced to (-2.9±6.6)% at T=20 min and (-2.7±5)% at T=35 min for SUR and (1.9% ± 6.2)% at T=20 min and (1.7 ± 3.3)% at T=35 min for SUV. For the DTP studies, the observed differences of SUR and SUV between late and early scans were (48 ± 11)% and (24 ± 8.4)%, respectively. After correction, these differences were reduced to (2.6 ± 6.9)% and (-2.4±7.3)%, respectively. CONCLUSION: If FDG kinetics is irreversible in the targeted tissue, correction of SUV and SUR for scan time variability is possible with good accuracy. The correction distinctly improves comparability of lesion uptake values measured at different times post injection.

FDG PET/MR for lymph node staging in head and neck cancer.

OBJECTIVE: To assess the diagnostic value of PET/MR (positron emission tomography/magnetic resonance imaging) with FDG (18F-fluorodeoxyglucose) for lymph node staging in head and neck cancer. MATERIALS AND METHODS: This prospective study was approved by the local ethics committee; all patients signed informed consent. Thirty-eight patients with squamous cell carcinoma of the head and neck region underwent a PET scan on a conventional scanner and a subsequent PET/MR on a whole-body hybrid system after a single intravenous injection of FDG. The accuracy of PET, MR and PET/MR for lymph node metastases were compared using receiver operating characteristic (ROC) analysis. Histology served as the reference standard. RESULTS: Metastatic disease was confirmed in 16 (42.1%) of 38 patients and 38 (9.7%) of 391 dissected lymph node levels. There were no significant differences between PET/MR, MR and PET and MR (p>0.05) regarding accuracy for cervical metastatic disease. Based on lymph node levels, sensitivity and specificity for metastatic involvement were 65.8% and 97.2% for MR, 86.8% and 97.0% for PET and 89.5% and 95.2% for PET/MR. CONCLUSIONS: In head and neck cancer, FDG PET/MR does not significantly improve accuracy for cervical lymph node metastases in comparison to MR or PET.

The PET-derived tumor-to-blood standard uptake ratio (SUR) is superior to tumor SUV as a surrogate parameter of the metabolic rate of FDG.

BACKGROUND: The standard uptake value (SUV) approach in oncological positron emission tomography has known shortcomings, all of which affect the reliability of the SUV as a surrogate of the targeted quantity, the metabolic rate of [18F]fluorodeoxyglucose (FDG), Km. Among the shortcomings are time dependence, susceptibility to errors in scanner and dose calibration, insufficient correlation between systemic distribution volume and body weight, and, consequentially, residual inter-study variability of the arterial input function (AIF) despite SUV normalization. Especially the latter turns out to be a crucial factor adversely affecting the correlation between SUV and Km and causing inter-study variations of tumor SUVs that do not reflect actual changes of the metabolic uptake rate. In this work, we propose to replace tumor SUV by the tumor-to-blood standard uptake ratio (SUR) in order to distinctly improve the linear correlation with Km. METHODS: Assuming irreversible FDG kinetics, SUR can be expected to exhibit a much better linear correlation to Km than SUV. The theoretical derivation for this prediction is given and evaluated in a group of nine patients with liver metastases of colorectal cancer for which 15 fully dynamic investigations were available and Km could thus be derived from conventional Patlak analysis. RESULTS: For any fixed time point T at sufficiently late times post injection, the Patlak equation predicts a linear correlation between SUR and Km under the following assumptions: (1) approximate shape invariance (but arbitrary scale) of the AIF across scans/patients and (2) low variability of the apparent distribution volume Vr (the intercept of the Patlak Plot). This prediction - and validity of the underlying assumptions - has been verified in the investigated patient group. Replacing tumor SUVs by SURs does improve the linear correlation of the respective parameter with Km from r = 0.61 to r = 0.98. CONCLUSIONS: SUR is an easily measurable parameter that is highly correlated to Km. In this respect, it is clearly superior to SUV. Therefore, SUR should be seriously considered as a drop-in replacement for SUV-based approaches.