Increased evidence for the prognostic value of primary tumor asphericity in pretherapeutic FDG PET for risk stratification in patients with head and neck cancer.

PURPOSE: In a previous study, we demonstrated the first evidence that the asphericity (ASP) of pretherapeutic FDG uptake in the primary tumor provides independent prognostic information in patients with head and neck cancer. The aim of this work was to confirm these results in an independent patient group examined at a different site. METHODS: FDG-PET/CT was performed in 37 patients. The primary tumor was delineated by an automatic algorithm based on adaptive thresholding. For the resulting ROIs, the metabolically active part of the tumor (MTV), SUVmax, SUVmean, total lesion glycolysis (TLG) and ASP were computed. Univariate Cox regression with respect to progression free survival (PFS) and overall survival (OS) was performed. For survival analysis, patients were divided in groups of high and low risk according to the parameter cut-offs defined in our previous work. In a second step, the cut-offs were adjusted to the present data. Univariate and multivariate Cox regression was performed for the pooled data consisting of the current and the previously described patient group (N = 68). In multivariate Cox regression, clinically relevant parameters were included. RESULTS: Univariate Cox regression using the previously published cut-off values revealed TLG (hazard ratio (HR) = 3) and ASP (HR = 3) as significant predictors for PFS. For OS MTV (HR = 2.7) and ASP (HR = 5.9) were significant predictors. Using the adjusted cutoffs MTV (HR = 2.9/3.3), TLG (HR = 3.1/3.3) and ASP (HR = 3.1/5.9) were prognostic for PFS/OS. In the pooled data, multivariate Cox regression revealed a significant prognostic value with respect to PFS/OS for MTV (HR = 2.3/2.1), SUVmax (HR = 2.1/2.5), TLG (HR = 3.5/3.6), and ASP (HR = 3.4/4.4). CONCLUSIONS: Our results confirm the independent prognostic value of ASP of the pretherapeutic FDG uptake in the primary tumor in patients with head and neck cancer. Moreover, these results demonstrate that ASP can be determined unambiguously across different sites.

Quantitative assessment of the asphericity of pretherapeutic FDG uptake as an independent predictor of outcome in NSCLC.

BACKGROUND: The aim of the present study was to evaluate the predictive value of a novel quantitative measure for the spatial heterogeneity of FDG uptake, the asphericity (ASP) in patients with non-small cell lung cancer (NSCLC). METHODS: FDG-PET/CT had been performed in 60 patients (15 women, 45 men; median age, 65.5 years) with newly diagnosed NSCLC prior to therapy. The FDG-PET image of the primary tumor was segmented using the ROVER 3D segmentation tool based on thresholding at the volume-reproducing intensity threshold after subtraction of local background. ASP was defined as the relative deviation of the tumor's shape from a sphere. Univariate and multivariate Cox regression as well as Kaplan-Meier (KM) analysis and log-rank test with respect to overall (OAS) and progression-free survival (PFS) were performed for clinical variables, SUVmax/mean, metabolically active tumor volume (MTV), total lesion glycolysis (TLG), ASP and "solidity", another measure of shape irregularity. RESULTS: ASP, solidity and "primary surgical treatment" were significant independent predictors of PFS in multivariate Cox regression with binarized parameters (HR, 3.66; p<0.001, HR, 2.11; p=0.05 and HR, 2.09; p=0.05), ASP and "primary surgical treatment" of OAS (HR, 3.19; p=0.02 and HR, 3.78; p=0.01, respectively). None of the other semi-quantitative PET parameters showed significant predictive value with respect to OAS or PFS. Kaplan-Meier analysis revealed a probability of 2-year PFS of 52% in patients with low ASP compared to 12% in patients with high ASP (p<0.001). Furthermore, it showed a higher OAS rate in the case of low versus high ASP (1-year-OAS, 91% vs. 67%: p=0.02). CONCLUSIONS: The novel parameter asphericity of pretherapeutic FDG uptake seems to provide better prognostic value for PFS and OAS in NCSLC compared to SUV, metabolic tumor volume, total lesion glycolysis and solidity.

Asphericity of pretherapeutic tumour FDG uptake provides independent prognostic value in head-and-neck cancer.

OBJECTIVE: To propose a novel measure, namely the 'asphericity' (ASP), of spatial irregularity of FDG uptake in the primary tumour as a prognostic marker in head-and-neck cancer. METHODS: PET/CT was performed in 52 patients (first presentation, n = 36; recurrence, n = 16). The primary tumour was segmented based on thresholding at the volume-reproducible intensity threshold after subtraction of the local background. ASP was used to characterise the deviation of the tumour's shape from sphere symmetry. Tumour stage, tumour localisation, lymph node metastases, distant metastases, SUVmax, SUVmean, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were also considered. The association of overall (OAS) and progression-free survival (PFS) with these parameters was analysed. RESULTS: Cox regression revealed high SUVmax [hazard ratio (HR) = 4.4/7.4], MTV (HR = 4.6/5.7), TLG (HR = 4.8/8.9) and ASP (HR = 7.8/7.4) as significant predictors with respect to PFS/OAS in case of first tumour manifestation. The combination of high MTV and ASP showed very high HRs of 22.7 for PFS and 13.2 for OAS. In case of recurrence, MTV (HR = 3.7) and the combination of MTV/ASP (HR = 4.2) were significant predictors of PFS. CONCLUSIONS: ASP of pretherapeutic FDG uptake in the primary tumour improves the prediction of tumour progression in head-and-neck cancer at first tumour presentation. KEY POINTS: Asphericity (ASP) characterises the spatial heterogeneity of FDG uptake in tumours. ASP is a promising prognostic parameter in head-and-neck cancer. ASP is useful for identification of high-risk patients with head-and-neck cancer.

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.

Comparative evaluation of SUV, tumor-to-blood standard uptake ratio (SUR), and dual time point measurements for assessment of the metabolic uptake rate in FDG PET.

BACKGROUND: We have demonstrated recently that the tumor-to-blood standard uptake ratio (SUR) is superior to tumor standardized uptake value (SUV) as a surrogate of the metabolic uptake rate K m of fluorodeoxyglucose (FDG), overcoming several of the known shortcomings of the SUV approach: excellent linear correlation of SUR and K m from Patlak analysis was found using dynamic imaging of liver metastases. However, due to the perfectly standardized uptake period used for SUR determination and the comparatively short uptake period, these results are not automatically valid and applicable for clinical whole-body examinations in which the uptake periods (T) are distinctly longer and can vary considerably. Therefore, the aim of this work was to investigate the correlation between SUR derived from clinical static whole-body scans and K m-surrogate derived from dual time point (DTP) measurements. METHODS: DTP (18)F-FDG PET/CT was performed in 90 consecutive patients with histologically proven non-small cell lung cancer (NSCLC). In the PET images, the primary tumor was delineated with an adaptive threshold method. For determination of the blood SUV, an aorta region of interest (ROI) was delineated manually in the attenuation CT and transferred to the PET image. Blood SUV was computed as the mean value of the aorta ROI. SUR values were computed as ratio of tumor SUV and blood SUV. SUR values from the early time point of each DTP measurement were scan time corrected to 75 min postinjection (SURtc). As surrogate of K m, we used the SUR(T) slope, K slope, derived from DTP measurements since it is proportional to the latter under the given circumstances. The correlation of SUV and SURtc with K slope was investigated. The prognostic value of SUV, SURtc, and K slope for overall survival (OS) and progression-free survival (PFS) was investigated with univariate Cox regression in a homogeneous subgroup (N=31) treated with primary chemoradiation. RESULTS: Correlation analysis revealed for both, SUV and SURtc, a clear linear correlation with K slope (P<0.001). Correlation SUR vs. K slope was considerably stronger than correlation SUV vs. K slope (R (2)=0.92 and R (2)=0.69, respectively, P<0.001). Univariate Cox regression revealed SURtc and K slope as significant prognostic factors for PFS (hazard ratio (HR) =3.4/ P=0.017 and HR =4.3/ P=0.020, respectively). For SUV, no significant effect was found. None of the investigated parameters was prognostic for OS. CONCLUSIONS: Scan-time-corrected SUR is a significantly better surrogate of tumor FDG metabolism in clinical whole-body PET compared to SUV. The very high linear correlation of SUR and DTP-derived K slope (which is proportional to actual K m) implies that for histologically proven malignant lesions, FDG-DTP does not provide added value in comparison to the SUR approach in NSCLC.

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.

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.

The influence of different signal-to-background ratios on spatial resolution and F18-FDG-PET quantification using point spread function and time-of-flight reconstruction.

BACKGROUND: F18-fluorodeoxyglucose positron-emission tomography (FDG-PET) reconstruction algorithms can have substantial influence on quantitative image data used, e.g., for therapy planning or monitoring in oncology. We analyzed radial activity concentration profiles of differently reconstructed FDG-PET images to determine the influence of varying signal-to-background ratios (SBRs) on the respective spatial resolution, activity concentration distribution, and quantification (standardized uptake value [SUV], metabolic tumor volume [MTV]). METHODS: Measurements were performed on a Siemens Biograph mCT 64 using a cylindrical phantom containing four spheres (diameter, 30 to 70 mm) filled with F18-FDG applying three SBRs (SBR1, 16:1; SBR2, 6:1; SBR3, 2:1). Images were reconstructed employing six algorithms (filtered backprojection [FBP], FBP + time-of-flight analysis [FBP + TOF], 3D-ordered subset expectation maximization [3D-OSEM], 3D-OSEM + TOF, point spread function [PSF], PSF + TOF). Spatial resolution was determined by fitting the convolution of the object geometry with a Gaussian point spread function to radial activity concentration profiles. MTV delineation was performed using fixed thresholds and semiautomatic background-adapted thresholding (ROVER, ABX, Radeberg, Germany). RESULTS: The pairwise Wilcoxon test revealed significantly higher spatial resolutions for PSF + TOF (up to 4.0 mm) compared to PSF, FBP, FBP + TOF, 3D-OSEM, and 3D-OSEM + TOF at all SBRs (each P < 0.05) with the highest differences for SBR1 decreasing to the lowest for SBR3. Edge elevations in radial activity profiles (Gibbs artifacts) were highest for PSF and PSF + TOF declining with decreasing SBR (PSF + TOF largest sphere; SBR1, 6.3%; SBR3, 2.7%). These artifacts induce substantial SUVmax overestimation compared to the reference SUV for PSF algorithms at SBR1 and SBR2 leading to substantial MTV underestimation in threshold-based segmentation. In contrast, both PSF algorithms provided the lowest deviation of SUVmean from reference SUV at SBR1 and SBR2. CONCLUSIONS: At high contrast, the PSF algorithms provided the highest spatial resolution and lowest SUVmean deviation from the reference SUV. In contrast, both algorithms showed the highest deviations in SUVmax and threshold-based MTV definition. At low contrast, all investigated reconstruction algorithms performed approximately equally. The use of PSF algorithms for quantitative PET data, e.g., for target volume definition or in serial PET studies, should be performed with caution - especially if comparing SUV of lesions with high and low contrasts.

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.

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.