Jan Petr

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

BackgroundThe 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.MethodsAssuming 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.ResultsFor 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.ConclusionsSUR 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.

A method for model-free partial volume correction in oncological PET

BackgroundAs is well known, limited spatial resolution leads to partial volume effects (PVE) and consequently to limited signal recovery. Determination of the mean activity concentration of a target structure is thus compromised even at target sizes much larger than the reconstructed spatial resolution. This leads to serious size-dependent underestimates of true signal intensity in hot spot imaging. For quantitative PET in general and in the context of therapy assessment in particular it is, therefore, mandatory to perform an adequate partial volume correction (PVC). The goal of our work was to develop and to validate a model-free PVC algorithm for hot spot imaging.MethodsThe algorithm proceeds in two automated steps. Step 1: estimation of the actual object boundary with a threshold based method and determination of the total activity A measured within the enclosed volume V. Step 2: determination of the activity fraction B, which is measured outside the object due to the partial volume effect (spill-out). The PVE corrected mean value is then given by Cmean = (A+B)/V. For validation simulated tumours were used which were derived from real patient data (liver metastases of a colorectal carcinoma and head and neck cancer, respectively). The simulated tumours have characteristics (regarding tumour shape, contrast, noise, etc.) which are very similar to those of the underlying patient data, but the boundaries and tracer accumulation are exactly known. The PVE corrected mean values of 37 simulated tumours were determined and compared with the true mean values.ResultsFor the investigated simulated data the proposed approach yields PVE corrected mean values which agree very well with the true values (mean deviation (± s.d.): (−0.8±2.5)%).ConclusionsThe described method enables accurate quantitative partial volume correction in oncological hot spot imaging.

An automatic method for accurate volume delineation of heterogeneous tumors in PET

PURPOSE Accurate volumetric tumor delineation is of increasing importance in radiation treatment planning. Many tumors exhibit only moderate tracer uptake heterogeneity and delineation methods using an adaptive threshold lead to robust results. These methods use a tumor reference value R (e.g., ROI maximum) and the tumor background Bg to compute the volume reproducing threshold. This threshold corresponds to an isocontour which defines the tumor boundary. However, the boundaries of strongly heterogeneous tumors can not be described by an isocontour anymore and therefore conventional threshold methods are not suitable for accurate delineation. The aim of this work is the development and validation of a delineation method for heterogeneous tumors. METHODS The new method (voxel-specific threshold method, VTM) can be considered as an extension of an adaptive threshold method (lesion-specific threshold method, LTM), where instead of a lesion-specific threshold for the whole ROI, a voxel-specific threshold is computed by determining for each voxel Bg and R in the close vicinity of the voxel. The absolute threshold for the considered voxel is then given by Tabs=T×(R-Bg)+Bg, where T=0.39 was determined with phantom measurements. VALIDATION 30 clinical datasets from patients with non-small-cell lung cancer were used to generate 30 realistic anthropomorphic software phantoms of tumors with different heterogeneities and well-known volumes and boundaries. Volume delineation was performed with VTM and LTM and compared with the known lesion volumes and boundaries. RESULTS In contrast to LTM, VTM was able to reproduce the true tumor boundaries accurately, independent of the heterogeneity. The deviation of the determined volume from the true volume was (0.8±4.2)% for VTM and (11.0±16.4)% for LTM. CONCLUSIONS In anthropomorphic software phantoms, the new method leads to promising results and to a clear improvement of volume delineation in comparison to conventional background-corrected thresholding. In the next step, the suitability for clinical routine will be further investigated.

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

BackgroundStandard 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.MethodsAssuming 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.ResultsFor 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.ConclusionIf 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.

Partial volume correction in arterial spin labeling using a Look‐Locker sequence

Partial volume (PV) effects are caused by limited spatial resolution and significantly affect cerebral blood flow investigations with arterial spin labeling. Therefore, accurate PV correction (PVC) procedures are required. PVC is commonly based on PV maps obtained from segmented high‐resolution T1‐weighted images. Segmentation of these images is error‐prone, and it can be difficult to coregister these images accurately with the single‐shot ASL images such as those created by echo‐planar imaging (EPI). In this paper, an alternative method for PV map generation is proposed.

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.

The spatial coefficient of variation in arterial spin labeling cerebral blood flow images

Macro-vascular artifacts are a common arterial spin labeling (ASL) finding in populations with prolonged arterial transit time (ATT) and result in vascular regions with spuriously increased cerebral blood flow (CBF) and tissue regions with spuriously decreased CBF. This study investigates whether there is an association between the spatial signal distribution of a single post-label delay ASL CBF image and ATT. In 186 elderly with hypertension (46% male, 77.4 ± 2.5 years), we evaluated associations between the spatial coefficient of variation (CoV) of a CBF image and ATT. The spatial CoV and ATT metrics were subsequently evaluated with respect to their associations with age and sex – two demographics known to influence perfusion. Bland–Altman plots showed that spatial CoV predicted ATT with a maximum relative error of 7.6%. Spatial CoV was associated with age (β = 0.163, p = 0.028) and sex (β = −0.204, p = 0.004). The spatial distribution of the ASL signal on a standard CBF image can be used to infer between-participant ATT differences. In the absence of ATT mapping, the spatial CoV may be useful for the clinical interpretation of ASL in patients with cerebrovascular pathology that leads to prolonged transit of the ASL signal to tissue.

Template-based approach for detecting motor task activation-related hyperperfusion in pulsed ASL data.

Arterial spin labeling (ASL) permits the noninvasive measurement of quantitative values of cerebral blood flow (CBF) and is thus well adapted to study inter‐ and intrasubject perfusion variations whether at rest or during an fMRI task. In this study, a template approach to detect brain activation as a CBF difference between resting and activated groups was compared with a standard generalized linear model (GLM) analysis. A basal perfusion template of PICORE‐Q2TIPS ASL images acquired at 3T from a group of 25 healthy subjects (mean age 31.6 ± 8.3 years) was created. The second group of 12 healthy subjects (mean age 28.6 ± 2.7 years) performed a block‐design motor task. The template was compared with the mean activated image of the second group both at the individual and at the group level to extract activation maps. The results obtained using a GLM analysis of the whole sequence was used as ground truth for comparison. The influences of spatial normalization using DARTEL registration and of correction of partial volume effects (PVE) in the construction of the template were assessed. Results showed that a basal perfusion template can detect activation‐related hyperperfusion in motor areas. The true positive ratio was increased by 2.5% using PVE‐correction and by 3.2% using PVE‐correction with DARTEL registration. On average, the group comparison presented a 2.2% higher true positive ratio than the one‐to‐many comparison. Hum Brain Mapp 35:1179–1189, 2014.

Comparison of arterial spin labeling registration strategies in the multi-center GENetic frontotemporal dementia initiative (GENFI)

To compare registration strategies to align arterial spin labeling (ASL) with 3D T1‐weighted (T1w) images, with the goal of reducing the between‐subject variability of cerebral blood flow (CBF) images.

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.