Jens Langner

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.

Suitability of bilateral filtering for edge-preserving noise reduction in PET

BackgroundTo achieve an acceptable signal-to-noise ratio (SNR) in PET images, smoothing filters (SF) are usually employed during or after image reconstruction preventing utilisation of the full intrinsic resolution of the respective scanner. Quite generally Gaussian-shaped moving average filters (MAF) are used for this purpose. A potential alternative to MAF is the group of so-called bilateral filters (BF) which provide a combination of noise reduction and edge preservation thus minimising resolution deterioration of the images. We have investigated the performance of this filter type with respect to improvement of SNR, influence on spatial resolution and for derivation of SUVmax values in target structures of varying size.MethodsData of ten patients with head and neck cancer were evaluated. The patients had been investigated by routine whole body scans (ECAT EXACT HR+, Siemens, Erlangen). Tomographic images were reconstructed (OSEM 6i/16s) using a Gaussian filter (full width half maximum (FWHM): Γ0 = 4 mm). Image data were then post-processed with a Gaussian MAF (FWHM: ΓM = 7 mm) and a Gaussian BF (spatial domain: ΓS = 9 mm, intensity domain: ΓI = 2.5 SUV), respectively. Images were assessed regarding SNR as well as spatial resolution. Thirty-four lesions (volumes of about 1-100 mL) were analysed with respect to their SUVmax values in the original as well as in the MAF and BF filtered images.ResultsWith the chosen filter parameters both filters improved SNR approximately by a factor of two in comparison to the original data. Spatial resolution was significantly better in the BF-filtered images in comparison to MAF (MAF: 9.5 mm, BF: 6.8 mm). In MAF-filtered data, the SUVmax was lower by 24.1 ± 9.9% compared to the original data and showed a strong size dependency. In the BF-filtered data, the SUVmax was lower by 4.6 ± 3.7% and no size effects were observed.ConclusionBilateral filtering allows to increase the SNR of PET image data while preserving spatial resolution and preventing smoothing-induced underestimation of SUVmax values in small lesions. Bilateral filtering seems a promising and superior alternative to standard smoothing filters.

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.

Optimized List-Mode Acquisition and Data Processing Procedures for ACS2 Based PET Systems

PET systems using the acquisition control system version 2 (ACS2), e.g. the ECAT Exact HR PET scanner series, offer a rather restricted list-mode functionality. For instance, typical transfers of acquisition data consume a considerable amount of time. This represents a severe obstacle to the utilization of potential advantages of list-mode acquisition. In our study, we have developed hardware and software solutions which do not only allow for the integration of list-mode into routine procedures, but also improve the overall runtime stability of the system. We show that our methods are able to speed up the transfer of the acquired data to the image reconstruction and processing workstations by a factor of up to 140. We discuss how this improvement allows for the integration of list-mode-based post-processing methods such as an event-driven movement correction into the data processing environment, and how list-mode is able to improve the overall flexibility of PET investigations in general. Furthermore, we show that our methods are also attractive for conventional histogram-mode acquisition, due to the improved stability of the ACS2 system.

Dual time point based quantification of metabolic uptake rates in 18F-FDG PET

BackgroundAssessment of dual time point (DTP) positron emission tomography was carried out with the aim of a quantitative determination of Km, the metabolic uptake rate of [18F]fluorodeoxyglucose as a measure of glucose consumption.MethodsStarting from the Patlak equation, it is shown that Km≈mt/ca0+V̄r/τa, where mt is the secant slope of the tissue response function between the dual time point measurements centered at t = t0. ca0=ca(t0) denotes arterial tracer concentration, V̄r is an estimate of the Patlak intercept, and τa is the time constant of the ca(t) decrease. We compared the theoretical predictions with the observed relation between Ks=mt/ca0 and Km in a group of nine patients with liver metastases of colorectal cancer for which dynamic scans were available, and Km was derived from conventional Patlak analysis. Twenty-two lesion regions of interest (ROIs) were evaluated. ca(t) was determined from a three-dimensional ROI in the aorta. Furthermore, the correlation between Km and late standard uptake value (SUV) as well as retention index was investigated. Additionally, feasibility of the approach was demonstrated in a whole-body investigation.ResultsPatlak analysis yielded a mean Vr of V̄r=0.53±0.08 ml/ml. The patient averaged τa was 99 ± 23 min. Linear regression between Patlak-derived Km and DTP-derived Ks according to Ks = b · Km + a yielded b = 0.98 ± 0.05 and a = -0.0054 ± 0.0013 ml/min/ml (r = 0.98) in full accordance with the theoretical predictions b = 1 and a≈-V̄r/τa. Ks exhibits better correlation with Km than late SUV and retention index, respectively. Ks(c)=Ks+V̄r/τa is proposed as a quantitative estimator of Km which is independent of patient weight, scan time, and scanner calibration.ConclusionQuantification of Km from dual time point measurements compatible with clinical routine is feasible. The proposed approach eliminates the issues of static SUV and conventional DTP imaging regarding influence of chosen scanning times and inter-study variability of the input function. Ks and Ks(c) exhibit improved stability and better correlation with the true Km. These properties might prove especially relevant in the context of radiation treatment planning and therapy response control.

Locally adaptive filtering for edge preserving noise reduction on images with low SNR in PET

As well known, the signal-to-noise ratio (SNR) of PET images can be considerably low. This is especially true for whole-body examinations of heavy patients, for respiratory-gated studies, and dynamic studies with short frames. In these cases moving average filters (MAF) such as a Gaussian filter are applied in order to achieve an acceptable SNR. Image resolution is, however, considerably reduced by these MAFs. This affects detectability and quantification of small structures. Interesting alternatives to MAFs are non-linear, locally adaptive filters (NLF), which enable noise reduction while preserving sharp edges.

Modeling magnetization transfer effects of Q2TIPS bolus saturation in multi-TI pulsed arterial spin labeling.

To estimate the relaxation time changes during Q2TIPS bolus saturation caused by magnetization transfer effects and to propose and evaluate an extended model for perfusion quantification which takes this into account.

Event-by-event attenuation measurement for ACS2-based PET systems

Patient motion during acquisition is known to produce severe image artefacts and to limit the image quality in PET. Moreover, it affects exact quantification of tracer kinetic transport processes. To overcome these limitations, different motion correction methods have already been introduced in the past. They either allow for realigning the images of the individual frames of a dynamic PET study via spatial transformations [1] or for realigning each single coincidence event of a list-mode data stream prior to image reconstruction [2]. In both cases, however, patient motion is only compensated during the emission phase of a PET acquisition. This is the case because PET scanners, with a separate radiation source (e.g. [68Ge]) for the transmission measurement, allow for acquiring the attenuation data in histogram-mode only. For an accurate motion correction, however, the patient motion occurring during the several minutes lasting transmission phase also needs to be corrected. This requires the transmission to be processed in list-mode, too. In our study we analysed the hardware and software possibilities and requirements - here of an ACS2-based PET scanner (ECAT Exact HR+, Siemens/CTI, Knoxville, Tennessee) - to enable the attenuation measurement to be processed in list-mode. Together with some analysis on motion corrected phantom studies, this should demonstrate the advantages of a fully motion corrected study compared to an emission-corrected study only.