Repeatability of SUV measurements in serial PET.

PURPOSE: The standardized uptake value (SUV) is a quantitative measure of FDG tumor uptake frequently used as a tool to monitor therapeutic response. This study aims to (i) assess the reproducibility and uncertainty of SUV max and SUV mean, due to purely statistical, i.e., nonbiological, effects and (ii) to establish the minimum uncertainty below which changes in SUV cannot be expected to be an indicator of physiological changes. METHODS: Three sets of measurements were made using a GE Discovery STE PET/CT Scanner in 3D mode: (1) A uniform 68Ge 20 cm diameter cylindrical phantom was imaged. Thirty serial frames were acquired for durations of 3, 6, 10, 15, and 30 min. (2) Esser flangeless phantom (Data Spectrum, approximately 6.1 L) with fillable thin-walled cylinders inserts (diameters: 8, 12, 16, and 25 mm; height: approximately 3.8 mm) was scanned for five consecutive 3 min runs. The cylinders were filled with 18FDG with a 37 kBq/cc concentration, and with a target-to-background ratio (T/BKG) of 3/1. (3) Eight cancer patients with healthy livers were scanned approximately 1.5 h post injection. Three sequential 3 min scans were performed for one bed position covering the liver, with the patient and bed remaining at the same position for the entire length of the scan. Volumes of interest were drawn on all images using the corresponding CT and then transferred to the PET images. For each study (1-3), the average percent change in SUV mean and SUV max were determined for each run pair. Moreover, the repeatability coefficient was calculated for both the SUV mean and SUV max for each pair of runs. Finally, the overall ROI repeatability coefficient was determined for each pair of runs. RESULTS: For the 68Ge phantom the average percent change in SUV max and SUV mean decrease as a function of increasing acquisition time from 4.7 +/- 3.1 to 1.1 +/- 0.6%, and from 0.14 +/- 0.09 to 0.04 +/- 0.03%, respectively. Similarly, the coefficients of repeatability also decrease between the 3 and 30 min acquisition scans, in the range of 10.9 +/- 3.9% - 2.6 +/- 0.9%, and 0.3 +/- 0.1% - 0.10 +/- 0.04%, for the SUV max and SUV mean, respectively. The overall ROI repeatability decreased from 18.9 +/- 0.2 to 6.0 +/- 0.1% between the 3 and 30 min acquisition scans. For the l8FDG phantom, the average percent change in SUV max and SUV mean decreases with target diameter from 3.6 +/- 2.0 to 1.5 +/- 0.8% and 1.5 +/- 1.3 to 0.26 +/- 0.15%, respectively, for targets from 8-25 mm in diameter and for a region in the background (BKG). The coefficients of repeatability for SUV max and SUV mean also decrease as a function of target diameter from 7.1 +/- 2.5 to 2.4 +/- 0.9 and 4.2 +/- 1.5 to 0.6 +/- 0.2, respectively, for targets from 8 mm to BKG in diameter. Finally, overall ROI repeatability decreased from 12.0 +/- 4.1 to 13.4 +/- 0.5 targets from 8 mm to BKG in diameter. Finally, for the measurements in healthy livers the average percent change in SUVmax and SUV mean were in the range of 0.5 +/- 0.2% - 6.2 +/- 3.9% and 0.4 +/- 0.1 and 1.6 +/- 1%, respectively. The coefficients of repeatability for SUV max and SUV men are in the range of 0.6 +/- 0.7% - 9.5 +/- 12% and 0.6 +/- 0.7% - 2.9 +/- 3.6%, respectively. The overall target repeatability varied between 27.9 +/- 0.5% and 41.1 +/- 1.0%. CONCLUSIONS: The statistical fluctuations of the SUV mean are half as large as those of the SUV max in the absence of biological or physiological effects. In addition, for clinically applicable scan durations (i.e., approximately 3 min) and FDG concentrations, the SUV max and SUV mean have similar amounts of statistical fluctuation for small regions. However, the statistical fluctuations of the SUVmean rapidly decrease with respect tothe SUVmax as the statistical power of the data grows either due to longer scanning times or as the target regions encompass a larger volume.

A novel respiratory tracking system for smart-gated PET acquisition.

PURPOSE: In this study, the authors validated a novel respiratory tracking device, the multidimensional respiratory tracking (MDRT) system, that was designed to assist in correcting for respiratory motion in PET/CT images. The authors also investigated a novel PET acquisition technique, smart gating (SG), that enables to acquire motion-free PET data prospectively, with minimum user interference and with no additional postprocessing of the PET data. METHODS: MDRT uses visual tracking techniques to track simultaneously the two-dimensional (in the vertical plane) motion of multiple fiducial markers using a standard video camera. A threshold window is set at the breathing amplitude of interest using the MDRT GUI. A trigger is generated at a rate of 250 Hz as long as the breathing signal is within the threshold window. The triggers are fed into the PET scanner to initialize one single bin of a gated acquisition every 4 ms. No triggers are delivered as the breathing signal drifts outside the threshold window. Consequently, PET data are acquired only whenever the breathing signal is confined within the amplitude threshold window, thus resulting into a motion-free image set. The accuracy of MDRT in tracking the breathing signal was assessed (1) by comparing the period of an oscillating phantom, as measured by MDRT, to that measured with a photogate timer and (2) by comparing the MDRT output to that of the real-time position management (RPM) in ten patients. The SG PET/CT acquisition was validated in phantoms and in two stereotactic body radiosurgery (SBRS) lung DIBH-PET/CT patients. RESULTS: MDRT was in agreement with the photogate timer in determining the period of motion to less than 2%. The percent errors between MDRT and RPM in the positions of the peaks and troughs of the ten patients' breathing signals were within 10%. In phantoms, SG technique enables to correct for motion-induced artifacts in the PET images and improve the accuracy of PET quantitation. For the SBRS application, in one patient, the patient's CT lesion was not detected in the corresponding clinical PET images, while it exhibited an SUV of 1.8 in the DIBH image set. In the second patient, DIBH-PET images showed an improved PET-to-CT spatial matching and a 52% increase in the lesion SUV. CONCLUSIONS: MDRT has been shown to be accurate in tracking breathing motion and assisted in implementing a smart-gating PET acquisition technique that allowed to acquire prospectively motion-free PET images.

An iterative technique to segment PET lesions using a Monte Carlo based mathematical model.

PURPOSE: The need for an accurate lesion segmentation tool in 18FDG PET is a prerequisite for the estimation of lesion response to therapy, for radionuclide dosimetry, and for the application of 18FDG PET to radiotherapy planning. In this work, the authors have developed an iterative method based on a mathematical fit deduced from Monte Carlo simulations to estimate tumor segmentation thresholds. METHODS: The GATE software, a GEANT4 based Monte Carlo tool, was used to model the GE Advance PET scanner geometry. Spheres ranging between 1 and 6 cm in diameters were simulated in a 10 cm high and 11 cm in diameter cylinder. The spheres were filled with water-equivalent density and simulated in both water and lung equivalent background. The simulations were performed with an infinite, 8/1, and 4/1 target-to-background ratio (T/B). A mathematical fit describing the correlation between the lesion volume and the corresponding optimum threshold value was then deduced through analysis of the reconstructed images. An iterative method, based on this mathematical fit, was developed to determine the optimum threshold value. The effects of the lesion volume and T/B on the threshold value were investigated. This method was evaluated experimentally using the NEMA NU2-2001 IEC phantom, the ACNP cardiac phantom, a randomly deformed aluminum can, and a spheroidal shape phantom implemented artificially in the lung, liver, and brain of patient PET images. Clinically, the algorithm was evaluated in six lesions from five patients. Clinical results were compared to CT volumes. RESULTS: This mathematical fit predicts an existing relationship between the PET lesion size and the percent of maximum activity concentration within the target volume (or threshold). It also showed a dependence of the threshold value on the T/B, which could be eliminated by background subtraction. In the phantom studies, the volumes of the segmented PET targets in the PET images were within 10% of the nominal ones. Clinically, the PET target volumes were also within 10% of those measured from CT images. CONCLUSIONS: This iterative algorithm enabled accurately segment PET lesions, independently of their contrast value.

Phase and amplitude binning for 4D-CT imaging.

We compare the consistency and accuracy of two image binning approaches used in 4D-CT imaging. One approach, phase binning (PB), assigns each breathing cycle 2pi rad, within which the images are grouped. In amplitude binning (AB), the images are assigned bins according to the breathing signal's full amplitude. To quantitate both approaches we used a NEMA NU2-2001 IEC phantom oscillating in the axial direction and at random frequencies and amplitudes, approximately simulating a patient's breathing. 4D-CT images were obtained using a four-slice GE Lightspeed CT scanner operating in cine mode. We define consistency error as a measure of ability to correctly bin over repeated cycles in the same field of view. Average consistency error mue+/-sigmae in PB ranged from 18%+/-20% to 30%+/-35%, while in AB the error ranged from 11%+/-14% to 20%+/-24%. In PB nearly all bins contained sphere slices. AB was more accurate, revealing empty bins where no sphere slices existed. As a proof of principle, we present examples of two non-small cell lung carcinoma patients' 4D-CT lung images binned by both approaches. While AB can lead to gaps in the coronal images, depending on the patient's breathing pattern, PB exhibits no gaps but suffers visible artifacts due to misbinning, yielding images that cover a relatively large amplitude range. AB was more consistent, though often resulted in gaps when no data existed due to patients' breathing pattern. We conclude AB is more accurate than PB. This has important consequences to treatment planning and diagnosis.

Quantitation of respiratory motion during 4D-PET/CT acquisition.

We report on the variability of the respiratory motion during 4D-PET/CT acquisition. The respiratory motion for five lung cancer patients was monitored by tracking external markers placed on the abdomen. CT data were acquired over an entire respiratory cycle at each couch position. The x-ray tube status was recorded by the tracking system, for retrospective sorting of the CT data as a function of respiration phase. Each respiratory cycle was sampled in ten equal bins. 4D-PET data were acquired in gated mode, where each breathing cycle was divided into ten 500 ms bins. For both CT and PET acquisition, patients received audio prompting to regularize breathing. The 4D-CT and 4D-PET data were then correlated according to their respiratory phases. The respiratory periods, and average amplitude within each phase bin, acquired in both modality sessions were then analyzed. The average respiratory motion period during 4D-CT was within 18% from that in the 4D-PET sessions. This would reflect up to 1.8% fluctuation in the duration of each 4D-CT bin. This small uncertainty enabled good correlation between CT and PET data, on a phase-to-phase basis. Comparison of the average-amplitude within the respiration trace, between 4D-CT and 4D- PET, on a bin-by-bin basis show a maximum deviation of approximately 15%. This study has proved the feasibility of performing 4D-PET/CT acquisition. Respiratory motion was in most cases consistent between PET and CT sessions, thereby improving both the attenuation correction of PET images, and co-registration of PET and CT images. On the other hand, in two patients, there was an increased partial irregularity in their breathing motion, which would prevent accurately correlating the corresponding PET and CT images.

Four-dimensional (4D) PET/CT imaging of the thorax.

We have reported in our previous studies on the methodology, and feasibility of 4D-PET (Gated PET) acquisition, to reduce respiratory motion artifact in PET imaging of the thorax. In this study, we expand our investigation to address the problem of respiration motion in PET/CT imaging. The respiratory motion of four lung cancer patients were monitored by tracking external markers placed on the thorax. A 4D-CT acquisition was performed using a "step-and-shoot" technique, in which computed tomography (CT) projection data were acquired over a complete respiratory cycle at each couch position. The period of each CT acquisition segment was time stamped with an "x-ray ON" signal, which was recorded by the tracking system. 4D-CT data were then sorted into 10 groups, according to their corresponding phase of the breathing cycle. 4D-PET data were acquired in the gated mode, where each breathing cycle was divided into ten 0.5 s bins. For both CT and PET acquisitions, patients received audio prompting to regularize breathing. The 4D-CT and 4D-PET data were then correlated according to respiratory phase. The effect of 4D acquisition on improving the co-registration of PET and CT images, reducing motion smearing, and consequently increase the quantitation of the SUV, were investigated. Also, quantitation of the tumor motions in PET, and CT, were studied and compared. 4D-PET with matching phase 4D-CTAC showed an improved accuracy in PET-CT image co-registration of up to 41%, compared to measurements from 4D-PET with clinical-CTAC. Gating PET data in correlation with respiratory motion reduced motion-induced smearing, thereby decreasing the observed tumor volume, by as much as 43%. 4D-PET lesions volumes showed a maximum deviation of 19% between clinical CT and phase- matched 4D-CT attenuation corrected PET images. In CT, 4D acquisition resulted in increasing the tumor volume in two patients by up to 79%, and decreasing it in the other two by up to 35%. Consequently, these corrections have yielded an increase in the measured SUV by up to 16% over the clinical measured SUV, and 36% over SUV's measured in 4D-PET with clinical-CT Attenuation Correction (CTAC) SUV's. Quantitation of the maximum tumor motion amplitude, using 4D-PET and 4D-CT, showed up to 30% discrepancy between the two modalities. We have shown that 4D PET/CT is clinically a feasible method, to correct for respiratory motion artifacts in PET/CT imaging of the thorax. 4D PET/CT acquisition can reduce smearing, improve the accuracy in PET-CT co-registration, and increase the measured SUV. This should result in an improved tumor assessment for patients with lung malignancies.

Effect of respiratory gating on reducing lung motion artifacts in PET imaging of lung cancer.

Positron emission tomography (PET) has shown an increase in both sensitivity and specificity over computed tomography (CT) in lung cancer. However, motion artifacts in the 18F fluorodioxydoglucose (FDG) PET images caused by respiration persists to be an important factor in degrading PET image quality and quantification. Motion artifacts lead to two major effects: First, it affects the accuracy of quantitation, producing a reduction of the measured standard uptake value (SUV). Second, the apparent lesion volume is overestimated. Both impact upon the usage of PET images for radiation treatment planning. The first affects the visibility, or contrast, of the lesion. The second results in an increase in the planning target volume, and consequently a greater radiation dose to the normal tissues. One way to compensate for this effect is by applying a multiple-frame capture technique. The PET data are then acquired in synchronization with the respiratory motion. Reduction in smearing due to gating was investigated in both phantoms and patient studies. Phantom studies showed a dependence of the reduction in smearing on the lesion size, the motion amplitude, and the number of bins used for data acquisition. These studies also showed an improvement in the target-to-background ratio, and a more accurate measurement of the SUV. When applied to one patient, respiratory gating showed a 28% reduction in the total lesion volume, and a 56.5% increase in the SUV. This study was conducted as a proof of principle that a gating technique can effectively reduce motion artifacts in PET image acquisition.