Set Of PET Images Research Articles

Determining the minimal ultra-low dose CT for reliable attenuation correction of 18F-FDG PET-CT: a phantom study.

To investigate minimal required sub milli-Sievert (mSv) ultra-low dose CT and corresponding tube current and voltage for reliable attenuation correction and semi- quantitation in 18F-FDG PET-CT in an effort for radiation dose reduction. Methods: We performed a PET-CT investigational study using a NEMA torso phantom containing six spheres (diameter: 10, 13, 17, 22, 28, 37 mm) filled with a fixed concentration of 60 kBq/ml and a background of 15 kBq/ml of 18F-FDG. Two sets of PET images, separated by 2 hours, were acquired for 3 minutes in a single bed position using 3-D mode with and without time-of-flight in a GE D-690 scanner. Several sets of CT images were acquired for attenuation correction with different combinations of tube voltage (80, 100, 120 kVp) and effective mAs (tube current-time product divided by pitch), using the maximum beam collimation (64 x 0.625 mm). The lowest CT acquisition technique available on this scanner is 10 mA, 0.4 s and 1.375 for the tube current, tube rotation time and pitch, respectively. The CT radiation dose was estimated based on the computed tomography dose index volume (CTDIvol) measurements performed following the standard methodology and the Imaging Performance Assessment of CT Scanners (ImPACT) calculator. Each of the CT techniques was used for attenuation correction to the same PET acquisition, using ordered-subset expectation maximum (OSEM) algorithm with 24 subsets and 2 iterations. The maximal and average radioactivity (kBq/ml) and standardized uptake values (SUV) of the spheres were measured. The minimal ultra-low dose CT for attenuation correction was determined by reproducible SUV measurements (±10%) compared to our reference CT protocol of 100 kVp and 80 mA for 0.5 s rotation. Results: The minimal ultra-low dose of CT for reproducible quantification in all spheres (<10% relative difference) was determined to be 0.3 mSv for a combination of 100 kVp and 10 mA at 0.5 s rotation, 0.984 helical pitch (0.26 mGy measured CTDIvol) . Based on these results we could confidently determine the CT parameters for reliable attenuation correction of PET images while significantly reducing the associated radiation dose. Conclusion: Our phantom study provided guidance in using ultra-low dose CT for precise attenuation correction and semi-quantification of 18F-FDG PET imaging, which can further reduce CT dose and radiation exposure to patients in clinical PET-CT studies. Clinical application: Based on the data, we can further reduce the radiation dose to sub-mSv using an ultra-low dose CT protocol for reliable attenuation correction in clinical 18F-FDG PET-CT studies.

MO‐AB‐BRA‐10: Cancer Therapy Outcome Prediction Based On Dempster‐Shafer Theory and PET Imaging

Purpose:In cancer therapy, utilizing FDG‐18 PET image‐based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster‐Shafer theory (DST) based approach, evidential low‐dimensional transformation with feature selection (ELT‐FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics.Methods:First, a specific loss function with sparse penalty was developed to learn an adaptive low‐rank distance metric for representing the dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low‐dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1‐norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K‐nearest‐neighbor (EK‐ NN) classifier to predict treatment outcome.Results:Twenty‐five patients with stage II–III non‐small‐cell lung cancer and thirty‐six patients with esophageal squamous cell carcinomas treated with chemo‐radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave‐one‐out cross‐validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT‐FS leads to higher prediction accuracy for the training and testing sets both for lung‐cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal‐cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT‐FS also provides superior class separation in both test data sets.Conclusion:A novel DST‐ based approach has been proposed to predict cancer treatment outcome using PET image features and clinical characteristics. A specific loss function has been designed for robust accommodation of feature set incertitude and imprecision, facilitating adaptive learning of the dissimilarity metric for the EK‐NN classifier.

The reverse Warburg effect and 18F-FDG uptake in non-small cell lung cancer A549 in mice: a pilot study.

The purpose of this study was to observe the effect of fasting and feeding on (18)F-FDG uptake in a mouse model of human non-small cell lung cancer. In in vivo studies, (18)F-FDG small-animal PET scans were acquired in 5 mice bearing non-small cell lung cancer A549 xenografts on each flank with continuous feeding and after overnight fasting to observe the changes in intratumoral distribution of (18)F-FDG and tumor (18)F-FDG standardized uptake value (SUV). In ex vivo studies, intratumoral spatial (18)F-FDG distribution assessed by autoradiography was compared with the tumor microenvironment (including hypoxia by pimonidazole and stroma by hematoxylin and eosin stain). Five overnight-fasted mice and 5 fed mice with A549 tumors were observed. Small-animal PET scans were obtained in fed animals on day 1 and in the same animals after overnight fasting; the lapse was approximately 14 h. Blood glucose concentration after overnight fasting was not different from fed mice (P = 0.42), but body weight loss was significant after overnight fasting (P = 0.001). Intratumoral distribution of (18)F-FDG was highly heterogeneous in all tumors examined, and change in spatial intratumoral distribution of (18)F-FDG between 2 sets of PET images from the same mouse was remarkably different in all mice. Tumor (18)F-FDG mean SUV and maximum SUV were not significantly different between fed and fasted animals (all P > 0.05, n = 10). Only tumor mean SUV weakly correlated with blood glucose concentration (R(2) = 0.17, P = 0.03). In ex vivo studies, in fasted mice, there was spatial colocalization between high levels of (18)F-FDG uptake and pimonidazole-binding hypoxic cancer cells; in contrast, pimonidazole-negative normoxic cancer cells and noncancerous stroma were associated with low (18)F-FDG uptake. However, high (18)F-FDG uptake was frequently observed in noncancerous stroma of tumors but rarely in viable cancer cells of the tumors in fed animals. Host dietary status may play a key role in intratumoral distribution of (18)F-FDG. In the fed animals, (18)F-FDG accumulated predominantly in noncancerous stroma in the tumors, that is, reverse Warburg effect. In contrast, in fasted status, (18)F-FDG uptake was found in hypoxic cancer cells component (Pasteur effect). Our findings may provide a better understanding of competing cancer glucose metabolism hypotheses: the Warburg effect, reverse Warburg effect, and Pasteur effect.

SU-E-J-222: Evaluation of Deformable Registration of PET/CT Images for Cervical Cancer Brachytherapy

Purpose: PET/CT provides important functional information for radiotherapy targeting of cervical cancer. However, repeated PET/CT procedures for external beam and subsequent brachytherapy expose patients to additional radiation and are not cost effective. Our goal is to investigate the possibility of propagating PET-active volumes for brachytherapy procedures through deformable image registration (DIR) of earlier PET/CT and ultimately to minimize the number of PET/CT image sessions required. Methods: Nine cervical cancer patients each received their brachytherapy preplanning PET/CT at the end of EBRT with a Syed template in place. The planning PET/CT was acquired on the day of brachytherapy treatment with the actual applicator (Syed or Tandem and Ring) and rigidly registered. The PET/CT images were then deformably registered creating a third (deformed) image set for target prediction. Regions of interest with standardized uptake values (SUV) greater than 65% of maximum SUV were contoured as target volumes in all three sets of PET images. The predictive value of the registered images was evaluated by comparing the preplanning and deformed PET volumes with the planning PET volume using Dice's coefficient (DC) and center-of-mass (COM) displacement. Results: The average DCs were 0.12±0.14 and 0.19±0.16 for rigid and deformable predicted target volumes, respectively. The averagemore » COM displacements were 1.9±0.9 cm and 1.7±0.7 cm for rigid and deformable registration, respectively. The DCs were improved by deformable registration, however, both were lower than published data for DIR in other modalities and clinical sites. Anatomical changes caused by different brachytherapy applicators could have posed a challenge to the DIR algorithm. The physiological change from interstitial needle placement may also contribute to lower DC. Conclusion: The clinical use of DIR in PET/CT for cervical cancer brachytherapy appears to be limited by applicator choice and requires further investigation.« less

A Comparison of Techniques for (90)Y PET/CT Image-Based Dosimetry Following Radioembolization with Resin Microspheres.

90Y PET/CT following radioembolization has recently been established as a viable diagnostic tool, capable of producing images that are both quantitative and have superior image quality than alternative 90Y imaging modalities. Because radioembolization is assumed to be a permanent implant, it is possible to convert quantitative 90Y PET image sets into data representative of spatial committed absorbed-dose. Multiple authors have performed this transformation using dose-point kernel (DPK) convolution to account for the transport of the high-energy 90Y β-particles. This article explores a technique called the Local Deposition Method (LDM), an alternative to DPK convolution for 90Y image-based dosimetry. The LDM assumes that the kinetic energy from each 90Y β-particle is deposited locally, within the voxel where the decay occurred. Using the combined analysis of phantoms scanned using 90Y PET/CT and ideal mathematical phantoms, an accuracy comparison of DPK convolution and the LDM has been performed. Based on the presented analysis, DPK convolution provides no detectible accuracy benefit over the LDM for 90Y PET-based dosimetry. For PET systems with 90Y resolution poorer than 3.25 mm at full-width and half-max using a small voxel size, the LDM may produce a dosimetric solution that is more accurate than DPK convolution under ideal conditions; however, image noise can obscure some of the perceived benefit. As voxel size increases and resolution decreases, differences between the LDM and DPK convolution are reduced. The LDM method of post-radioembolization dosimetry has the advantage of not requiring additional post-processing. The provided conversion factors can be used to determine committed absorbed-dose using conventional PET image analysis tools. The LDM is a recommended option for routine post-radioembolization 90Y dosimetry based on PET/CT imaging.

A New Approach for Alzheimer&amp;apos;s Disease Diagnosis by using Association Rule over PET Images

disease is usually diagnosed from patient history and clinical information. Finding appropriate technologies and early detection of AD is of fundamental importance for early treatments. A set of PET images is selected for the study. In order to ensure that a given voxels in different images are refer to the same position the images are normalized using Spatial Normalization which are subjected to noise filter using Butter worth Filter. Intensity Normalization is required to perform direct image comparisons in which the intensity is normalized to an Imax value. Based on Activation Estimation the Region of Interest (ROI) is achieved which are subjected to Association Rule Mining by specifying the minimum support and the confidence values. Finally Computer Aided Diagnosis (CAD) method performs the image classification with verified rules based on threshold. The comparison of previous methods is performed the early finding of AD.

Validation of segmentation techniques for positron emission tomography using ex vivo images of oncological surgical specimens

ObjectiveTo design a novel ex vivo acquisition technique to establish a common framework to validate different segmentation techniques for oncological PET images. To evaluate several automatic segmentation algorithms on this set of images. Material and methodsIn 15 patients with cancer, ex vivo PET studies of surgical specimens removed during surgery were performed after injection of 18F-FDG. Images were acquired in two scanners: a clinical PET/CT and a high-resolution PET scanner. Real tumor volume was determined in each patient, and a reference image was generated for segmentation of each tumor. Images were segmented with 12 automatic algorithms and with a standard method for PET (relative threshold at 42%) and results were evaluated by quantitative parameters. ResultsIt has been possible to demonstrate by segmentation of PET images of surgical specimens that on high resolution PET images, 8 out of 12 evaluated segmentation techniques outperformed the standard method, whose value is 42%. However, none of the algorithms outperformed the standard method when applied on images from the clinical PET/CT. Due to the great interest of this set of PET images, all studies have been published on the Internet in order to provide a common framework for validation and comparison of different segmentation techniques. ConclusionsWe have proposed a novel technique to validate segmentation techniques for oncological PET images, acquiring ex vivo PET studies of surgical specimens. We have demonstrated the usefulness of this set of PET images by evaluating several automatic segmentation algorithms.

Monitoring tumour response during chemo-radiotherapy: a parametric method using FDG-PET/CT images in patients with oesophageal cancer

BackgroundThe objective of this study is to investigate the feasibility and the additional interest of a parametric imaging (PI) method to monitor the early tumour metabolic response in a prospective series of oesophageal cancer patients who underwent positron emission tomography with fluoro-2-deoxy-d-glucose (FDG-PET/CT) before and during curative-intent chemo-radiotherapy.MethodsFifty-seven patients with squamous cell carcinoma (SCC) of the oesophagus prospectively underwent FDG-PET/CT before chemo-radiotherapy (CRT) (PET1) and at 21 ± 3 days after the beginning of CRT (PET2). The outcome was assessed at 3 months and 1 year after the completion of CRT (clinical examination, CT scan or FDG-PET/CT, biopsy). For each patient, PET1 and PET2 were registered using CT images. The 2 PET image sets were subtracted, so the voxels with significant changes in FDG uptake were identified. A model-based analysis of this graph was used to identify the tumour voxels in which significant changes occurred between the two scans and yielded indices characterising these changes (green and red clusters). Quantitative parameters were compared with clinical outcome at 3 months and at 1 year.ResultsThe baseline tumour FDG uptake decreased significantly at PET2 (p < 0.0001). The tumour volume significantly decreased between PET1 and PET2 (p < 0.02). The initial functional volume of the lesion (TV1) was significantly lower (p < 0.02) in patients in clinical response (CR) at 3 months and 1 year. The volume of the lesion during the treatment (TV2) was significantly lower in patients identified as in CR at 3 months (p < 0.03), but did not predict the outcome at 1 year. Multivariate analyses of outcome at 3 months showed that the risk of failure/death increased with younger age (p = 0.001), larger metabolic volume on PET1 (p = 0.009) and larger volume with decreased FDG uptake (p = 0.047). As for outcome at 1 year, the risk of failure/death increased with younger age (p = 0.006), nodal involvement (p = 0.08) and larger volumes with increased uptake (p = 0.03).ConclusionA parametric method to assess tumour response on serial FDG-PET performed during chemo-radiotherapy was evaluated. Early metabolic changes, i.e. variations in FDG uptake, provided additional prognostic information in multivariate analyses ClinicalTrials.gov NCT 00934505.Trial registrationCurrent Controlled Trials ISRCTN7824458

AutoSPET: An SPM plugin to automatize neuroimages PET analysis

Neuroimaging analysis supports clinicians in the diagnosis of neurological diseases by extracting information from digital images. Due to the large number of images generated by new devices (e.g. PET ones), there is a lot of effort in defining computer-based tools to analyze and classify (brain) radiological images. Statistical tools, such as SPM (for Statistical Parametric Mapping), are largely used by physicians for image analysis. Nevertheless, large datasets analysis requires repetitive steps, due to the lack of automatic procedures. E.g. SPM requires human intervention during long and complex steps.We here present a tool, called AutoSPET (for Automatic SPM analysis for PET images), which allows to perform SPM analyses on large sets of PET images. It works as a meta-component orchestrating interactions with SPM, Matlab and with SPM plugins via a unified user interface. AutoSPET has been tested with real clinical datasets and it is publicly available as an official SPM plugin on the SPM website.

Deformation effect on SUVmax changes in thoracic tumors using 4-D PET/CT scan.

Respiratory motion blurs the standardized uptake value (SUV) and leads to a further signal reduction and changes in the SUV maxima. 4D PET can provide accurate tumor localization as a function of the respiratory phase in PET/CT imaging. We investigated thoracic tumor motion by respiratory 4D CT and assessed its deformation effect on the SUV changes in 4D PET imaging using clinical patient data. Twelve radiation oncology patients with thoracic cancer, including five lung cancer patients and seven esophageal cancer patients, were recruited to the present study. The 4D CT and PET image sets were acquired and reconstructed for 10 respiratory phases across the whole respiratory cycle. The optical flow method was applied to the 4D CT data to calculate the maximum displacements of the tumor motion in respiration. Our results show that increased tumor motion has a significant degree of association with the SUVmax loss for lung cancer. The results also show that the SUVmax loss has a higher correlation with tumors located at lower lobe of lung or at lower regions of esophagus.

PET-based geometrical calibration of a pinhole SPECT add-on for an animal PET scanner

We developed SPECT imaging capability on an animal PET scanner to provide a cost effective option for animal SPECT imaging. The SPECT add-on sub-system was enabled by mechanically integrating a multiple-pinhole collimator in the PET detector ring. This study introduces a method to calibrate the geometrical parameters of the SPECT add-on using the PET imaging capability of the scanner. The proposed PET imaging-based calibration method consists of two steps: (1) paint the pinhole apertures of the collimator with a positron emitting radioactive solution; and (2) image the collimator inside the scanner in PET mode. The geometrical parameters of the multi-pinhole SPECT add-on can then be derived directly from a set of PET images by simple linear calculation and used in defining the SPECT system. The method was compared to our implementation of a SPECT calibration approach with model-based fitting of SPECT projection data. The procedure for carrying out the PET imaging-based calibration method is simpler and faster than that of our implementation of the SPECT model-based calibration method. Since it does not require model fitting, the uniqueness of the calibration result is warranted. Better quality SPECT images were reconstructed using the PET-derived calibration parameters rather than our implementation of the SPECT model-based calibration parameters. We conclude that the proposed PET imaging-based calibration method provides a highly effective means for enabling SPECT imaging on a PET scanner.

Improved imaging of intrahepatic colorectal metastases with 18F-fluorodeoxyglucose respiratory-gated positron emission tomography

In 18F-fluorodeoxyglucose PET/CT, respiratory motion induces bias in image interpretations (i.e. organ misregistration or lesion omission/underestimation). The present study applied our custom gating method (referred to as 'CT-based gated PET' and that has already been validated by our research group) to PET imaging of the liver and compared its per lesion sensitivity with that of standard clinical (i.e. ungated) PET. A total of 13 patients scheduled for liver surgery were referred to our department for PET/CT imaging. Each patient underwent both ungated and CT-based gated PET imaging protocols. Two independent, blinded observers interpreted the two sets of PET images and reached a consensus when necessary. Image interpretations were combined with histological analysis and/or intraoperative ultrasound examination to compute each method's per lesion sensitivity and true positive fraction. Analyses were also performed by considering lesions according to their size (longest axis over 10 mm or over 15 mm). Forty-eight lesions were confirmed by pathology reports. When considering all the uptakes, the ungated and the CT-based gated PET methods had sensitivities of 54.2 and 64.6% (P=0.025) and true positive fractions of 83.9 and 86.1%, respectively. When considering uptakes greater than 10 mm in size, ungated and CT-based gated PET had sensitivities of 74.3 and 88.6% (P=0.025), respectively. For lesions greater than 15 mm in size, the corresponding sensitivities were 85.2 and 100% (P=0.046). CT-based gated PET yielded a higher lesion-based sensitivity than routine, ungated PET did. Hence, this method improves the detection of intrahepatic colorectal metastases--especially for lesions that are close in size to the detection limit of the PET gantry.

Does the Use of IV Contrast Enhanced CT for Attenuation Correction Affect Clinical Interpretation of Head and Neck PET/CT?

Purpose of Report: Evaluate the effect of IV contrast use with FDG PET/CT on clinical interpretation of PET images for head and neck cancer. Procedures: 20 consecutive patients referred for PET/CT and contrast enhanced CT of the head and neck had two sets of PET images obtained. One set used standard low dose CT for attenuation correction, and the other used IV contrast enhanced diagnostic quality CT for attenuation correction. Two blinded nuclear medicine physicians interpreted the results. Results: No statistically significant difference in clinical interpretation of the PET images was found. It was noted that PET scans attenuation corrected with IV contrast CTs had greater incidence of abnormal appearing lesions (P<0.01). Conclusion: It is reasonable to use contrast enhanced CT for attenuation correction in PET/CT of head and neck cancer. This would allow for a reduction in radiation dose delivered to patient.

SU-FF-T-640: Evaluation of Monte Carlo Treatment Planning for CyberKnife Stereotactic Radiosurgery/radiotherapy Treatments of Head and Body Lesions

Purpose: To evaluate Monte Carlo calculated plans for Cyberknife Stereotactic Radiosurgery/Radiotherapy treatments of head and body lesions. Method and Materials: The Multiplan is the Cyberknife treatment planning system which recently implemented a Monte Carlo(MC) in addition to the original pencil‐beam based Raytrace (RT) algorithm for dose calculations. This study compares DVHs and maximum doses (Dmax) to the lesions and selected critical organs obtained by the two algorithms. Planning is done on CT fused with either MRI or PET image sets as appropriate. A treatment plan is created on the Multiplan 2.1 using the RT with equivalent pathlength inhomogemeity corrections. When an acceptable distribution is obtained, the plan is recalculated using MC with 1% relative mean standard deviation. The number of beams, beam directions, and monitor units are kept the same. The dose distributions are then compared with respect to maximum doses to target and critical organs, as well as target coverage. Results: For lung lesions PTV Dmax calculated by the RT are on average larger then the MCdoses by up to a factor of 1.63 while Dmax to critical structures were up to 4 times greater. For cranial and abdominal targets the differences in maximum doses and tumor coverage were generally less than 2% between the two plans. Larger differences of ∼5% are noted for planning for lesions in the nasopharynx in the vicinity of air cavities. Conclusion: In lungMC can produce large differences in target and critical organs'dose coverage relative to RT. RT tends to underdose target structures and the effect is more pronounced as the collimator size decreases. Smaller differences are observed in plans for sites where beams traverse mostly homogeneous water‐equivalent tissue. Therefore the Monte Carlo algorithm should be consistently used for planning for lesions in lung and near air cavities.

Small nodule detectability evaluation using a generalized scan-statistic model

In this paper is investigated the use of the scan statistic for evaluating the detectability of small nodules in medical images. The scan-statistic method is often used in applications in which random fields must be searched for abnormal local features. Several results of the detection with localization theory are reviewed and a generalization is presented using the noise nodule distribution obtained by scanning arbitrary areas. One benefit of the noise nodule model is that it enables determination of the scan-statistic distribution by using only a few image samples in a way suitable both for simulation and experimental setups. Also, based on the noise nodule model, the case of multiple targets per image is addressed and an image abnormality test using the likelihood ratio and an alternative test using multiple decision thresholds are derived. The results obtained reveal that in the case of low contrast nodules or multiple nodules the usual test strategy based on a single decision threshold underperforms compared with the alternative tests. That is a consequence of the fact that not only the contrast or the size, but also the number of suspicious nodules is a clue indicating the image abnormality. In the case of the likelihood ratio test, the multiple clues are unified in a single decision variable. Other tests that process multiple clues differently do not necessarily produce a unique ROC curve, as shown in examples using a test involving two decision thresholds. We present examples with two-dimensional time-of-flight (TOF) and non-TOF PET image sets analysed using the scan statistic for different search areas, as well as the fixed position observer.