Positron emission tomography-based assessment of metabolic gradient and other prognostic features in sarcoma

Intratumoral heterogeneity biomarkers derived from positron emission tomography (PET) imaging with fluorodeoxyglucose (FDG) are of interest for a number of cancers, including sarcoma. A range of radiomic texture variables, adapted from general methodologies for image analysis, has shown promise in the setting. In the context of sarcoma, our group introduced an alternative model-based approach to the measurement of heterogeneity. In this approach, the heterogeneity of a tumor is characterized by the extent to which the 3-D FDG uptake pattern deviates from a simple elliptically contoured structure. By using a nonparametric analysis of the uptake profile obtained from this spatial model, a variable assessing the metabolic gradient of the tumor is developed. The work explores the prognostic potential of this new variable in the context of FDG-PET imaging of sarcoma. A mature clinical series involving 197 patients, 88 of whom have complete time-to-death information, is used. Texture variables based on the imaging data are also evaluated in this series and a range of appropriate machine learning methodologies are then used to explore the complementary prognostic roles for structure and texture variables. We conclude that both texture-based and model-based variables can be combined to achieve enhanced prognostic assessments of outcome for patients with sarcoma based on FDG-PET imaging information

FDG uptake heterogeneity in FIGO IIb cervical carcinoma does not predict pelvic lymph node involvement

TRANSLATIONAL RELEVANCE: Many types of cancer are located and assessed via positron emission tomography (PET) using the 18F-fluorodeoxyglucose (FDG) radiotracer of glucose uptake. There is rapidly increasing interest in exploiting the intra-tumor heterogeneity observed in these FDG-PET images as an indicator of disease outcome. If this image heterogeneity is of genuine prognostic value, then it either correlates to known prognostic factors, such as tumor stage, or it indicates some as yet unknown tumor quality. Therefore, the first step in demonstrating the clinical usefulness of image heterogeneity is to explore the dependence of image heterogeneity metrics upon established prognostic indicators and other clinically interesting factors. If it is shown that image heterogeneity is merely a surrogate for other important tumor properties or variations in patient populations, then the theoretical value of quantified biological heterogeneity may not yet translate into the clinic given current imaging technology. PURPOSE: We explore the relation between pelvic lymph node status at diagnosis and the visually evident uptake heterogeneity often observed in 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) images of cervical carcinomas. EXPERIMENTAL DESIGN: We retrospectively studied the FDG-PET images of 47 node negative and 38 node positive patients, each having FIGO stage IIb tumors with squamous cell histology. Imaged tumors were segmented using 40% of the maximum tumor uptake as the tumor-defining threshold and then converted into sets of three-dimensional coordinates. We employed the sphericity, extent, Shannon entropy (S) and the accrued deviation from smoothest gradients (ζ) as image heterogeneity metrics. We analyze these metrics within tumor volume strata via: the Kolmogorov-Smirnov test, principal component analysis and contingency tables. RESULTS: We found no statistically significant difference between the positive and negative lymph node groups for any one metric or plausible combinations thereof. Additionally, we observed that S is strongly dependent upon tumor volume and that ζ moderately correlates with mean FDG uptake. CONCLUSIONS: FDG uptake heterogeneity did not indicate patients with differing prognoses. Apparent heterogeneity differences between clinical groups may be an artifact arising from either the dependence of some image metrics upon other factors such as tumor volume or upon the underlying variations in the patient populations compared

A new assessment model for tumor heterogeneity analysis with [18]F-FDG PET images

It has been shown that the intratumor heterogeneity can be characterized with quantitative analysis of the [18]F-FDG PET image data. The existing models employ multiple parameters for feature extraction which makes it difficult to implement in clinical settings for the quantitative characterization. This article reports an easy-to-use and differential SUV based model for quantitative assessment of the intratumor heterogeneity from 3D [18]F-FDG PET image data. An H index is defined to assess tumor heterogeneity by summing voxel-wise distribution of differential SUV from the [18]F-FDG PET image data. The summation is weighted by the distance of SUV difference among neighboring voxels from the center of the tumor and can thus yield increased values for tumors with peripheral sub-regions of high SUV that often serves as an indicator of augmented malignancy. Furthermore, the sign of H index is used to differentiate the rate of change for volume averaged SUV from its center to periphery. The new model with the H index has been compared with a widely-used model of gray level co-occurrence matrix (GLCM) for image texture characterization with phantoms of different configurations and the [18]F-FDG PET image data of 6 lung cancer patients to evaluate its effectiveness and feasibility for clinical uses. The comparison of the H index and GLCM parameters with the phantoms demonstrate that the H index can characterize the SUV heterogeneity in all of 6 2D phantoms while only 1 GLCM parameter can do for 1 and fail to differentiate for other 2D phantoms. For the 8 3D phantoms, the H index can clearly differentiate all of them while the 4 GLCM parameters provide complicated patterns in the characterization. Feasibility study with the PET image data from 6 lung cancer patients show that the H index provides an effective single-parameter metric to characterize tumor heterogeneity in terms of the local SUV variation, and it has higher correlation with tumor volume change after radiotherapy (R2 = 0.83) than the 4 GLCM parameters (R2 = 0.63, 0.73, 0.59 and 0.75 for Energy, Contrast, Local Homogeneity and Entropy respectively). The new model of the H index has the capacity to characterize the intratumor heterogeneity feature from 3D [18]F-FDG PET image data. As a single parameter with an intuitive definition, the H index offers potential for clinical applications

Noninvasive Visualization of the Activated αvβ3 Integrin in Cancer Patients by Positron Emission Tomography and [(18)F]Galacto-RGD

BACKGROUND: The integrin αvβ3 plays an important role in angiogenesis and tumor cell metastasis, and is currently being evaluated as a target for new therapeutic approaches. Several techniques are being studied to enable noninvasive determination of αvβ3 expression. We developed [(18)F]Galacto-RGD, a (18)F-labeled glycosylated αvβ3 antagonist, allowing monitoring of αvβ3 expression with positron emission tomography (PET). METHODS AND FINDINGS: Here we show by quantitative analysis of images resulting from a small-animal PET scanner that uptake of [(18)F]Galacto-RGD in the tumor correlates with αvβ3 expression subsequently determined by Western blot analyses. Moreover, using the A431 human squamous cell carcinoma model we demonstrate that this approach is sensitive enough to visualize αvβ3 expression resulting exclusively from the tumor vasculature. Most important, this study shows, that [(18)F]Galacto-RGD with PET enables noninvasive quantitative assessment of the αvβ3 expression pattern on tumor and endothelial cells in patients with malignant tumors. CONCLUSIONS: Molecular imaging with [(18)F]Galacto-RGD and PET can provide important information for planning and monitoring anti-angiogenic therapies targeting the αvβ3 integrins and can reveal the involvement and role of this integrin in metastatic and angiogenic processes in various diseases

Use of intensity - and spatial-based image descriptors to characterise and quantify neoplastic lesions in positron emission tomography

Intra-tumour biological heterogeneity is a characteristic shared by all cancers and is thought to contribute to treatment failure. Within-lesion spatial heterogeneity can be qualitatively visualised in Positron Emission Tomography (PET) imaging. Quantifying the variability of the biological processes and the complexity of the signal being measured in PET oncology is essential. The aim of this thesis was to develop and validate intensity- and spatial-based metrics to quantitatively account for the complexity of radiotracer uptake and to annotate intra-tumour PET heterogeneity. Texture analysis was employed to characterise the in vivo tumour heterogeneity of cell proliferation in breast tumours using 18F-fluorothymidine (18F-FLT) PET. The repeatability of the feature measurements was assessed in patients who had two PET scans prior to therapy. Associations between features at baseline and clinical response measured after three cycles of chemotherapy were explored. Associations between feature changes at one week after the start of chemotherapy and clinical response were also explored. Furthermore, the influence of analysis parameters and imaging protocols were studied. A subset of textural features produced reliable measurements and were associated with treatment response. A technique based on multifractal analysis was also developed for characterising the space-filling properties of an object of interest in PET imaging. The derived spatial index was further combined with intensity metrics and the technique was shown to correct for partial volume effects. The method was illustrated on mathematical objects, validated on test-retest 18F-FLT PET clinical data and applied to realistic PET simulations. This work contributes to the demonstration that intensity- and spatial-based image analysis methods can supplement existing methods in PET quantification studies. These techniques provide some improvements on existing methods to derive classical quantitative PET indices and permit extraction of additional information to further characterise patient populations in the clinical setting and in relation to therapy.Open Acces

Novel aspects for methodology and utilization of PET/CT imaging in head and neck cancer

Avainsanat: PET, PET/TT, pään ja kaulan alueen syöpä, [18F]EF5, [18F]FDG, hypoksia, molekulaarinen kuvantaminen, sädehoidon suunnittelu Positron emission tomography (PET), combined with computed tomography (CT),plays a key role in the management of head and neck cancer (HNC). In this thesis, novel aspects for PET/CT imaging of HNC regarding low oxygen levels, or hypoxia, and detection of glucose metabolism were evaluated. Hypoxia is a frequently observed hallmark of cancer contributing to radiotherapy resistance and poor prognosis. Enhanced glucose metabolism is characteristic of a malignant tumor, which is exploited in an everyday clinical application of [18F]FDG PET imaging. This study aimed to further investigate the feasibility of a novel hypoxia PET tracer [18F]EF5 and the potential of dynamic [18F]FDG PET/CT imaging in HNC. The first study indicated a favorable human biodistribution and radiation dosimetric profile of the hypoxia tracer [18F]EF5. The second preclinical study showed that the growth rate of human HNC xenografts in nude mice during the exponential growth period correlated with [18F]EF5 uptake in PET/CT images. In the third study, paired [18F]EF5 PET/CT scans performed for untreated HNC patients with a median time interval of seven days presented predominantly highly repeatable results. In the fourth study, advanced mathematical methodology for tracer uptake analysis was evaluated using dynamic [18F]FDG PET/CT in patients who were referred to chemoradiotherapy for oropharyngeal cancer. However, the method showed only a modest performance in the distinction of malignant, inflammatory and healthy tissues. In conclusion, further evaluation of [18F]EF5 PET/CT imaging and dynamic [18F]FDG PET/CT imaging seems important in the development of more effective strategies for the management of HNC