Francesca Gallivanone

Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM) Maps generated via a new optimized SPM procedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimers Disease—AD, Frontotemporal Lobar Degeneration—FTLD, Dementia with Lewy bodies—DLB and Mild Cognitive Impairment—MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPM Maps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPM Maps showed the highest predictive prognostic value (mean LOC = 2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions.

PVE Correction in PET-CT Whole-Body Oncological Studies From PVE-Affected Images

Partial Volume Effect (PVE) in PET-CT oncological studies affects the estimation of quantitative parameters useful for lesion malignancy differentiation and for monitoring disease and response to therapy. The aim of this work was to investigate the clinical feasibility and accuracy of PVE correction methods based on Recovery Coefficients (RC) as function of measured Lesion-to-Background ratio (L/B)m and measured lesion volume (Vm). PET-CT measurements were performed. The radioactivity concentration (Cm) and Vm were measured from images using Operator-Dependent and Operator-Independent (OI) techniques. RC curves were obtained combining RC from NEMA 2001 IQ phantom measurements as function of Sphere-to-Background ratio (S/B)m and sphere Vm. PVE correction was applied to PET-CT studies of anthropomorphic oncological phantoms and to PET-CT oncological studies (basal and follow up). The underestimation of Cm due to PVE in the NEMA IQ spheres (up to 80%) confirmed the severity of the error. The more feasible (always applicable, noise insensitive, reproducible) way to measure radioactivity was found by the use of an OI threshold technique. Our results showed that this measurement technique allows to achieve a PVE correction accuracy >; 87% (error in radioactivity estimate <; 13%) for a sphere diameter >; 1 cm. In patient studies the PVE correction was found to modify both SUV and SUV variations during patient follow up and our analysis showed that a PVE corrected SUV quantification increases the diagnostic confidence of oncological PET-CT studies.

Combination of gene expression and genome copy number alteration has a prognostic value for breast cancer

Specific genome copy number alterations, such as deletions and amplifications are an important factor in tumor development and progression, and are also associated with changes in gene expression. By combining analyses of gene expression and genome copy number we identified genes as candidate biomarkers of BC which were validated as prognostic factors of the disease progression. These results suggest that the proposed combined approach may become a valuable method for BC prognosis.

A Graph-Based Method for PET Image Segmentation in Radiotherapy Planning: A Pilot Study

Target volume delineation of Positron Emission Tomography (PET) images in radiation treatment planning is challenging because of the low spatial resolution and high noise level in PET data. The aim of this work is the development of an accurate and fast method for semi-automatic segmentation of metabolic regions on PET images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Validation was first performed on phantoms containing spheres and irregular inserts of different and known volumes, then tumors from a patient with head and neck cancer were segmented to discuss the clinical applicability of this algorithm. Experimental results show that the segmentation algorithm is accurate and fast and meets the physician requirements in a radiotherapy environment.

Statistical Voxel-Based Methods and [18F]FDG PET Brain Imaging: Frontiers for the Diagnosis of AD.

Recommended guidelines for the diagnosis of dementia due to Alzheimers Disease (AD) were revised in recent years, including Positron Emission Tomography (PET) as an in-vivo diagnostic imaging technique for the diagnosis of neurodegeneration. In particular PET, using 18Ffluorodeoxiglucouse ([18F]FDG), is able to detect very early changes of glucose consumption at the synaptic level, enabling to support both early and differential diagnosis of AD. In standard clinical practice, interpretation of [18F] FDG-PET images is usually achieved through qualitative assessment. Visual inspection although only reveals information visible at human eyes resolution, while information at a higher resolution is missed. Furthermore, qualitative assessment depends on the degree of expertise of the clinician, preventing from the definition of accurate and standardized imaging biomarkers. Automated and computerized image processing methods have been proposed to support the in-vivo assessment of brain PET studies. In particular, objective statistical image analyses, enabling the comparison of one patients images to a group of control images have been shown to carry important advantages for detecting significant metabolic changes, including the availability of more objective, cross-center reliable metrics and the detectability of brain subtle functional changes, as occurring in prodromal AD. The purpose of the current review is to provide a systematic overview encompassing the frontiers recently reached by quantitative approaches for the statistical analysis of PET brain images in the study of AD, with a particular focus on Statistical Parametric Mapping. Main achievements, e.g. in terms of standardized biomarkers of AD as well as of sensitivity and specificity, will be discussed.

FDG PET CT as theranostic imaging in diagnosis of non-small cell lung cancer

Objective of this work was to evaluate the role of 18F-fluorodeoxyglucose (FDG) positron-emission tomography features as theranostic imaging biomarkers in non-small cell lung cancer. In a retrospective protocol, 31 stage I-III NSCLC patients were enrolled. Patients underwent FDG PET/CT for staging purposes before surgery and were followed for two years after surgery. PET images were quantitatively analyzed. For the primary lesion, metabolic tumour volume, maximum standardized uptake value (SUV), SUV corrected for partial volume effect, total lesion glycolysis, 14 histogram and four shape-and-size features were extracted as PET imaging features. PET features were correlated with histology and 2-year disease-free survival (DFS). Significant correlations were found between grading, T parameter, N status, pathological stage and different FDG PET features. Histogram-based features energy and kurtosis resulted to be predictive for DFS. The cut-off value identified for kurtosis was able to separate the adenocarcinoma patients with different outcomes. FDG PET features are able to characterize lung cancer lesions, suggesting the possibility of reliable imaging biopsy, and have a predictive role in adenocarcinoma patients undergoing surgery.

Targeted radionuclide therapy frontiers in theranostics

The concept of targeted radionuclide therapy (TRT) relies on the use of injected nuclear medicine as treating agents, targeted at the cellular or molecular level. The growth of the interest in TRT was stimulated by the advances in radionuclide production and labeling as well as by the improvement in the knowledge of appropriate and specific molecular targets. In recent years, different studies on TRT were focused on the evaluation of radionuclide compounds able to combine imaging of the disease with TRT, in a theranostic approach. This approach is of particular interest towards the personalization of treatments, allowing both the baseline characterization of oncological pathologies and treatment optimization by correct dosimetric calculation as well as therapy monitoring. This paper presents a review of recent literature on TRT, with a particular focus on clinical applications promoting such a theranostic approach, showing the impact of the synergy of diagnostic imaging and therapeutics.

PVE correction in PET from PVE affected images

Partial Volume Effect (PVE) in Positron Emission Tomography (PET), as a consequence of the PET limited spatial resolution, causes underestimation of radiotracer uptake in oncological lesions and needs to be corrected. Aim of this work was to develop a method for PVE correction of PET-CT oncological studies, based on curves of Recovery Coefficients (RC) as a function of measured Lesion-to-Background ratio (L/Bm) and measured lesion volume (Vm). MATERIALS AND METHODS. Measurements were performed on the PET-CT scanner Discovery STE (GE Medical Systems). Measured radioactivity concentration (Cm) and Vm were estimated using both Operator-Dependent (OD) and Operator-Independent (OI) measurement techniques. RC curves were obtained by NEMA 2001 IQ phantom measurements. PVE correction was applied to anthropomorphic phantoms miming different body districts and oncological lesions. PVE correction was also applied to 16 oncological patients (both basal and follow up studies). RESULTS The underestimation of Cm (up to 80%) confirmed the severity of the error. Residual errors between GS and PVE corrected Cm showed that the more accurate way to measure radioactivity at a regional level is by the use of an OI threshold technique. The results on the accuracy of the PVE correction method showed that the method achieves an accuracy > 88% for lesion diameter > 1cm. In patient studies PVE correction was found to modify both SUV and SUV variations (δSUV) during patient follow up, and our analysis showed that a PVE corrected SUV quantification increases the diagnostic confidence. CONCLUSION Results proved that the proposed PVE correction method, combined with an OI threshold technique for the measurement of the radioactivity uptake, is feasible and accurate in a clinical setting.

Partial volume correction methods based on measured lesion-to-background ratio in PET-CT oncological studies

This study evaluates Operator-Dependent (OD) and Operator-Independent (OI) methods for Partial Volume effect Correction (PVC) in PET-CT oncological studies. The proposed PVC methods are based on curves of Recovery Coefficients (RC) versus Measured Lesion-to-Background ratios (M-L/B). NEMA IQ phantom PET-CT measurements were performed for RC curves estimation, for M-L/B from 2 to 30. Validation of the PVC methods was performed by 18F-FDG PET-CT studies of a Breast Oncological Phantom, miming from 1cm to 1.56 cm lesions in breasts, for prepared L/B from 14 to 54. An OI PVC method based on a threshold-technique for the estimation of lesion uptake was found the most accurate method (accuracy >80%). PVC methods were applied to the SUV quantification of 11 18F-FDG PET-CT oncological studies. Results prove PV strongly affects lesion quantification and needs to be corrected. When a decrement in the PET lesion volume is observed, PVC-SUV always decreased well fitting the clinical assessment, as from diagnostic report. When an increment in the PET lesion volume is observed, results suggest PVC-SUV should be used together with the PET lesion volume for a better characterization or therapy response of oncological lesions.