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Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with –omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles).

The aim of our study was to establish empirically to what extent reduced glucose uptake in the precuneus, posterior cingulate and/or temporo-parietal cortex (PCTP), which is thought to indicate brain amyloidosis in patients with dementia or MCI due to Alzheimer’s Disease (AD), permits to distinguish amyloid-positive from amyloid-negative patients with non-classical AD phenotypes at the single-case level. We enrolled 127 neurodegenerative patients with cognitive impairment and a positive (n. 63) or negative (n. 64) amyloid marker (cerebrospinal fluid or amy-PET). Three rating methods of FDG-PET scan were applied: purely qualitative visual interpretation of uptake images (VIUI), and visual reading assisted by a semi-automated and semi-quantitative tool: INLAB, provided by the Italian National Research Council, or Cortex ID Suite, marketed by GE Healthcare. Fourteen scans (11.0%) patients remained unclassified by VIUI or INLAB procedures, therefore, validity values were computed on the remaining 113 cases. The three rating approaches showed good total accuracy (77–78%), good to optimal sensitivity (81–93%), but poorer specificity (62–75%). VIUI showed the highest sensitivity and the lowest specificity, and also the highest proportion of unclassified cases. Cases with asymmetric temporo-parietal hypometabolism and a progressive aphasia or corticobasal clinical profile, in particular, tended to be rated as AD-like, even if biomarkers indicated non-amyloid pathology. Our findings provide formal support to the value of PCTP hypometabolism for single-level diagnosis of amyloid pathophysiology in atypical AD, but also highlight the risk of qualitative assessment to misclassify patients with non-AD PPA or CBS underpinned by asymmetric temporo-parietal hypometabolism.

Prostate cancer (PC) is a male common neoplasm and is the second leading cause of cancer death in American men. PC is traditionally diagnosed by the evaluation of prostate secreted antigen (PSA) in the blood. Due to the high levels of false positives, digital rectal examination and transrectal ultrasound guided biopsy are necessary in uncertain cases with elevated PSA levels. Nevertheless, the high mortality rate suggests that new PC biomarkers are urgently needed to help clinical diagnosis. In a previous study, we have identified a network of genes, altered in high Gleason Score (GS) PC (GS ≥ 7), being regulated by miR‐153. Until now, no publication has explained the mechanism of action of miR‐153 in PC. By in vitro studies, we found that the overexpression of miR‐ 153 in high GS cell lines is required to control cell proliferation, migration and invasion rates, targeting Kruppel‐like factor 5 (KLF5). Moreover, miR‐153 could be secreted by exosomes and microvesicles in the microenvironment and, once entered into the surrounding tissue, could influence cellular growth. Being upregulated in high GS human PC, miR‐153 could be proposed as a circulating biomarker for PC diagnosis.

Aim. To evaluate reproducibility and stability of radiomic features as effects of the use of different volume segmentation methods and reconstruction settings. The potential of radiomics in really capturing the presence of heterogeneous tumor uptake and irregular shape was also investigated. Materials and Methods. An anthropomorphic phantom miming real clinical situations including synthetic lesions with irregular shape and nonuniform radiotracer uptake was used. 18F-FDG PET/CT measurements of the phantom were performed including 38 lesions of different shape, size, lesion-to-background ratio, and radiotracer uptake distribution. Different reconstruction parameters and segmentation methods were considered. COVs were calculated to quantify feature variations over the different reconstruction settings. Friedman test was applied to the values of the radiomic features obtained for the considered segmentation approaches. Two sets of test-retest measurement were acquired and the pairwise intraclass correlation coefficient was calculated. Fifty-eight morphological and statistical features were extracted from the segmented lesion volumes. A Mann-Whitney test was used to evaluate significant differences among each feature when calculated from heterogeneous versus homogeneous uptake. The significance of each radiomic feature in terms of capturing heterogeneity was evaluated also by testing correlation with gold standard indexes of heterogeneity and sphericity. Results. The choice of the segmentation method has a strong impact on the stability of radiomic features (less than 20% can be considered stable features). Reconstruction affects the estimate of radiomic features (only 26% are stable). Thirty-one radiomic features (53%) resulted to be reproducible, 11 of them are able to discriminate heterogeneity. Among these, we found a subset of 3 radiomic features strongly correlated with GS heterogeneity index that can be suggested as good features for retrospective evaluations

The aim of this work was to develop a method to manufacture oncological phantoms for quantitation purposes in 18F-FDG PET and DW-MRI studies. Radioactive and diffusion materials were prepared using a mixture of agarose and sucrose radioactive gels. T2 relaxation and diffusion properties of gels at different sucrose concentrations were evaluated. Realistic oncological lesions were created using 3D-printed plastic molds filled with the gel mixture. Once solidified, gels were extracted from molds and immersed in a low-radioactivity gel simulating normal background tissue. A breast cancer phantom was manufactured using the proposed method as an exploratory feasibility study, including several realistic oncological configurations in terms of both radioactivity and diffusion. The phantom was acquired in PET with 18F-FDG, immediately after solidification, and in DW-MRI the following day. Functional volumes characterizing the simulated BC lesions were segmented from PET and DW-MRI images. Measured radioactive uptake and ADC values were compared with gold standards. Phantom preparation was straightforward, and the time schedule was compatible with both PET and MRI measurements. Lesions appeared on 18F-FDG PET and DW-MRI images as expected, without visible artifacts. Lesion functional parameters revealed the phantom’s potential for validating quantification methods, in particular for new generation hybrid PET-MRI systems.

BACKGROUND: Statistical Parametric Mapping (SPM) has been applied for single-subject evaluation of [18F]FDG uptake in Alzheimer Disease (AD). In a single-subject framework, the patient is compared to a dataset of [18F]FDG PET images from healthy subjects (HS) evaluating brain metabolic abnormalities. No studies exist that assess the effects on SPM analysis of HS [18F]FDG PET datasets acquired from different subjects and using different PET scanners including the same or different PET scanners than those used for patients. This work aims to elucidate this issue from a methodological perspective. METHODS: We considered six different [18F]FDG PET datasets, from different HS populations, acquired by different PET scanners. We applied SPM5 procedures for single-subject comparison with each of the six HS datasets in 10 probable AD patients showing the typical [18F] FDG pattern. We also implemented the same comparison in 3 probable AD patients and in 7 patients with a clinical diagnosis of Mild Cognitive Impariment (MCI), showing subtle changes on visual inspection of [18F]FDG distribution. RESULTS: Considering the 10 patients with the typical [18F]FDG pattern, the results were comparable for all the SPM maps. In the 3 probable AD patients with subtle changes in [18F]FDG distribution, no significant AD pattern emerged when a small number (<20) of HS was used, whereas a significant AD pattern appeared when a large (>50) HS image set was used. In the 7 considered MCI patients the use of a large (>50) HS image set allowed to assess significant hypometabolic patterns related to a probable neurodegenerative pathology. CONCLUSIONS: The use of large HS datasets of PET scans (>50) is recommended for single-subject SPM analysis. On condition that appropriate preprocessing steps are provided, large HS datasets can include HS images acquired with different PET systems, not including images from the same scanner of that used for patients

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.

Purpose: The aim of this study was to evaluate the role of imaging features derived from [18F]FDG-PET/CT to provide in vivo characterization of breast cancer (BC). Methods: Images from 43 patients with a first diagnosis of BC were reviewed. Images were acquired before any treatment. Histological data were derived from pretreatment biopsy or surgical histological specimen; these included tumor type, grade, ER and PgR receptor status, lymphovascular invasion, Ki67 index, HER2 status, and molecular subtype. Standard parameters (SUVmean, TLG, MTV) and advanced imaging features (histogram-based and shape and size features) were evaluated. Univariate analysis, hierarchical clustering analysis, and exact Fisher’s test were used for statistical analysis of data. Imaging-derived metrics were reduced evaluating the mutual correlation within group of features as well as the mutual correlation between groups of features to form a signature. Results: A significant correlation was found between some advanced imaging features and the histological type. Different molecular subtypes were characterized by different values of two histogram-based features (median and energy). A significant association was observed between the imaging signature and luminal A and luminal B HER2 negative molecular subtype and also when considering luminal A, luminal B HER2-negative and HER2-positive groups. Similar results were found between the signature and all five molecular subtypes and also when considering the histological types of BC. Conclusions: Our results suggest a complementary role of standard PET imaging parameters and advanced imaging features for the in vivo biological characterization of BC lesions

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.

Objective. [18F]Fluorodeoxyglucose (18F-FDG) PET/CT is increasingly used to assess organ involvement and response to treatment in IgG4-related disease (IgG4-RD), but clear correlations between 18F-FDG uptake and disease activity have not been established yet. We aimed to correlate the intensity and distribution of 18F-FDG uptake with validated clinical, serological and immunological parameters of IgG4-RD activity. Methods. Twenty patients with active IgG4-RD underwent a baseline 18F-FDG PET/CT. Ten patients repeated 18F-FDG PET/CT after immunosuppressive treatments. 18F-FDG tissue uptake was measured using the standardized uptake value corrected for the partial volume effect (PVC-SUV) and the total lesion glycolysis (TLG) with (TLGtot+ln) and without (TLGtot-ln) lymph nodes. Disease activity was assessed by means of clinical parameters [IgG4-RD Responder Index (RI)], serological (ESR and CRP) and immunological (serum IgG4 and circulating plasmablasts) biomarkers. The enhanced liver fibrosis score was exploited as a biomarker for fibroblast activation. Results. Thirteen (65%) patients had two or more organs affected by IgG4-RD. All patients had active IgG4-RD as defined by a median IgG4-RD RI value of 9 (range 6-15; normal < 3). Serum IgG4 and plasmablasts were elevated in 85% of patients. Circulating plasmablasts positively correlated with PVCSUV (P = 0.027), inversely correlated with TLGtot-ln (P = 0.023) and did not correlate with TLGtot+ln (P > 0.05). No statistically significant correlation was found between PVC-SUV or TLG and IgG4-RD RI, ESR, CRP, serum IgG4 or enhanced liver fibrosis score (P > 0.05). Clinical response to immunosuppressive therapies was associated with a consensual reduction of circulating plasmablasts, PVC-SUV, TLGtot+ln and TLGtot-ln values (P < 0.05 for all comparisons). Conclusions. 18F-FDG uptake of IgG4-RD lesions reflects immunological perturbations of the B cell compartment rather than fibroblast activation and extracellula

Objective: Human cancers display intra-tumor phenotypic heterogeneity and recent research has focused on developing image processing methods extracting imaging descriptors to characterize this heterogeneity. This work assesses the role of pretreatment 18F-FDG PET and DWI-MR with respect to the prognosis and prediction of neoadjuvant chemotherapy (NAC) outcomes when image features are used to characterize primitive lesions from breast cancer (BC). Materials and methods: A retrospective protocol included 38 adult women with biopsy-proven BC. Patients underwent a pre-therapy 18F-FDG PET/CT whole-body study and a pre-therapy breast multi-parametric MR study. Patients were then referred for NAC treatment and then for surgical resection, with an evaluation of the therapy response. Segmentation methods were developed in order to identify functional volumes both on 18F-FDG PET images and ADC maps. Macroscopic and histogram features were extracted from the defined functional volumes. Results: Our work demonstrates that macroscopic and histogram features from 18F-FDG PET are able to biologically characterize primitive BC, and define the prognosis. In addition, histogram features from ADC maps are able to predict the response to NAC. Conclusion: Our work suggests that pre-treatment 18F-FDG PET and pre-treatment DWI-MR provide useful complementary information for biological characterization and NAC response prediction in BC.

Introduction: Differential diagnosis of parkinsonian disorders can be difficult on clinical grounds, especially in the early stage. Recent advancements in 18-F-fluorodeoxyglucose positron emission tomography (FDG-PET) imaging reveals different patterns of regional glucose metabolism in idiopathic Parkinson’s disease (IPD) and atypical parkinsonian syndromes, such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), which may help differentiating between these conditions. Purpose: To assess the utility of FDG-PET imaging in differential diagnosis of Parkinsonism in clinical practice. Methods: FDG-PET was performed in 72 patients with parkinsonism (age 34–80 years) referred to our center by movement disorder specialists. FDG-PET diagnosis was obtained by visual assessment of individual scans combined with voxel-based statistical parametric mapping analysis. FDG-PET diagnosis assigned at the time of imaging was compared with the final clinical diagnosis made by the movement disorder specialists after ≥2 years follow-up. Results: FDG-PET findings were consistent with IPD in 27, MSA in 18, PSP in 19 and CBS in 2 patients. The final clinical diagnosis was IPD in 29, MSA in 20, PSP in 21 and CBS in 2 patients. Concordance between the FDG-PET and clinical diagnoses was 92% in the overall sample (IPD 93%, MSA 90%, PSP 91% and CBS 100%). The diagnostic accuracy of FDG-PET was 93% for IPD and MSA and 97% for PSP. Conclusion: FDG-PET may help differentiate between IPD, MSA, PSP and CBS among patients presenting with parkinsonian symptoms, which is important for patient counselling and making early decisions about treatment

Brain energy metabolism actively regulates synaptic transmission and activity. We have previously shown that acute footshock (FS)-stress induces fast and long-lasting functional and morphological changes at excitatory synapses in prefrontal cortex (PFC). Here, we asked whether FS-stress increased energy metabolism in PFC, and modified related cognitive functions. Using positron emission tomography (PET), we found that FS-stress induced a redistribution of glucose metabolism in the brain, with relative decrease of [18F]FDG uptake in ventro-caudal regions and increase in dorso-rostral ones. Absolute [18F]FDG uptake was inversely correlated with serum corticosterone. Increased specific hexokinase activity was also measured in purified PFC synaptosomes (but not in total extract) of FS-stressed rats, which positively correlated with 2-Deoxy [3H] glucose uptake by synaptosomes. In line with increased synaptic energy demand, using an electron microscopy-based stereological approach, we found that acute stress induced a redistribution of mitochondria at excitatory synapses, together with an increase in their volume. The fast functional and metabolic activation of PFC induced by acute stress, was accompanied by rapid and sustained alterations of working memory performance in delayed response to T-maze test. Taken together, the present data suggest that acute stress increases energy consumption at PFC synaptic terminals and alters working memory.

Recommended guidelines for the diagnosis of dementia due to Alzheimer’s 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 patient’s 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.

18F-Fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET) is a standard functional diagnostic technique to in vivo image cancer. Different quantitative paramters can be extracted from PET images and used as in vivo cancer biomarkers. Between PET biomarkers Metabolic Tumor Volume (MTV) has gained an important role in particular considering the development of patient-personalized radiotherapy treatment for non-homogeneous dose delivery. Different imaging processing methods have been developed to define MTV. The different proposed PET segmentation strategies were validated in ideal condition (e.g. in spherical objects with uniform radioactivity concentration), while the majority of cancer lesions doesn't fulfill these requirements. In this context, this work has a twofold objective: 1) to implement and optimize a fully automatic, threshold-based segmentation method for the estimation of MTV, feasible in clinical practice 2) to develop a strategy to obtain anthropomorphic phantoms, including non-spherical and non-uniform objects, miming realistic oncological patient conditions. The developed PET segmentation algorithm combines an automatic threshold-based algorithm for the definition of MTV and a k-means clustering algorithm for the estimation of the background. The method is based on parameters always available in clinical studies and was calibrated using NEMA IQ Phantom. Validation of the method was performed both in ideal (e.g. in spherical objects with uniform radioactivity concentration) and non-ideal (e.g. in non-spherical objects with a non-uniform radioactivity concentration) conditions. The strategy to obtain a phantom with synthetic realistic lesions (e.g. with irregular shape and a non-homogeneous uptake) consisted into the combined use of standard anthropomorphic phantoms commercially and irregular molds generated using 3D printer technology and filled with a radioactive chromatic alginate. The proposed segmentation algorithm was feasible in a clin

Hybrid PET/MRI represents an innovative diagnostic technology for non-invasive in vivo imaging of cancer. Although the current clinical experience is limited to few clinical centres investing in such an ambitious technology, preliminary results are showing potentials for hybrid PET/MRI to enter in the clinical setting as imaging technology that can profoundly impact on the pool of available in vivo multimodal imaging studies. The higher contrast increases detectability of oncological lesions in specific applications; the reduction of radiation exposure leads benefits for children and young adults and for follow-up studies; the multi-functionality of PET/MRI opens up to several opportunities for assessing cancer disease and for addressing oncological patients to optimal care.

Objective. The aim of this work was to assess robustness and reliability of an adaptive thresholding algorithm for the biological target volume estimation incorporating reconstruction parameters. Method. In a multicenter study, a phantom with spheres of different diameters (6.5-57.4 mm) was filled with 18F-FDG at different target-to-background ratios (TBR: 2.5-70) and scanned for different acquisition periods (2-5 min). Image reconstruction algorithms were used varying number of iterations and postreconstruction transaxial smoothing. Optimal thresholds (TS) for volume estimation were determined as percentage of the maximum intensity in the cross section area of the spheres. Multiple regression techniques were used to identify relevant predictors of TS. Results. The goodness of the model fit was high (R2: 0.74-0.92). TBR was the most significant predictor of TS. For all scanners, except the Gemini scanners, FWHM was an independent predictor of TS. Significant differences were observed between scanners of different models, but not between different scanners of the same model. The shrinkage on cross validation was small and indicative of excellent reliability of model estimation. Conclusions. Incorporation of postreconstruction filtering FWHM in an adaptive thresholding algorithm for the BTV estimation allows obtaining a robust and reliable method to be applied to a variety of different scanners, without scanner-specific individual calibration.

We report the case of Niemann–Pick disease type C with extensive phenotypic heterogeneity in two monozygotic twins. One of the twins presented with a history of obsessive–compulsive disorder and slowly progressive inferior limb clumsiness, dysphagia and dysarthria. Neurological examination revealed a broad-based ataxic gait, limb dysmetria, downward vertical gaze palsy, brisk lower limb reflexes and ankle clonus, while neuropsychological assessment revealed global cognitive deficits in multiple domains. Complete neurological and neuropsychological evaluation in the asymptomatic monozygotic twin brother only revealed mild neurological impairment. In the hypothesis of Niemann–Pick disease type C, Filipin test, measurement of plasma oxysterols levels and genetic analysis were carried out in both twins. Filipin staining showed massive intracellular accumulation of non-esterified cholesterol, plasma oxysterols levels were elevated and genetic analysis revealed a homozygous c.2662 C > T (p.P888S) mutation in the NPC1 gene (18q11.2) in both twins. 18F-FDG-PET imaging with single-subject analysis revealed a reduced frontal and temporal glucose metabolism, which correlated with disease progression. This case supports the phenotypic variability of Mendelian inherited disorders in monozygotic twins, likely due to epigenetic differences and post-zygotic mutagenesis.

We report a case study demonstrating the value of prone positioning in positron emission tomography (PET) of a woman with diagnosed breast cancer (BC) addressed to lumpectomy. Surgeon required 18F-fluorodeoxiglucose (18F-FDG) PET study for staging and assessment of lymphnode involvement/metastasis prior to lumpectomy: a whole-body supine study and a prone acquisition of breast. Supine study revealed one lesion, while prone study revealed two lesions. Prone PET findings changed diagnosis and therapeutic intervention for patient who was subsequently subjected to quadrantectomy.

Purpose: To assess whether changes in diffusionweighted MRI (DW-MRI) and 18F-fluoro-2-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT), correlate with treatment response to neoadjuvant therapy (NT), as expressed by tumor regression grade (TRG), from locally advanced gastric adenocarcinoma (GA). Materials and Methods: Seventeen patients underwent both DW-MRI and 18F-FDG-PET/CT scans before and after the end of NT. Apparent diffusion coefficient (ADC) and mean standardized uptake value (SUV) corrected for partial volume effect (PVC-SUVBW-mean) were evaluated and compared with histopathological TRG. Results: Pre- And post-NT and percentage changes forADC and PVC-SUVBW-mean were assessed. Post-NT ADC and DADC showed a significant inverse correlation with TRG (r=-0.71; P=0.0011 and r=-0.78; P=0.00020, respectively) and significant differences in their mean values were found between responders (TRG 1-2-3) and nonresponders (TRG 4-5) (P=0.0009; P=0.000082, respectively). No correlations with TRG were found for pre-NT ADC and for all PVC-SUVBW-mean values as well as between DADC and D PVC-SUVBW-mean. Conclusion: DW-MRI seems more accurate than 18FFDG-PET/CT and ADC modifications may represent a reproducible tool to assess tumor response for GA

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 (Alzheimer's 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