Emilia Giovanna Vanoli

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.

FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort

Background/aims In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimers disease (AD) dementia and non-AD dementias. Methods We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as “typical-AD”, “atypical-AD” (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), “non-AD” (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or “negative” patterns. To perform the statistical analyses, the individual patterns were grouped either as “AD dementia vs. non-AD dementia (all diseases)” or as “FTD vs. non-FTD (all diseases)”. Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. Results The multivariate logistic model identified FDG-PET “AD” SPM classification (Expβ = 19.35, 95% C.I. 4.8–77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64–25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The “FTD” SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1–63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55–70.46, p < 0.001). Conclusions Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.

Simultaneous PET-MRI Studies of the Concordance of Atrophy and Hypometabolism in Syndromic Variants of Alzheimer's Disease and Frontotemporal Dementia: An Extended Case Series

BACKGROUND Simultaneous PET-MRI is used to compare patterns of cerebral hypometabolism and atrophy in six different dementia syndromes. OBJECTIVES The primary objective was to conduct an initial exploratory study regarding the concordance of atrophy and hypometabolism in syndromic variants of Alzheimers disease (AD) and frontotemporal dementia (FTD). The secondary objective was to determine the effect of image analysis methods on determination of atrophy and hypometabolism. METHOD PET and MRI data were acquired simultaneously on 24 subjects with six variants of AD and FTD (n = 4 per group). Atrophy was rated visually and also quantified with measures of cortical thickness. Hypometabolism was rated visually and also quantified using atlas- and SPM-based approaches. Concordance was measured using weighted Cohens kappa. RESULTS Atrophy-hypometabolism concordance differed markedly between patient groups; kappa scores ranged from 0.13 (nonfluent/agrammatic variant of primary progressive aphasia, nfvPPA) to 0.49 (posterior cortical variant of AD, PCA). Heterogeneity was also observed within groups; the confidence intervals of kappa scores ranging from 0-0.25 for PCA to 0.29-0.61 for nfvPPA. More widespread MRI and PET changes were identified using quantitative methods than on visual rating. CONCLUSION The marked differences in concordance identified in this initial study may reflect differences in the molecular pathologies underlying AD and FTD syndromic variants but also operational differences in the methods used to diagnose these syndromes. The superior ability of quantitative methodologies to detect changes on PET and MRI, if confirmed on larger cohorts, may favor their usage over qualitative visual inspection in future clinical diagnostic practice.

Quantifying the robustness of [ 18 F]FDG-PET/CT radiomic features with respect to tumor delineation in head and neck and pancreatic cancer patients

PURPOSE To investigate the robustness of PET radiomic features (RF) against tumour delineation uncertainty in two clinically relevant situations. METHODS Twenty-five head-and-neck (HN) and 25 pancreatic cancer patients previously treated with 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based planning optimization were considered. Seven FDG-based contours were delineated for tumour (T) and positive lymph nodes (N, for HN patients only) following manual (2 observers), semi-automatic (based on SUV maximum gradient: PET_Edge) and automatic (40%, 50%, 60%, 70% SUV_max thresholds) methods. Seventy-three RF (14 of first order and 59 of higher order) were extracted using the CGITA software (v.1.4). The impact of delineation on volume agreement and RF was assessed by DICE and Intra-class Correlation Coefficients (ICC). RESULTS A large disagreement between manual and SUV_max method was found for thresholds  ≥50%. Inter-observer variability showed median DICE values between 0.81 (HN-T) and 0.73 (pancreas). Volumes defined by PET_Edge were better consistent with the manual ones compared to SUV40%. Regarding RF, 19%/19%/47% of the features showed ICC < 0.80 between observers for HN-N/HN-T/pancreas, mostly in the Voxel-alignment matrix and in the intensity-size zone matrix families. RFs with ICC < 0.80 against manual delineation (taking the worst value) increased to 44%/36%/61% for PET_Edge and to 69%/53%/75% for SUV40%. CONCLUSIONS About 80%/50% of 72 RF were consistent between observers for HN/pancreas patients. PET_edge was sufficiently robust against manual delineation while SUV40% showed a worse performance. This result suggests the possibility to replace manual with semi-automatic delineation of HN and pancreas tumours in studies including PET radiomic analyses.

Unfavourable gender effect of high body mass index on brain metabolism and connectivity

The influence of Body Mass Index (BMI) on neurodegeneration in dementia has yet to be elucidated. We aimed at exploring the effects of BMI levels on cerebral resting-state metabolism and brain connectivity, as crucial measures of synaptic function and activity, in a large group of patients with Alzheimer’s Dementia (AD) (n = 206), considering gender. We tested the correlation between BMI levels and brain metabolism, as assessed by 18F-FDG-PET, and the modulation of the resting-state functional networks by BMI. At comparable dementia severity, females with high BMI can withstand a lower degree of brain metabolism dysfunction, as shown by a significant BMI-brain metabolism correlation in the temporal-parietal regions, which are typically vulnerable to AD pathology (R = 0.269, p = 0.009). Of note, high BMI was also associated with reduced connectivity in frontal and limbic brain networks, again only in AD females (p < 0.05 FDR-corrected, k = 100 voxels). This suggests a major vulnerability of neural systems known to be selectively involved in brain compensatory mechanisms in AD females. These findings indicate a strong gender effect of high BMI and obesity in AD, namely reducing the available reserve mechanisms in female patients. This brings to considerations for medical practice and health policy.

Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification

The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification. PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT (18F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global 18F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVrCT, SUVrMRI) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations. We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVrCT and SUVrMRI global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm). The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis.

FDG-PET/CT Predicts Outcome in Oropharingeal Carcinoma Patients Undergoing Intensity Modulated Radiation Therapy with Dose Escalation to FDG-avid Tumour Volumes

OBJECTIVE To evaluate the predictive value of FDG-PET/CT parameters on outcome of oropharyngeal squamocellular cancer (OSCC) patients undergoing helical tomotherapy (HTT), with dose escalation to FDG-PET/CT positive tumour volumes using the simultaneous integrated boost (SIB) technique. MATERIALS AND METHODS We analysed 41 patients studied by FDG-PET/CT and treated with radical intent between 2005 and 2014 for OSCC. HTT-SIB was delivered in 30 fractions concomitantly: 69 Gy, as SIB, to the PET-positive volume (biological target volume - BTV-PET), both to the primary tumour (T) and lymph nodes (N), 66 Gy to the T and positive N, 54 Gy to the laterocervical nodes at risk. Selected PET parameters were recovered: maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) obtained with different thresholds (40-50-60% of the SUVmax) for T and N. The correlation between these parameters and the 3-year overall (OS), cancer specific (CSS), disease free (DFS), local relapse free for T and N (LRFS-T and LRFS-N) and distant metastasis free (DMFS) survivals was investigated. RESULTS The median follow-up was 37 months (range: 3-125). The 3-year OS, CSS, DFS, LRFST, LRFS-N and DMFS were 86%, 88%, 76%, 83%, 88% and 91%, respectively. BTVT+ N>30.9cc and BTV-T>22.4cc were correlated with CSS (p=0.02) and OS (p=0.006) respectively; TLG-T-60>34.6cc was correlated with CSS (p=0.04) and OS (p=0.01). MTV-T-60>4.4cc could predict a higher risk of relapse/death (CSS: p=0.033; hazard ratio (HR) =10.92; OS: p=0.01; HR=16.4; LRFS-T: p=0.02; HR=13.90; LRFS-T+N: p=0.03; HR=6.50). CONCLUSION PET parameters predicted survival outcomes and may be considered in the future in the implementation of more personalized treatment schedules in patients affected by OSCC undergoing radiotherapy. FDG-PET/CT dose escalated HTT-SIB allowed very promising 3-year disease control rates in OSCC patients.