In silico approach for the definition of radiomirnomic signatures for breast cancer differential diagnosis

Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling. BACKGROUND: Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype. METHODS: We describe a computational approach that correlates phenotype from magnetic resonance imaging (MRI) of breast cancer (BC) lesions with microRNAs (miRNAs), mRNAs, and regulatory networks, developing a radiomiRNomic map. We validated our approach to the relationships between MRI and miRNA expression data derived from BC patients. We obtained 16 radiomic features quantifying the tumor phenotype. We integrated the features with miRNAs regulating a network of pathways specific for a distinct BC subtype. RESULTS: We found six miRNAs correlated with imaging features in Luminal A (miR-1537, -205, -335, -337, -452, and -99a), seven miRNAs (miR-142, -155, -190, -190b, -1910, -3617, and -429) in HER2+, and two miRNAs (miR-135b and -365-2) in Basal subtype. We demonstrate that the combination of correlated miRNAs and imaging features have better classification power of Luminal A versus the different BC subtypes than using miRNAs or imaging alone. CONCLUSION: Our computational approach could be used to identify new radiomiRNomic profiles of multi-omics biomarkers for BC differential diagnosis and prognosis

Impact of Radiometric Variability on Ultra-High Resolution Hyperspectral Imagery Over Aquatic Vegetation: Preliminary Results

Over the last two decades, advancements in airborne imaging spectroscopy have prompted the exploitation of lightweight drones for detailed vegetation assessment at unprecedented resolutions. Yet, surface reflectance anisotropy and view-illumination effects may bias spectra extracted from push-broom scanners and derived spectral indices (SIs), particularly over aquatic vegetation, thus impacting the retrieval of biophysical and biochemical vegetation parameters. In this study, the impact of illumination conditions (overcast versus clear sky) and angular configurations (i.e., solar and viewing angles) on radiometric variability of centimetric resolution drone data was empirically investigated over four different aquatic plant species, representing different growth forms and canopy structures. Nadir-normalized reflectance spectra, broadband SIs, and the spectral angle distance to proximal leaf reflectance were used for characterizing and quantifying radiometric variability at canopy and leaf levels. Our findings demonstrated a decrement in reflectance under diffuse light conditions, especially in highly reflective domains within Green (520-580 nm) and Near-Infrared (700-850 nm) ranges, and a marked angular reflectance anisotropy in high absorption spectral regions (i.e., 450-500 nm and 630-700 nm) for aquatic vegetation. The normalized difference vegetation index (NDVI) showed overall lower sensitivity to incoming light variability and angular configurations compared to other tested SIs, whereas the water adjusted vegetation index (WAVI), suitably designed for aquatic vegetation, was less affected by angular anisotropy in floating plants. Indeed, radiometric variability exhibited a dependence on aquatic plant features, i.e., leaf orientation, canopy structure, and affinity with water (as canopy background)

Prognostic Value of 18 F-Fluorocholine PET Parameters in Metastatic Castrate-Resistant Prostate Cancer Patients Treated with Docetaxel

Background and Aim. The availability of new treatments for metastatic castrate-resistant prostate cancer (mCRPC) patients increases the need for reliable biomarkers to help clinicians to choose the better sequence strategy. The aim of the present retrospective and observational work is to investigate the prognostic value of 18 F-fluorocholine ( 18 F-FCH) positron emission tomography (PET) parameters in mCRPC. Materials and Methods. Between March 2013 and August 2016, 29 patients with mCRPC were included. They all received three-weekly docetaxel after androgen deprivation therapy, and they underwent 18 F-FCH PET/computed tomography (CT) before and after the therapy. Semi-quantitative indices such as maximum standardized uptake value (SUV max ), mean standardized uptake value (SUV mean ) with partial volume effect (PVC-SUV) correction, metabolically active tumour volume (MATV), and total lesion activity (TLA) with partial volume effect (PVC-TLA) correction were measured both in pre-treatment and post-treatment 18 F-FCH PET/CT scans for each lesion. Whole-body indices were calculated as sum of values measured for each lesion (SSUV max , SPVC-SUV, SMATV, and STLA). Progression-free survival (PFS) and overall survival (OS) were considered as clinical endpoints. Univariate and multivariate hazard ratios for whole-body 18 F-FCH PET indices were performed, and p<0.05 was considered as significant. Results. Cox regression analysis showed a statistically significant correlation between PFS, SMATV, and STLA. No correlations between OS and 18 F-FCH PET parameters were defined probably due to the small sample size. Conclusions. Semi-quantitative indices such as SMATV and STLA at baseline have a prognostic role in patients treated with docetaxel for mCRPC, suggesting a potential role of 18 F-FCH PET/CT imaging in clinical decision-making

An Adaptive Thresholding Method for BTV Estimation Incorporating PET Reconstruction Parameters: A Multicenter Study of the Robustness and the Reliability

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

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 (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

Metabolic impact of partial volume correction of [18F]FDG PET-CT oncological studies on the assessment of tumor response to treatment

The aim of this work is to evaluate the metabolic impact of Partial Volume Correction (PVC) on the measurement of the Standard Uptake Value (SUV) from [18F]FDG PET-CT oncological studies for treatment monitoring purpose

Gel dosimetry measurements and Monte Carlo modeling for external radiotherapy photon beams. Comparison with a treatment planning system dose distribution

Gel dosimetry has proved to be useful to determine absorbed dose distributions in radiotherapy, as well as to validate treatment plans. Gel dosimetry allows dose imaging and is particularly helpful for non-uniform dose distribution measurements, as may occur when multiple-field irradiation techniques are employed. In this work, we report gel-dosimetry measurements and Monte Carlo (PENELOPE®) calculations for the dose distribution inside a tissue-equivalent phantom exposed to a typical multiple-field irradiation. Irradiations were performed with a 10 MV photon beam from a Varian® Clinac 18 accelerator. The employed dosimeters consisted of layers of Fricke Xylenol Orange radiochromic gel. The method for absorbed dose imaging was based on analysis of visible light transmittance, usually detected by means of a CCD camera. With the aim of finding a simple method for light transmittance image acquisition, a commercial flatbed-like scanner was employed. The experimental and simulated dose distributions have been compared with those calculated with a commercially available treatment planning system, showing a reasonable agreement.Fil: Valente, Mauro Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentina. Università degli Studi di Milano; Italia. Istituto Nazionale Di Fisica Nucleare; ItaliaFil: Aon, Egle. Centro Médico Deán Funes; ArgentinaFil: Brunetto, M.. Centro Médico Deán Funes; Argentina. Vidt Centro Médico; ArgentinaFil: Castellano, Gustavo Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; ArgentinaFil: Gallivanone, F.. Università degli Studi di Milano; ItaliaFil: Gambarini, G.. Università degli Studi di Milano; Italia. Istituto Nazionale Di Fisica Nucleare; Itali