Michele Larobina

Metabolic Tumor Volume Assessed by 18F-FDG PET/CT for the Prediction of Outcome in Patients with Multiple Myeloma

18F-FDG PET/CT allows the direct measurement of metabolic tumor burden in a variety of different malignancies. The aim of this study was to assess whether metabolic tumor volume (MTV) determined by 18F-FDG PET/CT could be used in the prediction of progression-free and overall survival in multiple myeloma patients. Methods: Forty-seven patients (18 women, 29 men; mean age ± SD, 63 ± 11 y) with stage IIIA disease who had undergone whole-body 18F-FDG PET/CT were retrospectively evaluated. Images underwent a 3-dimensional region-of-interest analysis including all focal lesions with a maximum standardized uptake value > 2.5. The MTV of each lesion was calculated using an automated contouring program based on the standardized uptake value and developed with a threshold of 40% of the maximum standardized uptake value. The total MTV of each patient was defined as the sum of metabolic volume of all focal lesions. Patients were treated and then subjected to a mean follow-up period of 24 mo. Results: In the 47 patients studied, MTV range was 1.3–316.3 mL, with a median of 23.7 mL. A direct, significant correlation was found between MTV and the percentage of diffuse infiltration of bone marrow by plasma cells (r = 0.46, P = 0.006), whereas hemoglobin levels were inversely correlated with MTV (r = −0.56, P = 0.0001). At follow-up, patients who developed progressive disease (n = 18) showed a significantly higher MTV (74.7 ± 19.3 vs. 29.8 ± 5.1 mL, P = 0.009) than patients without progressive disease (n = 29). Furthermore, patients who died of myeloma (n = 9) had a significantly higher MTV (123.2 ± 30.6 vs. 28.9 ± 4.2 mL, P = 0.0001) than survivors (n = 38). No differences in age, plasma cell infiltration, M protein, albumin, β2-microglobulin, performance status, International Staging System score, and presence or absence of a bone marrow transplant were found between groups. The MTV cutoff level was determined by receiver-operating-characteristic curve analysis, and the best discriminative value found for predicting progression-free and overall survival was 42.2 and 77.6 mL, respectively. By Kaplan–Meier analysis and log-rank testing, progression-free and overall survival at follow-up were significantly better in patients showing an MTV lower than the cutoff than in those having an MTV higher than the cutoff (χ2 = 3.9, P = 0.04, and χ2 = 56.3, P < 0.0001, respectively). Conclusion: The direct measurement of tumor burden obtained by calculating MTV on 18F-FDG PET/CT images may be used in the prediction of progression-free and overall survival in myeloma patients.

Segmentation of magnetic resonance brain images through discriminant analysis

Segmentation (tissue classification) of medical images obtained from a magnetic resonance (MR) system is a primary step in most applications of medical image post-processing. This paper describes nonparametric discriminant analysis methods to segment multispectral MR images of the brain. Starting from routinely available spin-lattice relaxation time, spin-spin relaxation time, and proton density weighted images (T1w, T2w, PDw), the proposed family of statistical methods is based on: (i) a transform of the images into components that are statistically independent from each other; (ii) a nonparametric estimate of probability density functions of each tissue starting from a training set; (iii) a classic Bayes 0-1 classification rule. Experiments based on a computer built brain phantom (brainweb) and on eight real patient data sets are shown. A comparison with parametric discriminant analysis is also reported. The capability of nonparametric discriminant analysis in improving brain tissue classification of parametric methods is demonstrated. Finally, an assessment of the role of multispectrality in classifying brain tissues is discussed.

Stereotaxy-Based Regional Brain Volumetry Applied to Segmented MRI: Validation and Results in Deficit and Nondeficit Schizophrenia

A method for postprocessing of segmented routine brain MRI studies providing automated definition of major structures (frontal, parietal, occipital, and temporal lobes; cerebellar hemispheres; and lateral ventricles) according to the Talairach atlas is presented. The method was applied to MRI studies from 25 normal subjects (NV), 14 patients with deficit schizophrenia (DS), and 14 with nondeficit schizophrenia (NDS), to evaluate their gray matter and CSF regional volumes. The two patient groups did not differ in mean age at illness onset, duration of illness, severity of psychotic symptoms, or disorganization; DS had more severe avolition and worse social functioning than NDS. For validation purposes, brain structures were manually outlined on original MR images in 10 studies, thus obtaining reference measures. Manual and automated measures were repeated 1 month apart to measure reproducibilities of both methods. The automated method required less than 1 min/operator per study vs more than 30 min for manual assessment. Mean absolute difference per structure between the two techniques was 4.8 ml. Overall reproducibility did not significantly differ between the two methods. In subjects with schizophrenia, a significant decrease in GM and increase in CSF were found. GM loss was confined to frontal and temporal lobes. Lateral ventricles were significantly larger bilaterally in NDS compared to NV and only on the right in NDS compared to DS. The finding of greater structural brain abnormalities in NDS adds to the evidence that deficit schizophrenia does not represent just the more severe end of the schizophrenia continuum.

Measurement of global brain atrophy in Alzheimer's disease with unsupervised segmentation of spin-echo MRI studies.

In 16 patients with probable Alzheimers disease (AD; NINDS criteria, age range 56–78 years), gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) absolute and fractional volumes were measured with an unsupervised multiparametric post‐processing segmentation method based on estimates of relaxation rates R1, R2 (R1 = 1/T1; R2 = 1/T2) and proton density [N(H)] from conventional spin‐echo studies (Alfano et al. Magn. Reson. Med. 1997;37:84–93). Global brain atrophy, and GM and WM fractions significantly correlated with Mini‐Mental Status Examination and Blessed Dementia Scale scores. Compared with normals, brain compartments in AD patients showed decreased GM (−6.84 ± 1.58%) and WM fractions (−9.79 ± 2.47%) and increased CSF fractions (+58.80 ± 10.37%). Changes were more evident in early‐onset AD patients. In AD, measurement of global brain atrophy obtained by a computerized procedure based on routine magnetic resonance studies could complement the information provided by neuropsychological tests for the assessment of disease severity. J. Magn. Reson. Imaging 2000;11:260–266.

Medical Image File Formats

Image file format is often a confusing aspect for someone wishing to process medical images. This article presents a demystifying overview of the major file formats currently used in medical imaging: Analyze, Neuroimaging Informatics Technology Initiative (Nifti), Minc, and Digital Imaging and Communications in Medicine (Dicom). Concepts common to all file formats, such as pixel depth, photometric interpretation, metadata, and pixel data, are first presented. Then, the characteristics and strengths of the various formats are discussed. The review concludes with some predictive considerations about the future trends in medical image file formats.

PET/CT Imaging in Mouse Models of Myocardial Ischemia

Different species have been used to reproduce myocardial infarction models but in the last years mice became the animals of choice for the analysis of several diseases, due to their short life cycle and the possibility of genetic manipulation. Many techniques are currently used for cardiovascular imaging in mice, including X-ray computed tomography (CT), high-resolution ultrasound, magnetic resonance imaging, and nuclear medicine procedures. Cardiac positron emission tomography (PET) allows to examine noninvasively, on a molecular level and with high sensitivity, regional changes in myocardial perfusion, metabolism, apoptosis, inflammation, and gene expression or to measure changes in anatomical and functional parameters in heart diseases. Currently hybrid PET/CT scanners for small laboratory animals are available, where CT adds high-resolution anatomical information. This paper reviews mouse models of myocardial infarction and discusses the applications of dedicated PET/CT systems technology, including animal preparation, anesthesia, radiotracers, and images postprocessing.

Descent Algorithms on Oblique Manifold for Source-Adaptive ICA Contrast

A Riemannian manifold optimization strategy is proposed to facilitate the relaxation of the orthonormality constraint in a more natural way in the course of performing independent component analysis (ICA) that employs a mutual information-based source-adaptive contrast function. Despite the extensive development of manifold techniques catering to the orthonormality constraint, only a limited number of works have been dedicated to oblique manifold (OB) algorithms to intrinsically handle the normality constraint, which has been empirically shown to be superior to other Riemannian and Euclidean approaches. Imposing the normality constraint implicitly, in line with the ICA definition, essentially guarantees a substantial improvement in the solution accuracy, by way of increased degrees of freedom while searching for an optimal unmixing ICA matrix, in contrast with the orthonormality constraint. Designs of the steepest descent, conjugate gradient with Hager-Zhang or a hybrid update parameter, quasi-Newton, and cost-effective quasi-Newton methods intended for OB are presented in this paper. Their performance is validated using natural images and systematically compared with the popular state-of-the-art approaches in order to assess the performance effects of the choice of algorithm and the use of a Riemannian rather than Euclidean framework. We surmount the computational challenge associated with the direct estimation of the source densities using the improved fast Gauss transform in the evaluation of the contrast function and its gradient. The proposed OB schemes may find applications in the offline image/signal analysis, wherein, on one hand, the computational overhead can be tolerated, and, on the other, the solution quality holds paramount interest.

Evaluation of supervised methods for the classification of major tissues and subcortical structures in multispectral brain magnetic resonance images

This work investigates the capability of supervised classification methods in detecting both major tissues and subcortical structures using multispectral brain magnetic resonance images. First, by means of a realistic digital brain phantom, we investigated the classification performance of various Discriminant Analysis methods, K-Nearest Neighbor and Support Vector Machine. Then, using phantom and real data, we quantitatively assessed the benefits of integrating anatomical information in the classification, in the form of voxels coordinates as additional features to the intensities or tissue probabilistic atlases as priors. In addition we tested the effect of spatial correlations between neighboring voxels and image denoising. For each brain tissue we measured the classification performance in terms of global agreement percentage, false positive and false negative rates and kappa coefficient. The effectiveness of integrating spatial information or a tissue probabilistic atlas has been demonstrated for the aim of accurately classifying brain magnetic resonance images.

Genetic deletion in uncoupling protein 3 augments 18F-fluorodeoxyglucose cardiac uptake in the ischemic heart

BackgroundWe investigated the effects of uncoupling protein 3 (UCP3) genetic deletion on 18F-fluorodeoxyglucose (FDG) cardiac uptake by positron emission tomography (PET)/computed tomography (CT) dedicated animal system after permanent coronary artery ligation.MethodsCardiac 18F-FDG PET/CT was performed in UCP3 knockout (UCP3-/-) and wild-type (WT) mice one week after induction of myocardial infarction or sham procedure.ResultsIn sham-operated mice no difference in left ventricular (LV) volume was detectable between WT and UCP3-/-. After myocardial infarction, LV volume was higher in both WT and UCP3-/- compared to sham animals, with a significant interaction (p < 0.05) between genotype and myocardial infarction. In sham-operated animals no difference in FDG standardized uptake value (SUV) was detectable between WT (1.8 ± 0.6) and UCP3-/- (1.8 ± 0.6). After myocardial infarction SUV was significantly higher in remote areas than in infarcted territories in both UCP3-/- and WT mice (both p < 0.01). Moreover, in remote areas, SUV was significantly higher (p < 0.001) in UCP3-/- as compared to WT, while in the infarcted territory SUV was comparable (p = 0.29). A significant relationship (r = 0.68, p < 0.001) between LV volume and SUV was found.ConclusionsIn a mice model of permanent coronary occlusion, UCP3 deficiency results in a metabolic shift that favored glycolytic metabolism and increased FDG uptake in remote areas.

Label-free imaging of lipid droplets in cells by stimulated Raman microscopy

Recent technological developments in ultrafast laser physics have permitted to make new kind of nonlinear microscopies, as microscopy based on Stimulated Raman scattering. These techniques are based on vibrational contrast mechanism for imaging with high sensitivity, high spatial and spectral resolution and 3D sectioning capability. The interest in the study of lipids and the possibility to image lipid droplets, thanks to their isolated Raman peaks associated with vibrational C-H bond, have encouraged investigation and identification of lipid structures inside cells, taking advantage of Stimulated Raman Scattering (SRS) imaging. In this work, we report and discuss label free images on biological environmental and structural analysis, to detect lipid microstructures inside adipocyte cells.