Giuseppe La Tona

Comparison of Visual and Quantitative Analysis for Characterization of Insonated Liver Tumors After Microbubble Contrast Injection

OBJECTIVE The objective of our study was to compare diagnostic performance of visual and quantitative analysis for the characterization of liver tumors insonated at low transmit power after microbubble contrast agent injection. SUBJECTS AND METHODS This series comprised 166 liver tumors (1-5 cm in diameter) in 166 patients (99 men, 67 women; mean age +/- SD, 58 +/- 11 years) scanned at low transmit power (mechanical index: 0.1-0.14) after sulfur hexafluoride-filled microbubble injection. Digital cine clips recorded at the arterial phase (10-40 sec after contrast injection) and late phase (100-300 sec) were analyzed to characterize liver tumors as benign or malignant. Visual analysis was performed by three independent blinded reviewers who evaluated enhancement patterns at the arterial phase and subjective tumor conspicuity at the late phase. Quantitative analysis of videotape intensity (VI: gray-scale levels, 0-255) was performed to calculate objective tumor conspicuity at the late phase: (VI(tumor) - VI(liver)) / VI(liver). RESULTS Characteristic enhancement patterns were observed in malignant tumors (peripheral rimlike) and benign tumors (peripheral nodular or central and spoke-wheel-shaped). Malignant (n = 95) versus benign (n = 71) tumors differed for subjective (median value: -1 vs 1, respectively) and objective conspicuity at the late phase (-0.6 vs 0.15, respectively; p = 0.001, Mann-Whitney U test) due to persistent microbubble uptake in benign tumors. Diagnostic performance of visual (odds ratio: reviewer 1 = 4.28, reviewer 2 = 10.18, reviewer 3 = 9.56) and quantitative (odds ratio: 89.33) analyses differed significantly in the characterization of liver tumors (p = 0.01, chi-square test). CONCLUSION Quantitative analysis revealed higher diagnostic performance than visual analysis to characterize liver tumors insonated at low transmit power after microbubble contrast agent injection.

Automatic Volumetric Liver Segmentation Using Texture Based Region Growing

In this paper an automatic texture based volumetric region growing method for liver segmentation is proposed. 3D seeded region growing is based on texture features with the automatic selection of the seed voxel inside the liver organ and the automatic threshold value computation for the region growing stop condition. Co-occurrence 3D texture features are extracted from CT abdominal volumes and the seeded region growing algorithm is based on statistics in the features space. Each CT volume is composed by 230 slices, having 512 x 512 pixels as spatial resolution, and 12-bit gray level resolution. In this initial feasible study, 5 healthy volunteer acquisitions has been used. Tests have been performed on both basal phase and arterial phase images. Segmentation result shows the effectiveness of the proposed method: liver organ is correctly recognized and segmented, leaving out liver vessels form the segmented area and overcoming the “organ-splitting” problem. The goodness of the proposed method has been confirmed by manual liver segmentation results, having analogous and super-imposable behavior.

Role of virtopsy in the post-mortem diagnosis of drowning

PurposeDue to admitted limits of autopsy-based studies in the diagnosis of drowning, virtopsy is considered the new imaging horizon in these post-mortem studies. The aim of our study was to evaluate the role of virtopsy performed through computed tomography (CT) in the forensic diagnosis of drowning.Materials and methodsWe retrospectively examined the CT data of four cadavers recovered from sea water and suspected to have died by drowning. Each patient underwent a full-body post-mortem CT scan, and then a traditional autopsy.ResultsAll the cadavers showed fluid in the airways and patchy ground-glass opacities in the lung. Only one patient had no fluid in the digestive tract; this patient had a left parietal bone fracture with a large gap and other multiple bone fractures (nose, clavicle, first rib and patella). One of the three patients who had fluid in the digestive tract had no fluid in the paranasal sinuses. This latter patient showed cerebral oedema with subarachnoid and intraventricular haemorrhage, multiple bone fractures (orbital floor, ribs, sacrum and acetabular edge) and air in the heart, in the aorta and in bowel loops.ConclusionTo date, there are no autopsy findings pathognomonic of drowning. This study proves that virtopsy is a useful tool in the diagnosis of drowning in that it allows us to understand if the victim was alive or dead when he entered the water and if the cause of death was drowning.

Imaging evaluation of facial complex strut fractures.

High-resolution multidetector computed tomography with multiplanar reformations and 3-D postprocessing often provides the detail necessary for preoperative assessment of facial injuries. Maxillofacial fractures are classified in the following manner: upper face fractures, midface fractures (the most frequent), Le Fort fractures, and lower face or mandible fractures. The facial skeleton is a framework of vertical and horizontal buttresses that ensures a better resistance to trauma, but serves also as reference for maxillofacial surgery to restore facial size and shape. Radiologists should know how to diagnose and report the main types of facial fracture.

Corrigendum to “Radiological Features of Gastrointestinal Lymphoma”

[This corrects the article DOI: 10.1155/2016/2498143.].

Assessment of cerebral microbleeds by susceptibility-weighted imaging in Alzheimer’s disease patients: A neuroimaging biomarker of the disease

Purpose The objective of this study was to correlate the presence and distribution of cerebral microbleeds in Alzheimer’s disease patients with cerebrospinal fluid biomarkers (amyloid-beta and phosphorylated tau 181 protein levels) and cognitive decline by using susceptibility-weighted imaging magnetic resonance sequences at 1.5 T. Material and methods Fifty-four consecutive Alzheimer’s disease patients underwent brain magnetic resonance imaging at 1.5 T to assess the presence and distribution of cerebral microbleeds on susceptibility-weighted imaging images. The images were analyzed in consensus by two neuroradiologists, each with at least 10 years’ experience. Dementia severity was assessed with the Mini-Mental State Examination score. A multiple regression analysis was performed to assess the associations between the number and location of cerebral microbleed lesions with the age, sex, duration of the disease, cerebrospinal fluid amyloid-beta and phosphorylated tau 181 protein levels, and cognitive functions. Results A total of 296 microbleeds were observed in 54 patients; 38 patients (70.4%) had lobar distribution, 13 patients (24.1%) had non-lobar distribution, and the remaining three patients (5.6%) had mixed distribution, demonstrating that Alzheimer’s disease patients present mainly a lobar distribution of cerebral microbleeds. The age and the duration of the disease were correlated with the number of lobar cerebral microbleeds (P < 0.001). Cerebrospinal fluid amyloid-beta, phosphorylated tau 181 protein levels, and cognitive decline were correlated with the number of lobar cerebral microbleeds in Alzheimer’s disease patients (P < 0.001). Conclusion Lobar distribution of cerebral microbleeds is associated with Alzheimer’s disease and the number of lobar cerebral microbleeds directly correlates with cerebrospinal fluid amyloid-beta and phosphorylated tau 181 protein levels and with the cognitive decline of Alzheimer’s disease patients.

Radiological Features of Gastrointestinal Lymphoma

Gastrointestinal lymphomas represent 5–20% of extranodal lymphomas and mainly occur in the stomach and small intestine. Clinical findings are not specific, thus often determining a delay in the diagnosis. Imaging features at conventional and cross-sectional imaging must be known by the radiologist since he/she plays a pivotal role in the diagnosis and disease assessment, thus assisting in the choice of the optimal treatment to patients. This review focuses on the wide variety of imaging presentation of esophageal, gastric, and small and large bowel lymphoma presenting their main imaging appearances at conventional and cross-sectional imaging, mainly focusing on computed tomography and magnetic resonance, helping in the choice of the best imaging technique for the disease characterization and assessment and the recognition of potential complications.

Fast fingerprints classification only using the directional image

The classification phase is an important step of an automatic fingerprint identification system, where the goal is to restrict only to a subset of the whole database the search time. The proposed system classifies fingerprint images in four classes using only directional image information. This approach, unlike the literature approaches, uses the acquired fingerprint image without enhancement phases application. The system extracts only directional image and uses three concurrent decisional modules to classify the fingerprint. The proposed system has a high classification speed and a very low computational cost. The experimental results show a classification rate of 87.27%.

The Presence of White Matter Lesions Is Associated With the Fibrosis Severity of Nonalcoholic Fatty Liver Disease

AbstractWe tested whether nonalcoholic fatty liver disease (NAFLD) and/or its histological severity are associated with vascular white matter lesions (WML) in patients with biopsy-proven NAFLD and in non-NAFLD controls.Data were recorded in 79 consecutive biopsy-proven NAFLD, and in 82 controls with normal ALT and no history of chronic liver diseases, without ultrasonographic evidence of steatosis and liver stiffness value <6 KPa. All subjects underwent magnetic resonance assessment and WML were classified according to the Fazekas score as absent (0/III), or present (mild I/III; moderate II/III, and severe I/III). For the purpose of analyses, all controls were considered without NASH and without F2–F4 liver fibrosis.WML were found in 26.7% of the entire cohort (43/161), of moderate–severe grade in only 6 cases. The prevalence was similar in NAFLD versus no-NAFLD (29.1% vs 24.3%; P = 0.49), but higher in NASH vs no-NASH (37.7% vs 21.2%, P = 0.02) and F2–F4 vs F0-F1 fibrosis (47.3% vs 20.3%, P = 0.001). In both the entire cohort and in NAFLD, only female gender (OR 4.37, 95% CI: 1.79–10.6, P = 0.001; and OR 5.21, 95% CI: 1.39–19.6, P = 0.01), age > 45 years (OR 3.09, 95% CI: 1.06–9.06, P = 0.03; and OR 11.1, 95% CI: 1.14–108.7, P = 0.03), and F2–F4 fibrosis (OR 3.36, 95% CI: 1.29–8.73, P = 0.01; and OR 5.34, 95% CI: 1.40–20.3, P = 0.01) were independently associated with WML (mostly of mild grade) by multivariate analysis. Among NAFLD, the prevalence of WML progressively increased from patients without (1/18; 5.5%), or with 1 (1/17, 5.8%), to those with 2 (9/30; 30%) and further to those with 3 (12/14; 85.7%) risk factors.The presence of WML is not associated with NAFLD, but with metabolic diseases in general, and fibrosis severity of NAFLD. Clinical implications of this issue need to be assessed by longitudinal studies.

Simulation and Anticipation as Tools for Coordinating with the Future

A key goal in designing an artificial intelligence capable of performing complex tasks is a mechanism that allows it to efficiently choose appropriate and relevant actions in a variety of situations and contexts. Nowhere is this more obvious than in the case of building a general intelligence, where the contextual choice and application of actions must be done in the presence of large numbers of alternatives, both subtly and obviously distinct from each other. We present a framework for action selection based on the concurrent activity of multiple forward and inverse models. A key characteristic of the proposed system is the use of simulation to choose an action: the system continuously simulates the external states of the world (proximal and distal) by internally emulating the activity of its sensors, adopting the same decision process as if it were actually operating in the world, and basing subsequent choice of action on the outcome of such simulations. The work is part of our larger effort to create new observation-based machine learning techniques. We describe our approach, an early implementation, and an evaluation in a classical AI problem-solving domain: the Sokoban puzzle.