Sergio Casciaro

Optimal Enhancement Configuration of Silica Nanoparticles for Ultrasound Imaging and Automatic Detection at Conventional Diagnostic Frequencies

Objectives:To experimentally investigate the acoustical behavior of silica nanoparticles within conventional diagnostic ultrasound fields and to determine a suitable configuration, in terms of particle size and concentration, for their employment as targetable contrast agents. We also assessed the effectiveness of a novel method for automatic detection of targeted silica nanoparticles for future tissue typing applications. Materials and Methods:Silica nanospheres of variable size (160, 330, and 660 nm in diameter) and concentration (1010–1013 part/mL) were dispersed in different custom-designed agarose-based gel samples and imaged at 7.5 MHz with a conventional echograph linked to a research platform for radiofrequency signal acquisition. Off-line analysis included evaluation of backscattered ultrasound amplitude, image brightness, and nanoparticle automatic detection through radiofrequency signal processing. Results:Amplitude of nanoparticle-backscattered signals linearly increased with particle number concentration, but image brightness did not show the same trend, because the logarithmic compression caused the reaching of a “plateau” where brightness remained almost constant for further increments in particle concentration. On the other hand, both backscatter amplitude and image brightness showed significant increments when particle diameter was increased. Taking into account particle size constraints for tumor targeting (pore size of tumor endothelium and trapping effects because of reticulo-endothelial system limit the dimension of effectively employable particles to less than 380 nm), a suitable compromise is represented by the employment of 330-nm silica nanospheres at a concentration of about 1 to 2 × 1011 part/mL. These particles, in fact, showed the best combination of number concentration and diameter value to obtain an effective enhancement on conventional echographic images. Furthermore, also the sensitivity of the developed method for automatic nanoparticle detection had a maximum (72.8%) with 330-nm particles, whereas it was lower with both bigger and smaller particles (being equal to 64.1% and 17.5%, respectively). Conclusions:Silica nanoparticles at a diameter of about 330 nm are very promising contrast agents for ultrasound imaging and specific tumor targeting at conventional diagnostic frequencies, being in particular automatically detectable with high sensitivity already at low doses. Future studies will be carried out to assess the acoustic behavior of nanoparticles with different geometries/sizes and to improve sensitivity of the automatic detection algorithm.

Fully Automatic Liver Segmentation through Graph-Cut Technique

The accurate knowledge of the liver structure including blood vessels topography, liver surface and lesion localizations is usually required in treatments like liver ablations and radiotherapy. In this paper, we propose an approach for automatic segmentation of liver complex geometries. It consists of applying a graph-cut method initialized by an adaptive threshold. The algorithm has been tested on 10 datasets (CT and MR). A parametric comparison with the results obtained by previous algorithms based on active contour is also carried out and discussed. Main limitations of active contour approaches result to be overcome and segmentation is improved. Feasibility to routinely use graph-cut approach for automatic liver segmentation is also demonstrated.

Major osteoporotic fragility fractures: Risk factor updates and societal impact

Osteoporosis is a silent disease without any evidence of disease until a fracture occurs. Approximately 200 million people in the world are affected by osteoporosis and 8.9 million fractures occur each year worldwide. Fractures of the hip are a major public health burden, by means of both social cost and health condition of the elderly because these fractures are one of the main causes of morbidity, impairment, decreased quality of life and mortality in women and men. The aim of this review is to analyze the most important factors related to the enormous impact of osteoporotic fractures on population. Among the most common risk factors, low body mass index; history of fragility fracture, environmental risk, early menopause, smoking, lack of vitamin D, endocrine disorders (for example insulin-dependent diabetes mellitus), use of glucocorticoids, excessive alcohol intake, immobility and others represented the main clinical risk factors associated with augmented risk of fragility fracture. The increasing trend of osteoporosis is accompanied by an underutilization of the available preventive strategies and only a small number of patients at high fracture risk are recognized and successively referred for therapy. This report provides analytic evidences to assess the best practices in osteoporosis management and indications for the adoption of a correct healthcare strategy to significantly reduce the osteoporosis burden. Early diagnosis is the key to resize the impact of osteoporosis on healthcare system. In this context, attention must be focused on the identification of high fracture risk among osteoporotic patients. It is necessary to increase national awareness campaigns across countries in order to reduce the osteoporotic fractures incidence.

Hepatic vessel segmentation for 3D planning of liver surgery experimental evaluation of a new fully automatic algorithm.

RATIONALE AND OBJECTIVES The aim of this study was to identify the optimal parameter configuration of a new algorithm for fully automatic segmentation of hepatic vessels, evaluating its accuracy in view of its use in a computer system for three-dimensional (3D) planning of liver surgery. MATERIALS AND METHODS A phantom reproduction of a human liver with vessels up to the fourth subsegment order, corresponding to a minimum diameter of 0.2 mm, was realized through stereolithography, exploiting a 3D model derived from a real human computed tomographic data set. Algorithm parameter configuration was experimentally optimized, and the maximum achievable segmentation accuracy was quantified for both single two-dimensional slices and 3D reconstruction of the vessel network, through an analytic comparison of the automatic segmentation performed on contrast-enhanced computed tomographic phantom images with actual model features. RESULTS The optimal algorithm configuration resulted in a vessel detection sensitivity of 100% for vessels > 1 mm in diameter, 50% in the range 0.5 to 1 mm, and 14% in the range 0.2 to 0.5 mm. An average area overlap of 94.9% was obtained between automatically and manually segmented vessel sections, with an average difference of 0.06 mm(2). The average values of corresponding false-positive and false-negative ratios were 7.7% and 2.3%, respectively. CONCLUSIONS A robust and accurate algorithm for automatic extraction of the hepatic vessel tree from contrast-enhanced computed tomographic volume images was proposed and experimentally assessed on a liver model, showing unprecedented sensitivity in vessel delineation. This automatic segmentation algorithm is promising for supporting liver surgery planning and for guiding intraoperative resections.

Fully Automatic Segmentations of Liver and Hepatic Tumors From 3-D Computed Tomography Abdominal Images: Comparative Evaluation of Two Automatic Methods

An adaptive initialization method was developed to produce fully automatic processing frameworks based on graph-cut and gradient flow active contour algorithms. This method was applied to abdominal Computed Tomography (CT) images for segmentation of liver tissue and hepatic tumors. Twenty-five anonymized datasets were randomly collected from several radiology centres without specific request on acquisition parameter settings nor patient clinical situation as inclusion criteria. Resulting automatic segmentations of liver tissue and tumors were compared to their reference standard delineations manually performed by a specialist. Segmentation accuracy has been assessed through the following evaluation framework: dice similarity coefficient (DSC), false negative ratio (FNR), false positive ratio (FPR) and processing time. Regarding liver surfaces, graph-cuts achieved a DSC of 95.49% ( FPR=2.35% and FNR=5.10%), while active contours reached a DSC of 96.17% (FPR=3.35% and FNR=3.87%). The analyzed datasets presented 52 tumors: graph-cut algorithm detected 48 tumors with a DSC of 88.65%, while active contour algorithm detected only 44 tumors with a DSC of 87.10%. In addition, in terms of time performances, less time was requested for graph-cut algorithm with respect to active contour one. The implemented initialization method allows fully automatic segmentation leading to superior overall performances of graph-cut algorithm in terms of accuracy and processing time. The initialization method here presented resulted suitable and reliable for two different segmentation techniques and could be further extended.

Use of the Resection Map system as guidance during hepatectomy

BackgroundThe objective of this work is to evaluate a new concept of intraoperative three-dimensional (3D) visualization system to support hepatectomy. The Resection Map aims to provide accurate cartography for surgeons, who can therefore anticipate risks, increase their confidence and achieve safer liver resection.MethodsIn an experimental prospective cohort study, ten consecutive patients admitted for hepatectomy to three European hospitals were selected. Liver structures (portal veins, hepatic veins, tumours and parenchyma) were segmented from a recent computed tomography (CT) study of each patient. The surgeon planned the resection preoperatively and read the Resection Map as reference guidance during the procedure. Objective (amount of bleeding, tumour resection margin and operating time) and subjective parameters were retrieved after each case.ResultsThree different surgeons operated on seven patients with the navigation aid of the Resection Map. Veins displayed in the Resection Map were identified during the surgical procedure in 70.1% of cases, depending mainly on size. Surgeons were able to track resection progress and experienced improved orientation and increased confidence during the procedure.ConclusionsThe Resection Map is a pragmatic solution to enhance the orientation and confidence of the surgeon. Further studies are needed to demonstrate improvement in patient safety.

Entropy Index in Quantitative EEG Measurement for Diagnosis Accuracy

Electroencephalogram (EEG) remains the most immediate, simple, and rich source of information for understanding phenomena related to brain electrical activities. It is certainly a source of basic and interesting information to be extracted using specific and appropriate techniques. The most important aspect in processing EEG signals is to use less co-lateral assets and instrumentation in order to carried out a possible diagnosis; this is the approach of early diagnosis. Advanced estimate spectral analysis can reveal new information encompassed in EEG signals by means of specific parameters or indices. The research proposes a multidimensional approach with a combined use of decimated signal diagonalization (DSD) as basis from which it is possible to work by finding appropriate signal windows for revealing expected information and overcoming signal processing limitations encountered in quantitative EEG. Important information, about the state of the patient under observation, must be extracted from calculated DSD bispectrum. For this aim, it is useful to define an assessment index about the dynamic process associated with the analyzed signal. This information is measured by means of entropy, since the degree of order/disorder of the recorded EEG signal will be reflected in the obtained DSD bispectrum. The general advantage of multidimensional approach is to reveal eventual stealth frequencies “in space and in time” giving a topological vision to be correlated to physical areas which these frequencies emerge from. Long term and sleeping EEG recorded are analyzed, and the results obtained are of interest for an accurate diagnosis of the patients clinical condition.

Harmonic Ultrasound Imaging of Nanosized Contrast Agents for Multimodal Molecular Diagnoses

The aim of the present work was to demonstrate the possibility of selective detection of nanoparticle contrast agents (NPCAs) on diagnostic echographic images by exploiting the second harmonic component they introduce in the spectra of corresponding ultrasound signals, as a consequence of nonlinear distortion during ultrasound propagation. We employed silica nanospheres (SiNSs) of variable diameter (160 nm, 330 nm, and 660 nm) dispersed in different volume concentrations (range 0.07-0.8%) in agarose gel samples that were automatically scanned through a digital ecograph using narrow-band ultrasound pulses at 6.6 MHz and variable mechanical index (MI range 0.2-0.6). In the first part of the study, the intensity peaks of four different spectral components of the backscattered signal were considered: fundamental (detected in correspondence of the incident ultrasound frequency), subharmonic (detected at half of the fundamental frequency), ultra harmonic (detected at 1.5 times the fundamental frequency), and second harmonic (detected at twice the fundamental frequency). Subsequently, based on the experimental results of the first part of the study and on our recently reported findings, the focus was moved to a detailed comparison between subharmonic and second harmonic trend, which were determined as a function of nanoparticle composition, sample concentration, and MI. The experiments were also repeated on different agarose samples, containing SiNSs covered by an outer shell of smaller magnetic nanoparticles, made of either iron oxide (IO) or FePt-IO nanocrystals. Obtained results show that this new ultrasound-based method for NPCA imaging has a detection sensitivity similar to that of our previously introduced subharmonic-based technique in the presence of 330-nm SiNSs, but performs significantly better in the detection of both the types of “dual mode” NPCAs. The fact that the reported detection method was optimized for identification of 330-nm SiNSs (a sort of “ideal” size for the development of novel tumor-targeting NPCAs) and that the magnetically coated particles are detectable also through magnetic resonance imaging makes the presented second harmonic ultrasound method a valuable solution for the introduction of new protocols for multimodal molecular diagnoses employing only nonionizing radiations.

Hydrogel based tissue mimicking phantom for in‐vitro ultrasound contrast agents studies

Ultrasound medical imaging (UMI) is the most widely used image analysis technique, and often requires advanced in-vitro set up to perform morphological and functional investigations. These studies are based on contrast properties both related to tissue structure and injectable contrast agents (CA). In this work, we present a three-dimensional structure composed of two different hydrogels reassembly the microvascular network of a human tissue. This phantom was particularly suitable for the echocontrastographic measurements in human microvascular system. This phantom has been characterized to present the acoustic properties of an animal liver, that is, acoustic impedance (Z) and attenuation coefficient (AC), in UMI signal analysis in particular; the two different hydrogels have been selected to simulate the target organ and the acoustic properties of the vascular system. The two hydrogels were prepared starting from cellulose derivatives to simulating the target organ parenchyma and using a PEG-diacrylate to reproduce the vascular system. Moreover, harmonic analysis was performed on the hydrogel mimicking the liver parenchyma hydrogel to evaluate the ultrasound (US) distortion during echographic measurement. The phantom was employed in the characterization of an experimental US CA. Perfect agreement was found when comparing the hydrogel acoustical properties materials with the corresponding living reference tissues (i.e., vascular and parenchimal tissue).

Experimental Investigations of Nonlinearities and Destruction Mechanisms of an Experimental Phospholipid-Based Ultrasound Contrast Agent

Objectives:We sought to characterize the acoustical behavior of the experimental ultrasound contrast agent BR14 by determining the acoustic pressure threshold above which nonlinear oscillation becomes significant and investigating microbubble destruction mechanisms. Materials and methods:We used a custom-designed in vitro setup to conduct broadband attenuation measurements at 3.5 MHz varying acoustic pressure (range, 50–190 kPa). We also performed granulometric analyses on contrast agent solutions to accurately measure microbubble size distribution and to evaluate insonification effects. Results:Attenuation did not depend on acoustic pressure less than 100 kPa, indicating this pressure as the threshold for the appearance of microbubble nonlinear behavior. At the lowest excitation amplitude, attenuation increased during insonification, while, at higher excitation levels, the attenuation decreased over time, indicating microbubble destruction. The destruction rate changed with pressure amplitude suggesting different destruction mechanisms, as it was confirmed by granulometric analysis. Conclusions:Microbubbles showed a linear behavior until 100 kPa, whereas beyond this value significant nonlinearities occurred. Observed destruction phenomena seem to be mainly due to gas diffusion and bubble fragmentation mechanisms.