Cardiac amyloidosis detection by early bisphosphonate (99mTc-HMDP) scintigraphy.

OBJECTIVE: To determine one or more indexes able to detect the presence of cardiac amyloidosis (CA) from planar scintigraphy images after injection of 99mTc-HMDP tracer and to identify the earliest acquisition time able to ensure an accurate diagnosis of amyloid transthyretin CA. METHODS AND RESULTS: A total of 38 patients were included: 18 subjects with a final diagnosis of ATTR-CA and 20 controls. Dynamic planar images of the anterior thorax were acquired, starting at intravenous injection of ≈ 700 MBq of 99mTc-HMDP. From time/activity curves (TAC) of regions of interest such as heart, vascular region, right ribcage, and soft tissues, several indices were considered. From the analysis, it resulted that both TACHeart/Bone(t) and RIheart-bone(t), for t > 6 minutes, well distinguish ATTR-CA patients from controls subjects. This is confirmed by the area under curves (AUC) analysis giving AUC values =.9 at t ≅ 6 minutes and AUC ≅ 1 for t > 10 minutes. CONCLUSIONS: The method proposed allows determining the presence of ATTR-CA, in an inexpensive manner both in terms of examination costs and time spent.

Cardiac amyloidosis characterization by kinetic model fitting on [18F]florbetaben PET images.

OBJECTIVE: To evaluate the feasibility of kinetic modeling-based approaches from [18F]-Flobetaben dynamic PET images as a non-invasive diagnostic method for cardiac amyloidosis (CA) and to identify the two AL- and ATTR-subtypes. METHODS AND RESULTS: Twenty-one patients with diagnoses of CA (11 patients with AL-subtype and 10 patients with ATTR-subtype of CA) and 15 Control patients with no-CA conditions underwent PET/CT imaging after [18F]Florbetaben bolus injection. A two-tissue-compartment (2TC) kinetic model was fitted to time-activity curves (TAC) obtained from left ventricle wall and left atrium cavity ROIs to estimate kinetic micro- and macro-parameters. Combinations of kinetic parameters were evaluated with the purpose of distinguishing Control subjects and CA patients, and to correctly label the last ones as AL- or ATTR-subtype. Resulting sensitivity, specificity, and accuracy for Control subjects were: 0.87, 0.9, 0.89; as far as CA patients, the sensitivity, specificity, and accuracy were respectively 0.9, 1, and 0.97 for AL-CA patients and 0.9, 0.92, 0.97 for ATTR-CA patients. CONCLUSION: Pharmacokinetic analysis based on a 2TC model allows cardiac amyloidosis characterization from dynamic [18F]Florbetaben PET images. Estimated model parameters allows to not only distinguish between Control subjects and patients, but also between AL- and ATTR-amyloid patients.

Imaging Techniques as an Aid in the Early Detection of Cardiac Amyloidosis.

The idea that performing a proper succession of imaging tests and techniques allows an accurate and early diagnosis of cardiac amyloidosis, avoiding the need to perform the myocardial biopsy, is becoming increasingly popular. Furthermore, being imaging techniques non-invasive, it is possible to perform the follow-up of the pathology through repeated image acquisitions. In the present review, the various innovative imaging methodologies are presented, and it is discussed how they have been applied for early diagnosis of cardiac amyloidosis (CA), also to distinguish the two most frequent subtypes in CA: immunoglobulin light chain amyloidosis (AL) and transthyretin amyloidosis (ATTR); this allows to perform the therapy in a targeted and rapid manner.

Models and Methods in Cardiac Imaging for Metabolism Studies.

Cardiac health depends on the heart's ability to utilize different substrates to support overall oxidative metabolism. To characterize a variety of cardiac diseases, there is an ever-growing demand for an accurate non-invasive approach to evaluating myocardial substrate metabolism. Data obtained from quantitative metabolic imaging modalities add functional information to the anatomic imaging modalities and can aid patient management. The goal of this review is to emphasize the role of non-invasive imaging techniques (such as PET, SPECT, MR spectroscopy and spectroscopic imaging) to detect the metabolic footprints of heart disease. The advancements of models and methods to estimate kinetic parameters of dynamic processes using data acquired from cardiac imaging modalities is discussed.

Noise correlations and SNR in phased-array MRS.

The acquisition of magnetic resonance spectroscopy (MRS) signals by multiple receiver coils can improve the signal-to-noise ratio (SNR) or alternatively can reduce the scan time maintaining a reliable SNR. However, using phased array coils in MRS studies requires efficient data processing and data combination techniques in order to exploit the sensitivity improvement of the phased array coil acquisition method. This paper describes a novel method for the combination of MRS signals acquired by phased array coils, even in presence of correlated noise between the acquisition channels. In fact, although it has been shown that electric and magnetic coupling mechanisms produce correlated noise in the coils, previous algorithms developed for MRS data combination have ignored this effect. The proposed approach takes advantage of a noise decorrelation stage to maximize the SNR of the combined spectra. In particular Principal Component Analysis (PCA) was exploited to project the acquired spectra in a subspace where the noise vectors are orthogonal. In this subspace the SNR weighting method will provide the optimal overall SNR. Performance evaluation of the proposed method is carried out on simulated (1)H-MRS signals and experimental results are obtained on phantom (1)H-MR spectra using a commercially available 8-element phased array coil. Noise correlations between elements were generally low due to the optimal coil design, leading to a fair SNR gain (about 0.5%) in the center of the field of view (FOV). A greater SNR improvement was found in the peripheral FOV regions.

The biological effects of diagnostic cardiac imaging.

In this paper the authors deal with the main imaging techniques available to clinical cardiologists, with a brief overview of biophysical and biological aspects which are of relevance for the assessment of health effects related to the exposure of patients to both ionizing and non ionizing radiation. A main contribute is the reviewing published evidence on biological effects of radiation, trying to compose a balanced issue in order to increase awareness and knowledge about radiation exposure from cardiac imaging and implications for health risk.

Evaluation of a web-based network for reproducible T2* MRI assessment of iron overload in thalassemia.

PURPOSE: To build and evaluate a national network able to improve the care of thalassemia, a genetic disorder in haemoglobin synthesis often associated with iron accumulation in a variety of organs, due to the continuous blood transfusions. METHODS: The MIOT (Myocardial Iron Overload in Thalassemia) network is constituted by thalassemia and magnetic resonance imaging (MRI) centers. Thalassemia centers are responsible for patient recruitment and collection of anamnestic and clinical data. MRI centers have been equipped with a standardized acquisition technique and an affordable workstation for image analysis. They are able to perform feasible and reproducible heart and liver iron overload assessments for a consistent number of thalassemia patients in a robust manner. All centers are linked by a web-based network, configured to collect and share patient data. RESULTS: On 30th March 2008, 695 thalassemia patients were involved in the network. The completion percentage of the patient records in the database was 85+/-6.5%. Six hundred and thirteen patients (88%) successfully underwent MRI examination. Each MRI center had a specific absorption capacity that remained constant over time, but the network was capable of sustaining an increasing number of patients due to continuous enrollment of new centers. The patient's comfort, assessed as the mean distance from the patient home locations to the MRI centers, significantly increased during the network's evolution. CONCLUSION: The MIOT network seems to be a robust and scalable system in which T2* MRI-based cardiac and liver iron overload assessment is available, accessible and reachable for a significant and increasing number of thalassemia patients in Italy (about 420 per year), reducing the mean distance from the patient locations to the MRI sites from 951km to 387km. A solid, wide and homogeneous database will constitute an important scientific resource, shortening the time scale for diagnostic, prognostic and therapeutical evidence-based research on the management of thalassemia disease.

Fundamentals in cardiovascular imaging technologies.

The aim of this paper is to introduce the prominent in vivo cardiovascular imaging modalities such as magnetic resonance imaging, nuclear imaging and ultrasound from both the physical and molecular imaging perspectives. A brief introduction to the molecular imaging principles is also reported. Special emphasis will be given to the imaging parameters of sensitivity and spatial resolution, and the trade-off between spatial resolution, image contrast and target size.

Independent component analysis applied to the removal of motion artifacts from electrocardiographic signals.

Electrocardiographic (ECG) signals are affected by several kinds of artifacts that may hide vital signs of interest. In this study we apply independent component analysis (ICA) to isolate motion artifacts. Standard or instantaneous ICA, which is currently the most addressed ICA model within the context of artifact removal, is compared to two other ICA techniques. The first technique is a frequency domain approach to convolutive mixture separation. The second is based on temporally constrained ICA, which enables the estimation of only one component close to a particular reference signal. Performance indexes evaluate ECG complex enhancement and relevant heart rate errors. Our results show that both convolutive and constrained ICA implementations perform better than standard ICA, thus opening up a new field of application for these two methods. Moreover, statistical analysis reveals that constrained ICA and convolutive ICA do not significantly differ concerning heart rate estimation, even though the latter overcomes the former in ECG morphology recovery.

Multichannel techniques for motion artifacts removal from electrocardiographic signals.

Electrocardiographic (ECG) signals are affected by several kinds of artifacts, that may hide vital signs of interest. Motion artifacts, due to the motion of the electrodes in relation to patient skin, are particularly frequent in bioelectrical signals acquired by wearable systems. In this paper we propose different approaches in order to get rid of motion confounds. The first approach we follow starts from measuring electrode motion provided by an accelerometer placed on the electrode and use this measurement in an adaptive filtering system to remove the noise present in the ECG. The second approach is based on independent component analysis methods applied to multichannel ECG recordings; we propose to use both instantaneous model and a frequency domain implementation of the convolutive model that accounts for different paths of the source signals to the electrodes.

A compatible electrocutaneous display for functional magnetic resonance imaging application.

In this paper we propose an MR (magnetic resonance) compatible electrocutaneous stimulator able to inject an electric current, variable in amplitude and frequency, into the fingertips in order to elicit tactile skin receptors (mechanoreceptors). The desired goal is to evoke specific tactile sensations selectively stimulating skin receptors by means of an electric current in place of mechanical stimuli. The field of application ranges from functional magnetic resonance imaging (fMRI) tactile studies to augmented reality technology. The device here proposed is designed using safety criteria in order to comply with the threshold of voltage and current permitted by regulations. Moreover, MR safety and compatibility criteria were considered in order to perform experiments inside the MR scanner during an fMRI acquisition for functional brain activation analysis. Psychophysical laboratory tests are performed in order to define the different evoked tactile sensation. After verifying the device MR safety and compatibility on a phantom, a test on a human subject during fMRI acquisition is performed to visualize the brain areas activated by the simulated tactile sensation.

Automated cardiac MR image segmentation: theory and measurement evaluation.

We present a new approach to magnetic resonance image segmentation with a Gradient-Vector-Flow-based snake applied to selective smoothing filtered images. The system also allows automated image segmentation in the presence of grey scale inhomogeneity, as in cardiac Magnetic Resonance imaging. Removal of such inhomogeneities is a difficult task, but we proved that using non-linear anisotropic diffusion filtering, myocardium edges are selectively preserved. The approach allowed medical data to be automatically segmented in order to track not only endocardium, which is usually a less difficult task, but also epicardium in anatomic and perfusion studies with Magnetic Resonance. The method developed proceeds in three distinct phases: (a) an anisotropic diffusion filtering tool is used to reduce grey scale inhomogeneity and to selectively preserve edges; (b) a Gradient-Vector-Flow-based snake is applied on filtered images to allow capturing a snake from a long range and to move into concave boundary regions; and (c) an automatic procedure based on a snake is used to fit both endocardium and epicardium borders in a multiphase, multislice examination. A good agreement (P<0.001) between manual and automatic data analysis, based on the mean difference+/-SD, was assessed in a pool of 907 cardiac function and perfusion images.

Non-linear prediction for oesophageal voice analysis.

Herein, non-linear prediction methods are applied to oesophageal voice analysis. The research aims to investigate normal and pathological subjects, in order to improve knowledge of the oesophageal voice behaviour. Analysis is performed in the reconstructed phase space, using both non-linear prediction with local linear approximation and the S-Map method. Preliminary results seem to confirm that in normal subjects a non-linear stable deterministic behaviour takes place, while in pathological subjects the non-linear contribution reduces while the time series becomes unstable.

Combining high-performance computing and networking for advanced 3-D cardiac imaging.

This paper deals with the integration of a powerful parallel computer-based image analysis and visualization system for cardiology into a hospital information system. Further services are remote access to the hospital Web server through an internet network. The visualization system includes dynamic three-dimensional representation of two types of medical images (e.g., magnetic resonance and nuclear medicine) as well as two images in the same modality (e.g., basal versus stress images). A series of software tools for quantitative image analysis developed for supporting diagnosis of cardiac disease are also available, including automated image segmentation and quantitative time evaluation of left ventricular volumes and related indices during cardiac cycle, myocardial mass, and myocardial perfusion indices. The system has been tested both at a specialized cardiologic center and for remote consultation in diagnosis of cardiac disease by using anatomical and perfusion magnetic resonance images.

On-line 3D evaluation of left ventricular wall motion in magnetic resonance imaging.

In the present research a system for medical image processing has been proposed, which allows dynamic 3D visualization and successive left ventricular wall analysis. The 3D volume rendering algorithm results are presented using a friendly Graphical User Interface (GUI) giving the possibility to change interactively image processing and visualization parameters at any step, to perform simple and effective image manipulations. The left ventricular wall detection algorithm is based on the evaluation of classified volumetric data during volume rendering algorithm. In fact classification operation includes a 3D segmentation. The system has been tested in medical environment, for Magnetic Resonance (MR) images. Resulting studies have demonstrated a very high global efficiency in practical situations by using typical data volume dimensions.

Real-time multimodal medical image processing: a dynamic volume-rendering application.

In the present research, a system for medical image processing has been proposed, which allows multimodal dynamic three-dimensional (3-D) visualization interactively and in real time. The system has been conceived to support medical specialists in the diagnosis of moving organs, such as the heart during the cardiac cycle, allowing them to compare information on perfusion/contraction match as a basis for diagnosis of important cardiovascular diseases. The 3-D volume-rendering algorithm runs on a SIMD machine because of the great amount of data to be manipulated by always using the same operations. One of the features of the algorithm is the possibility to change, interactively, image processing and visualization parameters at any step, and to perform simple and effective image manipulations. Performance studies have demonstrated a very high global efficiency in practical situations by using typical data-volume dimensions. The system has been tested in the medical environment, by using magnetic resonance (MR) and single-photon emission-computed tomographic (SPECT) images.

A model of ultrasound backscatter for the assessment of myocardial tissue structure and architecture.

A statistical parametric model of returning echoes from myocardium is theorized in order to investigate the relationship between normal myocardium structure and spectral signatures with the use of ultrasonic tissue characterization. It is hypothesized, that in a clinical setting the normal myofiber architecture in the left ventricular wall is structured as a matrix of cylinder scatterers whose orientation and spatial distribution vary according to two different statistical distribution laws: 1) a Gaussian law to approximate parametric angular myofiber variability at each site within the myocardial wall; 2) a gamma distribution law to describe parametric regularity in scatterer interdistance. In the model, the effect of the angle of insonification with respect to the alignment of myofibers on ultrasound backscatter was considered. The slope of the power spectral density (PSD) evaluated within the echocardiographic transducer bandwidth has been used as a ultrasonic tissue characterization parameter. The model has been tested by computer simulation and in vitro measurements on myocardial pig tissue specimens. The concordance between experimental and simulated results confirms that the model accounts for the process underlying the echo formation from normal myocardium. Moreover, it provides a simple method of simulation which can be easily implemented and used for the assessment of pathologic alterations.

A regression model of ultrasound reflectivity from normal myocardium.

In this paper the potentialities of back-scattered ultrasound to detect changes in transmural myocardial wall structure have been assessed by using a second order regression model of integrated back-scatter. The model was tested through simulation studies and experimental measurements. The experimental results prove the proposed model attractive to detect physiological transmural changes in myofibre orientation from epicardial to endocardial left ventricular wall.