Hardware for quasi-single-shot multifrequency magnetic induction tomography (MIT): the Graz Mk2 system

Detection of acute ventilatory problems via magnetic induction in a newborn animal model

BACKGROUND

Magnetic induction measurement (MIM) is a noninvasive method for the contactless registration of respiration in newborn piglets by using measurement coils positioned at the bottom of an incubator. Acute pulmonary problems may be determinants of poor neurological and psychomotor outcomes in preterm infants. The current study tested the detection of pulmonary ventilation disorders via MIM in 11 newborn piglets.

METHODS

Six measurement coils determined changes in magnetic induction, depending on the ventilation of the lung, in comparison with flow resistance. Contactless registration of induced acute pulmonary ventilation disorders (apnea, atelectasis, pneumothorax, and aspiration) was detected by MIM.

RESULTS

All pathologies except aspiration were detected by MIM. Significant changes occurred after induction of apnea (three coils), malposition of the tube (one coil), and pneumothorax (three coils) (p ≤ 0.05). No significant changes occurred after induction of aspiration (p = 0.12).

CONCLUSIONS

MIM seems to have some potential to detect acute ventilation disorders in newborn piglets. The location of the measurement coil related to the animal's position plays a critical role in this process. In addition to an early detection of acute pulmonary problems, potential information pointing to a therapeutic intervention, for example, inhalations or medical respiratory analepsis, may be conceivable with MIM in the future.

IMPACT

MIM seems to be a method in which noncontact ventilation disorders of premature and mature infants can be detected. This study is an extension of the experimental setup to obtain preliminary evidence for detection of respiratory activity in neonatal piglets. For the first time, MIM is used to register acute ventilation problems of neonates. The possibility of an early detection of acute ventilation problems via MIM may provide an opportunity to receive patient-side information for therapeutical interventions like inhalations or medical respiratory analepsis.

Urinary Bladder Volume Monitoring Using Magnetic Induction Tomography: A Rotational Simulation Model for Anatomical Slices within the Pelvic Region

Urinary bladder volume monitoring can benefit from contactless measurements, as alternative to the traditional medical methods of transurethral catheterization or ultrasound examination. The emerging modality of Magnetic Induction Tomography (MIT) offers the possibility for estimation of the intravesical volume in the physiological and pathological states using conductivity map reconstructions of the tissues present in the pelvic region. Within MIT, eddy currents originating from the conductive urine can produce their own magnetic field in response to an external magnetic source that is susceptible of being detected outside the body by means of a static ring of sensing coils. However, the ill-conditioned and ill-posed nature of the MIT Inverse Problem make the numerical implementation and conductivity estimation highly laborious. In this paper, we present a rotational frame model based on the MIT principles with application in urodynamic studies, which allows to extend the number of contactless measurements without increasing the overall dimension of the simulation domain, at the expense of solving multiple MIT Forward Problems. On the inversion process, the single-step Gauss-Newton method with Laplacian regularizer is recruited to estimate the bladder volume non-invasively and remotely (estimation error of 19%), paving the way for this technique to surpass the current limitations found in intravesical volume monitoring in quasi-real time.

Detection and Elimination of Signal Errors Due to Unintentional Movements in Biomedical Magnetic Induction Tomography Spectroscopy (MITS)

In biomedical MITS, slight unintentional movements of the patient during measurement can contaminate the aimed images to a great extent. This study deals with measurement optimization in biomedical MITS through the detection of these unpredictable movements during measurement and the elimination of the resulting movement artefacts in the images to be reconstructed after measurement. The proposed detection and elimination (D&E) methodology requires marking the surface of the object under investigation with specific electromagnetically perturbing markers during multi-frame measurements. In addition to the active marker concept already published, a new much simpler passive marker concept is presented. Besides the biological signal caused by the object, the markers will perturb the primary magnetic field inducing their own signals. The markers' signals will be used for the detection of any unwanted object movements and the signal frames corrupted thereby. The corrupted signal frames will be then excluded from image reconstruction in order to prevent any movement artefacts from being imaged with the object. In order to assess the feasibility of the developed D&E technique, different experiments followed by image reconstruction and quantitative analysis were performed. Hereof, target movements were provoked during multifrequency, multiframe measurements in the β-dispersion frequency range on a saline phantom of physiological conductivity. The phantom was marked during measurement with either a small single-turn coil, an active marker, or a small soft-ferrite plate, a passive marker. After measurement, the erroneous phantom signals were corrected according to the suggested D&E strategy, and images of the phantom before and after correction were reconstructed. The corrected signals and images were then compared to the erroneous ones on the one hand, and to other true ones gained from reference measurements wherein no target movements were provoked on the other hand. The obtained qualitative and quantitative measurement and image reconstruction results showed that the erroneous phantom signals could be accurately corrected, and the movement artefacts could be totally eliminated, verifying the applicability of the novel D&E technique in measurement optimization in biomedical MITS and supporting the proposed aspects.

Screening and Biosensor-Based Approaches for Lung Cancer Detection

Early diagnosis of lung cancer helps to reduce the cancer death rate significantly. Over the years, investigators worldwide have extensively investigated many screening modalities for lung cancer detection, including computerized tomography, chest X-ray, positron emission tomography, sputum cytology, magnetic resonance imaging and biopsy. However, these techniques are not suitable for patients with other pathologies. Developing a rapid and sensitive technique for early diagnosis of lung cancer is urgently needed. Biosensor-based techniques have been recently recommended as a rapid and cost-effective tool for early diagnosis of lung tumor markers. This paper reviews the recent development in screening and biosensor-based techniques for early lung cancer detection.

A special phase detector for magnetic inductive measurement of cerebral hemorrhage

Cerebral hemorrhage is an important clinical problem that is often monitored and studied with expensive techniques, such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). These devices are not readily available in economically underdeveloped regions of the world and in emergency departments and emergency zones. The magnetic inductive method is an emerging technology that may become a new tool to detect cerebral hemorrhage. In this study, a special phase detector (PD) was developed and used for cerebral hemorrhage detection with the magnetic inductive method. The performance indicated that the PD can achieve phase noise as low as 6 m° and a 4-hour phase drift as low as 30 m° at 21.4 MHz. The noise and drift decreased as the frequency decreased. The performance at 10.7 MHz was slightly better than that of other recently developed phase detection systems. To test the practicality of the system, the PD was used to detect the volume change in a self-made physical model of the brain. The measured phase shift was approximately proportional to the volume change of physiological saline inside the model. The change of the phase shift increased as the volume change and frequency increased. The results are in agreement with those from previous reports. To verify the feasibility of in vivo detection, an autologous blood injection model was established in rabbit brain. The results from the injection group showed a similar trend of increasing phase shift change with increasing injection volume. The average phase shift change induced by a 3-ml injection of blood was 0.502°±0.119°, which was much larger than that of the control group. The measurement system can distinguish a minimal cerebral hemorrhage volume of approximately 0.5 ml. All of the results demonstrated that the PD used with this method can detect cerebral hemorrhage.

Hardware and software design for a National Instrument-based magnetic induction tomography system for prospective biomedical applications

Magnetic induction tomography (MIT) is a new and emerging type of tomography technique that is able to map the passive electromagnetic properties (in particular conductivity) of an object. Excitation coils are used to induce eddy currents in the medium, and the magnetic field produced by the induced eddy current is then sensed by the receiver coils. Because of its non-invasive and contactless feature, it becomes an attractive technique for many applications (especially in biomedical area) compared to traditional contact electrode-based electrical impedance tomography. Due to the low contrast in conductivity between biological tissues, an accurate and stable hardware system is necessary. Most MIT systems in the literature employ external signal generators, power amplifiers and highly stable down-conversion electronics to obtain a satisfactory phase measurement. However, this would increase design complexity substantially. In this paper, a National Instrument-based MIT system is developed at the University of Bath, aiming for biomedical applications. The system utilizes National Instrument products to accomplish all signal driving, switching and data acquisition tasks, which ease the system design whilst providing satisfactory performance. This paper presents a full-scaled medical MIT system, from the sensor and system hardware design, eddy current model verification to the image reconstruction software: the performance of this MIT instrumentation system is characterized in detail, including the system accuracy and system stability. The methods of solving eddy current problem are presented. The reconstructed images of detecting the presence of saline solutions are also included in this paper, which show the capability of national instrument products to be developed into a full-scaled biomedical MIT system, by demonstrating the practical experimental results.

Anisotropic conductivity tensor imaging using magnetic induction tomography

Magnetic induction tomography aims to reconstruct the electrical conductivity distribution of the human body using non-contact measurements. The potential of the method has been demonstrated by various simulation studies and a number of phantom experiments. These studies have all relied on models having isotropic distributions of conductivity, although the human body has a highly heterogeneous structure with partially anisotropic properties. Therefore, whether the conventional modeling approaches used so far are appropriate for clinical applications or not is still an open question. To investigate the problem, we performed a simulation study to investigate the feasibility of (1) imaging anisotropic perturbations within an isotropic medium and (2) imaging isotropic perturbations inside a partially anisotropic background. The first is the case for the imaging of anomalies that have anisotropic characteristics and the latter is the case e.g. in lung imaging where an anisotropic skeletal muscle tissue surrounds the lungs and the rib cage. An anisotropic solver based on the singular value decomposition was used to attain conductivity tensor images to be compared with the ones obtained from isotropic solvers. The results indicate the importance of anisotropic modeling in order to obtain satisfactory reconstructions, especially for the imaging of the anisotropic anomalies, and address the resolvability of the conductivity tensor components.

Forward modelling of magnetic induction tomography: a sensitivity study for detecting haemorrhagic cerebral stroke

For a magnetic induction tomography (MIT) system operating at 10 MHz, the signals produced by a haemorrhagic cerebral stroke were computed using an anatomically realistic, multi-layer, finite element (FE) head model comprising 12 tissues. The eddy-current problem was approximated using the commercial FE package, Comsol Multiphysics, and the numerical techniques employed were validated using a benchmark test. Mesh convergence for the head model was investigated for first- and second-order elements. MIT signals were computed for strokes of different sizes and locations in the brain to judge the sensitivity of the MIT configuration. The results revealed that for a large peripheral stroke (volume 50 cm(3)), 27% of the signals were above the phase noise level achievable in our current data-collection hardware (approximately 20 m degrees). In order to detect the same percentage of the signals due to a centrally located small stroke, a reduction in phase noise to 1 m degrees was necessary.