Integrating clinical research in an operative screening and diagnostic breast imaging department: First experience, results and perspectives using microwave imaging

Rationale and objectives

Clinical research is crucial for evaluating new medical procedures and devices. It is important for healthcare units and hospitals to minimize the disruptions caused by conducting clinical studies; however, complex clinical pathways require dedicated recruitment and study designs.This work presents the effective introduction of novel microwave breast imaging (MBI), via MammoWave apparatus, into the clinical routine of an operative screening and diagnostic breast imaging department for conducting a multicentric clinical study.

Materials and methods

Microwave breast imaging, using MammoWave apparatus, was performed on volunteers coming from different clinical pathways. Clinical data, comprising demographics and conventional radiologic reports (used as reference standard), was collected; a satisfaction questionnaire was filled by every volunteer. Microwave images were analyzed by an automatic clinical decision support system, which quantified their corresponding features to discriminate between breasts with no relevant radiological findings (NF) and breasts with described findings (WF).

Results

Conventional breast imaging (DBT, US, MRI) and MBI were performed and adapted to assure best clinical practices and optimum pathways. 180 volunteers, both symptomatic and asymptomatic, were enrolled in the study. After microwave images' quality assessment, 48 NF (15 dense) and 169 WF (88 dense) breasts were used for the prospective study; 48 (18 dense) breasts suffered from a histology-confirmed carcinoma. An overall sensitivity of 85.8 % in breasts lesions' detection was achieved by the microwave imaging apparatus.

Conclusion

An optimum recruitment strategy was implemented to assess MBI. Future trials may show the clinical usefulness of microwave imaging, which may play an important role in breast screening.

Dielectric Characterization of Breast Biopsied Tissues as Pre-Pathological Aid in Early Cancer Detection: A Blinded Feasibility Study

Dielectric characterization has significant potential in several medical applications, providing valuable insights into the electromagnetic properties of biological tissues for disease diagnosis, treatment planning, and monitoring of therapeutic interventions. This work presents the use of a custom-designed electromagnetic characterization system, based on an open-ended coaxial probe, for discriminating between benign and malignant breast tissues in a clinical setting. The probe's development involved a well-balanced compromise between physical feasibility and its combined use with a reconstruction algorithm known as the virtual transmission line model (VTLM). Immediately following the biopsy procedure, the dielectric properties of the breast tissues were reconstructed, enabling tissue discrimination based on a rule-of-thumb using the obtained dielectric parameters. A comparative analysis was then performed by analyzing the outcomes of the dielectric investigation with respect to conventional histological results. The experimental procedure took place at Complejo Hospitalario Universitario de Toledo-Hospital Virgen de la Salud, Spain, where excised breast tissues were collected and subsequently analyzed using the dielectric characterization system. A comprehensive statistical evaluation of the probe's performance was carried out, obtaining a sensitivity, specificity, and accuracy of 81.6%, 61.5%, and 73.4%, respectively, compared to conventional histological assessment, considered as the gold standard in this investigation.

A multicentric, single arm, prospective, stratified clinical investigation to evaluate MammoWave's ability in breast lesions detection

Microwave imaging is a safe and promising new technology in breast radiology, avoiding discomfort of breast compression and usage of ionizing radiation. This paper presents the first prospective microwave breast imaging study during which both symptomatic and asymptomatic subjects were recruited. Specifically, a prospective multicentre international clinical trial was performed in 2020-2021, to investigate the capability of a microwave imaging device (MammoWave) in allowing distinction between breasts with no radiological finding (NF) and breasts with radiological findings (WF), i.e., with benign or malignant lesions. Each breast scan was performed with the volunteers lying on a dedicated examination table in a comfortable prone position. MammoWave output was compared to reference standard (i.e., radiologic study obtained within the last month and integrated with histological one if available and deemed necessary by responsible investigator) to classify breasts into NF/WF categories. MammoWave output consists of a selection of microwave images' features (determined prior to trials' start), which allow distinction between NF and WF breasts (using statistical significance p<0.05). 353 women were enrolled in the study (mean age 51 years ± 12 [SD], minimum age 19, maximum age 78); MammoWave data from the first 15 women of each site, all with NF breasts, were used for calibration. Following central assessor evaluation, 111 NF (48 dense) and 272 WF (136 dense) breasts were used for comparison with MammoWave output. 272 WF comprised 182 benign findings and 90 malignant histology-confirmed cancer. A sensitivity of 82.3% was achieved (95%CI: 0.78-0.87); sensitivity is maintained when limiting the investigation to histology-confirmed breasts cancer only (90 histology-confirmed breasts cancer have been included in this analysis, having sizes ranging from 3 mm to 60 mm). Specificity value of approximately 50% was achieved as expected, since thresholds were calculated (for each feature) using median value obtained after recruiting the first 15 women (of each site), all NF. This prospective trial may represent another step for introducing microwave imaging into clinical practice, for helping in breast lesion identification in asymptomatic women.

A Multicentric, Single Arm, Prospective, Stratified Clinical Investigation to Confirm MammoWave's Ability in Breast Lesions Detection

Novel techniques, such as microwave imaging, have been implemented in different prototypes and are under clinical validation, especially for breast cancer detection, due to their harmless technology and possible clinical advantages over conventional imaging techniques. In the prospective study presented in this work, we aim to investigate through a multicentric European clinical trial (ClinicalTrials.gov Identifier NCT05300464) the effectiveness of the MammoWave microwave imaging device, which uses a Huygens-principle-based radar algorithm for image reconstruction and comprises dedicated image analysis software. A detailed clinical protocol has been prepared outlining all aspects of this study, which will involve adult females having a radiologist study output obtained using conventional exams (mammography and/or ultrasound and/or magnetic resonance imaging) within the previous month. A maximum number of 600 volunteers will be recruited at three centres in Italy and Spain, where they will be asked to sign an informed consent form prior to the MammoWave scan. Conductivity weighted microwave images, representing the homogeneity of the tissues' dielectric properties, will be created for each breast, using a conductivity = 0.3 S/m. Subsequently, several microwave image parameters (features) will be used to quantify the images' non-homogenous behaviour. A selection of these features is expected to allow for distinction between breasts with lesions (either benign or malignant) and those without radiological findings. For all the selected features, we will use Welch's t-test to verify the statistical significance, using the gold standard output of the radiological study review.

Automated breast lesion localisation in microwave imaging employing simplified pulse coupled neural network

MammoWave is a microwave imaging device for breast lesion detection, employing two antennas which rotate azimuthally (horizontally) around the breast. The antennas operate in the 1-9 GHz band and are set in free space, i.e., pivotally, no matching liquid is required. Microwave images, subsequently obtained through the application of Huygens Principle, are intensity maps, representing the homogeneity of the dielectric properties of the breast tissues under test. In this paper, MammoWave is used to realise tissues dielectric differences and localise lesions by segmenting microwave images adaptively employing pulse coupled neural network (PCNN). Subsequently, a non-parametric thresholding technique is modelled to differentiate between breasts having no radiological finding (NF) or benign (BF) and breasts with malignant finding (MF). Resultant findings verify that automated breast lesion localization with microwave imaging matches the gold standard achieving 81.82% sensitivity in MF detection. The proposed method is tested on microwave images acquired from a feasibility study performed in Foligno Hospital, Italy. This study is based on 61 breasts from 35 patients; performance may vary with larger number of datasets and will be subsequently investigated.

Ultra-Wideband (UWB) Systems in Biomedical Sensing

The extremely low power transmission levels of ultra-wideband (UWB) technology, alongside its advantageously large bandwidth, make it a prime candidate for being used in numerous healthcare scenarios, which require short-range high-data-rate communications and safe radar-based applications [...].

Breast lesion detection through MammoWave device: Empirical detection capability assessment of microwave images' parameters

MammoWave is a microwave imaging device for breast lesions detection, which operates using two (azimuthally rotating) antennas without any matching liquid. Images, subsequently obtained by resorting to Huygens Principle, are intensity maps, representing the homogeneity of tissues' dielectric properties. In this paper, we propose to generate, for each breast, a set of conductivity weighted microwave images by using different values of conductivity in the Huygens Principle imaging algorithm. Next, microwave images' parameters, i.e. features, are introduced to quantify the non-homogenous behaviour of the image. We empirically verify on 103 breasts that a selection of these features may allow distinction between breasts with no radiological finding (NF) and breasts with radiological findings (WF), i.e. with lesions which may be benign or malignant. Statistical significance was set at p<0.05. We obtained single features Area Under the receiver operating characteristic Curves (AUCs) spanning from 0.65 to 0.69. In addition, an empirical rule-of-thumb allowing breast assessment is introduced using a binary score S operating on an appropriate combination of features. Performances of such rule-of-thumb are evaluated empirically, obtaining a sensitivity of 74%, which increases to 82% when considering dense breasts only.

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

In this paper, we present an investigation of different artefact removal methods for ultra-wideband Microwave Imaging (MWI) to evaluate and quantify current methods in a real environment through measurements using an MWI device. The MWI device measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. A simple two-layered phantom mimicking human head tissue is realised, applying a cylindrically shaped inclusion to emulate brain haemorrhage. Detection has been successfully achieved using the superimposition of five transmitter triplet positions, after applying different artefact removal methods, with the inclusion positioned at 0°, 90°, 180°, and 270°. The different artifact removal methods have been proposed for comparison to improve the stroke detection process. To provide a valid comparison between these methods, image quantification metrics are presented. An "ideal/reference" image is used to compare the artefact removal methods. Moreover, the quantification of artefact removal procedures through measurements using MWI device is performed.

Design of Distributed Spiral Resonators for the Decoupling of MRI Double-Tuned RF Coils

OBJECTIVE

A systematic analytical approach to design Spiral Resonators (SRs), acting as distributed magnetic traps (DMTs), for the decoupling of concentric Double-Tuned (DT) RF coils suitable for Ultra-High Field (7 T) MRI is presented.

METHODS

The design is based on small planar SRs placed in between the two RF loops (used for signal detection of the two nuclei of interest). We developed a general framework based on a fully analytical approach to estimate the mutual coupling between the RF coils and to provide design guidelines for the geometry and number of SRs to be employed. Starting from the full-analytical estimations of the SRs geometry, electromagnetic simulations for improving and validating the performance can be carried out.

RESULTS AND CONCLUSION

We applied the method to a test case of a DT RF coil consisting of two concentric and coplanar loops used for 7 T MRI, tuned at the Larmor frequencies of the proton (¹H, 298 MHz) and sodium (²³Na, 79 MHz) nuclei, respectively. We performed numerical simulations and experimental measurements on fabricated prototypes, which both demonstrated the effectiveness of the proposed design procedure.

SIGNIFICANCE

The decoupling is achieved by printing the SRs on the same dielectric substrate of the RF coils thus allowing a drastic simplification of the fabrication procedure. It is worth noting that there are no physical connections between the decoupling SRs and the ¹H/²³Na RF coils, thus providing a mechanically robust experimental set-up, and improving the transceiver design with respect to other traditional decoupling techniques.

Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data

Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for breast lesion detection is used to accumulate clinical data from subjects undergoing breast examinations at the Department of Diagnostic Imaging, Perugia Hospital, Perugia, Italy. This paper presents the first ever clinical demonstration and comparison of a microwave ultra-wideband (UWB) device augmented by machine learning with subjects who are simultaneously undergoing conventional breast examinations. Non-ionizing microwave signals are transmitted through the breast tissue and the scattering parameters (S-parameter) are received via a dedicated moving transmitting and receiving antenna set-up. The output of a parallel radiologist study for the same subjects, performed using conventional techniques, is taken to pre-process microwave data and create suitable data for the machine intelligence system. These data are used to train and investigate several suitable supervised machine learning algorithms nearest neighbour (NN), multi-layer perceptron (MLP) neural network, and support vector machine (SVM) to create an intelligent classification system towards supporting clinicians to recognise breasts with lesions. The results are rigorously analysed, validated through statistical measurements, and found the quadratic kernel of SVM can classify the breast data with 98% accuracy.

Occupational exposure in MR facilities due to movements in the static magnetic field

PURPOSE

The exposure of operators moving in the static field of magnetic resonance (MR) facilities was assessed through measurements of the magnetic flux density, which is experienced as variable in time because of the movement. Collected data were processed to allow the comparison with most recent and authoritative safety standards.

METHODS

Measurements of the experienced magnetic flux density B were performed using a probe worn by volunteers moving in MR environments. A total of 55 datasets were acquired nearby a 1.5 T, 3 T, and 7 T whole body scanners. Three different metrics were applied: the maximum intensity of B, to be compared with 2013/35/EU Directive exposure limit values for static fields; the maximum variation of the vector B on every 3s-interval, for comparison with the ICNIRP-2014 basic restriction aimed at preventing vertigo effects; two weighted-peak indices (for "sensory" and "health" effects: SENS-WP, HLTH-WP), assessing compliance with ICNIRP-2014 and EU Directive recommendations intended to prevent stimulation effects.

RESULTS

Peak values of |B| were greater than 2 T in nine of the 55 datasets. All the datasets at 1.5 T and 3 T were compliant with the limit for vertigo effects, whereas six datasets at 7 T turned out to be noncompliant. At 7 T, all 36 datasets were noncompliant for the SENS-WP index and 26 datasets even for the HLTH-WP one.

CONCLUSIONS

Results demonstrate that compliance with EU Directive limits for static fields does not guarantee compliance with ICNIRP-2014 reference levels and clearly show that movements in the static field could be the key component of the occupational exposure to EMF in MR facilities.

Radiofrequency magnetic resonance coils and communication antennas: Simulation and design strategies

Coils simulation and design is a fundamental task to maximize Signal-to-Noise Ratio in Magnetic Resonance applications. In the meantime, in the last years the issue of accurate communication antennas analysis has grown. Coil design techniques take advantage of computer simulations in dependence on the magnetic field wavelength and coil sizes. In particular, since at high frequencies coils start to behave as antennas, modern Magnetic Resonance coil development exploits numerical methods typically employed for antennas simulation. This paper reviews coil and antenna performance parameters and focuses on the different simulation approaches in dependence on the near/far field zones and operating frequency.

Evaluation of 3D radio-frequency electromagnetic fields for any matching and coupling conditions by the use of basis functions

A procedure for evaluating radio-frequency electromagnetic fields in anatomical human models for any matching and coupling conditions is introduced. The procedure resorts to the extraction of basis functions: such basis functions, which represent the fields produced by each individual port without any residual coupling, are derived through an algebraic procedure which uses the S parameter matrix and the fields calculated in one (only) full-wave simulation. The basis functions are then used as building-blocks for calculating the fields for any other S parameter matrix. The proposed approach can be used both for volume coil driven in quadrature and for parallel transmission configuration.

Electromagnetic characterization of an MR volume coil with multilayered cylindrical load using a 2-D analytical approach

We present an analytical method for the analysis of Radio Frequency (RF) volume coils for Magnetic Resonance Imaging (MRI), using a 2-D full wave solution with loading by multilayered cylinders. This allows the characterization of radio-frequency E, H, B1, B1(+) fields. Comparisons are provided with experimental data obtained at 7.0 T. The procedure permits us to clearly separate the solution to single line source problem (which we call the primordial solution) and the composite solution (i.e. full coil, i.e. the summations of primordial solutions according to the resonator drive configuration). The capability of separating the primordial solution and the composite one is fundamental for a thorough analysis of the phenomena of dielectric resonance, and of standing wave and multi-source interference. We show that dielectric resonance can be identified only by looking at the electromagnetic field from a single line source.

Pleural mesothelioma after a short interval from first exposure in the wine filter industry

Pleural mesotheliomas are usually reported after a long interval has passed since first exposure to asbestos. We, however, describe a case observed after a latent period of only 7.5 years in a worker exposed in a factory manufacturing auxiliary products for wine treatment, including chrysotile asbestos filters. The exposure to asbestos lasted 3-4 months per year, during which airborne fiber concentrations ranged from 1 to 4 ff/cc in the patient's workplace. Due to the characteristics of the manufacturing process, the asbestos fibers were very thin in diameter. The patient also suffered from nasal breathing impairment. An examination of the literature showed that asbestos-related mesotheliomas have been reported, albeit rarely, after less than 10 years from onset of exposure. Therefore, it is believed that this case should be related to past exposure to asbestos.