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Carobbio ALC, Cheng Z, Gianiorio T, Missale F, Africano S, Ascoli A, Fragale M, Filauro M, Marchi F, Guastini L, Mora F, Parrinello G, Canevari FRM, Peretti G, Mattos LS. Electric Bioimpedance Sensing for the Detection of Head and Neck Squamous Cell Carcinoma. Diagnostics (Basel) 2023; 13:2453. [PMID: 37510197 PMCID: PMC10377945 DOI: 10.3390/diagnostics13142453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 07/09/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
The early detection of head and neck squamous cell carcinoma (HNSCC) is essential to improve patient prognosis and enable organ and function preservation treatments. The objective of this study is to assess the feasibility of using electrical bioimpedance (EBI) sensing technology to detect HNSCC tissue. A prospective study was carried out analyzing tissue from 46 patients undergoing surgery for HNSCC. The goal was the correct identification of pathologic tissue using a novel needle-based EBI sensing device and AI-based classifiers. Considering the data from the overall patient cohort, the system achieved accuracies between 0.67 and 0.93 when tested on tissues from the mucosa, skin, muscle, lymph node, and cartilage. Furthermore, when considering a patient-specific setting, the accuracy range increased to values between 0.82 and 0.95. This indicates that more reliable results may be achieved when considering a tissue-specific and patient-specific tissue assessment approach. Overall, this study shows that EBI sensing may be a reliable technology to distinguish pathologic from healthy tissue in the head and neck region. This observation supports the continuation of this research on the clinical use of EBI-based devices for early detection and margin assessment of HNSCC.
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Affiliation(s)
- Andrea Luigi Camillo Carobbio
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
- Section of Otorhinolaryngology-Head and Neck Surgery, Department of Neurosciences, University of Padua-"Azienda Ospedaliera di Padova", 35128 Padua, Italy
| | - Zhuoqi Cheng
- Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, Denmark
| | - Tomaso Gianiorio
- Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Francesco Missale
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Molecular and Translational Medicine, University of Brescia, 25125 Brescia, Italy
- Department of Head & Neck Oncology & Surgery, Antoni Van Leeuwenhoek, Nederlands Kanker Instituut, 1066 Amsterdam, The Netherlands
| | - Stefano Africano
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Alessandro Ascoli
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Marco Fragale
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Marta Filauro
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Experimental Medicine (DIMES), University of Genoa, 16132 Genoa, Italy
| | - Filippo Marchi
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Luca Guastini
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Francesco Mora
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | | | - Frank Rikki Mauritz Canevari
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Giorgio Peretti
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Leonardo S Mattos
- Department of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy
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Perera-Bel E, Aycock KN, Salameh ZS, Gomez-Barea M, Davalos RV, Ivorra A, Ballester MAG. PIRET-A Platform for Treatment Planning in Electroporation-Based Therapies. IEEE Trans Biomed Eng 2023; 70:1902-1910. [PMID: 37015676 PMCID: PMC10281020 DOI: 10.1109/tbme.2022.3232038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Tissue electroporation is the basis of several therapies. Electroporation is performed by briefly exposing tissues to high electric fields. It is generally accepted that electroporation is effective where an electric field magnitude threshold is overreached. However, it is difficult to preoperatively estimate the field distribution because it is highly dependent on anatomy and treatment parameters. OBJECTIVE We developed PIRET, a platform to predict the treatment volume in electroporation-based therapies. METHODS The platform seamlessly integrates tools to build patient-specific models where the electric field is simulated to predict the treatment volume. Patient anatomy is segmented from medical images and 3D reconstruction aids in placing the electrodes and setting up treatment parameters. RESULTS Four canine patients that had been treated with high-frequency irreversible electroporation were retrospectively planned with PIRET and with a workflow commonly used in previous studies, which uses different general-purpose segmentation (3D Slicer) and modeling software (3Matic and COMSOL Multiphysics). PIRET outperformed the other workflow by 65 minutes (× 1.7 faster), thanks to the improved user experience during treatment setup and model building. Both approaches computed similarly accurate electric field distributions, with average Dice scores higher than 0.93. CONCLUSION A platform which integrates all the required tools for electroporation treatment planning is presented. Treatment plan can be performed rapidly with minimal user interaction in a stand-alone platform. SIGNIFICANCE This platform is, to the best of our knowledge, the most complete software for treatment planning of irreversible electroporation. It can potentially be used for other electroporation applications.
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Bogusiewicz J, Bojko B. Insight into new opportunities in intra-surgical diagnostics of brain tumors. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.117043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Current status of the preclinical evaluation of alternating electric fields as a form of cancer therapy. Bioelectrochemistry 2023; 149:108287. [DOI: 10.1016/j.bioelechem.2022.108287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 09/28/2022] [Accepted: 10/02/2022] [Indexed: 11/06/2022]
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Arjun BS, Sitaramgupta VSNV, Aswin S, Rao S, Pandya HJ. A System-based Approach for the Evaluation of Electromechanical Properties of Brain Tumors. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:2585-2591. [PMID: 36086534 DOI: 10.1109/embc48229.2022.9871879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
We have developed a semi-automated system integrated with MEMS-based electromechanical sensors to characterize human brain tumors. The electrical impedance and elastic moduli of three types of brain tumors and six normal brain regions were evaluated using the system. The impedance and elastic modulus of glioma was found to be significantly lower than the normal region. It was also observed that the white matter tissues had higher impedance and elastic moduli compared with the grey matter of the same neuroanatomic location. There were observable differences in the electromechanical behavior of gliomas, which originate from glial cells to that of schwannoma and meningioma of different cellular origins. Clinical Relevance- The observations suggest that simultaneous electromechanical characterization of brain tumors can serve as an effective tool for tumor delineation. The developed tool can be used alongside gold standard histopathological analysis to better understand human brain tumors.
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Li X, Oziel M, Rubinsky B. Evaluating the therapeutic effect of tumor treating fields (TTFields) by monitoring the impedance across TTFields electrode arrays. PeerJ 2022; 10:e12877. [PMID: 35186474 PMCID: PMC8833244 DOI: 10.7717/peerj.12877] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/12/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Tumor Treating Fields (TTFields), are a novel, non-invasive tissue ablation technology for treatment of cancer. Tissue ablation is achieved through the continuous delivery of a narrow range of electromagnetic fields across a tumor, for a period of months. TTFields are designed to affect only cells that divide and to interfere with the cell division process. The therapy is monitored with MRI imaging, performed every couple of months. Current technology is unable to assess the treatment effectiveness in real time. METHODS We propose that the effect of the treatment can be assessed, in real time, by continuously measuring the change in electrical impedance across the TTFields delivery electrode arrays. An in vitro anatomic skull experimental study, with brain and tumor mimics phantom tissues was conducted to confirm the potential value of the proposed monitoring system. RESULTS Experiments show that measuring the change in the impedance amplitude between opposite TTFields electrode arrays, at a typical TTFields treatment frequency of (200 kHz), can detect changes in the tumor radius with a sensitivity that increases with the radius of the tumor. The study shows that TTFields electrode arrays can be used to assess the effectiveness of TTFields treatment on changes in the tumor dimensions in real time, throughout the treatement. This monitoring system may become a valuable addition to the TTFields cancer treatment technology. It could provide the means to continuously assess the effectiveness of the treatment, and thereby optimize the design of the treatment protocol.
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Affiliation(s)
- Xing Li
- National University of Defense Technology, Electronic Countermeasure Institute, Hefei, Anhui, China
| | - Moshe Oziel
- Department of Physiology and Pharmacology, Tel Aviv University, Tel Aviv, Israel
| | - Boris Rubinsky
- Department of Mechanical Engineering, Department of Bioenegineering, University of California, Berkeley, CA, USA
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Su B, Yu S, Yan H, Hu YD, Buzurovic I, Liu D, Liu L, Teng Y, Tang J, Wang J, Liu W. Biopsy Needle System With a Steerable Concentric Tube and Online Monitoring of Electrical Resistivity and Insertion Forces. IEEE Trans Biomed Eng 2021; 68:1702-1713. [PMID: 33606624 DOI: 10.1109/tbme.2021.3060541] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Biopsies are the gold standard for clinical diagnosis. However, a discrepancy between the biopsy sample and target tissue because of misplacement of the biopsy spoon can lead to errors in the diagnosis and subsequent treatment. Thus, correctly determining whether the needle tip is in the tumor is crucial for accurate biopsy results. METHODS A biopsy needle system was designed with a steerable, flexible, and superelastic concentric tube; electrodes to monitor the electrical resistivity; and load cells to monitor the insertion force. The degrees of freedom were analyzed for two working modes: straight-line and deflection. RESULTS Experimental results showed that the system could perceive the tissue type in online based on the electrical resistivity. In addition, changes in the insertion force indicated transitions between the interfaces of adjacent tissue layers. CONCLUSION The two monitoring methods guarantee that the biopsy spoon is at the desired position inside the tumor during an operation. SIGNIFICANCE The proposed biopsy needle system can be integrated into an autonomous robotic biopsy system.
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Lang S, Gan LS, McLennan C, Kirton A, Monchi O, Kelly JJP. Preoperative Transcranial Direct Current Stimulation in Glioma Patients: A Proof of Concept Pilot Study. Front Neurol 2020; 11:593950. [PMID: 33329346 PMCID: PMC7710969 DOI: 10.3389/fneur.2020.593950] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 10/22/2020] [Indexed: 01/24/2023] Open
Abstract
Background: Transcranial direct current stimulation (tDCS) has been used extensively in patient populations to facilitate motor network plasticity. However, it has not been studied in patients with brain tumors. We aimed to determine the feasibility of a preoperative motor training and tDCS intervention in patients with glioma. In an exploratory manner, we assessed changes in motor network connectivity following this intervention and related these changes to predicted electrical field strength from the stimulated motor cortex. Methods: Patients with left-sided glioma (n=8) were recruited in an open label proof of concept pilot trial and participated in four consecutive days of motor training combined with tDCS. The motor training consisted of a 60-min period where the subject learned to play the piano with their right hand. Concurrently, they received 40 min of 2 mA anodal tDCS of the left motor cortex. Patients underwent task and resting state fMRI before and after this intervention. Changes in both the connectivity of primary motor cortex (M1) and general connectivity across the brain were assessed. Patient specific finite element models were created and the predicted electrical field (EF) resulting from stimulation was computed. The magnitude of the EF was extracted from left M1 and correlated to the observed changes in functional connectivity. Results: There were no adverse events and all subjects successfully completed the study protocol. Left M1 increased both local and global connectivity. Voxel-wide measures, not constrained by a specific region, revealed increased global connectivity of the frontal pole and decreased global connectivity of the supplementary motor area. The magnitude of EF applied to the left M1 correlated with changes in global connectivity of the right M1. Conclusion: In this proof of concept pilot study, we demonstrate for the first time that tDCS appears to be feasible in glioma patients. In our exploratory analysis, we show preoperative motor training combined with tDCS may alter sensorimotor network connectivity. Patient specific modeling of EF in the presence of tumor may contribute to understanding the dose-response relationship of this intervention. Overall, this suggests the possibility of modulating neural networks in glioma patients.
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Affiliation(s)
- Stefan Lang
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Non-invasive Neurostimulation Network, University of Calgary, Calgary, AB, Canada
| | - Liu Shi Gan
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Non-invasive Neurostimulation Network, University of Calgary, Calgary, AB, Canada
| | - Cael McLennan
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Adam Kirton
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Non-invasive Neurostimulation Network, University of Calgary, Calgary, AB, Canada
| | - Oury Monchi
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Non-invasive Neurostimulation Network, University of Calgary, Calgary, AB, Canada
| | - John J P Kelly
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada.,Charbonneau Cancer Institute, University of Calgary, Calgary, AB, Canada
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Lang ST, Gan LS, McLennan C, Monchi O, Kelly JJP. Impact of Peritumoral Edema During Tumor Treatment Field Therapy: A Computational Modelling Study. IEEE Trans Biomed Eng 2020; 67:3327-3338. [PMID: 32286953 DOI: 10.1109/tbme.2020.2983653] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND Tumor treatment fields (TTFie-lds) are an approved adjuvant therapy for glioblastoma (GBM). The magnitude of applied electrical field has been shown to be related to the anti-tumoral response. However, peritumoral edema may result in shunting of electrical current around the tumor, thereby reducing the intra-tumoral electric field. In this study, we systematically address this issue with computational simulations. METHODS Finite element models are created of a human head with varying amounts of peritumoral edema surrounding a virtual tumor. The electric field distribution was simulated using the standard TTFields electrode montage. Electric field magnitude was extracted from the tumor and related to edema thickness. Two patient specific models were created to confirm these results. RESULTS The inclusion of peritumoral edema decreased the average magnitude of the electric field within the tumor. In the model considering a frontal tumor and an anterior-posterior electrode configuration, ≥6 mm of peritumoral edema decreased the electric field by 52%. In the patient specific models, peritumoral edema decreased the electric field magnitude within the tumor by an average of 26%. The effect of peritumoral edema on the electric field distribution was spatially heterogenous, being most significant at the tissue interface between edema and tumor. CONCLUSIONS The inclusion of peritumoral edema during TTFields modelling may have a dramatic effect on the predicted electric field magnitude within the tumor. Given the importance of electric field magnitude for the anti-tumoral effects of TTFields, the presence of edema should be considered both in future modelling studies and when planning TTField therapy.
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Iredale E, Deweyert A, Hoover DA, Chen JZ, Schmid S, Hebb MO, Peters TM, Wong E. Optimization of multi-electrode implant configurations and programming for the delivery of non-ablative electric fields in intratumoral modulation therapy. Med Phys 2020; 47:5441-5454. [PMID: 32978963 DOI: 10.1002/mp.14496] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 09/10/2020] [Accepted: 09/12/2020] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Application of low intensity electric fields to interfere with tumor growth is being increasingly recognized as a promising new cancer treatment modality. Intratumoral modulation therapy (IMT) is a developing technology that uses multiple electrodes implanted within or adjacent tumor regions to deliver electric fields to treat cancer. In this study, the determination of optimal IMT parameters was cast as a mathematical optimization problem, and electrode configurations, programming, optimization, and maximum treatable tumor size were evaluated in the simplest and easiest to understand spherical tumor model. The establishment of electrode placement and programming rules to maximize electric field tumor coverage designed specifically for IMT is the first step in developing an effective IMT treatment planning system. METHODS Finite element method electric field computer simulations for tumor models with 2 to 7 implanted electrodes were performed to quantify the electric field over time with various parameters, including number of electrodes (2 to 7), number of contacts per electrode (1 to 3), location within tumor volume, and input waveform with relative phase shift between 0 and 2π radians. Homogeneous tissue specific conductivity and dielectric values were assigned to the spherical tumor and surrounding tissue volume. In order to achieve the goal of covering the tumor volume with a uniform threshold of 1 V/cm electric field, a custom least square objective function was used to maximize the tumor volume covered by 1 V/cm time averaged field, while maximizing the electric field in voxels receiving less than this threshold. An additional term in the objective function was investigated with a weighted tissue sparing term, to minimize the field to surrounding tissues. The positions of the electrodes were also optimized to maximize target coverage with the fewest number of electrodes. The complexity of this optimization problem including its non-convexity, the presence of many local minima, and the computational load associated with these stochastic based optimizations led to the use of a custom pattern search algorithm. Optimization parameters were bounded between 0 and 2π radians for phase shift, and anywhere within the tumor volume for location. The robustness of the pattern search method was then evaluated with 50 random initial parameter values. RESULTS The optimization algorithm was successfully implemented, and for 2 to 4 electrodes, equally spaced relative phase shifts and electrodes placed equidistant from each other was optimal. For 5 electrodes, up to 2.5 cm diameter tumors with 2.0 V, and 4.1 cm with 4.0 V could be treated with the optimal configuration of a centrally placed electrode and 4 surrounding electrodes. The use of 7 electrodes allow for 3.4 cm diameter coverage at 2.0 V and 5.5 cm at 4.0 V. The evaluation of the optimization method using 50 random initial parameter values found the method to be robust in finding the optimal solution. CONCLUSIONS This study has established a robust optimization method for temporally optimizing electric field tumor coverage for IMT, with the adaptability to optimize a variety of parameters including geometrical and relative phase shift configurations.
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Affiliation(s)
- Erin Iredale
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Andrew Deweyert
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Douglas A Hoover
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,London Regional Cancer Program, London Health Sciences Centre, London, ON, Canada
| | - Jeff Z Chen
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,London Regional Cancer Program, London Health Sciences Centre, London, ON, Canada
| | - Susanne Schmid
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Matthew O Hebb
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Terry M Peters
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,Robarts Research Institute, Western University, London, ON, Canada
| | - Eugene Wong
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,Department of Physics and Astronomy, Western University, London, ON, Canada
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