WO2021250563A1 - An in-vivo, intraoperative probe for brain tumour margin delineation and methods thereof - Google Patents

Abstract

The present invention relates to an in-vivo intraoperative probe (100) for brain tumour margin delineation comprising of biochip carrier (104), distal end (106), handle (108), low noise data transfer cable (112) with a multichannel connector (114) or wireless connectivity (Bluetooth, Wi-Fi, RF) to transfer the data from biochip/sensors (102) to an interface module (200). The present invention also relates to a method for delineate tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin using an intraoperative probe.

Description

AN IN-VIVO , INTRAOPERATIVE PROBE FOR BRAIN TUMOUR MARGIN DEUINEATION AND METHODS THEREOF

FIEUD OF THE INVENTION

[1] The present invention generally relates to a system or device for tumour margin delineation. Specifically, the present invention relates to an in-vivo intraoperative probe for brain tumour margin delineation comprising of biochips/sensors, biochip carrier, distal end, handle, low noise data transfer cable with a multichannel connector or wireless connectivity (Bluetooth, Wi-Fi, RF) to transfer data from the biochip/sensors to an interface module. The present invention also relates to a method for delineate tumour margin based on measurements of a single or multiple properties of brain tissues using an intra-operative probe to detect tumour margin.

BACKGROUND OF THE INVENTION

[2] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.

[3] Brain tumours have a high incidence, mortality and morbidity in patients with over 300,000 new cases and over 200,000 related deaths reported every year, globally. Primary brain tumours originating from within the brain or spine are graded from I to IV based on the aggressiveness, as per the WHO grading system. Grade I are slow spreading and are usually considered benign while, Grade II is low-grade glioma which have the potential to become higher grade. Grade III and IV are characterised by rapid growth, spread to nearby tissues, increased necrosis, vascularisation and, low survival rates. Among the tumours, gliomas are the most frequent. They originate from transformed glial cells which surround the neurons and provide supportive functions as well as insulation between neurons.

[4] Brain tumours are usually treated by surgical resection, followed by adjuvant chemotherapy and radiation. The primary objective of surgery is to remove tumour regions without impairing neurological functions. The accuracy and efficacy of resection strongly influences the effectiveness of chemotherapy and radiation, whilst minimizing damage to surrounding tissues and associated neurological loss. A conservative resection can lead to significant residual tumour, leading to progression and recurrence, whereas an excessive resection can lead to neurological impairment due to removal of adjacent normal tissue. Improved extent of resection (EOR) corresponds to higher survival rate and lower chances of recurrence after the surgery. Gross total resection (GTR) is necessary to reduce the recurrence of gliomas and depends on the surgeon’s ability to delineate between normal and tumour tissues. Due to the heterogeneity of the brain tissues, especially in the regions affected by gliomas, the gross total resection is generally not achieved. Therefore, discrimination of tumour from normal brain tissue and associated resection must be carried out with the highest possible accuracy to provide best patient outcomes.

[5] Various intraoperative tools and techniques, for instance, Awake craniotomy, Fluorescence-guided surgery, Intraoperative MRI, Raman spectroscopy, Positron emission spectroscopy (PET), Functional magnetic resonance imaging (fMRI), Diffusion tensor imaging (DTI), Transcranial magnetic stimulation (TMS) and Direct electric stimulation (DES) have been used to delineate tumour margin. However, preoperative imaging and planning cannot be completely relied due to brain shift and brain plasticity. These methods are limited by factors such as anaphylactic reactions to fluorescence agents, seizures arising due to stimulation, slower intra-operative data acquisition rates, cost associated with the development of facility, additional operating time, equipment size and associated costs, etc. Therefore, tools based on alternative modalities need to be developed that are capable of intraoperatively delineate tumour from normal brain tissues.

[6] As the disease such as tumour progresses, significant tissue deterioration and variations causes neuropathological changes. Neuropathological changes in affected brain tissue can also lead to changes in other physical properties of the tissues. These property variations can hence be suitably used as modalities for tumour delineation. For example, the electrical properties of biological tissues have been widely explored as they can provide valuable insights into the biological processes within the tissue. Electrical characterisation is concerned with defining how a biological system behaves in response to an applied current flow such as the resistance to the flow (resistance), and also, the ability to store charges (capacitance). Studies have shown that the tumour has different electrical properties with respect to the adjacent healthy tissue and such measurements have been employed to delineate between tumour and normal tissues. The variations in these properties can be due to higher water content, elevated or decreased ion concentrations, and even the change in dielectric behaviour of cell membranes because of cellular necrosis and excessive vascularization. Tumours have been reported to have a lower specific resistivity compared to normal tissues. Electrical resistivity as well as impedance measurements have been carried out on animal brain tissues (ex-vivo and in-vivo), and human brain tissues (ex-vivo). These studies have shown significant variability in reported absolute resistivity across subjects, but the trends between normal tissues and tumour have been consistent.

[7] Similar to variation in electrical properties of tissues, mechanical properties of tissues such as viscoelasticity, stiffness etc., are also known to vary due to tissue damage caused by disease progression and hence, can be used as a biomarker for tumour delineation. The mechanical property that is known to be linked to the tumour formation is due to the modified structure of extracellular matrix (ECM) proteins. Based on several studies using Atomic Force Microscopy (AFM) and micro-sensors, it is known that the stiffness of the cancerous tissue significantly differs from the normal tissue in breast. The change in stiffness can be directly linked to cancer progression. Most of the mechanical property measurement experiments inferred less viscous and softer nature of tumour tissue compared to normal healthy tissue. In human brain, research work has been carried out for characterizing the visco-elastic properties of human brain tissues in order to treat the brain damages due to impact (A. Samadi-Dooki, G. Z. Voyiadjis, and R. W. Stout, “A combined experimental, modeling, and computational approach to interpret the viscoelastic response of the white matter brain tissue during indentation,” J. Mech. Behav. Biomed. Mater., vol. 77, pp. 24-33, 2018). Studies concerning understanding of variation in mechanical properties of brain tissue due to Alzheimer’s are being reported (Kihan Park, G. E. Fonsberry, M. Gearing, A. I. Fevey, and J. P. Desai, “Viscoelastic Properties of Human Autopsy Brain Tissues as Biomarkers for Alzheimer’s Diseases,” IEEE Trans. Biomed. Eng., vol. 66, no. 6, pp. 1705- 1713, 2019). Magnetic resonance elastography (MRE) is an alternative technique, based on elasticity imaging technique that utilizes mechanical shear waves to measure stiffness of the tissues and have been utilized for sub-surface tumour detection. However, studies concerning the mechanical properties of human brain tissues for tumour margin delineation are limited.

[8] The sensors/biochips can be made of many available techniques like MEMS or surface chemistry or nanoimprint or screen printing or any of the other lithography -based processes or technology. These technologies have the potential to be mass manufactured, with multifunctionality and miniaturization. Microelectromechanical systems (MEMS) is a technology derived from the integrated circuit (IC) industry and widely used for the miniaturization of systems such as mechanical, optical, fluidic and, magnetic. Miniaturization is achieved by microfabrication techniques, such as bulk and surface micromachining, aided by photolithography. MEMS-based sensors are of interest in medical applications due to their ability to analyze biological materials at the microscale. The major contributions of MEMS in the biomedical domain are sensors such as pressure sensors, gas sensors, sensors for prosthetics and, impedance sensors. MEMS-based sensors for delineating between tumour and normal tissues in breast cancer using resistivity measurement have been reported (H. J. Pandya et ah, “Towards an automated MEMS-based characterization of benign and cancerous breast tissue using bioimpedance measurements,” Sens. Actuators B Chem., vol. 199, pp. 259-268, 2014; H. J. Pandya, K. Park, and J. P. Desai, “Design and fabrication of a flexible MEMS-based electro-mechanical sensor array for breast cancer diagnosis,” J. Micromechanics Microengineering, vol. 25, no. 7, p. 075025, 2015).

[9] Similarly, other properties of tissues also vary as the tumour affects the brain tissues such as optical, pH, thermal or dielectric etc. Also, multiple of these parameters can also change together, and coupling effects between them are also possible. By measuring these variations, the probe can carry out tumour margin delineation.

[10] Therefore, there is a need to develop an intra-operative probe for delineating tumour margin based on measurements of a single or multiple properties of brain tissues such as electrical, mechanical, acoustic, optical, pH, thermal, dielectric or any combination thereof to detect tumour margin.

OBJECT OF THE INVENTION

[11] An object of the present invention is to provide an in-vivo intraoperative probe for delineating tumour margin of brain tissues.

[12] Another object of the present invention is to provide an in-vivo intraoperative probe for delineating tumour margin based on MEMS technology which increases the probability of attaining gross total resection, improves post-surgical quality of life by reducing damage to surrounding live tissues and functional tissues and increases the accuracy of tumour resection,

[13] Another object of the present invention is to provide an in-vivo intraoperative probe for delineating tumour margin that is simple, portable and cost-effective.

[14] Another object of the present invention is to provide an in-vivo intraoperative probe for delineating tumour margin that can work on real time basis thereby reducing the time of surgery.

[15] Another object of the present invention is to provide a method for delineate tumour margin based on measurements of an individual or multiple properties of brain tissues using an intraoperative probe to detect tumour margin. SUMMARY OF THE INVENTION

[16] The present invention relates to a system for tumour margin delineation. Specifically, the present invention relates to an in-vivo intraoperative probe for brain tumour margin delineation.

[17] In an aspect, the present invention relates to an in-vivo intraoperative probe for delineating tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin, comprising: a biochip carrier that integrate sensors onto the intraoperative probe, the sensors detects a set of data pertaining to properties of tissues of a subject; a distal end which is unidirectionally or multi-directionally steerable to have access to tissues in different orientations with respect to surgical cavity, wherein the distal end is coupled to the biochip carrier; a handle coupled with the distal end for holding the intraoperative probe, the handle comprises buttons, knobs, and a printed circuit board (PCB) in casing of the handle, wherein the PCB configured to process the detected data; and an interface module receives the set of data from the sensors through the PCB using a low noise data transfer cable coupled to a multichannel connector or through wireless connectivity, wherein based on the received set of data, the tumour margin of the subject is delineated.

[18] In another aspect of the present disclosure, the biochip carrier is present on the tip, sides, or within the distal end of the probe, wherein the sensors comprise individual or array of electrodes, force sensors, piezoelectric-based or capacitance-based micromachined ultrasound transducers (MUTs), heating elements, temperature measurement sensors, optics, pH sensing layers and a combination thereof to perform multifunctional measurements.

[19] In another aspect of the present disclosure, the electrodes of sensors are made of any or a combination of metals, alloys and conducting polymers, wherein the metals are selected from a group comprising gold, platinum, titanium, silver, and a combination thereof.

[20] In another aspect of the present disclosure, the sensors allow the probe to detect the properties of the brain tissues in contact with or in proximity to the sensor, wherein the sensors detect electrical properties, mechanical properties, acoustic properties, optical properties, dielectric properties, pH properties, thermal properties and a combination thereof, wherein electrical properties, dielectric properties, and pH properties is measured by touching the tissue surface with electrodes, the mechanical properties are measured using indenting the tissue using the probe tip, ultrasound imaging and elastography is performed using MUTs contacting the brain surface, the optical properties and the thermal properties is measured by contact or proximity sensors. [21] In another aspect of the present disclosure, the distal end is composed of an outer lumen and an inner lumen between which tendons or shape memory alloys (SMA) is placed for actuation.

[22] In another aspect of the present disclosure, the actuation mechanisms to control the probe is selected from a group comprising magnetic, pneumatic, hydraulic, electrostatic, smart actuator materials (SMA), tendon based mechanical actuation and a combination thereof, wherein the probe is handled manually or robotically.

[23] In another aspect of the present disclosure, the interface module comprises a display and a control panel, wherein the display is a Graphical User Interface (GUI) configured to display the processed data for straightforward interpretation, and the control panel is configured to calibrate of the probe, steering of the distal end and to activate/deactivate the probe.

[24] In another aspect of the present disclosure, the electrodes for electrical characterisation are used for neural recording and stimulation, the probe configured to determine neurological disorders when the properties of the affected tissues vary from normal tissues and the probe determines other forms of tumours and pathologies affecting other body parts of the subject.

[25] In another aspect of the present disclosure, the biochips/sensors integrated onto the probe is fabricated using microelectromechanical systems (MEMS), PCB fabrication, surface chemistry, nanoimprint, screen printing, lithography-based processes or technology or a combination thereof.

[26] In an aspect, the present invention relates a method for delineate tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin using an intraoperative probe comprising: steering a distal end comprising sensors to come into contact or within close proximity of brain tissues using a handle of a probe to detect a set of data pertaining to properties of tissues of a subject, the handle comprises buttons, knobs, and a printed circuit board (PCB) in casing of the handle, wherein the PCB configured to process the detected data; transferring the set of data from the sensors to an interface module through the PCB using a low noise data transfer cable coupled to a multichannel connector or through wireless connectivity; and delineating tumour margin of the subject based on the set of data received in the interface module.

[27] In another aspect of the present invention, the biochips/sensors measures electrical properties, mechanical properties, acoustic properties, optical properties, pH, thermal properties or combination thereof. [28] In another aspect of the present invention, the steering of distal end is carried out manually by means of buttons or knobs in the handle or robotically by means of pre-planning or using adaptive methods such as machine learning.

[29] In another aspect of the present invention, the transfer of data is optionally carried out using wireless modes selected from Bluetooth, Wi-Fi and radio frequency (RF) module.

[30] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.

BRIEF DESCRIPTION OF THE DRAWINGS

[31] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[32] FIG. 1A illustrates an in-vivo intraoperative probe integrated with sensors/ biochips for brain tumour margin delineation, in accordance with embodiments of the present disclosure.

[33] FIG. IB illustrates an exploded view of an in-vivo intraoperative probe integrated with sensors/ biochips for brain tumour margin delineation, in accordance with embodiments of the present disclosure.

[34] FIG. 1C represents isometric view, top view, side view and front view of an in-vivo intraoperative probe, in accordance with embodiments of the present disclosure.

[35] FIG. 2A illustrates an interface module of the in-vivo intra-operative probe for brain tumour margin detection, in accordance with embodiments of the present disclosure.

[36] FIG. 2B represents isometric view, top view, bottom view, side view and front view of an interface module of the in-vivo intra-operative probe for brain tumour margin detection, in accordance with embodiments of the present disclosure.

[37] FIG. 3 represents the Graphical User Interface (GUI) for tumour margin delineation in the interface display unit, in accordance with embodiments of the present disclosure. [38] FIG. 4 represents the steerability of the intra-operative probe of the present disclosure.

[39] FIG. 5 illustrates the image of an in-vivo intraoperative probe for brain tumour margin detection operated by a robotic arm, in accordance with embodiments of the present disclosure.

[40] FIG. 6A illustrates the schematic representation of the signal conditioning circuit that is used within the probe, in accordance with embodiments of the present disclosure.

[41] FIG. 6B illustrates a flow chart of a method for delineate tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin using an intraoperative probe, in accordance with embodiments of the present disclosure.

[42] FIG. 7 depicts the Scanning Electron Microscopy (SEM) image of the electrodes of the biochip used for measuring electrical resistivity, in accordance with embodiments of the present disclosure.

[43] FIG. 8 represents process flow for the fabrication of the biochip for measuring tissue resistivity (a) single side polished silicon wafer is taken (b) oxide is thermally grown over silicon (c) photoresist spin is coated over the silicon dioxide (d) photoresist is patterned (e) titanium/platinum deposited over patterned photoresist (f) Lift-off process used to realise the electrodes (g) biochip design dimensions.

[44] FIG. 9 illustrates a platform for studying electrical resistivity of brain tissues ( Ex-vivo ), in accordance with embodiments of the present disclosure.

[45] FIG. 10 illustrates schematic representation of the resistivity measurement circuit used in the electronic module, in accordance with embodiments of the present disclosure.

[46] FIG. 11 illustrates the resistivity of normal tissues and tumour (a) Plot of resistivity of brain tissues versus tumour (b) Variation in the resistivity of tissues of different anatomical regions of human brain across three different subjects (c) Mean resistivity of different anatomical regions of formalin fixed human brain tissue samples and tumour (Glioblastoma, Meningioma) (d) Variation of measured resistivity due to anisotropy across three different axes for the same sample from different anatomical regions of the same.

[47] FIG. 12 illustrates a schematic view of fabricated probe for electrical characterization of brain tissues, in accordance with embodiments of the present disclosure. [48] FIG. 13 illustrates a graphical view of impedance vs frequency for tumour and adjacent normal tissue, in accordance with embodiments of the present disclosure.

[49] FIG. 14A illustrates a graphical view of plot of stiffness at 30% strain for tumour and adjacent normal tissue, in accordance with embodiments of the present disclosure.

[50] FIG. 14B illustrates a graphical view of the plot of load vs displacement for tumour and adjacent normal tissue, in accordance with embodiments of the present disclosure.

[51] FIG. 15A illustrates an exemplary view of pulser-receiver circuit for acoustic characterization, in accordance with embodiments of the present disclosure.

[52] FIG. 15B illustrates a graphical view of plot of transmitted pulse amplitude vs time, in accordance with embodiments of the present disclosure.

[53] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the system, one or more components of the system may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

DETAILED DESCRIPTION OF THE INVENTION

[54] The following is a detailed description of embodiments of the disclosure. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.

[55] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.

[56] Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments

[57] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

[58] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.

[59] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

[60] Various terms as used herein are shown below. To the extent a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.

[61] Embodiments of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc.) or combining software and hardware implementation that may all generally be referred to herein as a “circuit,” “module,” “component,” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product comprising one or more computer readable media having computer readable program code embodied thereon.

[62] As used herein, and unless the context dictates otherwise, the term "coupled to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean “communicatively coupled with” over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.

[63] The present invention relates to a system for tumour margin delineation. Specifically, the present invention relates to an in-vivo intraoperative probe for brain tumour margin delineation. The present invention provides an in-vivo intraoperative probe for delineating tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin that improves the extent of resection which is a well sought out parameter to evaluate the success of surgical resection of tumour, increases the probability of attaining gross total resection, which is essential for recurrence free survival, and reduces damage to surrounding live tissues and functional tissues thereby improving post-surgical quality of life. The in-vivo intraoperative probe of the present invention further addresses the issue of brain shift or plasticity of brain tissues once the dura is opened as part of craniotomy thereby increase the accuracy of tumour resection.

[64] According to the present invention, the intraoperative probe can work on real-time basis and hence, reduce the time of surgery. The intraoperative probe can analyze one or more properties of the tissues, to create tumour margin by cross comparing the data obtained, thereby increasing reliability and cross-checking for possible disparity.

[65] In another embodiment, the present disclosure provides an intra-operative probe that can delineate between tumour and normal tissues of human brain in-vivo based on variations in electrical, acoustic, mechanical, optical, pH, thermal, dielectric properties or combination thereof of brain tissues. The intraoperative probe can be used by a neurosurgeon during surgical resection of tumour. It can be manually operated as well as by means of a robot. The intraoperative probe comes along with interfacing unit that helps in raw data readout for the neurosurgeon. The interfacing unit has a Graphical User Interface (GUI), that displays a virtual margin created using the data obtained from the intraoperative probe.

[66] In an embodiment, the present disclosure relates to an in-vivo intraoperative probe 100 for delineating tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin, comprising a biochip carrier 104 that can integrate sensors 102 also interchangeably referred to as biochips onto the intraoperative probe 100, the sensors 102 detects a set of data pertaining to properties of tissues of a subject/patient. A distal end 106 which is unidirectionally or multi-directionally steerable to have access to tissues in different orientations with respect to surgical cavity, wherein the distal end 106 is coupled to the biochip carrier 104. A handle 108 coupled to the distal end 106 for holding the intraoperative probe 100, the handle 108 comprises buttons/knobs 110, and a printed circuit board (PCB) 122 in casing of the handle 108, the PCB 122 configured to process the detected data. An interface module 200 receives the set of data from the biochips/sensors 102 through the PCB 122 using a low noise data transfer cable 112 coupled to a multichannel connector 114.

[67] FIG. 1A illustrates an in-vivo intraoperative probe integrated with sensors/ biochips for brain tumour margin delineation, in accordance with embodiments of the present disclosure.

[68] Referring to FIG. 1A, an in-vivo intraoperative probe 100 for delineating tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin. The intraoperative probe 100 consists of a handle 108 for the neurosurgeon to hold the probe 100 and manually do the tumour margin identification and a distal end 106 is unidirectionally or multi-directionally steerable like a catheter. The steerability is configured to provide more degrees of freedom for the intraoperative probe 100, especially while the intraoperative probe 100 is being used to detect tumour margin from regions other than the surface of the brain. The tip or surface of the distal end 106 consists of a biochip/sensor carrier 104, where the biochips/sensors 102 are attached. This biochip/sensor carrier 104 is an electrical interconnecting module as well as an attachment unit between the distal end of the intraoperative probe 100 and biochip 102. The steering of the distal end 106 is controlled by the buttons or knobs 110 or other tactile sensors provided on the handle 108. The output signal from the biochip/sensors 102 is transferred via a low noise data transfer cable 112 of the intraoperative probe 100 to an interface module (200) by means of a multichannel connector 114.

[69] In an exemplary embodiment, the sensor/biochip 102 can include individual or array of electrodes, force sensors, piezoelectric-based or capacitance-based micromachined ultrasound transducers (MUTs), heating elements, temperature measurement sensors, optics, pH sensing layers and a combination of any for multifunctional measurements. These sensors allow the probe 100 to measure electrical, mechanical, acoustic, optical, dielectric, pH, thermal, and other properties of the brain tissues in contact with or in proximity to the sensor 102. The sensors 102 can sense the following properties:

• electrical properties such as resistivity, impedance and the likes. • mechanical properties such as stiffness, visco-elasticity, creep, relaxation, elasticity, bulk modulus, shear modulus and the likes.

• acoustic properties such as absorbance, scattering, diffraction, attenuation, reflectance, speed of sound and the likes.

• optical properties such as absorbance, scattering, attenuation, reflectance, diffraction, and the likes.

• pH

• thermal properties such as temperature, thermal conductivity, heat capacity and the likes.

• dielectric properties such as permittivity and dielectric constant or a combination of multiple of these properties.

[70] In another embodiment of the present disclosure, the steerability of the distal end 106 can be achieved by means of tendon-based actuation mechanism, shape memory alloys (SMA) or any other actuation methods available. The steering mechanism within probe 100 configured to bend the distal end 106 of the probe 100 to access tissues in different orientations with respect to the surgical cavity. Different actuation mechanisms to steer the probe tips can include magnetic, pneumatic, hydraulic, electrostatic, smart actuator materials (SMA) and tendon based mechanical actuation. When the probe 100 is used by hand, the steering can be achieved through buttons, knobs, tactile sensors, or other methods. The steering can also be performed by giving commands on the interface module 200 (also interchangeably referred to as interface unit 200, herein). The steering can be carried out robotically, using surgical pre-planning or using adaptive methods such as machine learning. While steering the tip position, sensors 102 can be calculated by means of feedback for accurate and reliable measurement of properties and to prevent undue indentation.

[71] In another embodiment, the output signal from the biochip/sensors 102 is transferred to an interfacing module 200 by means of wireless transmission using technologies, for example but not limited to, Bluetooth, Wi-Fi, or RF.

[72] FIG. IB illustrates an exploded view of an in-vivo intraoperative probe integrated with sensors/ biochips for brain tumour margin delineation, in accordance with embodiments of the present disclosure.

[73] The distal end 106 of the in-vivo intraoperative probe 100 may be composed of an outer lumen 120, an inner lumen 116, between which a SMA actuator 118 is placed for actuation. This construction pattern can vary according to the type of actuation mechanisms being used and the placement of sensors 102 and interconnects. In another embodiment, the SMA actuator 118 can be replaced with tendons for tendon-based actuation mechanism. The steering of the distal end 106 is controlled by the buttons or knobs 110 or other tactile sensors provided on the handle 108 while used by hand. The electrical connectivity from the biochip/sensor 102 to the intraoperative probe 100 is made by PCB 122 through the inside of the inner lumen 116. The raw electronic data from the biochip 102 is processed by the PCB 122 for signal conditioning/processing amplifiers, filters and other necessary electronic circuits etc., within the handle 108 of the intraoperative probe 100.

[74] In another embodiment of the present disclosure, the PCB 122 within the handle 108 of the intraoperative probe 100 also contains circuit for the actuation mechanism for steering, powering and transmission of data.

[75] FIG. 1C represents isometric view, top view, side view and front view of an in-vivo intraoperative probe, in accordance with embodiments of the present disclosure. In an embodiment of the present disclosure, FIG 1C illustrates the isometric view, top view, side view and front view of an in-vivo intraoperative probe 100 for delineating tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin.

[76] FIG. 2A illustrates an interface module of the in-vivo intra-operative probe for brain tumour margin detection, in accordance with embodiments of the present disclosure.

[77] Referring to FIG. 2A, the interface module 200 have a display unit 202 that can be touch sensitive or not and, a control panel 204. The display unit 202 has a graphical user interface (GUI), for readouts of raw data, as well as processed data for easier interpretation. The processed data can even be used for identifying the tumour margin by means of a virtual representation of tumour margin. The control panel 204 is useful for the calibration and tuning of the intraoperative probe 100, steering of the distal end 106 is required, powering ON and OFF etc. The interface module 200 is connected to the main power source and contains electronics for powering up the intraoperative probe circuits and actuators. The output signals from the PCB are collected at the interface module 200 by means of a multichannel connector 206 via a low noise data transfer cable of the intraoperative probe 100.

[78] In another embodiment of the present disclosure, the output signals from the PCB are collected at the interface module 200 by means of wireless transmission using technologies like Bluetooth, Wi-Fi, RF etc. [79] In another embodiment of the present invention, as illustrated in Fig. 2B is the isometric view, top view, bottom view, side view and front view of an interface module of the in-vivo intra-operative probe for brain tumour margin detection.

[80] FIG. 3 represents the Graphical User Interface (GUI) for tumour margin delineation in the interface display unit, in accordance with embodiments of the present disclosure.

[81] FIG. 3 illustrates the GUI 300 for readouts of raw data, as well as processed data for easier interpretation. The GUI 300 can be interactive as well as non-interactive. The processed data can be used to identify the tumour margin through a virtual representation of the tumour margin. A camera (also referred to as image capturing unit, herein) can be used to map the tissue region being sensed to its corresponding properties, and tumour margin can be represented over that captured image. The control panel 204 can be used to calibrate the probe 100, steering of the distal end 106 is required, powering ON and OFF or activate/deactivate the probe etc. The interface unit 200 can be connected to the main power source and contain electronics to power up the probe circuits and actuators. The GUI of the display unit 202 has image of the brain tissues and tabs to read the multiple properties such as electrical, mechanical and the likes. Also, GUI has tabs to connect, start acquisition, stop acquisition and save data in order to give instructions to the biochip/sensors 102 of the intraoperative probe 100. The GUI 300 also provides a virtual tumour margin delineation interface.

[82] FIG. 4 represents the steerability of the intra-operative probe of the present disclosure. In another embodiment of the present disclosure, FIG. 4 illustrates the steerability of the intra-operative probe 100. The steering mechanism within the intraoperative probe 100 helps to bend the distal end 106 of the probe 100 to have access to tissues in different orientations with respect to the surgical cavity. In an embodiment, different actuation mechanisms that can be employed to control the probe 100 or probe tip are selected from magnetic, pneumatic, hydraulic, electrostatic, smart actuator materials (SMA) and tendon based mechanical actuation. When the probe is used by hand, the steering can be achieved by means of buttons, knobs or tactile sensors or other methods. The steering can be carried out by giving commands on the interface unit. Robotically the steering can be carried out, by means of pre-planning or using adaptive methods such as machine learning.

[83] FIG. 5 illustrates the image of an in-vivo intraoperative probe for brain tumour margin detection operated by a robotic arm, in accordance with embodiments of the present disclosure. FIG. 5 illustrates image of the in-vivo intra-operative probe for brain tumour margin detection operated by a robotic arm. The robotic arm can also be used to operate the intraoperative probe 100 of the present disclosure. Using the robotic arm under the supervision of an experience neurosurgeon has the added advantages of repeatability and reliability. In an embodiment, the steering of the distal end 106 during robotic surgery can be electronic, rather than buttons provided on handle 108. The surgery could be pre-planned based on pre-operative imaging, and robot can be pre-programmed or controlled remotely by an operator.

[84] FIG. 6A illustrates the schematic representation of the signal conditioning circuit that is used within the probe, in accordance with embodiments of the present disclosure. FIG. 6 A is an electronic printed circuit board 122 for signal conditioning/processing the raw electronic data from the biochip/sensors 102 of the intraoperative probe 100. The PCB 122 includes amplifiers, filters and other necessary electronic circuits within the probe handle. This PCB 122 also contains circuit for the actuation mechanism for steering, powering and transmission of data.

[85] According to the present disclosure, the intra-operative probe 100 can be used by the neurosurgeon by hand or robotically during a craniotomy procedure to remove tumour. The surgical resection can be pre-planned by means of pre-operative imaging to get the approximate location of the tumour. The intraoperative probe 100 can be maneuverer inside the surgical cavity and can be used to measure the properties of the tissues. The measured data is transferred to the PCB 122 within the probe handle 108, where the raw data is processed and transmitted to the interface module 200. A virtual tumour margin is displayed for the neurosurgeon to precisely identify the tumour from the normal tissues. Further, this margin can be referred by the surgeon to resect the tumour.

[86] The biochip/sensor 202 of the present disclosure that are integrated onto the probe 100 can be fabricated using multiple techniques like MEMS, conventional PCB fabrication, surface chemistry, nanoimprint, screen printing or any of the other lithography-based processes or technology or a combination thereof. These biochips/sensors 102 can be suitably attached to the probe 100 by means of biochip carrier 104 with suitable interconnection technology such as wire bonding, flip-chip, ball grid array, pogo pin assembly and other well- known packaging techniques. The biochip/sensors 102 can measure electrical properties such as resistivity, impedance, dielectric behaviour etc., mechanical properties such as stiffness, visco-elasticity, hardness etc., optical properties such as absorbance, scattering etc., pH, thermal properties such as temperature, thermal conductivity, heat capacity etc., and dielectric properties such as permittivity or combination of multiple of these properties. [87] FIG. 6B illustrates a flow chart of a method for delineate tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin using an intraoperative probe. At block 602 steering the distal end comprising biochips/sensors 102 to come into contact or within close proximity of brain tissues using the handle 108 of the probe 100 to detect the set of data pertaining to properties of tissues of the subject, the handle 108 comprises buttons, knobs, and PCB 122 in casing of the handle 108, where the PCB 122 configured to process the detected data received from the sensor 102.

[88] At block 604, transferring data from the biochips/sensors 102 to the interfacing module 200 through PCB 122 using the low noise data transfer cable 112 with a multichannel connector 114 or wirelessly (Bluetooth, Wi-Fi, RF), and at block 606, delineating tumour margin of the subject based on the set of data received in the interface module 200.

[89] In another embodiment of the present disclosure, the sensors/biochip 102 can be steered to contact or come in close proximity of the brain tissues, and the properties can be measured. The measurement protocols can vary according to property being measured. The mechanical properties of the tissues can be measured by means of indenting the tissue to a known displacement and measuring the reaction force. The mechanical properties can be measured using indenting the tissue using the probe tip. The generated reaction for various indentation stimuli can be used to understand tissue properties like stiffness, relaxation, elasticity, creep and the likes. Ultrasound imaging and elastography can be carried out using micromachined ultrasound transducers (MUTs), touching the brain surface. Other acoustic property of tissues, such as attenuation, reflectance, diffraction etc., can also be measured. The electrical, dielectric, pH can be measured by touching the tissue surface with electrodes. The optical and thermal properties of the tissues can be measured by contact or proximity based sensors. The data can be transferred to the PCB/ASIC within the probe handle 108 consisting of various signal conditioning circuits. After processing the data, the data can be transferred wired/wirelessly to the interface unit 200.

[90] In another embodiment of the present disclosure, the sensor/biochip 102 can be fabricated on various substrate materials such as silicon, glass, ceramic and polymer as substrate. In an embodiment, different processes such as microfabrication, PCB fabrication, MEMS, surface chemistry, nanoimprint or any of the other lithography-based processes or technology as well as screen printing, drop casting etc., can be used to fabricate the sensors 102. All sensors can be fabricated as single elements or as an array of elements. The electrodes or pads for measuring the electrical, thermal, pH properties can be made of gold, platinum, titanium, silver or any other metals, alloys or conducting polymers or a combination thereof.

[91] In another embodiment of the present disclosure, the force sensing can be achieved based on piezoresistivity, piezoelectricity, electromagnetically or other methods. Optical sensing can be achieved using combinations of lasers, light emitting diodes (LEDs) with infrared or other wavelengths, and photodetectors. The optics within the probe can also consist of micro-mirrors, light sources, fibre optical cables, lenses etc. Electrical sensors can work based on resistivity or impedance measurements. An array of electrodes can be used for electrical impedance tomography. Ultrasound transducers can be based on conventional piezoelectric crystals (piezoelectric crystals sandwiched between electrodes) or fabricated using micromachining techniques micromachined transducers (MUTs). These MUTs can be piezoelectric (PMUTs) or capacitive (CMUTs). Piezoelectric materials like lead zirconate titanate (PZT), Zinc oxide (ZnO), Aluminium nitride (AIN), Barium Titanate (BaTi03), or others can be used for fabricating the PMUTs. The CMUTs can be made using polymer- based methods (polyCMUTs). Thermal sensors can work based on heat transfer, resistance changes, or other forms of indicating temperature variation.

[92] The dimensions, design, construction methodology, materials of the intraoperative probe 100, the biochip 102 and the interface unit 200 can vary as requirement arises. There can be changes in the data representation in the interface unit 200. Electronic system integrated with microchip, electronics for data acquisition, processing and transmission, high fidelity connectors for reliable contact with sensor pads, and display for easy read-out of test results can be modified. The data transmittal can be wired or wireless.

[93] In another embodiment, the intraoperative probe 100 of the present disclosure is useful for other neurological disorders like Alzheimer’s, Parkinson’s, Stroke, Epilepsy etc., if properties of the affected tissues vary from normal tissues. The proposed probe 100 can also be used in other forms of tumours and pathologies affecting other parts of the body such as the liver, breast, lungs, stomach, mouth and the likes.

[94] In yet another embodiment, platform for measuring electrical resistivity of human brain tissues is developed to use the electrical resistivity property as a biomarker for the in- vivo intraoperative probe for delineating normal and tumour brain tissues and thereby improving brain tumour resection.

[95] Development of a platform integrated with MEMS -based biochips for measuring the electrical resistivity of formalin-fixed human brain tissues and tumour A. Biochip Fabrication [96] The MEMS-based biochips were fabricated using a 4-inch silicon substrate using a single mask process. The microfabrication process flow used for the fabrication of biochip is as follows: (a) a 4-inch 500 pm thick single side polished (100) oriented silicon (Si) wafer was used as a substrate, (b) lpm thick silicon dioxide (S1O2) was grown by dry oxidation at 1100 °C, (c) 1.3 pm of positive photoresist (PR) S 1813 was spin-coated at 4000 rpm for 40 seconds, followed by soft-bake at 90°C for 1 minute, (d) PR was exposed using MJB4 mask aligner and patterned using darkfield mask followed by development and post-exposure bake at 110 °C for 1 minute, (e) Ti/Pt (25nm/150nm) was deposited using E-beam evaporation (TECPORT E-beam evaporator), and (f) Ti/Pt was patterned using a lift-off technique to form the electrodes. Finally, automatic dicing machine (DAD321 Disco Wafer Dicer) was used to release the fabricated biochips from the silicon wafer. The biochip sensing region covers an area of 330pm x 330pm. The electrodes have a uniform width of 30pm and an interelectrode spacing of 15pm. The biochip has a total dimension of 10mm x 5 mm (L x B) (Fig. 8(g)). The size of the biochip was selected to enable the integration of the biochip with slide fit contacts provided in the platform for measurements. The SEM image of sensing electrodes of the biochip is shown in FIG. 7 and process flow for the fabrication of the biochip for measuring tissue resistivity is shown in FIG. 8.

B. Digital analogue converter (DAC) based platform for brain tissue studies 1. Mechanical actuation unit

[97] The platform for studying the brain tissue properties using electrical resistivity is shown in FIG.9. The dimensions of the platform are 180mm x 140mm x 180mm (F x B x H). The casing is made of 20mm x 20mm (W x B) aluminium extrusions and the casing out of lmm brushed SS sheet cut by laser cutting. 3D printing using PEA (polylactic acid) is used to fabricate custom-designed parts such as clamps, fixtures, etc. for the platform. The platform consists of a vertical indentation stage actuated using a NEMA 17 stepper motor with a resolution of 200 steps per revolution. The rotary motion of the motor gets converted to translational motion in ±Z direction by means of a four- start ACME threaded rod with a pitch of 2mm, along with an anti-backlash nut. Two precision linear guide rails with a total displacement of 35mm were used to guide the indentation stage. Arduino Mega 2560 was used as the controller for mechanical actuation and bidirectional motor movements are regulated by the RAMPS 1.4 motor driver unit. End-stop limit switches are provided at axis limits for calibration of home positions as well as to prevent overrunning of the stage and damage. At the tip of the indentation stage, the provision of slide fit contacts is provided to fix the microfabricated biochip P which acts as the indenter (see FIG. 9). [98] A fixed tissue holder along with a similar slide fit contacts to fix biochip Q (see FIG. 9) is provided at the base of the platform which is also aligned with the axis of movement of the biochip P. The tissue is placed in the tissue holder over biochip Q sensing region and biochip P is brought down in -Z direction. The contact of biochip P with tissue is ensured by monitoring the changes in resistance values measured. After the biochip contacts the tissue, we restrict the -Z movement (indentation) of biochip P to 500 pm to keep the experiment parameter (indentation) consistent while performing repeatable measurements

2. Electronic Module

[99] A Meanwell LRS-150-12 Switched Mode Power Supply (SMPS) is used to power the entire platform by converting 220 V AC power supply to ±12 voltage DC supply. The circuit schematics for the electronic module designed for sensor readout is shown in FIG. 10. A resistive voltage divider circuit is used for calculating the tissue resistance. Since the resistance values measured span from MQs range to few a kQs, the accuracy of the measured value significantly depends upon the difference in the order of magnitude of the known resistance and measurand resistance. Four resistors Rl, R2, R3, and R4 with resistance values in ranging from 101<W to 10MW are used for calibrating the voltage divider circuit. These resistors are provided with 5V DC supply and are connected to the voltage divider via a 4:1 multiplexer. The select pins of the multiplexer are connected to the microcontroller ATmega328P. The biochips P and Q used for measuring the tissue resistance are connected to the microcontroller by means of CD4066, a quad bilateral switch. By switching the CD4066, the platform will be able to measure resistance of the tissue placed between the biochips. The switching is controlled by the microcontroller and happens in sequence after the tissue is placed in the tissue holder and command to measure the resistance is given. To measure resistance, the pair of bilateral switches U3.1 and U3.4 is activated. The active electrodes in this configuration will be the electrode A (Refer fig. 8(g)) of both P and Q. The output of the voltage divider is given to the buffer amplifier Ul.l (see Fig.10) for avoiding loading effect. The output of the buffer stage is connected to the microcontroller’s ADC for measuring the voltage from the voltage divider. The ADC measures the voltage four times, switching the calibration resistors from Rl to R4 using multiplexer. From the four voltage values obtained, the resistor that gives the voltage level closer to the mid voltage range, i.e., 2.5V is the taken as the calibration resistor. This resistor ideally has the resistance in comparable range as that of the tissue being placed between the biochips. The resistance of the tissue is then measured and recorded for calculating the resistivity.

C. Tissue preparation [100] Formalin-fixed relatively normal human brains (N=3) collected from road traffic accident victims following written informed consent from close relative of deceased (Ethical clearance document no.

IEC/2015) were obtained from the Human

Brain Tissue Repository (Brain Bank)at National Institute of Mental Health & Neurosciences (NIMHANS) for this study. The brains were sliced serially in the coronal plane. Cubical tissue blocks of dimensions approximately 5 mm x 5mm x 5mm were then extracted using a surgical scalpel from these slices by a trained neuropathologist (AM, SR). A total of n = 82 normal brain tissue blocks were obtained from representative neuroanatomical regions (Frontal Grey Matter (FGM) = 6, Frontal White Matter (FWM) = 12, Caudate (CAU) = 8, Putamen = 9, Thalamus = 12, Hippocampus = 12, Internal Capsule (IC) = 11, Corpus Callosum White Matter (CC) = 12) (Fig.10). Similar cubical blocks were prepared from tumour samples which were resected from patients and then preserved by formalin fixation. A total of n=8 blocks of Glioblastoma (GBM) and n=4 blocks of Meningioma (following histological confirmation) were obtained. The dimensions of the tissue blocks were noted thrice using a digital Vernier caliper since the tissues blocks varied in surface morphology based on the regions they belong to and the physiology. The mean value of dimensions was recorded and was used for calculating resistivity after the resistance measurements were carried out. Also, tissue blocks following measurements were processed for paraffin embedding. Serial sections at 5micrometers were cut and stained with Hematoxylin-eosin, Luxol Fast Blue for delineating myelin, cresyl violet for demonstrating neuronal component. Masson trichrome stain to delineate vascularity, and matrix were performed and each parameter analysed across the tissue blocks. The sections from tumors were subjected to Hematoxylin-eosin and appropriate immunohistochemistry for characterizing tumor grade. Results:

[101] A total of n=82 normal tissue blocks and n=12 tumour blocks, obtained from N=3 formalin-fixed subject brains were intended using biochip P. Time taken for loading and measurement of a single sample was around 5 minutes. The resistivity of normal tissues and tumour were calculated. The coefficient of variation in the calculated resistivity for each sample was less than 10% in all the sample categories. The plot of mean resistivity of normal tissues versus tumour is shown in FIG. 11(a). Welch’s t-test for unequal sample size and assuming unequal variance, showed significant statistical difference between resistivity of tumour and normal tissues (p<0.0001) and the power at 5% significance level was found to be 0.93. The lower values of resistivities for tumour compared to normal brain tissues agree with the findings reported in literatures (C. Senft, A. Bink, K. Franz, H. Vatter, T. Gasser, and V. Seifert, “Intraoperative MRI guidance and extent of resection in glioma surgery: a randomised, controlled trial,” Lancet Oncol., vol. 12, no. 11, pp. 997-1003, Oct. 2011; M. Jermyn et al, “Intraoperative brain cancer detection with Raman spectroscopy in humans,” Sci. Transl. Med., vol. 7, no. 274, p. 274ral9, Feb. 2015).

5 [102] The mean resistivity of different anatomical regions of normal tissues, and the two types of tumours (Glioblastoma and Meningioma) were also individually calculated. FIG. 11(b) shows the variation in the resistivity of different anatomical regions of normal brain across three different subjects. The changes in the resistivity values of tissues from subject to subject may be attributed by factors such as age, physiology and various other parameters (J.

10 Latikka and H. Eskola, “The Resistivity of Human Brain Tumours In Vivo,” Ann. Biomed. Eng., vol. 47, no. 3, pp. 706-713, Mar. 2019). FIG. 11(c) clearly shows the variation of mean resistivity among different regions of the brain due to heterogenous behaviour of the tissue and the values are tabulated in Table I below. Also, similar to the literature (D. G. Southwell,

S. L. Hervey-Jumper, D. W. Perry, and M. S. Berger, “Intraoperative mapping during repeat 15 awake craniotomy reveals the functional plasticity of adult cortex,” J. Neurosurg., vol. 124, no. 5, pp. 1460-1469, May 2016; C. Gabriel, S. Gabriel, and E. Corthout, “The dielectric properties of biological tissues: I. Literature survey,” Phys. Med. Biol., vol. 41, no. 11, pp. 2231-2249, Nov. 1996), results shows reduced resistivity of grey matter compared to white matter, and this could be due to the higher water content. FIG. 11(d) shows the anisotropy in 20 measured resistivity across anterior, superior and, medial axes of normal human brain tissues obtained from different anatomical regions.

Table I

THE MEAN RESISTIVITY OF DIFFERENT ANATOMICAL REGIONS OF BRAIN, GLIOBLASTOMA AND, MENINGIOMA FWM FGM CCWM IC PUTAMEN BGC THALAMUS HIPPOCAMPUS GBM MENINGIOMA

Mean Resistivity 903 615 543 462 365 314 307 314 154 106 Standard Deviation 393 350 372 234 245 113 148 105 77 25 Co-efficient of variation 43.5 56.8 68.5 50.6 66.7 36 48 33 50 23.8

Mean Resistivity, Standard Deviation are in shown in W-cm, Co-efficient of variation in %.

[103] The platform for measuring electrical resistivity of human brain tissues is developed. The platform consists of a mechanical indentation unit and a tissue holder that 25 were incorporated with microfabricated MEMS -based biochip. An electronic module with resistivity measurement circuit based on Direct Applied Current technique is integrated onto the platform. The resistivity of formalin-fixed tumour and brain tissues obtained from three different subjects were measured. Tumour tissues were found to have a lower resistivity (134 ± 71 W-cm) compared to normal brain tissues (480 ± 339 W-cm) and a clear delineation between the resistivity of normal tissues and tumour was observed and confirmed using statistical analysis. The variation in electrical resistivity due to the heterogeneity and anisotropy of different anatomical regions of the brain was also investigated. The resistivity measurement using the MEMS -based biochips as contact electrodes, yielded results similar to that obtained using conventional electrodes reported in the literature. The electrodes of the biochip occupy significantly lower area compared to conventional electrodes, and good contact interface was formed. Based on the present study, the electrical resistivity can be used as a biomarker for the development of MEMS -based in-vivo intraoperative tool for delineating normal and tumour brain tissues and thereby improving brain tumour resection.

[104] FIG. 12 illustrates a schematic view of fabricated probe for electrical characterization of brain tissues, in accordance with embodiments of the present disclosure. A prototype of the intraoperative probe 100 is developed to delineate between tumour tissue and normal tissue using electrical properties of tissues. Electrical impedance measurement can be carried out on freshly excised tumour samples, and normal tissues obtained from cadaver post-mortem.

[105] FIG. 13 illustrates a graphical view of impedance vs frequency for tumour and adjacent normal tissue, in accordance with embodiments of the present disclosure. A clear delineation between tumour and normal tissue can be observed, showing the capability of the probe to identify tumour margin, where tumour has lower impedance compared to normal tissue.

[106] FIG. 14A illustrates a graphical view of plot of stiffness at 30% strain for tumour and adjacent normal tissue, in accordance with embodiments of the present disclosure. Brain tissue mechanical characterization is illustrated in FIG. 14A, mechanical behaviour of freshly excised tumour tissues and adjacent normal tissues from the cadaver brain were experimentally characterised using the portable platform. It was found that the tumour tissues were stiffer compared to normal tissues.

[107] FIG. 14B illustrates a graphical view of the plot of load vs displacement for tumour and adjacent normal tissue, in accordance with embodiments of the present disclosure. On loading, the tumour and normal tissues at different strain rates showed that tumour tissues were strain hardened at lower strains compared to adjacent normal tissues. Also, the lack of distinction in tissue behaviour for tumour at different strain rates due to disintegrated tissue structure can be seen.

[108] FIG. 15A illustrates an exemplary view of pulser-receiver circuit for acoustic characterization, in accordance with embodiments of the present disclosure. Brain tissue acoustic characterization is shown in FIG. 15 A. Acoustic behaviour of freshly excised tumour tissues and adjacent normal tissues from the cadaver brain were experimentally characterised using the portable platform. A custom-made pulse-receiver circuit is developed to actuate a 1 MHz PZT-5H transducer and sense the reflected ultrasound waves.

[109] FIG. 15B illustrates a graphical view of plot of transmitted pulse amplitude vs time, in accordance with embodiments of the present disclosure. The plot shown in FIG. 15B, depicts tumour tissues exhibited higher acoustic attenuation compared to normal tissues.

[110] It will be apparent to those skilled in the art that the probe 100 of the disclosure may be provided using some or all of the mentioned features and components without departing from the scope of the present disclosure. While various embodiments of the present disclosure have been illustrated and described herein, it will be clear that the disclosure is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the scope of the disclosure, as described in the claims.

ADVANTAGES OF THE PRESENT INVENTION

[111] The present invention provides an intraoperative probe that improves the extent of resection which is a well sought out parameter to evaluate the success of surgical resection of tumour.

[112] The present invention provides an intraoperative probe that increases the probability of attaining gross total resection, which is essential for recurrence free survival.

[113] The present invention provides an intraoperative probe that reduces damage to surrounding live tissues and functional tissues, thereby improving post-surgical quality of life.

[114] The present invention provides an intraoperative probe that addresses the issue of brain shift or plasticity of brain tissues once the dura is opened as part of craniotomy. This increases the accuracy of tumour resection.

[115] The present invention provides an intraoperative probe that can analyze one or more properties of the tissues, to create tumour margin by cross comparing the data obtained, thereby increasing reliability and cross-checking for possible disparity.

[116] The intraoperative probe of the present invention works real time basis and hence, reduces the time of surgery.

[117] The intraoperative probe of the present invention helps in intra-operative surgical planning and aid neurosurgeons to take critical decisions on resection. [118] The intraoperative probe of the present invention provides improved healthcare at reduced cost. The sensor chip, probe can be mass produced reducing cost of equipment significantly.

[119] The intraoperative probe of the present invention is portable and requires simple infrastructure requirement compared to other intra-operative tools under use.

[120] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

Claims

We Claim:

1. An intraoperative probe (100) for delineating tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin, comprising: a biochip carrier (104) that integrate sensors (102) onto the intraoperative probe, the sensors (102) detect a set of data pertaining to properties of tissues of a subject; a distal end (106) which is unidirectionally or multi-directionally steerable to have access to tissues in different orientations with respect to surgical cavity, wherein said distal end (106) is coupled to the biochip carrier (104); a handle (108) coupled with said distal end (106) for holding the intraoperative probe (100), the handle comprises buttons, knobs, and a printed circuit board (PCB) (122) in a casing of the handle (108), wherein said PCB (122) configured to process the detected data received from the sensors (102); and an interface module (200) receives the set of data from the sensors (102) through the PCB (122) using a low noise data transfer cable (112) coupled to a multichannel connector (114) or through wireless connectivity, wherein based on the received set of data, the tumour margin of the subject is delineated.

2. The intraoperative probe as claimed in claim 1, wherein the biochip carrier (104) is present on the tip, sides, or within the distal end (106) of the probe, wherein the sensors (102) comprise individual or array of electrodes, force sensors, piezoelectric -based or capacitance- based micromachined ultrasound transducers (MUTs), heating elements, temperature measurement sensors, optics, pH sensing layers and a combination thereof to perform multifunctional measurements.

3. The intraoperative probe as claimed in claim 2, wherein the electrodes of sensors (102) are made of any or a combination of metals, alloys and conducting polymers, wherein the metals are selected from a group comprising gold, platinum, titanium, silver, and a combination thereof.

4. The intraoperative probe as claimed in claim 2, wherein the sensors (102) allow the probe (100) to detect the properties of the brain tissues in contact with or in proximity to the sensor, wherein the sensors (102) detect electrical properties, mechanical properties, acoustic properties, optical properties, dielectric properties, pH properties, thermal properties and a combination thereof, wherein the electrical properties, dielectric properties, and pH properties are measured by contacting the tissue surface with electrodes, the mechanical properties are measured using indenting the tissue using the probe tip, ultrasound imaging and elastography is performed using MUTs contacting the brain surface, the optical properties and the thermal properties is measured by contact or proximity sensors.

5. The intraoperative probe as claimed in claim 1, wherein the distal end (106) is composed of an outer lumen (120) and an inner lumen (116) between which tendons or shape memory alloys (SMA) (118) is placed for actuation.

6. The intraoperative probe as claimed in claim 5, wherein the actuation mechanisms to control the probe (100) is selected from a group comprising magnetic, pneumatic, hydraulic, electrostatic, smart actuator materials (SMA), tendon based mechanical actuation and a combination thereof, wherein the probe (100) is handled manually or robotically.

7. The intraoperative probe as claimed in claim 1, wherein the interface module (200) comprises a display (202) and a control panel (204), wherein the display (202) is a graphical user interface (GUI) configured to display the processed data for straightforward interpretation, wherein an image capturing unit in the GUI maps the tissue region being sensed to its corresponding properties, and the control panel (204) is configured to calibrate the probe (100), steering of the distal end (106) and to activate/deactivate the probe (100).

8. The intraoperative probe as claimed in claim 1, wherein the electrodes for electrical characterisation is used for neural recording and stimulation, the probe (100) configured to determine neurological disorders when the properties of the affected tissues vary from normal tissues and the probe (100) determines other forms of tumours and pathologies affecting other body parts of the subject.

9. The intraoperative probe as claimed in claim 1, wherein the sensors (102) integrated onto the probe (100) is fabricated using microelectromechanical systems (MEMS), PCB fabrication, surface chemistry, nanoimprint, screen printing, lithography-based processes or a combination thereof.

10. A method (600) for delineate tumour margin based on measurements of an individual or multiple properties of brain tissues to detect tumour margin using an intraoperative probe comprising: steering (602) a distal end comprising sensors to come into contact or within close proximity of brain tissues using a handle of a probe to detect a set of data pertaining to properties of tissues of a subject, the handle comprises buttons, knobs, and a printed circuit board (PCB) in casing of the handle, wherein the PCB configured to process the detected data received from the sensor; transferring (604) the set of data from the sensors to an interface module through the PCB using a low noise data transfer cable coupled to a multichannel connector or through wireless connectivity; and delineating (606) tumour margin of the subject based on the set of data received in the interface module.