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Chen W, Brandes Z, Roy R, Chekmareva M, Pandya HJ, Desai JP, Foran DJ. Robot-Guided Atomic Force Microscopy for Mechano-Visual Phenotyping of Cancer Specimens. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2015; 21:1224-1235. [PMID: 26343283 PMCID: PMC4729564 DOI: 10.1017/s1431927615015007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Atomic force microscopy (AFM) and other forms of scanning probe microscopy have been successfully used to assess biomechanical and bioelectrical characteristics of individual cells. When extending such approaches to heterogeneous tissue, there exists the added challenge of traversing the tissue while directing the probe to the exact location of the targeted biological components under study. Such maneuvers are extremely challenging owing to the relatively small field of view, limited availability of reliable visual cues, and lack of context. In this study we designed a system that leverages the visual topology of the serial tissue sections of interest to help guide robotic control of the AFM stage to provide the requisite navigational support. The process begins by mapping the whole-slide image of a stained specimen with a well-matched, consecutive section of unstained section of tissue in a piecewise fashion. The morphological characteristics and localization of any biomarkers in the stained section can be used to position the AFM probe in the unstained tissue at regions of interest where the AFM measurements are acquired. This general approach can be utilized in various forms of microscopy for navigation assistance in tissue specimens.
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Affiliation(s)
- Wenjin Chen
- Center for Biomedical Imaging & Informatics, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08901, USA
- Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, One RWJ Place, New Brunswick, NJ 08901, USA
| | - Zachary Brandes
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, Glenn L. Martin Hall, College Park, MD 20742, USA
| | - Rajarshi Roy
- Department of Mechanical Engineering, Vanderbilt University, Room 409, 2400 Highland Avenue, Nashville, TN 37205, USA
| | - Marina Chekmareva
- Center for Biomedical Imaging & Informatics, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08901, USA
| | - Hardik J. Pandya
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, Glenn L. Martin Hall, College Park, MD 20742, USA
| | - Jaydev P. Desai
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, Glenn L. Martin Hall, College Park, MD 20742, USA
| | - David J. Foran
- Center for Biomedical Imaging & Informatics, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, 195 Little Albany Street, New Brunswick, NJ 08901, USA
- Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, One RWJ Place, New Brunswick, NJ 08901, USA
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Pandya HJ, Roy R, Chen W, Chekmareva MA, Foran DJ, Desai JP. Accurate characterization of benign and cancerous breast tissues: aspecific patient studies using piezoresistive microcantilevers. Biosens Bioelectron 2015; 63:414-424. [PMID: 25128621 PMCID: PMC4167594 DOI: 10.1016/j.bios.2014.08.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2014] [Revised: 07/05/2014] [Accepted: 08/01/2014] [Indexed: 11/30/2022]
Abstract
Breast cancer is the largest detected cancer amongst women in the US. In this work, our team reports on the development of piezoresistive microcantilevers (PMCs) to investigate their potential use in the accurate detection and characterization of benign and diseased breast tissues by performing indentations on the micro-scale tissue specimens. The PMCs used in these experiments have been fabricated using laboratory-made silicon-on-insulator (SOI) substrate, which significantly reduces the fabrication costs. The PMCs are 260 μm long, 35 μm wide and 2 μm thick with resistivity of order 1.316×10(-3) Ω cm obtained by using boron diffusion technique. For indenting the tissue, we utilized 8 μm thick cylindrical SU-8 tip. The PMC was calibrated against a known AFM probe. Breast tissue cores from seven different specimens were indented using PMC to identify benign and cancerous tissue cores. Furthermore, field emission scanning electron microscopy (FE-SEM) of benign and cancerous specimens showed marked differences in the tissue morphology, which further validates our observed experimental data with the PMCs. While these patient aspecific feasibility studies clearly demonstrate the ability to discriminate between benign and cancerous breast tissues, further investigation is necessary to perform automated mechano-phenotyping (classification) of breast cancer: from onset to disease progression.
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Affiliation(s)
- Hardik J Pandya
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA.
| | - Rajarshi Roy
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
| | - Wenjin Chen
- Center for Biomedical Imaging & Informatics, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Marina A Chekmareva
- Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ 08903, USA
| | - David J Foran
- Center for Biomedical Imaging & Informatics, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USA
| | - Jaydev P Desai
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
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Pandya HJ, Park K, Chen W, Chekmareva MA, Foran DJ, Desai JP. Simultaneous MEMS-based electro-mechanical phenotyping of breast cancer. LAB ON A CHIP 2015; 15:3695-706. [PMID: 26224116 PMCID: PMC4550491 DOI: 10.1039/c5lc00491h] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Carcinomas are the most commonly diagnosed cancers originating in the skin, lungs, breasts, pancreas, and other organs and glands. In most of the cases, the microenvironment within the tissue changes with the progression of disease. A key challenge is to develop a device capable of providing quantitative indicators in diagnosing cancer by measuring alteration in electrical and mechanical property of the tissues from the onset of malignancy. We demonstrate micro-electro-mechanical-systems (MEMS) based flexible polymer microsensor array capable of simultaneously measuring electro-mechanical properties of the breast tissues cores (1 mm in diameter and 10 μm in thickness) from onset through progression of the cancer. The electrical and mechanical signatures obtained from the tissue cores shows the capability of the device to clearly demarcate the specific stages of cancer in epithelial and stromal regions providing quantitative indicators facilitating the diagnosis of breast cancer. The present study shows that electro-mechanical properties of the breast tissue core at the micro-level are different than those at the macro-level.
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Affiliation(s)
- Hardik J Pandya
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, Maryland 20742, USA.
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Pandya HJ, Chen W, Goodell LA, Foran DJ, Desai JP. Mechanical phenotyping of breast cancer using MEMS: a method to demarcate benign and cancerous breast tissues. LAB ON A CHIP 2014; 14:4523-32. [PMID: 25267099 PMCID: PMC4224189 DOI: 10.1039/c4lc00594e] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The mechanical properties of tissue change significantly during the progression from healthy to malignant. Quantifying the mechanical properties of breast tissue within the tumor microenvironment can help to delineate benign from cancerous stages. In this work, we study high-grade invasive ductal carcinoma in comparison with their matched tumor adjacent areas, which exhibit benign morphology. Such paired tissue cores obtained from eight patients were indented using a MEMS-based piezoresistive microcantilever, which was positioned within pre-designated epithelial and stromal areas of the specimen. Field emission scanning electron microscopy studies on breast tissue cores were performed to understand the microstructural changes from benign to malignant. The normal epithelial tissues appeared compact and organized. The appearance of cancer regions, in comparison, not only revealed increased cellularity but also showed disorganization and increased fenestration. Using this technique, reliable discrimination between epithelial and stromal regions throughout both benign and cancerous breast tissue cores was obtained. The mechanical profiling generated using this method has the potential to be an objective, reproducible, and quantitative indicator for detecting and characterizing breast cancer.
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Affiliation(s)
- Hardik J Pandya
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, Maryland 20742, USA.
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Roy R, Desai JP. Determination of mechanical properties of spatially heterogeneous breast tissue specimens using contact mode atomic force microscopy (AFM). Ann Biomed Eng 2014; 42:1806-22. [PMID: 25015130 PMCID: PMC5172611 DOI: 10.1007/s10439-014-1057-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2014] [Accepted: 06/16/2014] [Indexed: 01/12/2023]
Abstract
This paper outlines a comprehensive parametric approach for quantifying mechanical properties of spatially heterogeneous thin biological specimens such as human breast tissue using contact-mode Atomic Force Microscopy. Using inverse finite element (FE) analysis of spherical nanoindentation, the force response from hyperelastic material models is compared with the predicted force response from existing analytical contact models, and a sensitivity study is carried out to assess uniqueness of the inverse FE solution. Furthermore, an automation strategy is proposed to analyze AFM force curves with varying levels of material nonlinearity with minimal user intervention. Implementation of our approach on an elastic map acquired from raster AFM indentation of breast tissue specimens indicates that a judicious combination of analytical and numerical techniques allow more accurate interpretation of AFM indentation data compared to relying on purely analytical contact models, while keeping the computational cost associated an inverse FE solution with reasonable limits. The results reported in this study have several implications in performing unsupervised data analysis on AFM indentation measurements on a wide variety of heterogeneous biomaterials.
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Affiliation(s)
- Rajarshi Roy
- Robotics, Automation, and Medical Systems (RAMS)
Laboratory, Department of Mechanical Engineering, University of Maryland, College
Park, MD, USA
- Maryland Robotics Center, Institute for Systems Research
(ISR), Department of Mechanical Engineering, University of Maryland, College Park,
MD, USA
| | - Jaydev P. Desai
- Robotics, Automation, and Medical Systems (RAMS)
Laboratory, Department of Mechanical Engineering, University of Maryland, College
Park, MD, USA
- Maryland Robotics Center, Institute for Systems Research
(ISR), Department of Mechanical Engineering, University of Maryland, College Park,
MD, USA
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Roy R, Chen W, Cong L, Goodell LA, Foran DJ, Desai JP. Probabilistic estimation of mechanical properties of biomaterials using atomic force microscopy. IEEE Trans Biomed Eng 2014; 61:547-56. [PMID: 24081838 DOI: 10.1109/tbme.2013.2283597] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Nanoindentation using contact-mode atomic force microscopy (AFM) has emerged as a powerful tool for effective material characterization of a wide variety of biomaterials across multiple length scales. However, the interpretation of force-indentation experimental data from AFM is subject to some debate. Uncertainties in AFM data analysis stems from two primary sources: The exact point of contact between the AFM probe and the biological specimen and the variability in the spring constant of the AFM probe. While a lot of attention has been directed toward addressing the contact-point uncertainty, the effect of variability in the probe spring constant has not received sufficient attention. In this paper, we report on an error-in-variables-based Bayesian change-point approach to quantify the elastic modulus of human breast tissue samples after accounting for variability in both contact point and the probe spring constant. We also discuss the efficacy of our approach to a wide range of hyperparameter values using a sensitivity analysis.
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Pandya HJ, Kim HT, Roy R, Desai JP. MEMS based Low Cost Piezoresistive Microcantilever Force Sensor and Sensor Module. MATERIALS SCIENCE IN SEMICONDUCTOR PROCESSING 2014; 19:163-173. [PMID: 24855449 PMCID: PMC4026197 DOI: 10.1016/j.mssp.2013.12.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
In the present work, we report fabrication and characterization of a low-cost MEMS based piezoresistive micro-force sensor with SU-8 tip using laboratory made silicon-on-insulator (SOI) substrate. To prepare SOI wafer, silicon film (0.8 µm thick) was deposited on an oxidized silicon wafer using RF magnetron sputtering technique. The films were deposited in Argon (Ar) ambient without external substrate heating. The material characteristics of the sputtered deposited silicon film and silicon film annealed at different temperatures (400-1050°C) were studied using atomic force microscopy (AFM) and X-ray diffraction (XRD) techniques. The residual stress of the films was measured as a function of annealing temperature. The stress of the as-deposited films was observed to be compressive and annealing the film above 1050°C resulted in a tensile stress. The stress of the film decreased gradually with increase in annealing temperature. The fabricated cantilevers were 130 µm in length, 40 µm wide and 1.0 µm thick. A series of force-displacement curves were obtained using fabricated microcantilever with commercial AFM setup and the data were analyzed to get the spring constant and the sensitivity of the fabricated microcantilever. The measured spring constant and sensitivity of the sensor was 0.1488N/m and 2.7mV/N. The microcantilever force sensor was integrated with an electronic module that detects the change in resistance of the sensor with respect to the applied force and displays it on the computer screen.
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Affiliation(s)
- H. J. Pandya
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
| | - Hyun Tae Kim
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
| | - Rajarshi Roy
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
| | - Jaydev P. Desai
- Department of Mechanical Engineering, Maryland Robotics Center, Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
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