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Serra N, Cubeddu R, Maffeis G, Damagatla V, Pifferi A, Taroni P. In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density. Sci Rep 2024; 14:19154. [PMID: 39160254 PMCID: PMC11333589 DOI: 10.1038/s41598-024-70099-x] [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] [Received: 04/24/2024] [Accepted: 08/13/2024] [Indexed: 08/21/2024] Open
Abstract
In this study, time domain diffuse optical spectroscopy is performed in the range 600-1100 nm on 11 healthy volunteers with a portable system for the quantitative characterization of breast tissue in terms of optical properties and optically-derived blood parameters, tissue constituent concentrations, and scattering parameters. A measurement protocol involving different geometries (reflectance and transmittance), subject's positions (sitting and lying down), probing locations (outer, lower, and inner breast quadrants), and source-detector distances (2 and 3 cm) allowed us to investigate the effect of tissue heterogeneity and different measurement configurations on the results with the aim of identifying the best experimental conditions for the estimate of breast density (i.e., amount of fibro-glandular tissue in the breast) as a strong independent risk factor for breast cancer. Transmittance results, that in previous studies correlated strongly with mammographic density, are used as a reference for the initial test of the simpler and more comfortable reflectance measurement configuration. The higher source-detector distance, which probes deeper tissue, retrieves optical outcomes in agreement with higher average density tissue. Similarly, results on the outer quadrants indicate higher density than internal quadrants. These findings are coherent with breast anatomy since the concentration of dense fibro-glandular stroma is higher in deep tissue and towards the external portion of the breast, where the mammary gland is located. The dataset generated with this laboratory campaign is used to device an optimal measurement protocol for a future clinical trial, where optical results will be correlated with conventional mammographic density, allowing us to identify a subset of wavelengths and measurement configurations for an effective estimate of breast density. The final objective is the design of a simplified, compact and cost-effective optical device for a non-invasive, routine assessment of density-associated breast cancer risk.
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Affiliation(s)
- Nicola Serra
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.
| | - Rinaldo Cubeddu
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - Giulia Maffeis
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - Vamshi Damagatla
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - Antonio Pifferi
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - Paola Taroni
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
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2
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Zhou X, Xia Y, Uchitel J, Collins-Jones L, Yang S, Loureiro R, Cooper RJ, Zhao H. Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]. BIOMEDICAL OPTICS EXPRESS 2023; 14:3234-3258. [PMID: 37497520 PMCID: PMC10368025 DOI: 10.1364/boe.484044] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/29/2023] [Accepted: 05/25/2023] [Indexed: 07/28/2023]
Abstract
Over the past several decades, near-infrared spectroscopy (NIRS) has become a popular research and clinical tool for non-invasively measuring the oxygenation of biological tissues, with particular emphasis on applications to the human brain. In most cases, NIRS studies are performed using continuous-wave NIRS (CW-NIRS), which can only provide information on relative changes in chromophore concentrations, such as oxygenated and deoxygenated hemoglobin, as well as estimates of tissue oxygen saturation. Another type of NIRS known as frequency-domain NIRS (FD-NIRS) has significant advantages: it can directly measure optical pathlength and thus quantify the scattering and absorption coefficients of sampled tissues and provide direct measurements of absolute chromophore concentrations. This review describes the current status of FD-NIRS technologies, their performance, their advantages, and their limitations as compared to other NIRS methods. Significant landmarks of technological progress include the development of both benchtop and portable/wearable FD-NIRS technologies, sensitive front-end photonic components, and high-frequency phase measurements. Clinical applications of FD-NIRS technologies are discussed to provide context on current applications and needed areas of improvement. The review concludes by providing a roadmap toward the next generation of fully wearable, low-cost FD-NIRS systems.
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Affiliation(s)
- Xinkai Zhou
- HUB of Intelligent Neuro-engineering (HUBIN), Aspire CREATe, IOMS, Division of Surgery and Interventional Science, University College London (UCL), London, HA7 4LP, UK
| | - Yunjia Xia
- HUB of Intelligent Neuro-engineering (HUBIN), Aspire CREATe, IOMS, Division of Surgery and Interventional Science, University College London (UCL), London, HA7 4LP, UK
- DOT-HUB, Department of Medical Physics & Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Julie Uchitel
- Department of Paediatrics, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Liam Collins-Jones
- DOT-HUB, Department of Medical Physics & Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Shufan Yang
- HUB of Intelligent Neuro-engineering (HUBIN), Aspire CREATe, IOMS, Division of Surgery and Interventional Science, University College London (UCL), London, HA7 4LP, UK
- School of Computing, Engineering & Build Environment, Edinburgh Napier University, Edinburgh, UK
| | - Rui Loureiro
- Aspire CREATe, Department of Orthopaedics & Musculoskeletal Science, UCL, London, HA7 4LP, UK
| | - Robert J. Cooper
- DOT-HUB, Department of Medical Physics & Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Hubin Zhao
- HUB of Intelligent Neuro-engineering (HUBIN), Aspire CREATe, IOMS, Division of Surgery and Interventional Science, University College London (UCL), London, HA7 4LP, UK
- DOT-HUB, Department of Medical Physics & Biomedical Engineering, UCL, London, WC1E 6BT, UK
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3
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Feng J, Zhang W, Li Z, Jia K, Jiang S, Dehghani H, Pogue BW, Paulsen KD. Deep-learning based image reconstruction for MRI-guided near-infrared spectral tomography. OPTICA 2022; 9:264-267. [PMID: 35340570 PMCID: PMC8952193 DOI: 10.1364/optica.446576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/12/2022] [Indexed: 05/02/2023]
Abstract
Non-invasive near-infrared spectral tomography (NIRST) can incorporate the structural information provided by simultaneous magnetic resonance imaging (MRI), and this has significantly improved the images obtained of tissue function. However, the process of MRI guidance in NIRST has been time consuming because of the needs for tissue-type segmentation and forward diffuse modeling of light propagation. To overcome these problems, a reconstruction algorithm for MRI-guided NIRST based on deep learning is proposed and validated by simulation and real patient imaging data for breast cancer characterization. In this approach, diffused optical signals and MRI images were both used as the input to the neural network, and simultaneously recovered the concentrations of oxy-hemoglobin, deoxy-hemoglobin, and water via end-to-end training by using 20,000 sets of computer-generated simulation phantoms. The simulation phantom studies showed that the quality of the reconstructed images was improved, compared to that obtained by other existing reconstruction methods. Reconstructed patient images show that the well-trained neural network with only simulation data sets can be directly used for differentiating malignant from benign breast tumors.
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Affiliation(s)
- Jinchao Feng
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Wanlong Zhang
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Zhe Li
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Kebin Jia
- Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
| | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA
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4
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Wang Y, Li S, Wang Y, Yan Q, Wang X, Shen Y, Li Z, Kang F, Cao X, Zhu S. Compact fiber-free parallel-plane multi-wavelength diffuse optical tomography system for breast imaging. OPTICS EXPRESS 2022; 30:6469-6486. [PMID: 35299431 DOI: 10.1364/oe.448874] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/05/2022] [Indexed: 06/14/2023]
Abstract
To facilitate the clinical applicability of the diffuse optical inspection device, a compact multi-wavelength diffuse optical tomography system for breast imaging (compact-DOTB) with a fiber-free parallel-plane structure was designed and fabricated for acquiring three-dimensional optical properties of the breast in continuous-wave mode. The source array consists of 56 surface-mounted micro light-emitting diodes (LEDs), each integrating three wavelengths (660, 750, and 840 nm). The detector array is arranged with 56 miniaturized surface-mounted optical sensors, each encapsulating a high-sensitivity photodiode (PD) and a low-noise current amplifier with a gain of 24×. The system provides 3,136 pairs of source-detector measurements at each wavelength, and the fiber-free design largely ensures consistency between source/detection channels while effectively reducing the complexity of system operation and maintenance. We have evaluated the compact-DOTB system's characteristics and demonstrated its performance in terms of reconstruction positioning accuracy and recovery contrast with breast-sized phantom experiments. Furthermore, the breast cancer patient studies have been carried out, and the quantitative results indicate that the compact-DOTB system is able to observe the changes in the functional tissue components of the breast after receiving the neoadjuvant chemotherapy (NAC), demonstrating the great potential of the proposed compact system for clinical applications, while its cost and ease of operation are competitive with the existing breast-DOT devices.
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5
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Development of digital breast tomosynthesis and diffuse optical tomography fusion imaging for breast cancer detection. Sci Rep 2020; 10:13127. [PMID: 32753578 PMCID: PMC7403423 DOI: 10.1038/s41598-020-70103-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 07/20/2020] [Indexed: 02/06/2023] Open
Abstract
Diffuse optical tomography (DOT) non-invasively measures the functional characteristics of breast lesions using near infrared light to probe tissue optical properties. This study aimed to evaluate a new digital breast tomosynthesis (DBT)/DOT fusion imaging technique and obtain preliminary data for breast cancer detection. Twenty-eight women were prospectively enrolled and underwent both DBT and DOT examinations. DBT/DOT fusion imaging was created after acquisition of both examinations. Two breast radiologists analyzed DBT and DOT images independently, and then finally evaluated the fusion images. The diagnostic performance of each reading session was compared and interobserver agreement was assessed. The technical success rate was 96.4%, with one failure due to an error during DOT data storage. Among the 27 women finally included in the analysis, 13 had breast cancer. The areas under the receiver operating characteristic curve (AUCs) for DBT were 0.783 and 0.854 for readers 1 and 2, respectively. DOT showed comparable diagnostic performance to DBT for both readers. The AUCs were significantly improved (P = 0.004) when the DBT/DOT fusion images were used. Interobserver agreements were highest for the DBT/DOT fusion images. In conclusion, this study suggests that DBT/DOT fusion imaging technique appears to be a promising tool for breast cancer diagnosis.
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6
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A review of optical breast imaging: Multi-modality systems for breast cancer diagnosis. Eur J Radiol 2020; 129:109067. [PMID: 32497943 DOI: 10.1016/j.ejrad.2020.109067] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 05/04/2020] [Accepted: 05/09/2020] [Indexed: 11/24/2022]
Abstract
This review of optical breast imaging describes basic physical and system principles and summarizes technological evolution with a focus on multi-modality platforms and recent clinical trial results. Ultrasound-guided diffuse optical tomography and co-registered ultrasound and photoacoustic imaging systems are emphasized as models of state of the art optical technology that are most conducive to clinical translation.
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7
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Cochran JM, Busch DR, Lin L, Minkoff DL, Schweiger M, Arridge S, Yodh AG. Hybrid time-domain and continuous-wave diffuse optical tomography instrument with concurrent, clinical magnetic resonance imaging for breast cancer imaging. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-11. [PMID: 30680976 PMCID: PMC6345326 DOI: 10.1117/1.jbo.24.5.051409] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 12/10/2018] [Indexed: 05/10/2023]
Abstract
Diffuse optical tomography has demonstrated significant potential for clinical utility in the diagnosis and prognosis of breast cancer, and its use in combination with other structural imaging modalities improves lesion localization and the quantification of functional tissue properties. Here, we introduce a hybrid diffuse optical imaging system that operates concurrently with magnetic resonance imaging (MRI) in the imaging suite, utilizing commercially available MR surface coils. The instrument acquires both continuous-wave and time-domain diffuse optical data in the parallel-plate geometry, permitting both absolute assignment of tissue optical properties and three-dimensional tomography; moreover, the instrument is designed to incorporate diffuse correlation spectroscopic measurements for probing tissue blood flow. The instrument is described in detail here. Image reconstructions of a tissue phantom are presented as an initial indicator of the system's ability to accurately reconstruct optical properties and the concrete benefits of the spatial constraints provided by concurrent MRI. Last, we briefly discuss how various data combinations that the instrument could facilitate, including tissue perfusion, can enable more comprehensive assessment of lesion physiology.
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Affiliation(s)
- Jeffrey M. Cochran
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
- Address all correspondence to Jeffrey M. Cochran, E-mail:
| | - David R. Busch
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
- University of Texas Southwestern Medical Center, Department of Anesthesiology and Pain Management, Dallas, Texas, United States
- University of Texas Southwestern Medical Center, Department of Neurology and Neurotherapeutics, Dallas, Texas, United States
- Children’s Hospital of Philadelphia, Department of Neurology, Philadelphia, Pennsylvania, United States
| | - Li Lin
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
- California Institute of Technology, Department of Medical Engineering, Pasadena, California, United States
| | - David L. Minkoff
- Emory University, Department of Medicine, Atlanta, Georgia, United States
| | - Martin Schweiger
- University College London, Centre for Medical Image Computing, London, United Kigdom
| | - Simon Arridge
- University College London, Centre for Medical Image Computing, London, United Kigdom
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
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8
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Vavadi H, Mostafa A, Zhou F, Uddin KMS, Althobaiti M, Xu C, Bansal R, Ademuyiwa F, Poplack S, Zhu Q. Compact ultrasound-guided diffuse optical tomography system for breast cancer imaging. JOURNAL OF BIOMEDICAL OPTICS 2018; 24:1-9. [PMID: 30350491 PMCID: PMC6197842 DOI: 10.1117/1.jbo.24.2.021203] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 09/19/2018] [Indexed: 05/02/2023]
Abstract
Near-infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response in patients with locally advanced breast cancers. The path toward commercialization of DOT techniques depends upon the improvement of robustness and user-friendliness of this technique in hardware and software. In this study, we introduce our recently developed ultrasound-guided DOT system, which has been improved in system compactness, robustness, and user-friendliness by custom-designed electronics, automated data preprocessing, and implementation of a new two-step reconstruction algorithm. The system performance has been tested with several sets of solid and blood phantoms and the results show accuracy in reconstructed absorption coefficients as well as blood oxygen saturation. A clinical example of a breast cancer patient, who was undergoing neoadjuvant chemotherapy, is given to demonstrate the system performance.
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Affiliation(s)
- Hamed Vavadi
- University of Connecticut, BME and ECE Departments, Connecticut, United States
| | - Atahar Mostafa
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
| | - Feifei Zhou
- University of Connecticut, BME and ECE Departments, Connecticut, United States
| | - K. M. Shihab Uddin
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
| | - Murad Althobaiti
- University of Connecticut, BME and ECE Departments, Connecticut, United States
| | - Chen Xu
- New York City College of Technology, Brooklyn, New York, United States
| | - Rajeev Bansal
- University of Connecticut, BME and ECE Departments, Connecticut, United States
| | - Foluso Ademuyiwa
- Washington University School of Medicine, Department of Medical Oncology, St. Louis, Missouri, United States
| | - Steven Poplack
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Quing Zhu
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
- Address all correspondence to: Quing Zhu, E-mail:
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9
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Zhang L, Jiang S, Zhao Y, Feng J, Pogue BW, Paulsen KD. Direct Regularization From Co-Registered Contrast MRI Improves Image Quality of MRI-Guided Near-Infrared Spectral Tomography of Breast Lesions. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:1247-1252. [PMID: 29727287 PMCID: PMC5987778 DOI: 10.1109/tmi.2018.2794548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
An approach using direct regularization from co-registered dynamic contrast enhanced magnetic reson- ance images was used to reconstruct near-infrared spectral tomography patient images, which does not need image segmentation. 20 patients with mammography/ultrasound confirmed breast abnormalities were involved in this paper, and the resulting images indicated that tumor total hemoglobin concentration contrast differentiated malignant from benign cases (p-value = 0.021). The approach prod- uced reconstructed images, which significantly reduced surface artifacts near the source-detector locations (p-value = 4.16e-6).
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10
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Zhao Y, Burger WR, Zhou M, Bernhardt EB, Kaufman PA, Patel RR, Angeles CV, Pogue BW, Paulsen KD, Jiang S. Collagen quantification in breast tissue using a 12-wavelength near infrared spectral tomography (NIRST) system. BIOMEDICAL OPTICS EXPRESS 2017; 8:4217-4229. [PMID: 28966860 PMCID: PMC5611936 DOI: 10.1364/boe.8.004217] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 08/22/2017] [Accepted: 08/22/2017] [Indexed: 05/20/2023]
Abstract
A portable near infrared spectral tomography (NIRST) system was adapted for breast cancer detection and treatment monitoring with improved speed of acquisition for parallel 12 wavelengths of parallel frequency-domain (FD) and continuous-wavelength (CW) measurement. Using a novel gain adjustment scheme in the Photomultiplier Tube detectors (PMTs), the data acquisition time for simultaneous acquisition involving three FD and three CW wavelengths, has been reduced from 90 to 55 seconds, while signal variation was also reduced from 2.1% to 1.1%. Tomographic images of breast collagen content have been recovered for the first time, and image reconstruction approaches with and without collagen content included have been validated in simulation studies and normal subject exams. Simulations indicate that including collagen content into the reconstruction procedure can significantly reduce the overestimation in total hemoglobin, water and lipid by 8.9μM, 1.8% and 15.8%, respectively, and underestimates in oxygen saturation by 9.5%, given an average 10% background collagen content. A breast cancer patient with invasive ductal carcinoma was imaged and the reconstructed images show that the recovered tumor/background contrast in total hemoglobin increased from 1.5 to 1.7 when collagen was included in reconstruction.
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Affiliation(s)
- Yan Zhao
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - William R. Burger
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Mingwei Zhou
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Erica B. Bernhardt
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
| | - Peter A. Kaufman
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
- Department of Medicine, Geisel School of Medicine, Dartmouth College, Hanover NH 03755, USA
| | - Roshani R. Patel
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
| | - Christina V. Angeles
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
| | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
- Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon NH 03756, USA
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11
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RUIZ JESSICA, NOUIZI FAROUK, CHO JAEDU, ZHENG JIE, LI YIFAN, CHEN JEONHOR, SU MINYING, GULSEN GULTEKIN. Breast density quantification using structured-light-based diffuse optical tomography simulations. APPLIED OPTICS 2017; 56:7146-7157. [PMID: 29047975 PMCID: PMC6691974 DOI: 10.1364/ao.56.007146] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 07/26/2017] [Indexed: 05/08/2023]
Abstract
We present the feasibility of structured-light-based diffuse optical tomography (DOT) to quantify the breast density with an extensive simulation study. This study is performed on multiple numerical breast phantoms built from magnetic resonance imaging (MRI) images. These phantoms represent realistic tissue morphologies and are given typical breast optical properties. First, synthetic data are simulated at five wavelengths using our structured-light-based DOT forward problem. Afterwards, the inverse problem is solved to obtain the absorption images and subsequently the chromophore concentration maps. Parameters, such as segmented volumes and mean concentrations, are extracted from these maps and used in a regression model to estimate the percent breast densities. These estimations are correlated with the true values from MRI, r=0.97, showing that our new technique is promising in measuring breast density.
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Affiliation(s)
- JESSICA RUIZ
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - FAROUK NOUIZI
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - JAEDU CHO
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - JIE ZHENG
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - YIFAN LI
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - JEON-HOR CHEN
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
- E-Da Hospital and I-Shou University, Kaohsiung, Taiwan
| | - MIN-YING SU
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
| | - GULTEKIN GULSEN
- Tu & Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697, USA
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12
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Zimmermann BB, Deng B, Singh B, Martino M, Selb J, Fang Q, Sajjadi AY, Cormier J, Moore RH, Kopans DB, Boas DA, Saksena MA, Carp SA. Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:46008. [PMID: 28447102 PMCID: PMC5406652 DOI: 10.1117/1.jbo.22.4.046008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 04/07/2017] [Indexed: 05/02/2023]
Abstract
Diffuse optical tomography (DOT) is emerging as a noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (up to 1 Hz) image acquisition rate to enable tracking hemodynamic changes induced by the mammographic breast compression. The system integrates 96 continuous-wave and 24 frequency-domain source locations as well as 32 continuous wave and 20 frequency-domain detection locations into low-profile plastic plates that can easily mate to the DBT compression paddle and x-ray detector cover, respectively. We demonstrate system performance using static and dynamic tissue-like phantoms as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division.
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Affiliation(s)
- Bernhard B. Zimmermann
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Cambridge, Massachusetts, United States
| | - Bin Deng
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
| | - Bhawana Singh
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
| | - Mark Martino
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Juliette Selb
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Amir Y. Sajjadi
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
| | - Jayne Cormier
- Massachusetts General Hospital, Breast Imaging Division, Department of Radiology, Boston, Massachusetts, United States
| | - Richard H. Moore
- Massachusetts General Hospital, Breast Imaging Division, Department of Radiology, Boston, Massachusetts, United States
| | - Daniel B. Kopans
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
- Massachusetts General Hospital, Breast Imaging Division, Department of Radiology, Boston, Massachusetts, United States
| | - David A. Boas
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
| | - Mansi A. Saksena
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
- Massachusetts General Hospital, Breast Imaging Division, Department of Radiology, Boston, Massachusetts, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Harvard Medical School, Department of Radiology, Boston, Massachusetts, United States
- Address all correspondence to: Stefan A. Carp, E-mail:
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13
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Jiang S, Pogue BW. A Comparison of Near-Infrared Diffuse Optical Imaging and 18F-FDG PET/CT for the Early Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy. J Nucl Med 2016; 57:1166-7. [DOI: 10.2967/jnumed.116.174367] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 03/18/2016] [Indexed: 11/16/2022] Open
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14
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Zhao Y, Pogue BW, Haider SJ, Gui J, diFlorio-Alexander RM, Paulsen KD, Jiang S. Portable, parallel 9-wavelength near-infrared spectral tomography (NIRST) system for efficient characterization of breast cancer within the clinical oncology infusion suite. BIOMEDICAL OPTICS EXPRESS 2016; 7:2186-201. [PMID: 27375937 PMCID: PMC4918575 DOI: 10.1364/boe.7.002186] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Revised: 05/05/2016] [Accepted: 05/10/2016] [Indexed: 05/09/2023]
Abstract
A portable near-infrared spectral tomography (NIRST) system was developed with simultaneous frequency domain (FD) and continuous-wave (CW) optical measurements for efficient characterization of breast cancer in a clinical oncology setting. Simultaneous FD and CW recordings were implemented to speed up acquisition to 3 minutes for all 9 wavelengths, spanning a range from 661nm to 1064nm. An adjustable interface was designed to fit various breast sizes and shapes. Spatial images of oxy- and deoxy-hemoglobin, water, lipid, and scattering components were reconstructed using a 2D FEM approach. The system was tested on a group of 10 normal subjects, who were examined bilaterally and the recovered optical images were compared to radiographic breast density. Significantly higher total hemoglobin and water were estimated in the high density relative to low density groups. One patient with invasive ductal carcinoma was also examined and the cancer region was characterized as having a contrast ratio of 1.4 in total hemoglobin and 1.2 in water.
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Affiliation(s)
- Yan Zhao
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Steffen J. Haider
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Jiang Gui
- Department of Radiology, Dartmouth Hitchcock Medical Center, Lebanon, NH 03756, USA
| | | | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
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Zimmermann BB, Fang Q, Boas DA, Carp SA. Frequency domain near-infrared multiwavelength imager design using high-speed, direct analog-to-digital conversion. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:16010. [PMID: 26813081 PMCID: PMC4726736 DOI: 10.1117/1.jbo.21.1.016010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2015] [Accepted: 12/14/2015] [Indexed: 05/18/2023]
Abstract
Frequency domain near-infrared spectroscopy (FD-NIRS) has proven to be a reliable method for quantification of tissue absolute optical properties. We present a full-sampling direct analog-to-digital conversion FD-NIR imager. While we developed this instrument with a focus on high-speed optical breast tomographic imaging, the proposed design is suitable for a wide-range of biophotonic applications where fast, accurate quantification of absolute optical properties is needed. Simultaneous dual wavelength operation at 685 and 830 nm is achieved by concurrent 67.5 and 75 MHz frequency modulation of each laser source, respectively, followed by digitization using a high-speed (180 MS/s) 16-bit A/D converter and hybrid FPGA-assisted demodulation. The instrument supports 25 source locations and features 20 concurrently operating detectors. The noise floor of the instrument was measured at <1.4 pW/√Hz, and a dynamic range of 115+ dB, corresponding to nearly six orders of magnitude, has been demonstrated. Titration experiments consisting of 200 different absorption and scattering values were conducted to demonstrate accurate optical property quantification over the entire range of physiologically expected values.
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Affiliation(s)
- Bernhard B. Zimmermann
- Harvard Medical School, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Charlestown, Massachusetts 02129, United States
- Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - David A. Boas
- Harvard Medical School, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Charlestown, Massachusetts 02129, United States
| | - Stefan A. Carp
- Harvard Medical School, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Charlestown, Massachusetts 02129, United States
- Address all correspondence to: Stefan A. Carp, E-mail:
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16
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Nouizi F, Luk A, Thayer D, Lin Y, Ha S, Gulsen G. Experimental validation of a high-resolution diffuse optical imaging modality: photomagnetic imaging. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:16009. [PMID: 26790644 PMCID: PMC4719037 DOI: 10.1117/1.jbo.21.1.016009] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 12/11/2015] [Indexed: 05/25/2023]
Abstract
We present experimental results that validate our imaging technique termed photomagnetic imaging (PMI). PMI illuminates the medium under investigation with a near-infrared light and measures the induced temperature increase using magnetic resonance imaging. A multiphysics solver combining light and heat propagation is used to model spatiotemporal distribution of temperature increase. Furthermore, a dedicated PMI reconstruction algorithm has been developed to reveal high-resolution optical absorption maps from temperature measurements. Being able to perform measurements at any point within the medium, PMI overcomes the limitations of conventional diffuse optical imaging. We present experimental results obtained on agarose phantoms mimicking biological tissue with inclusions having either different sizes or absorption contrasts, located at various depths. The reconstructed images show that PMI can successfully resolve these inclusions with high resolution and recover their absorption coefficient with high-quantitative accuracy. Even a 1-mm inclusion located 6-mm deep is recovered successfully and its absorption coefficient is underestimated by only 32%. The improved PMI system presented here successfully operates under the maximum skin exposure limits defined by the American National Standards Institute, which opens up the exciting possibility of its future clinical use for diagnostic purposes.
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Affiliation(s)
- Farouk Nouizi
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
| | - Alex Luk
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
| | - Dave Thayer
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, 510 South Kingshighway Boulevard, St. Louis, Missouri 63110, United States
| | - Yuting Lin
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
- Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, 55 Fruit Street, Boston, Massachusetts 02144, United States
| | - Seunghoon Ha
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
- Philips Healthcare, N27 West 23676 Paul Road, Pewaukee, Wisconsin 53072, United States
| | - Gultekin Gulsen
- University of California, Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, 164 Irvine Hall, Irvine, California, United States
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17
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Zhang L, Zhao Y, Jiang S, Pogue BW, Paulsen KD. Direct regularization from co-registered anatomical images for MRI-guided near-infrared spectral tomographic image reconstruction. BIOMEDICAL OPTICS EXPRESS 2015; 6:3618-30. [PMID: 26417528 PMCID: PMC4574684 DOI: 10.1364/boe.6.003618] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Revised: 07/16/2015] [Accepted: 08/17/2015] [Indexed: 05/18/2023]
Abstract
Combining anatomical information from high resolution imaging modalities to guide near-infrared spectral tomography (NIRST) is an efficient strategy for improving the quality of the reconstructed spectral images. A new approach for incorporating image information directly into the inversion matrix regularization was examined using Direct Regularization from Images (DRI), which encodes the gray-scale data into the NIRST image reconstruction problem. This process has the benefit of eliminating user intervention such as image segmentation of distinct regions. Specifically, the Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) image intensity value differences within the anatomical image were used to implement an exponentially-weighted regularization function between the image pixels. The algorithm was validated using simulated reconstructions with noise, and the results showed that spatial resolution and robustness of the reconstructed images were significantly improved by appropriate choice of the regularization weight parameters. The proposed approach was also tested on in vivo breast data acquired in a recent clinical trial combining NIRST / MRI for cancer tumor characterization. Relative to the standard "no priors" diffuse recovery, the contrast of the tumor to the normal surrounding tissue increased from 2.4 to 3.6, and the difference between the tumor size segmented from DCE-MR images and reconstructed optical images decreased from 18% to 6%, while there was an overall decrease in surface artifacts.
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Affiliation(s)
- Limin Zhang
- Thayer School of Engineering, Dartmouth College, Hanover NH 03755, USA
- College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key Laboratory of Biomedical Detecting Techniques and Instrument, Tianjin 300072, China
| | - Yan Zhao
- Thayer School of Engineering, Dartmouth College, Hanover NH 03755, USA
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover NH 03755, USA
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, Hanover NH 03755, USA
| | - Keith D. Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover NH 03755, USA
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18
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Mastanduno MA, Xu J, El-Ghussein F, Jiang S, Yin H, Zhao Y, Wang K, Ren F, Gui J, Pogue BW, Paulsen KD. MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI. Clin Cancer Res 2015; 21:3906-12. [PMID: 26019171 DOI: 10.1158/1078-0432.ccr-14-2546] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 05/11/2015] [Indexed: 11/16/2022]
Abstract
PURPOSE The purpose of this study was to determine the diagnostically most important molecular biomarkers quantified by magnetic resonance-guided (MR) near-infrared spectral tomography (NIRST) that distinguish malignant breast lesions from benign abnormalities when combined with outcomes from clinical breast MRI. EXPERIMENTAL DESIGN The study was HIPAA compliant and approved by the Dartmouth Institutional Review Board, the NIH, the United States State Department, and Xijing Hospital. MR-guided NIRST evaluated hemoglobin, water, and lipid content in regions of interest defined by concurrent dynamic contrast-enhanced MRI (DCE-MRI) in the breast. MRI plus NIRST was performed in 44 subjects (median age, 46, age range, 20-81 years), 28 of whom had subsequent malignant pathologic diagnoses, and 16 had benign conditions. A subset of 30 subject examinations yielded optical data that met minimum sensitivity requirements to the suspicious lesion and were included in the analyses of diagnostic performance. RESULTS In the subset of 30 subject examinations meeting minimum optical data sensitivity criterion, the MR-guided NIRST separated malignant from benign lesions using total hemoglobin (HbT; P < 0.01) and tissue optical index (TOI; P < 0.001). Combined MRI plus TOI data caused one false positive and 1 false negative, and produced the best diagnostic performance, yielding an AUC of 0.95, sensitivity of 95%, specificity of 89%, positive predictive value of 95%, and negative predictive value of 89%, respectively. CONCLUSIONS MRI plus NIRST results correlated well with histopathologic diagnoses and could provide additional information to reduce the number of MRI-directed biopsies.
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Affiliation(s)
| | - Junqing Xu
- Department of Radiology, Xijing Hospital, Xi'an, China
| | - Fadi El-Ghussein
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Xi'an, China.
| | - Yan Zhao
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Ke Wang
- Department of Radiology, Xijing Hospital, Xi'an, China
| | - Fang Ren
- Department of Radiology, Xijing Hospital, Xi'an, China
| | - Jiang Gui
- Department of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire
| | - Brian W Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Keith D Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire. Department of Diagnostic Radiology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire.
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19
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Zhao Y, Mastanduno MA, Jiang S, EI-Ghussein F, Gui J, Pogue BW, Paulsen KD. Optimization of image reconstruction for magnetic resonance imaging-guided near-infrared diffuse optical spectroscopy in breast. JOURNAL OF BIOMEDICAL OPTICS 2015; 20:56009. [PMID: 26000795 PMCID: PMC4572095 DOI: 10.1117/1.jbo.20.5.056009] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Accepted: 04/28/2015] [Indexed: 05/18/2023]
Abstract
An optimized approach to nonlinear iterative reconstruction of magnetic resonance imaging (MRI)-guided near-infrared spectral tomography (NIRST) images was developed using an L-curve-based algorithm for the choice of regularization parameter. This approach was applied to clinical exam data to maximize the reconstructed values differentiating malignant and benign lesions. MRI/NIRST data from 25 patients with abnormal breast readings (BI-RADS category 4-5) were analyzed using this optimal regularization methodology, and the results showed enhanced p values and area under the curve (AUC) for the task of differentiating malignant from benign lesions. Of the four absorption parameters and two scatter parameters, the most significant differences for benign versus malignant were total hemoglobin (HbT) and tissue optical index (TOI) with p values = 0.01 and 0.001, and AUC values = 0.79 and 0.94, respectively, in terms of HbT and TOI. This dramatically improved the values relative to fixed regularization (p value = 0.02 and 0.003; AUC = 0.75 and 0.83) showing that more differentiation was possible with the optimal method. Through a combination of both biomarkers, HbT and TOI, the AUC increased from 82.9% (fixed regulation = 0.1) to 94.3% (optimal method).
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Affiliation(s)
- Yan Zhao
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
- Address all correspondence to: Yan Zhao, E-mail:
| | - Michael A. Mastanduno
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Shudong Jiang
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Fadi EI-Ghussein
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Jiang Gui
- Dartmouth College, Geisel School of Medicine, Department of Community and Family Medicine, Hanover, New Hampshire 03755, United States
| | - Brian W. Pogue
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Keith D. Paulsen
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
- Dartmouth College, Geisel School of Medicine, Department of Community and Family Medicine, Hanover, New Hampshire 03755, United States
- Dartmouth College, Geisel School of Medicine, Department of Diagnostic Radiology, Hanover, NH03755, United States
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20
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Wang J, Lin D, Lin J, Yu Y, Huang Z, Chen Y, Lin J, Feng S, Li B, Liu N, Chen R. Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening. JOURNAL OF BIOMEDICAL OPTICS 2014; 19:087003. [PMID: 25138208 DOI: 10.1117/1.jbo.19.8.087003] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2014] [Accepted: 07/28/2014] [Indexed: 05/18/2023]
Abstract
Surface-enhanced Raman scattering (SERS) spectra of serum proteins purified from human serum samples were employed to detect colorectal cancer. Acetic acid as a new aggregating agent was introduced to increase the magnitude of the SERS enhancement. High-quality SERS spectra of serum proteins were acquired from 103 cancer patients and 103 healthy volunteers. Tentative assignments of SERS bands reflect that some specific biomolecular contents and protein secondary structures change with colorectal cancer progression. Principal component analysis combined with linear discriminant analysis was used to assess the capability of this approach for identifying colorectal cancer, yielding diagnostic accuracies of 100% (sensitivity: 100%; specificity: 100%) based on albumin SERS spectroscopy and 99.5% (sensitivity: 100%; specificity: 99%) based on globulin SERS spectroscopy, respectively. A partial least squares (PLS) approach was introduced to develop diagnostic models. An albumin PLS model successfully predicted the unidentified subjects with a diagnostic accuracy of 93.5% (sensitivity: 95.6%; specificity: 91.3%) and the globulin PLS model gave a diagnostic accuracy of 93.5% (sensitivity: 91.3%; specificity: 95.6%). These results suggest that serum protein SERS spectroscopy can be a sensitive and clinically powerful means for colorectal cancer detection.
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Affiliation(s)
- Jing Wang
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Duo Lin
- Fujian University of Traditional Chinese Medicine, College of Integrated Traditional Chinese and Western Medicine, Fuzhou 350122, China
| | - Juqiang Lin
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Yun Yu
- Fujian University of Traditional Chinese Medicine, College of Integrated Traditional Chinese and Western Medicine, Fuzhou 350122, China
| | - Zufang Huang
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Yanping Chen
- Teaching Hospital of Fujian Medical University, Fujian Provincial Cancer Hospital, Fuzhou 350014, China
| | - Jinyong Lin
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Shangyuan Feng
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Buhong Li
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Nenrong Liu
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
| | - Rong Chen
- Fujian Normal University, Ministry of Education and Fujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine, Fuzhou 350007, China
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Mastanduno MA, El-Ghussein F, Jiang S, Diflorio-Alexander R, Junqing X, Hong Y, Pogue BW, Paulsen KD. Adaptable near-infrared spectroscopy fiber array for improved coupling to different breast sizes during clinical MRI. Acad Radiol 2014; 21:141-50. [PMID: 24439327 DOI: 10.1016/j.acra.2013.09.025] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2013] [Revised: 09/11/2013] [Accepted: 09/12/2013] [Indexed: 11/19/2022]
Abstract
RATIONALE AND OBJECTIVES Near-infrared spectroscopy (NIRS) of breast can provide functional information on the vascular and structural compartments of tissues in regions identified during simultaneous magnetic resonance imaging (MRI). NIRS can be acquired during dynamic contrast-enhanced MRI (DCE-MRI) to accomplish image-guided spectroscopy of the enhancing regions, potentially increasing the diagnostic specificity of the examination and reducing the number of biopsies performed as a result of inconclusive MRI breast imaging studies. MATERIALS AND METHODS We combine synergistic attributes of concurrent DCE-MRI and NIRS with a new design of the clinical NIRS breast interface that couples to a standard MR breast coil and allows imaging of variable breast sizes. Spectral information from healthy volunteers and cancer patients is recovered, providing molecular information in regions defined by the segmented MR image volume. RESULTS The new coupling system significantly improves examination utility by allowing improved coupling of the NIR fibers to breasts of all cup sizes and lesion locations. This improvement is demonstrated over a range of breast sizes (cup size A through D) and normal tissue heterogeneity using a group of eight healthy volunteers and two cancer patients. Lesions located in the axillary region and medial-posterior breast are now accessible to NIRS optodes. Reconstructed images were found to have biologically plausible hemoglobin content, oxygen saturation, and water and lipid fractions. CONCLUSIONS In summary, a new NIRS/MRI breast interface was developed to accommodate the variation in breast sizes and lesion locations that can be expected in clinical practice. DCE-MRI-guided NIRS quantifies total hemoglobin, oxygenation, and scattering in MR-enhancing regions, increasing the diagnostic information acquired from MR examinations.
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Affiliation(s)
- Michael A Mastanduno
- Thayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH 03755.
| | - Fadi El-Ghussein
- Thayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH 03755
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH 03755
| | | | - Xu Junqing
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shannxi, China
| | - Yin Hong
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shannxi, China
| | - Brian W Pogue
- Thayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH 03755
| | - Keith D Paulsen
- Thayer School of Engineering, Dartmouth College, 14 Engineering Dr., Hanover, NH 03755; Department of Diagnostic Radiology, Dartmouth Medical School, Lebanon, NH
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El-Ghussein F, Jiang S, Pogue BW, Paulsen KD. Comparison of magnetic resonance imaging-compatible optical detectors for in-magnet tissue spectroscopy: photodiodes versus silicon photomultipliers. JOURNAL OF BIOMEDICAL OPTICS 2014; 19:070502. [PMID: 25006986 PMCID: PMC4160972 DOI: 10.1117/1.jbo.19.7.070502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2014] [Revised: 06/12/2014] [Accepted: 06/16/2014] [Indexed: 06/03/2023]
Abstract
Tissue spectroscopy inside the magnetic resonance imaging (MRI) system adds a significant value by measuring fast vascular hemoglobin responses or completing spectroscopic identification of diagnostically relevant molecules. Advances in this type of spectroscopy instrumentation have largely focused on fiber coupling into and out of the MRI; however, nonmagnetic detectors can now be placed inside the scanner with signal amplification performed remotely to the high field environment for optimized light detection. In this study, the two possible detector options, such as silicon photodiodes (PD) and silicon photomultipliers (SiPM), were systematically examined for dynamic range and wavelength performance. Results show that PDs offer 10⁸(160 dB) dynamic range with sensitivity down to 1 pW, whereas SiPMs have 10⁷(140 dB) dynamic range and sensitivity down to 10 pW. A second major difference is the spectral sensitivity of the two detectors. Here, wavelengths in the 940 nm range are efficiently captured by PDs (but not SiPMs), likely making them the superior choice for broadband spectroscopy guided by MRI.
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Affiliation(s)
- Fadi El-Ghussein
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Shudong Jiang
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Brian W. Pogue
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
| | - Keith D. Paulsen
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire 03755, United States
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