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Nizam NI, Ochoa M, Smith JT, Intes X. Deep learning-based fusion of widefield diffuse optical tomography and micro-CT structural priors for accurate 3D reconstructions. BIOMEDICAL OPTICS EXPRESS 2023; 14:1041-1053. [PMID: 36950248 PMCID: PMC10026582 DOI: 10.1364/boe.480091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/10/2023] [Accepted: 01/24/2023] [Indexed: 06/17/2023]
Abstract
Widefield illumination and detection strategies leveraging structured light have enabled fast and robust probing of tissue properties over large surface areas and volumes. However, when applied to diffuse optical tomography (DOT) applications, they still require a time-consuming and expert-centric solving of an ill-posed inverse problem. Deep learning (DL) models have been recently proposed to facilitate this challenging step. Herein, we expand on a previously reported deep neural network (DNN) -based architecture (modified AUTOMAP - ModAM) for accurate and fast reconstructions of the absorption coefficient in 3D DOT based on a structured light illumination and detection scheme. Furthermore, we evaluate the improved performances when incorporating a micro-CT structural prior in the DNN-based workflow, named Z-AUTOMAP. This Z-AUTOMAP significantly improves the widefield imaging process's spatial resolution, especially in the transverse direction. The reported DL-based strategies are validated both in silico and in experimental phantom studies using spectral micro-CT priors. Overall, this is the first successful demonstration of micro-CT and DOT fusion using deep learning, greatly enhancing the prospect of rapid data-integration strategies, often demanded in challenging pre-clinical scenarios.
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2
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Synchrotron X-ray Radiation (SXR) in Medical Imaging: Current Status and Future Prospects. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12083790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Synchrotron X-ray radiation (SXR) has been widely studied to explore the structure of matter. Recently, there has been an intense focus on the medical application of SXR in imaging. This review is intended to explore the latest applications of SXR in medical imaging and to shed light on the advantages and drawbacks of this modality. The article highlights the latest developments in other fields that can greatly enhance the capability and applicability of SXR. The potentials of using machine and deep learning (DL)-based methods to generate synthetic images to use in regular clinics along with the use of photon counting X-ray detectors for spectral medical imaging with SXR are also discussed.
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3
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Nouizi F, Algarawi M, Erkol H, Luk A, Gulsen G. Multiwavelength photo-magnetic imaging algorithm improved for direct chromophore concentration recovery using spectral constraints. APPLIED OPTICS 2021; 60:10855-10861. [PMID: 35200850 DOI: 10.1364/ao.439250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 11/12/2021] [Indexed: 06/14/2023]
Abstract
Multiwavelength photo-magnetic imaging (PMI) is a novel combination of diffuse optics and magnetic resonance imaging, to the best of our knowledge, that yields tissue chromophore concentration maps with high resolution and quantitative accuracy. Here, we present the first experimental results, to the best of our knowledge, obtained using a spectrally constrained PMI image reconstruction method, where chromophore concentration maps are directly recovered, unlike the conventional two-step approach that requires an intermediate step of reconstructing wavelength-dependent absorption coefficient maps. The imposition of the prior spectral information into the PMI inverse problem improves the reconstructed image quality and allows recovery of highly quantitative concentration maps, which are crucial for effective cancer detection and characterization. The obtained results demonstrate the higher performance of the direct reconstruction method. Indeed, the reconstructed concentration maps are not only of higher quality but also obtained approximately 2 times faster than the conventional method.
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4
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Wang J, Chu Y, Wang B, Jiang T. A Narrative Review of Ultrasound Technologies for the Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer. Cancer Manag Res 2021; 13:7885-7895. [PMID: 34703310 PMCID: PMC8523361 DOI: 10.2147/cmar.s331665] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/29/2021] [Indexed: 12/21/2022] Open
Abstract
The incidence and mortality rate of breast cancer (BC) in women currently ranks first worldwide, and neoadjuvant chemotherapy (NAC) is widely used in patients with BC. A variety of imaging assessment methods have been used to predict and evaluate the response to NAC. Ultrasound (US) has many advantages, such as being inexpensive and offering a convenient modality for follow-up detection without radiation emission. Although conventional grayscale US is typically used to predict the response to NAC, this approach is limited in its ability to distinguish viable tumor tissue from fibrotic scar tissue. Contrast-enhanced ultrasound (CEUS) combined with a time-intensity curve (TIC) not only provides information on blood perfusion but also reveals a variety of quantitative parameters; elastography has the potential capacity to predict NAC efficiency by evaluating tissue stiffness. Both CEUS and elastography can greatly improve the accuracy of predicting NAC responses. Other US techniques, including three-dimensional (3D) techniques, quantitative ultrasound (QUS) and US-guided near-infrared (NIR) diffuse optical tomography (DOT) systems, also have advantages in assessing NAC response. This paper reviews the different US technologies used for predicting NAC response in BC patients based on the previous literature.
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Affiliation(s)
- Jing Wang
- Department of Ultrasound, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People's Republic of China
| | - Yanhua Chu
- Department of Ultrasound, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People's Republic of China
| | - Baohua Wang
- Department of Ultrasound, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People's Republic of China
| | - Tianan Jiang
- Department of Ultrasound, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People's Republic of China
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5
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Zhang M, Li S, Zou Y, Zhu Q. Deep learning-based method to accurately estimate breast tissue optical properties in the presence of the chest wall. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-210118RR. [PMID: 34672146 PMCID: PMC8527162 DOI: 10.1117/1.jbo.26.10.106004] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 08/30/2021] [Indexed: 05/02/2023]
Abstract
SIGNIFICANCE In general, image reconstruction methods used in diffuse optical tomography (DOT) are based on diffusion approximation, and they consider the breast tissue as a homogenous, semi-infinite medium. However, the semi-infinite medium assumption used in DOT reconstruction is not valid when the chest wall is underneath the breast tissue. AIM We aim to reduce the chest wall's effect on the estimated average optical properties of breast tissue and obtain accurate forward model for DOT reconstruction. APPROACH We propose a deep learning-based neural network approach where a convolution neural network (CNN) is trained to simultaneously obtain accurate optical property values for both the breast tissue and the chest wall. RESULTS The CNN model shows great promise in reducing errors in estimating the optical properties of the breast tissue in the presence of a shallow chest wall. For patient data, the CNN model predicted the breast tissue optical absorption coefficient, which was independent of chest wall depth. CONCLUSIONS Our proposed method can be readily used in DOT and diffuse spectroscopy measurements to improve the accuracy of estimated tissue optical properties.
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Affiliation(s)
- Menghao Zhang
- Washington University in St. Louis, Department of Electrical and Systems Engineering, St. Louis, Missouri, United States
| | - Shuying Li
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
| | - Yun Zou
- Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States
| | - Quing Zhu
- Washington University in St. Louis, Department of Electrical and Systems Engineering, St. Louis, Missouri, United States
- 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,
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6
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Zou Y, Zeng Y, Li S, Zhu Q. Machine learning model with physical constraints for diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2021; 12:5720-5735. [PMID: 34692211 PMCID: PMC8515969 DOI: 10.1364/boe.432786] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 08/06/2021] [Accepted: 08/09/2021] [Indexed: 05/02/2023]
Abstract
A machine learning model with physical constraints (ML-PC) is introduced to perform diffuse optical tomography (DOT) reconstruction. DOT reconstruction is an ill-posed and under-determined problem, and its quality suffers by model mismatches, complex boundary conditions, tissue-probe contact, noise etc. Here, for the first time, we combine ultrasound-guided DOT with ML to facilitate DOT reconstruction. Our method has two key components: (i) a neural network based on auto-encoder is adopted for DOT reconstruction, and (ii) physical constraints are implemented to achieve accurate reconstruction. Both qualitative and quantitative results demonstrate that the accuracy of the proposed method surpasses that of existing models. In a phantom study, compared with the Born conjugate gradient descent (Born-CGD) reconstruction method, the ML-PC method decreases the mean percentage error of the reconstructed maximum absorption coefficient from 16.41% to 13.4% for high contrast phantoms and from 23.42% to 9.06% for low contrast phantoms, with improved depth distribution of the target absorption maps. In a clinical study, better contrast was obtained between malignant and benign breast lesions, with the ratio of the medians of the maximum absorption coefficient improved from 1.63 to 2.22.
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Affiliation(s)
- Yun Zou
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63130, USA
| | - Yifeng Zeng
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63130, USA
| | - Shuying Li
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63130, USA
| | - Quing Zhu
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63130, USA
- Department of Radiology, Washington University School of Medicine, St. Louis 63110, USA
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7
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Di Sciacca G, Di Sieno L, Farina A, Lanka P, Venturini E, Panizza P, Dalla Mora A, Pifferi A, Taroni P, Arridge SR. Enhanced diffuse optical tomographic reconstruction using concurrent ultrasound information. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200195. [PMID: 34218668 PMCID: PMC8255947 DOI: 10.1098/rsta.2020.0195] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/25/2021] [Indexed: 05/26/2023]
Abstract
Multimodal imaging is an active branch of research as it has the potential to improve common medical imaging techniques. Diffuse optical tomography (DOT) is an example of a low resolution, functional imaging modality that typically has very low resolution due to the ill-posedness of its underlying inverse problem. Combining the functional information of DOT with a high resolution structural imaging modality has been studied widely. In particular, the combination of DOT with ultrasound (US) could serve as a useful tool for clinicians for the formulation of accurate diagnosis of breast lesions. In this paper, we propose a novel method for US-guided DOT reconstruction using a portable time-domain measurement system. B-mode US imaging is used to retrieve morphological information on the probed tissues by means of a semi-automatical segmentation procedure based on active contour fitting. A two-dimensional to three-dimensional extrapolation procedure, based on the concept of distance transform, is then applied to generate a three-dimensional edge-weighting prior for the regularization of DOT. The reconstruction procedure has been tested on experimental data obtained on specifically designed dual-modality silicon phantoms. Results show a substantial quantification improvement upon the application of the implemented technique. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.
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Affiliation(s)
- G. Di Sciacca
- Department of Computer Science, University College London, London WC1E 6BT, UK
| | - L. Di Sieno
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32 20133 Milano, Italy
| | - A. Farina
- Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie, Piazza Leonardo da Vinci, 32 20133 Milano, Italy
| | - P. Lanka
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32 20133 Milano, Italy
| | - E. Venturini
- Breast Imaging Unit, San Raffaele Scientific Hospital, Milano, Italy
| | - P. Panizza
- Breast Imaging Unit, San Raffaele Scientific Hospital, Milano, Italy
| | - A. Dalla Mora
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32 20133 Milano, Italy
| | - A. Pifferi
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32 20133 Milano, Italy
| | - P. Taroni
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci, 32 20133 Milano, Italy
| | - S. R. Arridge
- Department of Computer Science, University College London, London WC1E 6BT, UK
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8
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Li S, Zhang M, Zhu Q. Ultrasound segmentation-guided edge artifact reduction in diffuse optical tomography using connected component analysis. BIOMEDICAL OPTICS EXPRESS 2021; 12:5320-5336. [PMID: 34513259 PMCID: PMC8407838 DOI: 10.1364/boe.428107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/09/2021] [Accepted: 07/12/2021] [Indexed: 05/02/2023]
Abstract
Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated potential value for breast cancer diagnosis and treatment response assessment. However, in clinical use, the chest wall, poor probe-tissue contact, and tissue heterogeneity can all cause image artifacts. These image artifacts, appearing commonly as hot spots in the non-lesion regions (edge artifacts), can decrease the reconstruction accuracy and cause misinterpretation of lesion images. Here we introduce an iterative, connected component analysis-based image artifact reduction algorithm. A convolutional neural network (CNN) is used to segment co-registered US images to extract the lesion location and size to guide the artifact reduction. We demonstrate its performance using Monte Carlo simulations on VICTRE digital breast phantoms and breast patient images. In simulated tissue mismatch models, this algorithm successfully reduces edge artifacts without significantly changing the reconstructed target absorption coefficients. With clinical data it improves the optical contrast between malignant and benign groups, from 1.55 without artifact reduction to 1.91 with artifact reduction. The proposed algorithm has a broad range of applications in other modality-guided DOT imaging.
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Affiliation(s)
- Shuying Li
- Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130, USA
| | - Menghao Zhang
- Department of Electrical & Systems Engineering, Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130, USA
| | - Quing Zhu
- Department of Biomedical Engineering, Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130, USA
- Department of Radiology, Washington University School of Medicine, 660 S Euclid Ave, St. Louis 63110, USA
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9
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Li S, Huang K, Zhang M, Uddin KMS, Zhu Q. Effect and correction of optode coupling errors in breast imaging using diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2021; 12:689-704. [PMID: 33680536 PMCID: PMC7901340 DOI: 10.1364/boe.411595] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 11/27/2020] [Accepted: 12/08/2020] [Indexed: 05/18/2023]
Abstract
In diffuse optical tomography (DOT) and spectroscopy (DOS) using handheld probes, tissue curvature can cause bad fiber-to-tissue contact. Understanding and minimizing image artifacts caused by these coupling errors would significantly improve DOT and DOS image quality. In this work, we utilized Monte Carlo simulations and experiments with gelatin-Intralipid phantoms to systematically study the influence of source or detector (optode) coupling errors. Optode coupling errors can increase the amplitude and decrease the phase of the measured diffuse reflectance, creating artifacts in the reconstructed absorption maps, such as hot spots on the edges. We propose an outlier removal algorithm that can correct these image artifacts, and we demonstrate its performance using simulations, phantom experiments, and breast patient data acquired with bad probe contact due to a dense or small breast. Further, we designed and implemented a new resistance-type thin-film force sensor array that provides real-time optode coupling feedback and guides the outlier removal to minimize optode coupling errors. Our approaches and study results have significant implications for reducing image artifacts arising from handheld probes, which are commonly used with mobile and wearable DOT and DOS devices.
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Affiliation(s)
- Shuying Li
- Department of Biomedical Engineering,
Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130,
USA
| | - Kexin Huang
- Department of Biomedical Engineering,
Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130,
USA
| | - Menghao Zhang
- Department of Electrical and Systems
Engineering, Washington University in St. Louis, 1 Brookings Dr, St.
Louis 63130, USA
| | - K. M. Shihab Uddin
- Department of Biomedical Engineering,
Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130,
USA
| | - Quing Zhu
- Department of Biomedical Engineering,
Washington University in St. Louis, 1 Brookings Dr, St. Louis 63130,
USA
- Department of Radiology, Washington
University School of Medicine, 660 S Euclid Ave, St. Louis 63110,
USA
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10
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Maffeis G, Ferocino E, Mora AD, Pifferi A, Cubeddu R, Taroni P. In vivo test-driven upgrade of a time domain multi-wavelength optical mammograph. BIOMEDICAL OPTICS EXPRESS 2021; 12:1105-1122. [PMID: 33680561 PMCID: PMC7901327 DOI: 10.1364/boe.412210] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/06/2021] [Accepted: 01/19/2021] [Indexed: 05/23/2023]
Abstract
A recent upgrade of the time domain multi-wavelength optical mammograph developed by Politecnico di Milano achieved good performance in laboratory tests [Biomed. Opt. Express9, 755 (2018).10.1364/BOE.9.000755]. However, it proved unsatisfactory when in vivo measurements were finally performed. That led to a further upgrade, including the replacement of the time-to-digital converter with a new model, and the related set-up changes. The new instrument version offers improved laboratory performance (as assessed through established protocols: BIP and MEDPHOT) and good in vivo performance (extension of the scanned breast area, repeatability, consistency of estimated tissue composition with physiology). Besides introducing the new set-up and detailing its laboratory and in vivo performance, we highlight the importance of systematic in vivo testing before entering clinical trials.
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Affiliation(s)
- Giulia Maffeis
- Politecnico di Milano, Department of Physics, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
| | - Edoardo Ferocino
- Politecnico di Milano, Department of Physics, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
| | - Alberto Dalla Mora
- Politecnico di Milano, Department of Physics, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
| | - Antonio Pifferi
- Politecnico di Milano, Department of Physics, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
- CNR-Istituto di Fotonica e Nanotecnologie, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
| | - Rinaldo Cubeddu
- Politecnico di Milano, Department of Physics, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
| | - Paola Taroni
- Politecnico di Milano, Department of Physics, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
- CNR-Istituto di Fotonica e Nanotecnologie, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy
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11
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Carbone NA, Vera DA, Iriarte DI, Pomarico JA, Macdonald R, Grosenick D. Camera-based CW Diffuse Optical Tomography for obtaining 3D absorption maps by means of digital tomosynthesis. Biomed Phys Eng Express 2020; 6. [PMID: 35039466 DOI: 10.1088/2057-1976/abc633] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/30/2020] [Indexed: 11/11/2022]
Abstract
We present a novel method for obtaining a 3D absorption map of a tissue-like turbid slab in the near-infrared spectral range by tomosynthesis. Transmittance data are obtained for a large number of oblique projection directions by scanning a cw laser source across the surface of the slab and by using a CCD camera for spatially resolved light detection. A perturbation model of light transport is used to convert the intensity maps for the different projections into absorption maps. By applying the tomosynthesis approach to these new maps, 3D absorption information on embedded inclusions has been obtained for the first time. The number and the positions of the lateral offset detectors have been optimized by employing a structural similarity index for comparison of the reconstructed with the true absorption data. We present 3D reconstruction of absorption maps using both Monte Carlo simulations and experiments on phantoms with breast-like optical properties. A comparison with conventional 3D reconstruction by a finite element approach shows the superior location performance of tomosynthesis.
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Affiliation(s)
- N A Carbone
- CIFICEN (UNCPBA-CONICET-CICPBA), Pinto 399, B7000GHG Tandil, Argentina
| | - D A Vera
- CIFICEN (UNCPBA-CONICET-CICPBA), Pinto 399, B7000GHG Tandil, Argentina
| | - D I Iriarte
- CIFICEN (UNCPBA-CONICET-CICPBA), Pinto 399, B7000GHG Tandil, Argentina
| | - J A Pomarico
- CIFICEN (UNCPBA-CONICET-CICPBA), Pinto 399, B7000GHG Tandil, Argentina
| | - R Macdonald
- Physikalisch-Technische Bundesanstalt (PTB), Abbestraße 2-12, 10587 Berlin, Germany
| | - D Grosenick
- Physikalisch-Technische Bundesanstalt (PTB), Abbestraße 2-12, 10587 Berlin, Germany
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12
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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: 8] [Impact Index Per Article: 2.0] [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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13
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Lo PA, Su SP, Chiang HK. Small-animal 360-deg fluorescence diffuse optical tomography using structural prior information from ultrasound imaging. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-11. [PMID: 32129028 PMCID: PMC7052526 DOI: 10.1117/1.jbo.25.3.036001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 01/23/2020] [Indexed: 06/10/2023]
Abstract
We demonstrate dual modality of free-space fluorescence diffuse optical tomography (FDOT) and handheld ultrasound (US) imaging to reveal both functional and structural information in small animals. FDOT is a noninvasive method for examining the fluorophore inside an object from the light distribution of the surface. In FDOT, a 660-nm continuous wave diode laser was used as an excitation source and an electron-multiplying charge-coupled device (EMCCD) was used for fluorescence data acquisition. Both the laser and EMCCD were mounted on a 360-deg rotation gantry for the transmission optical data collection. The structural information is obtained from a 6- to 17-MHz handheld US linear transducer by single-side access and conducts in the reconstruction as soft priors. The rotation ranges from 0 deg to 360 deg; different rotation degrees, object positions, and parameters were determined for comparison. Both phantom and tissue phantom results demonstrate that fluorophore distribution can be recovered accurately and quantitatively using this imaging system. Finally, an animal study confirms that the system can extract a dual-modality image, validating its feasibility for further in vivo experiments. In all experiments, the error and standard deviation decrease as the rotation degree is increased and the error was reduced to 10% when the rotation degree was increased over 135 deg.
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Affiliation(s)
- Pei-An Lo
- National Yang-Ming University, Institute of Biomedical Engineering, Taipei, Taiwan
| | - Shih-Po Su
- National Yang-Ming University, Institute of Biomedical Engineering, Taipei, Taiwan
| | - Huihua Kenny Chiang
- National Yang-Ming University, Institute of Biomedical Engineering, Taipei, Taiwan
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14
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Di Sieno L, Contini D, Lo Presti G, Cortese L, Mateo T, Rosinski B, Venturini E, Panizza P, Mora M, Aranda G, Squarcia M, Farina A, Durduran T, Taroni P, Pifferi A, Mora AD. Systematic study of the effect of ultrasound gel on the performances of time-domain diffuse optics and diffuse correlation spectroscopy. BIOMEDICAL OPTICS EXPRESS 2019; 10:3899-3915. [PMID: 31452983 PMCID: PMC6701515 DOI: 10.1364/boe.10.003899] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 07/01/2019] [Accepted: 07/01/2019] [Indexed: 05/06/2023]
Abstract
Recently, multimodal imaging has gained an increasing interest in medical applications thanks to the inherent combination of strengths of the different techniques. For example, diffuse optics is used to probe both the composition and the microstructure of highly diffusive media down to a depth of few centimeters, but its spatial resolution is intrinsically low. On the other hand, ultrasound imaging exhibits the higher spatial resolution of morphological imaging, but without providing solid constitutional information. Thus, the combination of diffuse optical imaging and ultrasound may improve the effectiveness of medical examinations, e.g. for screening or diagnosis of tumors. However, the presence of an ultrasound coupling gel between probe and tissue can impair diffuse optical measurements like diffuse optical spectroscopy and diffuse correlation spectroscopy, since it may provide a direct path for photons between source and detector. A systematic study on the effect of different ultrasound coupling fluids was performed on tissue-mimicking phantoms, confirming that a water-clear gel can produce detrimental effects on optical measurements when recovering absorption/reduced scattering coefficients from time-domain spectroscopy acquisitions as well as particle Brownian diffusion coefficient from diffuse correlation spectroscopy ones. On the other hand, we show the suitability for optical measurements of other types of diffusive fluids, also compatible with ultrasound imaging.
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Affiliation(s)
- Laura Di Sieno
- Politecnico di Milano - Dipartimento di Fisica, Milano, Italy
| | - Davide Contini
- Politecnico di Milano - Dipartimento di Fisica, Milano, Italy
| | - Giuseppe Lo Presti
- ICFO - Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels (Barcelona), Spain
| | - Lorenzo Cortese
- ICFO - Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels (Barcelona), Spain
| | | | | | - Elena Venturini
- Scientific Institute (IRCCS) Ospedale San Raffaele - Breast Imaging Unit, Milano, Italy
| | - Pietro Panizza
- Scientific Institute (IRCCS) Ospedale San Raffaele - Breast Imaging Unit, Milano, Italy
| | - Mireia Mora
- IDIBAPS, Fundació Clínic per la Recerca Biomèdica, Barcelona, Spain
| | - Gloria Aranda
- IDIBAPS, Fundació Clínic per la Recerca Biomèdica, Barcelona, Spain
| | - Mattia Squarcia
- IDIBAPS, Fundació Clínic per la Recerca Biomèdica, Barcelona, Spain
| | - Andrea Farina
- Consiglio Nazionale delle Ricerche - Istituto di Fotonica e Nanotecnologie, Milano, Italy
| | - Turgut Durduran
- ICFO - Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels (Barcelona), Spain
- Instituciò Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Paola Taroni
- Politecnico di Milano - Dipartimento di Fisica, Milano, Italy
- Consiglio Nazionale delle Ricerche - Istituto di Fotonica e Nanotecnologie, Milano, Italy
| | - Antonio Pifferi
- Politecnico di Milano - Dipartimento di Fisica, Milano, Italy
- Consiglio Nazionale delle Ricerche - Istituto di Fotonica e Nanotecnologie, Milano, Italy
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15
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Uddin KMS, Zhu Q. Reducing image artifact in diffuse optical tomography by iterative perturbation correction based on multiwavelength measurements. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-8. [PMID: 31119903 PMCID: PMC6529735 DOI: 10.1117/1.jbo.24.5.056005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 04/19/2019] [Indexed: 05/18/2023]
Abstract
Ultrasound (US) guided diffuse optical tomography has demonstrated great potential for breast cancer diagnosis, treatment monitoring, and chemotherapy response prediction. Optical measurements of four different wavelengths are used to reconstruct unknown optical absorption maps, which are then used to calculate the hemoglobin concentration distribution of the US visible lesion. Reconstructed absorption maps are prone to image artifacts from outliers in measurement data from tissue heterogeneity, bad coupling between tissue and light guides, and motion by patient or operator. We propose an automated iterative perturbation correction algorithm to reduce image artifacts based on the structural similarity index (SSIM) of absorption maps of four optical wavelengths. The initial image is estimated from the truncated pseudoinverse solution. The SSIM was calculated for each wavelength to assess its similarity with other wavelengths. An absorption map is repeatedly reconstructed and projected back into measurement space to quantify projection error. Outlier measurements with highest projection errors are iteratively removed until all wavelength images are structurally similar with SSIM values greater than a threshold. Clinical data demonstrate statistically significant improvement in image artifact reduction.
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Affiliation(s)
- K. M. Shihab Uddin
- Washington University in St Louis, Biomedical Engineering Department, St. Louis, Missouri, United States
| | - Quing Zhu
- Washington University in St Louis, Biomedical Engineering Department, St. Louis, Missouri, United States
- Address all correspondence to Quing Zhu, E-mail:
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16
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Xu S, Shihab Uddin KM, Zhu Q. Improving DOT reconstruction with a Born iterative method and US-guided sparse regularization. BIOMEDICAL OPTICS EXPRESS 2019; 10:2528-2541. [PMID: 31149382 PMCID: PMC6524590 DOI: 10.1364/boe.10.002528] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 03/14/2019] [Accepted: 03/20/2019] [Indexed: 05/22/2023]
Abstract
Ultrasound (US)-guided diffuse optical tomography (DOT) is a promising low-cost imaging technique for diagnosis and assessment of breast cancer. US-guided DOT is best implemented in reflection geometry, which can be co-registered with US pulse-echo imaging and also minimizes the tissue depth for adequate light penetration. However, due to intense light scattering, the DOT reconstruction problem is ill-posed. In this communication, we describe a new non-linear Born iterative reconstruction method with US-guided depth-dependent ℓ 1 sparse regularization for improving DOT reconstruction by incorporating a priori lesion depth and shape information from the co-registered US image. Our method iteratively solves the inverse problem by updating the photon-density wave using the finite difference method, computing the weight matrix based on Born approximation, and reconstructing the absorption map using the fast iterative shrinkage-thresholding optimization algorithm (FISTA). We validate our method using both phantom and patient data and compare the results with those using the first order linear Born method. Phantom experiments demonstrate that the non-linear Born method provides more accurate target absorption reconstruction and better resolution than the linear Born method. Clinical studies on 20 patients show that non-linear Born reconstructs more realistic tumor shapes than linear Born, and improves the malignant-to-benign lesion contrast ratio from 2.73 to 3.07 , which is a 12.5 % improvement. For lesions approximately more than 2.0 cm in diameter, the average malignant-to-benign lesion contrast ratio is increased from 2.68 to 3.31 , which is a 23.5 % improvement.
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Affiliation(s)
- Shiqi Xu
- Elecctrical and Systems Engineering Department, Washington University in St. Louis, 1 Brookings Dr. St. Louis, MO 63130,
USA
| | - K. M. Shihab Uddin
- Biomedical Engineering Department, Washington University in St. Louis, 1 Brookings Dr. St. Louis, MO 63130,
USA
| | - Quing Zhu
- Biomedical Engineering Department, Washington University in St. Louis, 1 Brookings Dr. St. Louis, MO 63130,
USA
- Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO 63110,
USA
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17
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Comparison of Lipid and Water Contents by Time-domain Diffuse Optical Spectroscopy and Dual-energy Computed Tomography in Breast Cancer Patients. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9071482] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We previously compared time-domain diffuse optical spectroscopy (TD-DOS) with magnetic resonance imaging (MRI) using various water/lipid phantoms. However, it is difficult to conduct similar comparisons in the breast, because of measurement differences due to modality-dependent differences in posture. Dual-energy computed tomography (DECT) examination is performed in the same supine position as a TD-DOS measurement. Therefore, we first verified the accuracy of the measured fat fraction of fibroglandular tissue in the normal breast on DECT by comparing it with MRI in breast cancer patients (n = 28). Then, we compared lipid and water signals obtained in TD-DOS and DECT from normal and tumor-tissue regions (n = 16). The TD-DOS breast measurements were carried out using reflectance geometry with a source–detector separation of 3 cm. A semicircular region of interest (ROI), with a transverse diameter of 3 cm and a depth of 2 cm that included the breast surface, was set on the DECT image. Although the measurement area differed between the modalities, the correlation coefficients of lipid and water signals between TD-DOS and DECT were rs = 0.58 (p < 0.01) and rs = 0.90 (p < 0.01), respectively. These results indicate that TD-DOS captures the characteristics of the lipid and water contents of the breast.
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18
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Althobaiti M, Vavadi H, Zhu Q. An Automated Preprocessing Method for Diffuse Optical Tomography to Improve Breast Cancer Diagnosis. Technol Cancer Res Treat 2019; 17:1533033818802791. [PMID: 30278830 PMCID: PMC6170968 DOI: 10.1177/1533033818802791] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
The ultrasound-guided diffuse optical tomography is a noninvasive imaging technique for breast cancer diagnosis and treatment monitoring. The technique uses a handheld probe capable of providing measurements of multiple wavelengths in a few seconds. These measurements are used to estimate optical absorptions of lesions and calculate the total hemoglobin concentration. Any measurement errors caused by low signal to noise ratio data and/or movements during data acquisition would reduce the accuracy of reconstructed total hemoglobin concentration. In this article, we introduce an automated preprocessing method that combines data collected from multiple sets of lesion measurements of 4 optical wavelengths to detect and correct outliers in the perturbation. Two new measures of correlation between each pair of wavelength measurements and a wavelength consistency index of all reconstructed absorption maps are introduced. For phantom and patients' data without evidence of measurement errors, the correlation coefficient between each pair of wavelength measurements was above 0.6. However, for patients with measurement errors, the correlation coefficient was much lower. After applying the correction method to 18 patients' data with measurement errors, the correlation has improved and the wavelength consistency index is in the same range as the cases without wavelength-dependent measurement errors. The results show an improvement in classification of malignant and benign lesions.
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Affiliation(s)
- Murad Althobaiti
- 1 Biomedical Engineering Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Hamed Vavadi
- 2 Biomedical Engineering Department, University of Connecticut, Mansfield, CT, USA
| | - Quing Zhu
- 3 Biomedical Engineering Department, Washington University in St Louis, St Louis, MO, USA
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19
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Feng J, Sun Q, Li Z, Sun Z, Jia K. Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography. JOURNAL OF BIOMEDICAL OPTICS 2018; 24:1-12. [PMID: 30569669 PMCID: PMC6992907 DOI: 10.1117/1.jbo.24.5.051407] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 11/30/2018] [Indexed: 05/02/2023]
Abstract
Diffuse optical tomography (DOT) is a promising noninvasive imaging modality and is capable of providing functional characteristics of biological tissue by quantifying optical parameters. The DOT image reconstruction is ill-posed and ill-conditioned, due to the highly diffusive nature of light propagation in biological tissues and limited boundary measurements. The widely used regularization technique for DOT image reconstruction is Tikhonov regularization, which tends to yield oversmoothed and low-quality images containing severe artifacts. It is necessary to accurately choose a regularization parameter for Tikhonov regularization. To overcome these limitations, we develop a noniterative reconstruction method, whereby optical properties are recovered based on a back-propagation neural network (BPNN). We train the parameters of BPNN before DOT image reconstruction based on a set of training data. DOT image reconstruction is achieved by implementing a single evaluation of the trained network. To demonstrate the performance of the proposed algorithm, we compare with the conventional Tikhonov regularization-based reconstruction method. The experimental results demonstrate that image quality and quantitative accuracy of reconstructed optical properties are significantly improved with the proposed algorithm.
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Affiliation(s)
- Jinchao Feng
- Beijing Univ. of Technology, China
- Beijing Lab. of Advanced Information Networks, China
| | | | - Zhe Li
- Beijing Univ. of Technology, China
- Beijing Lab. of Advanced Information Networks, China
| | - Zhonghua Sun
- Beijing Univ. of Technology, China
- Beijing Lab. of Advanced Information Networks, China
| | - Kebin Jia
- Beijing Univ. of Technology, China
- Beijing Lab. of Advanced Information Networks, China
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20
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Hoi JW, Kim HK, Fong CJ, Zweck L, Hielscher AH. Non-contact dynamic diffuse optical tomography imaging system for evaluating lower extremity vasculature. BIOMEDICAL OPTICS EXPRESS 2018; 9:5597-5614. [PMID: 30460149 PMCID: PMC6238914 DOI: 10.1364/boe.9.005597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 08/26/2018] [Accepted: 08/27/2018] [Indexed: 06/09/2023]
Abstract
A novel multi-view non-contact dynamic diffuse optical tomographic imaging system for the clinical evaluation of vasculature in the lower extremities is presented. The system design and implementation are described in detail, including methods for simultaneously obtaining and reconstructing diffusely reflected and transmitted light using a system of mirrors and a single CCD camera. The system and its performance using numeric simulations and optical phantoms. Measurements of a healthy foot in vivo demonstrates the potential of the system in assessing perfusion within the foot.
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Affiliation(s)
- J. W. Hoi
- Department of Biomedical Engineering, Columbia University, 351 Engineering Terrace, 500 W. 120th St., New York, NY 10027, USA
| | - H. K. Kim
- Department of Radiology, Columbia University, 630 W. 168th St., New York, NY 10032, USA
| | - C. J. Fong
- Department of Biomedical Engineering, Columbia University, 351 Engineering Terrace, 500 W. 120th St., New York, NY 10027, USA
| | - L. Zweck
- Faculty of Engineering, Friedrich-Alexander-Universität, Martensstraße 5a, 91058 Erlangen, Germany
| | - A. H. Hielscher
- Department of Biomedical Engineering, Columbia University, 351 Engineering Terrace, 500 W. 120th St., New York, NY 10027, USA
- Department of Radiology, Columbia University, 630 W. 168th St., New York, NY 10032, USA
- Department of Electrical Engineering, Columbia University, 1300 S.W. Mudd, 500 W. 120th St., New York, NY 10027, USA
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21
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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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22
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Feng J, Jiang S, Pogue BW, Paulsen K. Weighting function effects in a direct regularization method for image-guided near-infrared spectral tomography of breast cancer. BIOMEDICAL OPTICS EXPRESS 2018; 9:3266-3283. [PMID: 29984097 PMCID: PMC6033579 DOI: 10.1364/boe.9.003266] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 05/23/2018] [Accepted: 06/11/2018] [Indexed: 05/18/2023]
Abstract
Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast by 10%, the contrast to noise ratio by 20% and the full width half maximum (FWHM) by 30%. The results from phantoms and human images show that a linear inverse distance weighting function appears optimal, and that incorporation of this function can generally improve the recovered total hemoglobin contrast of the tumor to the normal surrounding tissue by more than 15% in human cases.
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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
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
- Beijing Laboratory of Advanced Information Networks, Beijing 100124, China
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
| | - Brian W. Pogue
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
| | - Keith Paulsen
- Thayer School of Engineering, Dartmouth College, NH 03755, USA
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23
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Zhu Q, Tannenbaum S, Kurtzman SH, DeFusco P, Ricci A, Vavadi H, Zhou F, Xu C, Merkulov A, Hegde P, Kane M, Wang L, Sabbath K. Identifying an early treatment window for predicting breast cancer response to neoadjuvant chemotherapy using immunohistopathology and hemoglobin parameters. Breast Cancer Res 2018; 20:56. [PMID: 29898762 PMCID: PMC6001175 DOI: 10.1186/s13058-018-0975-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 04/30/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Breast cancer pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) varies with tumor subtype. The purpose of this study was to identify an early treatment window for predicting pCR based on tumor subtype, pretreatment total hemoglobin (tHb) level, and early changes in tHb following NAC. METHODS Twenty-two patients (mean age 56 years, range 34-74 years) were assessed using a near-infrared imager coupled with an Ultrasound system prior to treatment, 7 days after the first treatment, at the end of each of the first three cycles, and before their definitive surgery. Pathologic responses were dichotomized by the Miller-Payne system. Tumor vascularity was assessed from tHb; vascularity changes during NAC were assessed from a percentage tHb normalized to the pretreatment level (%tHb). After training the logistic prediction models using the previous study data, we assessed the early treatment window for predicting pathological response according to their tumor subtype (human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), triple-negative (TN)) based on tHb, and %tHb measured at different cycles and evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS In the new study cohort, maximum pretreatment tHb and %tHb changes after cycles 1, 2, and 3 were significantly higher in responder Miller-Payne 4-5 tumors (n = 13) than non-or partial responder Miller-Payne 1-3 tumors (n = 9). However, no significance was found at day 7. The AUC of the predictive power of pretreatment tHb in the cohort was 0.75, which was similar to the performance of the HER2 subtype as a single predictor (AUC of 0.78). A greater predictive power of pretreatment tHb was found within each subtype, with AUCs of 0.88, 0.69, and 0.72, in the HER2, ER, and TN subtypes, respectively. Using pretreatment tHb and cycle 1 %tHb, AUC reached 0.96, 0.91, and 0.90 in HER2, ER, and TN subtypes, respectively, and 0.95 regardless of subtype. Additional cycle 2 %tHb measurements moderately improved prediction for the HER2 subtype but did not improve prediction for the ER and TN subtypes. CONCLUSIONS By combining tumor subtypes with tHb, we predicted the pCR of breast cancer to NAC before treatment. Prediction accuracy can be significantly improved by incorporating cycle 1 and 2 %tHb for the HER2 subtype and cycle 1 %tHb for the ER and TN subtypes. TRIAL REGISTRATION ClinicalTrials.gov, NCT02092636 . Registered in March 2014.
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Affiliation(s)
- Quing Zhu
- Biomedical Engineering and Radiology, Washington University in St Louis, One Brookings Drive, Mail Box 1097, Whitaker Hall 300D, St. Louis, MO 63130 USA
| | - Susan Tannenbaum
- University of Connecticut Health Center, Farmington, CT 06030 USA
| | | | | | | | | | - Feifei Zhou
- University of Connecticut, Storrs, CT 06269 USA
| | - Chen Xu
- New York City College of Technology, City University of New York (CUNY), New York, USA
| | - Alex Merkulov
- University of Connecticut Health Center, Farmington, CT 06030 USA
| | - Poornima Hegde
- University of Connecticut Health Center, Farmington, CT 06030 USA
| | - Mark Kane
- University of Connecticut Health Center, Farmington, CT 06030 USA
| | - Liqun Wang
- Department of Statistics, University of Manitoba, 186 Dysart Road, Winnipeg, Manitoba, R3T 2N2 Canada
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24
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Lee S, Kim JG. Breast tumor hemodynamic response during a breath-hold as a biomarker to predict chemotherapeutic efficacy: preclinical study. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-5. [PMID: 29706036 DOI: 10.1117/1.jbo.23.4.048001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 04/13/2018] [Indexed: 06/08/2023]
Abstract
Continuous wave diffuse optical tomographic/spectroscopic system does not provide absolute concentrations of chromophores in tissue and monitor only the changes of chromophore concentration. Therefore, it requires a perturbation of physiological signals, such as blood flow and oxygenation. In that sense, a few groups reported that monitoring a relative hemodynamic change during a breast tissue compression or a breath-hold to a patient can provide good contrast between tumor and nontumor. However, no longitudinal study reports the utilization of a breath-hold to predict tumor response during chemotherapy. A continuous wave near-infrared spectroscopy was employed to monitor hemodynamics in rat breast tumor during a hyperoxic to normoxic inhalational gas intervention to mimic a breath-hold during tumor growth and chemotherapy. The reduced oxyhemoglobin concentration during inhalational gas intervention correlated well with tumor growth, and it responded one day earlier than the change of tumor volume after chemotherapy. In conclusion, monitoring tumor hemodynamics during a breath-hold may serve as a biomarker to predict chemotherapeutic efficacy of tumor.
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Affiliation(s)
- Songhyun Lee
- Gwangju Institute of Science and Technology, Department of Biomedical Science and Engineering, Gwang, Republic of Korea
| | - Jae Gwan Kim
- Gwangju Institute of Science and Technology, Department of Biomedical Science and Engineering, Gwang, Republic of Korea
- Gwangju Institute of Science and Technology, School of Electrical Engineering and Computer Science,, Republic of Korea
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25
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Niu S, Zhu Q, Jiang Y, Zhu J, Xiao M, You S, Zhou W, Xiao Y. Correlations Among Ultrasound-Guided Diffuse Optical Tomography, Microvessel Density, and Breast Cancer Prognosis. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2018; 37:833-842. [PMID: 29048710 DOI: 10.1002/jum.14416] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 06/01/2017] [Accepted: 06/26/2017] [Indexed: 06/07/2023]
Abstract
OBJECTIVES To investigate the correlation among ultrasound-guided diffuse optical tomography (DOT), microvessel density, and breast cancer prognosis. METHODS Before surgery, the total hemoglobin (Hb) concentrations of 184 female patients with breast cancer with only a single lesion were measured. During follow-up, 23 patients had recurrence or metastatic disease after surgery. Among these patients, 18 with recurrence or metastatic disease within 3 years after surgery were paired with 18 patients without recurrence or metastatic disease. We retrospectively reviewed the pathologic sections of those 36 patients, conducted immunohistochemical staining, and counted the microvessel densities. Then we analyzed the correlation between microvessel density and total Hb, compared total Hb and microvessel density among breast cancers with different prognoses, and tested the value of DOT in predicting the prognosis of breast cancer. RESULTS Microvessel density and total Hb were linearly correlated (r = 0.584; P < .001). Total Hb and microvessel density were significantly increased in the metastasis group (P = .001 and .027, respectively). A receiver operating characteristic curve analysis showed that at a total Hb cutoff value of 221.7 μmol/L, the sensitivity, specificity, and area under the curve of DOT for predicting recurrence or metastasis were 0.826, 0.516, and 0.660, respectively. CONCLUSIONS The total Hb concentration can reflect a tumor's blood supply. Patients with a high total Hb concentration and microvessel density have a higher risk for a poorer prognosis. Total Hb can be used as an indicator of breast cancer prognosis. Diffuse optical tomography can help physicians identify patients with a high risk of metastasis and make clinical decisions.
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Affiliation(s)
- Sihua Niu
- Departments of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qingli Zhu
- Departments of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuxin Jiang
- Departments of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jiaan Zhu
- Departments of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Mengsu Xiao
- Departments of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shanshan You
- Departments of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Weixun Zhou
- Department of Ultrasound, Peking University People's Hospital, Beijing, China
| | - Yu Xiao
- Department of Ultrasound, Peking University People's Hospital, Beijing, China
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26
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Gunther JE, Lim EA, Kim HK, Flexman M, Altoé M, Campbell JA, Hibshoosh H, Crew KD, Kalinsky K, Hershman DL, Hielscher AH. Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer. Radiology 2018; 287:778-786. [PMID: 29431574 DOI: 10.1148/radiol.2018161041] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Purpose To identify dynamic optical imaging features that associate with the degree of pathologic response in patients with breast cancer during neoadjuvant chemotherapy (NAC). Materials and Methods Of 40 patients with breast cancer who participated in a longitudinal study between June 2011 and March 2016, 34 completed the study. There were 13 patients who obtained a pathologic complete response (pCR) and 21 patients who did not obtain a pCR. Imaging data from six subjects were excluded from the study because either the patients dropped out of the study before it was finished or there was an instrumentation malfunction. Two weeks into the treatment regimen, three-dimensional images of both breasts during a breath hold were acquired by using dynamic diffuse optical tomography. Features from the breath-hold traces were used to distinguish between response groups. Receiver operating characteristic (ROC) curves and sensitivity analysis were used to determine the degree of association with 5-month treatment outcome. Results An ROC curve analysis showed that this method could identify patients with a pCR with a positive predictive value of 70.6% (12 of 17), a negative predictive value of 94.1% (16 of 17), a sensitivity of 92.3% (12 of 13), a specificity of 76.2% (16 of 21), and an area under the ROC curve of 0.85. Conclusion Several dynamic optical imaging features obtained within 2 weeks of NAC initiation were identified that showed statistically significant differences between patients with pCR and patients without pCR as determined 5 months after treatment initiation. If confirmed in a larger cohort prospective study, these dynamic imaging features may be used to predict treatment outcome as early as 2 weeks after treatment initiation. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Jacqueline E Gunther
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Emerson A Lim
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Hyun K Kim
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Molly Flexman
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Mirella Altoé
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Jessica A Campbell
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Hanina Hibshoosh
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Katherine D Crew
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Kevin Kalinsky
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Dawn L Hershman
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
| | - Andreas H Hielscher
- From the Departments of Biomedical Engineering (J.E.G., M.F., M.A., A.H.H.) and Electrical Engineering (A.H.H.), Columbia University, 500 W 120th St, Mudd Bldg, ET351, MC 8904, New York, NY 10027; Department of Medicine, Division of Hematology/Oncology (E.A.L., J.A.C., K.D.C., K.K., D.L.H.), Department of Radiology (H.K.K., A.H.H.), Department of Pathology and Cell Biology (H.H.), and Department of Epidemiology (K.D.C., D.L.H.), Columbia University Medical Center, New York, NY
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Yoshizawa N, Ueda Y, Mimura T, Ohmae E, Yoshimoto K, Wada H, Ogura H, Sakahara H. Factors affecting measurement of optic parameters by time-resolved near-infrared spectroscopy in breast cancer. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-6. [PMID: 29488362 DOI: 10.1117/1.jbo.23.2.026010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Accepted: 02/02/2018] [Indexed: 05/09/2023]
Abstract
The purpose of this study was to evaluate the effects of the thickness and depth of tumors on hemoglobin measurements in breast cancer by optical spectroscopy and to demonstrate tissue oxygen saturation (SO2) and reduced scattering coefficient (μs') in breast tissue and breast cancer in relation to the skin-to-chest wall distance. We examined 53 tumors from 44 patients. Total hemoglobin concentration (tHb), SO2, and μs' were measured by time-resolved spectroscopy (TRS). The skin-to-chest wall distance and the size and depth of tumors were measured by ultrasonography. There was a positive correlation between tHb and tumor thickness, and a negative correlation between tHb and tumor depth. SO2 in breast tissue decreased when the skin-to-chest wall distance decreased, and SO2 in tumors tended to be lower than in breast tissue. In breast tissue, there was a negative correlation between μs' and the skin-to-chest wall distance, and μs' in tumors was higher than in breast tissue. Measurement of tHb in breast cancer by TRS was influenced by tumor thickness and depth. Although SO2 seemed lower and μs' was higher in breast cancer than in breast tissue, the skin-to-chest wall distance may have affected the measurements.
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Affiliation(s)
- Nobuko Yoshizawa
- Hamamatsu University School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Hi, Japan
| | - Yukio Ueda
- Hamamatsu Photonics K.K. Central Research Laboratory, Hamakitaku, Hamamatsu, Japan
| | - Tetsuya Mimura
- Hamamatsu Photonics K.K. Central Research Laboratory, Hamakitaku, Hamamatsu, Japan
| | - Etsuko Ohmae
- Hamamatsu Photonics K.K. Central Research Laboratory, Hamakitaku, Hamamatsu, Japan
| | - Kenji Yoshimoto
- Hamamatsu Photonics K.K. Central Research Laboratory, Hamakitaku, Hamamatsu, Japan
| | - Hiroko Wada
- Hamamatsu Photonics K.K. Central Research Laboratory, Hamakitaku, Hamamatsu, Japan
| | - Hiroyuki Ogura
- Hamamatsu University School of Medicine, Department of Breast Surgery, Higashiku, Hamamatsu, Japan
| | - Harumi Sakahara
- Hamamatsu University School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Hi, Japan
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Vedantham S, Karellas A. Emerging Breast Imaging Technologies on the Horizon. Semin Ultrasound CT MR 2018; 39:114-121. [PMID: 29317033 DOI: 10.1053/j.sult.2017.09.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Early detection of breast cancers by mammography in conjunction with adjuvant therapy has contributed to reduction in breast cancer mortality. Mammography remains the "gold-standard" for breast cancer screening but is limited by tissue superposition. Digital breast tomosynthesis and more recently, dedicated breast computed tomography have been developed to alleviate the tissue superposition problem. However, all of these modalities rely upon x-ray attenuation contrast to provide anatomical images, and there are ongoing efforts to develop and clinically translate alternative modalities. These emerging modalities could provide for new contrast mechanisms and may potentially improve lesion detection and diagnosis. In this article, several of these emerging modalities are discussed with a focus on technologies that have advanced to the stage of in vivo clinical evaluation.
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Affiliation(s)
- Srinivasan Vedantham
- Department of Medical Imaging, University of Arizona College of Medicine, Banner University Medical Center, Tucson, AZ.
| | - Andrew Karellas
- Department of Medical Imaging, University of Arizona College of Medicine, Banner University Medical Center, Tucson, AZ
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29
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Mostafa A, Vavadi H, Uddin KMS, Zhu Q. Diffuse optical tomography using semiautomated coregistered ultrasound measurements. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:1-12. [PMID: 29260537 PMCID: PMC5746059 DOI: 10.1117/1.jbo.22.12.121610] [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: 05/07/2017] [Accepted: 12/04/2017] [Indexed: 05/18/2023]
Abstract
Diffuse optical tomography (DOT) has demonstrated huge potential in breast cancer diagnosis and treatment monitoring. DOT image reconstruction guided by ultrasound (US) improves the diffused light localization and lesion reconstruction accuracy. However, DOT reconstruction depends on tumor geometry provided by coregistered US. Experienced operators can manually measure these lesion parameters; however, training and measurement time are needed. The wide clinical use of this technique depends on its robustness and faster imaging reconstruction capability. This article introduces a semiautomated procedure that automatically extracts lesion information from US images and incorporates it into the optical reconstruction. An adaptive threshold-based image segmentation is used to obtain tumor boundaries. For some US images, posterior shadow can extend to the chest wall and make the detection of deeper lesion boundary difficult. This problem can be solved using a Hough transform. The proposed procedure was validated from data of 20 patients. Optical reconstruction results using the proposed procedure were compared with those reconstructed using extracted tumor information from an experienced user. Mean optical absorption obtained from manual measurement was 0.21±0.06 cm-1 for malignant and 0.12±0.06 cm-1 for benign cases, whereas for the proposed method it was 0.24±0.08 cm-1 and 0.12±0.05 cm-1, respectively.
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Affiliation(s)
- Atahar Mostafa
- Washington University in St.
Louis, Biomedical Engineering Department, St. Louis, Missouri,
United States
| | - Hamed Vavadi
- University of Connecticut,
Biomedical Engineering Department, Storrs, Connecticut, United
States
| | - K. M. Shihab Uddin
- Washington University in St.
Louis, Biomedical Engineering Department, St. Louis, Missouri,
United States
| | - Quing Zhu
- Washington University in St.
Louis, Biomedical Engineering Department, St. Louis, Missouri,
United States
- Address all correspondence to: Quing Zhu, E-mail:
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30
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Uddin KMS, Mostafa A, Anastasio M, Zhu Q. Two step imaging reconstruction using truncated pseudoinverse as a preliminary estimate in ultrasound guided diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2017; 8:5437-5449. [PMID: 29296479 PMCID: PMC5745094 DOI: 10.1364/boe.8.005437] [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: 08/04/2017] [Revised: 10/15/2017] [Accepted: 10/19/2017] [Indexed: 05/18/2023]
Abstract
Due to the correlated nature of diffused light, the problem of reconstructing optical properties using diffuse optical tomography (DOT) is ill-posed. US-, MRI- or x-ray-guided DOT approaches can reduce the total number of parameters to be estimated and improve optical reconstruction accuracy. However, when the target volume is large, the number of parameters to estimate can exceed the number of measurements, resulting in an underdetermined imaging model. In such cases, accurate image reconstruction is difficult and regularization methods should be employed to obtain a useful solution. In this manuscript, a simple two-step reconstruction method that can produce useful image estimates in DOT is proposed and investigated. In the first step, a truncated Moore-Penrose Pseudoinverse solution is computed to obtain a preliminary estimate of the image that can be reliably determined from the measured data; subsequently, this preliminary estimate is incorporated into the design of a penalized least squares estimator that is employed to compute the final image estimate. By use of phantom data, the proposed method was demonstrated to yield more accurate images than those produced by conventional reconstruction methods. The method was also evaluated with clinical data that included 10 benign and 10 malignant cases. The capability of reconstructing high contrast malignant lesions was demonstrated to be improved by use of the proposed method.
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31
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Zouaoui J, Di Sieno L, Hervé L, Pifferi A, Farina A, Mora AD, Derouard J, Dinten JM. Chromophore decomposition in multispectral time-resolved diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2017; 8:4772-4787. [PMID: 29082101 PMCID: PMC5654816 DOI: 10.1364/boe.8.004772] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 08/10/2017] [Accepted: 08/31/2017] [Indexed: 05/04/2023]
Abstract
Multicomponent phantom measurements are carried out to evaluate the ability of multispectral time domain diffuse optical tomography in reflectance geometry to quantify the position and the composition of small heterogeneities at depths of 1-1.5 cm in turbid media. Time-resolved data were analyzed with the Mellin-Laplace transform. Results show good localization and correct composition gradation of objects but still a lack of absolute material composition accuracy when no a priori geometry information is known.
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Affiliation(s)
- Judy Zouaoui
- Univ. Grenoble Alpes, F-38000 Grenoble, France, CEA, LETI, MINATEC Campus, F-38054 Grenoble, France
| | - Laura Di Sieno
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, Milano I-20133, Italy
| | - Lionel Hervé
- Univ. Grenoble Alpes, F-38000 Grenoble, France, CEA, LETI, MINATEC Campus, F-38054 Grenoble, France
| | - Antonio Pifferi
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, Milano I-20133, Italy
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, Milano I-20133, Italy
| | - Andrea Farina
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, Milano I-20133, Italy
| | - Alberto Dalla Mora
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, Milano I-20133, Italy
| | | | - Jean-Marc Dinten
- Univ. Grenoble Alpes, F-38000 Grenoble, France, CEA, LETI, MINATEC Campus, F-38054 Grenoble, France
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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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33
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Lim EA, Gunther JE, Kim HK, Flexman M, Hibshoosh H, Crew K, Taback B, Campbell J, Kalinsky K, Hielscher A, Hershman DL. Diffuse optical tomography changes correlate with residual cancer burden after neoadjuvant chemotherapy in breast cancer patients. Breast Cancer Res Treat 2017; 162:533-540. [PMID: 28190249 DOI: 10.1007/s10549-017-4150-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2016] [Accepted: 02/07/2017] [Indexed: 11/29/2022]
Abstract
PURPOSE Breast cancer (BC) patients who achieve a favorable residual cancer burden (RCB) after neoadjuvant chemotherapy (NACT) have an improved recurrence-free survival. Those who have an unfavorable RCB will have gone through months of ineffective chemotherapy. No ideal method exists to predict a favorable RCB early during NACT. Diffuse optical tomography (DOT) is a novel imaging modality that uses near-infrared light to assess hemoglobin concentrations within breast tumors. We hypothesized that the 2-week percent change in DOT-measured hemoglobin concentrations would associate with RCB. METHODS We conducted an observational study of 40 women with stage II-IIIC BC who received standard NACT. DOT imaging was performed at baseline and 2 weeks after treatment initiation. We evaluated the associations between the RCB index (continuous measure), class (categorical 0, I, II, III), and response (RCB class 0/I = favorable, RCB class II/III = unfavorable) with changes in DOT-measured hemoglobin concentrations. RESULTS The RCB index correlated significantly with the 2-week percent change in oxyhemoglobin [HbO2] (r = 0.5, p = 0.003), deoxyhemoglobin [Hb] (r = 0.37, p = 0.03), and total hemoglobin concentrations [HbT] (r = 0.5, p = 0.003). The RCB class and response significantly associated with the 2-week percent change in [HbO2] (p ≤ 0.01) and [HbT] (p ≤ 0.02). [HbT] 2-week percent change had sensitivity, specificity, positive, and negative predictive values for a favorable RCB response of 86.7, 68.4, 68.4, and 86.7%, respectively. CONCLUSION The 2-week percent change in DOT-measured hemoglobin concentrations was associated with the RCB index, class, and response. DOT may help guide NACT for women with BC.
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Affiliation(s)
- Emerson A Lim
- Division of Hematology/Oncology, Department of Medicine, Columbia University Medical Center, 161 Fort Washington Avenue, 9th Floor, New York, NY, 10032, USA.
| | - Jacqueline E Gunther
- Department of Biomedical Engineering, Columbia University, 500 West 120th Street, 341 Mudd Bldg, New York, NY, 10027, USA
| | - Hyun K Kim
- Department of Radiology, Columbia University, 650 West 168th Street, Black Building, Rm 1727, New York, NY, 10032, USA
| | - Molly Flexman
- Philips Research Americas, 2 Canal Park, 3rd Floor, Cambridge, MA, 02141, USA
| | - Hanina Hibshoosh
- Department of Pathology and Cell Biology, Columbia University Medical Center, 630 West 168th Street, VC 14-215, New York, NY, 10032, USA
| | - Katherine Crew
- Division of Hematology/Oncology, Department of Medicine, Department of Epidemiology, Columbia University Medical Center, 161 Fort Washington Avenue, 10th Floor, New York, NY, 10032, USA
| | - Bret Taback
- Department of Surgery, Columbia University Medical Center, 161 Fort Washington Avenue, 10th Floor, New York, NY, 10032, USA
| | - Jessica Campbell
- Herbert Irving Comprehensive Cancer Center, 161 Fort Washington Avenue, Mezzanine, New York, NY, 10032, USA
| | - Kevin Kalinsky
- Division of Hematology/Oncology, Department of Medicine, Department of Epidemiology, Columbia University Medical Center, 161 Fort Washington Avenue, 10th Floor, New York, NY, 10032, USA
| | - Andreas Hielscher
- Department of Biomedical Engineering, Columbia University, Engineering Terrace 351, Mail Code 8904, New York, NY, 10027, USA
| | - Dawn L Hershman
- Division of Hematology/Oncology, Department of Medicine, Department of Epidemiology, Columbia University Medical Center, 161 Fort Washington Avenue, 10th Floor, New York, NY, 10032, USA
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Althobaiti M, Vavadi H, Zhu Q. Diffuse optical tomography reconstruction method using ultrasound images as prior for regularization matrix. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:26002. [PMID: 28152129 PMCID: PMC5299136 DOI: 10.1117/1.jbo.22.2.026002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Accepted: 01/12/2017] [Indexed: 05/05/2023]
Abstract
Ultrasound-guided diffuse optical tomography (DOT) is a promising imaging technique that maps hemoglobin concentrations of breast lesions to assist ultrasound (US) for cancer diagnosis and treatment monitoring. The accurate recovery of breast lesion optical properties requires an effective image reconstruction method. We introduce a reconstruction approach in which US images are encoded as prior information for regularization of the inversion matrix. The framework of this approach is based on image reconstruction package “NIRFAST.” We compare this approach to the US-guided dual-zone mesh reconstruction method, which is based on Born approximation and conjugate gradient optimization developed in our laboratory. Results were evaluated using phantoms and clinical data. This method improves classification of malignant and benign lesions by increasing malignant to benign lesion absorption contrast. The results also show improvements in reconstructed lesion shapes and the spatial distribution of absorption maps.
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Affiliation(s)
- Murad Althobaiti
- University of Connecticut, Department of Biomedical Engineering, Storrs, Connecticut, United States
| | - Hamed Vavadi
- University of Connecticut, Department of Biomedical Engineering, Storrs, Connecticut, United States
| | - Quing Zhu
- Washington University in St. Louis, Department of Biomedical Engineering, Missouri, United States
- Address all correspondence to: Quing Zhu, E-mail:
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35
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Nandy S, Mostafa A, Kumavor PD, Sanders M, Brewer M, Zhu Q. Characterizing optical properties and spatial heterogeneity of human ovarian tissue using spatial frequency domain imaging. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:101402. [PMID: 26822943 PMCID: PMC4728740 DOI: 10.1117/1.jbo.21.10.101402] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 12/17/2015] [Indexed: 05/15/2023]
Abstract
A spatial frequency domain imaging (SFDI) system was developed for characterizing ex vivo human ovarian tissue using wide-field absorption and scattering properties and their spatial heterogeneities. Based on the observed differences between absorption and scattering images of different ovarian tissue groups, six parameters were quantitatively extracted. These are the mean absorption and scattering, spatial heterogeneities of both absorption and scattering maps measured by a standard deviation, and a fitting error of a Gaussian model fitted to normalized mean Radon transform of the absorption and scattering maps. A logistic regression model was used for classification of malignant and normal ovarian tissues. A sensitivity of 95%, specificity of 100%, and area under the curve of 0.98 were obtained using six parameters extracted from the SFDI images. The preliminary results demonstrate the diagnostic potential of the SFDI method for quantitative characterization of wide-field optical properties and the spatial distribution heterogeneity of human ovarian tissue. SFDI could be an extremely robust and valuable tool for evaluation of the ovary and detection of neoplastic changes of ovarian cancer.
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Affiliation(s)
- Sreyankar Nandy
- University of Connecticut, Biomedical Engineering Department, 371 Fairfield Way, U-4157, Storrs, Connecticut 06269-4157, United States
| | - Atahar Mostafa
- University of Connecticut, Department of Electrical and Computer Engineering, 371 Fairfield Way, U-4157, Storrs, Connecticut 06269-4157, United States
| | - Patrick D Kumavor
- University of Connecticut, Biomedical Engineering Department, 371 Fairfield Way, U-4157, Storrs, Connecticut 06269-4157, United States
| | - Melinda Sanders
- University of Connecticut Health Center, Pathology Department, Farmington, Connecticut 06030, United States
| | - Molly Brewer
- University of Connecticut Health Center, Division of Gynecologic Oncology, Farmington, Connecticut 06030, United States
| | - Quing Zhu
- University of Connecticut, Biomedical Engineering Department, 371 Fairfield Way, U-4157, Storrs, Connecticut 06269-4157, United States
- University of Connecticut, Department of Electrical and Computer Engineering, 371 Fairfield Way, U-4157, Storrs, Connecticut 06269-4157, United States
- Address all correspondence to: Quing Zhu, E-mail:
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Vavadi H, Zhu Q. Automated data selection method to improve robustness of diffuse optical tomography for breast cancer imaging. BIOMEDICAL OPTICS EXPRESS 2016; 7:4007-4020. [PMID: 27867711 PMCID: PMC5102542 DOI: 10.1364/boe.7.004007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 08/16/2016] [Accepted: 09/03/2016] [Indexed: 05/18/2023]
Abstract
Imaging-guided 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 of breast cancers. However, diffused light measurements are sensitive to artifacts caused by outliers and errors in measurements due to probe-tissue coupling, patient and probe motions, and tissue heterogeneity. In general, pre-processing of the measurements is needed by experienced users to manually remove these outliers and therefore reduce imaging artifacts. An automated method of outlier removal, data selection, and filtering for diffuse optical tomography is introduced in this manuscript. This method consists of multiple steps to first combine several data sets collected from the same patient at contralateral normal breast and form a single robust reference data set using statistical tests and linear fitting of the measurements. The second step improves the perturbation measurements by filtering out outliers from the lesion site measurements using model based analysis. The results of 20 malignant and benign cases show similar performance between manual data processing and automated processing and improvement in tissue characterization of malignant to benign ratio by about 27%.
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Affiliation(s)
- Hamed Vavadi
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, USA
| | - Quing Zhu
- Department of Biomedical Engineering, Washington University in St. Louis, USA
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Hoshi Y, Yamada Y. Overview of diffuse optical tomography and its clinical applications. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:091312. [PMID: 27420810 DOI: 10.1117/1.jbo.21.9.091312] [Citation(s) in RCA: 80] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 06/13/2016] [Indexed: 05/23/2023]
Abstract
Near-infrared diffuse optical tomography (DOT), one of the most sophisticated optical imaging techniques for observations through biological tissue, allows 3-D quantitative imaging of optical properties, which include functional and anatomical information. With DOT, it is expected to be possible to overcome the limitations of conventional near-infrared spectroscopy (NIRS) as well as offering the potential for diagnostic optical imaging. However, DOT has been under development for more than 30 years, and the difficulties in development are attributed to the fact that light is strongly scattered and that diffusive photons are used for the image reconstruction. The DOT algorithm is based on the techniques of inverse problems. The radiative transfer equation accurately describes photon propagation in biological tissue, while, because of its high computation load, the diffusion equation (DE) is often used as the forward model. However, the DE is invalid in low-scattering and/or highly absorbing regions and in the vicinity of light sources. The inverse problem is inherently ill-posed and highly undetermined. Here, we first summarize NIRS and then describe various approaches in the efforts to develop accurate and efficient DOT algorithms and present some examples of clinical applications. Finally, we discuss the future prospects of DOT.
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Affiliation(s)
- Yoko Hoshi
- Hamamatsu University School of Medicine, Department of Biomedical Optics, Institute for Medical Photonics Research, Preeminent Medical Photonics Education and Research Center, 1-20-1 Handayama, Higashi-ku, Hamamatsu 431-3192, Japan
| | - Yukio Yamada
- University of Electro-Communications, Brain Science Inspired Life Support Research Center, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan
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Tromberg BJ, Zhang Z, Leproux A, O'Sullivan TD, Cerussi AE, Carpenter PM, Mehta RS, Roblyer D, Yang W, Paulsen KD, Pogue BW, Jiang S, Kaufman PA, Yodh AG, Chung SH, Schnall M, Snyder BS, Hylton N, Boas DA, Carp SA, Isakoff SJ, Mankoff D. Predicting Responses to Neoadjuvant Chemotherapy in Breast Cancer: ACRIN 6691 Trial of Diffuse Optical Spectroscopic Imaging. Cancer Res 2016; 76:5933-5944. [PMID: 27527559 DOI: 10.1158/0008-5472.can-16-0346] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 07/03/2016] [Indexed: 02/03/2023]
Abstract
The prospective multicenter ACRIN 6691 trial was designed to evaluate whether changes from baseline to mid-therapy in a diffuse optical spectroscopic imaging (DOSI)-derived imaging endpoint, the tissue optical index (TOI), predict pathologic complete response (pCR) in women undergoing breast cancer neoadjuvant chemotherapy (NAC). DOSI instruments were constructed at the University of California, Irvine (Irvine, CA), and delivered to six institutions where 60 subjects with newly diagnosed breast tumors (at least 2 cm in the longest dimension) were enrolled over a 2-year period. Bedside DOSI images of the tissue concentrations of deoxy-hemoglobin (ctHHb), oxy-hemoglobin (ctHbO2), water (ctH2O), lipid, and TOI (ctHHb × ctH2O/lipid) were acquired on both breasts up to four times during NAC treatment: baseline, 1-week, mid-point, and completion. Of the 34 subjects (mean age 48.4 ± 10.7 years) with complete, evaluable data from both normal and tumor-containing breast, 10 (29%) achieved pCR as determined by central pathology review. The percent change in tumor-to-normal TOI ratio (%TOITN) from baseline to mid-therapy ranged from -82% to 321%, with a median of -36%. Using pCR as the reference standard and ROC curve methodology, %TOITN AUC was 0.60 (95% CI, 0.39-0.81). In the cohort of 17 patients with baseline tumor oxygen saturation (%StO2) greater than the 77% population median, %TOITN AUC improved to 0.83 (95% CI, 0.63-1.00). We conclude that the combination of baseline functional properties and dynamic optical response shows promise for clinical outcome prediction. Cancer Res; 76(20); 5933-44. ©2016 AACR.
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Affiliation(s)
- Bruce J Tromberg
- Beckman Laser Institute and Medical Clinic, University of California Irvine, Irvine, California.
| | - Zheng Zhang
- Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Anaïs Leproux
- Beckman Laser Institute and Medical Clinic, University of California Irvine, Irvine, California
| | - Thomas D O'Sullivan
- Beckman Laser Institute and Medical Clinic, University of California Irvine, Irvine, California
| | - Albert E Cerussi
- Beckman Laser Institute and Medical Clinic, University of California Irvine, Irvine, California
| | | | - Rita S Mehta
- Department of Medicine, University of California Irvine, Irvine, California
| | - Darren Roblyer
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Wei Yang
- Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Keith D Paulsen
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Brian W Pogue
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Shudong Jiang
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire
| | - Peter A Kaufman
- Section of Hematology and Oncology, Dartmouth-Hitchcock Medical Center, Norris Cotton Cancer Center, Lebanon, New Hampshire
| | - Arjun G Yodh
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania
| | - So Hyun Chung
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mitchell Schnall
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Bradley S Snyder
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Nola Hylton
- Department of Radiology, University of California, San Francisco, California
| | - David A Boas
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Stefan A Carp
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Steven J Isakoff
- Hematology Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - David Mankoff
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
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Tran WT, Childs C, Chin L, Slodkowska E, Sannachi L, Tadayyon H, Watkins E, Wong SL, Curpen B, Kaffas AE, Al-Mahrouki A, Sadeghi-Naini A, Czarnota GJ. Multiparametric monitoring of chemotherapy treatment response in locally advanced breast cancer using quantitative ultrasound and diffuse optical spectroscopy. Oncotarget 2016; 7:19762-80. [PMID: 26942698 PMCID: PMC4991417 DOI: 10.18632/oncotarget.7844] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Accepted: 02/05/2016] [Indexed: 11/25/2022] Open
Abstract
PURPOSE This study evaluated pathological response to neoadjuvant chemotherapy using quantitative ultrasound (QUS) and diffuse optical spectroscopy imaging (DOSI) biomarkers in locally advanced breast cancer (LABC). MATERIALS AND METHODS The institution's ethics review board approved this study. Subjects (n = 22) gave written informed consent prior to participating. US and DOSI data were acquired, relative to the start of neoadjuvant chemotherapy, at weeks 0, 1, 4, 8 and preoperatively. QUS parameters including the mid-band fit (MBF), 0-MHz intercept (SI), and the spectral slope (SS) were determined from tumor ultrasound data using spectral analysis. In the same patients, DOSI was used to measure parameters relating to tumor hemoglobin and composition. Discriminant analysis and receiver-operating characteristic (ROC) analysis was used to classify clinical and pathological response during treatment and to estimate the area under the curve (AUC). Additionally, multivariate analysis was carried out for pairwise QUS/DOSI parameter combinations using a logistic regression model. RESULTS Individual QUS and DOSI parameters, including the (SI), oxy-hemoglobin (HbO2), and total hemoglobin (HbT) were significant markers for response after one week of treatment (p < 0.01). Multivariate (pairwise) combinations increased the sensitivity, specificity and AUC at this time; the SI + HbO2 showed a sensitivity/specificity of 100%, and an AUC of 1.0. CONCLUSIONS QUS and DOSI demonstrated potential as coincident markers for treatment response and may potentially facilitate response-guided therapies. Multivariate QUS and DOSI parameters increased the sensitivity and specificity of classifying LABC patients as early as one week after treatment.
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Affiliation(s)
- William T. Tran
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
- Centre for Health and Social Care Research, Sheffield Hallam University, Sheffield, UK
| | - Charmaine Childs
- Centre for Health and Social Care Research, Sheffield Hallam University, Sheffield, UK
| | - Lee Chin
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
| | | | - Lakshmanan Sannachi
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Hadi Tadayyon
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Elyse Watkins
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
| | | | - Belinda Curpen
- Division of Radiology, Sunnybrook Hospital, Toronto, Canada
| | - Ahmed El Kaffas
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
| | - Azza Al-Mahrouki
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
| | - Ali Sadeghi-Naini
- Department of Radiation Oncology, Sunnybrook Hospital, Toronto, Canada
| | - Gregory J. Czarnota
- Department of Radiation Oncology, University of Toronto, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
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