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China D, Feng Z, Hooshangnejad H, Sforza D, Vagdargi P, Bell MAL, Uneri A, Sisniega A, Ding K. FLEX: FLexible Transducer With External Tracking for Ultrasound Imaging With Patient-Specific Geometry Estimation. IEEE Trans Biomed Eng 2024; 71:1298-1307. [PMID: 38048239 PMCID: PMC10998498 DOI: 10.1109/tbme.2023.3333216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2023]
Abstract
Flexible array transducers can adapt to patient-specific geometries during real-time ultrasound (US) image-guided therapy monitoring. This makes the system radiation-free and less user-dependency. Precise estimation of the flexible transducer's geometry is crucial for the delay-and-sum (DAS) beamforming algorithm to reconstruct B-mode US images. The primary innovation of this research is to build a system named FLexible transducer with EXternal tracking (FLEX) to estimate the position of each element of the flexible transducer and reconstruct precise US images. FLEX utilizes customized optical markers and a tracker to monitor the probe's geometry, employing a polygon fitting algorithm to estimate the position and azimuth angle of each transducer element. Subsequently, the traditional DAS algorithm processes the delay estimation from the tracked element position, reconstructing US images from radio-frequency (RF) channel data. The proposed method underwent evaluation on phantoms and cadaveric specimens, demonstrating its clinical feasibility. Deviations in tracked probe geometry compared to ground truth were minimal, measuring 0.50 ± 0.29 mm for the CIRS phantom, 0.54 ± 0.35 mm for the deformable phantom, and 0.36 ± 0.24 mm on the cadaveric specimen. Reconstructing the US image using tracked probe geometry significantly outperformed the untracked geometry, as indicated by a Dice score of 95.1 ± 3.3% versus 62.3 ± 9.2% for the CIRS phantom. The proposed method achieved high accuracy (<0.5 mm error) in tracking the element position for various random curvatures applicable for clinical deployment. The evaluation results show that the radiation-free proposed method can effectively reconstruct US images and assist in monitoring image-guided therapy with minimal user dependency.
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Kyme AZ, Fulton RR. Motion estimation and correction in SPECT, PET and CT. Phys Med Biol 2021; 66. [PMID: 34102630 DOI: 10.1088/1361-6560/ac093b] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 06/08/2021] [Indexed: 11/11/2022]
Abstract
Patient motion impacts single photon emission computed tomography (SPECT), positron emission tomography (PET) and X-ray computed tomography (CT) by giving rise to projection data inconsistencies that can manifest as reconstruction artifacts, thereby degrading image quality and compromising accurate image interpretation and quantification. Methods to estimate and correct for patient motion in SPECT, PET and CT have attracted considerable research effort over several decades. The aims of this effort have been two-fold: to estimate relevant motion fields characterizing the various forms of voluntary and involuntary motion; and to apply these motion fields within a modified reconstruction framework to obtain motion-corrected images. The aims of this review are to outline the motion problem in medical imaging and to critically review published methods for estimating and correcting for the relevant motion fields in clinical and preclinical SPECT, PET and CT. Despite many similarities in how motion is handled between these modalities, utility and applications vary based on differences in temporal and spatial resolution. Technical feasibility has been demonstrated in each modality for both rigid and non-rigid motion, but clinical feasibility remains an important target. There is considerable scope for further developments in motion estimation and correction, and particularly in data-driven methods that will aid clinical utility. State-of-the-art machine learning methods may have a unique role to play in this context.
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Affiliation(s)
- Andre Z Kyme
- School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales, AUSTRALIA
| | - Roger R Fulton
- Sydney School of Health Sciences, The University of Sydney, Sydney, New South Wales, AUSTRALIA
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Tavitian B, Perez-Liva M. Hybrid PET-CT-Ultrasound Imaging. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00020-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Beyer T, Bidaut L, Dickson J, Kachelriess M, Kiessling F, Leitgeb R, Ma J, Shiyam Sundar LK, Theek B, Mawlawi O. What scans we will read: imaging instrumentation trends in clinical oncology. Cancer Imaging 2020; 20:38. [PMID: 32517801 PMCID: PMC7285725 DOI: 10.1186/s40644-020-00312-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 04/17/2020] [Indexed: 12/16/2022] Open
Abstract
Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", and - through the wider adoption of advanced analysis, including machine learning approaches and a "big data" concept - move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.
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Affiliation(s)
- Thomas Beyer
- QIMP Team, Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Währinger Gürtel 18-20/4L, 1090, Vienna, Austria.
| | - Luc Bidaut
- College of Science, University of Lincoln, Lincoln, UK
| | - John Dickson
- Institute of Nuclear Medicine, University College London Hospital, London, UK
| | - Marc Kachelriess
- Division of X-ray imaging and CT, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, DE, Germany
| | - Fabian Kiessling
- Institute for Experimental Molecular Imaging, University Clinic and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, DE, Germany
- Fraunhofer Institute for Digital Medicine MEVIS, Am Fallturm 1, 28359, Bremen, DE, Germany
| | - Rainer Leitgeb
- Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, AT, Austria
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lalith Kumar Shiyam Sundar
- QIMP Team, Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Währinger Gürtel 18-20/4L, 1090, Vienna, Austria
| | - Benjamin Theek
- Institute for Experimental Molecular Imaging, University Clinic and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, DE, Germany
- Fraunhofer Institute for Digital Medicine MEVIS, Am Fallturm 1, 28359, Bremen, DE, Germany
| | - Osama Mawlawi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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Elangovan H, Yao W, Nicolaides K. A Multimodality Navigation System for Endoscopic Fetal Surgery: A Phantom Case Study for Congenital Diaphragmatic Hernia. Surg Innov 2018; 26:27-36. [PMID: 30484382 DOI: 10.1177/1553350618813244] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This article presents a multi-modality tracking and navigation system achieved by merging optical tracking and ultrasound imaging into a novel navigation software to help in surgical pre-planning and real-time target setting and guidance. Fetal surgeries require extensive experience in coordination of hand-eye-ultrasound-surgical equipment, knowledge, and precise assessment of relative anatomy. While there are navigation systems available for similar constrained working spaces in arthroscopic and cardiovascular procedures, fetal minimally invasive surgery does not yet have a dedicated navigation platform capable of supporting robotic instruments that can be adapted to the set of unique procedures. This article discusses the testing of the novel multi-modality navigation system in a phantom environment developed for this purpose. The outcomes suggest that the subjects demonstrated an increase in average reaching accuracy by about 60% and an overall reduction in time taken by 33.6%. They also showed higher levels of confidence in reaching the targets, which was visualised from the pattern of trajectory of movements during the procedure. To evaluate the navigation system, a phantom surgical environment was found necessary. Therefore, the article also discusses the details of the development of a fetal phantom environment for congenital diaphragmatic hernia for surgical testing, evaluation, and training. A surgical procedure was conducted on the phantom using the proposed tracking navigation system and using only ultrasound.
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Affiliation(s)
| | - Wei Yao
- 1 University of Strathclyde, Glasgow, Scotland, UK
| | - Kypros Nicolaides
- 2 King's College Hospital, Fetal Medicine Research Institute, London, UK
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Provost J, Garofalakis A, Sourdon J, Bouda D, Berthon B, Viel T, Perez-Liva M, Lussey-Lepoutre C, Favier J, Correia M, Pernot M, Chiche J, Pouysségur J, Tanter M, Tavitian B. Simultaneous positron emission tomography and ultrafast ultrasound for hybrid molecular, anatomical and functional imaging. Nat Biomed Eng 2018; 2:85-94. [PMID: 31015628 DOI: 10.1038/s41551-018-0188-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Accepted: 12/23/2017] [Indexed: 12/21/2022]
Abstract
Positron emission tomography-computed tomography (PET-CT) is the most sensitive molecular imaging modality, but it does not easily allow for rapid temporal acquisition. Ultrafast ultrasound imaging (UUI)-a recently introduced technology based on ultrasonic holography-leverages frame rates of up to several thousand images per second to quantitatively map, at high resolution, haemodynamic, biomechanical, electrophysiological and structural parameters. Here, we describe a pre-clinical scanner that registers PET-CT and UUI volumes acquired simultaneously and offers multiple combinations for imaging. We demonstrate that PET-CT-UUI allows for simultaneous images of the vasculature and metabolism during tumour growth in mice and rats, as well as for synchronized multi-modal cardiac cine-loops. Combined anatomical, functional and molecular imaging with PET-CT-UUI represents a high-performance and clinically translatable technology for biomedical research.
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Affiliation(s)
- Jean Provost
- Institut Langevin, Ecole Supérieure de Physique et de Chimie Industrielles, Paris Sciences and Letters Research University CNRS UMR 7587 Inserm U979, Inserm Technology Research Accelerator in Biomedical Ultrasound, Paris, France
| | - Anikitos Garofalakis
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Joevin Sourdon
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Damien Bouda
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Béatrice Berthon
- Institut Langevin, Ecole Supérieure de Physique et de Chimie Industrielles, Paris Sciences and Letters Research University CNRS UMR 7587 Inserm U979, Inserm Technology Research Accelerator in Biomedical Ultrasound, Paris, France
| | - Thomas Viel
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Mailyn Perez-Liva
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Charlotte Lussey-Lepoutre
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Pierre et Marie Curie, Paris, France.,Nuclear Medicine Department, Pitié-Salpêtrière Hospital, Paris, France
| | - Judith Favier
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France.,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Mafalda Correia
- Institut Langevin, Ecole Supérieure de Physique et de Chimie Industrielles, Paris Sciences and Letters Research University CNRS UMR 7587 Inserm U979, Inserm Technology Research Accelerator in Biomedical Ultrasound, Paris, France
| | - Mathieu Pernot
- Institut Langevin, Ecole Supérieure de Physique et de Chimie Industrielles, Paris Sciences and Letters Research University CNRS UMR 7587 Inserm U979, Inserm Technology Research Accelerator in Biomedical Ultrasound, Paris, France
| | - Johanna Chiche
- Faculté de Médecine, Université de Nice Sophia Antipolis, Nice, France.,Équipe Contrôle Métabolique des Morts Cellulaires, Inserm, U1065, Centre Méditerranéen de Médecine Moléculaire, Nice, France
| | - Jacques Pouysségur
- Institute for Research on Cancer and Aging, Université de Nice Sophia Antipolis, Centre Antoine Lacassagne, Nice, France.,Department of Medical Biology, Centre Scientifique de Monaco, Monaco, Monaco
| | - Mickael Tanter
- Institut Langevin, Ecole Supérieure de Physique et de Chimie Industrielles, Paris Sciences and Letters Research University CNRS UMR 7587 Inserm U979, Inserm Technology Research Accelerator in Biomedical Ultrasound, Paris, France.
| | - Bertrand Tavitian
- Inserm, UMR970, Paris Cardiovascular Research Center, Paris, France. .,Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France. .,Department of Radiology, Georges Pompidou European Hospital, Paris, France.
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Brandner ED, Chetty IJ, Giaddui TG, Xiao Y, Huq MS. Motion management strategies and technical issues associated with stereotactic body radiotherapy of thoracic and upper abdominal tumors: A review from NRG oncology. Med Phys 2017; 44:2595-2612. [PMID: 28317123 DOI: 10.1002/mp.12227] [Citation(s) in RCA: 99] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 01/23/2017] [Accepted: 03/10/2017] [Indexed: 12/11/2022] Open
Abstract
The efficacy of stereotactic body radiotherapy (SBRT) has been well demonstrated. However, it presents unique challenges for accurate planning and delivery especially in the lungs and upper abdomen where respiratory motion can be significantly confounding accurate targeting and avoidance of normal tissues. In this paper, we review the current literature on SBRT for lung and upper abdominal tumors with particular emphasis on addressing respiratory motion and its affects. We provide recommendations on strategies to manage motion for different, patient-specific situations. Some of the recommendations will potentially be adopted to guide clinical trial protocols.
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Affiliation(s)
- Edward D Brandner
- Department of Radiation Oncology, University of Pittsburgh Cancer Institute and UPMC CancerCenter, Pittsburgh, PA, 15232, USA
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Tawfik G Giaddui
- Sidney Kimmel Cancer Center, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Ying Xiao
- Imaging and Radiation Oncology Core (IROC), University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - M Saiful Huq
- Department of Radiation Oncology, University of Pittsburgh Cancer Institute and UPMC CancerCenter, Pittsburgh, PA, 15232, USA
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Ipsen S, Bruder R, O'Brien R, Keall PJ, Schweikard A, Poulsen PR. Online 4D ultrasound guidance for real-time motion compensation by MLC tracking. Med Phys 2017; 43:5695. [PMID: 27782689 DOI: 10.1118/1.4962932] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
PURPOSE With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom. METHODS A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2%/2 mm γ-tests. RESULTS The overall tracking system latency was 172 ms. The mean 2D root-mean-square tracking error was 1.03 mm (0.80 mm prostate, 1.31 mm lung). MLC tracking improved the dose delivery in all cases with an overall reduction in the γ-failure rate of 91.2% (3%/3 mm) and 89.9% (2%/2 mm) compared to no motion compensation. Low modulation VMAT plans had no (3%/3 mm) or minimal (2%/2 mm) residual γ-failures while tracking reduced the γ-failure rate from 17.4% to 2.8% (3%/3 mm) and from 33.9% to 6.5% (2%/2 mm) for plans with high modulation. CONCLUSIONS Real-time 4D ultrasound tracking was successfully integrated with online MLC tracking for the first time. The developed framework showed an accuracy and latency comparable with other MLC tracking methods while holding the potential to measure and adapt to target motion, including rotation and deformation, noninvasively.
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Affiliation(s)
- Svenja Ipsen
- Institute for Robotics and Cognitive Systems, University of Luebeck, Luebeck 23562, Germany
| | - Ralf Bruder
- Institute for Robotics and Cognitive Systems, University of Luebeck, Luebeck 23562, Germany
| | - Rick O'Brien
- Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006, Australia
| | - Paul J Keall
- Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006, Australia
| | - Achim Schweikard
- Institute for Robotics and Cognitive Systems, University of Luebeck, Luebeck 23562, Germany
| | - Per R Poulsen
- Department of Clinical Medicine, Aarhus University and Department of Oncology, Aarhus University Hospital, Aarhus 8000, Denmark
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