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Zhi X, Sun Y, Cai F, Wang S, Gao H, Wu F, Zhang L, Shen Z. Oxidized Low-Density Lipoprotein (Ox-LDL)-Triggered Double-Lock Probe for Spatiotemporal Lipoprotein Oxidation and Atherosclerotic Plaque Imaging. Adv Healthc Mater 2023; 12:e2301595. [PMID: 37557912 DOI: 10.1002/adhm.202301595] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/25/2023] [Indexed: 08/11/2023]
Abstract
Low-density lipoprotein (LDL), especially oxidative modified LDL (Ox-LDL), is the key risk factor for plaque accumulation and the development of cardiovascular disease. Herein, a highly specific Ox-LDL-triggered fluorogenic-colorimetric probe Pro-P1 is developed for visualizing the oxidation and aggregation progress of lipoproteins and plaque. A series of green fluorescent protein chromophores with modified donor-acceptor structures, containing carbazole as an electron donor and various substituents including pyridine-vinyl (P1), phenol-vinyl (P2), N, N-dimethylaniline-vinyl (P3), and thiophene-vinyl (P4), have been synthesized and evaluated. Emission spectroscopy and theoretical calculations of P1-P4 indicate that P1 shows enhanced green fluorescence (λem = 560 nm) by inhibiting its twisted intramolecular charge transfer in the presence of Ox-LDL. This feature allows the selection of P1 as a sensitive probe to directly visualize ferroptosis and Cu2+ -mediated LDL oxidative aggregation via in situ formation of fluorophore-bound Ox-LDL in living cells. The red-emissive probe Pro-P1 (λem = 660 nm) is prepared via borate protection of P1, which can be cleaved into P1 under high expression of HOCl and Ox-LDL condition at the lesion site, resulting in enhanced green emission. The plaque area and size with clear boundaries can be delineated by colorimetric fluorescence imaging and fluorescence lifetime imaging with precise differentiation.
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Affiliation(s)
- Xu Zhi
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Yufen Sun
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Fangjian Cai
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Sisi Wang
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Hu Gao
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Fan Wu
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Lei Zhang
- School of Chemistry and Chemical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
| | - Zhen Shen
- State Key Laboratory of Coordination Chemistry, Collaborative Innovation Center of Advanced Microstructures, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
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Predicting EGFR mutational status from pathology images using a real-world dataset. Sci Rep 2023; 13:4404. [PMID: 36927889 PMCID: PMC10020556 DOI: 10.1038/s41598-023-31284-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 03/09/2023] [Indexed: 03/18/2023] Open
Abstract
Treatment of non-small cell lung cancer is increasingly biomarker driven with multiple genomic alterations, including those in the epidermal growth factor receptor (EGFR) gene, that benefit from targeted therapies. We developed a set of algorithms to assess EGFR status and morphology using a real-world advanced lung adenocarcinoma cohort of 2099 patients with hematoxylin and eosin (H&E) images exhibiting high morphological diversity and low tumor content relative to public datasets. The best performing EGFR algorithm was attention-based and achieved an area under the curve (AUC) of 0.870, a negative predictive value (NPV) of 0.954 and a positive predictive value (PPV) of 0.410 in a validation cohort reflecting the 15% prevalence of EGFR mutations in lung adenocarcinoma. The attention model outperformed a heuristic-based model focused exclusively on tumor regions, and we show that although the attention model also extracts signal primarily from tumor morphology, it extracts additional signal from non-tumor tissue regions. Further analysis of high-attention regions by pathologists showed associations of predicted EGFR negativity with solid growth patterns and higher peritumoral immune presence. This algorithm highlights the potential of deep learning tools to provide instantaneous rule-out screening for biomarker alterations and may help prioritize the use of scarce tissue for biomarker testing.
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OUP accepted manuscript. Eur Heart J Cardiovasc Imaging 2022; 23:465-475. [DOI: 10.1093/ehjci/jeab287] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/21/2021] [Indexed: 11/13/2022] Open
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Liu X, Karmarkar P, Voit D, Frahm J, Weiss CR, Kraitchman DL, Bottomley PA. Real-Time High-Resolution MRI Endoscopy at up to 10 Frames per Second. BME FRONTIERS 2021; 2021:6185616. [PMID: 37849906 PMCID: PMC10521714 DOI: 10.34133/2021/6185616] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 02/02/2021] [Indexed: 10/19/2023] Open
Abstract
Objective. Atherosclerosis is a leading cause of mortality and morbidity. Optical endoscopy, ultrasound, and X-ray offer minimally invasive imaging assessments but have limited sensitivity for characterizing disease and therapeutic response. Magnetic resonance imaging (MRI) endoscopy is a newer idea employing tiny catheter-mounted detectors connected to the MRI scanner. It can see through vessel walls and provide soft-tissue sensitivity, but its slow imaging speed limits practical applications. Our goal is high-resolution MRI endoscopy with real-time imaging speeds comparable to existing modalities. Methods. Intravascular (3 mm) transmit-receive MRI endoscopes were fabricated for highly undersampled radial-projection MRI in a clinical 3-tesla MRI scanner. Iterative nonlinear reconstruction was accelerated using graphics processor units connected via a single ethernet cable to achieve true real-time endoscopy visualization at the scanner. MRI endoscopy was performed at 6-10 frames/sec and 200-300 μm resolution in human arterial specimens and porcine vessels ex vivo and in vivo and compared with fully sampled 0.3 frames/sec and three-dimensional reference scans using mutual information (MI) and structural similarity (3-SSIM) indices. Results. High-speed MRI endoscopy at 6-10 frames/sec was consistent with fully sampled MRI endoscopy and histology, with feasibility demonstrated in vivo in a large animal model. A 20-30-fold speed-up vs. 0.3 frames/sec reference scans came at a cost of ~7% in MI and ~45% in 3-SSIM, with reduced motion sensitivity. Conclusion. High-resolution MRI endoscopy can now be performed at frame rates comparable to those of X-ray and optical endoscopy and could provide an alternative to existing modalities, with MRI's advantages of soft-tissue sensitivity and lack of ionizing radiation.
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Affiliation(s)
- Xiaoyang Liu
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
- The Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Parag Karmarkar
- The Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Dirk Voit
- Biomedizinishe NMR, Max-Plank-Institut fur Biophysikalische Chemie, Gottingen, Germany
| | - Jens Frahm
- Biomedizinishe NMR, Max-Plank-Institut fur Biophysikalische Chemie, Gottingen, Germany
| | - Clifford R. Weiss
- The Division of Interventional Radiology, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Dara L. Kraitchman
- The Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Paul A. Bottomley
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
- The Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
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Manning WJ. Journal of Cardiovascular Magnetic Resonance: 2017/2018 in review. J Cardiovasc Magn Reson 2019; 21:79. [PMID: 31884956 PMCID: PMC6936125 DOI: 10.1186/s12968-019-0594-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/14/2022] Open
Abstract
There were 89 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 76 original research papers, 4 reviews, 5 technical notes, 1 guideline, and 3 corrections. The volume was down slightly from 2017 with a corresponding 15% decrease in manuscript submissions from 405 to 346 and thus reflects a slight increase in the acceptance rate from 25 to 26%. The decrease in submissions for the year followed the initiation of the increased author processing charge (APC) for Society for Cardiovascular Magnetic Resonance (SCMR) members for manuscripts submitted after June 30, 2018. The quality of the submissions continues to be high. The 2018 JCMR Impact Factor (which is published in June 2019) was slightly lower at 5.1 (vs. 5.46 for 2017; as published in June 2018. The 2018 impact factor means that on average, each JCMR published in 2016 and 2017 was cited 5.1 times in 2018. Our 5 year impact factor was 5.82.In accordance with Open-Access publishing guidelines of BMC, the JCMR articles are published on-line in a continuus fashion in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful for the JCMR audience to annually summarize the publications into broad areas of interest or themes, so that readers can view areas of interest in a single article in relation to each other and contemporaneous JCMR publications. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, as in the past two years, I have used this publication to also convey information regarding the editorial process and as a "State of our JCMR."This is the 12th year of JCMR as an open-access publication with BMC (formerly known as Biomed Central). The timing of the JCMR transition to the open access platform was "ahead of the curve" and a tribute to the vision of Dr. Matthias Friedrich, the SCMR Publications Committee Chair and Dr. Dudley Pennell, the JCMR editor-in-chief at the time. The open-access system has dramatically increased the reading and citation of JCMR publications and I hope that you, our authors, will continue to send your very best, high quality manuscripts to JCMR for consideration. It takes a village to run a journal and I thank our very dedicated Associate Editors, Guest Editors, Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner. These efforts have allowed the JCMR to continue as the premier journal of our field. This entire process would also not be possible without the dedication and efforts of our managing editor, Diana Gethers. Finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 4th year as your editor-in-chief. It has been a tremendous experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!
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Affiliation(s)
- Warren J Manning
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
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Leiner T, Rueckert D, Suinesiaputra A, Baeßler B, Nezafat R, Išgum I, Young AA. Machine learning in cardiovascular magnetic resonance: basic concepts and applications. J Cardiovasc Magn Reson 2019; 21:61. [PMID: 31590664 PMCID: PMC6778980 DOI: 10.1186/s12968-019-0575-y] [Citation(s) in RCA: 120] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 09/02/2019] [Indexed: 12/18/2022] Open
Abstract
Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers in improving imaging efficiency, quality, image analysis and interpretation, as well as patient evaluation. We discuss recent developments in the field of ML relevant to CMR in the areas of image acquisition & reconstruction, image analysis, diagnostic evaluation and derivation of prognostic information. To date, the main impact of ML in CMR has been to significantly reduce the time required for image segmentation and analysis. Accurate and reproducible fully automated quantification of left and right ventricular mass and volume is now available in commercial products. Active research areas include reduction of image acquisition and reconstruction time, improving spatial and temporal resolution, and analysis of perfusion and myocardial mapping. Although large cohort studies are providing valuable data sets for ML training, care must be taken in extending applications to specific patient groups. Since ML algorithms can fail in unpredictable ways, it is important to mitigate this by open source publication of computational processes and datasets. Furthermore, controlled trials are needed to evaluate methods across multiple centers and patient groups.
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Affiliation(s)
- Tim Leiner
- Department of Radiology | E.01.132, Utrecht University Medical Center, Heidelberglaan 100, 3584CX Utrecht, The Netherlands
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College, London, UK
| | - Avan Suinesiaputra
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Bettina Baeßler
- Department of Radiology, University Hospital of Cologne, Cologne, Germany
- Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Centre, Harvard Medical School, Boston, MA USA
| | - Ivana Išgum
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - Alistair A. Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Department of Biomedical Engineering, King’s College London, London, UK
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Liu X, Ellens N, Williams E, Burdette EC, Karmarkar P, Weiss CR, Kraitchman D, Bottomley PA. High-resolution intravascular MRI-guided perivascular ultrasound ablation. Magn Reson Med 2019; 83:240-253. [PMID: 31402512 DOI: 10.1002/mrm.27932] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 06/24/2019] [Accepted: 07/15/2019] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop and test in animal studies ex vivo and in vivo, an intravascular (IV) MRI-guided high-intensity focused ultrasound (HIFU) ablation method for targeting perivascular pathology with minimal injury to the vessel wall. METHODS IV-MRI antennas were combined with 2- to 4-mm diameter water-cooled IV-ultrasound ablation catheters for IV-MRI on a 3T clinical MRI scanner. A software interface was developed for monitoring thermal dose with real-time MRI thermometry, and an MRI-guided ablation protocol developed by repeat testing on muscle and liver tissue ex vivo. MRI thermal dose was measured as cumulative equivalent minutes at 43°C (CEM43 ). The IV-MRI IV-HIFU protocol was then tested by targeting perivascular ablations from the inferior vena cava of 2 pigs in vivo. Thermal dose and lesions were compared by gross and histological examination. RESULTS Ex vivo experiments yielded a 6-min ablation protocol with the IV-ultrasound catheter coolant at 3-4°C, a 30 mL/min flow rate, and 7 W ablation power. In 8 experiments, 5- to 10-mm thick thermal lesions of area 0.5-2 cm2 were produced that spared 1- to 2-mm margins of tissue abutting the catheters. The radial depths, areas, and preserved margins of ablation lesions measured from gross histology were highly correlated (r ≥ 0.79) with those measured from the CEM43 = 340 necrosis threshold determined by MRI thermometry. The psoas muscle was successfully targeted in the 2 live pigs, with the resulting ablations controlled under IV-MRI guidance. CONCLUSION IV-MRI-guided, IV-HIFU has potential as a precision treatment option that could preserve critical blood vessel wall during ablation of nonresectable perivascular tumors or other pathologies.
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Affiliation(s)
- Xiaoyang Liu
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland.,Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Nicholas Ellens
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland.,Acertara Acoustic Laboratories, Longmont, Colorado
| | | | | | - Parag Karmarkar
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Clifford R Weiss
- Division of Interventional Radiology, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Dara Kraitchman
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
| | - Paul A Bottomley
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland.,Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland
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Manning WJ. Journal of Cardiovascular Magnetic Resonance 2017. J Cardiovasc Magn Reson 2018; 20:89. [PMID: 30593280 PMCID: PMC6309095 DOI: 10.1186/s12968-018-0518-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 12/06/2018] [Indexed: 02/07/2023] Open
Abstract
There were 106 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 92 original research papers, 3 reviews, 9 technical notes, and 1 Position paper, 1 erratum and 1 correction. The volume was similar to 2016 despite an increase in manuscript submissions to 405 and thus reflects a slight decrease in the acceptance rate to 26.7%. The quality of the submissions continues to be high. The 2017 JCMR Impact Factor (which is published in June 2018) was minimally lower at 5.46 (vs. 5.71 for 2016; as published in June 2017), which is the second highest impact factor ever recorded for JCMR. The 2017 impact factor means that an average, each JCMR paper that were published in 2015 and 2016 was cited 5.46 times in 2017.In accordance with Open-Access publishing of Biomed Central, the JCMR articles are published on-line in continuus fashion and in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful to annually summarize the publications into broad areas of interest or theme, so that readers can view areas of interest in a single article in relation to each other and other contemporary JCMR articles. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, I have elected to use this format to convey information regarding the editorial process to the readership.I hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your very best, high quality manuscripts to JCMR for consideration. I thank our very dedicated Associate Editors, Guest Editors, and Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner and that the JCMR continues to be recognized as the forefront journal of our field. And finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 3rd year as your editor-in-chief. It has been a tremendous learning experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!
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Affiliation(s)
- Warren J Manning
- Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA, 02215, USA.
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