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Journal articles on the topic 'Multi-modal imaging'

To see the other types of publications on this topic, follow the link: Multi-modal imaging.

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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1

Mohankumar, Arthi, and Roshni Mohan. "Multi-Modal imaging of torpedo maculopathy." TNOA Journal of Ophthalmic Science and Research 61, no. 1 (2023): 143. http://dx.doi.org/10.4103/tjosr.tjosr_9_22.

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Alilet, Mona, Julien Behr, Jean-Philippe Nueffer, Benoit Barbier-Brion, and Sébastien Aubry. "Multi-modal imaging of the subscapularis muscle." Insights into Imaging 7, no. 6 (October 17, 2016): 779–91. http://dx.doi.org/10.1007/s13244-016-0526-1.

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Watkin, Kenneth L., and Michael A. McDonald. "Multi-Modal Contrast Agents." Academic Radiology 9, no. 2 (February 2002): S285—S289. http://dx.doi.org/10.1016/s1076-6332(03)80205-2.

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Merkle, Arno, Leah L. Lavery, Jeff Gelb, and Nicholas Piché. "Fusing Multi-scale and Multi-modal 3D Imaging and Characterization." Microscopy and Microanalysis 20, S3 (August 2014): 820–21. http://dx.doi.org/10.1017/s1431927614005820.

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Blinowska, Katarzyna, Gernot Müller-Putz, Vera Kaiser, Laura Astolfi, Katrien Vanderperren, Sabine Van Huffel, and Louis Lemieux. "Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration." Computational Intelligence and Neuroscience 2009 (2009): 1–10. http://dx.doi.org/10.1155/2009/813607.

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Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship.

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Dong, Di, Jie Tian, Yakang Dai, Guorui Yan, Fei Yang, and Ping Wu. "Unified reconstruction framework for multi-modal medical imaging." Journal of X-Ray Science and Technology 19, no. 1 (2011): 111–26. http://dx.doi.org/10.3233/xst-2010-0281.

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7

Bansal, Reema, Nitin Kumar, and Monika Balyan. "Multi-modal imaging in benign familial fleck retina." Indian Journal of Ophthalmology 69, no. 6 (2021): 1641. http://dx.doi.org/10.4103/ijo.ijo_633_21.

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Merk, Vivian, Johan Decelle, Si Chen, and Derk Joester. "Multi-modal correlative chemical imaging of aquatic microorganisms." Microscopy and Microanalysis 27, S1 (July 30, 2021): 298–300. http://dx.doi.org/10.1017/s1431927621001641.

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9

Cole, Laura M., Joshua Handley, Emmanuelle Claude, Catherine J. Duckett, Hardeep S. Mudhar, Karen Sisley, and Malcolm R. Clench. "Multi-Modal Mass Spectrometric Imaging of Uveal Melanoma." Metabolites 11, no. 8 (August 23, 2021): 560. http://dx.doi.org/10.3390/metabo11080560.

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Matrix assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI), was used to obtain images of lipids and metabolite distribution in formalin fixed and embedded in paraffin (FFPE) whole eye sections containing primary uveal melanomas (UM). Using this technique, it was possible to obtain images of lysophosphatidylcholine (LPC) type lipid distribution that highlighted the tumour regions. Laser ablation inductively coupled plasma mass spectrometry images (LA-ICP-MS) performed on UM sections showed increases in copper within the tumour periphery and intratumoural zinc in tissue from patients with poor prognosis. These preliminary data indicate that multi-modal MSI has the potential to provide insights into the role of trace metals and cancer metastasis.

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Beckus, Andre, Alexandru Tamasan, and George K. Atia. "Multi-Modal Non-Line-of-Sight Passive Imaging." IEEE Transactions on Image Processing 28, no. 7 (July 2019): 3372–82. http://dx.doi.org/10.1109/tip.2019.2896517.

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11

Lee, Junwon, Jeremy Rogers, Michael Descour, Elizabeth Hsu, Jesse Aaron, Konstantin Sokolov, and Rebecca Richards-Kortum. "Imaging quality assessment of multi-modal miniature microscope." Optics Express 11, no. 12 (June 16, 2003): 1436. http://dx.doi.org/10.1364/oe.11.001436.

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Sawai, Toshiki, Masato Matsubayashi, Fumiya Uchida, Masatoshi Miyahara, and Hideo Nishikawa. "Quadricuspid pulmonary valve evaluated by multi-modal imaging." European Heart Journal - Cardiovascular Imaging 19, no. 12 (July 31, 2018): 1333. http://dx.doi.org/10.1093/ehjci/jey113.

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Medina-Valdés, L., M. Pérez-Liva, J. Camacho, J. M. Udías, J. L. Herraiz, and N. González-Salido. "Multi-modal Ultrasound Imaging for Breast Cancer Detection." Physics Procedia 63 (2015): 134–40. http://dx.doi.org/10.1016/j.phpro.2015.03.022.

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14

Phillips, N. W., M. W. M. Jones, G. van Riessen, D. J. Vine, B. Abbey, and F. Hofmann. "Multi-modal Nanoscale Imaging of Materials and Biology." Microscopy and Microanalysis 24, S2 (August 2018): 32–33. http://dx.doi.org/10.1017/s1431927618012588.

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Hathon, Lori A., Michael T. Myers, Mike Dixon, and Kultaransingh Hooghan. "Multi-modal SEM Imaging for Shale Reservoir Characterization." Microscopy and Microanalysis 23, S1 (July 2017): 2116–17. http://dx.doi.org/10.1017/s1431927617011242.

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16

Schall, Ulrich, Paul E. Rasser, Ross Fulham, Juanita Todd, Patricia T. Michie, Philip B. Ward, Patrick Johnston, and Paul M. Thompson. "PHENOTYPING OF SCHIZOPHRENIA BY MULTI-MODAL BRAIN IMAGING." Schizophrenia Research 117, no. 2-3 (April 2010): 480–81. http://dx.doi.org/10.1016/j.schres.2010.02.906.

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17

Rabha, Diganta, Sritam Biswas, Nabadweep Chamuah, Manab Mandal, and Pabitra Nath. "Wide-field multi-modal microscopic imaging using smartphone." Optics and Lasers in Engineering 137 (February 2021): 106343. http://dx.doi.org/10.1016/j.optlaseng.2020.106343.

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Casciani, Emanuele, Chiara De Vincentiis, Maria Chiara Colaiacomo, and Gian Franco Gualdi. "Multi-Modal Imaging Technologies in Cardiovascular Risk Assessment." Therapeutic Apheresis and Dialysis 17, no. 2 (October 30, 2012): 138–49. http://dx.doi.org/10.1111/j.1744-9987.2012.01132.x.

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19

Gubarkova, Ekaterina V., Varvara V. Dudenkova, Felix I. Feldchtein, Lidia B. Timofeeva, Elena B. Kiseleva, Sergei S. Kuznetsov, Boris E. Shakhov, et al. "Multi-modal optical imaging characterization of atherosclerotic plaques." Journal of Biophotonics 9, no. 10 (November 25, 2015): 1009–20. http://dx.doi.org/10.1002/jbio.201500223.

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Hartley, Matthew, and Gerard Kleywegt. "Towards Public Archiving of Large, Multi-Modal Imaging Datasets." Microscopy and Microanalysis 28, S1 (July 22, 2022): 1526–27. http://dx.doi.org/10.1017/s1431927622006134.

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21

Soslow, Jonathan H., and Margaret M. Samyn. "Multi-modal imaging of the pediatric heart transplant recipient." Translational Pediatrics 8, no. 4 (October 2019): 322–38. http://dx.doi.org/10.21037/tp.2019.08.04.

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Shin, Tae-Hyun, Youngseon Choi, Soojin Kim, and Jinwoo Cheon. "Recent advances in magnetic nanoparticle-based multi-modal imaging." Chemical Society Reviews 44, no. 14 (2015): 4501–16. http://dx.doi.org/10.1039/c4cs00345d.

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23

Allegra Mascaro, Anna Letizia, Leonardo Sacconi, Ludovico Silvestri, Graham Knott, and Francesco S. Pavone. "Multi-Modal Optical Imaging of the Cerebellum in Animals." Cerebellum 15, no. 1 (October 17, 2015): 18–20. http://dx.doi.org/10.1007/s12311-015-0730-4.

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Zappia, Marcello, Francesco Di Pietto, Alberto Aliprandi, Simona Pozza, Paola De Petro, Alessandro Muda, and Luca Maria Sconfienza. "Multi-modal imaging of adhesive capsulitis of the shoulder." Insights into Imaging 7, no. 3 (April 23, 2016): 365–71. http://dx.doi.org/10.1007/s13244-016-0491-8.

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Prabhakar, Neeraj, Ilya Belevich, Markus Peurla, Xavier Heiligenstein, Huan-Cheng Chang, Cecilia Sahlgren, Eija Jokitalo, and Jessica M. Rosenholm. "Cell Volume (3D) Correlative Microscopy Facilitated by Intracellular Fluorescent Nanodiamonds as Multi-Modal Probes." Nanomaterials 11, no. 1 (December 23, 2020): 14. http://dx.doi.org/10.3390/nano11010014.

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Three-dimensional correlative light and electron microscopy (3D CLEM) is attaining popularity as a potential technique to explore the functional aspects of a cell together with high-resolution ultrastructural details across the cell volume. To perform such a 3D CLEM experiment, there is an imperative requirement for multi-modal probes that are both fluorescent and electron-dense. These multi-modal probes will serve as landmarks in matching up the large full cell volume datasets acquired by different imaging modalities. Fluorescent nanodiamonds (FNDs) are a unique nanosized, fluorescent, and electron-dense material from the nanocarbon family. We hereby propose a novel and straightforward method for executing 3D CLEM using FNDs as multi-modal landmarks. We demonstrate that FND is biocompatible and is easily identified both in living cell fluorescence imaging and in serial block-face scanning electron microscopy (SB-EM). We illustrate the method by registering multi-modal datasets.

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26

Pan, Wenjie, Linhan Huang, Jianbao Liang, Lan Hong, and Jianqing Zhu. "Progressively Hybrid Transformer for Multi-Modal Vehicle Re-Identification." Sensors 23, no. 9 (April 23, 2023): 4206. http://dx.doi.org/10.3390/s23094206.

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Multi-modal (i.e., visible, near-infrared, and thermal-infrared) vehicle re-identification has good potential to search vehicles of interest in low illumination. However, due to the fact that different modalities have varying imaging characteristics, a proper multi-modal complementary information fusion is crucial to multi-modal vehicle re-identification. For that, this paper proposes a progressively hybrid transformer (PHT). The PHT method consists of two aspects: random hybrid augmentation (RHA) and a feature hybrid mechanism (FHM). Regarding RHA, an image random cropper and a local region hybrider are designed. The image random cropper simultaneously crops multi-modal images of random positions, random numbers, random sizes, and random aspect ratios to generate local regions. The local region hybrider fuses the cropped regions to let regions of each modal bring local structural characteristics of all modalities, mitigating modal differences at the beginning of feature learning. Regarding the FHM, a modal-specific controller and a modal information embedding are designed to effectively fuse multi-modal information at the feature level. Experimental results show the proposed method wins the state-of-the-art method by a larger 2.7% mAP on RGBNT100 and a larger 6.6% mAP on RGBN300, demonstrating that the proposed method can learn multi-modal complementary information effectively.

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Badhiwala, Krishna N., Daniel L. Gonzales, Daniel G. Vercosa, Benjamin W. Avants, and Jacob T. Robinson. "Microfluidics for electrophysiology, imaging, and behavioral analysis of Hydra." Lab on a Chip 18, no. 17 (2018): 2523–39. http://dx.doi.org/10.1039/c8lc00475g.

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28

Gill, Jaidip, Robert Barry, Shreekanth Sreekantam, and Bashar Mohammed. "Multi-modal Imaging in Etanercept-induced Uveitis: A Case Series." Open Ophthalmology Journal 14, no. 1 (December 15, 2020): 70–74. http://dx.doi.org/10.2174/1874364102014010070.

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Introduction: To report with multi-modal imaging the clinical course of 3 patients with new-onset uveitis following treatment with etanercept. Methods: Retrospective case-note reviews were conducted of 3 patients previously established on etanercept who developed new-onset acute uveitis. Results and Discussion: Three patients were assessed with a mean age of 44.3 (43-47). Etanercept was indicated for the treatment of ankylosing spondylitis in two patients and psoriatic arthritis in 1 patient. Duration of etanercept treatment ranged from 7 to 10 years; however, in two cases, treatment recently changed to an etanercept biosimilar agent. Two patients were diagnosed with bilateral panuveitis and one patient had chronic relapsing anterior uveitis. Infection screen was negative in all three patients. 2 patients developed cystoid macular oedema as viewed on Spectral Domain OCT. Fundus fluorescein angiography was performed in one patient who demonstrated bilateral retinal vasculitis. All three patients were started on systemic and topical treatment. One patient received sub-tenon triamcinolone injection. Etanercept was discontinued for all patients. 1 of 3 patients lost vision at 7 months. 2 patients demonstrated long-term remission and one patient required intravitreal steroid implantation to stabilize an ongoing intraocular inflammation. Two patients who had complete remission were commenced on Adalimumab while the third patient was commenced on Secukinumab. Conclusion: The clinical course of uveitis developing paradoxically following etanercept treatment is variable. Multi-modal imaging is useful for the clinician that helps in diagnosing and monitoring associated macular oedema and retinal ischaemia. Cessation of etanercept and systemic corticosteroid treatment are often required to prevent ocular morbidity.

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Kang, Hae Min. "Multi-modal Imaging Analysis in the Patients with Traumatic Maculopathy." Journal of Retina 4, no. 1 (May 31, 2019): 32–35. http://dx.doi.org/10.21561/jor.2019.4.1.32.

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30

Tran, Vy, Daniel Poole, Justin Jeffery, Timothy Sheahan, Donald Creech, Aleksey Yevtodiyenko, Andrew Peat, Kevin Francis, Shihyun You, and Andrew Mehle. "Multi-Modal Imaging with a Toolbox of Influenza AReporter Viruses." Viruses 7, no. 10 (October 13, 2015): 5319–27. http://dx.doi.org/10.3390/v7102873.

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31

Egan, Gary F. "Multi-modal brain imaging for investigating and modeling neurological diseases." Neuroscience Research 68 (January 2010): e4-e5. http://dx.doi.org/10.1016/j.neures.2010.07.247.

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Boschi, Alessandra, Petra Martini, Emiliano Cazzola, Sara Cisternino, Teresa Ghirardi, Adriano Duatti, Giancarlo Gorgoni, et al. "Cyclotron-production of manganese-52 for multi-modal imaging applications." Nuclear Medicine and Biology 114-115 (November 2022): S46. http://dx.doi.org/10.1016/s0969-8051(22)02183-7.

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33

Calabria, Ferdinando, Gabriele Ciccariello, Carmela Falcone, Giuseppe Lucio Cascini, and Orazio Schillaci. "A case of Fahr’s disease examined by multi-modal imaging." European Journal of Nuclear Medicine and Molecular Imaging 42, no. 13 (August 13, 2015): 2098–99. http://dx.doi.org/10.1007/s00259-015-3162-y.

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Joshi, Bishnu P., and Thomas D. Wang. "Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging." Cancers 2, no. 2 (June 11, 2010): 1251–87. http://dx.doi.org/10.3390/cancers2021251.

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35

Sun, He, and Katherine L. Bouman. "Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 3 (May 18, 2021): 2628–37. http://dx.doi.org/10.1609/aaai.v35i3.16366.

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Computational image reconstruction algorithms generally produce a single image without any measure of uncertainty or confidence. Regularized Maximum Likelihood (RML) and feed-forward deep learning approaches for inverse problems typically focus on recovering a point estimate. This is a serious limitation when working with under-determined imaging systems, where it is conceivable that multiple image modes would be consistent with the measured data. Characterizing the space of probable images that explain the observational data is therefore crucial. In this paper, we propose a variational deep probabilistic imaging approach to quantify reconstruction uncertainty. Deep Probabilistic Imaging (DPI) employs an untrained deep generative model to estimate a posterior distribution of an unobserved image. This approach does not require any training data; instead, it optimizes the weights of a neural network to generate image samples that fit a particular measurement dataset. Once the network weights have been learned, the posterior distribution can be efficiently sampled. We demonstrate this approach in the context of interferometric radio imaging, which is used for black hole imaging with the Event Horizon Telescope, and compressed sensing Magnetic Resonance Imaging (MRI).

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Liu, Tracy W., Seth T. Gammon, and David Piwnica-Worms. "Multi-Modal Multi-Spectral Intravital Microscopic Imaging of Signaling Dynamics in Real-Time during Tumor–Immune Interactions." Cells 10, no. 3 (February 26, 2021): 499. http://dx.doi.org/10.3390/cells10030499.

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Intravital microscopic imaging (IVM) allows for the study of interactions between immune cells and tumor cells in a dynamic, physiologically relevant system in vivo. Current IVM strategies primarily use fluorescence imaging; however, with the advances in bioluminescence imaging and the development of new bioluminescent reporters with expanded emission spectra, the applications for bioluminescence are extending to single cell imaging. Herein, we describe a molecular imaging window chamber platform that uniquely combines both bioluminescent and fluorescent genetically encoded reporters, as well as exogenous reporters, providing a powerful multi-plex strategy to study molecular and cellular processes in real-time in intact living systems at single cell resolution all in one system. We demonstrate that our molecular imaging window chamber platform is capable of imaging signaling dynamics in real-time at cellular resolution during tumor progression. Importantly, we expand the utility of IVM by modifying an off-the-shelf commercial system with the addition of bioluminescence imaging achieved by the addition of a CCD camera and demonstrate high quality imaging within the reaches of any biology laboratory.

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Liu, Tracy W., Seth T. Gammon, David Fuentes, and David Piwnica-Worms. "Multi-Modal Multi-Spectral Intravital Macroscopic Imaging of Signaling Dynamics in Real Time during Tumor–Immune Interactions." Cells 10, no. 3 (February 25, 2021): 489. http://dx.doi.org/10.3390/cells10030489.

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A major obstacle in studying the interplay between cancer cells and the immune system has been the examination of proposed biological pathways and cell interactions in a dynamic, physiologically relevant system in vivo. Intravital imaging strategies are one of the few molecular imaging techniques that can follow biological processes at cellular resolution over long periods of time in the same individual. Bioluminescence imaging has become a standard preclinical in vivo optical imaging technique with ever-expanding versatility as a result of the development of new emission bioluminescent reporters, advances in genomic techniques, and technical improvements in bioluminescence imaging and processing methods. Herein, we describe an advance of technology with a molecular imaging window chamber platform that combines bioluminescent and fluorescent reporters with intravital macro-imaging techniques and bioluminescence spectral unmixing in real time applied to heterogeneous living systems in vivo for evaluating tumor signaling dynamics and immune cell enzyme activities concurrently.

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V, Bhavana, and Krishnappa H. K. "Multi-modal image fusion using contourlet and wavelet transforms: a multi-resolution approach." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 2 (November 1, 2022): 762. http://dx.doi.org/10.11591/ijeecs.v28.i2.pp762-768.

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In recent years, vast improvement and progress has been observed in the field of medical research, especially in digital medical imaging technology. Medical image fusion has been widely used in clinical diagnosis to get valuable information from different modalities of medical images to enhance its quality by fusing images like computed tomography (CT), and magnetic resonance imaging (MRI). MRI gives clear information on delicate tissue while CT gives details about denser tissues. A multi-resolution approach is proposed in this work for fusing medical images using non-sub-sampled contourlet transform (NSCT) and discrete wavelet transform (DWT). In this approach, initially the input images are decomposed using DWT at 4 levels and NSCT at 2 levels which helps to protect the vital data from the source images. This work shows significant enhancement in pixel clarity and preserves the information at the corners and edges of the fused image without any data loss. The proposed methodology with an improved entropy and mutual information helps the doctors in better clinical diagnosis of brain diseases.

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Liu, Yu, Xiaolin Lv, Heng Liu, Zijian Zhou, Jianpan Huang, Shenglan Lei, Shuhui Cai, et al. "Porous gold nanocluster-decorated manganese monoxide nanocomposites for microenvironment-activatable MR/photoacoustic/CT tumor imaging." Nanoscale 10, no. 8 (2018): 3631–38. http://dx.doi.org/10.1039/c7nr08535d.

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Xiao, Peng, Zhengyu Duan, Gengyuan Wang, Yuqing Deng, Qian Wang, Jun Zhang, Shanshan Liang, and Jin Yuan. "Multi-modal Anterior Eye Imager Combining Ultra-High Resolution OCT and Microvascular Imaging for Structural and Functional Evaluation of the Human Eye." Applied Sciences 10, no. 7 (April 7, 2020): 2545. http://dx.doi.org/10.3390/app10072545.

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To establish complementary information for the diagnosis and evaluation of ocular surface diseases, we developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Our customized UHR-OCT module achieves an axial resolution of ≈2.9 μm in corneal tissue with a broadband light source and an A-line acquisition rate of 24 kHz with a line array CCD camera. The microvascular imaging module has a lateral resolution of 3.5 μm under maximum magnification of ≈187.5× with an imaging rate of 60 frames/s, which is sufficient to image the conjunctival vessel network and record the movement trajectory of clusters of red blood cells. By combining the imaging optical paths of different modules, our customized multi-modal anterior eye imaging platform is capable of performing real-time cross-sectional UHR-OCT imaging of the anterior eye, conjunctival vessel network imaging, high-resolution conjunctival blood flow videography, fluorescein staining and traditional slit-lamp imaging on a single device. With self-developed software, a conjunctival vessel network image and blood flow videography were further analyzed to acquire quantitative morphological and hemodynamics parameters, including vessel fractal dimensions, blood flow velocity and vessel diameters. The ability of our multi-modal anterior eye imager to provide both structural and functional information for ophthalmic clinical applications was demonstrated on a healthy human subject and a keratitis patient.

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Cheng, Hanlong, Xueyan Wang, Xuan Liu, Xin Wang, Hao Wen, Yinkai Cheng, Anjian Xie, Yuhua Shen, Rupei Tang, and Manzhou Zhu. "An effective NIR laser/tumor-microenvironment co-responsive cancer theranostic nanoplatform with multi-modal imaging and therapies." Nanoscale 13, no. 24 (2021): 10816–28. http://dx.doi.org/10.1039/d1nr01645h.

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42

Toda, Kanon, Kazuya Kishizawa, Yuma Toyoda, Kohei Noda, Heeyoung Lee, Kentaro Nakamura, Koichi Ichige, and Yosuke Mizuno. "Characterization of modal interference in multi-core polymer optical fibers and its application to temperature sensing." Applied Physics Express 15, no. 7 (June 13, 2022): 072002. http://dx.doi.org/10.35848/1882-0786/ac749e.

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Abstract Various types of fiber-optic temperature sensors have been developed on the basis of modal interference in multimode fibers, which include not only glass fibers but also polymer optical fibers (POFs). Herein, we investigate the spectral patterns of the modal interference in multi-core POFs (originally developed for imaging) and observe their unique temperature dependencies with no clear frequency shift or critical wavelength. We then show that, by machine learning, the modal interference in the multi-core POFs can be potentially used for highly accurate temperature sensing with an error of ∼0.3 °C.

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Kuang, Xiao-yan, Huan Liu, Wen-yong Hu, and Yuan-zhi Shao. "Hydrothermal synthesis of core–shell structured TbPO4:Ce3+@TbPO4:Gd3+nanocomposites for magnetic resonance and optical imaging." Dalton Trans. 43, no. 32 (2014): 12321–28. http://dx.doi.org/10.1039/c4dt00249k.

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Multi-modal imaging based on multifunctional nanoparticles provides deep, non-invasive and highly sensitive imaging and is a promising alternative approach that can improve the sensitivity of early cancer diagnosis.

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Liu, Zhe, Qien Xu, Yihong Li, and Waner Chen. "Fluorescent C-dot nanocomposites as efficient photothermal agents and multi-modal imaging tracers." Materials Chemistry Frontiers 1, no. 3 (2017): 538–41. http://dx.doi.org/10.1039/c6qm00160b.

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45

Gibson, Lorna M., Thomas J. Littlejohns, Ligia Adamska, Steve Garratt, Nicola Doherty, Joanna M. Wardlaw, Giles Maskell, et al. "Impact of detecting potentially serious incidental findings during multi-modal imaging." Wellcome Open Research 2 (November 30, 2017): 114. http://dx.doi.org/10.12688/wellcomeopenres.13181.1.

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Background: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of participants and burdening of publicly-funded health services suggests that radiographer flagging is a justifiable approach in the UK Biobank imaging study. The potential scale of non-serious final diagnoses raises questions relating to handling IFs in other settings, such as commercial and public health screening.

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Gibson, Lorna M., Thomas J. Littlejohns, Ligia Adamska, Steve Garratt, Nicola Doherty, Joanna M. Wardlaw, Giles Maskell, et al. "Impact of detecting potentially serious incidental findings during multi-modal imaging." Wellcome Open Research 2 (May 3, 2018): 114. http://dx.doi.org/10.12688/wellcomeopenres.13181.2.

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Background: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of participants and burdening of publicly-funded health services suggests that radiographer flagging is a justifiable approach in the UK Biobank imaging study. The potential scale of non-serious final diagnoses raises questions relating to handling IFs in other settings, such as commercial and public health screening.

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47

Gibson, Lorna M., Thomas J. Littlejohns, Ligia Adamska, Steve Garratt, Nicola Doherty, Joanna M. Wardlaw, Giles Maskell, et al. "Impact of detecting potentially serious incidental findings during multi-modal imaging." Wellcome Open Research 2 (August 2, 2018): 114. http://dx.doi.org/10.12688/wellcomeopenres.13181.3.

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Abstract:

Background: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of participants and burdening of publicly-funded health services suggests that radiographer flagging is a justifiable approach in the UK Biobank imaging study. The potential scale of non-serious final diagnoses raises questions relating to handling IFs in other settings, such as commercial and public health screening.

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Pampaloni, Francesco. "Multi-Modal and Molecular Imaging of Cellular Microenvironment and Tissue Development." International Journal of Molecular Sciences 23, no. 13 (June 26, 2022): 7113. http://dx.doi.org/10.3390/ijms23137113.

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Imaging the interaction of individual cells with their surrounding tissue microenvironment is essential to advance in bioprinting, tissue engineering and cancer biology, to mention just three highly relevant fields in the life sciences [...]

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Mankar, Rupali, Chalapathi Charan Gajjela, Farideh Foroozandeh Shahraki, Saurabh Prasad, David Mayerich, and Rohith Reddy. "Multi-modal image sharpening in fourier transform infrared (FTIR) microscopy." Analyst 146, no. 15 (2021): 4822–34. http://dx.doi.org/10.1039/d1an00103e.

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Multi-modal fusion improves spatial resolution of FTIR images beyond diffraction-limit that improves classification of histology classes. Enhanced spatial details are comparable to O-PTIR which is a super-resolution spectroscopic imaging technology.

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Mangion, Sean E., Lydia Sandiford, Yousuf Mohammed, Michael S. Roberts, and Amy M. Holmes. "Multi-Modal Imaging to Assess the Follicular Delivery of Zinc Pyrithione." Pharmaceutics 14, no. 5 (May 17, 2022): 1076. http://dx.doi.org/10.3390/pharmaceutics14051076.

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Zinc pyrithione (ZnPT) is a widely used antifungal, usually applied as a microparticle suspension to facilitate delivery into the hair follicles, where it then dissociates into a soluble monomeric form that is bioactive against yeast and other microorganisms. In this study, we use multiphoton microscopy (MPM) and fluorescence lifetime imaging microscopy (FLIM) to characterise ZnPT formulations and map the delivery of particles into follicles within human skin. To simulate real-world conditions, it was applied using a massage or no-massage technique, while simultaneously assessing the dissolution using Zinpyr-1, a zinc labile fluorescent probe. ZnPT particles can be detected in a range of shampoo formulations using both MPM and FLIM, though FLIM is optimal for detection as it allows spectral and lifetime discrimination leading to increased selectivity and sensitivity. In aqueous suspensions, the ZnPT 7.2 µm particles could be detected up to 500 µm in the follicle. The ZnPT particles in formulations were finer (1.0–3.3 µm), resulting in rapid dissolution on the skin surface and within follicles, evidenced by a reduced particle signal at 24 h but enhanced Zinpyr-1 intensity in the follicular and surface epithelium. This study shows how MPM-FLIM multimodal imaging can be used as a useful tool to assess ZnPT delivery to skin and its subsequent dissolution.

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