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Journal articles on the topic 'Pre-clinical imaging'

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Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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1

Drexler, W. "SP-0516: Optical imaging in pre-clinical research." Radiotherapy and Oncology 106 (March 2013): S200. http://dx.doi.org/10.1016/s0167-8140(15)32822-x.

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2

Hazle, J. "WE-EF-204-01: Pre-Clinical Imaging for Co-Clinical Trials." Medical Physics 42, no. 6Part39 (June 2015): 3680. http://dx.doi.org/10.1118/1.4926004.

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3

Meikle, Steven, Stefan Eberl, and Hidehiro Iida. "Instrumentation and Methodology for Quantitative Pre-Clinical Imaging Studies." Current Pharmaceutical Design 7, no. 18 (December 1, 2001): 1945–66. http://dx.doi.org/10.2174/1381612013396961.

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4

Kondrashova, T., D. De Wan, M. U. Briones, and P. Kondrashov. "Integration of ultrasound imaging into pre-clinical dental education." European Journal of Dental Education 21, no. 4 (April 4, 2016): 228–34. http://dx.doi.org/10.1111/eje.12205.

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5

Madonna, R., C. Cevik, and N. Cocco. "Multimodality imaging for pre-clinical assessment of Fabry's cardiomyopathy." European Heart Journal - Cardiovascular Imaging 15, no. 10 (June 5, 2014): 1094–100. http://dx.doi.org/10.1093/ehjci/jeu080.

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6

Zöllner, Frank G., Raffi Kalayciyan, Jorge Chacón-Caldera, Fabian Zimmer, and Lothar R. Schad. "Pre-clinical functional Magnetic Resonance Imaging part I: The kidney." Zeitschrift für Medizinische Physik 24, no. 4 (December 2014): 286–306. http://dx.doi.org/10.1016/j.zemedi.2014.05.002.

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7

Meßner, Nadja M., Frank G. Zöllner, Raffi Kalayciyan, and Lothar R. Schad. "Pre-clinical functional Magnetic Resonance Imaging part II: The heart." Zeitschrift für Medizinische Physik 24, no. 4 (December 2014): 307–22. http://dx.doi.org/10.1016/j.zemedi.2014.06.008.

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8

Finegan, K., M. Babur, D. Forster, J. O’Connor, C. Tournier, and K. Williams. "A novel pre-clinical model for imaging cancer-associated inflammation." European Journal of Cancer 61 (July 2016): S107. http://dx.doi.org/10.1016/s0959-8049(16)61377-1.

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9

O'Neill, Karen, Scott K. Lyons, William M. Gallagher, Kathleen M. Curran, and Annette T. Byrne. "Bioluminescent imaging: a critical tool in pre-clinical oncology research." Journal of Pathology 220, no. 3 (October 27, 2009): 317–27. http://dx.doi.org/10.1002/path.2656.

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10

ÁLVAREZ, F. J., J. BISBE, V. BISBE, and A. DÁVALOS. "MAGNETIC RESONANCE IMAGING FINDINGS IN PRE-CLINICAL CREUTZFELDT-JAKOB DISEASE." International Journal of Neuroscience 115, no. 8 (January 2005): 1219–25. http://dx.doi.org/10.1080/00207450590914491.

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11

NAGUEH, S. "Tissue Doppler imaging for the pre-clinical diagnosis of cardiomyopathy." European Heart Journal 25, no. 21 (November 2004): 1865–66. http://dx.doi.org/10.1016/j.ehj.2004.08.013.

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12

Bimonte, Sabrina, Maddalena Leongito, Vincenza Granata, Antonio Barbieri, Vitale del Vecchio, Michela Falco, Aurelio Nasto, et al. "Electrochemotherapy in pancreatic adenocarcinoma treatment: pre-clinical and clinical studies." Radiology and Oncology 50, no. 1 (March 1, 2016): 14–20. http://dx.doi.org/10.1515/raon-2016-0003.

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Background Pancreatic adenocarcinoma is currently one of the deadliest cancers with high mortality rate. This disease leads to an aggressive local invasion and early metastases, and is poorly responsive to treatment with chemotherapy or chemo-radiotherapy. Radical resection is still the only curative treatment for pancreatic cancer, but it is generally accepted that a multimodality strategy is necessary for its management. Therefore, new alternative therapies have been considered for local treatment. Conclusions Chemotherapeutic resistance in pancreatic cancer is associated to a low penetration of drugs into tumour cells due to the presence of fibrotic stroma surrounding cells. In order to increase the uptake of chemotherapeutic drugs into tumour cells, electrochemotherapy can be used for treatment of pancreatic adenocarcinoma leading to an increased tumour response rate. This review will summarize the published papers reported in literature on the efficacy and safety of electrochemotherapy in pre-clinical and clinical studies on pancreatic cancer.
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13

Schmidt-Christensen, Anja, Julia Nilsson, Sofia Mayans, and Dan Holmberg. "THU-368-Multimodal pre-clinical imaging of liver inflammation and fibrosis." Journal of Hepatology 70, no. 1 (April 2019): e316. http://dx.doi.org/10.1016/s0618-8278(19)30616-4.

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14

Olde Heuvel, J., L. De Wit-Van Der Veen, M. P. M. Stokkel, H. G. Van Der Poel, D. S. Tuch, M. R. Grootendorst, K. N. Vyas, and C. H. Slump. "Cerenkov luminescence imaging for intraoperative specimen analysis: A pre-clinical evaluation." European Urology Supplements 18, no. 1 (March 2019): e668-e669. http://dx.doi.org/10.1016/s1569-9056(19)30493-2.

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15

Studen, A., D. Burdette, E. Chesi, V. Cindro, N. H. Clinthorne, W. Dulinski, J. Fuster, et al. "First coincidences in pre-clinical Compton camera prototype for medical imaging." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 531, no. 1-2 (September 2004): 258–64. http://dx.doi.org/10.1016/j.nima.2004.06.014.

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16

Bravin, Alberto, Paola Coan, and Pekka Suortti. "X-ray phase-contrast imaging: from pre-clinical applications towards clinics." Physics in Medicine and Biology 58, no. 1 (December 10, 2012): R1—R35. http://dx.doi.org/10.1088/0031-9155/58/1/r1.

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17

Badachhape, Andrew A., Aarav Kumar, Ketan B. Ghaghada, Igor V. Stupin, Mayank Srivastava, Laxman Devkota, Zbigniew Starosolski, et al. "Pre-clinical magnetic resonance imaging of retroplacental clear space throughout gestation." Placenta 77 (February 2019): 1–7. http://dx.doi.org/10.1016/j.placenta.2019.01.017.

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18

Parsons, David, Cody Church, and Alasdair Syme. "Toward a pre-clinical irradiator using clinical infrastructure." Physica Medica 58 (February 2019): 21–31. http://dx.doi.org/10.1016/j.ejmp.2019.01.006.

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19

Demine, Stephane, Michael L. Schulte, Paul R. Territo, and Decio L. Eizirik. "Beta Cell Imaging—From Pre-Clinical Validation to First in Man Testing." International Journal of Molecular Sciences 21, no. 19 (October 1, 2020): 7274. http://dx.doi.org/10.3390/ijms21197274.

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There are presently no reliable ways to quantify human pancreatic beta cell mass (BCM) in vivo, which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. Furthermore, the lack of beta cell imaging hampers the evaluation of the impact of new drugs aiming to prevent beta cell loss or to restore BCM in diabetes. We presently discuss the potential value of BCM determination as a cornerstone for individualized therapies in diabetes, describe the presently available probes for human BCM evaluation, and discuss our approach for the discovery of novel beta cell biomarkers, based on the determination of specific splice variants present in human beta cells. This has already led to the identification of DPP6 and FXYD2γa as two promising targets for human BCM imaging, and is followed by a discussion of potential safety issues, the role for radiochemistry in the improvement of BCM imaging, and concludes with an overview of the different steps from pre-clinical validation to a first-in-man trial for novel tracers.
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20

Kusko, Rebecca, Marina Iskandir, Allen Haynes, Simon Williams, Scott Shurmur, and Mohammad Ansari. "The effect of a multimodality cardiac imaging elective on pre-clinical medical students." Southwest Respiratory and Critical Care Chronicles 8, no. 35 (July 23, 2020): 72–76. http://dx.doi.org/10.12746/swrccc.v8i35.721.

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Abstract The Texas Tech University Health Sciences Center School of Medicine has developed an immersive Cardiac Imaging and Innovation week for medical students during their preclinical year. A pre- and post-survey administered to participants showed increased knowledge and improved impressions of cardiology. The students ranked the experience as high quality. This project suggests that similar elective experiences could enhance education during the preclinical period of medical education. Key words: medical education, cardiology, technology, imaging, echocardiography
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21

Kalen, Joseph D., David A. Clunie, Yanling Liu, James L. Tatum, Paula M. Jacobs, Justin Kirby, John B. Freymann, et al. "Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies." Tomography 7, no. 1 (February 5, 2021): 1–9. http://dx.doi.org/10.3390/tomography7010001.

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The small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (i.e., anesthesia, mouse model nomenclature, veterinary definitions, NCI Metathesaurus) were utilized to assist in defining terms implemented in pre-clinical imaging and new codes were added to integrate the specific small animal procedures and handling processes, such as housing, biosafety level, and pre-imaging rodent preparation. In addition to the standard DICOM fields, the small animal SR includes fields specific to small animal imaging such as tumor graft (i.e., melanoma), tissue of origin, mouse strain, and exogenous material, including the date and site of injection. Additionally, the mapping and harmonization developed by the Mouse-Human Anatomy Project were implemented to assist co-clinical research by providing cross-reference human-to-mouse anatomies. Furthermore, since small animal imaging performs multi-mouse imaging for high throughput, and queries for co-clinical research requires a one-to-one relation, an imaging splitting routine was developed, new Unique Identifiers (UID’s) were created, and the original patient name and ID were saved for reference to the original dataset. We report the implementation of the small animal SR using MRI datasets (as an example) of patient-derived xenograft mouse models and uploaded to The Cancer Imaging Archive (TCIA) for public dissemination, and also implemented this on PET/CT datasets. The small animal SR enhancement provides researchers the ability to query any DICOM modality pre-clinical and clinical datasets using standard vocabularies and enhances co-clinical studies.
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22

Kang, Keon Wook. "Preliminary Pre-Clinical Results and Overview on PET/MRI/Fluorescent Molecular Imaging." Open Nuclear Medicine Journal 2, no. 1 (November 29, 2010): 153–56. http://dx.doi.org/10.2174/1876388x01002010153.

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23

Dirlik Serim, Burcu, and Mustafa Kula. "Disease Models and Imaging Techniques Used in Pre-Clinical Studies - Endocrine Models." Nuclear Medicine Seminars 5, no. 1 (April 4, 2019): 88–95. http://dx.doi.org/10.4274/nts.galenos.2019.0011.

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24

Duara, Ranjan, David A. Loewenstein, Elizabeth Potter, Warren Barker, Ashok Raj, Michael Schoenberg, Yougui Wu, et al. "Pre-MCI and MCI: Neuropsychological, Clinical, and Imaging Features and Progression Rates." American Journal of Geriatric Psychiatry 19, no. 11 (November 2011): 951–60. http://dx.doi.org/10.1097/jgp.0b013e3182107c69.

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25

Leblond, Frederic, Scott C. Davis, Pablo A. Valdés, and Brian W. Pogue. "Pre-clinical whole-body fluorescence imaging: Review of instruments, methods and applications." Journal of Photochemistry and Photobiology B: Biology 98, no. 1 (January 2010): 77–94. http://dx.doi.org/10.1016/j.jphotobiol.2009.11.007.

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26

Rotman, Maarten, Thomas J. A. Snoeks, and Louise van der Weerd. "Pre-clinical optical imaging and MRI for drug development in Alzheimer's disease." Drug Discovery Today: Technologies 8, no. 2-4 (June 2011): e117-e125. http://dx.doi.org/10.1016/j.ddtec.2011.11.005.

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27

Nanni, Cristina, Domenico Rubello, and Stefano Fanti. "Role of small animal PET for molecular imaging in pre-clinical studies." European Journal of Nuclear Medicine and Molecular Imaging 34, no. 11 (March 10, 2007): 1819–22. http://dx.doi.org/10.1007/s00259-007-0394-5.

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28

Khosropanah, Pegah, Eric Tatt-Wei Ho, Kheng-Seang Lim, Si-Lei Fong, Minh-An Thuy Le, and Vairavan Narayanan. "EEG Source Imaging (ESI) utility in clinical practice." Biomedical Engineering / Biomedizinische Technik 65, no. 6 (November 18, 2020): 673–82. http://dx.doi.org/10.1515/bmt-2019-0128.

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AbstractEpilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73–91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.
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29

Shankavaram, U. T., M. Bredel, P. Tofilon, and K. Camphausen. "Predictive Pre-clinical Modeling of Glioblastoma Multiforme." International Journal of Radiation Oncology*Biology*Physics 78, no. 3 (November 2010): S492—S493. http://dx.doi.org/10.1016/j.ijrobp.2010.07.1152.

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30

Levenson, Richard, Joseph Beechem, and George McNamara. "Modern Trends in Imaging X: Spectral Imaging in Preclinical Research and Clinical Pathology." Analytical Cellular Pathology 35, no. 5-6 (2012): 339–61. http://dx.doi.org/10.1155/2012/904828.

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Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings.
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31

Mihaylov, Ivaylo B., Tulasigeri M. Totiger, Teresa M. Giret, Dazhi Wang, Benjamin Spieler, and Scott Welford. "Toward prediction of abscopal effect in radioimmunotherapy: Pre-clinical investigation." PLOS ONE 16, no. 8 (August 24, 2021): e0255923. http://dx.doi.org/10.1371/journal.pone.0255923.

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Purpose Immunotherapy (IT) and radiotherapy (RT) can act synergistically, enhancing antitumor response beyond what either treatment can achieve separately. Anecdotal reports suggest that these results are in part due to the induction of an abscopal effect on non-irradiated lesions. Systematic data on incidence of the abscopal effect are scarce, while the existence and the identification of predictive signatures or this phenomenon are lacking. The purpose of this pre-clinical investigational work is to shed more light on the subject by identifying several imaging features and blood counts, which can be utilized to build a predictive binary logistic model. Materials and methods This proof-of-principle study was performed on Lewis Lung Carcinoma in a syngeneic, subcutaneous murine model. Nineteen mice were used: four as control and the rest were subjected to combined RT plus IT regimen. Tumors were implanted on both flanks and after reaching volume of ~200 mm3 the animals were CT and MRI imaged and blood was collected. Quantitative imaging features (radiomics) were extracted for both flanks. Subsequently, the treated animals received radiation (only to the right flank) in three 8 Gy fractions followed by PD-1 inhibitor administrations. Tumor volumes were followed and animals exhibiting identical of better tumor growth delay on the non-irradiated (left) flank as compared to the irradiated flank were identified as experiencing an abscopal effect. Binary logistic regression analysis was performed to create models for CT and MRI radiomics and blood counts, which are predictive of the abscopal effect. Results Four of the treated animals experienced an abscopal effect. Three CT and two MRI radiomics features together with the pre-treatment neutrophil-to-lymphocyte (NLR) ratio correlated with the abscopal effect. Predictive models were created by combining the radiomics with NLR. ROC analyses indicated that the CT model had AUC of 0.846, while the MRI model had AUC of 0.946. Conclusions The combination of CT and MRI radiomics with blood counts resulted in models with AUCs of 1 on the modeling dataset. Application of the models to the validation dataset exhibited AUCs above 0.84, indicating very good predictive power of the combination between quantitative imaging and blood counts.
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32

Sayeram, Sunita, and Eric Buckland. "Bioptigen’s High-resolution Spectral-domain Optical Coherence Tomography Imaging for Clinical and Pre-clinical Research Applications." US Ophthalmic Review 03 (2012): 1. http://dx.doi.org/10.17925/usor.2007.03.00.1b.

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33

Pelin, Adrian, Jiahu Wang, John Bell, and Fabrice Le Boeuf. "The importance of imaging strategies for pre-clinical and clinical in vivo distribution of oncolytic viruses." Oncolytic Virotherapy Volume 7 (March 2018): 25–35. http://dx.doi.org/10.2147/ov.s137159.

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34

Farace, P., M. G. Giri, G. Meliadò, D. Amelio, L. Widesott, G. K. Ricciardi, S. Dall'Oglio, et al. "Clinical target volume delineation in glioblastomas: pre-operative versus post-operative/pre-radiotherapy MRI." British Journal of Radiology 84, no. 999 (March 2011): 271–78. http://dx.doi.org/10.1259/bjr/10315979.

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35

Fragogeorgi, Eirini A., Maritina Rouchota, Maria Georgiou, Marisela Velez, Penelope Bouziotis, and George Loudos. "In vivo imaging techniques for bone tissue engineering." Journal of Tissue Engineering 10 (January 2019): 204173141985458. http://dx.doi.org/10.1177/2041731419854586.

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Bone is a dynamic tissue that constantly undergoes modeling and remodeling. Bone tissue engineering relying on the development of novel implant scaffolds for the treatment of pre-clinical bone defects has been extensively evaluated by histological techniques. The study of bone remodeling, that takes place over several weeks, is limited by the requirement of a large number of animals and time-consuming and labor-intensive procedures. X-ray-based imaging methods that can non-invasively detect the newly formed bone tissue have therefore been extensively applied in pre-clinical research and in clinical practice. The use of other imaging techniques at a pre-clinical level that act as supportive tools is convenient. This review mainly focuses on nuclear imaging methods (single photon emission computed tomography and positron emission tomography), either alone or used in combination with computed tomography. It addresses their application to small animal models with bone defects, both untreated and filled with substitute materials, to boost the knowledge on bone regenerative processes.
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36

Hristov, D., K. Ahn, and G. Scott. "TU-E-214-02: Overhauser Oxygenation Imaging: Physics, Instrumentation and Pre-Clinical Applications." Medical Physics 38, no. 6Part29 (June 2011): 3772. http://dx.doi.org/10.1118/1.3613200.

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37

Lee, Yueh Z., Laurel Burk, Ko-han Wang, Guohua Cao, Jianping Lu, and Otto Zhou. "Carbon nanotube based X-ray sources: Applications in pre-clinical and medical imaging." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 648 (August 2011): S281—S283. http://dx.doi.org/10.1016/j.nima.2010.11.053.

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38

Bergeron, Mélanie, Jules Cadorette, Marc-André Tétrault, Jean-François Beaudoin, Jean-Daniel Leroux, Réjean Fontaine, and Roger Lecomte. "Imaging performance of LabPET APD-based digital PET scanners for pre-clinical research." Physics in Medicine and Biology 59, no. 3 (January 20, 2014): 661–78. http://dx.doi.org/10.1088/0031-9155/59/3/661.

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39

Garrood, T., M. Blades, D. O. Haskard, S. Mather, and C. Pitzalis. "A novel model for the pre-clinical imaging of inflamed human synovial vasculature." Rheumatology 48, no. 8 (June 2, 2009): 926–31. http://dx.doi.org/10.1093/rheumatology/kep117.

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40

Oh, Karen Y., Anne M. Kennedy, Antonio E. Frias, and Janice L. B. Byrne. "Fetal Schizencephaly: Pre- and Postnatal Imaging with a Review of the Clinical Manifestations." RadioGraphics 25, no. 3 (May 2005): 647–57. http://dx.doi.org/10.1148/rg.253045103.

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41

FUKUMURA, DAI, DAN G. DUDA, LANCE L. MUNN, and RAKESH K. JAIN. "Tumor Microvasculature and Microenvironment: Novel Insights Through Intravital Imaging in Pre-Clinical Models." Microcirculation 17, no. 3 (April 2010): 206–25. http://dx.doi.org/10.1111/j.1549-8719.2010.00029.x.

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42

Duara, Ranjan, David Loewenstein, Maria T. Greig-Custo, Elizabeth Potter, Balaibal Ashok Raj, John Schinka, Amy Borenstein, et al. "O1-05-07: Pre-MCI: Neuropsychological, clinical and imaging features, and progression rates." Alzheimer's & Dementia 6 (July 2010): S80. http://dx.doi.org/10.1016/j.jalz.2010.05.239.

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43

Miszczuk, Diana, Anna-Mari Karkkainen, Juho Koponen, Tuukka Miettinen, and Artem Shatillo. "Functional ultrasound – Novel in-vivo imaging technique for pre-clinical CNS drug discovery." IBRO Reports 6 (September 2019): S394—S395. http://dx.doi.org/10.1016/j.ibror.2019.07.1255.

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44

Powell, C., C. Mikropoulos, S. B. Kaye, C. M. Nutting, S. A. Bhide, K. Newbold, and K. J. Harrington. "Pre-clinical and clinical evaluation of PARP inhibitors as tumour-specific radiosensitisers." Cancer Treatment Reviews 36, no. 7 (November 2010): 566–75. http://dx.doi.org/10.1016/j.ctrv.2010.03.003.

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45

Ward, Ambber, Kum Kum Khanna, and Adrian P. Wiegmans. "Targeting homologous recombination, new pre-clinical and clinical therapeutic combinations inhibiting RAD51." Cancer Treatment Reviews 41, no. 1 (January 2015): 35–45. http://dx.doi.org/10.1016/j.ctrv.2014.10.006.

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46

Niazkhani, Z., R. Bal, and H. Pirnejad. "Clinical Communication in Diagnostic Imaging Studies." Applied Clinical Informatics 04, no. 04 (2013): 541–55. http://dx.doi.org/10.4338/aci-2013-06-ra-0042.

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SummaryObjective: To examine how and why the quality of clinical communication between radiologists and referring physicians was changed in the inpatient imaging process after implementation of a hospital information system (HIS).Methods: A mixed-method study of the chest X-ray (CXR) requests and reports, and their involved processes within a pre- and post-HIS implementation setting.Results: Documentation of patient age, patient ward, and name and signature of requesting physician decreased significantly in post-HIS CXR requests (P<0.05). However, documentation of requested position and technique increased significantly (P<0.05). In post-HIS CXR reports, documentation of patient age, patient chart number, urgent/normal status of requisition, position and technique of CXR, name of referring physician, and date of request were increased significantly (P<0.05). However, documentation of discussion for important findings was decreased significantly (P<0.05). The mean number of words in the body text of post-HIS reports was increased significantly (18.65 vs. 16.3, P = 0.00).Our qualitative findings highlighted that involving nursing and radiology staff in the communication loop between physicians and radiologists after the implementation resulted in extra steps in the workflow and more workload for them. To cope with the new workload, they adopted different workarounds that could explain the results seen in the quantitative study.Conclusion: The HIS improved communication of administrative and identification information but did not improve communication of clinically relevant information. The reason was traced to the complications that the inappropriate implementation of the system brought to clinical workflow and communication loop.Citation: Pirnejad H, Niazkhania Z, Bal R. Clinical communication in diagnosticimaging studies - mixedmethod study of pre- and post-implementation of a hospital information system. Appl Clin Inf 2013; 4: 541–555http://dx.doi.org/10.4338/ACI-2013-06-RA-0042
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47

Godfrey, L., J. Hanley, J. Napoli, J. Barbiere, M. Tuna, and D. H. Smith. "Robotically-assisted Minimally Invasive Brachytherapy: Pre-clinical Aspects." International Journal of Radiation Oncology*Biology*Physics 75, no. 3 (November 2009): S721. http://dx.doi.org/10.1016/j.ijrobp.2009.07.1642.

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48

Riou, L., A. Broisat, J. Dimastromatteo, G. Pons, D. Fagret, and C. Ghezzi. "Pre-Clinical and Clinical Evaluation of Nuclear Tracers for the Molecular Imaging of Vulnerable Atherosclerosis: An Overview." Current Medicinal Chemistry 16, no. 12 (April 1, 2009): 1499–511. http://dx.doi.org/10.2174/092986709787909596.

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49

Callewaert, Bram, Elizabeth A. V. Jones, Uwe Himmelreich, and Willy Gsell. "Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations." Diagnostics 11, no. 6 (May 21, 2021): 926. http://dx.doi.org/10.3390/diagnostics11060926.

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Abstract:
Alterations to the cerebral microcirculation have been recognized to play a crucial role in the development of neurodegenerative disorders. However, the exact role of the microvascular alterations in the pathophysiological mechanisms often remains poorly understood. The early detection of changes in microcirculation and cerebral blood flow (CBF) can be used to get a better understanding of underlying disease mechanisms. This could be an important step towards the development of new treatment approaches. Animal models allow for the study of the disease mechanism at several stages of development, before the onset of clinical symptoms, and the verification with invasive imaging techniques. Specifically, pre-clinical magnetic resonance imaging (MRI) is an important tool for the development and validation of MRI sequences under clinically relevant conditions. This article reviews MRI strategies providing indirect non-invasive measurements of microvascular changes in the rodent brain that can be used for early detection and characterization of neurodegenerative disorders. The perfusion MRI techniques: Dynamic Contrast Enhanced (DCE), Dynamic Susceptibility Contrast Enhanced (DSC) and Arterial Spin Labeling (ASL), will be discussed, followed by less established imaging strategies used to analyze the cerebral microcirculation: Intravoxel Incoherent Motion (IVIM), Vascular Space Occupancy (VASO), Steady-State Susceptibility Contrast (SSC), Vessel size imaging, SAGE-based DSC, Phase Contrast Flow (PC) Quantitative Susceptibility Mapping (QSM) and quantitative Blood-Oxygenation-Level-Dependent (qBOLD). We will emphasize the advantages and limitations of each strategy, in particular on applications for high-field MRI in the rodent’s brain.
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50

ELLIS, JAMES H., KAY H. VYDARENY, FRED L. BOOKSTEIN, and BARRY H. GROSS. "Impact of Pre-Radiology Clinical Years on Resident Performance." Investigative Radiology 24, no. 7 (July 1989): 568–74. http://dx.doi.org/10.1097/00004424-198907000-00011.

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