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21 results on '"Fulham, Michael"'

2. Contributors

Author

Akbilgic, Oguz, primary, AlAnzi, Turki, additional, An, Xiangdong, additional, Barrio, Jorge R., additional, Bertoldo, Alessandra, additional, Bi, Lei, additional, Bin, Sheng, additional, Cai, Weidong, additional, Cao, Longbing, additional, Chen, Hao, additional, Clarke, Robert, additional, Cobelli, Claudio, additional, Cui, Hui, additional, Dou, Qi, additional, Du, Yiping P., additional, Eberl, Stefan, additional, Fan, Ming, additional, Feng, Shi-Hao, additional, Feng, David Dagan, additional, Fischer, Gregory S., additional, Fu, Yi, additional, Fulham, Michael J., additional, Gao, Fan, additional, Hao, Manzhao, additional, Heng, Pheng-Ann, additional, Huang, Sung-Cheng, additional, Huang, H.K., additional, Huang, Jimmy Xiangji, additional, Istepanian, Robert S.H., additional, Jung, Younhyun, additional, Kamaleswaran, Rishikesan, additional, Kazanzides, Peter, additional, Kim, Jinman, additional, Kim, Minjeong, additional, Kong, Bin, additional, Kumar, Ashnil, additional, Lan, Ning, additional, Li, Zhongyu, additional, Li, Lihua, additional, Liu, Brent J., additional, Ma, Junbo, additional, Mao, Chunhong, additional, Masood, Saleha, additional, Mun, Seong K., additional, Pan, Yuxiang, additional, Qin, Jing, additional, Ressom, Habtom W., additional, Schoenewald, Caroline, additional, Shaban-Nejad, Arash, additional, Shen, Hong-Bin, additional, Shin, Eun Kyong, additional, Simaan, Nabil, additional, Smith, Nadine, additional, Song, Yang, additional, Taylor, Russell H., additional, Tsai, Tsung-Heng, additional, Tu, Jiawei, additional, Urbin, Michael A., additional, Wan, Hao, additional, Wang, Hao, additional, Wang, Yuqi, additional, Wang, Qian, additional, Wang, Xiuying, additional, Wang, Minkun, additional, Wang, Ping, additional, Wang, Yue, additional, Webb, Andrew, additional, Weber, Douglas J., additional, Wen, Lingfeng, additional, Wu, Anna M., additional, Wu, Guorong, additional, Xu, Jia-Yan, additional, Yan, Chenggang, additional, Yan, Ke, additional, Yang, Defu, additional, Zhang, Xiaofeng, additional, Zhang, Shaoting, additional, Zhang, Bin, additional, Zhang, Zhen, additional, Zhu, Yitan, additional, Zhuang, Liujing, additional, and Zuo, Wangmeng, additional

Published
2020
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3. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Author

Dincer, Aylin, Gordon, Brian A, Allegri, Ricardo, Ances, Beau M, Berman, Sarah B, Brickman, Adam M, Brooks, William S, Cash, David M, Chhatwal, Jasmeer P, Farlow, Martin R, la Fougère, Christian, Fox, Nick C, Hari-Raj, Amrita, Fulham, Michael J, Jack, Clifford R, Joseph-Mathurin, Nelly, Karch, Celeste M, Lee, Athene, Levin, Johannes, Masters, Colin L, McDade, Eric M, Oh, Hwamee, Perrin, Richard J, Keefe, Sarah J, Raji, Cyrus, Salloway, Stephen P, Schofield, Peter R, Su, Yi, Villemagne, Victor L, Wang, Qing, Weiner, Michael W, Xiong, Chengjie, Yakushev, Igor, Morris, John C, Flores, Shaney, Bateman, Randall J, L S Benzinger, Tammie, DIAN, Dominantly Inherited Alzheimer Network, McKay, Nicole S, Paulick, Angela M, Shady Lewis, Kristine E, Feldman, Rebecca L, and Hornbeck, Russ C

Subjects
Aging, mcSUVR, mean cortical standardized uptake value ratio, LOAD, late-onset Alzheimer disease, ROI, region of interest, Hippocampus, AUROC, area under the receiver operating characteristic, genetics [Alzheimer Disease], Neurodegenerative, Alzheimer's Disease, lcsh:RC346-429, pathology [Alzheimer Disease], 0302 clinical medicine, ADAD, autosomal dominant Alzheimer disease, 2.1 Biological and endogenous factors, CNADRC/DIAN, cognitively normal controls, Aetiology, PCDIAN, preclinical autosomal dominant Alzheimer disease, pathology [Atrophy], PiB, Pittsburg compound-B, 05 social sciences, Neurodegeneration, Regular Article, PSEN1, Presenilin 1, Magnetic Resonance Imaging, Preclinical, Neurology, Knight ADRC, Knight Alzheimer Disease Research Center, Cohort, Neurological, Biomarker (medicine), lcsh:R858-859.7, Alzheimer's disease, Alzheimer disease, Cortical signature, Amyloid, PSEN2, Presenilin 2, Cognitive Neuroscience, metabolism [Amyloid beta-Peptides], Dominantly Inherited Alzheimer Network DIAN, lcsh:Computer applications to medicine. Medical informatics, 050105 experimental psychology, PET, positron emission tomography, Temporal lobe, Cortical thickness, 03 medical and health sciences, Atrophy, Clinical Research, APP, amyloid precursor protein, medicine, Acquired Cognitive Impairment, PCADRC, preclinical Alzheimer disease, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, DIAN, Dominantly Inherited Alzheimer Network, ddc:610, lcsh:Neurology. Diseases of the nervous system, Amyloid beta-Peptides, AD, Alzheimer disease, business.industry, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), medicine.disease, CDR, clinical dementia rating, Brain Disorders, HCV, total hippocampal volume, ROC, receiver operating characteristic, Cortical map, pathology [Hippocampus], Autosomal dominant Alzheimer disease, AV-45, florbetapir, Positron-Emission Tomography, Dementia, APOE, apolipoprotein E, SUVR, standardized uptake value ratio, Neurology (clinical), business, Neuroscience, MRI, magnetic resonance imaging, diagnostic imaging [Alzheimer Disease], 030217 neurology & neurosurgery
Abstract

Highlights • Cortical signatures selective to AD could provide an early MRI biomarker. • Autosomal dominant Alzheimer disease (ADAD) may model an ideal AD signature. • ADAD and late-onset maps overlap in parietal cortex but contain unique features. • Signatures predicted increasing amyloid within their own, but not across cohorts. • These results indicate atrophy in AD can take multiple spatial patterns., Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.

Published
2020

4. CONTRIBUTORS

Author

Aberg, Judith A., primary, Abernethy, Amy P., additional, Abrahm, Janet L., additional, Adolph, Michael, additional, Aherne, Michael, additional, Allsopp, K., additional, Altisent, Rogelio, additional, Alvarez, Carmen Fernandez, additional, Amigo, Pablo, additional, Anderson, Wendy G., additional, Ang, Sik Kim, additional, Antonelli, Tiziana, additional, Armstrong, John, additional, Armstrong, Wendy S., additional, Arnold, Robert M., additional, Arranz, Pilar, additional, Augustyns, Koen, additional, Sáenz-Diez, Isabel Barreiro-Meiro, additional, Barreto, Pilar, additional, Barton, Debra, additional, Bates, Ursula, additional, Fernandez-Creuchet Santos, Maria B., additional, Bátiz, Jacinto, additional, Benedetti, Costantino, additional, Bennani-Baiti, Nabila, additional, Bennett, Michael I., additional, Berger, Kevin, additional, Bhatnagar, Mamta, additional, Bicanovsky, Lesley, additional, Blue, Lynda, additional, Bobb, Barton, additional, Body, Jean-Jacques, additional, Borasio, Gian Domenico, additional, Borreani, Claudia, additional, Bozzetti, Federico, additional, Bozzetti, Valentina, additional, Braybrooke, Jason, additional, Breitbart, William, additional, Bresnihan, Barry, additional, Broeckaert, Bert, additional, Bruera, Eduardo, additional, Brune, Kay, additional, Buckhout, Bradley, additional, Butow, Phyllis N., additional, Byock, Ira, additional, Byrne, Anthony, additional, Byrne, Clare, additional, Cable-Williams, Beryl E., additional, Callin, Sarah E., additional, Casarett, David, additional, Casper, David, additional, Cassell, Eric J., additional, Cassileth, Barrie, additional, Castagno, Emanuele, additional, Centeno, Carlos, additional, Ceranski, Walter, additional, Ceulemans, Lucas, additional, Chadha, Meghna, additional, Chamberlain, Bruce H., additional, Chang, Eric L., additional, Chang, Victor T., additional, Chochinov, Harvey Max, additional, Chow, Edward, additional, Christ, Grace, additional, Clark, Katherine, additional, Clarke, Stephen, additional, Clayton, Josephine M., additional, Cleary, James F., additional, Clein, Lawrence J., additional, Clemens, Katri Elina, additional, Clemens, Libby, additional, Colebunders, Robert, additional, Connor, Steven R., additional, Conraads, Viviane, additional, Cooney, Colm, additional, Costantini, Massimo, additional, Couceiro, Azucena, additional, Covington, Holly, additional, Cowan, John D., additional, Coyne, Patrick, additional, Crawford, Garnet, additional, Creedon, Brian, additional, Cronin, Hilary, additional, Cullen, Garret, additional, Cummings, Jennifer E., additional, Currow, David C., additional, Daeninck, Paul J., additional, Dalinis, Pamela, additional, Das, Prajnan, additional, Davis, Mellar P., additional, Davison, Sara N., additional, Deamant, Catherine, additional, de Lima, Liliana, additional, Delany, Conor P., additional, Demeulenaere, Peter, additional, Dergham, Lena, additional, Derycke, Noël, additional, Dhupar, Rajeev, additional, Dicato, Mario, additional, Dickerson, Edwin D., additional, Dickman, Andrew, additional, Dietrich, Maria, additional, Dixon, Pamela, additional, Dodd, Philip C., additional, D'Olimpio, James T., additional, Dombernowsky, Per, additional, Dooley, Michael, additional, Dudgeon, Deborah, additional, Dunn, Geoffrey P., additional, Dunwoodie, David, additional, Eades, Jane, additional, El Osta, Badi, additional, Elbert-Avila, Katja, additional, Ellershaw, John, additional, Estfan, Bassam, additional, Exton, Louise, additional, Fairchild, Alysa, additional, Farrelly, Matthew, additional, Fassbender, Konrad, additional, Faulhaber, Jason, additional, Fearon, Kenneth C.H., additional, Fenelon, Lynda E., additional, Ferson, Peter F., additional, Feyer, Petra, additional, Filbet, Marilene, additional, Firth, Pam, additional, FitzGerald, Susan F., additional, Flood, Hugh D., additional, Floriani, Francesca Crippa, additional, Ford, Paul J., additional, Fortner, Barry, additional, Foth, Darlene, additional, Fowler, Bridget, additional, Frame, Karen, additional, Fraser, Thomas G., additional, Frost, Fred, additional, Fulham, Michael J., additional, Gagnon, Pierre R., additional, Gallagher, Lisa M., additional, Gambles, Maureen, additional, Giri, Subhasis K., additional, Glare, Paul, additional, Goh, Cynthia R., additional, Gómez-Batiste, Xavier, additional, Gramlich, Leah, additional, Grassi, Luigi, additional, Grauer, Phyllis A., additional, Green, Claire, additional, Griffiths, Gareth, additional, Griffo, Yvona, additional, Groninger, Hunter, additional, Gruenewald, David A., additional, Gubili, Jyothirmai, additional, Gutgsell, Terence L., additional, Gwyther, Elizabeth, additional, Haber, Paul S., additional, Haemers, Achiel, additional, Haley, Mindi C., additional, Hanna, Mazen A., additional, Hardy, Janet R., additional, Haselkorn, Jodie, additional, Hauser, Katherine, additional, Heaven, Cathy, additional, Herman, Michael, additional, Herrstedt, Jørn, additional, Higgins, Stephen, additional, Higginson, Irene J., additional, Hilden, Joanne M., additional, Hillenbrand, Kathryn L., additional, Hinz, Burkhard, additional, Homsi, Jade, additional, Hood, Kerry, additional, Hou, Juliet Y., additional, Hubens, Guy, additional, Hudson, Peter, additional, Hughes, John G., additional, Hunt, John, additional, Hurwitz, Craig A., additional, Ibinson, James, additional, Janjan, Nora, additional, Jaspers, Birgit, additional, Jehser, Thomas, additional, Joffe, A. Mark, additional, John, Laurence, additional, Johnstone, Jennie, additional, Jones, J. Stephen, additional, Kane, Javier R., additional, Karafa, Matthew T., additional, Keaveny, Andrew P., additional, Keefe, Dorothy M.K., additional, Kelso, Catherine McVearry, additional, Kenny, Rose Anne, additional, Kern, Martina, additional, Khoshknabi, Dilara Seyidova, additional, Kirkova, Jordanka, additional, Kirsh, Kenneth L., additional, Kissane, David W., additional, Klaschik, Eberhard, additional, Komurcu, Seref, additional, Kottke-Marchant, Kandice, additional, Kozell, Kathryn M., additional, Krishnan, Sunil, additional, Kuban, Deborah, additional, Laber, Damian A., additional, Lagman, Ruth L., additional, Lalla, Rajesh V., additional, Lane, Deforia, additional, Larkin, Philip J., additional, Lasheen, Wael, additional, Lawlor, Peter, additional, LeGrand, Susan B., additional, Lens, Vincent, additional, Leskuski, Dona, additional, Levack, Pamela, additional, Levetown, Marcia, additional, Lewandowski, Jeanne G., additional, Lewis, William R., additional, Librach, S. Lawrence, additional, Lichtenthal, Wendy G., additional, Lickiss, J. Norelle, additional, Lijoi, Stefano, additional, Lin, Edward, additional, Lipman, Arthur G., additional, Livrozet, Jean-Michel, additional, Lloyd-Williams, Mari, additional, Logan, Richard M., additional, Martín, Francisco López-Lara, additional, Loprinzi, Charles L., additional, Loughnane, John, additional, Lucey, Michael, additional, Lyckholm, Laurie, additional, Macmillan, Carol, additional, Mair, Frances, additional, Makoni, Stephen N., additional, Malik, Bushra, additional, Malone, Kevin, additional, Maltoni, Marco, additional, Mani, Aruna, additional, Marchand, Lucille R., additional, Mareiniss, Darren P., additional, Marsland, Anna L., additional, Marston, Joan, additional, Martinez, Julia Romero, additional, Martínez de Ubago, Isabel, additional, Martins, Lina M., additional, Maughan, Timothy S., additional, Mayland, Catriona, additional, McClement, Susan E., additional, McCutcheon, Ian, additional, McGee, Michael F., additional, McGill, Neil, additional, McNamara, Stephen, additional, McPherson, Mary Lynn, additional, McQuay, Henry, additional, McQuillan, Regina, additional, McQuown, Robert E., additional, Meiring, Michelle, additional, Mercadante, Sebastiano, additional, Meyer, Elaine C., additional, Miller, Randy D., additional, Millerick, Yvonne, additional, Miniero, Roberto, additional, Mohamed, Armin, additional, Mooka, Busi, additional, Morrison, Helen M., additional, Muir, J. Cameron, additional, Mulcahy, Fiona, additional, Mulcahy, Hugh E., additional, Muller, Monica, additional, Müller-Busch, H. Christof, additional, Murray, Scott A., additional, Nauck, Friedemann, additional, Neasham, Katherine, additional, Nkosi, Busisiwe, additional, Noble, Simon, additional, Noguera, Antonio, additional, Nowak, Anna K., additional, Nuñez-Olarte, Juan, additional, Obbens, Eugenie A.M.T., additional, O'Brien, Tony, additional, Olden, Megan, additional, O'Leary, Norma, additional, Oliver, David, additional, Oliviere, David, additional, Omlin, Aurelius G., additional, Osenga, Kaci, additional, O'Shea, Diarmuid, additional, Ostgathe, Christophe, additional, Ottery, Faith D., additional, Ouellette, Michel, additional, Overton, Edgar Turner, additional, Palacios, Moné, additional, Palmer, Robert, additional, Palmer, Teresa, additional, Paradis, Carmen, additional, Parala, Armida G., additional, Pascual-López, Antonio, additional, Passik, Steven D., additional, Pawlik, Timothy M., additional, Payne, Malcolm, additional, Payne, Sheila, additional, Paz, Silvia, additional, Pereira, José, additional, Perkins, George, additional, Peschardt, Karin, additional, Pessin, Hayley, additional, Peterson, Douglas E., additional, Podichetty, Vinod K., additional, Pollens, Robin, additional, Pontifex, Eliza, additional, Poole, Susan, additional, Porta-Sales, Josep, additional, Poston, Graeme, additional, Powazki, Ruth D., additional, Powderly, William, additional, Pozuelo, Leopoldo, additional, Prommer, Eric, additional, Puchalski, Christina M., additional, Radbruch, Lukas, additional, Raes, David F.J., additional, Read, Jane, additional, Reddy, Anantha, additional, Reger, Steven I., additional, Rehm, Susan J., additional, Reich, Stephen G., additional, Rocafort, Javier, additional, Rosenblatt, Adam, additional, Rushton, Cynda Hylton, additional, Russell, K. Mitchell, additional, Ryan, Karen, additional, Rybicki, Lisa A., additional, Sacerdote, Paola, additional, Sahgal, Vinod, additional, Ann Sammon, Mary, additional, Sandrock, Dirk, additional, Sands, Mark, additional, Schilling, Denise L., additional, Schulz, Valerie Nocent, additional, Schum, Lisa N., additional, Selwyn, Peter, additional, Shadd, Joshua, additional, Shapiro, Charles L., additional, Sharif, Aktham, additional, Sharp, Helen M., additional, Shepard, Kirk V., additional, Sherwood, J. Timothy, additional, Shrestha, Nabin K., additional, Skipworth, Richard J.E., additional, Smith, Howard S., additional, Solomon, Mildred Z., additional, de Prado Otero, Diego Soto, additional, Spencer, Denise Wells, additional, Spice, Ron, additional, Spiegel, David, additional, Srivastava, Manish, additional, Staffurth, John N., additional, Starling, Randall, additional, Stewart, Grant D., additional, Stjernswärd, Jan, additional, Strasser, Florian, additional, Strauss, Edna, additional, Strohscheer, Imke, additional, Summey, Brett Taylor, additional, Sutton, Graham, additional, Sykes, Nigel P., additional, Taege, Alan J., additional, Tamburini, Marcello, additional, Tarumi, Yoko, additional, Tassinari, Davide, additional, Tattersall, Martin H.N., additional, Theil, Karl S., additional, Thomas, Keri, additional, Tookman, Adrian, additional, Torrubia, María P., additional, Towers, Anna, additional, Tsoi, Daphne, additional, Tucker, Rodney O., additional, Tulsky, James A., additional, Tunick, Rachel A., additional, Turner, Claire, additional, Twaddle, Martha L., additional, Twomey, Marie, additional, Ullrich, Christina, additional, Urch, Catherine E., additional, Vachon, Mary L.S., additional, Van den Eynden, Bart, additional, Vigano, Antonio, additional, Vlieghe, Erika, additional, Volandes, Angelo E., additional, Voltz, Raymond, additional, Walker, Paul W., additional, Watanabe, Sharon, additional, Weber, Michael A., additional, Weinstein, Elizabeth, additional, Weinstein, Sharon M., additional, Weise, Kathryn L., additional, Weisenfluh, Sherri, additional, Welsh, John, additional, White, Clare, additional, Wilson, Donna M., additional, Wolfe, Joanne, additional, Yavuzsen, Tugba, additional, Yee, Albert J.M., additional, Yerian, Lisa M., additional, and Zucchetti, Elena, additional

Published
2009
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12. Contributors

Author

Adam, M., primary, Alpert, Nathaniel M., additional, Anderson, J.R., additional, Andreasen, Nancy C., additional, Antonini, A., additional, Ardekani, Babak A., additional, Arndt, Stephan, additional, Ashburner, John, additional, Ashworth, Sharon, additional, Bailey, Dale L., additional, Baker, E., additional, Barnes, D.G., additional, Bench, C., additional, Bendriem, B., additional, Berdichevsky, D., additional, Biegon, A., additional, Blair, R.C., additional, Blomqvist, G., additional, Bloomfield, Peter M., additional, Ponto, Laura L. Boles, additional, Brakeman, Paul, additional, Braun, Michael, additional, Brooks, David J., additional, Brown, C.K., additional, Brown, W.D., additional, Bruckbauer, T., additional, Buckley, K.R., additional, Calonder, C., additional, Campbell, Gregory, additional, Carson, Richard E., additional, Chaly, Thomas, additional, Chan, G. L-Y., additional, Chen, Chin-Tu, additional, Cizadlo, Ted, additional, Cliffe, I.A., additional, Collins, D.L., additional, Cooper, Malcolm, additional, Crivello, F., additional, Crossnoe, M., additional, Cumming, Paul, additional, Cunningham, Vincent J., additional, Czernin, J., additional, Dahlbom, M., additional, Damasio, H., additional, DaSilva, J., additional, Witherspoon, Margaret E. Daube-, additional, DeJesus, O.T., additional, Delforge, J., additional, Dhawan, Vijay, additional, Dickhoven, S., additional, Diksic, Mirko, additional, Eberl, Stefan, additional, Egan, G.F., additional, Eidelberg, David, additional, Eriksson, Lars, additional, Evans, Alan C., additional, Fink, G.R., additional, Fischman, Alan J., additional, Fisher, Ronald E., additional, Fletcher, A., additional, Fontaine, A., additional, Ford, I., additional, Forse, G., additional, Frackowiak, R.S.J., additional, Frank, R.J., additional, Friston, K.J., additional, Frost, J. James, additional, Frouin, V., additional, Fujita, Hideaki, additional, Fujiwara, Takehiko, additional, Fukuda, H., additional, Fulham, Michael J., additional, Gee, Anthony D., additional, Gillings, N., additional, Gjedde, Albert, additional, Glaser, Robert, additional, Grabowski, T.J., additional, Graf, R., additional, Grafton, S.T., additional, Graham, Michael M., additional, Grasby, P., additional, Gunn, R.N., additional, Günther, I., additional, Hagisawa, S., additional, Haida, A., additional, Halber, M., additional, Hallett, Mark, additional, Hansen, Lars K., additional, Harris, Greg, additional, Haslam, Jane, additional, Hasselbalch, Steen, additional, Hatazawa, Jun, additional, Heiss, W.-D., additional, Herholz, K., additional, Herscovitch, Peter, additional, Herzog, H., additional, Hichwa, Richard D., additional, Hoh, C., additional, Holden, J.E., additional, Holm, Søren, additional, Holmes, A.P., additional, Holmes, C.J., additional, Hooper, Patrick K., additional, Houle, S., additional, Houser, D., additional, Huang, Sung-Cheng, additional, Hume, S.P., additional, Hurtig, Richard R., additional, Hussey, D., additional, Hutton, Brian F., additional, Iacoboni, M., additional, Ido, T., additional, Iida, Hidehiro, additional, Inoue, O., additional, Ishii, Kazunari, additional, Ishikawa, Tatsuya, additional, Itoh, H., additional, Itoh, Masatoshi, additional, Iwata, R., additional, Jadali, F., additional, Jagust, W., additional, Jivan, S., additional, Joliot, M., additional, Jones, A.K.P., additional, Jones, C., additional, Jones, Terry, additional, Kanno, Iwao, additional, Kao, Chien-Min, additional, Kapur, S., additional, Karbe, H., additional, Kessler, J., additional, Kilbourn, Michael R., additional, Kimura, Yuichi, additional, Kinahan, P.E., additional, Knorr, U., additional, Kobayashi, K., additional, Kops, E. Rota, additional, Kosugi, Yukio, additional, Kruger, Mark, additional, Kuwabara, Hiroto, additional, Lammertsma, Adriaan A., additional, Laurier, L., additional, Law, Ian, additional, Leenders, K.L., additional, Legg, B., additional, Levin, Z., additional, Lin, Kang-Ping, additional, Links, Jonathan M., additional, Lipinski, B., additional, Lopresti, B.J., additional, Löttgen, J., additional, Luthra, S.K., additional, Ma, Yilong, additional, Maguire, R.P., additional, Mahmood, K., additional, Malizia, Andrea L., additional, Mankoff, David A., additional, Marenco, Stefano, additional, Marrett, S., additional, Mathis, C.A., additional, Matsumura, Y., additional, Mazoyer, B., additional, Mazziotta, John C., additional, McCarron, J.A., additional, Meguro, K., additional, Meikle, Steven R., additional, Mejia, Marco A., additional, Mellet, E., additional, Meltzer, Carolyn Cidis, additional, Meyer, Ernst, additional, Millet, P., additional, Minoshima, S., additional, Mintun, M.A., additional, Missimer, J., additional, Miura, Shuichi, additional, Miyake, M., additional, Momose, Toshimitsu, additional, Mørch, Niels, additional, Morris, Evan D., additional, Morrish, Paul K., additional, Morrison, S., additional, Müller-Gärtner, H.W., additional, Murase, Kenya, additional, Muzi, Mark, additional, Myers, R., additional, Nakamura, Takashi, additional, Nariai, Tadashi, additional, Neelin, P., additional, Nickles, R.J., additional, Nishikawa, Junichi, additional, Nishizawa, Sadahiko, additional, Nutt, D.J., additional, O'Keefe, G.J., additional, O'Leary, Daniel S., additional, O'Sullivan, B.T., additional, O'Sullivan, Finbarr, additional, Oberschelp, W., additional, Ogawa, Toshihide, additional, Ono, S., additional, Osman, S., additional, Patlak, Clifford, additional, Paulson, Olaf B., additional, Pawlik, Gunter, additional, Petit, L., additional, Pietrzyk, U., additional, Pike, V.W., additional, Poline, J.-B., additional, Poole, K., additional, Price, J.C., additional, Psylla, M., additional, Pyzalski, Robert, additional, Rajeswaran, S., additional, Rakshi, James S., additional, Ranicar, Alex, additional, Rauch, Scott L., additional, Remy, P., additional, Reutens, David C., additional, Roberts, Andy, additional, Rosenqvist, G., additional, Rottenberg, D.A., additional, Rousset, Olivier G., additional, Ruth, T.J., additional, Sadato, Norihiro, additional, Samson, Y., additional, Sasaki, H., additional, Sase, Mikiya, additional, Sashin, D., additional, Schaper, K., additional, Schlaug, G., additional, Schnorr, L., additional, Seitz, R.J., additional, Senda, Michio, additional, Shelton, S.E., additional, Shields, Anthony F., additional, Shimosegawa, Eku, additional, Shiraishi, Masahiro, additional, Shrager, Richard, additional, Sidtis, J.J., additional, Simpson, N.R., additional, Smith, D., additional, Smith, Donald F., additional, Snow, B.J., additional, Snyder, Abraham Z., additional, Sossi, V., additional, Spelle, L., additional, Spence, Alexander, additional, Strother, S.C., additional, Stumpf, Martin J., additional, Suganami, Yusuke, additional, Svarer, Claus, additional, Swerdloff, S.J., additional, Syrota, A., additional, Taguchi, A., additional, Talarico, E., additional, Taylor, Chris, additional, Tellman, L., additional, Thiel, A., additional, Danguy, H. J. Tochon-, additional, Toga, Arthur W., additional, Toussaint, P.-J., additional, Townsend, D.W., additional, Toyama, Hinako, additional, Trébossen, R., additional, Tzourio, N., additional, Uchiyama, A., additional, Uemura, Kazuo, additional, Uno, H., additional, Vafaee, M., additional, Vingerhoets, F.J.G., additional, Vontobel, P., additional, Wagner, R., additional, Watabe, Hiroshi, additional, Watkins, G. Leonard, additional, Watson, J.D.G., additional, Wernick, Miles, additional, Wienhard, K., additional, Wilson, A.A., additional, Wilson, S., additional, Wollenweber, Scott D., additional, Wong, Dean F., additional, Woods, Roger P., additional, Worsley, K.J., additional, Yan, Yuchen, additional, Yanai, K., additional, Yang, J., additional, Yap, Jeffrey T., additional, Yu, D.C., additional, Zeien, Gene, additional, Zhou, Y., additional, and Zubieta, Jon Kar, additional

Published
1996
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13. Hyper-fusion network for semi-automatic segmentation of skin lesions.

Author

Bi L, Fulham M, and Kim J

Subjects
Algorithms, Humans, Image Processing, Computer-Assisted methods, Neural Networks, Computer, Skin Diseases diagnostic imaging
Abstract

Segmentation of skin lesions is an important step for imaging-based clinical decision support systems. Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When there are, however, insufficient training data to cover all the variations in skin lesions, where lesions from different patients may have major differences in size/shape/texture, these methods failed to segment the lesions that have image characteristics, which are less common in the training datasets. FCN-based semi-automatic segmentation methods, which fuse user-inputs with high-level semantic image features derived from FCNs offer an ideal complement to overcome limitations of automatic segmentation methods. These semi-automatic methods rely on the automated state-of-the-art FCNs coupled with user-inputs for refinements, and therefore being able to tackle challenging skin lesions. However, there are a limited number of FCN-based semi-automatic segmentation methods and all these methods focused on 'early-fusion', where the first few convolutional layers are used to fuse image features and user-inputs and then derive fused image features for segmentation. For early-fusion based methods, because the user-input information can be lost after the first few convolutional layers, consequently, the user-input information will have limited guidance and constraint in segmenting the challenging skin lesions with inhomogeneous textures and fuzzy boundaries. Hence, in this work, we introduce a hyper-fusion network (HFN) to fuse the extracted user-inputs and image features over multiple stages. We separately extract complementary features which then allows for an iterative use of user-inputs along all the fusion stages to refine the segmentation. We evaluated our HFN on three well-established public benchmark datasets - ISBI Skin Lesion Challenge 2017, 2016 and PH2 - and our results show that the HFN is more accurate and generalizable than the state-of-the-art methods, in particular with challenging skin lesions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Published
2022
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14. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease.

Author

Dincer A, Gordon BA, Hari-Raj A, Keefe SJ, Flores S, McKay NS, Paulick AM, Shady Lewis KE, Feldman RL, Hornbeck RC, Allegri R, Ances BM, Berman SB, Brickman AM, Brooks WS, Cash DM, Chhatwal JP, Farlow MR, la Fougère C, Fox NC, Fulham MJ, Jack CR Jr, Joseph-Mathurin N, Karch CM, Lee A, Levin J, Masters CL, McDade EM, Oh H, Perrin RJ, Raji C, Salloway SP, Schofield PR, Su Y, Villemagne VL, Wang Q, Weiner MW, Xiong C, Yakushev I, Morris JC, Bateman RJ, and L S Benzinger T

Subjects
Amyloid beta-Peptides metabolism, Atrophy pathology, Hippocampus pathology, Humans, Magnetic Resonance Imaging, Positron-Emission Tomography, Alzheimer Disease diagnostic imaging, Alzheimer Disease genetics, Alzheimer Disease pathology
Abstract

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (n ADRC  = 381; n DIAN  = 145), preclinical (n ADRC  = 153; n DIAN  = 76), and cognitively impaired (n ADRC  = 54; n DIAN  = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11 C-Pittsburgh compound B or 18 F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2020
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15. Convolutional sparse kernel network for unsupervised medical image analysis.

Author

Ahn E, Kumar A, Fulham M, Feng D, and Kim J

Subjects
Humans, Diagnostic Imaging, Image Processing, Computer-Assisted methods, Supervised Machine Learning, Unsupervised Machine Learning
Abstract

The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems. Such supervised approaches, however, are difficult to implement in the medical domain where large volumes of labelled data are difficult to obtain due to the complexity of manual annotation and inter- and intra-observer variability in label assignment. We propose a new convolutional sparse kernel network (CSKN), which is a hierarchical unsupervised feature learning framework that addresses the challenge of learning representative visual features in medical image analysis domains where there is a lack of annotated training data. Our framework has three contributions: (i) we extend kernel learning to identify and represent invariant features across image sub-patches in an unsupervised manner. (ii) We initialise our kernel learning with a layer-wise pre-training scheme that leverages the sparsity inherent in medical images to extract initial discriminative features. (iii) We adapt a multi-scale spatial pyramid pooling (SPP) framework to capture subtle geometric differences between learned visual features. We evaluated our framework in medical image retrieval and classification on three public datasets. Our results show that our CSKN had better accuracy when compared to other conventional unsupervised methods and comparable accuracy to methods that used state-of-the-art supervised convolutional neural networks (CNNs). Our findings indicate that our unsupervised CSKN provides an opportunity to leverage unannotated big data in medical imaging repositories., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Published
2019
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16. The combined therapeutic effects of 131 iodine-labeled multifunctional copper sulfide-loaded microspheres in treating breast cancer.

Author

Liu Q, Qian Y, Li P, Zhang S, Wang Z, Liu J, Sun X, Fulham M, Feng D, Chen Z, Song S, Lu W, and Huang G

Abstract

Compared to conventional cancer treatment, combination therapy based on well-designed nanoscale platforms may offer an opportunity to eliminate tumors and reduce recurrence and metastasis. In this study, we prepared multifunctional microspheres loading 131 I-labeled hollow copper sulfide nanoparticles and paclitaxel ( 131 I-HCuSNPs-MS-PTX) for imaging and therapeutics of W256/B breast tumors in rats. 18 F-fluordeoxyglucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) imaging detected that the expansion of the tumor volume was delayed ( P <0.05) following intra-tumoral (i.t.) injection with 131 I-HCuSNPs-MS-PTX plus near-infrared (NIR) irradiation. The immunohistochemical analysis further confirmed the anti-tumor effect. The single photon emission computed tomography (SPECT)/photoacoustic imaging mediated by 131 I-HCuSNPs-MS-PTX demonstrated that microspheres were mainly distributed in the tumors with a relatively low distribution in other organs. Our results revealed that 131 I-HCuSNPs-MS-PTX offered combined photothermal, chemo- and radio-therapies, eliminating tumors at a relatively low dose, as well as allowing SPECT/CT and photoacoustic imaging monitoring of distribution of the injected agents non-invasively. The copper sulfide-loaded microspheres, 131 I-HCuSNPs-MS-PTX, can serve as a versatile theranostic agent in an orthotopic breast cancer model.

Published
2018
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17. Acute unilateral peripheral vestibulopathy in neurosyphilis.

Author

Young AS, Carroll AS, Welgampola MS, McCluskey PJ, van Hal SJ, Thompson EO, Burn J, Fulham MJ, and Halmagyi GM

Subjects
Aged, Delayed Diagnosis, Facial Nerve diagnostic imaging, Humans, Male, Vestibular Function Tests, Neurosyphilis complications, Neurosyphilis diagnosis, Vestibular Neuronitis diagnosis, Vestibular Neuronitis etiology
Abstract

Introduction: Neurosyphilis producing basal meningitis presenting as sequential transient cranial nerve palsies was well recognized before the antibiotic era., Objective: To report two patients presenting with acute unilateral peripheral vestibulopathy due to syphilitic basal meningitis., Results: In Case 1 basal meningitis occurred early in the secondary phase of the infection, in Case 2 in the late latent phase. The diagnosis was not made immediately in either case; in Case 1 after previous presentation with increasing hearing loss and then with facial palsy and then a subsequent presentation with optic neuritis; in Case 2 after investigation for possible lymphoma., Conclusion: Syphilitic basal meningitis in either the secondary or in the latent phase can present as acute unilateral peripheral vestibulopathy with transient involvement of the facial or auditory nerve., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Published
2017
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18. PET-CT for staging and early response: results from the Response-Adapted Therapy in Advanced Hodgkin Lymphoma study.

Author

Barrington SF, Kirkwood AA, Franceschetto A, Fulham MJ, Roberts TH, Almquist H, Brun E, Hjorthaug K, Viney ZN, Pike LC, Federico M, Luminari S, Radford J, Trotman J, Fosså A, Berkahn L, Molin D, D'Amore F, Sinclair DA, Smith P, O'Doherty MJ, Stevens L, and Johnson PW

Subjects
Biopsy, Bleomycin therapeutic use, Bone Marrow pathology, Dacarbazine therapeutic use, Doxorubicin therapeutic use, Female, Fluorodeoxyglucose F18 analysis, Humans, Male, Neoplasm Staging methods, Radiopharmaceuticals analysis, Vinblastine therapeutic use, Antineoplastic Combined Chemotherapy Protocols therapeutic use, Hodgkin Disease drug therapy, Hodgkin Disease pathology, Positron-Emission Tomography methods
Abstract

International guidelines recommend that positron emission tomography-computed tomography (PET-CT) should replace CT in Hodgkin lymphoma (HL). The aims of this study were to compare PET-CT with CT for staging and measure agreement between expert and local readers, using a 5-point scale (Deauville criteria), to adapt treatment in a clinical trial: Response-Adapted Therapy in Advanced Hodgkin Lymphoma (RATHL). Patients were staged using clinical assessment, CT, and bone marrow biopsy (RATHL stage). PET-CT was performed at baseline (PET0) and after 2 chemotherapy cycles (PET2) in a response-adapted design. PET-CT was reported centrally by experts at 5 national core laboratories. Local readers optionally scored PET2 scans. The RATHL and PET-CT stages were compared. Agreement among experts and between expert and local readers was measured. RATHL and PET0 stage were concordant in 938 (80%) patients. PET-CT upstaged 159 (14%) and downstaged 74 (6%) patients. Upstaging by extranodal disease in bone marrow (92), lung (11), or multiple sites (12) on PET-CT accounted for most discrepancies. Follow-up of discrepant findings confirmed the PET characterization of lesions in the vast majority. Five patients were upstaged by marrow biopsy and 7 by contrast-enhanced CT in the bowel and/or liver or spleen. PET2 agreement among experts (140 scans) with a κ (95% confidence interval) of 0.84 (0.76-0.91) was very good and between experts and local readers (300 scans) at 0.77 (0.68-0.86) was good. These results confirm PET-CT as the modern standard for staging HL and that response assessment using Deauville criteria is robust, enabling translation of RATHL results into clinical practice., (© 2016 by The American Society of Hematology.)

Published
2016
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19. A graph-based approach for the retrieval of multi-modality medical images.

Author

Kumar A, Kim J, Wen L, Fulham M, and Feng D

Subjects
Fluorodeoxyglucose F18, Humans, Lung Neoplasms pathology, Positron-Emission Tomography, Radiopharmaceuticals, Reproducibility of Results, Sensitivity and Specificity, Tomography, X-Ray Computed, Algorithms, Lung Neoplasms diagnostic imaging, Multimodal Imaging, Radiographic Image Interpretation, Computer-Assisted methods
Abstract

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Published
2014
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20. Radiation dosimetry of the translocator protein ligands [18F]PBR111 and [18F]PBR102.

Author

Verschuer JD, Towson J, Eberl S, Katsifis A, Henderson D, Lam P, Wen L, Loc'h C, Mattner F, Thomson S, Mohamed A, and Fulham MJ

Subjects
Animals, Female, Humans, Ligands, Male, Multimodal Imaging, Papio, Positron-Emission Tomography, Radiometry, Rats, Tomography, X-Ray Computed, Imidazoles metabolism, Pyridines metabolism, Receptors, GABA-A metabolism
Abstract

Introduction: The translocator protein (TSPO) ligands [18F]PBR111 and [18F]PBR102 show promise for imaging neuroinflammation. Our aim was to estimate the radiation dose to humans from primate positron emission tomography (PET) studies using these ligands and compare the results with those obtained from studies in rodents., Methods: [18F]PBR111 and [18F]PBR102 PET-computed tomography studies were carried out in baboons. The cumulated activity in the selected source organs was obtained from the volume of interest time-activity curves drawn on coronal PET slices and adjusted for organ mass relative to humans. Radiation dose estimates were calculated in OLINDA/EXM Version 1.1 from baboon studies and compared with those calculated from Sprague-Dawley rat tissue concentration studies, also adjusted for relative organ mass., Results: In baboons, both ligands cleared rapidly from brain, lung, kidney and spleen and more slowly from liver and heart. For [18F]PBR111, the renal excretion fraction was 6.5% and 17% for hepatobiliary excretion; for [18F]PBR102, the renal excretion was 3.0% and 15% for hepatobiliary excretion. The estimated effective dose in humans from baboon data was 0.021 mSv/MBq for each ligand, whilst from rat data, the estimates were 0.029 for [18F]PBR111 and 0.041 mSv/MBq for [18F]PBR102., Conclusion: Biodistribution in a nonhuman primate model is better suited than the rat model for the calculation of dosimetry parameters when translating these ligands from preclinical to human clinical studies. Effective dose calculated from rat data was overestimated compared to nonhuman primate data. The effective dose coefficient for both these TSPO ligands determined from PET studies in baboons is similar to that for [18F]FDG., (Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.)

Published
2012
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21. A rapid solid-phase extraction method for measurement of non-metabolised peripheral benzodiazepine receptor ligands, [(18)F]PBR102 and [(18)F]PBR111, in rat and primate plasma.

Author

Katsifis A, Loc'h C, Henderson D, Bourdier T, Pham T, Greguric I, Lam P, Callaghan P, Mattner F, Eberl S, and Fulham M

Subjects
Acetamides chemistry, Acetamides metabolism, Animals, Chromatography, High Pressure Liquid, Chromatography, Thin Layer, Ligands, Male, Papio, Radiopharmaceuticals blood, Radiopharmaceuticals chemistry, Radiopharmaceuticals isolation & purification, Radiopharmaceuticals metabolism, Rats, Reproducibility of Results, Time Factors, Acetamides blood, Acetamides isolation & purification, Blood Chemical Analysis methods, Carrier Proteins metabolism, Fluorine Radioisotopes chemistry, Receptors, GABA-A metabolism, Solid Phase Extraction methods
Abstract

Objectives: To develop a rapid and reliable method for estimating non-metabolised PBR ligands fluoroethoxy ([(18)F]PBR102)- and fluoropropoxy ([(18)F]PBR111)-substituted 2-(6-chloro-2-phenyl)imidazo[1,2-a]pyridine-3-yl)-N,N-diethylacetamides in plasma., Methods: Rats and baboons were imaged with PET up to 2 h postinjection of [(18)F]PBR102 and [(18)F]PBR111 under baseline conditions, after pre-blocking or displacement with PK11195. Arterial plasma samples were directly analysed by reverse-phase solid-phase extraction (RP-SPE) and RP-HPLC and by normal-phase TLC. SPE cartridges were successively washed with acetonitrile/water mixtures. SPE eluant radioactivity was measured in a γ-counter to determine the parent compound fraction and then analysed by HPLC and TLC for validation., Results: In SPE, hydrophilic and lipophilic radiolabelled metabolites were eluted in water and 20% acetonitrile/water. All non-metabolised [(18)F]PBR102 and [(18)F]PBR111 were in SPE acetonitrile fraction as confirmed by HPLC and TLC analysis. Unchanged (%) [(18)F]PBR102 and [(18)F]PBR111 from SPE analysis in rat and baboon plasma agreed with those from HPLC and TLC analysis. In rats and baboons, the fraction of unchanged tracer followed a bi-exponential decrease, with half-lives of 7 to 10 min for the fast component and >80 min for the slow component for both tracers., Conclusions: Direct plasma SPE analysis of [(18)F]PBR102 and [(18)F]PBR111 can reliably estimate parent compound fraction. SPE was superior to HPLC for samples with low activity; it allows rapid and accurate metabolite analysis of a large number of plasma samples for improved estimation of metabolite-corrected input function during quantitative PET imaging studies., (Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.)

Published
2011
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