The University of Queensland

The Knowledge Translation of Early Cerebral Palsy (KiTE CP) Study: Implementing Screening among a High-risk Prospective Cohort of Australian infants

Kwong, Amanda KL., Eeles, Abbey, Anderson, Peter J., Badawi, Nadia, Boyd, Roslyn N., Cameron, Kate L., Cheong, Jeanie, Colditz, Paul, Koorts, Pieter, Crowle, Cathryn, Dale, Russell C., Doyle, Lex W., Fahey, Michael, George, Joanne, Hunt, Rod W., McNamara, Lynda, Morgan, Catherine, Novak, Iona, Olsen, Joy E., Reid, Nadia, Rieger, Ingrid, Whittingham, Koa and Spittle, Alicia J. (2024). The Knowledge Translation of Early Cerebral Palsy (KiTE CP) Study: Implementing Screening among a High-risk Prospective Cohort of Australian infants. The Journal of Pediatrics, 268 113949, 113949. doi: 10.1016/j.jpeds.2024.113949

Diagnostic accuracy of the Hammersmith Neonatal Neurological Examination in predicting motor outcome at 12 months for infants born very preterm

Howard, Grace T., Baque, Emmah, Colditz, Paul B., Chatfield, Mark D., Ware, Robert S., Boyd, Roslyn N. and George, Joanne M. (2023). Diagnostic accuracy of the Hammersmith Neonatal Neurological Examination in predicting motor outcome at 12 months for infants born very preterm. Developmental Medicine and Child Neurology, 65 (8), 1061-1072. doi: 10.1111/dmcn.15512

Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants

Pagnozzi, Alex M., van Eijk, Liza, Pannek, Kerstin, Boyd, Roslyn N., Saha, Susmita, George, Joanne, Bora, Samudragupta, Bradford, DanaKai, Fahey, Michael, Ditchfield, Michael, Malhotra, Atul, Liley, Helen, Colditz, Paul B., Rose, Stephen and Fripp, Jurgen (2023). Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants. NeuroImage, 267 119815, 1-10. doi: 10.1016/j.neuroimage.2022.119815

Neurological examination at 32-weeks postmenstrual age predicts 12-month cognitive outcomes in very preterm-born infants

Huf, Isabel U., Baque, Emmah, Colditz, Paul B., Chatfield, Mark D., Ware, Robert S., Boyd, Roslyn N. and George, Joanne M. (2022). Neurological examination at 32-weeks postmenstrual age predicts 12-month cognitive outcomes in very preterm-born infants. Pediatric Research, 93 (6), 1721-1727. doi: 10.1038/s41390-022-02310-6

Early motor repertoire of very preterm infants and relationships with 2-year neurodevelopment

Kwong, Amanda K.-L., Boyd, Roslyn N., Chatfield, Mark D., Ware, Robert S., Colditz, Paul B. and George, Joanne M. (2022). Early motor repertoire of very preterm infants and relationships with 2-year neurodevelopment. Journal of Clinical Medicine, 11 (7) 1833, 1833. doi: 10.3390/jcm11071833

Automating quantitative measures of an established conventional MRI scoring system for preterm-born infants scanned between 29 and 47 weeks’ postmenstrual age

van Eijk, L., Seidel, M., Pannek, K., George, J.M., Fiori, S., Guzzetta, A., Coulthard, A., Bursle, J., Ware, R.S., Bradford, D., Rose, S., Colditz, P.B., Boyd, R.N. and Fripp, J. (2021). Automating quantitative measures of an established conventional MRI scoring system for preterm-born infants scanned between 29 and 47 weeks’ postmenstrual age. American Journal of Neuroradiology, 42 (10), 1870-1877. doi: 10.3174/ajnr.a7230

Early clinical and MRI biomarkers of cognitive and motor outcomes in very preterm born infants

George, Joanne M., Colditz, Paul B., Chatfield, Mark D., Fiori, Simona, Pannek, Kerstin, Fripp, Jurgen, Guzzetta, Andrea, Rose, Stephen E., Ware, Robert S. and Boyd, Roslyn N. (2021). Early clinical and MRI biomarkers of cognitive and motor outcomes in very preterm born infants. Pediatric Research, 90 (6), 1243-1250. doi: 10.1038/s41390-021-01399-5

Brain microstructure and morphology of very preterm-born infants at term equivalent age: associations with motor and cognitive outcomes at 1 and 2 years

Pannek, Kerstin, George, Joanne M., Boyd, Roslyn N., Colditz, Paul B., Rose, Stephen E. and Fripp, Jurgen (2020). Brain microstructure and morphology of very preterm-born infants at term equivalent age: associations with motor and cognitive outcomes at 1 and 2 years. NeuroImage, 221 117163, 117163. doi: 10.1016/j.neuroimage.2020.117163

Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model

Saha, Susmita, Pagnozzi, Alex, Bourgeat, Pierrick, George, Joanne M., Bradford, DanaKai, Colditz, Paul B., Boyd, Roslyn N., Rose, Stephen E., Fripp, Jurgen and Pannek, Kerstin (2020). Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model. NeuroImage, 215 116807, 116807. doi: 10.1016/j.neuroimage.2020.116807

Prediction of childhood brain outcomes in infants born preterm using neonatal MRI and concurrent clinical biomarkers (PREBO-6): study protocol for a prospective cohort study

George, Joanne M., Pagnozzi, Alex M., Bora, Samudragupta, Boyd, Roslyn N., Colditz, Paul B., Rose, Stephen E., Ware, Robert S., Pannek, Kerstin, Bursle, Jane E., Fripp, Jurgen, Barlow, Karen, Iyer, Kartik, Leishman, Shaneen J. and Jendra, Rebecca L. (2020). Prediction of childhood brain outcomes in infants born preterm using neonatal MRI and concurrent clinical biomarkers (PREBO-6): study protocol for a prospective cohort study. BMJ Open, 10 (5) e036480, e036480. doi: 10.1136/bmjopen-2019-036480

Relationship between very early brain structure and neuromotor, neurological and neurobehavioral function in infants born <31 weeks gestational age

George, Joanne M., Fiori, Simona, Fripp, Jurgen, Pannek, Kerstin, Guzzetta, Andrea, David, Michael, Ware, Robert S, Rose, Stephen E, Colditz, Paul B and Boyd, Roslyn N (2018). Relationship between very early brain structure and neuromotor, neurological and neurobehavioral function in infants born <31 weeks gestational age. Early Human Development, 117, 74-82. doi: 10.1016/j.earlhumdev.2017.12.014

Fixel-based analysis reveals alterations is brain microstructure and macrostructure of preterm-born infants at term equivalent age

Pannek, Kerstin, Fripp, Jurgen, George, Joanne M., Fiori, Simona, Colditz, Paul B., Boyd, Roslyn N. and Rose, Stephen E. (2018). Fixel-based analysis reveals alterations is brain microstructure and macrostructure of preterm-born infants at term equivalent age. NeuroImage: Clinical, 18, 51-59. doi: 10.1016/j.nicl.2018.01.003

Erratum: Validation of an MRI Brain Injury and Growth Scoring System in Very Preterm Infants Scanned at 29- to 35-Week Postmenstrual Age (vol 38, pg 1435, 2017)

George, J. M., Fiori, S., Fripp, J., Pannek, K., Bursle, J., Moldrich, R. X., Guzzetta, A., Coulthard, A., Ware, R. S., Rose, S. E., Colditz, P. B. and Boyd, R. N. (2018). Erratum: Validation of an MRI Brain Injury and Growth Scoring System in Very Preterm Infants Scanned at 29- to 35-Week Postmenstrual Age (vol 38, pg 1435, 2017). American Journal of Neuroradiology, 39 (1), E8-E8. doi: 10.3174/ajnr.A5448

Diagnostic accuracy of early magnetic resonance imaging to determine motor outcomes in infants born preterm: A systematic review and meta-analysis

George, Joanne M, Pannek, Kerstin, Rose, Stephen E, Ware, Robert S, Colditz, Paul B and Boyd, Roslyn N (2017). Diagnostic accuracy of early magnetic resonance imaging to determine motor outcomes in infants born preterm: A systematic review and meta-analysis. Developmental Medicine and Child Neurology, 60 (2), 134-146. doi: 10.1111/dmcn.13611

Reply

George, J M, Fiori, S, Fripp, J, Pannek, K, Bursle, J, Moldrich, R X, Guzzetta, A, Coulthard, A, Ware, R S, Rose, S E, Colditz, P B and Boyd, R N (2017). Reply. American Journal of Neuroradiology, 39 (3), E40-E40. doi: 10.3174/ajnr.A5478

Validation of an MRI brain injury and growth scoring system in very preterm infants scanned at 29-to 35-week postmenstrual age

George, J. M., Fiori, S., Fripp, J., Pannek, K., Bursle, J., Moldrich, R. X., Guzzetta, A., Coulthard, A., Ware, R. S., Rose, S. E., Colditz, P. B. and Boyd, R. N. (2017). Validation of an MRI brain injury and growth scoring system in very preterm infants scanned at 29-to 35-week postmenstrual age. American Journal of Neuroradiology, 38 (7), 1435-1442. doi: 10.3174/ajnr.A5191

PPREMO: A prospective cohort study of preterm infant brain structure and function to predict neurodevelopmental outcome

George, Joanne M., Boyd, Roslyn N., Colditz, Paul B., Rose, Stephen E., Pannek, Kerstin, Fripp, Jurgen, Lingwood, Barbara E., Lai, Melissa M., Kong, Annice HT., Ware, Robert S., Coulthard, Alan, Finn, Christine M. and Bandaranayake, Sasaka E. (2015). PPREMO: A prospective cohort study of preterm infant brain structure and function to predict neurodevelopmental outcome. BMC Pediatrics, 15 (123) 123, 123. doi: 10.1186/s12887-015-0439-z

Investigating brain age deviation in preterm infants: a deep learning approach

Saha, Susmita, Pagnozzi, Alex, George, Joanne, Colditz, Paul B., Boyd, Roslyn, Rose, Stephen, Fripp, Jurgen and Pannek, Kerstin (2018). Investigating brain age deviation in preterm infants: a deep learning approach. First International Workshop DATRA 2018 and Third International Workshop PIPPI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, 16 September 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-00807-9_9

A spatio-temporal atlas of neonatal diffusion MRI based on kernel ridge regression

Shen, Kaikai, Fripp, Jurgen, Pannek, Kerstin, George, Joanne, Colditz, Paul, Boyd, Roslyn and Rose, Stephen (2017). A spatio-temporal atlas of neonatal diffusion MRI based on kernel ridge regression. 14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Melbourne, VIC, Australia, 18 - 21 April 2017. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ISBI.2017.7950484

The relationship between brain structure and function of very preterm infants, and the ability to predict neurodevelopmental outcomes

George, Joanne (2017). The relationship between brain structure and function of very preterm infants, and the ability to predict neurodevelopmental outcomes. PhD Thesis, Faculty of Medicine, The University of Queensland. doi: 10.14264/uql.2017.917