Parikh Lab

Publications

Tamm, L; McNally, KA; Altaye, M; Parikh, NA. Mathematics abilities associated with adaptive functioning in preschool children born preterm. Child Neuropsychology. 2024; 30:315-328.

Fisher, AP; Miley, AE; Glazer, S; Gies, LM; Parikh, NA; Lam, L; Wade, SL. Feasibility and acceptability of an online parenting intervention to address behaviour problems in moderately to extremely preterm pre-school and school-age children. Child: Care, Health and Development. 2024; 50:e13209.

Fu, TT; Barnes-Davis, ME; Fujiwara, H; Folger, AT; Merhar, SL; Kadis, DS; Poindexter, BB; Parikh, NA. Correlation of NICU anthropometry in extremely preterm infants with brain development and language scores at early school age. Scientific Reports. 2023; 13:15273.

Cuervo, S; Creaghead, N; Vannest, J; Hunter, L; Ionio, C; Altaye, M; Parikh, NA. Language Outcomes of Children Born Very Preterm in Relation to Early Maternal Depression and Anxiety. Brain Sciences. 2023; 13:1355.

Patronick, J; Glazer, S; Sidol, C; Parikh, NA; Wade, SL. Parenting Interventions Targeting Behavior for Children Born Preterm or Low Birth Weight: A Systematic Review. Journal of Pediatric Psychology. 2023; 48:676-687.

Li, Z; Li, H; Ralescu, AL; Dillman, JR; Parikh, NA; He, L. A novel collaborative self-supervised learning method for radiomic data. Neuroimage. 2023; 277:120229.

Wang, J; Li, H; Qu, G; Cecil, KM; Dillman, JR; Parikh, NA; He, L. Dynamic weighted hypergraph convolutional network for brain functional connectome analysis. Medical Image Analysis. 2023; 87:102828.

Kojima, K; Liu, C; Ehrlich, S; Kline-Fath, BM; Jain, S; Parikh, NA. Early surgery in very preterm infants is associated with brain abnormalities on term MRI: a propensity score analysis. Journal of Perinatology. 2023; 43:877-883.

Li, H; Li, Z; Du, K; Zhu, Y; Parikh, NA; He, L. A Semi-Supervised Graph Convolutional Network for Early Prediction of Motor Abnormalities in Very Preterm Infants. Diagnostics. 2023; 13:1508.

Kelly, KJ; Hutton, JS; Parikh, NA; Barnes-Davis, ME. Neuroimaging of brain connectivity related to reading outcomes in children born preterm: A critical narrative review. Frontiers in Pediatrics. 2023; 11:1083364.

Mahabee-Gittens, EM; Kline-Fath, BM; Harun, N; Folger, AT; He, L; Parikh, NA. Prenatal tobacco smoke exposure and risk of brain abnormalities on magnetic resonance imaging at term in infants born very preterm. 2023; 5:100856.

Li, Z; Li, H; Ralescu, AL; Dillman, JR; Parikh, NA; He, L. A Novel Collaborative Self-Supervised Learning Method for Radiomic Data. 2023; abs/2302.09807.

Brumbaugh, JE; Bell, EF; Do, BT; Greenberg, RG; Stoll, BJ; DeMauro, SB; Harmon, HM; Hintz, SR; Das, A; Puopolo, KM; et al. Incidence of and Neurodevelopmental Outcomes After Late-Onset Meningitis Among Children Born Extremely Preterm. JAMA Network Open. 2022; 5:e2245826.

Kline, JE; Dudley, J; Illapani, VS P; Li, H; Kline-Fath, B; Tkach, J; He, L; Yuan, W; Parikh, NA. Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology. Neuroimage. 2022; 264:119727.

Li, Z; Li, H; Braimah, A; Dillman, JR; Parikh, NA; He, L. A novel Ontology-guided Attribute Partitioning ensemble learning model for early prediction of cognitive deficits using quantitative Structural MRI in very preterm infants. Neuroimage. 2022; 260:119484.

Ali, R; Li, H; Dillman, JR; Altaye, M; Wang, H; Parikh, NA; He, L. A self-training deep neural network for early prediction of cognitive deficits in very preterm infants using brain functional connectome data. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2022; 52:2227-2240.

Jain, VG; Kline, JE; He, L; Kline-Fath, BM; Altaye, M; Muglia, LJ; DeFranco, EA; Ambalavanan, N; Parikh, NA. Acute histologic chorioamnionitis independently and directly increases the risk for brain abnormalities seen on magnetic resonance imaging in very preterm infants. American Journal of Obstetrics and Gynecology. 2022; 227:623.e1-623.e13.

Illapani, VS P; Edmondson, DA; Cecil, KM; Altaye, M; Kumar, M; Harpster, K; Parikh, NA. Magnetic resonance spectroscopy brain metabolites at term and 3-year neurodevelopmental outcomes in very preterm infants. Pediatric Research. 2022; 92:299-306.

Weber, AM; Jackson, YC; Elder, MR; Remer, SL; Parikh, NA; Hofherr, JJ; Voos, KC; Kaplan, HC. Application of a Risk Management Framework to Parent Sleep During Skin-to-Skin Care in the NICU. JOGNN - Journal of Obstetric, Gynecologic, and Neonatal Nursing. 2022; 51:336-348.

Chen, M; Li, H; Fan, H; Dillman, JR; Wang, H; Altaye, M; Zhang, B; Parikh, NA; He, L. ConCeptCNN: A novel multi-filter convolutional neural network for the prediction of neurodevelopmental disorders using brain connectome. Medical Physics. 2022; 49:3171-3184.

Zhang, H; Li, H; Dillman, JR; Parikh, NA; He, L. Multi-Contrast MRI Image Synthesis Using Switchable Cycle-Consistent Generative Adversarial Networks. Diagnostics. 2022; 12:816.

Barnes-Davis, ME; Williamson, BJ; Merhar, SL; Nagaraj, UD; Parikh, NA; Kadis, DS. Extracallosal Structural Connectivity Is Positively Associated With Language Performance in Well-Performing Children Born Extremely Preterm. Frontiers in Pediatrics. 2022; 10:821121.

Chandwani, R; Harpster, K; Kline, JE; Mehta, V; Wang, H; Merhar, SL; Schwartz, TL; Parikh, NA. Brain microstructural antecedents of visual difficulties in infants born very preterm. NeuroImage-Clinical. 2022; 34:102987.

Li, Z; Li, H; Braimah, A; Dillman, JR; Parikh, NA; He, L. A novel Ontology-guided Attribute Partitioning ensemble learning model for early prediction of cognitive deficits using quantitative Structural MRI in very preterm infants. Neuroimage. 2022; 260:119484.

Li, Z; Li, H; Braimah, A; Dillman, JR; Parikh, NA; He, L. A Novel Ontology-guided Attribute Partitioning Ensemble Learning Model for Early Prediction of Cognitive Deficits using Quantitative Structural MRI in Very Preterm Infants. 2022; abs/2202.04134.

Kline, JE; Yuan, W; Harpster, K; Altaye, M; Parikh, NA. Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants. Neuroimage. 2021; 245:118688.

Chalak, LF; Pappas, A; Tan, S; Das, A; Sánchez, PJ; Laptook, AR; Van Meurs, KP; Shankaran, S; Bell, EF; Davis, AS; et al. Association of Increased Seizures During Rewarming With Abnormal Neurodevelopmental Outcomes at 2-Year Follow-up: A Nested Multisite Cohort Study. JAMA Neurology. 2021; 78:1-10.

He, L; Li, H; Chen, M; Wang, J; Altaye, M; Dillman, JR; Parikh, NA. Deep Multimodal Learning From MRI and Clinical Data for Early Prediction of Neurodevelopmental Deficits in Very Preterm Infants. Frontiers in Neuroscience. 2021; 15:753033.

Chandwani, R; Kline, JE; Harpster, K; Tkach, J; Parikh, NA; Altaye, M; Arnsperger, A; Beiersdorfer, T; Bridgewater, K; Cahill, T; et al. Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants. Human Brain Mapping. 2021; 42:4708-4721.

Bugada, MC; Kline, JE; Parikh, NA. Microstructural Measures of the Inferior Longitudinal Fasciculus Predict Later Cognitive and Language Development in Infants Born With Extremely Low Birth Weight. Journal of Child Neurology. 2021; 36:981-989.

Parikh, NA. Is a New Era Coming for Bronchopulmonary Dysplasia Prevention With Corticosteroids?-Reply. JAMA Pediatrics. 2021; 175:1080-1081.

Merhar, SL; Jiang, W; Parikh, NA; Yin, W; Zhou, Z; Tkach, JA; Wang, L; Kline-Fath, BM; He, L; Braimah, A; et al. Effects of prenatal opioid exposure on functional networks in infancy. Developmental Cognitive Neuroscience. 2021; 51:100996.

Barnes-Davis, ME; Fujiwara, H; Drury, G; Merhar, SL; Parikh, NA; Kadis, DS. Functional Hyperconnectivity during a Stories Listening Task in Magnetoencephalography Is Associated with Language Gains for Children Born Extremely Preterm. Brain Sciences. 2021; 11:1271.

Yuan, W; Tamm, L; Harpster, K; Altaye, M; Illapani, VS P; Parikh, NA. Effects of intraventricular hemorrhage on white matter microstructural changes at term and early developmental outcomes in infants born very preterm. Neuroradiology: a journal devoted to neuroimaging and interventional neuroradiology. 2021; 63:1549-1561.

Merhar, SL; Kline, JE; Braimah, A; Kline-Fath, BM; Tkach, JA; Altaye, M; He, L; Parikh, NA. Prenatal opioid exposure is associated with smaller brain volumes in multiple regions. Pediatric Research. 2021; 90:397-402.

Adams-Chapman, I; Watterberg, KL; Nolen, TL; Hirsch, S; Cole, CA; Cotten, CM; Oh, W; Poindexter, BB; Zaterka-Baxter, KM; Das, A; et al. Neurodevelopmental outcome of preterm infants enrolled in myo-inositol randomized controlled trial. Journal of Perinatology. 2021; 41:2072-2087.

Parikh, MN; Chen, M; Braimah, A; Kline, J; McNally, K; Logan, JW; Tamm, L; Yeates, KO; Yuan, W; He, L; et al. Diffusion MRI Microstructural Abnormalities at Term-Equivalent Age Are Associated with Neurodevelopmental Outcomes at 3 Years of Age in Very Preterm Infants. American Journal of Neuroradiology. 2021; 42:1535-1542.

Parikh, NA. Does prolonged ductal patency cause bronchopulmonary dysplasia or is the direction of causation reversed?. The Journal of Pediatrics. 2021; 234:290-291.

Parikh, NA. The Swinging Pendulum of Postnatal Corticosteroid Use. JAMA Pediatrics. 2021; 175:e206842.

Parikh, NA; Sharma, P; He, L; Li, H; Altaye, M; Priyanka Illapani, VS; Arnsperger, A; Beiersdorfer, T; Bridgewater, K; Cahill, T; et al. Perinatal Risk and Protective Factors in the Development of Diffuse White Matter Abnormality on Term-Equivalent Age Magnetic Resonance Imaging in Infants Born Very Preterm. The Journal of Pediatrics. 2021; 233:58-65.e3.

Li, H; Chen, M; Wang, J; Illapani, VS P; Parikh, NA; He, L. Automatic Segmentation of Diffuse White Matter Abnormality on T2-weighted Brain MR Images Using Deep Learning in Very Preterm Infants. Radiology. Artificial intelligence.. 2021; 3:e200166.

Harpster, K; Merhar, S; Priyanka Illapani, VS; Peyton, C; Kline-Fath, B; Parikh, NA. Associations Between Early Structural Magnetic Resonance Imaging, Hammersmith Infant Neurological Examination, and General Movements Assessment in Infants Born Very Preterm. The Journal of Pediatrics. 2021; 232:80-86.e2.

Dworetz, AR; Natarajan, G; Langer, J; Kinlaw, K; James, JR; Bidegain, M; Das, A; Poindexter, B; Bell, EF; Cotten, CM; et al. Withholding or withdrawing life-sustaining treatment in extremely low gestational age neonates. Archives of Disease in Childhood: Fetal and Neonatal Edition. 2021; 106:238-243.

Li, H; He, L; Dudley, JA; Maloney, TC; Somasundaram, E; Brady, SL; Parikh, NA; Dillman, JR. DeepLiverNet: a deep transfer learning model for classifying liver stiffness using clinical and T2-weighted magnetic resonance imaging data in children and young adults. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2021; 51:392-402.

Laptook, AR; Shankaran, S; Barnes, P; Rollins, N; Do, BT; Parikh, NA; Hamrick, S; Hintz, SR; Tyson, JE; Bell, EF; et al. Limitations of Conventional Magnetic Resonance Imaging as a Predictor of Death or Disability Following Neonatal Hypoxic-Ischemic Encephalopathy in the Late Hypothermia Trial. The Journal of Pediatrics. 2021; 230:106-111.e6.

Logan, JW; Tan, J; Skalak, M; Fathi, O; He, L; Klein, J; Klebanoff, M; Parikh, NA. Adverse effects of perinatal illness severity on neurodevelopment are partially mediated by early brain abnormalities in infants born very preterm. Journal of Perinatology. 2021; 41:519-527.

Kline, JE; Illapani, VS P; Li, H; He, L; Yuan, W; Parikh, NA. Diffuse white matter abnormality in very preterm infants at term reflects reduced brain network efficiency. NeuroImage-Clinical. 2021; 31:102739.

Barnes-Davis, ME; Merhar, SL; Holland, SK; Parikh, NA; Kadis, DS. Extremely preterm children demonstrate hyperconnectivity during verb generation: A multimodal approach. NeuroImage-Clinical. 2021; 30:102589.

Parikh, NA; Harpster, K; He, L; Illapani, VS P; Khalid, FC; Klebanoff, MA; O’Shea, TM; Altaye, M. Novel diffuse white matter abnormality biomarker at term-equivalent age enhances prediction of long-term motor development in very preterm children. Scientific Reports. 2020; 10:15920.

He, L; Li, H; Wang, J; Chen, M; Gozdas, E; Dillman, JR; Parikh, NA. A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants. Scientific Reports. 2020; 10:15072.

Chen, M; Li, H; Wang, J; Yuan, W; Altaye, M; Parikh, NA; He, L. Early Prediction of Cognitive Deficit in Very Preterm Infants Using Brain Structural Connectome With Transfer Learning Enhanced Deep Convolutional Neural Networks. Frontiers in Neuroscience. 2020; 14:858.

Kline, JE; Illapani, VS P; He, L; Altaye, M; Logan, JW; Parikh, NA. Early cortical maturation predicts neurodevelopment in very preterm infants. Archives of Disease in Childhood: Fetal and Neonatal Edition. 2020; 105:460-465.

Tamm, L; Patel, M; Peugh, J; Kline-Fath, BM; Parikh, NA; Cincinnati, IN E P. Early brain abnormalities in infants born very preterm predict under-reactive temperament. Early Human Development. 2020; 144:104985.

Parikh, NA; He, L; Li, H; Illapani, VS P; Klebanoff, MA. Antecedents of Objectively Diagnosed Diffuse White Matter Abnormality in Very Preterm Infants. Pediatric Neurology. 2020; 106:56-62.

Parikh, NA; He, L; Illapani, VS P; Altaye, M; Folger, AT; Yeates, KO. Objectively Diagnosed Diffuse White Matter Abnormality at Term Is an Independent Predictor of Cognitive and Language Outcomes in Infants Born Very Preterm. The Journal of Pediatrics. 2020; 220:56-63.

Brumbaugh, JE; Bell, EF; Grey, SF; DeMauro, SB; Vohr, BR; Harmon, HM; Bann, CM; Rysavy, MA; Logan, JW; Colaizy, TT; et al. Behavior Profiles at 2 Years for Children Born Extremely Preterm with Bronchopulmonary Dysplasia. The Journal of Pediatrics. 2020; 219:152-159.e5.

Harmon, HM; Jensen, EA; Tan, S; Chaudhary, AS; Slaughter, JL; Bell, EF; Wyckoff, MH; Hensman, AM; Sokol, GM; DeMauro, SB; et al. Timing of postnatal steroids for bronchopulmonary dysplasia: association with pulmonary and neurodevelopmental outcomes. Journal of Perinatology. 2020; 40:616-627.

Merhar, SL; Gozdas, E; Tkach, JA; Parikh, NA; Kline-Fath, BM; He, L; Yuan, W; Altaye, M; Leach, JL; Holland, SK. Neonatal Functional and Structural Connectivity Are Associated with Cerebral Palsy at Two Years of Age. American Journal of Perinatology: neonatal and maternal-fetal medicine. 2020; 37:137-145.

Chen, M; Li, H; Wang, J; Dillman, JR; Parikh, NA; He, L. A Multichannel Deep Neural Network Model Analyzing Multiscale Functional Brain Connectome Data for Attention Deficit Hyperactivity Disorder Detection. Radiology. Artificial intelligence.. 2020; 2:e190012.

Kline, JE; Sita Priyanka Illapani, V; He, L; Parikh, NA. Automated brain morphometric biomarkers from MRI at term predict motor development in very preterm infants. NeuroImage-Clinical. 2020; 28:102475.