Nutchawan Jittapiromsak1,2, Ping Hou3, Ho-Ling Liu3, Jia Sun4, John M Slopis5, T Linda Chi1. 1. Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX. 2. Department of Radiology, Faculty of Medicine, Chulalongkorn University and the King Chulalongkorn Memorial Hospital, Pathumwan, Bangkok, Thailand. 3. Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX. 4. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX. 5. Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Abstract
BACKGROUND AND PURPOSE: The natural history of optic pathway glioma (OPG) is highly variable and unpredictable. We present a pilot study of the prognostic role of conventional and dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) in the evaluation of OPG. METHODS: We retrospectively reviewed 17 patients with 20 pretreatment OPG lesions who underwent conventional and DCE MRI between January 2010 and December 2016. Conventional MRI was evaluated for enhancement pattern, cystic component, optic nerve tortuosity, optic nerve dural ectasia, and optic nerve perineural thickening. The DCE MRI data were analyzed for quantitative parameters using the two-compartment pharmacokinetic model (Ktrans , kep , and ve ) and for semiquantitative parameters based on time-signal intensity curve (AUC60 , peak, and wash-in). The results were compared with the clinically progressive or nonprogressive tumor. RESULTS: Five progressive OPGs and 15 nonprogressive OPGs were included. Conventional MRI findings of diffuse enhancement and cystic component were significantly correlated with progressive OPGs (both P = .01). Conventional MRI yielded sensitivity of 60%, specificity of 100%, and accuracy of 90%. Ktrans , kep , and ve as well as AUC60 , peak, and wash-in were significantly higher in progressive OPGs (P < .05). Using DCE MRI increased diagnostic performance up to a sensitivity of 100%, specificity of 93%, and accuracy of 95%. CONCLUSION: DCE MRI accurately distinguished progressive and nonprogressive OPGs, with high sensitivities and specificities. DCE MRI has a significant prognostic role in predicting progressive OPGs, thus making it useful for the identification of patients who need close clinical and imaging follow-up.
BACKGROUND AND PURPOSE: The natural history of optic pathway glioma (OPG) is highly variable and unpredictable. We present a pilot study of the prognostic role of conventional and dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) in the evaluation of OPG. METHODS: We retrospectively reviewed 17 patients with 20 pretreatment OPG lesions who underwent conventional and DCE MRI between January 2010 and December 2016. Conventional MRI was evaluated for enhancement pattern, cystic component, optic nerve tortuosity, optic nerve dural ectasia, and optic nerve perineural thickening. The DCE MRI data were analyzed for quantitative parameters using the two-compartment pharmacokinetic model (Ktrans , kep , and ve ) and for semiquantitative parameters based on time-signal intensity curve (AUC60 , peak, and wash-in). The results were compared with the clinically progressive or nonprogressive tumor. RESULTS: Five progressive OPGs and 15 nonprogressive OPGs were included. Conventional MRI findings of diffuse enhancement and cystic component were significantly correlated with progressive OPGs (both P = .01). Conventional MRI yielded sensitivity of 60%, specificity of 100%, and accuracy of 90%. Ktrans , kep , and ve as well as AUC60 , peak, and wash-in were significantly higher in progressive OPGs (P < .05). Using DCE MRI increased diagnostic performance up to a sensitivity of 100%, specificity of 93%, and accuracy of 95%. CONCLUSION:DCE MRI accurately distinguished progressive and nonprogressive OPGs, with high sensitivities and specificities. DCE MRI has a significant prognostic role in predicting progressive OPGs, thus making it useful for the identification of patients who need close clinical and imaging follow-up.
Authors: Ezekiel Maloney; A Luana Stanescu; Francisco A Perez; Ramesh S Iyer; Randolph K Otto; Sarah Leary; Lotte Steuten; Amanda I Phipps; Dennis W W Shaw Journal: Pediatr Radiol Date: 2018-05-22
Authors: Jared M Pisapia; Hamed Akbari; Martin Rozycki; Jayesh P Thawani; Phillip B Storm; Robert A Avery; Arastoo Vossough; Michael J Fisher; Gregory G Heuer; Christos Davatzikos Journal: Neurooncol Adv Date: 2020-08-01
Authors: Natalie R Boonzaier; Patrick W Hales; Felice D'Arco; Bronwen C Walters; Ramneek Kaur; Kshitij Mankad; Jessica Cooper; Alki Liasis; Victoria Smith; Patricia O'Hare; Darren Hargrave; Christopher A Clark Journal: Neuroimage Clin Date: 2020-09-28 Impact factor: 4.881