MRI Radiomic Texture Analysis Separates Genetic Phenotypes in Cerebral Adrenoleukodystrophy
Poster No:
699
Submission Type:
Abstract Submission
Authors:
Sumit Niogi1, Shanaj Latif1, Jie Lin1, Stephanie van de Stadt2, Marc Engelen3, Otto Rapalino4, Patricia Musolino5, Florian Eichler5, Eric Mallack6
Institutions:
1Weill Cornell Medicine, New York, NY, 2Emma Children’s Hospital, Amsterdam University Medical Centers, Amsterdam, Netherlands, 3, Emma Children’s Hospital, Amsterdam University Medical Centers, Amsterdam, Netherlands, 4Harvard Medical School Massachusetts General Hospital, Boston, MA, 5Harvard Medical School, Massachusetts General Hospital, Boston, MA, 6Kennedy Kreiger Institute Johns Hopkins University School of Medicine, Baltimore, MD
First Author:
Co-Author(s):
Stephanie van de Stadt, MD
Emma Children’s Hospital, Amsterdam University Medical Centers
Amsterdam, Netherlands
Emma Children’s Hospital, Amsterdam University Medical Centers
Amsterdam, Netherlands
Marc Engelen, MD PhD
, Emma Children’s Hospital, Amsterdam University Medical Centers
Amsterdam, Netherlands
, Emma Children’s Hospital, Amsterdam University Medical Centers
Amsterdam, Netherlands
Eric Mallack, MD
Kennedy Kreiger Institute Johns Hopkins University School of Medicine
Baltimore, MD
Kennedy Kreiger Institute Johns Hopkins University School of Medicine
Baltimore, MD
Introduction:
Cerebral Adrenoleukodystrophy (CALD) is a devastating neurodegenerative disorder that occurs most often in childhood. Hematopoietic Stem-Cell Transplantation, and now Autologous Stem-Cell Gene Therapy, are most effective when initiated prior to the onset of neurological symptoms. Early identification of CALD is a significant challenge; there is no established genotype-phenotype relationship. Patients have to undergo rigorous MRI screening, including the use of gadolinium, to detect the onset of disease, with little means by which to predict disease progression and clinical outcomes. The earliest pathologic changes in CALD are decreased overall lipid content, increase in myelin very long chain lipid fractions, and decrease in myelin water content in histologically normal appearing white matter. Conventional medical imaging and other laboratory tests are largely insensitive to these early changes. At present, the first manifestations of the progressive phenotype of disease that requires treatment is an enhancing lesion on a post-contrast MRI scan. However, the treatment window between lesion enhancement and the first onset of symptoms is very small. MRI Texture Analysis may serve as an even earlier discriminator of the progressive phenotype by detecting early structural changes insensitive to visual interpretation or other methods. We hypothesize that early pathogenesis of the CALD phenotype manifests as microstructural changes detectable by MRI texture analysis.
Methods:
Thirty-six MRI T1 and T2 datasets (24 examples of disease progression; 12 non-progressors) were preprocessed using denoising and nonuniformity correction. Subsequently, a region of interest analysis was performed. The area of T2 hyperintense disease was segmented. Additionally, regions of normal appearing white matter were selected based on area where that may reflect symptomology: centrum semiovale; parietal white matter; corpus callosum, orbital frontal white matter, forceps minor; the cerebral penduncle; the middle cerebellar peduncle; and the internal capsule. Both 2D and 3D feature extraction was performed on the ROIs above. A fixed bin number of 32 was used. Subsequently, feature selection was performed. We hypothesize that Gray-Level Co-Occurrence (GLCM) will be the best phenotypic differentiator based on prior studies.
Results:
Given prevalence of T2 hyperintense disease in the peri-atrial white matter, we focused our assessment on normal appearing parietal white matter. Multiple GLCM metrics separated the progressor and non-progressor groups significantly on two-tailed non-parametric Mann-Whitney test. These include SumAverage (p=0.0357), SumSquares (p=0.0296), JointAverage (p=0.0357), and Autocorrelation (p=0.0324).
Conclusions:
Previous studies have shown that radiomic texture analysis can detect genetic mutation in gliomas (e.g. IDH mutation). To our knowledge, this is the first example of texture analysis performed in x-linked adrenoleukodystrophy to show separation between the self-halting and progressive phenotypes in those with genetically confirmed cerebral ALD. Because the analysis was performed in normal appearing white matter, we hypothesize that the texture analysis may reflect early demyelination or provide evidence of dysmyelination in those with the progressive phenotype.
Genetics:
Neurogenetic Syndromes 1
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
Neurological
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2. Mallack, E. J. et al. Presymptomatic Lesion in Childhood Cerebral Adrenoleukodystrophy: Timing and Treatment. Neurology 99, e512 (2022).
3. Mallack, E. J. et al. MRI surveillance of boys with X-linked adrenoleukodystrophy identified by newborn screening: Meta-analysis and consensus guidelines. J Inherit Metab Dis 44, 728–739 (2021).
4. Theda, C., Moser, A. B., Powers, J. M. & Moser, H. W. Phospholipids in X-linked adrenoleukodystrophy white matter: fatty acid abnormalities before the onset of demyelination. J Neurol Sci 110, 195–204 (1992).
5. Kunimatsu A, Yasaka K, Akai H, Sugawara H, Kunimatsu N, Abe O. Texture Analysis in Brain Tumor MR Imaging. Magn Reson Med Sci. 2022 Mar 1;21(1):95-109. doi: 10.2463/mrms.rev.2020-0159. Epub 2021 Mar 10. PMID: 33692222; PMCID: PMC9199980.