Literature DB >> 34503945

A Longitudinal Analysis of Early Lesion Growth in Presymptomatic Patients with Cerebral Adrenoleukodystrophy.

E J Mallack1,2, G Askin3, S van de Stadt4, P A Caruso5, P L Musolino6, M Engelen4, S N Niogi7,7, F S Eichler6.   

Abstract

BACKGROUND AND
PURPOSE: Cerebral adrenoleukodystrophy is a devastating neurological disorder caused by mutations in the ABCD1 gene. Our aim was to model and compare the growth of early cerebral lesions from longitudinal MRIs obtained in presymptomatic patients with progressive and arrested cerebral adrenoleukodystrophy using quantitative MR imaging-based lesion volumetry.
MATERIALS AND METHODS: We retrospectively quantified and modeled the longitudinal growth of early cerebral lesions from 174 MRIs obtained from 36 presymptomatic male patients with cerebral adrenoleukodystrophy. Lesions were manually segmented using subject-specific lesion-intensity thresholding. Volumes were calculated and plotted across time. Lesion velocity and acceleration were calculated between sequentially paired and triplet MRIs, respectively. Linear mixed-effects models were used to assess differences in growth parameters between progressive and arrested phenotypes.
RESULTS: The median patient age was 7.4 years (range, 3.9-37.0 years). Early-stage cerebral disease progression was inversely correlated with age (ρ = -0.6631, P < .001), early lesions can grow while appearing radiographically stable, lesions undergo sustained acceleration in progressive cerebral adrenoleukodystrophy (β = 0.10 mL/month2 [95% CI, 0.05-0.14 mL/month2], P < .001), and growth trajectories diverge between phenotypes in the presymptomatic time period.
CONCLUSIONS: Measuring the volumetric changes in newly developing cerebral lesions across time can distinguish cerebral adrenoleukodystrophy phenotypes before symptom onset. When factored into the overall clinical presentation of a patient with a new brain lesion, quantitative MR imaging-based lesion volumetry may aid in the accurate prediction of patients eligible for therapy.
© 2021 by American Journal of Neuroradiology.

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Year:  2021        PMID: 34503945      PMCID: PMC8562733          DOI: 10.3174/ajnr.A7250

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   4.966


  27 in total

Review 1.  Adrenoleukodystrophy: phenotype, genetics, pathogenesis and therapy.

Authors:  H W Moser
Journal:  Brain       Date:  1997-08       Impact factor: 13.501

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Journal:  Nat Rev Neurol       Date:  2015-09-15       Impact factor: 42.937

Review 3.  X-Linked adrenoleukodystrophy: overview and prognosis as a function of age and brain magnetic resonance imaging abnormality. A study involving 372 patients.

Authors:  H W Moser; D J Loes; E R Melhem; G V Raymond; L Bezman; C S Cox; S E Lu
Journal:  Neuropediatrics       Date:  2000-10       Impact factor: 1.947

4.  Onset of multiple sclerosis before adulthood leads to failure of age-expected brain growth.

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Journal:  Neurology       Date:  2014-11-05       Impact factor: 9.910

5.  Clinical and radiographic course of arrested cerebral adrenoleukodystrophy.

Authors:  Eric J Mallack; Stephanie van de Stadt; Paul A Caruso; Patricia L Musolino; Reza Sadjadi; Marc Engelen; Florian S Eichler
Journal:  Neurology       Date:  2020-06-01       Impact factor: 9.910

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7.  MRI surveillance of boys with X-linked adrenoleukodystrophy identified by newborn screening: Meta-analysis and consensus guidelines.

Authors:  Eric J Mallack; Bela R Turk; Helena Yan; Carrie Price; Michelle Demetres; Ann B Moser; Catherine Becker; Kim Hollandsworth; Laura Adang; Adeline Vanderver; Keith Van Haren; Maura Ruzhnikov; Joanne Kurtzberg; Gustavo Maegawa; Paul J Orchard; Troy C Lund; Gerald V Raymond; Molly Regelmann; Joseph J Orsini; Elisa Seeger; Stephan Kemp; Florian Eichler; Ali Fatemi
Journal:  J Inherit Metab Dis       Date:  2021-01-09       Impact factor: 4.982

8.  MRI brain lesions in asymptomatic boys with X-linked adrenoleukodystrophy.

Authors:  Afonso P Liberato; Eric J Mallack; Razina Aziz-Bose; Doug Hayden; Arne Lauer; Paul A Caruso; Patricia L Musolino; Florian S Eichler
Journal:  Neurology       Date:  2019-03-22       Impact factor: 11.800

9.  Neurocognitive benchmarks following transplant for emerging cerebral adrenoleukodystrophy.

Authors:  Elizabeth I Pierpont; David R Nascene; Ryan Shanley; Daniel L Kenney-Jung; Richard S Ziegler; Weston P Miller; Ashish O Gupta; Troy C Lund; Paul J Orchard; Julie B Eisengart
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10.  Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

Authors:  Ken Chang; Andrew L Beers; Harrison X Bai; James M Brown; K Ina Ly; Xuejun Li; Joeky T Senders; Vasileios K Kavouridis; Alessandro Boaro; Chang Su; Wenya Linda Bi; Otto Rapalino; Weihua Liao; Qin Shen; Hao Zhou; Bo Xiao; Yinyan Wang; Paul J Zhang; Marco C Pinho; Patrick Y Wen; Tracy T Batchelor; Jerrold L Boxerman; Omar Arnaout; Bruce R Rosen; Elizabeth R Gerstner; Li Yang; Raymond Y Huang; Jayashree Kalpathy-Cramer
Journal:  Neuro Oncol       Date:  2019-11-04       Impact factor: 12.300

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  1 in total

1.  Presymptomatic Lesion in Childhood Cerebral Adrenoleukodystrophy: Timing and Treatment.

Authors:  Eric James Mallack; Keith P Van Haren; Anna Torrey; Stephanie van de Stadt; Marc Engelen; Gerald V Raymond; Ali Fatemi; Florian S Eichler
Journal:  Neurology       Date:  2022-05-24       Impact factor: 11.800

  1 in total

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