Evidence map›Paper›PMID 36156185›Full record

ArticleCerebellum (London, England)2023

Toward More Accessible Fully Automated 3D Volumetric MRI Decision Trees for the Differential Diagnosis of Multiple System Atrophy, Related Disorders, and Age-Matched Healthy Subjects.

Jisoo Kim, Geoffrey S Young, Ashlan S Willett, Ariana T Pitaro, Grace F Crotty, Merlyne Mesidor, Kristie A Jones, Camden Bay, Min Zhang, Mel B Feany and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cerebellum (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jisoo KimDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Geoffrey S YoungDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Ashlan S WillettDivision of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Ariana T PitaroDivision of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Grace F CrottyDivision of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Merlyne MesidorDivision of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Kristie A JonesDivision of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Camden BayDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Min ZhangDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Mel B FeanyDepartment of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Xiaoyin XuDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Lei QinDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Vikram KhuranaDivision of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA. vkhurana@bwh.harvard.edu.ORCID http://orcid.org/0000-0002-4018-5527

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI JOHN MORRIS · 1985 to 2026
$69.5M
The natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 2005 to 2025
$49.5M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
THE XNAT IMAGING INFORMATICS PLATFORMR01EB009352 · NIBIB · WASHINGTON UNIVERSITY · PI Daniel Scott Marcus · 2009 to 2026
$9.3M
DRIVING PERFORMANCE IN PRECLINICAL ALZHEIMER'S DISEASER01AG043434 · NIA · WASHINGTON UNIVERSITY · PI ROE, CATHERINE M · 2012 to 2016
$2.4M
NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1 TR002345NIA NIH HHS P01 AG003991NIA NIH HHS P01 AG026276NIA NIH HHS R01 AG043434NIBIB NIH HHS R01 EB009352
6 · The paper itself

Abstract

Differentiating multiple system atrophy (MSA) from related neurodegenerative movement disorders (NMD) is challenging. MRI is widely available and automated decision-tree analysis is simple, transparent, and resistant to overfitting. Using a retrospective cohort of heterogeneous clinical MRIs broadly sourced from a tertiary hospital system, we aimed to develop readily translatable and fully automated volumetric diagnostic decision-trees to facilitate early and accurate differential diagnosis of NMDs. 3DT1 MRI from 171 NMD patients (72 MSA, 49 PSP, 50 PD) and 171 matched healthy subjects were automatically segmented using Freesurfer6.0 with brainstem module. Decision trees employing substructure volumes and a novel volumetric pons-to-midbrain ratio (3D-PMR) were produced and tenfold cross-validation performed. The optimal tree separating NMD from healthy subjects selected cerebellar white matter, thalamus, putamen, striatum, and midbrain volumes as nodes. Its sensitivity was 84%, specificity 94%, accuracy 84%, and kappa 0.69 in cross-validation. The optimal tree restricted to NMD patients selected 3D-PMR, thalamus, superior cerebellar peduncle (SCP), midbrain, pons, and putamen as nodes. It yielded sensitivities/specificities of 94/84% for MSA, 72/96% for PSP, and 73/92% PD, with 79% accuracy and 0.62 kappa. There was correct classification of 16/17 MSA, 5/8 PSP, 6/8 PD autopsy-confirmed patients, and 6/8 MRIs that preceded motor symptom onset. Fully automated decision trees utilizing volumetric MRI data distinguished NMD patients from healthy subjects and MSA from other NMDs with promising accuracy, including autopsy-confirmed and pre-symptomatic subsets. Our open-source methodology is well-suited for widespread clinical translation. Assessment in even more heterogeneous retrospective and prospective cohorts is indicated.

Indexed as

Multiple System AtrophyParkinson DiseaseSupranuclear Palsy, ProgressiveDecision TreesDiagnosis, DifferentialHealthy VolunteersHumansMagnetic Resonance ImagingProspective StudiesRetrospective StudiesAtypical parkinsonismMSAPDPSPVolumetric analysis

Identifiers

PMID36156185
PMCPMC10657274

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.