Neuropathological correlation supports automated image-based differential diagnosis in parkinsonism
Creators
- 1. Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, 11030, Manhasset, NY (United States)
- 2. Larner College of Medicine, University of Vermont Medical Center, Burlington, VT (United States)
- 3. Division of Movement Disorders, Columbia University Medical Center, New York, NY (United States)
- 4. Department of Neurology, Boston University School of Medicine, Boston University, Boston, MA (United States)
- 5. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA (United States)
- 6. Division of Neuropathology, Columbia University Medical Center, New York, NY (United States)
Description
Up to 25% of patients diagnosed as idiopathic Parkinson's disease (IPD) have an atypical parkinsonian syndrome (APS). We had previously validated an automated image-based algorithm to discriminate between IPD, multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). While the algorithm was accurate with respect to the final clinical diagnosis after long-term expert follow-up, its relationship to the initial referral diagnosis and to the neuropathological gold standard is not known. Patients with an uncertain diagnosis of parkinsonism were referred for F-fluorodeoxyglucose (FDG) PET to classify patients as IPD or as APS based on the automated algorithm. Patients were followed by a movement disorder specialist and subsequently underwent neuropathological examination. The image-based classification was compared to the neuropathological diagnosis in 15 patients with parkinsonism. At the time of referral to PET, the clinical impression was only 66.7% accurate. The algorithm correctly identified 80% of the cases as IPD or APS (p = 0.02) and 87.5% of the APS cases as MSA or PSP (p = 0.03). The final clinical diagnosis was 93.3% accurate (p < 0.001), but needed several years of expert follow-up. The image-based classifications agreed well with autopsy and can help to improve diagnostic accuracy during the period of clinical uncertainty.
Availability note (English)
Available from: http://dx.doi.org/10.1007/s00259-021-05302-6Additional details
Identifiers
Publishing Information
- Journal Title
- European Journal of Nuclear Medicine and Molecular Imaging
- Journal Volume
- 48
- Journal Issue
- 11
- Journal Page Range
- p. 3522-3529
- ISSN
- 1619-7070
- CODEN
- EJNMA6
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- Germany
- INIS RN
- 53002552
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ALGORITHMS; ATROPHY; AUTOMATION; AUTOPSY; CLASSIFICATION; COMPARATIVE EVALUATIONS; CORRELATIONS; DIAGNOSIS; FLUORINE 18; FLUORODEOXYGLUCOSE; IMAGE PROCESSING; NERVOUS SYSTEM DISEASES; NETWORK ANALYSIS; POSITRON COMPUTED TOMOGRAPHY; RADIOPHARMACEUTICALS
- Descriptors DEC
- ANTIMETABOLITES; BETA DECAY RADIOISOTOPES; BETA-PLUS DECAY RADIOISOTOPES; COMPUTERIZED TOMOGRAPHY; DIAGNOSTIC TECHNIQUES; DISEASES; DRUGS; EMISSION COMPUTED TOMOGRAPHY; EVALUATION; FLUORINE ISOTOPES; HOURS LIVING RADIOISOTOPES; ISOMERIC TRANSITION ISOTOPES; ISOTOPES; LABELLED COMPOUNDS; LIGHT NUCLEI; MATERIALS; MATHEMATICAL LOGIC; NANOSECONDS LIVING RADIOISOTOPES; NUCLEI; ODD-ODD NUCLEI; PATHOLOGICAL CHANGES; PROCESSING; RADIOACTIVE MATERIALS; RADIOISOTOPES; TOMOGRAPHY
Optional Information
- Notes
- Advanced Image Analyses (Radiomics and Artificial Intelligence)