Automated assessment of FDG-PET for differential diagnosis in patients with neurodegenerative disorders

Flavio Nobili, Cristina Festari, Daniele Altomare, Federica Agosta, Stefania Orini, Koen Van Laere, Javier Arbizu, Femke Bouwman, Alexander Drzezga, Peter Nestor, Zuzana Walker, Marina Boccardi
<span title="2018-05-02">2018</span> <i title="Springer Nature America, Inc"> <a target="_blank" rel="noopener" href="" style="color: black;">European Journal of Nuclear Medicine and Molecular Imaging</a> </i> &nbsp;
Purpose: To review literature until November 2015 and reach a consensus on whether automatic semi-quantification of brain FDG-PET is useful in the clinical setting for neurodegenerative disorders. Methods: Literature search was conducted in Medline, Embase, and Google scholar. Papers were selected with a lower limit of 30 patients (no limits with autopsy confirmation). Consensus recommendations were developed through a Delphi procedure, based on the expertise of panelists, who were also
more &raquo; ... about the availability and quality of evidence, assessed by an independent methodology team. Results: Critical outcomes were available in nine among the 17 papers initially selected. Only three papers performed the direct comparison between visual and automated assessment and quantified the incremental value provided by the latter. Sensitivity between visual and automatic analysis is similar but automatic assessment generally improves specificity, and marginally accuracy. Also, automated assessment increases diagnostic confidence. As expected, performance of visual analysis is reported to depend on expertise of readers. Conclusions: Tools for semi-quantitative evaluation are recommended to assist the nuclear medicine physician in reporting brain FDG-PET pattern in neurodegenerative conditions. However, heterogeneity, complexity and drawbacks of these tools should be known by users to avoid misinterpretation. Head-to-head comparisons and an effort to harmonize procedures are encouraged. Keywords: brain FDG-PET, visual reading, semi-quantitative assessment, computer-aided, dementia, neurodegenerative diseases. consistent with the EFNS guidance [14] though specifically adapted to FDG-PET studies [13]. PICO question for this paper. For this review, the PICO question was whether automated semiquantitative assessment of FDG-PET scans should be required, as adding sufficient information (in terms of increased accuracy, and versus pathology, biomarker-based diagnosis or conversion at follow-up) as compared to visual reading alone, to optimize the diagnostic work-up of patients with dementing neurodegenerative disorders. Eligibility criteria. Only original full papers published in English on international impacted journals were considered, excluding reviews, management guidelines, abstracts and gray literature. Any sample size was allowed if pathology was the gold standard for diagnosis. Otherwise, 30 subjects, demented patients and/or healthy controls, were requested as the minimum sample sizes. Literature search. Electronic search strategy, developed and tested with panelists, was performed using predefined strings, grounding on the specific PICO question and including a selection of terms taken from a largely inclusive literature selection, in order to pick all variants for the same keyword. Other details of the literature search are reported in the methodological paper [13]. Data extraction and quality assessment. CF extracted data for this review. The quality of evidence was assessed consensually within the methodology team based on study design, gold/reference standard, FDG-PET image assessment (visual or semi-quantitative methods), risk of bias, index test imprecision, applicability, effect size, and effect inconsistency [13]. A final assessment of relative availability of evidence was formulated, keeping into account evidence availability among all of the 21 PICOs. This ranking was summarized as very poor/lacking, poor, fair or good. RESULTS Among the 17 papers identified and screened by the referent panelist (FN), 14 were sent to the methodology team for data extraction and assessment (Figure 1 ). Two papers [15, 16] failed to show semiquantitative results and were not considered. Among the remaining 12, critical outcomes Mester J, et al. Evaluation of a new expert system for fully automated detection of the Alzheimer's dementia pattern in FDG PET. J Nucl Med. 2006;27:739-43. 17. Lehman VT, Carter RE, Claassen DO, Murphy RC, Lowe V, Petersen RC, et al. Visual assessment versus quantitative three-dimensional stereotactic surface projection fluorodeoxyglucose positron emission tomography for detection of mild cognitive impairment and Alzheimer disease. Clin Nucl Med. 2012;37:721-6. 18. Burdette JH, Minoshima S, Vander Borght T, Tran DD, Kuhl DE. Alzheimer disease: improved visual interpretation of PET images by using three-dimensional stereotaxic surface projections.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1007/s00259-018-4030-3</a> <a target="_blank" rel="external noopener" href="">pmid:29721650</a> <a target="_blank" rel="external noopener" href="">fatcat:lnp3elb365fclprnhnpv5y22ym</a> </span>
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