An account of data entry inconsistencies and their impact on positron emission tomography quantification. Issue 37 (September 2018)

• Record Type: Journal Article
• Authors: Nguyen, Tram; Baun, Christina; Høilund-Carlsen, Poul Flemming
• Other Names: Zhang. Heye section editor.
• Is Part Of: Medicine. Volume 97:Issue 37(2018)
• Publication Date: 2018-09
• Subjects: compliance -- error sources -- positron emission tomography -- protocol -- quantitative evaluation -- reproducibility of results; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000012312
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Reproducibility is essential to clinical application of positron emission tomography (PET) quantification. Human lapses in data registration and protocol compliance are pervasive sources of intrasite quantification variability. Although rarely assessed or reported, these lapses are ultimately a limitation to harmonization in multicenter clinical trials. A comprehensive account of their possible extent is relayed here. This is a retrospective audit of errors in manual registration of study parameters and in protocol adherence across a sample of in-center research projects over one year (201 patients, 222 PET/CT scans). Discrepancies in patient height and weight; tracer type; dose; injection; and scan times were listed. Correspondent variances in standardized uptake values (SUVs) normalized by body weight, SUV (BW), and body surface area, SUV (BSA), were assessed. Manual misregistrations totalled 41.8%. These were mainly small, but with a few large deviations, and most significant in weight (range: -1–100 kg) and dose (-19 to 12 MBq). Errors were more frequent and generally larger in non-routine studies. This also applied to protocol compliance. A 50.7% noncompliance was found with significant deviations in dose (-106 to 208 MBq) and especially in early scan uptake times (-37 to 54 min). Although misregistrations did not overall translate into significant SUV variability, noncompliance did. These errors contributed a factor 0.02 to 1.45 and 0.71 to 3.09 SUV (BW) change, respectively. SUV (BSA) saw a significant 21% to 22% decrease with mistyped height and weight. Inconsistency was frequent but less prominent in data entry than in protocol compliance. As both caused some substantial SUV variances, intra-site assessments and data checking are required for clinical trials.