title: Development and prospective evaluation of an automated software system for quality control of quantitative 99mTc-MAG3 renal studies.
abstract: Quantitative nuclear renography has numerous potential sources of error. We previously reported the initial development of a computer software module for comprehensively addressing the issue of quality control (QC) in the analysis of radionuclide renal images. The objective of this study was to prospectively test the QC software.
  
  
  METHODS
  The QC software works in conjunction with standard quantitative renal image analysis using a renal quantification program. The software saves a text file that summarizes QC findings as possible errors in user-entered values, calculated values that may be unreliable because of the patient's clinical condition, and problems relating to acquisition or processing. To test the QC software, a technologist not involved in software development processed 83 consecutive nontransplant clinical studies. The QC findings of the software were then tabulated. QC events were defined as technical (study descriptors that were out of range or were entered and then changed, unusually sized or positioned regions of interest, or missing frames in the dynamic image set) or clinical (calculated functional values judged to be erroneous or unreliable).
  
  
  RESULTS
  Technical QC events were identified in 36 (43%) of 83 studies. Clinical QC events were identified in 37 (45%) of 83 studies. Specific QC events included starting the camera after the bolus had reached the kidney, dose infiltration, oversubtraction of background activity, and missing frames in the dynamic image set.
  
  
  CONCLUSIONS
  QC software has been developed to automatically verify user input, monitor calculation of renal functional parameters, summarize QC findings, and flag potentially unreliable values for the nuclear medicine physician. Incorporation of automated QC features into commercial or local renal software can reduce errors and improve technologist performance and should improve the efficiency and accuracy of image interpretation.
authors.affiliation: Emory University School of Medicine, Atlanta, Georgia 30322, USA. rfolks@emory.edu
authors.forename: Russell D
authors.initials: RD
authors.lastname: Folks
authors.forename: Ernest V
authors.initials: EV
authors.lastname: Garcia
authors.forename: Andrew T
authors.initials: AT
authors.lastname: Taylor
mesh_terms: D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007674:Kidney Diseases / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011785:Quality Assurance, Health Care / Q000379:methods*; D011786:Quality Control; D011866:Radioisotope Renography / Q000379:methods*; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D012985:Software Design; D012986:Software Validation; D017263:Technetium Tc 99m Mertiatide
chemical_list: D019275:Radiopharmaceuticals; D017263:Technetium Tc 99m Mertiatide