Evidence map›Paper›PMID 22644714›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2012

iRENEX: a clinically informed decision support system for the interpretation of ⁹⁹mTc-MAG3 scans to detect renal obstruction.

Ernest V Garcia, Andrew Taylor, Russell Folks, Daya Manatunga, Raghuveer Halkar, Bital Savir-Baruch, Eva Dubovsky

Abstract read
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 18% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Diagnostic performance of an artificial intelligence-driven cardiac-structured reporting system for myocardial perfusion SPECT imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2020
    Article
  5. Article
  6. Radionuclides in nephrourology, Part 2: pitfalls and diagnostic applications.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2014
    Review
  7. Review
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

7 authors at 3 institutions in 1 country.

Ernest V GarciaDepartment of Radiology and Imaging Sciences, Emory University School of Medicine, 1364 Clifton Rd, NE, Atlanta, GA 30322, USA. Ernest.Garcia@emory.edu
Andrew Taylor
Russell Folks
Daya Manatunga
Raghuveer Halkar
Bital Savir-Baruch
Eva Dubovsky
Emory University · USEmory Healthcare · USUniversity of Alabama at Birmingham · US

Funding

Decision Support Systems for MAG3 RenographyR01EB008838 · NIBIB · EMORY UNIVERSITY · PI TAYLOR, ANDREW THOMPSON · 2008 to 2011
$1.6M
NIBIB NIH HHS R01 EB008838NIBIB NIH HHS R01-EB008838
6 · The paper itself

Abstract

purposeDecision support systems for imaging analysis and interpretation are rapidly being developed and will have an increasing impact on the practice of medicine. RENEX is a renal expert system to assist physicians evaluate suspected obstruction in patients undergoing mercaptoacetyltriglycine (MAG3) renography. RENEX uses quantitative parameters extracted from the dynamic renal scan data using QuantEM™II and heuristic rules in the form of a knowledge base gleaned from experts to determine if a kidney is obstructed; however, RENEX does not have access to and could not consider the clinical information available to diagnosticians interpreting these studies. We designed and implemented a methodology to incorporate clinical information into RENEX, implemented motion detection and evaluated this new comprehensive system (iRENEX) in a pilot group of 51 renal patients.

methodsTo reach a conclusion as to whether a kidney is obstructed, 56 new clinical rules were added to the previously reported 60 rules used to interpret quantitative MAG3 parameters. All the clinical rules were implemented after iRENEX reached a conclusion on obstruction based on the quantitative MAG3 parameters, and the evidence of obstruction was then modified by the new clinical rules. iRENEX consisted of a library to translate parameter values to certainty factors, a knowledge base with 116 heuristic interpretation rules, a forward chaining inference engine to determine obstruction and a justification engine. A clinical database was developed containing patient histories and imaging report data obtained from the hospital information system associated with the pertinent MAG3 studies. The system was fine-tuned and tested using a pilot group of 51 patients (21 men, mean age 58.2 ± 17.1 years, 100 kidneys) deemed by an expert panel to have 61 unobstructed and 39 obstructed kidneys.

resultsiRENEX, using only quantitative MAG3 data agreed with the expert panel in 87 % (34/39) of obstructed and 90 % (55/61) of unobstructed kidneys. iRENEX, using both quantitative and clinical data agreed with the expert panel in 95 % (37/39) of obstructed and 92 % (56/61) of unobstructed kidneys. The clinical information significantly (p < 0.001) increased iRENEX certainty in detecting obstruction over using the quantitative data alone.

conclusionOur renal expert system for detecting renal obstruction has been substantially expanded to incorporate the clinical information available to physicians as well as advanced quality control features and was shown to interpret renal studies in a pilot group at a standardized expert level. These encouraging results warrant a prospective study in a large population of patients with and without renal obstruction to establish the diagnostic performance of iRENEX.

Indexed as

Decision Support Systems, ClinicalTechnetium Tc 99m MertiatideFemaleHumansImage Interpretation, Computer-AssistedKidney DiseasesMaleMiddle AgedRadioisotope RenographyUncertaintyTechnetium Tc 99m Mertiatide

Identifiers

PMID22644714
PMCPMC3688257
OpenAlexW2040932439

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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.