Evidence map›Paper›PMID 22471689›Full record

ArticleBMC medical imaging2012

Semi-automatic analysis of standard uptake values in serial PET/CT studies in patients with lung cancer and lymphoma.

John Ly, Sabine Garpered, Peter Höglund, Eskil Jönsson, Sven Valind, Lars Edenbrandt, Per Wollmer

Open access · goldAbstract read
In one paragraph

Article in BMC medical imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

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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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 institutions in 1 country.

John LyDepartment of Clinical Sciences, Skåne University, Malmö, Sweden.
Sabine Garpered
Peter Höglund
Eskil Jönsson
Sven Valind
Lars Edenbrandt
Per Wollmer
Skåne University Hospital · SELund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChanges in maximum standardised uptake values (SUVmax) between serial PET/CT studies are used to determine disease progression or regression in oncologic patients. To measure these changes manually can be time consuming in a clinical routine. A semi-automatic method for calculation of SUVmax in serial PET/CT studies was developed and compared to a conventional manual method. The semi-automatic method first aligns the serial PET/CT studies based on the CT images. Thereafter, the reader selects an abnormal lesion in one of the PET studies. After this manual step, the program automatically detects the corresponding lesion in the other PET study, segments the two lesions and calculates the SUVmax in both studies as well as the difference between the SUVmax values. The results of the semi-automatic analysis were compared to that of a manual SUVmax analysis using a Philips PET/CT workstation. Three readers did the SUVmax readings in both methods. Sixteen patients with lung cancer or lymphoma who had undergone two PET/CT studies were included. There were a total of 26 lesions.

resultsLinear regression analysis of changes in SUVmax show that intercepts and slopes are close to the line of identity for all readers (reader 1: intercept = 1.02, R2 = 0.96; reader 2: intercept = 0.97, R2 = 0.98; reader 3: intercept = 0.99, R2 = 0.98). Manual and semi-automatic method agreed in all cases whether SUVmax had increased or decreased between the serial studies. The average time to measure SUVmax changes in two serial PET/CT examinations was four to five times longer for the manual method compared to the semi-automatic method for all readers (reader 1: 53.7 vs. 10.5 s; reader 2: 27.3 vs. 6.9 s; reader 3: 47.5 vs. 9.5 s; p < 0.001 for all).

conclusionsGood agreement was shown in assessment of SUVmax changes between manual and semi-automatic method. The semi-automatic analysis was four to five times faster to perform than the manual analysis. These findings show the feasibility of using semi-automatic methods for calculation of SUVmax in clinical routine and encourage further development of programs using this type of methods.

Indexed as

AlgorithmsFemaleFluorodeoxyglucose F18HumansImage EnhancementImage Interpretation, Computer-AssistedLung NeoplasmsLymphomaMaleMetabolic Clearance RateMiddle AgedPattern Recognition, AutomatedPositron-Emission TomographyRadiopharmaceuticalsReproducibility of ResultsSensitivity and SpecificityFluorodeoxyglucose F18Radiopharmaceuticals

Identifiers

PMID22471689
PMCPMC3350379
OpenAlexW2171490156

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.