Evidence map›Paper›PMID 25096328›Full record

ArticleMolecular imaging and biology2015

Clinical assessment of MR-guided 3-class and 4-class attenuation correction in PET/MR.

Hossein Arabi, Olivier Rager, Asma Alem, Arthur Varoquaux, Minerva Becker, Habib Zaidi

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In one paragraph

Article in Molecular imaging and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
5.9field-weighted citation impact, top 4% 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

23 citing papers in PubMed, 62 citations in OpenAlex.

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  12. Deep-JASC: joint attenuation and scatter correction in whole-bodyEuropean journal of nuclear medicine and molecular imaging · 2020
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  20. One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI.European journal of nuclear medicine and molecular imaging · 2016
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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

6 authors at 1 institution in 2 countries.

Hossein ArabiDivision of Nuclear Medicine and Molecular Imaging, Department of Medical Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland.
Olivier Rager
Asma Alem
Arthur Varoquaux
Minerva Becker
Habib Zaidi
University Hospital of Geneva · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe compare the quantitative accuracy of magnetic resonance imaging (MRI)-based attenuation correction (AC) using the 3-class attenuation map (PET-MRAC3c) implemented on the Ingenuity TF PET/MRI and the 4-class attenuation map (PET-MRAC4c) similar to the approach used on the Siemens mMR PET/MR considering CT-based attenuation-corrected PET images (PET-CTAC) as standard of reference. PROCEDURES: Fourteen patients with malignant tumors underwent whole-body sequential 2-deoxy-2-[(18)F]fluoro-D-glucose ((18)F-FDG) positron emission tomography (PET)/X-ray computed tomography (CT) and PET/MR imaging. A 3-class attenuation map was obtained from segmentation of T1-weighted MR images followed by assignment of attenuation coefficients (air 0 cm(-1), lung 0.022 cm(-1), soft tissue 0.096 cm(-1)), whereas a 4-class attenuation map was derived from a MR Dixon sequence (air 0 cm(-1), lung 0.018 cm(-1), fat 0.086 cm(-1), soft tissue 0.096 cm(-1)). Additional adipose tissue class and inner body air cavities (e.g., sinus and abdomen) were also considered. Different attenuation coefficients were assigned to the lungs since the two techniques were implemented as they were proposed without any modification. Standardized uptake value (SUV)mean and SUVmax metrics were calculated for volumes of interest in various organs/tissues and malignant lesions. Well-established metrics were used for the analysis of SUVs estimated using both PET-MRAC techniques and PET-CTAC including relative error, Spearman rank correlation, and Bland and Altman analysis.

resultsPET-MRAC3c and PET-MRAC4c revealed significant underestimation of SUV for normal organs (-17.4 ± 8.5 and -22.0 ± 6.8%, respectively) compared to PET-CTAC. Lesions' SUV presented the same trend with larger underestimation for PET-MRAC4c (-9.2 ± 6.1%) compared to PET-MRAC3c (-3.9 ± 9.0). The different attenuation coefficients assigned to the lungs with both techniques resulted in significant positive bias on PET-MRAC3c (18.6 ± 15.3%) and low negative bias on PET-MRAC4c (-0.5 ± 13.3%). Both approaches yielded the largest differences in and near bony structures. Despite the large bias, there was good correlation between PET-MRAC3c (R = 0.97, P < 0.01) and PET-CTAC, and PET-MRAC4c (R = 0.97, P < 0.01) and PET-CTAC, respectively.

conclusionsPET-MRAC3c resulted in significant systematic positive bias in the lungs owing to the lower attenuation coefficient used and negative bias in other regions. PET-MRAC4c slightly underestimated tracer uptake in the lungs and led to even larger negative bias than PET-MRAC3c in other body regions. The presence of artifacts in the MRAC might lead to misinterpretation of clinical studies. As such, the attenuation map needs to be checked for artifacts as part of the reading procedure to avoid misinterpretation of SUV measurements.

Indexed as

Magnetic Resonance ImagingMultimodal ImagingPositron-Emission TomographyArtifactsFemaleHumansMaleMiddle AgedRegression AnalysisTomography, X-Ray Computed

Identifiers

PMID25096328
OpenAlexW2015134308

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.