Evidence map›Paper›PMID 35377085›Full record

ArticleEJNMMI physics2022

Hybrid kernelised expectation maximisation for Bremsstrahlung SPECT reconstruction in SIRT with

Daniel Deidda, Ana M Denis-Bacelar, Andrew J Fenwick, Kelley M Ferreira, Warda Heetun, Brian F Hutton, Andrew P Robinson, James Scuffham, Kris Thielemans

Open access · goldAbstract read
In one paragraph

Article in EJNMMI physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

9 authors at 2 institutions in 1 country.

Daniel DeiddaNational Physical Laboratory, Teddington, UK. daniel.deidda@npl.co.uk.ORCID http://orcid.org/0000-0002-2766-4339
Ana M Denis-BacelarNational Physical Laboratory, Teddington, UK.
Andrew J FenwickNational Physical Laboratory, Teddington, UK.
Kelley M FerreiraNational Physical Laboratory, Teddington, UK.
Warda HeetunNational Physical Laboratory, Teddington, UK.
Brian F HuttonInstitute of Nuclear Medicine, University College London, London, UK.
Andrew P RobinsonNational Physical Laboratory, Teddington, UK.
James ScuffhamNational Physical Laboratory, Teddington, UK.
Kris ThielemansInstitute of Nuclear Medicine, University College London, London, UK.
National Physical Laboratory · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelective internal radiation therapy with Yttrium-90 microspheres is an effective therapy for liver cancer and liver metastases. Yttrium-90 is mainly a high-energy beta particle emitter. These beta particles emit Bremsstrahlung radiation during their interaction with tissue making post-therapy imaging of the radioactivity distribution feasible. Nevertheless, image quality and quantification is difficult due to the continuous energy spectrum which makes resolution modelling, attenuation and scatter estimation challenging and therefore the dosimetry quantification is inaccurate. As a consequence a reconstruction algorithm able to improve resolution could be beneficial.

methodsIn this study, the hybrid kernelised expectation maximisation (HKEM) is used to improve resolution and contrast and reduce noise, in addition a modified HKEM called frozen HKEM (FHKEM) is investigated to further reduce noise. The iterative part of the FHKEM kernel was frozen at the 72nd sub-iteration. When using ordered subsets algorithms the data is divided in smaller subsets and the smallest algorithm iterative step is called sub-iteration. A NEMA phantom with spherical inserts was used for the optimisation and validation of the algorithm, and data from 5 patients treated with Selective internal radiation therapy were used as proof of clinical relevance of the method.

resultsThe results suggest a maximum improvement of 56% for region of interest mean recovery coefficient at fixed coefficient of variation and better identification of the hot volumes in the NEMA phantom. Similar improvements were achieved with patient data, showing 47% mean value improvement over the gold standard used in hospitals.

conclusionsSuch quantitative improvements could facilitate improved dosimetry calculations with SPECT when treating patients with Selective internal radiation therapy, as well as provide a more visible position of the cancerous lesions in the liver.

Indexed as

Bremsstrahlung imagingKernel methodSPECT-CTSynergistic image reconstructionTomographic image reconstruction

Identifiers

PMID35377085
PMCPMC8980141
OpenAlexW4224310991

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.