Evidence map›Paper›PMID 26576995›Full record

ArticleEJNMMI research2015

A method for accurate spatial registration of PET images and histopathology slices.

Tanuj Puri, Anastasia Chalkidou, Rhonda Henley-Smith, Arunabha Roy, Paul R Barber, Teresa Guerrero-Urbano, Richard Oakley, Ricard Simo, Jean-Pierre Jeannon, Mark McGurk and 3 more

Abstract read
In one paragraph

Article in EJNMMI research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Comparison ofJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023
    Trial
  2. Article
  3. Article
  4. Article
  5. The promise of multiparametric imaging in oncology: how do we move forward?European journal of nuclear medicine and molecular imaging · 2016
    Article
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

13 authors.

Tanuj PuriDivision of Imaging Sciences and Biomedical Engineering, King's College London, London, UK. tanujpuri82@gmail.com.
Anastasia ChalkidouDivision of Imaging Sciences and Biomedical Engineering, King's College London, London, UK. anastasia.chalkidou@kcl.ac.uk.
Rhonda Henley-SmithOral Pathology Department, King's College London, London, UK. Rhonda.Henley-Smith@gstt.nhs.uk.
Arunabha RoyDivision of Imaging Sciences and Biomedical Engineering, King's College London, London, UK. roy.arunabha@gmail.com.
Paul R BarberDepartment of Oncology, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK. paul.barber@oncology.ox.ac.uk.
Teresa Guerrero-UrbanoDepartment of Clinical Oncology, Guy's & St Thomas' NHS Foundation Trust, London, UK. Teresa.GuerreroUrbano@gstt.nhs.uk.
Richard OakleyDepartment of Head & Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, UK. richard.oakley@gstt.nhs.uk.
Ricard SimoDepartment of Head & Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, UK. ricard.simo@gstt.nhs.uk.
Jean-Pierre JeannonDepartment of Head & Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, UK. jean-pierre.jeannon@gstt.nhs.uk.
Mark McGurkDepartment of Head & Neck Surgery, Guy's & St Thomas' NHS Foundation Trust, London, UK. mark.mcgurk@kcl.ac.uk.
Edward W OdellOral Pathology Department, King's College London, London, UK. edward.odell@kcl.ac.uk.
Michael J O'DohertyDivision of Imaging Sciences and Biomedical Engineering, King's College London, London, UK. michael.o'doherty@kcl.ac.uk.
Paul K MarsdenDivision of Imaging Sciences and Biomedical Engineering, King's College London, London, UK. paul.marsden@kcl.ac.uk.

Funding

Cancer Research UK 16463
6 · The paper itself

Abstract

backgroundAccurate alignment between histopathology slices and positron emission tomography (PET) images is important for radiopharmaceutical validation studies. Limited data is available on the registration accuracy that can be achieved between PET and histopathology slices acquired under routine pathology conditions where slices may be non-parallel, non-contiguously cut and of standard block size. The purpose of this study was to demonstrate a method for aligning PET images and histopathology slices acquired from patients with laryngeal cancer and to assess the registration accuracy obtained under these conditions.

methodsSix subjects with laryngeal cancer underwent a (64)Cu-copper-II-diacetyl-bis(N4-methylthiosemicarbazone) ((64)Cu-ATSM) PET computed tomography (CT) scan prior to total laryngectomy. Sea urchin spines were inserted into the pathology specimen to act as fiducial markers. The specimen was fixed in formalin, as per standard histopathology operating procedures, and was then CT scanned and cut into millimetre-thick tissue slices. A subset of the tissue slices that included both tumour and fiducial markers was taken and embedded in paraffin blocks. Subsequently, microtome sectioning and haematoxylin and eosin staining were performed to produce 5-μm-thick tissue sections for microscopic digitisation. A series of rigid registration procedures was performed between the different imaging modalities (PET; in vivo CT-i.e. the CT component of the PET-CT; ex vivo CT; histology slices) with the ex vivo CT serving as the reference image. In vivo and ex vivo CTs were registered using landmark-based registration. Histopathology and ex vivo CT images were aligned using the sea urchin spines with additional anatomical landmarks where available. Registration errors were estimated using a leave-one-out strategy for in vivo to ex vivo CT and were estimated from the RMS landmark accuracy for histopathology to ex vivo CT.

resultsThe mean ± SD accuracy for registration of the in vivo to ex vivo CT images was 2.66 ± 0.66 mm, and the accuracy for registration of histopathology to ex vivo CT was 0.86 ± 0.41 mm. Estimating the PET to in vivo CT registration accuracy to equal the PET-CT alignment accuracy of 1 mm resulted in an overall average registration error between PET and histopathology slices of 3.0 ± 0.7 mm.

conclusionsWe have developed a registration method to align PET images and histopathology slices with an accuracy comparable to the spatial resolution of the PET images.

Indexed as

HistopathologyMethodologyOncologyPETRegistration

Identifiers

PMID26576995
PMCPMC4648832

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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.