Evidence map›Paper›PMID 28064435›Full record

ArticleMedical physics2017

3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging.

Thomy Mertzanidou, John H Hipwell, Sara Reis, David J Hawkes, Babak Ehteshami Bejnordi, Mehmet Dalmis, Suzan Vreemann, Bram Platel, Jeroen van der Laak, Nico Karssemeijer and 3 more

Open access · hybridAbstract readValidation Study
In one paragraph

Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 22 citations in OpenAlex.

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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

13 authors at 3 institutions in 2 countries.

Thomy MertzanidouCentre for Medical Image Computing, University College London, WC1E 6BT, London, UK.
John H HipwellCentre for Medical Image Computing, University College London, WC1E 6BT, London, UK.
Sara ReisCentre for Medical Image Computing, University College London, WC1E 6BT, London, UK.
David J HawkesCentre for Medical Image Computing, University College London, WC1E 6BT, London, UK.
Babak Ehteshami BejnordiDiagnostic Image Analysis Group, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Mehmet DalmisDiagnostic Image Analysis Group, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Suzan VreemannDiagnostic Image Analysis Group, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Bram PlatelDiagnostic Image Analysis Group, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Jeroen van der LaakDiagnostic Image Analysis Group, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Nico KarssemeijerDiagnostic Image Analysis Group, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Meyke HermsenDepartment of Pathology, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Peter BultDepartment of Pathology, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Ritse MannDepartment of Radiology, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands.
Radboud University Medical Center · NLUniversity College London · GBRadboud University Nijmegen · NL

Funding

Cancer Research UK 16463
6 · The paper itself

Abstract

purposeIn breast imaging, radiological in vivo images, such as x-ray mammography and magnetic resonance imaging (MRI), are used for tumor detection, diagnosis, and size determination. After excision, the specimen is typically sliced into slabs and a small subset is sampled. Histopathological imaging of the stained samples is used as the gold standard for characterization of the tumor microenvironment. A 3D volume reconstruction of the whole specimen from the 2D slabs could facilitate bridging the gap between histology and in vivo radiological imaging. This task is challenging, however, due to the large deformation that the breast tissue undergoes after surgery and the significant undersampling of the specimen obtained in histology. In this work, we present a method to reconstruct a coherent 3D volume from 2D digital radiographs of the specimen slabs.

methodsTo reconstruct a 3D breast specimen volume, we propose the use of multiple target neighboring slices, when deforming each 2D slab radiograph in the volume, rather than performing pairwise registrations. The algorithm combines neighborhood slice information with free-form deformations, which enables a flexible, nonlinear deformation to be computed subject to the constraint that a coherent 3D volume is obtained. The neighborhood information provides adequate constraints, without the need for any additional regularization terms.

resultsThe volume reconstruction algorithm is validated on clinical mastectomy samples using a quantitative assessment of the volume reconstruction smoothness and a comparison with a whole specimen 3D image acquired for validation before slicing. Additionally, a target registration error of 5 mm (comparable to the specimen slab thickness of 4 mm) was obtained for five cases. The error was computed using manual annotations from four observers as gold standard, with interobserver variability of 3.4 mm. Finally, we illustrate how the reconstructed volumes can be used to map histology images to a 3D specimen image of the whole sample (either MRI or CT).

conclusionsQualitative and quantitative assessment has illustrated the benefit of using our proposed methodology to reconstruct a coherent specimen volume from serial slab radiographs. To our knowledge, this is the first method that has been applied to clinical breast cases, with the goal of reconstructing a whole specimen sample. The algorithm can be used as part of the pipeline of mapping histology images to ex vivo and ultimately in vivo radiological images of the breast.

Indexed as

AlgorithmsArtifactsBreastHistological TechniquesHumansImaging, Three-DimensionalMagnetic Resonance ImagingMammographyNonlinear DynamicsObserver VariationTomography, X-Ray Computed3D volume reconstructionbreast histology-radiology registrationserial breast specimen images

Identifiers

PMID28064435
PMCPMC6849622
OpenAlexW2569021041

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.