Evidence map›Paper›PMID 28386717›Full record

ArticleEuropean radiology2017

Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study.

Mirabela Rusu, Prabhakar Rajiah, Robert Gilkeson, Michael Yang, Christopher Donatelli, Rajat Thawani, Frank J Jacono, Philip Linden, Anant Madabhushi

Abstract read
In one paragraph

Article in European radiology, 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
–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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Harnessing non-destructive 3D pathology.Nature biomedical engineering · 2021
    Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. 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

9 authors.

Mirabela RusuDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA. mirabela.rusu@gmail.com.ORCID http://orcid.org/0000-0002-0372-0367
Prabhakar RajiahUT Southwestern Medical Center, Dallas, TX, USA.
Robert GilkesonUniversity Hospitals, Cleveland Medical Center and Case Western Reserve University, Cleveland, OH, USA.
Michael YangUniversity Hospitals, Cleveland Medical Center and Case Western Reserve University, Cleveland, OH, USA.
Christopher DonatelliUniversity Hospitals, Cleveland Medical Center and Case Western Reserve University, Cleveland, OH, USA.
Rajat ThawaniDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Frank J JaconoUniversity Hospitals, Cleveland Medical Center and Case Western Reserve University, Cleveland, OH, USA.
Philip LindenUniversity Hospitals, Cleveland Medical Center and Case Western Reserve University, Cleveland, OH, USA.
Anant MadabhushiDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA. anant.madabhushi@case.edu.

Funding

Computerized histologic image predictor of cancer outcomeR01CA202752 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI FELDMAN, MICHAEL D, GANESAN, SHRIDAR · 2016 to 2020
$3.1M
MR Fingerprinting and Computerized Decision Support for Prostate CancerR01CA208236 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GULANI, VIKAS, PONSKY, LEE EVAN · 2017 to 2022
$3.0M
Pathology Image Informatics Platform for visualization, analysis and managementU24CA199374 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI GURCAN, METIN NAFI, MADABHUSHI, ANANT · 2015 to 2019
$2.9M
Comprehensive quantitative ultrafast 3D liver MRIR01DK098503 · NIDDK · CASE WESTERN RESERVE UNIVERSITY · PI GULANI, VIKAS, SEIBERLICH, NICOLE · 2013 to 2017
$2.6M
Decision support with MRI for targeting, evaluating laser ablation for prostate cR21CA167811 · NCI · RUTGERS, THE STATE UNIV OF N.J. · PI MADABHUSHI, ANANT · 2012 to 2013
$516k
Histologic image-based aggressiveness prediction in p16+ oropharyngeal carcinomaR21CA179327 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI MADABHUSHI, ANANT · 2014 to 2015
$389k
Computerized morphologic-molecular predictor of progression in DCISR21CA195152 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI BADVE, SUNIL S., MADABHUSHI, ANANT · 2015 to 2016
$388k
Decision Support System for Predicting outcome of ER+ breast cancersR43EB015199 · NIBIB · IBRIS, INC. · PI GANESAN, SHRIDAR, HARDING, DAVE · 2011 to 2011
$207k
Foundation for the National Institutes of Health (US) R21CA167811-01Foundation for the National Institutes of Health (US) R21CA179327-01Foundation for the National Institutes of Health (US) R21CA19515201Foundation for the National Institutes of Health (US) U24CA199374-01National Institute of Diabetes and Digestive and Kidney Diseases (US) R01DK098503-02NCI NIH HHS R01 CA202752NCI NIH HHS R01 CA208236NCI NIH HHS R21 CA167811NCI NIH HHS R21 CA179327NCI NIH HHS R21 CA195152NCI NIH HHS U24 CA199374NIBIB NIH HHS R43 EB015199NIDDK NIH HHS R01 DK098503U.S. Department of Defense (US) PC120857U.S. Department of Defense (US) W81XWH-13-1-0487
6 · The paper itself

Abstract

objectiveTo develop an approach for radiology-pathology fusion of ex vivo histology of surgically excised pulmonary nodules with pre-operative CT, to radiologically map spatial extent of the invasive adenocarcinomatous component of the nodule.

methodsSix subjects (age: 75 ± 11 years) with pre-operative CT and surgically excised ground-glass nodules (size: 22.5 ± 5.1 mm) with a significant invasive adenocarcinomatous component (>5 mm) were included. The pathologist outlined disease extent on digitized histology specimens; two radiologists and a pulmonary critical care physician delineated the entire nodule on CT (in-plane resolution: <0.8 mm, inter-slice distance: 1-5 mm). We introduced a novel reconstruction approach to localize histology slices in 3D relative to each other while using CT scan as spatial constraint. This enabled the spatial mapping of the extent of tumour invasion from histology onto CT.

resultsGood overlap of the 3D reconstructed histology and the nodule outlined on CT was observed (65.9 ± 5.2%). Reduction in 3D misalignment of corresponding anatomical landmarks on histology and CT was observed (1.97 ± 0.42 mm). Moreover, the CT attenuation (HU) distributions were different when comparing invasive and in situ regions.

conclusionThis proof-of-concept study suggests that our fusion method can enable the spatial mapping of the invasive adenocarcinomatous component from 2D histology slices onto in vivo CT. KEY POINTS: • 3D reconstructions are generated from 2D histology specimens of ground glass nodules. • The reconstruction methodology used pre-operative in vivo CT as 3D spatial constraint. • The methodology maps adenocarcinoma extent from digitized histology onto in vivo CT. • The methodology potentially facilitates the discovery of CT signature of invasive adenocarcinoma.

Indexed as

AdenocarcinomaAdultAgedAged, 80 and overFemaleHumansLung NeoplasmsMaleMiddle AgedMultiple Pulmonary NodulesNeoplasm InvasivenessProof of Concept StudyTomography, X-Ray ComputedComputed tomographyComputer-assisted image processingLung adenocarcinomaMultimodal imagingPathology

Identifiers

PMID28386717
PMCPMC5630490

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Registered trials

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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.