Evidence map›Paper›PMID 38753135›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

An endoscopic chisel: intraoperative imaging carves 3D anatomical models.

Jan Emily Mangulabnan, Roger D Soberanis-Mukul, Timo Teufel, Manish Sahu, Jose L Porras, S Swaroop Vedula, Masaru Ishii, Gregory Hager, Russell H Taylor, Mathias Unberath

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Global region reidentification for camera relocalization in video-based surgical navigation.International journal of computer assisted radiology and surgery · 2026
    Article
  3. 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

10 authors.

Jan Emily MangulabnanJohns Hopkins University, Baltimore, MD, 21211, USA. jmangul1@jh.edu.ORCID http://orcid.org/0009-0005-5941-0535
Roger D Soberanis-MukulJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0000-0003-0712-0534
Timo TeufelJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0009-0008-3263-6894
Manish SahuJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0000-0003-2158-823X
Jose L PorrasJohns Hopkins Medical Institutions, Baltimore, MD, 21287, USA.
S Swaroop VedulaJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0000-0002-6992-2957
Masaru IshiiJohns Hopkins Medical Institutions, Baltimore, MD, 21287, USA.
Gregory HagerJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0000-0002-6662-9763
Russell H TaylorJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0000-0001-6272-1100
Mathias UnberathJohns Hopkins University, Baltimore, MD, 21211, USA.ORCID http://orcid.org/0000-0002-0055-9950

Funding

Improved Surgical Navigation Using Video-CT RegistrationR01EB030511 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI HAGER, GREGORY DONALD, ISHII, MASARU · 2021 to 2024
$2.4M
NIBIB NIH HHS R01 EB030511NIH HHS R01EB03051
6 · The paper itself

Abstract

purposePreoperative imaging plays a pivotal role in sinus surgery where CTs offer patient-specific insights of complex anatomy, enabling real-time intraoperative navigation to complement endoscopy imaging. However, surgery elicits anatomical changes not represented in the preoperative model, generating an inaccurate basis for navigation during surgery progression.

methodsWe propose a first vision-based approach to update the preoperative 3D anatomical model leveraging intraoperative endoscopic video for navigated sinus surgery where relative camera poses are known. We rely on comparisons of intraoperative monocular depth estimates and preoperative depth renders to identify modified regions. The new depths are integrated in these regions through volumetric fusion in a truncated signed distance function representation to generate an intraoperative 3D model that reflects tissue manipulation

resultsWe quantitatively evaluate our approach by sequentially updating models for a five-step surgical progression in an ex vivo specimen. We compute the error between correspondences from the updated model and ground-truth intraoperative CT in the region of anatomical modification. The resulting models show a decrease in error during surgical progression as opposed to increasing when no update is employed.

conclusionOur findings suggest that preoperative 3D anatomical models can be updated using intraoperative endoscopy video in navigated sinus surgery. Future work will investigate improvements to monocular depth estimation as well as removing the need for external navigation systems. The resulting ability to continuously update the patient model may provide surgeons with a more precise understanding of the current anatomical state and paves the way toward a digital twin paradigm for sinus surgery.

Indexed as

EndoscopyImaging, Three-DimensionalModels, AnatomicSurgery, Computer-AssistedTomography, X-Ray ComputedHumansParanasal SinusesAnatomy model updateDepth estimationSinusTruncated signed distance function

Identifiers

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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.