Evidence map›Paper›PMID 41475406›Full record

ArticleComputer assisted surgery (Abingdon, England)2026

No cancer left behind: a testbed and demonstration of concept for photoacoustic tumor bed inspection.

Laura Connolly, Hyunwoo Song, Keshuai Xu, Anton Deguet, Simon Leonard, Gabor Fichtinger, Parvin Mousavi, Russell H Taylor, Emad Boctor

Abstract read
In one paragraph

Article in Computer assisted surgery (Abingdon, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Laura ConnollyDepartment of Electrical and Computer Engineering, Queen's University, Kingston, Canada.ORCID 0009-0005-8675-160X
Hyunwoo SongLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.ORCID 0000-0002-1166-8079
Keshuai XuLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Anton DeguetLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.ORCID 0000-0003-3856-2095
Simon LeonardLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.ORCID 0000-0001-6429-4755
Gabor FichtingerSchool of Computing, Queen's University, Kingston, Canada.ORCID 0000-0002-6354-262X
Parvin MousaviSchool of Computing, Queen's University, Kingston, Canada.
Russell H TaylorLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.ORCID 0000-0001-6272-1100
Emad BoctorLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.ORCID 0000-0002-9536-6720

Funding

Open Software Platform for Data-Driven Image-Guided Robotic InterventionsR01EB020667 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI DIAZ-MERCADO, YANCY, KRIEGER, AXEL · 2015 to 2024
$4.1M
NIBIB NIH HHS R01 EB020667
6 · The paper itself

Abstract

Cancer resection surgery is unsuccessful if tumor tissue is left behind in the surgical cavity. Identifying the residual cancer requires additional imaging or postoperative histological analysis. Photoacoustic imaging can be used to image both the surface and depths of the resection cavity; however, its performance hinges on consistent probe placement and stable acoustic and optical coupling. As intra-cavity deployment of photoacoustic imaging is largely uncharted, several potential embodiments warrant rigorous investigation. We address this need with an open-source robotic testbed for intraoperative tumor-bed inspection using photoacoustic imaging. The platform integrates the da Vinci Research Kit, depth imaging, and electromagnetic tracking to automate cavity scanning and maintain repeatable probe trajectories. Using tissue-mimicking phantoms, we (i) demonstrate a novel imaging embodiment for photoacoustic tumor-bed inspection and (ii) show how this testbed can be used to investigate and optimize tumor bed inspection strategies and configurations. This study establishes the feasibility of detecting and mapping residual cancer within a simulated surgical cavity. The primary contribution is the testbed itself, designed for integration with existing surgical navigation workflows and rapid prototyping. This testbed serves as an essential foundation for systematic evaluation of photoacoustic, robot-assisted strategies for improving intraoperative margin assessment.

Indexed as

Neoplasm, ResidualNeoplasmsPhotoacoustic TechniquesRobotic Surgical ProceduresSurgery, Computer-AssistedFeasibility StudiesHumansPhantoms, Imagingbreast-conserving surgerymargin detectionPhotoacousticsrobotics

Identifiers

PMID41475406
PMCPMC12925404

What OpenQuestion holds

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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.