Evidence map›Paper›PMID 36319922›Full record

ArticleInternational journal of computer assisted radiology and surgery2023

Automated elaborate resection planning for bone tumor surgery.

Dave Hill, Tom Williamson, Chow Yin Lai, Martin Leary, Milan Brandt, Peter Choong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Revolutionizing bone tumor management: cutting-edge breakthroughs in limb-saving treatments.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024
    Review
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

6 authors.

Dave HillCentre for Additive Manufacturing, School of Engineering, RMIT University, 58 Cardigan St, Carlton, 3001, Australia.ORCID http://orcid.org/0000-0002-8410-344X
Tom WilliamsonCentre for Additive Manufacturing, School of Engineering, RMIT University, 58 Cardigan St, Carlton, 3001, Australia. tommwilliamson@gmail.com.ORCID http://orcid.org/0000-0001-7986-1302
Chow Yin LaiDepartment of Electronic and Electrical Engineering, University College London, Malet Place and Torrington Place, Roberts Building, Level 7, London, WC1E 7JE, UK.ORCID http://orcid.org/0000-0002-9632-6624
Martin LearyCentre for Additive Manufacturing, School of Engineering, RMIT University, 58 Cardigan St, Carlton, 3001, Australia.ORCID http://orcid.org/0000-0002-2135-1681
Milan BrandtCentre for Additive Manufacturing, School of Engineering, RMIT University, 58 Cardigan St, Carlton, 3001, Australia.ORCID http://orcid.org/0000-0002-2437-3413
Peter ChoongDepartment of Surgery, University of Melbourne, Level 2, Clinical Sciences Building, 29 Regent Street, Fitzroy, 3065, Australia.ORCID http://orcid.org/0000-0002-3522-7374

Funding

IMCRC IMCRC/STR/180917
6 · The paper itself

Abstract

purposePlanning for bone tumor resection surgery is a technically demanding and time-consuming task, reliant on manual positioning of planar cuts in a virtual space. More elaborate cutting approaches may be possible through the use of surgical robots or patient-specific instruments; however, methods for preparing such a resection plan must be developed.

methodsThis work describes an automated approach for generating conformal bone tumor resection plans, where the resection geometry is defined by the convex hull of the tumor, and a focal point. The resection geometry is optimized using particle swarm, where the volume of healthy bone collaterally resected with the tumor is minimized. The approach was compared to manually prepared planar resection plans from an experienced surgeon for 20 tumor cases.

resultsIt was found that algorithm-generated hull-type resections greatly reduced the volume of collaterally resected healthy bone. The hull-type resections resulted in statistically significant improvements compared to the manual approach (paired t test, p < 0.001).

conclusionsThe described approach has potential to improve patient outcomes by reducing the volume of healthy bone collaterally resected with the tumor and preserving nearby critical anatomy.

Indexed as

Bone NeoplasmsSurgery, Computer-AssistedAlgorithmsHumansAutomated planningBone tumorsOrthopedic oncologyRobotic surgerySurgical planning

Identifiers

PMID36319922
PMCPMC9939503

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.