Evidence map›Paper›PMID 35774413›Full record

ArticleIEEE journal of translational engineering in health and medicine2022

Stiffness Assessment and Lump Detection in Minimally Invasive Surgery Using In-House Developed Smart Laparoscopic Forceps.

Wael Othman, Kojo E Vandyck, Carlos Abril, Juan S Barajas-Gamboa, Juan P Pantoja, Matthew Kroh, Mohammad A Qasaimeh

Open access · goldAbstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. A Minimally Invasive Robotic Tissue Palpation Device.IEEE transactions on bio-medical engineering · 2024
    Article
  7. Article
  8. 'Now you can see me, now you don't': seeking the invisible lung nodule.Interdisciplinary cardiovascular and thoracic surgery · 2023
    Article
  9. Next-Generation Microfluidics for Biomedical Research and Healthcare Applications.Biomedical engineering and computational biology · 2023
    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

7 authors at 2 institutions in 2 countries.

Wael OthmanEngineering DivisionNew York University Abu Dhabi Abu Dhabi United Arab Emirates.ORCID 0000-0003-0429-6171
Kojo E VandyckEngineering DivisionNew York University Abu Dhabi Abu Dhabi United Arab Emirates.ORCID 0000-0002-9811-4959
Carlos AbrilCleveland Clinic Abu DhabiDepartment of General SurgeryDigestive Disease Institute Abu Dhabi United Arab Emirates.ORCID 0000-0002-0943-509X
Juan S Barajas-GamboaCleveland Clinic Abu DhabiDepartment of General SurgeryDigestive Disease Institute Abu Dhabi United Arab Emirates.
Juan P PantojaCleveland Clinic Abu DhabiDepartment of General SurgeryDigestive Disease Institute Abu Dhabi United Arab Emirates.
Matthew KrohCleveland Clinic OhioDepartment of General SurgeryDigestive Disease and Surgery Institute Cleveland OH 44195 USA.
Mohammad A QasaimehEngineering DivisionNew York University Abu Dhabi Abu Dhabi United Arab Emirates.ORCID 0000-0003-1122-9698
New York University Abu Dhabi · AECleveland Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Minimally invasive surgery (MIS) incorporates surgical instruments through small incisions to perform procedures. Despite the potential advantages of MIS, the lack of tactile sensation and haptic feedback due to the indirect contact between the surgeon's hands and the tissues restricts sensing the strength of applied forces or obtaining information about the biomechanical properties of tissues under operation. Accordingly, there is a crucial need for intelligent systems to provide an artificial tactile sensation to MIS surgeons and trainees. This study evaluates the potential of our proposed real-time grasping forces and deformation angles feedback to assist surgeons in detecting tissues' stiffness. A prototype was developed using a standard laparoscopic grasper integrated with a force-sensitive resistor on one grasping jaw and a tunneling magneto-resistor on the handle's joint to measure the grasping force and the jaws' opening angle, respectively. The sensors' data are analyzed using a microcontroller, and the output is displayed on a small screen and saved to a log file. This integrated system was evaluated by running multiple grasp-release tests using both elastomeric and biological tissue samples, in which the average force-to-angle-change ratio precisely resembled the stiffness of grasped samples. Another feature is the detection of hidden lumps by palpation, looking for sudden variations in the measured stiffness. In experiments, the real-time grasping feedback helped enhance the surgeons' sorting accuracy of testing models based on their stiffness. The developed tool demonstrated a great potential for low-cost tactile sensing in MIS procedures, with room for future improvements. Significance: The proposed method can contribute to MIS by assessing stiffness, detecting hidden lumps, preventing excessive forces during operation, and reducing the learning curve for trainees.

Indexed as

Equipment DesignLaparoscopyMinimally Invasive Surgical ProceduresSurgical InstrumentsTouchangle sensorforce sensorlaparoscopylump detectionMinimally invasive surgeryrobotic surgerystiffness assessmenttactile sensing

Identifiers

PMID35774413
PMCPMC9216325
OpenAlexW4285021911

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.