Evidence map›Paper›PMID 38839807›Full record

ArticleScientific reports2024

Electrical lymph node scanning (ELS) system for real-time intra-operative detection of involved axillary lymph nodes in adjuvant breast cancer patients.

Fereshteh Abbasvandi, Reihane Mahdavi, Mahdis Bayat, Farzane Hajighasemi, Fahimeh Jahanbakhshi, Faeze Aghaei, Nafiseh Sami, Batoul Khoundabi, Hossein Ataee, Narges Yousefpour and 9 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
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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

19 authors.

Fereshteh Abbasvandi *ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, P.O. Box 1517964311, Tehran, Iran.
Reihane Mahdavi *Nano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Mahdis BayatNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Farzane HajighasemiNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Fahimeh JahanbakhshiNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Faeze AghaeiNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Nafiseh SamiNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Batoul KhoundabiIran-Helal Institute of Applied Science and Technology, Red Crescent Society of Iran, Tehran, Iran.
Hossein AtaeeNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Narges YousefpourNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Parisa HoseinpourATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, P.O. Box 1517964311, Tehran, Iran.
Seyed Mohamad Sadegh Mousavi KiasaryNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Maryam Omrani HashemiCancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Fatemeh ShojaeianNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Atieh AkbariCancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Najmeh BagherhosseiniCancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Afshin MoradiDepartment of Pathology, Shohada Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad Esmaeil AkbariCancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Me-akbari@sbmu.ac.ir.ORCID 0000-0003-0567-2044
Mohammad AbdolahadNano Bioelectronics Devices Lab, Cancer Electronics Research Group, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran. m.abdolahad@ut.ac.ir.ORCID 0000-0002-1091-3095

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lymph node (LN) status is an essential prognostic factor in breast cancer (BC) patients, with an important role in the surgical and therapeutic plan. Recently, we have been developed a novel system for real-time intra-operative electrical LN scanning in BC patients. The ELS scores were calibrated by pathological evaluation of the LNs. Herein, we evaluated the efficacy of ELS in a prospective study for non-chemo-treated breast cancer patients. This is a prospective study in which ELS scores are blind for pathologists who declare the clearance or involvement of LNs based on permanent pathology as the gold standard. ELS and frozen-section (FS) pathology results were achieved intra-operatively, and samples were sent for the permanent pathology. The score of ELS did not affect the surgeons' decision, and the treatment approach was carried out based on FS pathology and pre-surgical data, such as imaging and probable biopsies. Patients were recruited from October 2021 through November 2022, and 381 lymph nodes of 97 patients were included in the study. In this study we recruited 38 patients (39.2%) with sentinel lymph node biopsy (SLNB) and 59 patients (60.8%) with ALND. Of the 381 LNs scored by ELS, 329 sentinel LNs underwent routine pathology, while others (n = 52) underwent both FS and permanent pathology. ELS showed a sensitivity of 91.4% for node-positive patients, decreasing to 84.8% when considering all LNs. Using ROC analysis, ELS diagnosis showed a significant AUC of 0.878 in relation to the permanent pathology gold standard. Comparison of ELS diagnosis for different tumor types and LN sizes demonstrated no significant differences, while increasing LN size correlated with enhanced ELS sensitivity. This study confirmed ELS's efficacy in real-time lymph node detection among non-chemo-treated breast cancer patients. The use of ELS's pathological scoring for intra-operative LN diagnosis, especially in the absence of FS pathology or for non-sentinel LN involvement, could improve prognosis and reduce complications by minimizing unnecessary dissection.

Indexed as

AxillaBreast NeoplasmsLymphatic MetastasisLymph NodesAdultAgedFemaleHumansLymph Node ExcisionMiddle AgedProspective StudiesSentinel Lymph Node BiopsyBreast cancer surgeryElectrical impedance spectroscopy (EIS)Impedance phase slope (IPS)Nodal stagingPathology

Identifiers

PMID38839807
PMCPMC11153595

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