Sentinel Lymph Node Biopsy in Breast Cancer Using Different Types of Tracers According to Molecular Subtypes and Breast Density—A Randomized Clinical Study

<b>Background:</b> Sentinel lymph node biopsy (SLNB) has become a method more and more frequently used in loco-regional breast cancer in the initial stages. Starting from the first report on the technical feasibility of the sentinel node method in breast cancer, published by Krag (1993) and Giuliano (1994), the method underwent numerous improvements and was also largely used worldwide. <b>Methods:</b> This article is a prospective study that took place at the "SJUPBT Surgery Clinic Timisoara" over a period of 1 year between July 2023 and July 2024, during which 137 underwent sentinel lymph node biopsy (SLNB) based on the current guidelines. For the identification of sentinel lymph nodes, we used various methods, including single traces and also a dual tracer and triple tracer. <b>Results:</b> Breast density represents a predictive biomarker for the identification rate of a sentinel node, being directly correlated with BMI (above 30 kg/m<sup>2</sup>) and with an age of above 50 years. The classification of the patients according to breast density represents an important criterion given that an adipose breast density (Tabar-Gram I-II) represents a lower IR of SLN compared with a density of the fibro-nodular type (Tabar-Gram III-V). We did not obtain any statistically significant data for the linear correlations between IR and the molecular profile, whether referring to the luminal subtypes (Luminal A and Luminal B) or to the non-luminal ones (HER2+ and TNBC), with <i>p</i> > 0.05, 0.201 [0.88, 0.167]; z = 1.82.

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Journal
Diagnostics
Published
2024-10-31
DOI
https://doi.org/10.3390/diagnostics14212439
Citations
1
Primary Topic
AI in cancer detection
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article
Field-Weighted Citation Impact
0.35
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article

Sentinel Lymph Node Biopsy in Breast Cancer Using Different Types of Tracers According to Molecular Subtypes and Breast Density—A Randomized Clinical Study

Dan Brebu, Ionuţ Flaviu Faur, Bogdan Totolici, Cătălin Vlăduț Ionuț Feier et al.
1 citations
Diagnostics
AI in cancer detection
0.35
article

Sentinel Lymph Node Biopsy in Breast Cancer Using Different Types of Tracers According to Molecular Subtypes and Breast Density—A Randomized Clinical Study

Dan Brebu, Ionuţ Flaviu Faur, Bogdan Totolici, Cătălin Vlăduț Ionuț Feier, Alexandru Isaic, Amadeus Dobrescu, Cristi Tarţa, Carmen Neamţu, Paul Pașca, Ioana Adelina Clim, Cătălin Prodan-Bărbulescu, Vlad Braicu, Ciprian Duţă
article en
1 citations

Abstract

<b>Background:</b> Sentinel lymph node biopsy (SLNB) has become a method more and more frequently used in loco-regional breast cancer in the initial stages. Starting from the first report on the technical feasibility of the sentinel node method in breast cancer, published by Krag (1993) and Giuliano (1994), the method underwent numerous improvements and was also largely used worldwide. <b>Methods:</b> This article is a prospective study that took place at the "SJUPBT Surgery Clinic Timisoara" over a period of 1 year between July 2023 and July 2024, during which 137 underwent sentinel lymph node biopsy (SLNB) based on the current guidelines. For the identification of sentinel lymph nodes, we used various methods, including single traces and also a dual tracer and triple tracer. <b>Results:</b> Breast density represents a predictive biomarker for the identification rate of a sentinel node, being directly correlated with BMI (above 30 kg/m<sup>2</sup>) and with an age of above 50 years. The classification of the patients according to breast density represents an important criterion given that an adipose breast density (Tabar-Gram I-II) represents a lower IR of SLN compared with a density of the fibro-nodular type (Tabar-Gram III-V). We did not obtain any statistically significant data for the linear correlations between IR and the molecular profile, whether referring to the luminal subtypes (Luminal A and Luminal B) or to the non-luminal ones (HER2+ and TNBC), with <i>p</i> > 0.05, 0.201 [0.88, 0.167]; z = 1.82.

DiagnosticsVol. 14(21)
Arad County Clinical Hospital (RO), Spitalul Clinic Judeţean de Urgenţă "Pius Brînzeu" Timişoara (RO), Victor Babeș University of Medicine and Pharmacy Timișoara (RO), Vasile Goldis Western University of Arad (RO)
Good health and well-being
Openalex Percentile: Top 32%
AI in cancer detection
0.35
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