Evidence map›Paper›PMID 40115012›Full record

ArticleFrontiers in oncology2025

Baseline cross-sectional imaging of locally advanced high-risk breast cancer facilitates highly customized radiation therapy in surgically inaccessible anatomical areas.

Tomasz Borowiec, Rafał Matkowski, Bożena Cybulska-Stopa, Tomasz Kuniej, Andrzej Kołodziejczyk, Dorota Dupla, Adam Maciejczyk

Abstract read
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Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Tomasz BorowiecLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.
Rafał MatkowskiLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.
Bożena Cybulska-StopaLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.
Tomasz KuniejLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.
Andrzej KołodziejczykLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.
Dorota DuplaLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.
Adam MaciejczykLower Silesian Oncology, Pulmonology and Hematology Center, Wroclaw, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Routine medical imaging used for preliminary breast cancer workup, such as mammography (MMG) and ultrasound (US), has limited utility for radiation oncologists. We hypothesized that the inclusion of cross-sectional imaging (CT scan or PET-CT) prior to primary systemic therapy (PST) would improve clinical staging accuracy and facilitate customized postoperative radiation therapy planning. Therefore, this study aimed to compare the standard baseline imaging with extended radiological staging. Methods: To assess our hypothesis, we performed a prospective, single-center study that included 132 participants who were recruited from October 2015 to March 2020. We quantified the value of cross-sectional imaging compared to those of MMG and US. Descriptive statistics, the Friedman and chi-square tests were performed, and p < 0.05 was considered significant. Results: Patients were grouped into two cohorts: the CT scan cohort (n = 87) and the PET-CT cohort (n = 43). A comparison of the value of cross-sectional imaging with those of MMG and US revealed that staging and radiation planning were altered by this additional procedure. The originally determined disease stage changed in 36.8% and 51.2% of cases in the first and second groups, respectively. The consistency between the assessment of involved axillary lymph nodes using imaging (cN) and the postoperative pathology report (pN) were evaluated. In most cases, clinical and pathological evaluation were consistent, with χ2(1) = 18.98; p < 0.001 for CT scan, and χ2(1) = 6.41; p = 0.03 for PET-CT. Conclusions: Cross-sectional imaging is recommended for patients with locally advanced high-risk breast cancer. A highly customized radiation therapy, including a dose boost, was administered in nine patients with affected lymph nodes that were surgically inaccessible. This procedure was facilitated by extended radiological staging.

Indexed as

breast cancerhigh-risk patientspre-treatment imagingprimary systemic therapytreatment individualization

Identifiers

PMID40115012
PMCPMC11923551

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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.